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Universal health care? : access to primary care and missed health care of young adult Canadians Marshall, Emily Gard 2007

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UNIVERSAL H E A L T H CARE? ACCESS TO PRIMARY CARE AND MISSED H E A L T H CARE OF YOUNG ADULT CANADIANS by Emi ly Gard Marshall B . A . , The University of British Columbia, 1997 M.Sc . , Dalhousie University, 1999 A THESIS S U B M I T T E D I N P A R T I A L F U L F I L L M E N T O F T H E R E Q U I R E M E N T S F O R T H E D E G R E E O F D O C T O R O F P H I L O S O P H Y in T H E F A C U L T Y OF G R A D U A T E S T U D I E S (Interdisciplinary Studies) T H E U N I V E R S I T Y O F B R I T I S H C O L U M B I A A P R I L 2007 © Emi ly Gard Marshall, 2007 ABSTRACT Prevalence of missed health care by life course stage is examined with a critique of the measure of missed care. Canadians reporting missed care has increased from 4.2% in 1995 to 12.5% in 2001. Research questions: 1. Who reports missed care in Canada? 2. What are the relationships among life course stages, social support, predisposing, enabling and need factors to the reporting of missed care? 3. What is the role that life course stages play in the relationships among social support, predisposing, enabling, and need factors? 4. What kinds of health care are Canadians reporting they missed? 5. What reasons are provide for missing care?; and 6. Who accesses primary care and what is the relationship to reporting missed care? Methods: Analysis was done using the Canadian Community Health Survey Cycle 2.1. Nested multiple logistic regression models explore the relationships among variables of interest predicting missed care. Results: Young adults (18-30) are more likely to report missed care compared to other age groups and are least likely to have a regular doctor. Social support is most significantly protective against missed care for young adults. Weak sense of belonging to a local community and lower income are stronger predictors of missed care for young adults. Young adults differ from others in the reasons they report for missed care (i.e., more likely to report cost as a barrier). Discussion: It's not clear i f the difference between young adults and other life course stages is in actual missed care or expectations of primary care. Yet, the literature on emerging adulthood invites curiosity about how delayed adulthood leaves them in less stable, financially insecure, socially and institutionally isolated situations that have subsequent consequences for primary care access. Changes in models of primary care have led to a decline in comprehensive care and more drop-in clinics; while, not having a regular doctor is associated with missed care. I f patterns of inadequate primary care access established in young adulthood are perpetuated in later life, this may foretell undesirable consequences for the health of Canadians. A new model for measuring unmet health care needs is proposed. i i TABLE OF CONTENTS Abstract i i Table of Contents i i i List of Tables vi List of Figures vi i i Acknowledgements xi Dedication ix 1.0 I N T R O D U C T I O N 1 1.1 From Multidisciplinary to Interdisciplinary 3 1.2 Universal Health Care: Equity in Access 6 1.3 Theoretical Underpinnings for Access to Health Care 7 2.0 L I T E R A T U R E R E V I E W 10 2.1 Determinants of Health : 10 2.2 Health Care in Canada : , 12 2.2.1 Primary Care 12 2.2.2 The History of Canada's Universal Health Care System 14 2.2.3 The Canada Health Act '. 16 2.2.4 Debating Universal Health Care 17 2.3 Access to Health Care 20 2.4 Health Care Access: Barriers and Facilitators 25 2.4.1 The Medical Model 26 2.4.2 The Social Experience of Health Care 26 2.4.3 Youth Access to Health Care 30 2.4.4 General Access to Health Care Issues ....34 2.5 Adolescence and Young adulthood 39 2.6 Yoii th and Health: Why it is Important to Study their Access to Care 44 i i i 2.6.1 Health Risk Behaviours 45 2.6.2 Sexual Health , 46 2.6.3 Mental Health 48 2.7 Stress and Health... 49 2.8 Social Relationships and Health 52 2.9 Summary 56 3.0 M E T H O D S 57 3.1 Study Design 57 3.1.1 Research Questions and Hypotheses 58 3.1.2 Data Set: The Canadian Community Health Survey Cycle 2.1, 2003 ...60 3.1.3 Data Analysis 64 4.0 R E S U L T S 69 4.1 Demographic Characteristics of the Population and Young Adults 69 4.2 Who Reports Missed Health Care in Canada? Is Missed Care Related to Age, Social Support, Predisposing, Enabling, or Need Factors? 81 4.3 What Kinds of Care Are People Not Receiving, and What Reasons Do They Provide For Not Accessing Care? Who Does Not Have a Regular Doctor? 98 4.3.1 Predisposing Factors to Having a Regular Doctor 103 4.3.2 Enabling and Need Factors for Having a Regular Doctor 104 4.3.3 Social Support and Having a Regular Doctor 105 4.4 Who Accesses Primary Health Care and What is the Relationship between Health Care Access and Reporting Missed Care? 106 4.4.1 Predisposing Factors and Number of Consultations with Family Doctor 107 4.4.2 Enabling and Need factors for Number o f Consultations with Family Doctor 108 4.4.3 Social Support and Number of Consultations with Family Doctor 109 4.4.4 Reasons for Missed Care and Number of Consultations with Physicians 110 iv 4.5 Answering Hypotheses 112 5.0 D I S C U S S I O N A N D P O L I C Y I M P L I C A T I O N S 114 5.1 Predicting Missed Care 114 5.2 Proposed Model for Assessing Unmet Health Care Needs 121 5.3 Why Young Adults Matter 124 5.4 Limitations o f the Study and Research Opportunities ". 127 5.5 Strengths of the Study. 131 5.6 Recommendations '. 132 6.0 C O N C L U S I O N 137 7.0 Bibliography ; 138 . v L I S T O F T A B L E S Table 4.1.1 Demographic Characteristics of the Population 71 Table 4.1.2 Age In Four Categories B y Marital Status (Percentages) 73 Table 4.1.3 Age In Six Categories B y Liv ing Arrangement (Percentages) 74 Table 4.1.4 Marital Status by L iv ing Arrangement : 74 Table 4.1.5 Age, Marital Status and Liv ing Arrangement by Income Adequacy 76 Table 4.1.6 Age, L iv ing arrangement, and Marital Status by Worked at Job 77 Table 4.1.7 Age and L iv ing Arrangement by Currently Attending a School/College/University 78 Table 4.1.8 Age, Marital Status and Liv ing Arrangement by Sense of Belonging to a Local Community 79 Table 4.2.1 Age (6 Categories) and Reporting Missed Care 82 Table 4.2.2 Marital Status, L iv ing Arrangement, and Sense of Belonging to a Local Community and Reporting Missed Care .'. 85 Table 4.2.3 Income Adequacy, Personal Income (for those aged 20 and older), Prescription Medical Insurance, Self-reported Health Status and Has a Regular Doctor by Reporting Missed Care :„ 86 Table 4.2.4 L iv ing in a Rural or Urban Area, Immigrant Status, Length of Time in Canada since Immigration, Can Speak English or French, and Sex by Reporting Missed Care ; 88 Table 4.2.5 Summary of all Bivariate Crosstabulation Tables Predicting Missed Care....89 Table 4.2.6: Results from Logistic Regression Modeling the Report of Missed Health CareN=135573 93 Table 4.2.7 Logistic Regression Model 3 on for the Report of Missed Care for Five Age groups 96 Table 4.3.1 Type of Care Not Received 98 Table 4.3.2 Reasons for Care Not Being Received ,...99 vi Table 4.3.3 Age groups, Marital Status, and Income Adequacy by Reason for Missed Care (for those reporting missed care) percentages) 101 Table 4.3.4 Sense of Belonging, Rural-Urban and Sex by Reason for Missed Care (Among those who report missing care) 102 Table 4.3.5 Predisposing Factors: Age, Sex, Immigrant Status and Can Speak English or French by Has a Regular Doctor 104 Table 4.3.6 Enabling and Need Factors: Income Adequacy, Rural Urban and Self-Reported Health Status by Has a Regular Doctor 105 Table 4.3.7 Social Support: Marital Status, Liv ing Arrangement, Having a Job, Sense of Belonging by Has a Regular Doctor 106 Table 4.4.1 Age Groups by Number of Consultations with Family Doctor 108 Table 4.4.2 No Regular Doctor by Number of Consultations with a Family Doctor ......109 Table 4.4.3 Sense o f Belonging to a Local Community by Number o f Consultations With Family Doctor 109 Table 4.4.4 Self-Perceived Missed Health Care Needs by Number o f Consultations Wi th a Family Doctor 110 Table 4.4.5 Number of physician visits by reasons health care was not received (For those who report missed care) 111 vn LIST OF FIGURES Figure 2.1.1 Feedback Loop for Human Well-Being and Economic Costs 11 Figure 2.5.1 Interprovincial Migration Rates by Age and Sex, Canada, 1996-2001 43 Figure 4.2.1 Missed Care by Age 82 Figure 5.1 Time-line for Model of Unmet Health Care Needs 123 v i i i ACKNOWLEDGMENTS I gratefully acknowledge the support and guidance of my committee. In particular, I offer my enduring gratitude to Prof. Brian Elliott whose encouragement and ideas fostered my progress to completion. I also thank Dr. John Gilbert and Dr. Kenneth Craig for expanding my vision and believing in my academic abilities. I am also grateful to Dr. R ima Wilkes for her insight into my analysis and recommendations that led to a stronger, more significant study. Special thanks are owed to my parents, Victor and Joanne Marshall who have supported me emotionally, financially and academically throughout my years of education. Both have brought me "life course perspective" and I am so grateful for their many gifts and teachings. They are both mentors and my inspirations. Finally, I would like to thank my husband, Michael Laramie for his continued love, support and humour as I worked towards my doctoral degree. This work is a tribute to his belief in me. ix To my mother, (Professor Joanne Gard9A.arshalt, who taught tne By example that women could, achieve anything, that we could Be smart, strong, Beautiful, talented, goofy, and loved... & To my father, Professor Victor 'William Marshall xvfw taught me By example that hard work\andcommitment are always worth the effort, and that family is vital. With love, 'Emily x 1.0 INTRODUCTION A s a s o c i a l w e l f a r e s t a t e , t h e h e a l t h c a r e s y s t e m i s t h e m o s t s i g n i f i c a n t i n s t i t u t i o n t h a t i s p u b l i c l y f u n d e d a n d p r o v i d e s s e r v i c e s t o a l l C a n a d i a n s . T h e C a n a d i a n h e a l t h c a r e s y s t e m i s b u i l t o n t h e p r e m i s e o f u n i v e r s a l a c c e s s t o h e a l t h c a r e , r e g a r d l e s s o f s o c i o e c o n o m i c s t a t u s o r d e m o g r a p h i c c h a r a c t e r i s t i c s . T h e a i m o f t h e C a n a d a H e a l t h A c t i s t o e n s u r e t h a t a l l e l i g i b l e C a n a d i a n r e s i d e n t s h a v e r e a s o n a b l e a c c e s s t o m e d i c a l l y n e c e s s a r y i n s u r e d s e r v i c e s o n a p r e p a i d b a s i s , w i t h o u t d i r e c t c h a r g e s a t t h e p o i n t o f s e r v i c e . H o w e v e r , i n e q u i t i e s ( i . e . , s o c i o - d e m o g r a p h i c d e t e r m i n a n t s ) i n p r i m a r y c a r e u s e i n C a n a d a a r e k n o w n , a n d r e q u i r e i n v e s t i g a t i o n . C a n a d i a n s a r e i n c r e a s i n g l y c o n c e r n e d a b o u t t h e i r p r i m a r y h e a l t h c a r e s y s t e m , e s p e c i a l l y a c c e s s t o , a n d q u a l i t y o f c a r e r e c e i v e d . I f a g r o w i n g p e r c e n t a g e o f t h e p u b l i c m i s s h e a l t h c a r e ( i n p a r t i c u l a r d u e t o l o n g w a i t s a n d u n a v a i l a b l e s e r v i c e s ) , i t s h o u l d b e a c o n c e r n t h a t p u b l i c s u p p o r t f o r t h e u n i v e r s a l h e a l t h c a r e s y s t e m w i l l e r o d e . T h i s i n t e r d i s c i p l i n a r y w o r k e x a m i n e s a c c e s s t o p r i m a r y c a r e i n C a n a d a , h y p o t h e s i z i n g t h a t y o u n g a d u l t s w i l l m i s s n e e d e d h e a l t h c a r e m o r e t h a n i n d i v i d u a l s i n o t h e r s t a g e s i n t h e l i f e c o u r s e . Y o u n g p e o p l e a r e o f p a r t i c u l a r i n t e r e s t a s p r e d i s e a s e p a t h w a y s s t a r t i n a d o l e s c e n t s a n d y o u n g a d u l t h o o d . T h a t i s , w h i l e y o u t h a r e h e a l t h y , t h e y a r e a t t h e b e g i n n i n g s o f c u m u l a t i v e p r o c e s s e s t h a t c a n c r e a t e a " b u r d e n o f h e a l t h p r o b l e m s t h a t w i l l m a n i f e s t i n l a t e r l i f e . " ( C a l l , R i e d e l , H e i n e t a l . 2002) T h i s r e s e a r c h i s s i g n i f i c a n t a s r e s u l t s i d e n t i f y s u b - p o p u l a t i o n s a t r i s k o f n o t a c c e s s i n g a d e q u a t e a n d t i m e l y h e a l t h c a r e . T h i s r e s e a r c h w i l l b e o f b e n e f i t f o r u n d e r s t a n d i n g t h e r e l a t i o n s h i p s b e t w e e n m u l t i p l e f a c t o r s s u c h a s l i f e c o u r s e s t a g e , s o c i a l s u p p o r t , a n d o t h e r s o c i o - d e m o g r a p h i c c h a r a c t e r i s t i c s a n d m i s s e d h e a l t h c a r e . T h i s k n o w l e d g e l e a d s t o p o l i c y i m p l i c a t i o n f o r p u b l i c h e a l t h , e d u c a t i o n , a n d s e r v i c e d e l i v e r y . A s a r e s e a r c h e r , m y i n i t i a l i n t e r e s t i n p r i m a r y c a r e a c c e s s f o r y o u n g p e o p l e b e g a n w i t h m y m a s t e r s t h e s i s r e s e a r c h o n a d o l e s c e n t g i r l s ' a c c e s s t o p h y s i c i a n s e r v i c e s r e l a t e d t o t h e i r s e x u a l h e a l t h i n r u r a l N o v a S c o t i a ( M a r s h a l l , 2000). A n i m p o r t a n t f i n d i n g w a s a c o m m o n 1 experience of adolescentgirls transitioning from being dependent on their parents, (commonly their mother), to determine i f they needed to see a primary care physician, making their appointments and going to the physician with them, to a new phase where young women would decide for themselves i f care was needed, and would access that care themselves. They also transitioned from being uncomfortable disclosing their sexual activity to a physician, causing them to delay care, to feeling that going to the doctor to get birth control was a responsible decision, and no longer worrying i f their physician would judge their sexual behaviour. Subsequent study of adolescent development and the transitions to adulthood led to a curiosity about the broader experiences of young adults in Canada, and the potential consequences of the trend towards delayed adulthood on access to health care. Dramatic changes in the timing, sequencing, and variation of the transitions to adulthood have created a period in the life course where those aged eighteen to thirty have extended dependence, unstable social support, more financial insecurity, and increased mobility. Some researchers refer to this period in the life course as 'emerging adulthood', a term coined by Jeffrey Arnett (2001). Emerging adulthood focuses on the psychological consequences of being in a liminal state between adolescence and adulthood, and self-definition of this "no longer a teenager", but not quite a fully-independent adult, time of life. Arnett argues that during emerging adulthood, young people have little meaningful commitment to relationships and organizations; they experiment with social roles, and have relative independence from age-normative tasks. What is most important is how young people themselves identify as being adults, and what Arnett calls 'individualistic' indicators of maturity (Arnett 1994, 2001). However, the work of Shanahan and colleagues (Shanahan, Porfeli, Mortimer, & Erickson, 2005) demonstrated through multivariate modeling that family transition markers and self-perceived adulthood are interrelated (Shanahan et a l , 2005). 2 James Cote refers to 'youthhood', as a phase of life when individuals aim to achieve "psychological adulthood" (2000). In congruence with Arnett, Cote favors emotional and cognitive maturity as well as an advanced sense of ethics as defining entry into adulthood, rather than the traditional markers of marriage, having children, leaving the parental home, and entering the workforce. These concepts will be further illuminated in the literature review. What has become evident in demographic, anthropological and psychological research is that we have entered a time when young adulthood is a lengthier period of the life course, ripe for research into the patterns and variability of this new life stage. Arnett (2000, 2004) initially proposed that the time of life roughly between the ages of 18 to 25 be considered the "distinct period" of the life course called "emerging adulthood". However, more research testing Arnett's theoretical constructs have demonstrated that it is 18 to 30 year olds, and not only 18 to 25 year olds who share the same individualistic themes of identity exploration, possibilities, instability, and self-focus (Reifman, Arnett, & Colwell, 2003). For the purpose of this study, young adults will refer to those aged 18 to 30. This age range was chosen as it reflects both the "emerging adulthood" time-frame in North America as defined by Arnett (2000; Reifman, Arnett, & Colwell 2003), as well as the sociological trends of post-adolescent, yet delayed, transitions to adulthood . Other recent work from a sociological perspective studies "early adulthood" and examines the trends for those aged 16 to 30 (Furstenberg, Rumbaut, & Settersten, 2005). It is probable that 18-30 year olds would be considered adults both biologically and legally; however, they may still be developing into adulthood psychologically and socially, and it is these characteristics of this relatively new stage in the life course that is of interest in this research. 1.1 From Multidisciplinarity to Interdisciplinarity With the changes we have seen in North America in relation to marital status, living arrangements, geographic mobility, protracted education, delayed parenthood, and prolonged 3 financial insecurity, it is important to ask whether these have consequences for the access of young Canadian adults' primary care. This research sets out to see i f there is a relationship between life course stage and access to primary care, and i f so, what factors may be enabling or inhibiting access to care. This study is interdisciplinary in nature because, as the celebrated Canadian sociologist demographer observed long ago, "population study is unavoidably an interdisciplinary field" (Wrong, 1964). First, demography is the study of human populations, and often includes the size, distribution, and composition of populations as well as related dynamic processes such as mortality, fertility, migration and so on (Pol & Thomas, 2001; Wrong, 1964). Health demography examines i f factors such as age, marital status, and income influence morbidity and mortality, health status and health behaviours of populations. The field of health demography is also preoccupied with the reverse relationship of how health-related phenomena affect demographic attributes (Pol & Thomas, 2001). A related field to demography is epidemiology. Epidemiology literally means the study of epidemics. Contemporary epidemiology is far more diverse, and refers to the study of origin and progression of illness and health within a population. Epidemiologists focus on populations rather than individuals, and their work is akin to demography in that way. Epidemiology is also related to the field of 'health services research', focusing on the impact of changing demographic attributes on health services, and vice versa. Since fields relate to social phenomena and relationships between individuals, populations and institutions, sociology is also a key discipline on which to rely. Medical sociology in particular developed as a distinct subfield by the 1950s and is characterized as the sociology of medicine, rather than sociology in medicine (Pol & Thomas, 2001). B y the 1960s medical sociology had taken on a stronger epidemiological character, researching the relationship between poverty and poor health, the diversity of health care, and the significance of difference in health status attributable to demographic characteristics. Medical sociology has 4 contributed key concepts to the field and established the relationships between health and age, sex, race, marital status, religion and others, as well as interactions between variables indicating the complexity of these relationships (Pol & Thomas, 2001). In redefining health and illness concepts, the "paradigms in the field [have] shifted from 'medical care' to 'health care', the discipline has become redefined as the 'sociology of health and health care'" (Pol & Thomas, 2001). A s the social relates down to collective behaviour as well as the individual, it is also important to underscore the significance of the field of health psychology. Health psychology is concerned, in particular, "with all psychological aspects of health and illness across the life span." (Taylor, 1995) Health psychology stems from behavioural medicine which is more concerned with observing behaviour than in cognition (Poole, Matheson, & Cox, 2001). In its early days, health psychology studied the mental health and psychosomatic medicine, though it quickly grew through the 1980s to make contributions to our understandings of the importance of emotional health with more of a focus on cognition. Along with cognitive understandings of health and illness experiences and behaviours, health psychology delved into personality factors, as well as stress and coping (Poole et al., 2001). Health psychology led to the expansion of health services to include psychologists, the development of behaviour-change programs to influence health related behaviours such as smoking, patient preparation for medical care and illness progression, and methodological contributions to the study of health (Taylor, 1995). A n interdisciplinary approach to the study of equitable health care access provides a broader perspective that accounts for multiple health-related, social, demographic, life course factors and allows us to understand the relative importance of the different factors under investigation. 5 1.2 Universal Heal th Ca re : Equ i ty in Access When reading about the history of health services in Canada, we are first struck by how universal health care is the most important entrenched value that Canadians share. "Po l l after poll confirms how much Canadians value the principle of universal access to health services, and how proud we are of having constructed such an equitable system." (Rachlis & Kushner, 1994) Canada is the only country that does not allow any private administration of health care services that are already provided publicly (Government of Canada, 2006). However, universal health care did not just appear as a great invention lauded by all in 1968. It was a battle to create a universal health care system, to fight for its inception, implementation and development (Rachlis & Kushner, 1994). There are continued battles to retain a universal health care system and it is an ongoing challenge to ensure that all Canadians have equitable access to our universal health care system. This dissertation explores the question of equitable access to health care from a unique set of perspectives to help us better understand some of the socio-demographic factors related to equitable health care access. A better understanding of the social underpinnings of demonstrable inequalities in access to our universal health care system leads to new policies and continuous changes in the delivery of health care services- changes that reflect and keep in step with shifts in society and culture. When trying to assess inequity in access to health care, we can ask what care individuals are receiving, and what care are they missing that they believe they need. In nationally representative studies of health and health care use, the percentage of Canadians reporting missed health care (a self-reported measure of those who answered "yes" to the question: "During the past 12 months, was there ever a time when you felt that you needed health care but you didn't receive it?") has been steadily increasing over time from 4.2% in 1994/5, 5.1% in 1996/7, 6.3% in 1998/9, to 12.5% in 2000/1 (Sanmartin, Houle, Tremblay, & Berthelot, 2002). It may be that some individuals who report missing needed care did not actually need to access 6 health care. However, it is also likely that many individuals are not receiving care (at least in a timely way) for important health concerns. Certainly from a preventative perspective, timely and appropriate access to needed primary health care can ultimately save money and improve quality of life. From a policy perspective, it is better to have fewer individuals reporting missed health care. This measure is used to determine adequate health care service access, and to compare across health care systems. (Though it is important to note that this dissertation research questions the validity of the measure of perceived missed health care as a measure of actual unmet health care needs.) Yet, its use in the literature is undeniable as a recent analysis of primary health care and health systems performance in five countries used missed health care as a primary indicator of the quality of a health care system (Schoen et al., 2004). Hence, missed health care is an important issue to be understood and addressed. Along with the measure of missed health care, this dissertation also looks at whether Canadians have a regular physician, and their reported number of visits to their primary care physician. 1.3 Theoretical Underpinnings for Access to Health Care Aside from trends over time of increasing missed health care in Canada, there may also be significant differences in the patterns of who does not access needed care and the reasons why. Ronald Andersen created the original behavioural model of health services use which focuses on predisposing, enabling, and need factors as predictive of health service utilization (Andersen, 1995). Andersen's model of access to care (and the subsequent revision of it) has become the most widely used, having been cited more than 800 times (Goldsmith, 2006). (Andersen's model will be discussed further in the literature review). However, there remains a paucity of interdisciplinary population-based research in Canada with complex design that accounts for multiple socio-demographic variables when studying primary health care utilization, 7 in particular when examining the reporting of missed health care. Moreover, no research has focused specifically on young adults and their access to health care in Canada. O f all age groups, adolescents and young adults have often been reported as having the lowest rates of primary care use (Cheng & Kle in , 1995; Kle in , Wilson, McNul ty , Kapphahn, & Collins, 1999). The lower rate of primary health care use among adolescents and young adults is often attributed to the belief that they are the healthiest members of society (Health Canada, 2004). This belief may be misleading as the available literature demonstrates that adolescents indeed miss needed care (Dubow, Lovko, & Kausch, 1990). Dubow et al., (1990) report approximately two-thirds of American adolescents experiencing health problems failed to seek help from any source. Ford and colleagues' nationally representative study of American adolescents' forgone health care found that 18.7% miss needed care at least one time over the last year, and those that miss needed care were also at increased health risk due to other factors including risk behaviours (Ford, Bearman & Moody, 1999). Research has shown that adolescents miss needed care due to multiple barriers, many of which are unique to youth. These barriers w i l l be discussed in more detail further on. The life course stages of adolescence and young adulthood come with social, behavioural and biological changes that may precipitate the need for physician services, but simultaneously generate specific disadvantages for seeking appropriate care. For example, adolescents and young adults have higher rates of risk behaviours (i.e., unprotected sexual intercourse, alcohol and other drug use). A s a result, they have a need for prevention and care for health issues related to birth control, sexually transmitted infection (STI) testing and treatment, and drug awareness. These are difficult topics for a patient to broach with a physician. Al so , mental health issues often first arise during adolescence, and would require physician diagnosis and care. However, mental health is another difficult topic to broach with a physician. Generally, adolescents and young adults are in the process of changing from being dependent on others (e.g., parents) to 8 identify their care needs to a stage where they are identifying their need for care themselves, and accessing that care independently. During adolescence and young adulthood many individuals experience great changes in social networks that may alter the supports that would encourage the access of appropriate primary care. Young adulthood comes with many upheavals, changes, and developmental issues that may impact the need for care as well as the ability to seek needed care from physicians. Moreover, young adults are learning and practicing new skills including identifying the need for care, arranging for care, and communicating with physicians in order to receive care. To explore the relationship between young adulthood and access to primary care, research was conducted to develop and test theory using the Canadian Community Health Survey (CCHS, Cycle 2.1). The models developed explore the relationships between age, gender and diverse demographic context variables (especially those that relate to the transitions to adulthood) and Andersen's model of health service utilization, in relation to utilization of primary health care and the reporting of missed health care in Canada. Particular attention is paid to missed care. Analysis uncovers patterns of missed care and primary health care utilization for different stages of the life course, gender, and other socio-demographic characteristics. This dissertation produces some interesting findings, but it also lays the groundwork for more on the significant of life stages and transitions in the study of young adults and how they use and are treated by the health care system. 9 2.0 L I T E R A T U R E R E V I E W This review of the literature w i l l cover key conceptual topics related to the proposed dissertation research. These include: the determinants of health, health care in Canada, access to health care, adolescent and youth development, emerging adulthood and youth health. Moreover, it wi l l outline the development of the dissertation research questions and hypotheses. 2.1 Determinants of Heal th The National Research Council 's (NRC) recent publication (Singer & Ryff, 2001) New Horizons in Health: An Integrative Approach provides analysis and judgment to set research agendas and influence public policy from respected experts in their fields. In their book, they site an interdisciplinary approach to understanding health and health behaviours. Under the key influences on pathways to health, the N R C list: 1) predisease pathways as the identification of early and long-term biological, behavioural, and social precursors to disease; 2) positive biological, behavioural, and psychological factors that contribute to disease resistance, and wellness; 3) environmentally induced gene expression; 4) personal ties which influence health and disease; 5) collective properties of healthy communities; 6) inequality and health with a growing awareness of socioeconomic hierarchies, racism, discrimination, and stigmatization being linked to differences in health and illness; 7) population health including macro trends in health status, how the macro-economy and population health are linked and the performance of the health care system; 8) interventions; 9) methodology and 10) infrastructures (Singer & Ryff 2001, p. 23r24). What is most compelling about these lists of factors that contribute to health is how they are so imbedded in the biological, social, and the institutional. In fact, the authors state that, "The scope of these priorities is expansive, and integrative, with each encompassing wide areas of research. Some represent phenomena at the individual level, while others deal with 10 m a c r o - l e v e l ( e . g . , p o p u l a t i o n ) i s s u e s . " ( S i n g e r & R y f f , 2 0 0 1 , p . 2 4 ) W e i g h t i n g o f t h e s e d i f f e r e n t f a c t o r s i s n o t e v e n c o n s i d e r e d , a s t h e y a r e s o " i n t e g r a t e d " . T h e ' s o c i a l d e t e r m i n a n t s o f p o p u l a t i o n h e a l t h ' , a n o t h e r i n t e g r a t i v e a p p r o a c h , i s a p e r s p e c t i v e n o w c o m m o n l y u s e d t o e x p l o r e w h y s o m e i n d i v i d u a l s a r e m o r e o r l e s s h e a l t h y t h a n o t h e r s . T h e s o c i a l d e t e r m i n a n t s o f h e a l t h a r e m a n y a n d v a r i e d a n d t h e r e a r e s e v e r a l b r o a d a p p r o a c h e s t o s t u d y i n g t h e m . T h e r e i s a g o o d d e a l o f d i s p u t e a s to w h a t f a c t o r s c a n b e c o n s i d e r e d a s d e t e r m i n a n t s o f h e a l t h , h o w m u c h t h e v a r i o u s f a c t o r s c o n t r i b u t e t o p a t t e r n s o f v a r i a b i l i t y i n h e a l t h , a s w e l l a s t h e m e c h a n i s m s b y w h y w h i c h t h e y o p e r a t e . S t a u n c h s u p p o r t e r s o f t h e s o c i a l d e t e r m i n a n t s o f h e a l t h p e r s p e c t i v e a r g u e t h a t t h e r e a r e n u m e r o u s a n d i n t e r r e l a t e d s o c i a l f a c t o r s a f f e c t i n g p o p u l a t i o n h e a l t h ( C o r i n , 1 9 9 4 ; E v a n s , 1 9 9 4 ; H e r t z m a n , F r a n k , & E v a n s , 1 9 9 4 ) . O n e -e x a m p l e o f k e y s o c i a l d e t e r m i n a n t s i s r e p r e s e n t e d i n a m o d e l d e v e l o p e d b y E v a n s a n d S t o d d a r t ( s e e b e l o w f o r r e p r o d u c t i o n ) : F i g u r e 2 . 1 . 1 F e e d b a c k L o o p f o r H u m a n W e l l - B e i n g a n d E c o n o m i c C o s t s . Individual Response -Behaviour -Biology 7 K Social Environment A Health & Function Physical Environm ent 1, Dis ease ijenetic . Endowment Health Care Well-Being Prosperity \ ( E v a n s & S t o d d a r t , 1 9 9 4 : p . 5 3 ) 11 According to Evans and Stoddart (1994) a determinants of health perspective suggests that social influences play a more significant role than health care provision on health and illness in the population. While Evans and Stoddart (1994) argue that the role of health care is "marginal" , it remains in their model (see above). Moreover, many critics of population health (Coburn et al., 2003; Guidotti, 1997; Poland, Coburn, Robertson, & Eakin, 1998) believe that health care plays a larger role in the health and well-being of citizens (through primary, secondary and tertiary care, health promotion, and prevention), than Evans and colleagues would lead us to believe. The N R C report cited above (Singer & Ryff, 2001) also sites the medical system as "an important part of health." A s they relate, there is a great deal of discussion that focuses on access to health care and that "understanding how the system operates and how well it works is therefore a central issue for behavioral and social research." (Singer & Ryff, 2001, p.137) Within a determinants of health perspective, health care is a small, but vital and consistent component of individual and population health models. A s such, health care use and access are still important health issues, as well as important public policy concerns for those 'social determinants' writers. In Canada, a universal health care system has been created for providing health services to individuals. It is the access and use of the primary medical care system that is explored in this dissertation. 2.2 Health Care in Canada 2.2.1 Primary Care Primary care in this study refers to basic, everyday health care accessed by Canadians. Primary care could be visiting the family doctor or nurse practitioner, talking to a dietician or pharmacist, or other health care professional. Primary health care, a broader term than primary care, would include services delivered to individuals (primary care) and population level "public health" initiatives (Muldoon, Hogg, & Levitt, 2006). While primary care is more commonly defined as 12 "that level of a health service system that provides entry into the system for all new needs and problems, provides person-focused (not disease-oriented) care over time, provides care for all but very uncommon or unusual conditions, and coordinates or integrates care provided elsewhere by others." (Starfield, 1998, 8-9). In 1994, the Canadian Medical Association wrote that there is national and international consensus that primary care is best delivered by a physician educated in comprehensive care and that specifically, family physicians are trained to deliver these services as a basic component of their practices (Canadian Medical Association, 1994). However, there are alternative models of care that suggest physicians are not the sole, nor always the optimal gate-keepers for primary care access. As the Canadian Medical Association defines, Primary medical care is the foundation for the Canadian Health Care System and is critical in maintaining and improving the well being of Canadians. It includes disease prevention, health promotion, health system reform, methods of service delivery, education, research, and quality management. (1994, p . l ) As a result, the family physician or general practitioner is often the initial point of entry into the health care system for most Canadians. However, there is a growing move towards broadening the definition of primary care, to primary health care, acknowledging a broader understanding of the physical, emotional and social aspects of the determinants of health. There is also a move towards expanding the roles of providers in part to address the more comprehensive care models that follow from understanding the broader primary health care as well to f i l l the gap in service availability versus needs (Romanow, 2002). A s Romanow reports (2002), physicians make up a small proportion of health care workers as, Across Canada there were over 1.5 million people working in health care and social services in 2000. Nurses (including registered nurses, licensed practical nurses, and registered psychiatric nurses) made up 35% of the health workforce while physicians made up 8%. The remaining 57% included a range of health care providers such as chiropractors, medical radiation technologists, social workers, and home care workers... (p.92). Moreover, when exploring the need for role expansion, the Romanow report states, 13 There is little doubt that the doctor-patient relationship is central to the care physicians provide. Yet it also means they have often been unwilling to share responsibility for the care of their patients with others who are in a good position to coordinate care across the different aspects of the health care system, from diagnostic tests, to acute care and home care. An increasing emphasis on primary health care - where physicians are expected to participate in and share responsibilities with a team of different health care professionals - will also have an impact on patterns ofpractice for physicians as well as the way they are paid for their services, (p. 107) The Romanow report goes on to say that while physicians have traditionally played the "gate-keeper" role, deciding what types of services a patient needs and where those services should be provided, both nurses and case managers have been identified as capable of being "gatekeepers" to the health care system (2002). For this dissertation, access to primary care, rather than primary health care is of interest, thus not including public health initiatives. However, it is important to recognize that when respondents were asked about whether they missed health care in the last year (the main outcome variable under study in this analysis), no instructions were given as to how they define "health care". A s a result, responses may address whether they missed access to primary care services from family physicians and general practitioners, nurses and nurse practitioners, physician specialists, diagnostic services, or other health care services such as physiotherapy, chiropractic, eye care, or any other range of what might be considered "health care" services. Some of these services might be expected to be covered under the Canadian universal health care system, while others might not. 2.2.2 The His tory of Canada 's Universal Heal th Care System The Canadian health care system is built on the premise of universal access to health care, regardless of socioeconomic status or demographic characteristics (House of Commons, 1984). 14 Canada's universal public health care system is paid for through taxes and in some provinces they also charge health insurance premiums. Free hospital service was first offered in the province of Saskatchewan with several other provinces following suit prior to 1957 (Government of Canada, 2006). The creation of our national system was controversial, and began in 1957 when the Hospital Insurance and Diagnostic Services Act was approved by Parliament (Government of Canada, 2006). The Act provided free acute hospital services to Canadians. In 1961 the federal government established the Royal Commission on Health Services, chaired by Justice Emmett Hal l to study and report on the health care needs of Canadians (Government of Canada, 2006). The following year, the Government of Saskatchewan offered free access to physician services to all its citizens (Government of Canada, 2006). A s one might expect, this decision was met with resistance, and in response, the physicians of Saskatchewan went on strike. The physicians were able to secure the right to practice outside the public program and to charge patients higher fees than those reimbursed by the province (Government of Canada, 2006). In 1964-1965, the Royal Commission on Health Services released a two-volume report . recommending a comprehensive and universal medicare system that would cover physician care as well as prescription drugs for all Canadians (Government of Canada, 2006). B y 1966 the majority of Canadians were insured for physician services through various private and public insurance plans (Government of Canada 2006; Rachlis & Kushner, 1994). That year the Government of Canada passed the Medical Care Act of 1966 which provides free access to physician services. However, this created a long-standing political dilemma, as constitutionally in the British North America Act of 1867 health had been the jurisdiction of the provinces, given to them back when it was considered an unimportant political responsibility (Rachlis & Kushner, 1994). Yet the provinces would be dependent on federal financial contributions to run the health 15 care systems. Each province thus had to negotiate with the federal government in order to provide free access to physicians and hospitals. B y 1972 each province had established its own system of free access to physician services and the federal government shared in the funding (Government of Canada, 2006). In a 1980 report, Emmett Hal l recommended the abolition of extra-billing and user fees and a collaborative means of setting provincial payment rates for doctors be implemented (Government of Canada, 2006). Thus, the Canada Health Act was passed by the Canadian Government in 1984 and included the main recommendations of the Hal l report and also established penalties for provinces that did not comply. B y 1987 all provinces had banned extra-billing. Since its inception there has been great debate, research, and discussion as to how to best manage the Canadian universal health care system. 2.2.3 The Canada Heal th A c t The Canada Health Act is Canada's federal health insurance legislation and it states that the primary objective of Canadian health care policy is: ...to protect, promote and restore the physical and mental well-being of residents of Canada and to facilitate reasonable access to health services without financial or other barriers. (House of Commons, 1984) The Canada Health Act establishes criteria and conditions related to insured health care services and extended health care services that the provinces and territories must meet in order to receive the full federal cash contribution under the Canada Health and Social Transfer (CHST). A s such, the aim of the Canada Health Act is to ensure that all eligible Canadian residents have reasonable access to medically necessary insured services on a prepaid basis, without direct charges at the point of service. The five criteria for the provision of universal health care set out by the Canada Health Act are: 1. Public Administration (section 8); 2. Comprehensiveness 16 (section 9); 3. Universality (section 10); 4. Portability (section 11); and 5. Accessibility (section 12). The intent of the accessibility criterion (section 12) is to ensure reasonable access to insured hospital, medical and surgical-dental services on uniform terms and conditions, unprecluded or unimpeded, either directly or indirectly, by charges (user charges or extra-billing) or other means (e.g., discrimination on the basis of age, health status or financial circumstances). In addition, the health care insurance plans of the province or territory must provide: reasonable compensation to physicians and dentists for all the insured health care services they provide; and payment to hospitals to cover the cost of insured health care services. Reasonable access in terms of physical availability of medically necessary services has been interpreted under the Canada Health Act using the "where and as available" rule. Thus, residents of a province or territory are entitled to have access on uniform terms and conditions to insured health care services at the setting "where" the services are provided and "as" the services are available in that setting (Health Canada, 2002). 2.2.4 Debating Universa l Health Care The Canadian health care system is continually threatened, and some provinces are increasingly moving towards some privatization of it (Rachlis & Kushner, 1994). There is continued strain as costs rise, a higher volume of services is provided and the population includes a higher proportion of older people (Rachlis & Kushner, 1994). Canada spent an estimated $142 billion on health care in 2005, with $18.2 bil l ion on physician visits (Decter, 2005). B y the end of 2002 three major studies on how to fix the Canadian health care system had been released. First, there was the Mazankowski Report, commissioned by Alberta Premier Ralph Kl ine . The report called for an expanded role for private funding in the system. Among the forty-four recommendations, 17 Mazankowski (2002) called for: 1) coverage limitation to be decided by a panel; 2) a service guarantee that would guarantee Albertans access to services within 90 days of a diagnosis and physician recommendation; 3) establishment of an electronic health record; 4) province-wide standards; 5) blend private, public, and not-for-profit health care providers; 6) new sources of revenue including increasing health-care premiums, introducing user-fees, taxing people for the services they use and expanding private insurance; and 7) physicians would be required to work a percentage of their time in the public system to ensure both private and public systems have access to the best physicians. Alberta has acted upon some of the report's recommendations. For example, in October 2003, the province became the first in Canada to create an electronic database. The province also set up a panel to look at which services should continue to be covered by the province and which should be de-listed. Another key report was the Senate report (often referred to as the Ki rby report) that was presented by the Senate Committee on Social Affairs, Science and Technology for the Federal Government in 2002. The report looked at the history of health care in Canada and other countries, was divided into six phases and heard from more than 400 witnesses. The recommendations for reform were the most talked about aspects of the work. The key recommendation was a dedicated tax (lower-income Canadians would pay less than higher income Canadians) that would raise $5 bill ion a year for hospitals, equipment, physician and nurse recruitment and other system improvements. Other Ki rby recommendations included: 1) the government should pay for out-of-province or out-of-country treatment i f patients can not receive timely care in their home province; 2) individual out-of-pocket expenses for prescription medication should be capped at three percent of family income; 3) provincial and federal governments should contribute fifty-fifty to fund a post-acute home care program; 4) an independent commissioner should evaluate and monitor reforms; and 5) there should be change 18 to the way hospitals and physicians are funded. However, the Ki rby report had the unfortunate timing of being released a month before the much anticipated Royal Commission on the Future of Health Care in Canada. Former Saskatchewan premier Roy Romanow was the head of the Commission on the Future of Health Care in Canada, and the final report was published in November 2002. The report contained forty-seven recommendations (Romanow, 2002). The main recommendations included: 1) like Kirby , there should be a cash infusion, whereby the federal government should raise its annual contribution to Medicare by $6.5 bil l ion in 2005-6 to be raised from general revenue, noting accumulated federal surpluses (he calls this a "regressive" tax); 2) stable funding whereby provinces would be guaranteed a minimum amount of money every year, with Ottawa never paying less than twenty-five percent of the cost of insured medical services under the Canada Health Act ; 3) increased accountability for how money is set aside for medicare and how it is actually spent. This could be accomplished by establishing the Health Council of Canada who would issue public reports on spending; 4) limited pharmacare; 5) increased home care payments; 6) limiting the role of the private sector to preserve "the integrity and viability" of public health insurance.. It is clear that while a universal health care system is central to Canadian values and identity (Rachlis & Kushner, 1994), it is also a service that has been contested since its inception, and remains up for public and governmental debate. The provinces and the federal government struggle with how to provide the best health care for Canadians. First and foremost, it is the responsibility of the two levels of Government in Canada to live up to the Canada Health Act. A s defined by the Government of Canada, there is a goal of equitable access to health care. Yet, inequities in primary care use in Canada are well-established and there are figures showing quite clearly that a percentage of the population reports missing needed care. These prompt several 1 9 questions: Who misses needed care, and why do some groups of individuals miss more needed care than others? Are there patterns to who misses care? This dissertation hypothesizes that young adults miss a disproportionate amount of needed care due to factors related to their stage in the life course. This research therefore contributes to public and policy-making concerns about the universality of health care in Canada, but the analysis also takes us beyond critique, and leads to some positive proposals. 2.3 Access to Heal th Care There are two main ways researchers evaluate equity in access to health care: 1) utilization of health care services, and 2) health outcomes (Millman, 1993). Health care use includes visits or consultations with physicians, nurses, specialists, hospital and pharmacy visits. Effective access to health care is indicated when higher levels of use are correlated to higher self-rated health status (Andersen, 1995). Utilization is considered an excellent measure of 'realized access'. While health outcomes are not explored in this analysis they include birth and death records, birth weights, and other outside government-collected measures of health. Many studies have analyzed variation in health care use in different countries and across Canada, while regionally localized studies are less common (Law et. al., 2005). Newbold and Dunlop both found significant variations in care use between provinces, which persisted after controlling for individual level factors (1995; 2000). While need is the strongest predictor of health care service use, past research suggests that different socio-demographic determinants play a role in determining health care use (Dunlop et al., 2000; Veugelers & Y i p , 2003). In order for an individual to use health care services the opportunity for use must be available as well as the knowledge that the services exist, "people must have the means and know-how to get to those services and make use of them" (Andersen, 1995:3). In order for an individual to arrive at a doctor's office he or she w i l l have decided that 20 they have a health concern that w i l l not go away on its own and that they are not capable of managing the situation themselves (Seiffge-Krenke, 1998). Perceptions of symptoms and their interpretation have also been found to vary across cultural and ethnic backgrounds resulting in . different patterns of health care use across ethnic lines (Clarke, 1990:94). The theoretical framework that w i l l inform this research is The Behavioral Model of Health Services' first developed by Ronald Andersen while he was working on his Ph.D. at the University of Chicago in the 1960s and repeatedly revised over the decades (Andersen, 1995:1). In a review of the literature by Goldsmith (2006) Andersen's behavioural model of health services utilization was found to be most widely known and used. This model provides the researcher with a way of conceptualizing a logical, time-sequenced understanding of the influence of individual characteristics on health care use. This model classifies individual-level characteristics based on the type of influence they have on health care use, in this case predisposing, enabling and need factors. Previously applied to the Canadian context, Andersen's model evaluates the independent contribution of various components in predicting health care use (Law et. al., 2005). This model provides a structure through which to analyze the relationships between individual-level characteristics and health care use. Andersen divides determinants of health care use into three types of determinants: predisposing, enabling, and need-based. Predisposing determinants are characteristics that an individual has prior to contracting an illness or needing to visit a hospital that w i l l have an effect on the likelihood of accessing health care. A range of characteristics can be considered predisposing and have previously been found to influence health care use such as age, gender, 1 To scientists, the phrase "the theory of..." signals a particularly well-tested idea. A hypothesis is an idea or suggestion that has been put forward to explain a set of observations. It may be expressed in terms of a mathematical model. The model makes a number of predictions that can be tested in experiments. After many tests have been made, i f the model can be refined to correctly describe the outcome of all experiments, it begins to have a greater status than a mere suggestion. (Stanford University, 2007) 21 marital status, country of birth and education (Andersen, 1995). Gender differences in utilization studies have been noted in multiple studies (Doyal, 1995; Lorber, 1997). While 'class' could be considered a predisposing factor as it has been previously found to influence health care use (Clarke, 1990), it is not included in Andersen's model. The second category of determinants in the model are enabling factors (these can also be viewed as factors that are barriers to care access), such as income, region, mobility and distance from a health care facility and social support. Region and area have previously been found to have a significant impact on health care use in a study of four neighbourhoods in Hamilton, Ontario (Law et. al. 2005: 4). Past research has found a positive relationship between higher socioeconomic status and better health status that could be indicative of better access to health care (Newbold et. al., 1995; Kephart et. al., 1998; Glazier et. a l , 2000). Mobi l i ty is also expected to have an impact on health care use since, "Mobil i ty , like frequent re-potting of plants, tends to disrupt root systems, and it takes time for an uprooted individual to put down new roots" (Putnam, 1996). Apply this to health care use and we can appreciate that an individual moving to anew community must learn how and where health care is provided in their new community, find a physician who is accepting new patients and build a relationship with that health care provider. Given that young adults are the most mobile in Canadian society compared with other age groups, there is increased need to examine this factor for health care access in relation to life course and transitions to adulthood. Increased social ties have been found to have a positive impact on health care use (Andersen, 1995). Human touch, emotional support, protection against the loss of self-esteem, development of a sense of self-worth, networks of mutual obligation and feelings of belonging can all be gained from social support. Social support networks also provide information and help foster healthy habits (Freund & McGuire , 1999). Finally, the third type category of determinants of health care access is 'need' as a factor that can have an effect an individual's health and their propensity to access health care 22 (Andersen, 1995). Andersen's model measures need with self-rated health status and stress (Law et. al. 2005). Elements of Andersen's early behavioural model w i l l be used in the analysis of health care access in this dissertation, but w i l l be expanded to incorporate social support factors that relate specifically to young adulthood such as job status and sense of belonging to a local community as well . Andersen has cited the flexibility and adaptability of his model as strengths, and acknowledges as positive that the model has been revised or added to by researchers over the years (Andersen, 1995). Researchers have added components they felt were necessary. Gelberg (2000) for instance, added 'vulnerable domains' to address vulnerable populations, and Kronenfeld (1978, 1980) added 'provider of care' variables. A s Goldsmith (2006) notes, "Aday and Awe (1979) have documented other instances where researchers have added components, .. .describing such behaviour as a positive indication of the flexibility of the behavioral model." (p.22) Despite its popularity, Andersen's model is not without its empirical and theoretical criticisms. It has never been a very strong predictor of health care utilization and has explained little in actual health service utilization (Patrick et al., 1988, Porter 2000; among others.) Moreover, as noted by Goldsmith (2006), the behavioural model has been critiqued for measuring access to health.care as a static phenomenon rather than one that shifts over time (Pescosolido & Kronenfeld, 1995), for its failure to incorporate individual perceptions and beliefs (Thomas & Perchansky, 1984), and for not addressing the interaction between the health care system.and the individual (Gold, 1988). I w i l l be addressing not only social support variables that, are related to the status of young adults, but I w i l l also be the first to examine whether Andersen's model can predict perceptions of missed health care rather than health care utilization. In relation to health care access, it is crucial to look at the consumer-perspective. Missed health care has been identified as a critical indicator for access problems (Chen & Hou 2002) and is cited in many studies (Chen & 23 Hou, 2002; Sanmartin et al., 2002; Chen et a l , 2002; Lasser, Himmelstein & Woolhandler, 2006). Three of the studies cited here were conducted by Statistics Canada and utilized the C C H S and/or the National Population Health Survey. Chen and Hou (2002) reported the prevalence of self-reported missed health care and the extent to which they were attributable to perceived problems with service availability or acceptability. They found that in 1989/99 about seven percent of Canadian adults, an estimated 1.5 mill ion, reported having "unmet care needs" in the previous year. Around half of the missed care, was attributed to acceptability problems such as being too busy. Service availability was the main cause in thirty-nine percent of cases. They also found that missed care due to service availability problems were not significantly associated with socioeconomic status, while those due to accessibility were inversely associated with household income. Sanmartin et. al., (2002) examined the rise in missed health care between 1994, 1996 and 2000. They found that the percentage of people reporting missed care rose gradually between 1994/5 and 1998/99, then doubled (from 6% to over 12%) between 1998/99 and 2000/1. Long waiting time and unavailability of services were the reasons most frequently reported for missed care. However, the percentage reporting all reasons for missed care increased between 1999 and 2001. Chen et al. (2002) also published reports of trends in reporting missed care in 1994 and 2001 and the reasons given for missing care. The emphasis here was on wait times being too long and the unavailability of services, and results were broken down by gender, self-reported health, chronic condition, chronic pain, distress, general practitioner consulted in past year, specialist consulted in last year, doctor's authority score, and self-care score. They found that perceptions of missed care are on the rise, people with health problems are more likely to complain of long wait times, income affects missed health care stemming from cost or transportation difficulties, personal circumstances and attitudes account for most missed care, and that women were more likely than men to report missed care (Chen et al., 2002). Finally, in a 24 comparison of access to care, health status, and health disparities in the United States and Canada, American respondents were more likely than Canadians to have reported missed care (Lasser, Himmelstein, & Woolhandler 2006). 2.4 Health Care Access: Barriers and Facilitators There is a dynamic process implicated in the access of health care that involves the individual heeding care, the system providing care, and numerous factors that can encourage or intervene in this process of accessing primary care (Sanmartin et al., 2002). Adolescence and young adulthood involve three kinds of development: physical, cognitive and social. Each of these developmental processes has an impact on health care needs as well as the abilities of youth to access appropriate health care. There may be increasing skills, including learning when and how to seek help, such as primary care physicians. Adolescents and young adults are of particular interest because they are in the process of developing patterns that w i l l be held throughout their lives Hansell & Mechanic, 1985). Cheng and Kle in (1995) argue that many problems (physical, mental, and sexual) found among adolescents and young adults are preventable, and this "makes the availability of certain health services - including reproductive health services, diagnosis and treatment of sexually transmitted diseases and human immunodeficiency virus (HIV) , and mental health and substance abuse services - critically important for. this age group. When these services are not accessible to youth, the result is missed opportunities for prevention." (Cheng & K l e i n , 1995). This reality is placed within a context where adolescents and young adults have the lowest rate of primary care use (Klein et al., 1999; Cheng and Kle in , 1995). Kle in ' s study of access to care among adolescents found that nearly a third of the 6748 adolescents surveyed had missed needed care. The most common reason for missing needed care was 'not wanting a parent to know' (35%). So, what is the prevalence of missed care among young adults? To understand the propensity to 25 miss health care, it is important to understand the model upon which our health care system is based. 2.4.1 The Medical Model The belief system within which medical practitioners operate has led to the creation of a medical model of health and disease. Disease is clearly defined as "a definite morbid process having a characteristic strain of symptoms - it may affect the whole body or any of its parts, and its etiology, pathology, and prognosis may be known or unknown." (Inglefinger, 1982 in Bolaria & Dickinson, 1994). Medical scientists "searched for organisms causing infections and single lesions in non-infections disorders... Contemporary medical knowledge is rooted in the paradigm of the 'specific etiology' of disease, that is, diseases are assumed to have a specific cause to be analyzed in the body's cellular and biochemical systems." (Bolaria, 1994: 2). As Fabrega (1993) states, "General medical theory argues for the reality and centrality of disease factors (that is, organic changes)..." (p.7). Thus, from the perspective of a physician, the medical model prescribes that there be a pathology leading to symptoms which require a diagnosis, followed by treatment with the end goal of a reversal or amelioration of pathology. This bio-medical model does not include prevention, education and so on - issues which are extremely important for youth health. Moreover, physicians are constrained by time and financial interests limiting their focus on education and prevention (Green, Erikson, & Schor, 1988). 2.4.2 The Social Experience of Health Care B y its very nature, medicine is more than science - it has social dimensions as well . Theoretically, the "construction of medical knowledge is intersubjective reality in the context of highly organized interpersonal and institutional relationships." (Good & Good, 1993) . Sociology and anthropology further our understanding of the biomedical model of disease and pathology by introducing understandings of sickness as social phenomena and illness as a lived experience. The theoretical perspectives which underlie these approaches are diverse. Functionalist theorists 26 saw the training of doctors as an especially interesting example of socialization - a long process filing the person to the socially scripted role of 'the doctor'. They were among the first to appreciate that such training involved moral as well as technical instruction. Young men and women studying to be doctors are being prepared for a distinctive kind of occupation, namely a profession. Other sociologists adopted the conceptual framework of symbolic interactionism, viewing illness as deviance. For example, being sick may be perceived, or constructed, as providing a reprieve from the responsibilities of everyday life; in some traditions, illness is interpreted as deviance and medicine is a form of social control; medical training is a process of socialization and diagnosis is a matter of doctor-patient negotiation (Nettleton, 1995). Moreover, since the medical system has been shown not to treat individuals equally, issues of how socio-economic status, age, gender, ethnicity, and disability affect the social distribution of health and illness, access to health care services and treatment received are important areas of study (Mechanic, 1995). The realities of the biomedical model of disease and pathology, as well as the social contexts of illness and sickness, leave practitioners with limited options from the system within which they operate for helping patients, including adolescents and young adults in need of primary health services. One of the key issues needing to be addressed is the process by which individual seek care. Sieffge-Krenke (1998) presents decision-making processes that adolescents use for seeking health care. These processes begin with the perception of symptoms and interpreting them as such. This perception and interpretation of symptoms is followed by a phase in which the patient decides to seek medical treatment. From the processes involved with seeking health care as outlined by Sieffge-Krenke and others, we can see that by its very nature, deciding to, and going to seek help from a physician is a social process. However, individuals vary in their sensitivity to physical symptoms and how they define their symptoms as serious or important (Sieffge-Krenke 1998). These differences in the perception and qualification of symptoms have been found to 27 vary by cultural and socioeconomic differences. For example, Freund and McGuire (1991) found that low-income individuals show a higher tolerance of symptoms than higher income individuals. Zola (1966) found cultural differences whereby some individuals postponed consulting a physician, despite symptoms, particularly i f the symptoms were considered unusual or threatening^ and required legitimization or approval of other people before seeking medical care. In fact, Sieffge-Krenke argues that "many i l l people postpone consulting a physician, sometimes to a point when little can be done to treat the illness or disease" (p. 184). Avoidance of physicians is often related to the severity of an illness and fears of physicians, unwanted diagnosis, painful procedures (Sieffge-Krenke, 1998). There can also be a concern about not wasting a doctor's time with an illness that is not serious enough. It is vital to acknowledge that most people use alternative sources for help when they are i l l as an alternative to seeking medical care, or as a precursor to seeking medical care from a physician (Sieffge-Krenke, 1998; Freund & McGuire , 1999). Individuals w i l l engage in self-care, take medication, and seek information and comfort from their support systems (Sieffge-Krenke, 1998). However, at some point, most individuals decide to seek medical care from a primary care physician. A t that time, they wi l l enter the "role" of a patient. Although the functionalists were the first to make sustained analysis of ' roles ' , it was the interactionists like Becker and Goffman who explored the social dynamics whereby the 'sick role' was constructed and played out. Like physicians, a patient's role in the medical model follows a script as well . First a patient may present to their family physician with complaints of their symptoms (Frankel, 1994) . In this regard, the patient is looking for legitimization of their illness through a physician's diagnosis of pathology (Frankel, 1994). Yet, there may be several problems for youth accessing the health services they want within this medical model. First, within the hierarchical relationship with the physician there would be a power imbalance (Frankel, 1994) which may 28 make an already sensitive subject, such as mental or sexual health, and risk behaviours more difficult to address. In addition, within this model of care, mental or sexual health do not fit into the ascribed medical model, as an individual seeking mental or sexual health services may not be presenting with a chief complaint with symptoms or pathology (Merri l l , Laux, & Thornby, 1990). Finally, addressing sexual health with a physician can be particularly difficult for adolescent women as the course of diagnosis has been shown to make adolescent women uncomfortable with intimate physical examinations (Oandasan & Mal ik , 1998). They also fear judgment by physicians about their sexual activity (Marshall 2000). Yet, there are many individual and public-health level reasons why it is important to reduce missed care for young people. In terms of sexual health and prevention, the physician can provide education to help reduce unintended consequences of sexual activity, such as unwanted pregnancy and sexually transmitted infections including H I V / A I D S (Felows, 1992; Oandasan & Mal ik , 1998; Steben, 1990). Physicians can further help women with diagnosis and care for pregnancy, sexually transmitted infections, and counselling for potentially abusive sexual relationships (Oandasan & Mal ik , 1998; Steben, 1990). Moreover, in most cases, physicians are necessary providers for sexual health since a physician is required to prescribe oral contraception, or to screen for sexually transmitted infections. Also, mental health screening in primary care settings is effective in detecting youth who might benefit from interventions (Walker & Townsend, 1998). Some adolescents attempt to alleviate their distress by approaching some type of helping agent, either formal (e.g. mental health professional, teacher) or informal (e.g., family, friends). These "help-seeking" behaviours (Offer, K . I . & Ostrov, 1991) are coping strategies associated with better adjustment (e.g. Frydenberg, 1997). It is important to study patterns of adolescent help-seeking behaviours because adolescence is a time when health habits and help-seeking behaviours are learned and established (Hansel & Mechanic, 1985). 29 Thus, it is evident that within the biomedical model, physician primary care services are necessary for addressing youth health. A s a result, it is imperative to understand and overcome barriers that prevent adolescents and young adults accessing needed care. 2.4.3 Y o u t h Access to Heal th Care While there is a gap in the literature directly looking at young adults' access of health care, much can be learned from the broader literature on adolescent experiences. The available literature demonstrates that there are many issues for adolescents accessing physician services. Barriers to seeking help from a professional include adolescents' lack of knowledge about available resources, perceived characteristics of helpers (e.g., friendliness, helpfulness), and concerns about confidentiality (e.g., Dubow et al., 1990; Kapphahn, Wilson, & Kle in , 1999). Moreover, adolescents' perceptions of the person(s) offering help is a better predictor of their acceptance of help than is the youths' level of emotional distress (e.g., Offer et al., 1992). Other factors associated with adolescent access to primary care physicians include: the gender of the adolescent (e.g., Turner and Runtz, 1995; Schonert-Reichl, Offer and Howard, 1995); the gender of the physician (female adolescents preferring female physicians), (see K l e i n et al., 1999); the age of the adolescent (older adolescents being more likely to access professional health resources than younger adolescents) (e.g., Millstein, 1993); social cognitive development (see Seiffge-Krenke, 1998); and differences in symptoms experienced (King et al., 1988; Schonert-Reichl and Offer, 1992). Another aspect to accessing physician services for adolescents and young adults may be related to issues of l iving in a rural, suburban or urban community. In Canada, physicians are an integral link to the health care system, facilitating access to medical services such as referrals to psychiatrists and to administer medication. In rural communities, physicians may be the only medical resource available for assistance with health problems. In British Columbia the family physician: population ratio varies widely among health region areas, ranging from 0.76:1000 in 30 the Peace Liard region to 1.65:1000 in the Vancouver region (Thommasen, Gryboski, & Sun, 1999). Moreover, the problems with physician burnout in communities with low physician: population ratios is compounded by the fact that there is also a relative shortage of specialists working in these areas (Thommasen, Gryboski, & Sun, 1999). Indeed, smaller communities in rural regions of Canada report shortages of psychiatrists, and mental health services for adolescents (Sears & Sheppard, 1999). While the majority of the literature on rural access to health care in Canada is focused on remote northern areas, some of the key issues may be germane for other communities. These issues can include: recruitment and retention problems for physicians in rural areas leading to physician shortages and lack of continuity in care (Godwin, Lailey, Mi l le r , Moores, & Parsons, 1996; Sibbald, 1999); transportation needs to see a physician; lack of privacy and familiarity; fewer social and health supports; and increased poverty (Liepert &Reutter, 1998). Where there are problems in the physician-patient relationship, this may lead to access of these services being hindered for youths. A 1995 Canadian survey indicated that over one-third of Canadians are dissatisfied with their physicians, while a similar percentage reported physician behaviour as "arrogant" or "insensitive" (Posner, 1995). Problems are perceived from both sides of the physician-patient relationship. Physicians have reported that 20-25 percent of general practice visits result in communication difficulties (Pendleton & Hasler, 1983). However, this is argued to be an underestimation as, "physician evaluation of the terminology that patients understand is often inaccurate and the extent of miscommunication is under-recognized." (LindenSmith, 1998; Pendleton & Hasler, 1983). Ammerman et al.'s (1992) study of women aged thirteen to eighteen found that teens often misunderstood medical vocabulary related to sexual health. Millstein, Igra and Gans (1996) found gender differences among physicians in their addressing of adolescent sexual health. Their study of 1,217 physicians found that female 31 physicians reported providing prevention services at a higher percentage than their male counterparts. This would concur with Roter et al. (1991)'s findings that female physicians conducted longer medical visits with substantially more talk, than their male colleagues. Differences were especially evident during patient history taking, when female physicians were observed to talk forty percent more than male physicians, resulting in the patients of the female physician talking fifty-eight percent more than those of male physicians. Roter et al. (1991) also found that in their comparison of male and female physicians, female physicians engaged in more positive talk, partnership-building, question-asking and information giving than the male physicians. Likewise, compared to patients of male physicians, female physicians' patients engaged in more positive talk, more partnership-building, question-asking and information giving, related to both biomedical and psychosocial topics. Croft and Asmussen (1993)'s study involved focus groups with parents and 800 adolescents to determine the preferred physician role regarding families and sexual development. Results showed that physicians were believed by parents to be appropriate experts to assist in preventing negative risk behaviours including sexual intercourse, and emphasized the importance of the physician developing comfortable relationship early on with parents and youth to allow for reciprocal dialogue about sensitive topics. Parents also commented that physicians generally appeared uncomfortable when discussing personal issues, in particular sexuality, and frequently lacked communication skills (e.g., use of open-ended questions or statements) to foster conversation (Croft & Asmussen, 1993). Youth also identified physicians as a logical source of information about sexuality, but felt hesitant asking questions that they felt might prompt value-based discussions. Youth also expressed concern about confidentiality in their physician-patient relationship, and desired that physicians be more "askable" than they are perceived to be (Croft & Asmussen, 1993). A qualitative study done in Toronto (Oandasan & Mal ik , 1998) looked at the experiences 32 of female adolescents when visiting a family practitioner. With a small sample of eight participants, the following themes were identified: adolescent girls feel more comfortable with female physicians, adolescent girls feel uncomfortable during physical examinations, adolescents would like doctors to explain medical issues, adolescent girls want to be treated as teenagers by their doctors, and adolescent girls want their doctors to be more like friends (Oandasan & Mal ik , 1998). It appears from this study that barriers to physician services exist for adolescent women in Toronto and that these issues have the potential to be addressed through education and policy. However, the small number of participants requires confirmation of findings from other research. In Nova Scotia, in-depth interviews with 28 adolescent girls identified multiple barriers that stopped and/or delayed access to sexual health services from physicians (Marshall, 2000). Barriers included fear of P A P tests, concerns regarding confidentiality and reactions of older and male physicians (Marshall, 2000). It was also found that barriers to accessing physician care were overcome by adolescent girls as they became more confident in their choices and felt they were making responsible decisions to seek care (Marshall* 2000). These findings might shed light onto the mechanisms through which those who miss needed care for sexual health services might seek care later through personal development and social perceptions. It has been demonstrated how important good communication can be between physician and patient/client. The available literature shows that, from the patients' perspective, the most significant expressions from physicians include: "exploring the presenting problem thoroughly, expressing empathy and caring, handling patients' feelings, using comforting and listening skills, being attentive to verbal cues, using open-ended questions, involving patients in decisions, inspiring trust, and expressing interest in patients' opinions." (LindenSmith, 1998). While this may seem like a challenging list of preferences for physicians to accomplish, good communication can effect the outcome of a medical encounter. Studies indicate that patient satisfaction with their physician leads to increased compliance, less physician changing, and a 33 higher likelihood of seeking care at an appropriate time (Wolliscroft et al., 1994). On the other hand, poor communication has been cited as one of the leading causes of problems in the physician-patient relationship (LindenSmith, 1998). A l l of these outcomes, both positive and negative, have implications for adolescents seeking physician primary care services. It is clear that adolescents (as well as all other age groups) have been shown to have multiple barriers to health care access. It would be interesting to see i f the issues pertaining to adolescents persist into young adulthood, or are compounded by aspects related to the transitions to adulthood. 2.4.4 Genera l Access to Health Care Issues Moving from adolescent health care access issues to the general Canadian population, there are some recent findings of note. Demonstrating the importance of the topic of health care access, Statistics Canada has two recent reports on Canadians' access and barriers to health care, analyzing different national population data sets. The report "Access to Health Care Services in Canada, 2003" is a descriptive report of the Health Services Access Survey (HSAS) cross-sectional data, a subset of the Canadian Community Health Survey (CCHS) , 2003 (Sanmartin, Gendron, Berthelot, & Murphy, 2004). The H S A S is a nationally representative data set (not including the territories), including Canadians aged 15 years and older, N=32,005, with a response rate of 87.1%. The health and health care access data is limited to self-report, and includes data at the provincial and national levels. Overall, Sanmartin et al., (Sanmartin et al., 2004) found that 86% of Canadians report having a regular family physician. Sanmartin and colleagues (2004) further describe that fifty-seven percent of Canadians aged 15 years and older report requiring routine care for themselves in the last twelve months. In total, sixteen percent of Canadians report barriers to care, with provincial differences. Approximately one in four Canadians who required immediate care for a minor health problem had experienced difficulties accessing health care. However, due the sampling design only accessing those living in private 34 dwellings, many at risk-individuals such as street kids, and the homeless would have been missed. As a result, these figures may be an underestimation of the proportion of Canadians without a regular physician and difficulties in access to care. The top four barriers to health care'during regular office hours were: 1) difficulty getting an appointment (44%); 2) long waits for an appointment (37%); 3) long in-office waits (22%); and 4) difficulty contacting a physician (17%). The data are broken down by province and by time of day that care was needed. However, the report does not break down the data by any other socio-demographic factors such as age, gender, or rural/urban/suburban location which would have been useful. Nor is there any multivariate analysis done that might incorporate more complex understandings of missed care, or inclusion of variables such as ethnicity or socioeconomic status (SES). A t least based on self-report, a large number of Canadians (16%) are reporting barriers to care despite the vast majority (86%) reporting that they have a family physician. There was no information reported on whether those without a physician were more likely to report difficulties in accessing care. A report with more information on Canadians' access to health care services is Sanmartin et al.'s (2002) study on the trends in missed health care among Canadians from 1994/95 to 2001. This report describes three waves of cross-sectional (not longitudinal) data. The data are from the first half (September 2000 through February 2001) of data collection for Cycle 1.1 of the C C H S and from cross-sectional (1994/95 through 1998/99) household components of the National Population Health Survey (NPHS). The results from each data source are compared, providing a compelling, though largely descriptive, analysis of the trends in missed health care, as well as speculation as to the root causes. "Unmet health care needs", or more appropriately labelled, "missed care" is a self-report variable and is defined as "the difference between health care services deemed necessary to deal with a particular health problem and the actual services received." (p. 15) Sanmartin et al. found 35 that the proportion of people aged twelve or older reporting missed heath care rose slightly but steadily from 4.2% in 1994/95 to 5.1% in 1996/97 and 6.3% in 1998/99. However, between 1998/99 and 2000/01, reports of missed care rose substantially. Preliminary data from the C C H S indicate that 12.5% of Canadians aged 12 or older, 3.2 mill ion Canadians, experienced missed care in 2000/01. This is nearly double the proportion of missed health care reported just two years earlier. The proportion, as well as the absolute numbers, of Canadians reporting missed care has risen. For example, the number who felt that they waited too long for services rose from an estimated 358,000 in 1998/99 to 969,000 in 2000/01. The C C H S results show substantial increases in missed care for both sexes and across age groups. In 2001, almost eleven percent of men reported missed care, more than double the 5.2% who did so in 1998/99. The increase among women was from 7.4% in 1998/99 to 14% in 2000/01. The increase in missed care from 1994/95 to 2000/01 was statistically significant for each age group. The greatest increase was among 35- to 64 year olds, from.6.4% in 1998/99 to 13.2% in 2000/0.1. The .12- to 34 year-olds increased reporting of missed care from 6.6% in 1998/99 to 13.2% in 2000/01; and from 3.9% to 7.4% for those 65 years of age and older. 'Unmet needs' can arise, according to Sanmartin et al., (2002), as a result of features of the health care system (e.g., unavailability of services or waiting times), or as a result of the personal circumstances of those seeking care (ex., socio-economic status or time constraints). In: both the 1998/99 and 2000/01 data sets, the most common reason self-reported for missed care related to features of the health care system. Long waits and the unavailability of services when needed were cited most frequently. The relative proportion who attributed their missed care to factors reflecting their.personal circumstances declined between 1989/99 and 2000/01. For example, in the latter period, smaller proportions of respondents with missed care reported that they "didn't get around to it" or were "too busy". The system-related reasons reported for missed care include: waiting time too long; service not available when needed; and service not available 3 6 in area. The personal-related reasons for missed care included: 'didn't get around to it/didn't bother'; 'too busy'; 'felt care would be inadequate'; 'cost'; 'decided not to seek care'; 'didn't know where to go'; 'transportation problems'; 'dislikes doctor/afraid; personal/family responsibilities'; and 'other'. Sanmartin et al. (2002) then provide an interesting discussion speculating on the reasons why they found such an increasing trend in reported missed heath care. Health reforms involving fiscal restraint, reorganization or hospital restructuring might account for some of the increase, yet, evidence to date suggests that hospital downsizing and budget cuts have not resulted in less health care utilization or poorer health outcomes. Moreover, relative health care expenditures have increased approximately four percent since the mid-1990s, after adjusting for inflation. Hence, missed care may be affected by more that just the absolute amount of resources available. Missed care is likely related to the allocation of resources across services and regions. One of the most interesting points the authors bring out is the possibility that the perception of what constitutes timely delivery of care may have changed, rather than actual changes in care delivery. Public opinion polls suggest that the proportion of people who felt that the health care system should be the top priority of government policies grew from 30% in July 1998 to 55% in January 2000, reflecting an increased concern about the state of health care. On the other hand, in 1999, over 80% of Canadians were satisfied that the health care system could meet their own health needs and those of their friends and family. Characteristics of individuals requiring care (i.e., the increase in the proportion of seniors) may also contribute to the rise in reported missed care, though this seems unlikely given that seniors reported less missed care than other age groups. It is important to note that there may be problems in comparing data from the different waves of collection as questions were asked slightly differently, (e.g., different terminology used 37 to name 'family physicians') 2 . Also , the results are based on self-reported data rather than any objective criterion for unmet health care needs. Self-report data can be subject to sources of reporting error such as recall bias. Some of the other problems with self-report could be concerns on the part of respondents about the confidentiality of the data provided, wanting to give the answers that the respondent feels the interviewer desires, answering the way they think others would, fear that they might be judged by their answers, or not understanding the question (Bailey, 1994). Another issue with interpreting the data is that cross-sectional data analysis comes with limitations for examining changes that might occur over time. Further, there are limitations when trying to assess causality. According to Gray and Guppy (2003), four conditions must be met in order to establish that something causes another. First, there must be a relationship between both variables (i.e., they must co-vary). Second, temporal ordering must be established (i.e., the variable being affected must come after the one doing the affecting.). Third, spurious linkages must be accounted for. Fourth, there must be an explanatory rationale for the causal link (Gray & Guppy, 2003). While data collected at one point in time (cross-sectional) may have limitations, it is possible to establish the time order of many variables (such as gender and income). Thus, it is possible to draw causal inferences from cross-sectional data, provided that third variables (or spurious linkages) can be accounted for and explanatory rationale can be drawn. Another issue with the data presented by Sanmartin et.al. (2002) is that there is no distinction made between whether the missed care was missed completely or delayed. Despite these limitations, these reports are important as they identify key areas for further research. Questions such as: How does missed care vary by gender, location, social support, age and context? How is missed care different according the health problem the individual wants addressed? Is the rise in reported 2 Both 'general practitioners' and 'family physicians' provide primary care. The distinction in Canada is that family physicians have additional training. 38 missed care a cultural phenomenon based on media and political rhetoric, or is it grounded in increases in actual unmet care over the last decade? 2.5 Adolescence and Y o u n g Adul thood Adolescence is defined as the period of the life course that begins with the onset of puberty and ends with the attainment of adulthood (Arnett, 2001). A meta-analysis by Schlegel and Barry (1991) of ethnographies from around the world confirms that adolescence occurs in almost all cultures. Yet, the length, content, and experiences of daily life of adolescence vary, as do the factors used to define the boundaries between adolescence and adulthood and the social processes and institutions shaping the transition between them, for different cultures (Schlegel & Barry, 1991). The ages associated with the entry into adolescence, and exit from adolescence into adulthood, have increased over the last century in North America. Two explanations for why adolescence has moved forward chronologically in the life course are: the decline in the age of menarche and the growth of high school attendance to a normative experience for adolescents in North America (Arnett, 2001). Despite multiple options for defining adolescence, for research purposes, most studies use chronological definitions of adolescence, choosing to study the teen years (from approximately age 12 to 18), or to rely on convenience samples of adolescents attending secondary schools. However, due to societal changes in North America it has been argued that adolescence, or entry into adulthood, has been extended beyond age 18 (Feldman & Elliott, 1990; Shanahan, 2000). Trends in the United States reveal significant changes in the timing and sequencing of the transition to adulthood. Evidence of this is found in shifts in, for example, age at first marriage, birth of first child, or leaving parental home at a later age. Similar to the arguments made by Fasick (1994), Shanahan (2000)'views these changes in timing and sequencing as largely attributable to the modernization of society, and the standardization and individualization of the 39 life course. Moreover, these trends have been "complicated by short term economic fluctuations and discrete historical events and, within cohorts, by social inequalities such as gender, race, and socioeconomic status." (Shanahan 2000, p.668) The standardization of the life course can be seen in the organization of public services, employment opportunities by age, rights granted by the state by age, and others. Many of the changes seen in these patterns (i.e., standardization and compactness) can be attributed to increased health and the expansion of the education system over the last two centuries (Shanahan, 2000). Over time, 'standardization' of the transitions to adulthood increased as nation-states formed and developed. Creating integrated coherent, modern, states meant establishing common practices, laws, taxes, sets of entitlements, and so on. However, state-making could also bring great diversity. In recent years, especially since the 1970s, the new sources of diversity have developed, for example, new migration patterns, and at the same time, under the influence of neo-liberal ideology, many modern states have curtailed their activities, slackened their commitment to equity and favoured 'market-driven' and markedly more inequitable policies. Increased diversification has become especially notable since the 1960s through the 'individualization' of the life course. It is hypothesized (contentiously) that individuals have increasing agency in construction of their own biographies due to fewer constraints from family and locale (Shanahan, 2000). The argument is that the highly standardized trajectories of school, work, and family have been shattered by several structural and cultural developments since the 1960s, whereby links between educational certification and occupational status have weakened, the 'half-life' o f occupational training and expertise has decreased substantially, the family has reached new levels of instability, and cultural representations of love and work emphasize flexibility, choice, and impermanence (Shanahan, 2000). While the above arguments are under debate, and not yet adequately studied, it is true that traditional markers for the transition to 40 adulthood have "decompressed", yet continue to overlap, and that new pathways to adulthood have emerged with greater variability in sequencing of markers (Shanahan, 2000). These transformations make this time in the life course of particular interest for social research. Indeed, with these changes in the patterns of transitioning into adulthood, a new concept -'emerging adulthood'- has been labelled by Arnett (2000). Emerging adulthood is the period from roughly ages 18 to 25 or 30 and is a period of transitioning from adolescence to adulthood (Arnett, 2000). According to Arnett, the characteristics that distinguish it from other periods in the life course are that it is the "age of identity exploration, of instability, o f self-focus, of feeling in between, and of possibilities" (Arnett, 2004). To further clarify, emerging adulthood exists only in cultures in which young people are allowed to postpone entering adult roles, such as marriage and parenthood, until their mid-twenties and it is a recent phenomenon historically (Arnett, 2004). In North America, the transition to adulthood takes place legally at age 18, whereby one is considered an adult by the government (i.e., you are allowed to vote), but the transition can also be defined as entering roles considered to be part of adulthood such as full-time work, marriage, and parenthood (Arnett, 2000). In a study of U S college, students, young people report that the most important markers for the transition to adulthood are accepting responsibility for one's self, making independent decisions, and becoming financially independent, reflecting what Arnett labels "the individualistic values of the American majority culture" (Arnett, 1994). However, a sample of American college students from one university may be too narrow a sample from which to generalize. For example, one might speculate that many American college students are still economically dependent on their parents, while concomitantly haying achieved a certain amount of autonomy from their parents. A s a result college students may be less apt to want to acknowledge the transitions to financial independence, employment, marriage, and having children as being synonymous with adulthood i f they want to be thought of as 41 autonomous adults, while not yet having achieved these social markers. If it is desirable to be perceived as an autonomous adult, then it w i l l no doubt be in the student's self-interest to focus - on they ways in which they are adult, and to downplay the significance of the more traditional markers for transitioning to adulthood. According to Arnett, some of the reasons why young people are entering adult roles of marriage and parenthood later include the invention of the birth control p i l l and the subsequent ability to enter sexual relationships without necessarily becoming pregnant or feeling the need to marry; the increasing number of years devoted to education; and the changing role of women in society (Arnett, 2004) . Young adults are in a state of flux, with great variability in individual patterns for the assumption of adult roles throughout their twenties (Cohen, Kasen, Chen, Hartmark, & Gordon, 2003). While there is a gradual increase in the average age at which adult roles are assumed, the progress of individuals towards adulthood has been found to be much more variable, with a great deal of moving back and forth between increasing and decreasing dependency (Cohen et al., 2003). This indicates that young adulthood can be a protracted period of the life course that is also ambiguous in timing and transitions. The instability of emerging adulthood is illustrated by the fact that 18 to 25 year olds have the highest rates of residential change of any age group in the United States (Arnett, 2000). A similar pattern can be seen among Canadians by observing the inter-provincial migration rates. The chart below indicates that young adults aged 20 to 30 years have the highest rates of moving between provinces (Statistics Canada, 2002): 42 Figure 2.5.1 Interprovincial Mig ra t ion Rates by Age and Sex, Canada , 1996-2001 % Population aged 5 years and over Source : 2001 Census W i t h t h e i n c r e a s e i n i n s t a b i l i t y , s e l f - f o c u s a n d i d e n t i t y e x p l o r a t i o n a n d f o r m a t i o n , e m e r g i n g a d u l t s h a v e c h a r a c t e r i s t i c s d i s t i n c t f r o m a d o l e s c e n t s , a s w e l l a s a d u l t s ( A r n e t t , 2 0 0 4 ) . T h e s e c h a r a c t e r i s t i c s o f y o u n g a d u l t h o o d a r e o f t e n a c c o m p a n i e d b y c o n d i t i o n s o f f i n a n c i a l d e p e n d e n c e a n d i n s e c u r i t y c o n t i n u i n g t o a l a t e r a g e ( A r n e t t , 2 0 0 0 ; C o h e n e t a l . , 2 0 0 3 ; S h a n a h a n , 2 0 0 0 ) . R e l a t e d t o b e i n g i n t h e e a r l y s t a g e s o f w o r k i n g a n d / o r c o n t i n u i n g e d u c a t i o n c a n a l s o b e a n u n s t a b l e t i m e f o r y o u n g a d u l t s , w i t h l e s s e m p l o y m e n t s e c u r i t y , l o w e r w a g e s , a n d h i g h e r m o b i l i t y ( A r n e t t , 2 0 0 0 ; S h a n a h a n , 2 0 0 0 ) . These cumulative aspect of young adulthood suggests that many young adults may be in a less than opt imal situation developmentally, socially, financially, or in terms of their educational preparation to access health care independently when they need care. Moreover , with instabili ty and higher rates of migration (especially between provinces), there may be increased issues with finding a pr imary care physician. 4 3 T h u s , t h i s d i s s e r t a t i o n l o o k s a t t h e l i f e c o u r s e s t a g e o f y o u n g a d u l t h o o d i n r e l a t i o n t o h e a l t h c a r e a c c e s s , a s a s p e c t s u n i q u e t o t h i s p e r i o d i n t h e l i f e c o u r s e m a y h a v e a d r a m a t i c i m p a c t o n m i s s i n g n e e d e d h e a l t h c a r e . 2.6 Y o u t h and health: W h y it is Important to Study their Access to Care M o s t a d o l e s c e n t s a n d y o u n g a d u l t s a r e c o n s i d e r e d h e a l t h y ( C h e n g , S a v a g e a u , S a t t l e r , & D e W i t t , 1 9 9 3 ; S i e f f g e - K r e n k e , 1 9 9 8 ) . F r o m a p o p u l a t i o n h e a l t h p e r s p e c t i v e , a d o l e s c e n c e i s o f t e n p e r c e i v e d a s a p e r i o d i n l i f e w h e n i l l n e s s a n d u s e o f m e d i c a t i o n i s l e s s c o m m o n ( H e a l t h C a n a d a , 1 9 9 9 ) . H o w e v e r , t h i s m a y b e m i s l e a d i n g , a s a d o l e s c e n c e i s t h e l i f e s t a g e i n w h i c h m o r t a l i t y r a t e s h a v e i n c r e a s e d t h e m o s t d r a m a t i c a l l y i n r e c e n t d e c a d e s ( C h e n g e t a l . , 1 9 9 3 ) . I n t h e U n i t e d S t a t e s , t h e m o s t c o m m o n c a u s e s o f m o r b i d i t y a n d m o r t a l i t y d u r i n g a d o l e s c e n c e i n c l u d e : i n j u r i e s r e l a t e d t o v i o l e n c e ( v i o l e n t i n j u r i e s , a c c i d e n t s , h o m i c i d e s a n d s u i c i d e s a c c o u n t f o r 7 7 % o f a d o l e s c e n t d e a t h s i n t h e U S ) , c a r d i o v a s c u l a r d i s e a s e , c a n c e r , i n f e c t i o u s d i s e a s e s , c h r o n i c i l l n e s s e s a n d p s y c h o s o c i a l p r o b l e m s a n d d i s o r d e r s ( S i e f f g e - K r e n k e , 1 9 9 8 ) . C a l l a n d c o l l e a g u e s ( 2 0 0 2 ) a r g u e c o n v i n c i n g l y t h a t n a r r o w d e f i n i t i o n s o f h e a l t h b a s e d o n m o r b i d i t y a n d m o r t a l i t y i g n o r e u n d e r l y i n g c u m u l a t i v e p r o c e s s e s o f b e h a v i o u r s a n d e x p e r i e n c e s t h a t " c a n c r e a t e a b u r d e n o f h e a l t h p r o b l e m s t h a t w i l l b e m a n i f e s t e d i n l a t e r l i f e . " ( p . 7 0 ) . A d o l e s c e n c e a n d y o u n g a d u l t h o o d a r e k e y t i m e s f o r h e a l t h r i s k b e h a v i o u r s i n c l u d i n g w e i g h t p r o b l e m s a n d e a t i n g d i s o r d e r s , r i s k s a s s o c i a t e d w i t h s e x u a l a c t i v i t y , i n c l u d i n g u n w a n t e d p r e g n a n c y a n d s e x u a l l y t r a n s m i t t e d i n f e c t i o n s ( S T I s ) , c o n s u m p t i o n o f a l c o h o l , t o b a c c o , i l l i c i t d r u g s , a n d m e d i c a l l y p r e s c r i b e d s u b s t a n c e s ( A r n e t t , 2 0 0 1 ; S i e f f g e - K r e n k e , 1 9 9 8 ) . A p r i m a r y c a r e p h y s i c i a n i s o n e o f t h e f i r s t l i n k s t o p r e v e n t i o n a n d i n t e r v e n t i o n f o r a l l o f t h e s e h e a l t h i s s u e s t h a t a f f e c t a d o l e s c e n t s a n d y o u n g a d u l t s . T h u s e x a m i n i n g t h e p r e v a l e n c e o f m i s s e d c a r e a n d w h y t h e y m i s s c a r e i s c e n t r a l t o a d d r e s s i n g a d o l e s c e n t a n d y o u n g a d u l t h e a l t h . 4 4 2.6.1 Heal th R i s k Behaviours Health risk behaviours can also be studied in relation to transitions in the life course. Many developmental transitions during the second and third decades of life provide the structure that transforms children into adolescents and adolescents into young adults. These developmental transitions "are the paths that connect us to transformed physical, mental, and social selves." (Schulenberg, Maggs, & Hurrelmann, 1999, p . l ) Various developmental transitions from childhood to adulthood provide risks and opportunities for adolescent physical and mental health. More specifically, Schulenberg et al. (1999) present research, theory, and practice that relate normative and non-normative transitions during adolescence to health-compromising and health enhancing behaviours. This is of particular use as much of the adolescent risk research focuses only on "high risk" groups of adolescents. This dissertation proposes to look at normative transition experiences in relation to both transitions and health help-seeking. Discontinuity is an element common to all developmental transitions as "each transition involves some change in how we experience ourselves, and our world, as well as how others experience us." (Schulenberg et al., 1999, p . l ) One of the more interesting aspects of studying adolescence is that it is a time when multiple and simultaneous transitions are experienced. Stress and health risks as well as opportunity and enhancement can occur as adolescents make their way through developmental transitions and may even be part of the negotiation process. According to Shulenberg et al. (1999), there are four 'models' for viewing the relationship between developmental transitions and health risks and opportunities. The four models are: 1. Health risks as consequences of experiencing developmental transitions: storm and stress redux part one; 2. Developmental transitions as altering the developmental match between individual desires/needs and contextual affordances: storm and stress redux part two; 3. Health risks and health-enhancing behaviours as components of negotiating developmental transitions; and 4. Developmental transitions as exacerbators of health risk status (Schulenberg et al., 1999). The 45 relationship between health risk behaviours and transitions to adulthood wi l l not be explored in this dissertation, but it is an area for future investigation. 2.6.2 Sexual Heal th The majority of adolescents in Canada are sexually experienced. Fifteen percent of 12 to 14 year old girls in Canada have had sexual intercourse (Health Canada, 1999). According the Canada Youth and A I D S study (King, Beazley, et al., 1988), almost fifty percent of grade eleven students have had sexual intercourse. Negative consequences of sexual activity can include unwanted pregnancy, sexually transmitted infections (STIs), and physical or emotional abuse. Adolescent pregnancy is usually unintended (Felows, 1992), may result in low birth weight infants, and preterm delivery, and has an associated higher infant mortality rate (Fraser, Brockert, & Ward, 1995; McAnarney & Hendee, 1989). For women under the age of fifteen years, the complication rate is sixty percent higher than for the rate for all women giving birth (Feldman & Martel, 1994). Teen mothers complete less education than those who do.not bear children early (Feldman & Martell , 1994; McAnarney & Hendee, 1989). Teen mothers also . reach lower levels of work success and of long-term income, and feel less satisfied with their vocational achievements (Feldman & Martel, 1994). Study findings into the effects of early childbearing on children's outcomes have indicated that children of teen mothers fare no less well than their peers who were born to young adult mothers, though both fare worse than the children of adult mothers (Jaffee, 2002; Levine, Pollack, & Comfort, 2001; Furgusson & Woodward, 1999). This would suggest that young adult and adolescent mothers share problems, perhaps related to their life course stage, that negatively impact their parenting. Indeed, there is considerable evidence that the children of adolescent mothers experience poorer cognitive, academic, and behavioural outcomes during childhood when compared with children born to older mothers, and some of the differences persist even after accounting for social and economic disadvantages in the mother's pre-childbearing or current family 46 environment (Corcoran, 1999). Thus, it may be that the implications of childbearing during the years of young adulthood are similar to those which we have been concerned with for the children of teen mothers. In a study of education and psychosocial outcomes for young adults born to young mothers, Furgusson and Woodward (1999) looked at mothers who were <19, 20-24, 25-29, and over 30 at the time of the birth for the study child. Increasing maternal age was associated with declining risks of educational underachievement, juvenile crime, substance misuse, and mental health problems for their children (Furgusson & Woodward, 1999). They also found that increasing maternal age was associated with being more nurturing, supportive, and having more stable home environments (Furgusson & Woodward, 1999). These linkages between maternal and childhood environment explained most of the association between maternal age and later outcomes. A study of qualities of adolescent parenting that assessed mothers aged 17-22 found that younger age was associated with low parenting confidence, high parenting stress, and inappropriate parenting values (East, Matthews, & Felice, 1994). The authors called the coalition of these factors a "triple jeopardy" that led to low child acceptance and poor parenting practices (East, Matthews, & Felice, 1994). Another study that found early motherhood to have strong negative correlation with children's academic and behavioural outcomes also found no significant difference between mothers aged 20-21 and those under 19 (Levine, Pollack, & Comfort, 2001). Thus, young mothers may be dealing with unresolved issues as a consequence of adolescent pregnancy, and these consequences have relevance to their health care needs from primary care providers. Problems with sexually transmitted infections (STI) and sexual assault are relevant for young adults, and access to primary care can be helpful in identifying issues, diagnosing and treating them. In Canada, the highest rates of Chlamydia trachomatis infection (the most common STI) are reported in 15 to 19 year old females and 20 to 25 year old males, and are associated with high risk behaviours (Squires, et al., 1997; Torrence, 1996). Data regarding 47 sexual assault, including date rape is controversial due to varying definitions and reporting bias (Humphreys & Herold, 1996). Among academics, the generally agreed upon lifetime incidence of sexual assault in Canada is between fourteen to twenty-five percent (Humphreys & Herold, 1996). Less tangible aspects of well-being related to sexual health have not been explored as thoroughly in the literature. However, the percentage of youth who do experience negative consequences of their sexual activity (unwanted pregnancy, STIs, physical or emotional harm) is cause for concern and major focus for health service providers and researchers. 2.6.3 M e n t a l Heal th It is during adolescence that many emotional health problems first arise (Wells, Deykin, & Klerman, 1985). Adolescence is no longer believed by researchers to be a time of extreme emotional turmoil and "storm and stress" (e.g., Arnett, 2001; Offer & Schonert-Reichl, 1992). However, popular conceptions of the storm and stress of adolescence remain (Holmbeck & H i l l , 1988; Holmbeck et al., 1995). Nonetheless, adolescence and young adulthood are particularly challenging periods of life due to the co-occurrence of physical and cognitive development, alterations in interpersonal relationships (e.g., increased identification with peers rather than parents), and environmental shifts (e.g., school and work transitions). These normative life events, in conjunction with non-normative life events, may introduce new stress not previously encountered. Social epidemiology research suggests that mental illness is, in part, a by-product set in motion by stressful life experiences. Therefore, it is not surprising that the onset of adolescence is associated with higher levels of depression and stress (e.g., Larson & Ham, 1993) and greater prevalence of mental health problems generally (Compass, Hinden, & Gerhardt, 1995). The majority of individuals do not experience intense emotional distress during adolescence (Offer & Schonert-Reichl, 1992), however, international studies suggest that psychiatric disorders are exhibited by approximately twenty percent of youths (Offer & 48 Schonert-Reichl, 1992). Adolescents themselves report that mental health is a salient concern (e.g., Boehm, Schondel, Marlow, & Rose, 1995; Dubow et al., 1990; Mil ls tein, 1993). Canadian adolescents have been shown to be at risk for mental health problems (Davidson & Manion, 1996). For example, the suicide rate in Canada is one of the highest among industrialized countries, with a significant concentration of deaths by suicide among male adolescents and youth (Health Canada, 1999). 2.7 Stress and Heal th In relation to mental health, it is important to look at stress and coping abilities. While stress wi l l not be directly measures in this dissertation research, there may be ties between stress, social support, health status, and health care utilization. Brunner and Marmot (1999) overview literature and outline some of the specific pathways by which the environment and stress are understood to impact health. They state that humans today often activate their flight or fight response too hard and too often. From an evolutionary perspective, these stress responses have helped humans survive in the face of challenge. Yet, while our biology has remained essentially the same, our environment and challenges have changed dramatically over the last 10,000 years. One theory regarding stress-response is "the limits of stress reactivity" which relies on the principle that organisms require a stable internal environment in order to live successfully. The nature and size of biological responses to psychological demand (i.e., stress), influences health in several ways: 1) it may be directly responsible for disease; 2) it may increase vulnerability to certain illnesses; 3) the pattern of reactivity may disrupt existing disease processes; and 4) it might act as a trigger for acute events such as heart attacks (Brunner & Marmot, 1999). Kawachi and Berkman (2001) explore the relationship of social ties impacting mental health outcomes. Mental health outcomes are defined as stress reactions, psychological well-being, and psychological distress such as depressive symptoms and anxiety. Kawachi and 49 Berkman outline two alternatives, though not mutually exclusive, causal models for these relations. First, the "main effects model" proposes that social relationships have a beneficial effect on mental health regardless of whether individuals are under stress. The main effects model specifies several pathways, (i.e., social networks, positive affective states, and health promoting behaviours), through which participation in social networks can affect psychological well-being. According to Kawachi and Berkman (2001), the influence of social ties refers to the way members of a social network obtain normative guidance about health-relevant behaviours. The second model presented by Kawachi and Berkman (2001), is the "stress-buffering model" that posits social ties are related to well-being only for persons under stress. In the stress-buffering model, the perceived availability of functional support is thought to buffer the effects of stress by enhancing an individual's coping abilities. Social support is thought to buffer the effects of stress by enhancing an individual's coping abilities. Social support is hypothesized to prevent or modulate responses to stressful events that are damaging to health. The perceived availability of social support in the face of a stressful event may lead to a more benign appraisal of the situation, thereby preventing a cascade of ensuing negative emotional and behavioural responses. In all , integration in a social network can provide a sense of purpose, belonging and security, as well as recognition of self-worth. One's location in a network enhances the likelihood of accessing various forms of support that protect against distress (i.e., information). However, Kawachi and Berkman note that the protective effects of social ties on mental health are not uniform across groups in society. For example, gender differences in support derived from social network participation may partly account for the higher prevalence of psychological distress among women compared to men. Social connections may paradoxically increase levels of mental illness symptoms among women with low resources, especially i f such connections entail role strain associated with obligations to provide social support to others. 50 Stress and coping are increasingly interesting topics as evidence mounts to demonstrate their impacts on health. O f particular interest is the significance of the literature on coping. Thoits (2001) provides a selective review and summary of existing knowledge, unanswered questions, and a proposal for new research directions for stress, coping resources, coping strategies, and social support. There is a bias towards the impact stress has on mental health outcomes as her literature review did not cover medical or epidemiological journals. Further, her focus is on life events and chronic strains, rather than daily hassles. Thoits chooses to use the broad definition of stress by Holmes and Rake (1967), that includes, " . . .any environmental, social, or internal demand which requires the individual to readjust his/her usual behavior patterns." (p.56) Hence, a "stress reaction" would be a physiological or emotional state of arousal that normally results from the perception of stress or demand. Stress is not necessarily negative as it can motivate efforts to cope. However, as also discussed by other researchers, (see Brunner & Marmot, 1999; Kawachi & Berkman, 2001), as stress accumulates, the ability to cope can be overtaxed, impacting physical and/or psychological well being. The three types of stressors identified in the literature are: 1) [negative] life events-acute changes that require major behavioural readjustment within a short period of time, (e.g., divorce); 2) chronic strains (e.g., poverty; disabling injury); and 3) daily hassles- mini-events that require small behavioural readjustments during the course of a day, (e.g., traffic jams). Research, as cited by Thoits, consistently demonstrates that negative or threatening life events that were highly disruptive precipitate psychological distress and more serious forms of psychiatric disorder (e.g., anxiety and depression). The impact of chronic strains has been studied less frequently than life events. Nonetheless, the literature consistently reports that strains are also damaging to both physical and mental health. However, findings differ as to whether negative life events or chronic strains are more predictive of physical and mental health 51 problems. The contradictory findings may be due to the different ways events and strains have been measured across studies. Thoits describes as seminal the work of Pearlin (1989) that located individuals' experiences of ongoing strains and negative events within their social roles, which are, in turn, products of socio-culfural stratification by gender, race, and social class. Others, (e.g., Mirowsky & Ross, 1989) have pointed to structural powerlessness, alienation and lack of control as consequences of social stratification. Yet, Thoits' literature review finds a paucity of research examining the links between macro-level factors and micro-level experiences. Coping resources art social and personal characteristics that people may draw on when dealing with stressors. The two coping resources most frequently studied by sociologists are: 1) internal or external locus of control orientation (sense of control or mastery over life) and 2) self-esteem. On the other hand, coping strategies consist of behavioural and/or cognitive attempts to manage situational demands. They can include problem and emotion-focused strategies. A s discussed by many others, perceived control over life circumstances is inversely distributed by social status and by disadvantaged groups (i.e., gender, minority groups). Research shows that people tend to use multiple coping tactics for both life events and ongoing strains (Thoits, 2001). The more severe the strain, the greater the number of tactics used. Some coping strategies, (such as denial or alcohol use), have been found to be beneficial in the short term, but have deleterious consequences over the long-term. Appropriate coping strategies are likely stress-type related (hence, variable given the situation). 2.8 Social Relationships and Heal th As mentioned in the discussion of stress and coping, there is increasing evidence of a causal link between social support and health. Recent developments in research that interpret and explain the casual relationships between social relationships and health include: 1) the emergence of 52 theoretical models to test the causal relationship of social relationships on health in both humans and animals; 2) the culmination of empirical evidence that social relationships are a consequential predictor of mortality in human populations; and 3) increasing evidence for the causal impact of social relationships on psychological and physiological functioning in quasi-experimental and experimental studies of humans and animals (House, Landis, & Umberson, 1999). It is postulated that the culmination of this evidence suggests that a lack of social relationships constitutes " . . .a major risk factor for health- rivalling the effects of well-established health risk factors..." such as smoking, blood pressure, and obesity. There is a history of work on "social support" as the mechanism that maintains or sustains health by promoting adaptive behaviour or neuroendocrine responses in the face of stress or other health-hazards. While the rapid growth in social support literature between 1976 and 1981 held several limitations regarding the establishment of causal relationships, House et al. (1999) argue that many concerns have now been addressed with prospective mortality studies in human populations and a broadening base of laboratory and field experimental studies of humans and animals. Among prospective mortality studies of human populations, House and colleagues, discuss key research such as the Alameda County Study by Berkman and Syme that found persons who were low on an index of social networks were twice as likely to die as persons high on the index. The major limitation of the Alameda County Study according to House et al., is the lack of non-self-report data for health at baseline. Lucki ly , the principal author (House, 1999), was able to point to his own replication study in Tecumseh that addressed these shortcomings, as well as the Evans County Study (Shoenback et al.) that also predicted higher mortality with lower social networks- with stronger effects for males than females. This gender difference is a common finding among social support and health studies. Internationally, the authors find support from studies conducted in Sweden and Finland. In all, these studies are reported by House, Landis and Umberson (1999) to have relatively 53 consistent findings supporting the beneficial impact of social integration on age adjusted mortality rates. Some unexplained variation remains in sex and urban-rural differences, though they are speculated upon. For example, being married is consistently shown to be more beneficial to men's health, and becoming widowed more detrimental for men than women. Women, however, seem to benefit more than men from relationships with friends and relatives. These findings have relevance to transitions to adulthood as we see delays in marriage and increased mobility among young people. As a result, there may be decreased benefits from having a spouse for men, and increased difficulty in deriving supports from friends for both men and women with their increased mobility. Prospective mortality studies of human populations have grown in congruence with the findings of experimental and quasi-experimental research. House et al. (1999) cite evidence that the presence of a familiar member of the same species buffers the impact of experimentally induced stress on ulcers, hypertension, and neurosis in rats, mice and goats respectively; and reduces anxiety in humans. Clinical and laboratory data show that the presence of, or physical contact with, another person can moderate human cardio-vascular activity and reactivity in general, and in stressful contexts such as intensive care units. These processes have even been found to work across species. For example, petting by humans, or even their presence, reduces cardiovascular stress among dogs, cats, horses, and rabbits. Berkman (2000) stresses the evidence for, and significance of, social support, networks, cohesion and their impacts on health. She provides data comparing fifteen studies, the majority of which are community-based prospective studies, looking at the outcome of all-cause mortality in relation to social support (e.g., the Alameda County study by Berkman and Syme; Tecumseh, Michigan study by House et al., Evans County study by Shoenback et al.; and North Karelia Finland study by Kaplan et al.). Berkman also presents her study of patients among older people living in a community-dwelling in New Haven, C T , who just had a myocardial infarction (MI). 54 A multiple logistic regression analysis incorporating all significant bivariate effects, and controlling for covariates, found people who had no emotional support were almost three times as likely to die in the six-month follow-up period compared to people who had a lot of emotional support (OR 2.9, CI 1.2-6.9). Berkman (2000) demonstrates how relationships are important to health in ways beyond their capacity to provide support. Evidence now supports that the degree to which an individual is embedded in a social network and belongs to a community are related to health status. Here again Berkman describes findings from her work with Syme, the often-cited Alameda County nine-year prospective study that found that those who lack social ties were about two to three times as likely to die from all causes (including heart disease, stroke and cancer) in the follow-up period as people who had many sorts of contacts. Controlling for behavioural factors only accounted for a small part of the variance. One limitation of the Alameda county study was that at baseline health status relied only on self-report. Subsequent studies without such limitations have supported Berkman and Syme's findings in other communities. In fact, Berkman cited dozens of studies that demonstrated aspects of social relationships that are related to some form of health risk. ' This dissertation wi l l not look at the relationship between social support and health per se, but at social support and health help-seeking with a particular focus on young adults as compared to other life course stages. This focus is taken as young adults are hypothesized to be in a phase where social support systems are changing, and the awareness of trends over time that find young adults spending a longer period of their life out of their parental home and being single longer. With fewer young adults l iving with close social ties they may not have the benefit of those social ties (i.e., parents or spouse) who have greater time with them to observe their health, legitimize their sickness, and encouragement to seek medical care. 55 2.9 Summary Health care is important to individual and population health. Primary care from physicians and other service providers and equitable access to care are foundational to the Canadian health care system. Adolescence and young adulthood are distinct phases or periods in the life course with specific characteristics that may lead to increased experiences of missing needed health care. Youth are generally considered healthy, yet this might be misleading when interpreting their unmet health care needs. It is important to look at the need for care in the contexts of health risk behaviours, sexual and mental health specific to youth. Furthermore, the relationship between social support and health may be significantly related to missed care for young adults, as young adulthood is a time of great upheavals in geographic (re)location, changes in living partners (e.g., parents, friends/roommates, significant others and children), changes in school and/or work environments, proximity to friends and peers, and who most of their time is spent with. 5 6 3.0 METHODS 3.1 Study design This study explores the relationships among stage of the life course and other demographic context variables and access to primary health care in Canada. This study tests hypotheses and develops models using the cross-sectional data from the Canadian Community Health Survey ( C C H S , Cycle 2.1). The models developed explore the relationships among age, sex, diverse demographic context variables, especially those that relate to the transitions to adulthood, and the utilization of primary care and the reporting of missed care. Concepts of predisposing, enabling and need from Andersen's (1995; Aday & Andersen, 1975) model for access to medical care are incorporated into this analysis along with social support to predict missed care. In particular, predisposing factors include sex, immigrant status, and age3. Andersen would have also included 'marital status', 'education' and 'country of birth'. However, 'marital status' is highly correlated to ' l iving arrangement', which is incorporated into this model under social support. Rather than 'education' this model includes job status under social support as it is more related to the transitions to adulthood than level of education achieved. Enabling factors included in the model are 'income adequacy' 4, 'having prescription drug insurance', 'having a regular physician', and ' l iving in a rural or urban area'. Andersen would have included community-level variables related to distance from health care facility, but these are unavailable in the C C H S data. Need is measured by 'self-reported health status'. Andersen also included a variable on stress or emotional health status. The questions on stress in the C C H S were only asked a small sub-sample of the C C H S and emotional health status was too highly correlated with self-reported health status to be included in the final model. A final construct of social support is included in 3 Note: Age was run both in age groups as presented here, and as a continuous variable-not presented here. 4 Note: Total personal and total household income were also run. Income adequacy was chosen for two reasons. First, income adequacy has a higher response rate than other income questions. Second, income adequacy accounts for both household income and size of the household. Thus, a young person who may have a lower personal income but benefits from living in a household with parents with a higher income could be distinguished from a young person with a similar person income who lives alone. 57 the model, with ' l iv ing arrangement', 'job status' and 'sense of belonging to a local community'. These were added as the final step in the nested logistic regression model as they are related to aspects of young adulthood that might impact social factors affecting access to care. Particular critical attention is paid to 'missed health care'- to the types of care missed and the reasons given for missed care. Patterns of missed care and primary care utilization for different stages in the life course, gender and other socio-demographic characteristics are uncovered. This analysis allows for theory building and testing, and linking theory to data. Hypotheses, research questions, information on the data set, and analysis are described below. 3.1.1 Research Questions and Hypotheses Young adulthood is a phase of the life course that follows adolescence and includes many variously sequenced and timed transitions. Specifically, these transitions are: • from family of origin to independence and/or to creation of a new family unit; • from secondary school to higher education and/or paid employment; • changes in residence (location and cohabitants); and • changing social patterns from family to peers, and then to romantic partner. The process of transitioning to adulthood may cause a disruption of childhood and adolescent patterns of health care utilization through changes of residence location (migration), cohabitation, methods of health care access, and fewer health guardian influences (encouraging healthy behaviours including accessing timely and appropriate health care; most commonly the role of the mother in a family). With the transitions to adulthood there are often significant changes in the number and continuity of an individual's roles and relationships with and within institutions (i.e., education, workplace, the health care system), that may make knowledge and navigation of services such as health care more difficult. Also , some who had extended health care coverage through their parents' plans may find themselves with no extended health coverage for the first time. These disruptions may cause young adults to report higher levels of 58 missed health care than other age groups. With the many changes during young adulthood that occur as transitions to adulthood take place, there may also be a lower sense of belonging to a local community, that may be linked to feelings of isolation and anomie, less knowledge and fewer information sources about accessing health care. Research questions: 1. Who reports missed care in Canada? 2. What are the relationships among stages in the life course, predisposing, enabling and need factors and social support and the reporting of missed health care? 3. What is the role that life course stages play in the relationships among social support, predisposing, enabling, and need factors? 4. What kinds of health care are Canadians reporting they missed? 5. What reasons are provided for missing health care and how do the reasons vary by life course stage and other socio-demographic characteristics? 6. Who accesses primary health care and what is the relationship between health care access and reporting missed care? Hypotheses statements: H I : Young adults w i l l report more missed care than other age groups. Ho: There wi l l be no significant difference between the different life course stages and missed health care. H 2 : Social support, predisposing, enabling and need factors wi l l each be associated with missed care. Ho: Social support, predisposing, enabling, and need factors w i l l not each be associated with missed care. 59 H3: Age wi l l not remain a significant predictor of missed health care when controlling for social support, predisposing, enabling, and need factors. Ho: Age wi l l remain a significant predictor of missed health care when controlling for social support, predisposing, enabling, and need factors. H4: Life course stage w i l l affect the relationships among predisposing, enabling, need and social support factors and missed care. Ho: The relationships among predisposing, enabling, need and social support factors and missed care w i l l not be affected by life course stage. H5: Life course stage wi l l be related to health care utilization and reasons for missed health care. Ho: Life course stage wi l l not be related to health care utilization and reasons for missed health care. 3.1.2 Data Set: The Canadian Community Health Survey Cycle 2.1, 2003 The Canadian Community Health Survey (CCHS) is a national cross-sectional survey that collects information on the health and related socio-economic data of the Canadian population, aged 12 and older who are l iving in private dwellings. People l iving on Indian reserves, residents of institutions, full-time members of the Canadian Armed Forces, and residents of certain remote regions are excluded. The survey is administrated by Statistics Canada and the Canadian Institute for Health Information (CIHI). Data for the survey is collected in two-year cycles. Data for C C H S Cycle 2.1 was collected between January and December 2003, and was released in June 2004. The C C H S Cycle 2.1 covers approximately 98% of the Canadian population aged 12 or older. In total, and after removing the out-of-scope units, 166,222 households were selected to 60 participate in the C C H S Cycle 2.1. Out of these selected households, a response was obtained for 144,836 which results in an overall household-level response rate of 87.1%. Among these responding households 144,836 individuals (one per household) were selected to participate in the C C H S Cycle 2.1 out of which a response was obtained for 134,072 which results in an overall person-level response rate of 92.6%. At the Canadian level, this would yield a combined response rate of 80.7% for the C C H S Cycle 2.1. ( C C H S Guide, 2005) The survey is designed to provide reliable cross-sectional estimates at provincial, territorial and health region levels. A l l variables were run unweighted and weighted by the master data file weight provided by Statistics Canada. The weighting is designed by Statistics Canada to compensate for the ' complex survey sampling design, allowing for each respondent to represent the number of Canadians they should on key variables of sex, rural or urban dwelling and so on. When weighted, the C C H S 2.1 data results are meant to represent the population of Canada. Only the weighted data results can be released for publication. It is necessary to further account for the complex sampling design when estimating variances (i.e., standard deviation, confidence intervals and regression analyses.) For all bivariate relationships, results were vetted by looking at the Statistics Canada 'Coefficient of Variation' Tables for the Canadian population and for age groups (when applicable). A coefficient of variation is considered acceptable i f it falls between 0.0 and 15.5; marginal i f it falls between 16.6 and 33.3; and unacceptable i f it is over 33.3. N o coefficients of variation were found above 5 in this analysis, with most falling between 2 and 3. A s such, the data is an acceptable inference to the population with acceptable variance estimates. For the regression analysis, the original analysis presented in the tables here were produced using master data file weights adjusted for the sample in SPSS 14.0. The same procedure was then conducted in S U D A A N , incorporating the master weight and the 'bootvar' bootstrap weights (500 weights designed to account for the complex sampling design). A s expected, all odds 61 rations were the same for the analysis from SPSS and the S U D A A N using the bootstrap method, and there were extremely minor differences to the variance estimates (confidence intervals) that had the surprising effect of slightly decreasing the range of the confidence intervals, thus lowering a few of the p-values and increasing the significance on a few variables (particularly related to income adequacy). None of the significant relationships found in the original SPSS analysis had a less significant p-value in the new analysis. In order to err on the side of caution, I have presented the original SPSS analysis with adjusted population weights as they are more conservative estimates of variation (again, the odds ratios reported are identical.) Several variables were recoded for analysis purposes (i.e., to create dummy variables coded 0 and 1 to be used in logistic regression or to create desired reference categories). The C C H S Cycle 2.1 has indicators for the following concepts that are of interest in relation to this study: (provided with their operationalization in this study) 62 CONCEPT INDICATORS OPERATIONALIZATION Socio- Age Continuous age by year (12 and over.) demographics ( D H H C A G E ) Also transformed into various age group categories to facilitate comparisons on cross tabulation tables and to allow for release due to confidentiality constraints. Sex Dichotomous. ( D H H C S E X ) Recoded into dummy variable 'male' where female = 0; male =1. Lives in a rural or Dichotomous. urban area Recoded into dummy variable 'rural ' where ( G E O C D U R 2 ) urban = 0; rural = 1. Immigrant status Dichotomous. ( S D C C F I M M ) Recoded into dummy variable 'immigrant' where 0 = not immigrant; 1 = immigrant Language respondent Derived variable with 7 categories. can converse Recoded into a dummy variable 'language' ( S D C C D L N G ) where 0 = English or French; 1= not English or French Socio- L iv ing arrangement Derived variable. demographics ( D H H C L V G ) l=unattached alone; 2=unattached other; related to the 3=spouse/partner; 4=parent spouse child; transitions to 5=parent child; 6=child parent; 7=child parent adulthood sibling; 8=child 2 parent; 9=child 2 parent sibling; 10=ofher. Recoded into ' l iv ing arrangement 7' where 1-5 is the same as above, 6=other, and 7= all child variables. Marital status Categorical. l=now married, 2=common-law, ( D H H C M S ) 3=widowed, 4=separated, 5=divorced, 6=single Currently attending Dichotomous. Recoded into dummy variable school/college/univer 'student' where 0=not in school; l=in school sity (SDCC_8) Total personal Continuous. income ( I N C C 4) 11 income categories ( I N C C D P E R ) Income adequacy l=lowest; 2=lower middle; 3=middle, 4=upper ( INCCDIA5) middle, 5=highest. Also recoded into 'reinccdia5' where coding was reversed. Worked at a job in Dichotomous. Recoded into dummy variable the last year 'job' where l=no job; 0=job (GENC_08) Sense of belonging to l=very strong a local community 2=somewhat strong (GENC_10) 3=somewhat weak 4=very weak 63 CONCEPT INDICATORS OPERATIONALIZATION H e a l t h s t a t u s S e l f - p e r c e i v e d h e a l t h L i k e r t - s c a l e . l = e x c e l l e n t , 2 = v e r y g o o d , S t a t u s 3 = g o o d , 4 = f a i r , 5 = p o p r ( G E N C 0 1 ) H e a l t h c a r e N u m b e r o f C o n t i n u o u s . R e c o d e d i n t o 7 r e s p o n s e c a t e g o r i e s a c c e s s c o n s u l t a t i o n s w i t h ' n o d r v i s i t ' w h e r e 0 = 0 , 1 = 1 , . . . 7 = 7 o r m o r e . f a m i l y d o c t o r i n t h e p a s t y e a r ( H C U C _ 0 2 A ) H a s a r e g u l a r m e d i c a l D i c h o t o m o u s . R e c o d e d i n t o d u m m y v a r i a b l e d o c t o r ' n o d r ' w h e r e l = n o r e g u l a r d o c t o r , 0 = r e g u l a r . ( H C U C _ 1 A A ) d o c t o r . H a s p r e s c r i p t i o n D i c h o t o m o u s . R e c o d e d i n t o d u m m y v a r i a b l e h e a l t h i n s u r a n c e ' p r e s c i n ' 0 = y e s i n s u r a n c e , l = n o i n s u r a n c e . ( I N S C 1) M i s s e d h e a l t h S e l f - p e r c e i v e d u n m e t D i c h o t o m o u s . R e c o d e d i n t o d u m m y v a r i a b l e c a r e h e a l t h c a r e n e e d s ' m i s s e d c a r e ' w h e r e l = m i s s e d c a r e , 0 = n o ( H C U C 0 6 ) m i s s e d c a r e . R e a s o n f o r u n m e t S e v e r a l d i c h o t o m o u s v a r i a b l e s . c a r e ( H C U C _ 0 7 A - N ) T y p e o f c a r e n o t D i c h o t o m o u s v a r i a b l e s f o r : p h y s i c a l h e a l t h r e c e i v e d p r o b l e m s , e m o t i o n a l p r o b l e m , r e g u l a r c h e c k u p , ( H C U C 0 8 A - E ) c a r e o f i n j u r y , o t h e r . 3.1.3 Data Analysis A n a l y s i s o f t h e C C H S d a t a s e t s w a s d o n e i n t h r e e s t a g e s . S t a g e o n e w a s e x p l o r a t o r y d a t a a n a l y s i s o f t h e p u b l i c u s e d a t a s e t o f C C H S C y c l e s 1.1 a n d 2 . 1 . T h e p u b l i c u s e d a t a s e t a l l o w e d f o r d e s c r i p t i v e a n a l y s i s a n d b i v a r i a t e c o r r e l a t i o n s . H o w e v e r , i t d i d n o t a l l o w f o r a c c u r a t e s a m p l i n g e r r o r e s t i m a t e s . T h u s , i n o r d e r t o c o n d u c t m u l t i v a r i a t e a n a l y s i s , a c c e s s t o t h e f u l l C C H S 2 . 1 d a t a s e t w a s r e q u i r e d . A l s o , m a n y o f t h e v a r i a b l e s o f i n t e r e s t s u c h a s a g e a r e g r o u p e d c a t e g o r i c a l v a r i a b l e s i n t h e p u b l i c u s e d a t a , b u t t h e y a r e a v a i l a b l e i n t h e i r o r i g i n a l c o n t i n u o u s f o r m a t w i t h t h e f u l l d a t a s e t . T h e s e c o n d s t a g e i n v o l v e d a c c e s s i n g t h e d u m m y f u l l d a t a s e t f o r C C H S C y c l e 2 . 1 . T h e d u m m y d a t a s e t p r o v i d e d b y S t a t i s t i c s C a n a d a i n c l u d e s a l l o f t h e v a r i a b l e s ( s o m e t h a t w e r e n o t a v a i l a b l e i n t h e p u b l i c u s e d a t a s e t ) , a n d v a r i a b l e s s u c h a s a g e a r e n o l o n g e r g r o u p e d . H o w e v e r , t h e d u m m y d a t a s e t d o e s n o t h a v e t h e a c t u a l d a t a , b u t r a n d o m l y g e n e r a t e d r e s p o n s e s t h a t 6 4 correspond to the response categories for the variables in question. This dummy data set is created by Statistics Canada to allow for exploration of the data and planning of analysis while protecting the confidentiality of respondents. In stage two, univariate, bivariate and multivariate analysis was conducted until the syntax for the needed analysis was developed and refined. Next, access the full data set was needed to continue conducting analysis. In stage three, a successful application to access the C C H S Cycle 2.1 through the British Columbia Research Data Centre ( B C R D C ) was made, and final analysis was conducted through the B C R D C premises at the University of British Columbia. A l l analysis was vetted for confidentiality before release by the B C R D C staff. A l l analysis at the B C R D C was conducted using Statistical Package for the Social Sciences (SPSS) 14.0 and the logistic regression analysis was also conducted in S U D A A N to incorporate the 'bootvar' bootstrapping weights. Analysis of the P U M F and dummy data sets was conducted with SPSS 12.0. Analyses performed include: descriptive statistics, bivariate correlations and cross-tabulations, and multiple logistic regression modeling. Descriptive analysis was undertaken to explore all of the variables in the analysis. Missing data, distribution, measures of centre and spread, interquartile ranges, standard deviations, means, medians, and modes were analyzed as appropriate for given variables of interest. This analysis provided information on the prevalence of reported missed care, socio-demographic characteristics, and other concepts integral to analysis. A l l variables were run unweighted and weighted by the master data file weight provided by Statistics Canada. The weighting is designed by Statistics Canada to compensate for the complex survey sampling design, allowing for each respondent to represent the number of Canadians they should on key variables of sex, rural or urban dwelling, and so on. When weighted, the C C H S 2.1 data results are meant to represent the population of Canada. To account for any sampling design effects on estimates of variation (i.e., standard deviation), the Coefficient of Variation ( C V ) Tables were 65 examined. None of the results had a C V score over 5, and are thus at the high level of acceptable according to Statistics Canada. Several variables were recoded for analysis purposes (i.e., to create dummy variables coded 0 and 1 to be used in logistic regression). When variables were recoded, descriptive frequencies were run on the original and recoded variables to ensure their consistency. Bivariate correlations were run to establish if there were statistically significant relationships between variables of interest. Tests of significance and measures association were run for each pairing, using appropriate testing based on whether the dependent and independent variables were nominal, ordinal, interval or ratio. Scatterplots were run where appropriate. Bivariate correlations are primarily presented in cross-tabulation tables with corresponding Chi-square p-values to establish statistical significance and measures of association (e.g., Eta; Pearson's r) to assess the strength (and direction for some) of the associations. Issues of data weighting and assessing coefficients of variation are discussed above in section 3.1.2. To account for any sampling design effects on estimates of variation, the Coefficient of Variation (CV) Tables were examined. None of the results had a C V score over 5, and are thus at the high level of acceptable according to Statistics Canada. j Multiple logistic regression was used to predict the dependent variable, missed health care on the basis of independent variables and to determine the percent of variance in missed care explained by the models. Logistic regression assesses the relationship between one categorical dependent variable and several independent variables that can be both categorical and continuous. This logistic regression allows for the ranking of the relative importance of different independent variables, to assess interaction effects and to understand the impact of covariate control variables. Moreover, several nested models were run, in order to assess which model is better for predicting missed health care. 66 Logistic regression applies maximum likelihood estimation after transforming the dependent into a logit variable (the natural log of the odds of the dependent occurring or not). In this way, logistic regression estimates the probability of a certain event occurring. Logistic regression calculates changes in the log odds of the dependent, not changes in the dependent itself (as we would find in Ordinary Least Squares Regression (OLS)). It is important to remember that unlike O L S , logistic regression does not assume linearity of relationship between the independent variables and the dependent, does not require normally distributed variables, does not assume homoscedasticity, and in general has less stringent requirements. It does however require that observations are independent and that the logit of the independent variables is linearly related to the dependent. Since age was not linearly related fo missed care, several techniques were tested. First, age was divided into five categories. The division of age categories was also done for deductive reasons. Specifically, age was divided theoretically based on life course stages where adolescence refers to 12-17 year olds, emerging adults are 19-30, adults are 31-50, older adults 51-64, and seniors are 65 and older. Nineteen was a good cut-off age for the stage of young adulthood in this analysis from inductive reasons as well as the analysis found the shift in higher rates of missed care begins around age 19. The model was run with several different categorizations of age, and also for those aged 21 (where the reporting of missed care peaked) and older with age as a continuous variable to confirm the significance and strength of the relationship between age and missed care when controlling for other factors. For the multiple logistic regression, three models are presented (though several other models were run to establish consistency in findings). The dependent variables is missed care, a dichotomous variable, coded as a dummy variable where 0 = no missed care reported and 1= missed care reported. Independent variables were selected to represent predisposing, enabling, and need predictors (Aday & Andersen, 1975; Law et al., 2005) for missed care and socio-demographic characteristics related to the transitions to adulthood and social support. The model 67 was then run again for each of the different age groups, excluding age as an independent variable. The complex sampling method used by Statistics Canada required that the logistic regression be weighted by the master weight divided by the average of the master weight in order to correctly calculate the variance estimates ( C C H S 2.1 Guide, 2005, p.51). [Note from section 3.1.2 that the analysis was also conducted using S U D A A N in order to incorporate the population weight and the 'bootvar' bootstrap method to account for the sampling design. Odds ratios were the same, and the only difference observed was that a few of the odds ratios has increased in significance. Hence, the more conservative SPSS results were presented). Due to the analysis weighting, the n (number of cases) for the logistic regression procedure is the size of the sample less the number of cases with missing data (not the population of Canada). The percent of missing cases is 30%, primarily due to lower response rates for the income adequacy variable. Results for the logistic regression are presented with odds ratios and p-values. Confidence intervals were run, but are not included in the tables. A separate table with odds ratios and p-values is presented for simplicity. Intercorrelations were examined to check for multicolinearity, and none were found at 0.7 or higher. Observed and expected values on the Hosmer Lemeshow Test were also checked and no concerns were found. The models tested variables related to: 1) predisposing factors (i.e., age, gender, being an immigrant to Canada, not being able to speak English or French) 2) enabling factors (i.e., income adequacy, prescription drug insurance, having a regular physician, and l iving in a rural or urban area), 3) need (self-reported health status), and 4) social support (i.e. l iving arrangement, job status, and sense of belonging to a local community) as they may be associated with the reporting of missed care. 68 4.0 RESULTS Results of the analysis of the C C H S data w i l l be presented in several sections. First, a general overview of the demographic characteristics of the population and of young adults in Canada are presented (See section 4.1). Section 4.2 explores who reports missed health care in Canada, first by looking at bivariate relationships between life course stage, social support, predisposing, enabling, and need factors with missed care. This is followed by the presentation of nested multiple logistic regression models predicting missed health care. Section 4.2 also presents the final multiple logistic regression model run for each life course stage, allowing for comparison of the different relationships and differences related to life course stage. Section 4.3 describes the kinds of health care people report missing, and the reasons they provide for having missed care.. As the variable 'not having a regular physician' turned out to be such a significant predictor of missed care, this section also explores the relationships between socio-demographic characteristics and having a regular physician. Since earlier analysis indicated questions regarding the meaning of missed health care, section 4.4 looks at who accesses primary health care and what the relationship between health care access and reporting of missed care is. Results are presented in tables and text. A s the sample size was so large, almost all results are statistically significant. A s such, findings that have a larger effect size are addressed more than those with smaller effect sizes. However, because of theoretical interests, from time to time there is also discussion of other findings, even i f effect sizes are smaller. Thus both empirically significant and theoretically interesting findings are highlighted. 4.1 Demographic Characteristics of the Population and Young Adults in Canada This section describes characteristics of the Canadian population from analysis of the Canadian Community Health Survey (CCHS) Cycle 2.1 Master File data. The demographic data are presented weighted for the Canadian population, aged 12 and over, in accordance with the 69 directions of Statistics Canada for the C C H S Cycle 2.1. From Table 4.1.1 (see below), we see that approximately half of Canadians are male (50.7%), and half are female (49.3%). No alternate categories for sex, (i.e., transgendered) were provided. A t the time of the survey, the majority of Canadians (aged 12 and over) were between the ages of 31 and 50 (37.1%), 7.6% were between ages 26 and 30, and 12.7% were aged 18 to 25. There are six categories for marital status that recognized common-law relationships as a separate category. Fifty percent of Canadians are married, while 8.4% are in common-law relationships. Five percent are widowed, 2.3% are separated, and 4.4% are divorced. Another 30% of Canadians aged 12 and over are single (meaning they have never been married and are not living in common-law arrangements.) See table below for demographic characteristics: 70 Table 4.1.1 Demographic Characteristics of the Population (Weighted, Canadian Community Health Survey, 2000/2001)* Characteristic n % Missing % Age at time of survey 0 12-17 2519272 9.5 18-25 3381643 12.7 26-30 2028747' 7.6 31-50 . 9869794 37.1 51-64 4993526 18.8 65 and over 3785145 14.2 Sex 0 Male 13090301 49.3 Female 13487827 50.7 Marital Status • 0.2 N o w Married 13256792 50.0 Common-Law 2225029 8.4 Widowed 1328956 5.0 Separated 597973 2.3 Divorced 1168903 4.4 Single 7958028 30.0 T O T A L 100 Income (total personal) 19.5 No income • 1217108 5.7 < $5000 1336270 6.2 $5000-9,999 1781763 8.3 $10,000-14,999 2267857 10.6 $15,000-19,999 1668229 . 7.8 $20,000-29,999 3233053 15.1 $30,000-39,999 3001097 14.0 $40,000-49,999 2169123 10.1 $50,000-59,999 1582332 .7.4 $60,000-79,999 1769612 • 8.3 $80,000or more 1380961 6.5 T O T A L 100 Immigrant Status 3.2 Yes 5302773 20.0 N o 20421274 76.8 Rural/Urban 0 Urban 21572113 81.2 Rural 500614 18.8 Can converse in French 3.0 or English Yes 25257487 95.0 N o 522033 2.0 *note: N of sample = 134,072 There are several variables in the C C H S Cycle 2.1 that measure income, including both personal and household income. In the table above we see the breakdown of total personal income from all sources in eleven monetary categories. Another measure provided in the C C H S is income adequacy (a measure that is derived from household size and household income) that is divided into five categories.5 Income adequacy is useful to assess wealth as some individuals in a household have a lower income (such as older children who still live with their parents, or a spouse who is not in the labour force), yet they still have the advantages of l iving in a household where other members of the household contribute to household income. Further, income adequacy has a lower number of missing cases than other income variables. For income adequacy, 2.9% of Canadians fall into the lowest category, 6.2%> are in the lower middle, 19.8% of Canadians are in the middle, 34.4% are in the upper middle, and 36.7% are in the highest income adequacy category. Other important characteristics include whether people live in rural or urban areas, i f they are immigrants to Canada, and i f they can speak English or French. We find that 81.2 % of Canadians live in urban areas, while 18.8% are classified as l iving in rural areas. Immigrants account for 20.6% of Canadians, and only 2% of Canadians report not being able to speak English or French. 6 When comparing income adequacy for immigrants, 12.1% of immigrants to Canada are in the lowest and lower middle income adequacy groups. Meanwhile 24.4% are middle, 32.8% are upper middle and 30.8% are in the highest income adequacy group. Overall, a higher proportion of immigrants are represented in the lower two income adequacy groups than 5Note: Lowest income adequacy includes households with less than $10,000 a year with 1-4 people, and less than $15,000 a year if 5 or more people; lower middle income refers to 1-2 person households earning $10-14,999; 3-4 persons earning $10-19,999, and 5+ earning $15-29,999; middle income refers to 1-2 person households earning $15-29,999, 3-4 persons earning $20-39,999, and 5+ households earning $30-59,999; Upper middle income includes 1-2 persons earning $30-59,999, 3-4 persons earning $40-79,999, and 5+ earning $60-79,999; and highest income includes 1-2 persons earning more than $60,000 and 3+ earning more than $80,000 6 Note: CCHS was conducted in several languages; where necessary, Statistics Canada found local translators, and the survey was also translated into Chinese, Punjabi, Cree and Inuktitut. Although CCHS was conducted in several languages, those with a language barrier were less likely to be surveyed. (Quan et al., 2006) 72 non-immigrants (12.1% vs. 8.3% non-immigrants; while there is a lower proportion of immigrants in the middle, (24.4% immigrants; 16.6% non), upper middle (32.8% immigrants; 34.8 non) and highest (30.8% immigrants; 38.3% non) income brackets. Characteristics of Young Adults in Canada Since this dissertation examines access to health care with a particular interest in young adults, it is important first to explore young adulthood in Canada. This section wi l l explore the status of young adults with respect to marital status, living arrangements, income, jobs, enrolment in education, and their sense of belonging to a community in comparison with other stages of the life course. In terms of marital status, 66% of young adults aged 18-30 are single, 19.1% are married, and 12.6% are in common-law relationships (see Table 4.1.2). The highest percentage of common-law relationships is found in 18-30 year olds. Related to marital status is living arrangement (see table 4.1.3). A surprisingly high percentage, 40% of young adults aged 18 to 30 (when looking at 18 to 25 year olds the percentage increases to 55.7%), live with one or both parents. Meanwhile 13.1% of 18-30 year olds are unattached living with another person. Almost 10% of 26-30 and 31-50 year olds live alone. Table 4.1.2 Age In Four Categories B y Marital Status (Percentages) Marital Status N o w Common- Widowed Separated Divorced Single Total married law Age in Adolescent 0.0 0.2 0.0 0.0 0.1 99.7 100 Four 12-17 Groups Younger Adults 18-30 19.1 12.6 0.1 1.2 0.6 66.4 100 Adults 67.1 10.0 1.8 3.2 6.5 11.4 100 31-64 Seniors 60.1 1.6 28.0 1.5 4.5 4.2 100 65 and over Total 50.0 8.4 5.0 2.3 4.4 30.0 100 Chi-square p O . O O l ; Lambda 0.382, pO.OOl 73 Table 4.1.3 Age In Six Categories B y Liv ing Arrangement (Percentages) Living Arrangement Unatt Unatt Spouse Parent Parent Child Child other Total ached ached partner spouse child parent with 2 alone other child w/wout siblings parents w/w/out siblings Age in Adolescents 0.1 1.9 0.0 0.0 0.0 16.1 71.6 10.3 100 Four 12-17 Groups Younger adults 18-30 6.8 13.1 13.4 13.5 1.9 7.9 32.1 11.3 100 Adults 11.1 3.5 25.5 44.5 4.7 1.4 1.4 7.9 100 31-64 Seniors 28.6 2.8 51.5 6.0 4.3 0.1 0.0 6.8 100 65 and over Total 11.7 5.2 24.4 28.5 3.6 3.9 14.1 8.6 100 Chi square p< 0.001; Lambda 0.239, p O . O O l A s we can see below, (Table 4.1.4) marital status and living arrangement are highly correlated. O f interest are the 16% of singles who live unattached alone, while another 13.8% live unattached with others. Table 4.1.4 Marital Status by L iv ing Arrangement Martial Status Liv ing Arrangement N o w married Common law - Widowed Separated Divorced Single Total Unattached 0.7 0.7 67.4 36.1 49.8 16.0 11.6 Alone Unattached other 0.3 0.7 4.8 9.0 9.7 13.8 5.2 Spouse/partner 40.1 49.9 0.4 1.3 1.6 0.4 24.4 Parent spouse 50.6 37.1 0.0 1.0 0.9 0.1 28.5 child Parent child 0.2 0.1 16.4 36.2 23.9 2.6 3.6 Chi ld parent 0.0 0.1 0.3 2.4 2.8 12.3 3.9 w/w/out siblings Chi ld 2 parents 0.1 0.5 0.2 3.0 1.7 46.1 14.1 w/w/out siblings other 7.9 10.8 10.5 11.1 9.5 8.6 8.6 Total 100 100 100 100 100 100 100 Chi-square p O . O O l ; Lambda 0.538, p O . O O l (Marital Status Dependent) Income in Canada is correlated with age. (Note that in table 4.1.5, an increased number of age categories is used to demonstrate the variation of income adequacy by age with increased sensitivity.) The age group with the second highest percentage falling in the lowest income 74 adequacy (4.3%) is 20-24 year olds, preceded by those aged 60-64 years (see Table 4.1.5). Meanwhile young people under thirty and especially the elderly are least likely to have the highest income adequacy. Those who are married and common-law are far less likely to be in the lowest or lower middle income adequacy groups than other marital statuses. Those widowed, separated or divorced have the greatest likelihood of being in the lowest and lower middle income adequacy groups. Among those who are single, (which is primarily adolescents and younger adults, see table 4.1.2), almost 5% are in the lowest, 7.5% are in the lower middle, and 20.2% are in the middle income adequacy groups. Thus, those who are single, widowed, separated or divorced have lower income adequacy compared with those who are married or common-law. The distribution of income adequacy by living arrangement is very telling. Those who live alone, live with roommates (unattached with others) and single parents are far more likely to be in the lowest and lower middle income adequacy groups. Conversely, households where there is a married couple are most likely to be in the highest income group (Table 4.1.5). 75 Table 4.1.5 Age, Marital Status and L iv ing Arrangement by Income Adequacy Income Adequacy Lowest Lower middle Middle Upper middle Highest Total Age Adolescents 12-14 3.4 9.0 22.4 31.9 33.6 100 15-19 3.8 6.4 21.2 31.4 37.2 100 Younger 20-24 4.3 7.1 20.0 32.4 36.2 100 Adults 25-29 3.0 5.5 18.9 34.8 37.8 ' 100 Adults 30-34 2.4 4.8 17.1 35.6 40.1 100 35-39 2.1 5.1 17.1 34.9 40.8 100 40-44 2.3 4.6 16.2 35.0 42.0 100 45-49 2.7 4.5 13.0 34.9 44.9 100 50-54 2.6 3.8 13.3 32.8 47.6 100 55-59 3.1 4.5 15.2 34.6 42.5 100 60-64 4.7 5.7 22.1 39.2 28.4 ' 100 Seniors 65-69 2.0 9.5 33.3 37.5 17.7 100 70-74 1.6 10.8 37.8 36.5 13.2 100 75-79 1.8 13.4 38.0 32.2 14.6 100 80 or more 3.3 17.9 37.5 29.5 11.9 100 years Total 2.9 6.2 19.8 34.4 36.7 100 Chi-square p O . 0 0 1 ; Eta 0.214 Marital Married 1.4 3.4 19.9 35.5 41.8 100 Status . Common-law 1.3 4.6 15.9 36.5 41.7 100 Widowed, 5.7 16.8 30.2 31.4 15.9 100 separated, divorced Single 4.9 7.5 20.2 33.0 34.5 100 Total . 2.8 6.2 19.8 34.4 36.8 100 Chi-square p O . 0 0 1 ; Eta 0.245 Liv ing Unattached 8.6 16.2 28.2 33.3 13.7 100 Arrangement alone Unattached 6.0 9.4 21.9 31.6 31.1 100 other Spouse/partner 1.3 2.3 17.1 35.2 44.1 100 Parent, 1.2 4.2 1.6.4 37.3 .. 40.8 100 spouse, child Parent child 4.6 15.5 28.8 35.4 15.6 100 Chi ld , parent, 4.3 9.5 27.6 36.6 22.1 100 sibling Chi ld 2 1.9 3.5 15.2 31.4 47.9 • 100 parents, sibling Other 2.8 6.9 26.0 28.2 36.0 100 Total 2.8 6.2 19.8 34.5 36.7 100 Chi-square p O . 0 0 1 ; Eta 0.312 Income adequacy dependent So, what do young adults do in Canada? Over 90% of young adults aged 18-30 worked a job in the past year, the highest percentage employed for any age group. The next highest is adults aged 31-64 at 82.7% (Table 4.1.6). 34.3% of those aged 18-30 are attending school, college, or . university (Table 4.1.7.). Attending school explains a small percentage of the 34.6% who are living unattached alone who have not worked at a job (Table 4.1.6), but not by much, as only 6.1% of those attending school live alone (Table 4.1.7) (many others l iving alone who do not work may be retired, unemployed but seeking work, or on disability). Table 4.1.6 Age, L iv ing arrangement, arid Marital Status by Worked at Job Worked at a Job Yes N o Total Age Adolescent 12-17 66.9 33.1 100 Young Adult 18-30 90.1 9.9 100 Adult 31-64 82.7 17.3 100 Senior over 65 15.2 84.8 100 Total 77.1 22.9 100 Chi-square p O . 0 0 1 ; Eta 0.494 (Job dependent) Liv ing Unattached Alone 65.4 34.6 100 Arrangement Unattached other 83.1 16.9 100 Spouse/partner 64.5 35.5 100 Parent spouse child 85.5 14.5 100 Parent child 76.2 23.8 100 Chi ld parent w/w/out 81.3 18.7 100 siblings Chi ld 2 parents w/w/out 84.8 15.2 100 siblings other 79.6 20.4 100 Total 77 23 100 Chi-square p O . 0 0 1 ; Eta 0.221 (Job dependent) Marital Status N o w married 74.8 25.2 100 Common-law 87.8 12.2 100 Widowed 26.3 73.7. 100 Separated 77.9 22.1 100 Divorced 73.1 26.9 100 - Single 83.7 16.3 100 Total 77.1 29.9 100 Chi-square p O . 0 0 1 ; Eta 0.240 (Job dependent) Table 4.1.7 Age and L iv ing Arrangement by Currently Attending a School/College/University Currently Attending a School/College/University N o Yes Total Age categories Adolescent 12-17 5.5 94.5 100 Young Adult 18-30 65.7 34.3 100 Adult 31-64 95.9 4.1 100 Senior over 65 99.5 0.5 100 Total 81.6 18.4 100 Chi-square pO.OOO; Eta 0.714 Liv ing Unattached Alone 93.9 6.1 100 Arrangement Unattached other 76.2 23.8 100 Spouse/partner 96.4 3.6 100 Parent spouse child 95.4 4.6 100 Parent child 93.9 6.1 100 Chi ld parent w/w/out 43.3 56.7 100 siblings Chi ld 2 parents 29.8 70.2 100 . w/w/out siblings other 78.7 23.3 100 Total 81.7 18.3 100 Chi-square p<0.001; Eta 0.617 (student dependent) Another factor linked to life course stage may be sense of belonging to a local community. Young adults have much weaker sense of belonging to a local community than all other age groups as 33.6% and 33.5% of 20-24 and 25-29 year olds report somewhat weak sense of belonging respectively, while 13.6% and 11.7% of 20-24 and 25-29 year olds report a very weak sense of belonging to a local community (Table 4.1.8). Only 9.3% of 20-24 year olds report a very strong sense of belonging. In terms of marital status, those in common-law relationships report the weakest sense of belonging to a local community (47% reporting somewhat or very weak), followed by those who are separated (44.4%) and divorced (44.2%) (Table 4.1.8). Those who are unattached living with others report the weakest sense of belonging (48.4% reporting somewhat or very weak), followed by single parents (42.2%) and those who are unattached living alone (40.8%) (Table 4.1.8). 78 Table 4.1.8 Age, Marital Status and L iv ing Arrangement by Sense of Belonging to a Local Community Sense of Belonging to a Local Community Very Somewh Somewhat Very weak Total Strong at strong weak Age Adolescent 19.0 58.5 18.2 4.4 100 12-17 Young Adult 9.9 43.9 34.3 11.9 100 18-30 Adult 16.1 47.7 26.9 9.3 100 31-64 Senior 25.3 45.0 20.5 9.1 100 65 and older Total 16.3 47.6 26.8 9.4 100 Chi-square p O . O O l ; Spearman correlation -0.058, p O . O O l Marital N o w married 18.3 49.4 24.5 7.8 100 Status Common-law 10.8 42.2 35.1 11.9 100 Widowed 25.6 43.2 20.7 10.5 100 Separated 13.6 42.0 30.8 13.6 100 Divorced 14.8 41.0 29.8 14.4 100 Single 13.5 48.2 28.4 9.9 100 Total 16.3 47.6 26.8 9.4 100 Chi-square p O . O O l ; Eta 0.112 Liv ing Unattached 17.5 41.6 28.2 12.6 100 Arrangeme Alone nt Unattached 12.0 39.6 33.3 15.1 100 other Spouse/partne r 18.4 46.5 25.8 9.3 100 I Parent spouse 16.3 50.2 26.0 7.5 100 child Parent child 15.3. 42.5 29.7 12.5 100 Chi ld parent 13.0 48.8 27.9 10.4 100 w/w/out siblings Chi ld 2 15.0 53.3 25.3 6.4 100 parents w/w/out siblings other 15.3 46.6 26.9 11.2 100 Total 16.3 47.5 26.8 9.4 100 Chi-square p O . O O l ; Eta 0.85 (belonging dependent) Overall, we see l iving arrangements for young adults to be a highly variable, yet they demonstrate a relatively distinct stage of the life course. Some young adults live with their 79 parents, others alone or with roommates, while others live with spouses. Reporting being in a common-law relationship is quite common. Young adults tend to have lower income (except for seniors) than those in other life course stages. They are largely employed and/or in school. They are also more likely to have a weak sense of belonging compared with those in other stages of the life course. It is possible that the fewer social supports, generally lower income and instability associated with student life and early employment years may have an effect on whether young adults are more likely to report missed health care. 80 4.2 Who Reports Missed Health Care in Canada? Is Missed Care Related to Age, Social Support, Predisposing, Enabling, or Need Factors? So, who actually misses needed health care in Canada? One way to measure 'missed care' is 'self-perceived missed health care'. In the C C H S 2.1, respondents were asked i f "During the past 12 months, was there ever a time when you felt that you needed health care, but you didn't receive it?" Response categories were yes or no. This section w i l l explore the relationships between four main categories of concepts and the reporting of missed care as well as having a regular family doctor. The four main categories are: 1) predisposing factors (i.e., age, sex, being an immigrant to Canada, not being able to speak English or French); 2) enabling factors (i.e., income adequacy, prescription drug insurance, having a regular physician, and living in a rural or urban area); 3) need (self-reported health status); and 4) social support (i.e., l iving arrangement, job status, and sense of belonging to a local community) as they are hypothesized to be associated with the reporting of missed care. In total, 11.2% of Canadians report having missed care in the last year. The first hypothesis is confirmed as young adults are most likely to report missed care compared to those in all other life course stages (p<0.001) (see Table 4.2.1). [Note that here age is divided into six categories. Theoretically I am interested most in comparing those in the life course stage of young adulthood with other life course stages. However, as discussed in the literature review, emerging adulthood was originally defined by Arnett (1994) as including those aged 18 to 25, and has more recently been amended to include those up to age 30. Thus, I wanted to see both 18 to 25 year olds and compare them to 26 to 30 year olds in relation to the main dependent variable of interest. I also felt that the adult age range of 31-64 was quite broad, and from an empirical 81 p e r s p e c t i v e w e m i g h t c a p t u r e m o r e v a r i a t i o n i f d i v i d e d u p f u r t h e r . H e n c e , f o r t h i s t a b l e , t h e r e a d u l t s a g e d 3 1 - 5 0 a n d o l d e r a d u l t s a g e d 5 1 t o 6 4 . ] T a b l e 4 . 2 . 1 A g e ( 6 C a t e g o r i e s ) a n d R e p o r t i n g M i s s e d C a r e R e p o r t i n g M i s s e d C a r e N o Y e s T o t a l A g e A d o l e s c e n t s 9 3 . 4 6 . 6 1 0 0 1 2 - 1 7 Y o u n g e r A d u l t s 8 5 . 6 1 4 . 4 1 0 0 1 8 - 2 5 Y o u n g a d u l t s 8 5 . 0 1 5 . 0 1 0 0 2 6 - 3 0 A d u l t s 8 7 . 3 1 2 . 7 1 0 0 3 1 - 5 0 O l d e r a d u l t s 9 0 . 0 1 0 . 0 1 0 0 5 1 - 6 4 S e n i o r s 9 3 . 2 6 . 8 1 0 0 6 5 a n d o v e r T o t a l 8 8 . 8 1 1 . 2 1 0 0 C h i - s q u a r e p O . 0 0 1 ; E t a 0 . 0 9 2 F i g u r e 4 . 2 . 1 M i s s e d C a r e b y A g e 16 14 12 • 10 ra n c 8 s u £ 6 4 2 0 14 .4 Missed Care 15 12.7 6.6 12-17 10 6.8 11.2 26-30 31-50 51-64 Age Group 65 + Total S 2 In all , the highest rates of reporting missed care are found among younger and young adults with 14.4% of 18-25 year olds and 15% of 26-30 year olds reporting missed care. This appears to confirm the trend that young adulthood is a distinct phase of the life course that extends beyond age 25 to age 30. The percentage reporting missed care is lowest for adolescents (6.6%). After peaking for young adults, the percentage reporting of missed care steadily lowers with increasing age as 12.7% adults aged 31-50, 10% of older adults aged 51-64 and 6.8% of seniors reporting missed care. When age groups were run in a logistic regression to predict missed care, (with younger adults aged 18 to 25 as the reference group), each age group was independently predictive of less missed care (p<0.001 for each) compared to younger adults. The significance of young adulthood as a stage in the life course and its impact on access to health care is further confirmed by looking at other variables associated with life course transitions such as l iving arrangement, marital status, job status, sense of belonging to a local community, and income adequacy. Among different marital statuses, those who are separated (15.2%), common-law (14.8%), and divorced (14.6%) are most likely to report missed care, in contrast to those who are widowed (8%), now married (10.2%), or single (11.5%) (Table 4.2.2). Among living arrangements, those who are unattached living with others (14.9%), single parents (13.8%), and unattached living alone (12.7%) report the most missed care, while children living with their parents report the least missed care (Table 4.2.2). However, when we run living arrangement by missed care for just those aged 20 and older, children l iving with their parents no longer have the lowest rate of missed care (12.4%) (Table 4.2.2). (Note: We know from section 4.1 that young adults are most likely to be in common-law relationships, etc. However, this section of analysis did not select out cases based on age. Therefore, those who report missed care within these categories w i l l come from different ages.) Since children l iving with their parents could be adults, the same table for l iving arrangement and missed care was run for those over 20. 83 Among those over 20, we see an increase in the reporting of missed care for those living with one or more parents vs. children of all ages living with their parent(s) (11.8% and 8.7% respectively). The weaker the sense of belonging to a local community, the more l ikely the report of missed care, the highest rate being 17.2% for those who report a very weak sense of belonging to a local community (Table 4.2.2). This may also relate to young adults as they have weaker sense of belonging than all other age groups (see Table 4.1.2). 84 Table 4.2.2 Marital Status, L iv ing Arrangement, and Sense of Belonging to a Local Community and Reporting Missed Care Reporting Missed Care No Yes Total Marital Status N o w married 89.8 10.2 100 Common-law 85.2 14.8 100 Widowed 92.0 8.0 100 Separated 84.8 15.2 100 Divorced 85.4 14.6 100 Single 88.5 11.5 100 Total 88.8 11.2 100 Chi-square p O . O O l ; Eta 0.056 Liv ing Unattached Alone 87.3 12.7 100 Arrangement Unattached other 85.1 14.9 100 Spouse/partner 90.0 10.0 100 Parent spouse child 88.6 11.4 100 Parent child 86.2 13.8 100 Chi ld parent w/w/out 88.2 11.8 100 siblings Chi ld 2 parents 91.3 8.7 100 w/w/out sibling other 88.4 11.6 100 Total 88.9 11.1 100 Chi-square p O . O O l ; Eta 0.05 Liv ing Unattached Alone 90.0 10.0 100 Arrangement Unattached other 85.3 14.7 100 among those Spouse/partner 87.3 12.7 100 over the age of Parent spouse child 88.8 11.4 100 20 Parent child 86.2 13.8 100 Chi ld over 20 with 87.6 12.4 100 parent (s) other 87.8 12.2 100 Total 88.4 11.6 100 Chi-square pO.OO 1, Eta 0.041 Sense of Very Strong 90.6 9.4 100 Belonging Somewhat Strong 90.6 9.4 100 Somewhat weak 86.6 13.4 100 Very Weak 82.8 17.2 100 Total 88.8 11.2 100 Chi-square p O . O O l ; Eta 0.082 Looking at both income adequacy and total personal income for those 20 years of age and older, there is a significant relationship, whereby the lower income, the more likely to report missed 85 care, with the exception of no income and income below $5000 which may be a reflection of the system's ability to address the health care needs of those most vulnerable. See table 4.2.3 below. Table 4.2.3 Income Adequacy, Personal Income (for those aged 20 and older), Prescription Medical Insurance, Self-reported Health Status and Has a Regular Doctor by Reporting Missed Care Reporting Missed Care No Yes Income adequacy Lowest 82.1 17.9 100 Lower Middle 85.1 14.9 100 Middle 87.8 12.2 100 Upper middle 88.4 11.6 100 Highest 89.2 10.8 100 Total 88.2 11.8 100 Chi-square p<0.001; Spearman correlation -.035 Total Personal N o income 87.2 12.5 100 Income from all <$5,000 87.4 12.6 100 sources for those $5,000-$9,999 85.1 14.9 100 over age 20 $10,000-$ 14,999 86.7 13.3 100 $15,000-$19,999 85.9 14.1 100 $20,000-$29,999 88.0 12.0 100 $30,000-$39,999 89.1 10.9 100 $40,000-$49,999 89.4 10.6 100 $50,000-$59,999 88.3 11.7 100 $60,000-$79,999 89.7 10.3 100 $80,000 or more 90.8 9.2 100 Total 88.1 11.9 100 Chi-square p<0.001; Eta 0.047 Insurance for N o 87.4 12.6 100 prescription Yes 89.1 10.9 100 medication Total 88.8 11.2 100 Chi-square p O . 0 0 1 ; Eta 0.022 Self-perceived Excellent Health 93.6 6.4 100 health status Very good Health 90.3 9.7 100 Good Health 87.0 13.0 100 Fair health 82.1 19.9 100 Poor health 71.9 28.1 100 Total 88.8 11.2 100 Chi-square p O . 0 0 1 ; Eta 0.135 Has a Regular Yes 83.9 10.3 100 Doctor N o 89.7 16.2 100 Total 88.8 11.2 100 Chi-square p O . 0 0 1 ; Pearson's r=0.065, pO.001 Those without prescription drug insurance were more likely to report missed care than those with prescription medication insurance (12.6% vs. 10.9%). Those in fair (19.9%) or poor (28.1%) health are significantly more likely to report missing care than those in excellent (6.4%), very good (9.7%) or good (13.0%) health (Table 4.2.3). It may be that i f one is in worse health, the more likely one is to need to access health care, thus identifying more barriers to health care access. Another measure associated with missed care is whether people have a regular doctor for primary health care. If you do not have a regular doctor you are significantly more likely to report missing care (16.2% vs. 10.3%; r 0.065, pO .OOl ) (Table 4.2.3). There are four findings of particular interest when comparing the prevalence of reporting missed care. Those l iving in urban areas more likely to report missed care (11.2%) than those living in rural areas (10.8%) (Table 4.2.4). Non-immigrants report missed care with greater frequency (11.5%) than immigrants (10.0%) (Table 4.2.4). Those immigrants who have lived in Canada for nine or less years are slightly more likely than those who have been in Canada longer to report missed care (10.5% vs. 9.8%) (Table 4.2.4). Non-English or French speakers report missed care with the same frequency as those who speak English or French. Finally, women are more likely to report missed care (12.6%) than men (9.7%). 87 Table 4.2.4 L iv ing in a Rural or Urban Area, Immigrant Status, Length of Time in Canada since Immigration, Can Speak English or French, and Sex by Reporting Missed Care Reporting Missed Care , No Yes Total Rural or Urban Area Urban 88.8 11.2 100 Rural 89.2 10.8 100 Total 88,8 1L2 100 Chi-square p O . 0 0 1 ; Eta 0.005 Immigrant N o 88.5 11.5 100 Yes 90.0 10.0 100 Total 88^8 1_L2 100 Chi-square p O . 0 0 1 ; Eta 0.019 . Length of time in 0-9 years 89.5 10.5 100 Canada since 10 years or more 90.2 9.8 100 Immigration Total 9JX0 1O0 100 (immigrants only) Chi-square p O . 0 0 1 ; Eta 0.011 Can Speak English or N o 88.9 11.1 100 French Yes 88.9 11.1 100 Total 88.9 1L1 100_ N o significant difference Sex Female 87.4, 12.6 100 Male 90.3 9.7 100 Total 8 8 J 1L2 \00_ Chi-square p O . 0 0 1 ; Eta 0.046 These findings suggest that perceived missed care may have validity issues in its ability to measure actual missed care. The implications of these and other findings wi l l be explored in the discussion, section 5.0. The bivariate findings are summarized below in a table. Note that it is not appropriate to directly compare effect sizes (i.e., Eta values) as they may be based on different numbers of cases due to missing data. 88 T Table 4.2.5 Summary o f all Bivariate Crosstabulation Tables Predict ing M i s s e d Care Concept Independent Variable p-value Strength of Who reports missed Who reports missed for Chi - association health care the most? health care the least? square (Eta unless specified) Predisposing Age factors (5 groups based on life course stage.) Sex Immigrant status Can speak English or French O.001 0.092 . 18-25 year olds Adolescents (6.6%) (14.4%) and 26-30 followed closely by year olds (15.0%) seniors (6.8%) O.001 ' 0.046 Females (12.6%) Males (9.7%) <0.001 0.019 Non-immigrant Immigrant (11.5%) (10.5%) null No difference No difference Enabling . Income Factor Adequacy Prescription Drug Insurance Regular doctor Rural/Urban <0.001 -.035 Lowest income Highest (10.8%) (Spearman (17.9%); decreases as correlation) income increases <0.001 0.022 No insurance (12.6%) Insurance (10.9%) <0.001 0.135 No doctor (16.2%) Doctor (10.3%) <0.001 0.005 Rural (10.8%) Urban (11.2%) Need Self-reported health status <0.001 0.135 Poor health (28.1%); Excellent health decreases as health (6.4%) .increases Social Living Support Arrangement Marital Status Sense of Belonging to a local community <0.001 0.05 Unattached other Child living with 2 (12.7%), single parent parents (8.7%) (13.8%), unattached alone (12.7%) [Child over 20 years old living with parent (12.2%)] O.001 0.056 Separated (15.2%), . Widowed (8.0%) common-law (14.8%), divorced (14.6%) <0.001 0.082 Very weak (17.2%) Very strong and Weak (13.4%) somewhat strong (9.4%) 89 Summary: Young adults were the age category with the largest proportion of.missed care when compared to other age groups. Significant relationships were found between predisposing factors and reporting missed care, though not always as expected. In terms of sex, women report missed care more than men. Non-immigrants report missed care more than immigrants. Those who speak English arid French report missing care as frequently as those who can not. Enabling factors were also found to have significant relationships to reporting missed health care. The higher the income adequacy, the less likely a person is to report missed health care. Those with prescription drug insurance were less likely to report missed care than those without. One of the strongest relationships was between having a regular physician and reporting missed care, where those who have a regular physician were far less likely to report missed care. However, l iving in a rural area did not have people reporting missed care more frequently. Need, represented by self-reported health status, was also a strong predictor of missed health care. The lower one's health status, the greater likelihood of them reporting missed health care. Finally, social support was also tied to missed health care. L i v i n g without a parent or spouse puts people at increased risk or reporting missed care. Moreover, those who are in common-law relationships, separated or divorced are likely to report missed care more frequently. Logistic Regression Models Next, nested logistic regression models (Table 4.2.6) were run to explore the relative significance of several independent variables in predicting the dependent variable of missed health care. Inter-correlations were examined to check for multicolinearity, and all were found to be lower than 0.7. Observed and expected values on the Hosmer Lemeshow Test were also checked and no concerns were found. The models included variables related to: 90 1) predisposing factors (i.e., age, sex, being an immigrant to Canada, not being able to speak English or French); 2) enabling factors (i.e., income adequacy, prescription drug insurance, having a regular physician, and l iving in a rural or urban area); 3) need (self-reported health status); and 4) social support (i.e., l iving arrangement, job status, and sense of belonging to a local community) as they are hypothesized to be associated with the reporting of missed care. When examining logistic regression models, we can observe the odds ratios and significance (p-values) for each variable in the model to determine each variable's strength of association when controlling for the other variables, and the model's associated R-square to see its overall predictive ability. We can also observe changes in the odds ratios, significance, R-squares and -2 log likelihood between the different nested models. The odds ratios allow estimation of the odds of an event (one level of the dependent variable) occurring on the basis of the values of the predictor variables. A n odds ratio of 2 would mean that odds of being in the highest coded class of the dependent variable (missed care=yes) are multiplied by 2.0 when the independent variable increases by one unit. The significance (or p-value) tells us i f the results can be accepted or rejected (can not be differentiated from results that may be due to chance.) R-square is a measure of effect size. The Nagelkerke's R-square is a modification of the Cox and Snell coefficient and can vary from 0-1. It is the most commonly reported of the R-square estimates. However, it should be noted that there is no widely-accepted direct analog to ordinary least squares regression R-square. This is because, "and R-square measure seeks to make a statement about the 'percent of variance explained,' but the variance of a dichotomous or categorical dependent variable depends on the frequency distribution of that variable. For a dichotomous dependent variable, for instance, variance is at the maximum for a 50-50 split and the more lopsided the split, the lower the variance." (Garson, 2005) This would explain a large 91 proportion of the very low R-square values in this analysis since only 11.2% of respondents report missed care. The -2 log likelihood is an approximate Chi-squared statistic with df given by the number of extra parameters included in the model (Agresti & Finlay, 1997). If the value of the -2 log likelihood goes down enough, we can see i f the model with more variables added to it has significantly added to the predictability of the model. The three nested logistic regression models are presented below in table 4.2.6.Table. 7 7 Note that this regression analysis was performed in SPSS 14.0 with the stardardized population weight. As per the discussion section 3.1.2, the analysis was also run in SUDAAN incorporating the bootvar bootstrapping method. The findings support this analysis. 92 4.2.6: Results from Logistic Regression Modeling the Report of Missed Health Care N=135573 Model 1 Predisposing and Enabling Factors Odds Ratio Model 2 Model 3 Predisposing, Enabling Predisposing, Enabling, and Need Factors Need, and Social Support Odds Ratio Odds Ratio Predisposing Factors Male 0.69*** 0.69*** 0.68*** Immigrant 0.81*** 0.81*** 0.82*** Age groups: Adolescents 12-17 0.63*** 0.63*** 0.80* Young Adults 18-30 (reference category) u Adults 31-50 0.92* 0.85*** 0.78*** Older Adults 51-64 0.72*** 0.56*** 0.53*** Seniors 65 and older 049*** 0.35*** 0.35*** (Dis)Enabling Factors: Income Adequacy: Highest (reference category) Upper Middle I j2** 1.02 1.01 Middle j 27*** 1.05 1.04 Lower Middle 1.60***. 1.18* 1.16* Lowest j y2*** 1.22* 1.20t No Prescription Insurance 1.11** 1.13** 1 j 2** No Regular Doctor 1.50*** 1.63*** 1.57*** Rural (vs. Urban) 0.95 0.95 0.97 Need Self-reported Health Status: Excellent (reference category) Very Good 1.58*** 1.57*** Good 2 43*** , 2 41*** Fair 4 28*** 4 3 j * * * Poor Q, J2*** Q 52*** Social support Living Arrangement Lives unattached alone (reference category) Lives Unattached Other 0.89 Lives with spouse/partner 0.90 Lives with parent spouse and child 0.86** Parent (single) with child 0.94 Child with single parent 1.002 Child with single parent & sibling 0.62** Child with 2 parents 0.67*** Child with 2 parents and sibling 0.60*** Other living arrangement 0.86* Job status . Worked A Job In Past 12 Months 0.84*** Sense Of Belonging To A Local Community Somewhat or Very Weak I J Q * * * (vs. Somewhat and Very Strong) Nagelkerke R-square -2 L o g L i k e l i h o o d 0.021 26138.262 0.072 25258.853 0.076 25182.635 tpO.10; * p<0.05; ** p<0.01; *** pO.OOl 93 From the regression models we see that the chance of reporting missed care is lower for all age groups (adolescents, adults, older adults, and seniors) compared with young adults aged 18-30, even when controlling for predisposing factors, enabling factors, need and social support. The chance of reporting missed care decreases by a factor of 0.682 (p<0.001) for men vs. women. Thus, men are less likely to report missed care then women, even when controlling for all factors. Immigrants are also less likely to report missed care than non-immigrants. The chance of reporting missed care is increased the lower one's income adequacy is compared to the highest bracket, even when controlling for predisposing and enabling factors. However, only those in the lowest two categories of income adequacy remain statistically significant when adding need (self-reported health status) to the model. Need, as represented by self-reported health status, is one of the strongest predictors of missed health care, (along with age), where the greater the need, the higher the odds of reporting missed care. Reporting of missed care is more than 9 times more likely for those in poor health as compared to those in excellent health. Even those in good health are more likely than those in excellent health to report missed care (odds=T.576, p=<0.001). Not having a regular doctor is another strong predictor of missed health care. The chances of reporting missed care is 1.566 times more likely i f one does not have a regular physician. In the final model with social support, l iving with one or more parents is protective against reporting missed care when compared to living alone. Working a job is also protective, and those who have a weaker sense of belonging are at higher risk of reporting missed care. To compare the value of adding the new predictors for models two and three, a likelihood-ratio test based on the difference in the values of (-2 log L) for the models was calculated using the method outlined by Agresti & Finlay (1997). For comparing model one to model two, the -2 log L for model two was subtracted from the -2 log L for model one: 94 26138.262 - 25258.853 879.409 This, (879.409), is a chi-squared statistic with a degrees of freedom (df) equal to the number of new parameters in the equation; in this case df=4. When looked up on a Chi-square distribution values for right-tail probabilities, extremely strong evidence for a better fit was shown with the more complex model with p<0.0005). The same procedure was conducted to compare model two to model three. The Chi-squared statistic was 76.218, df=\\, p<0.0005. This again demonstrated that the more complex model three had statistically significantly better predictive power than models one or two. ' Overall the models are not highly predictive of missed care. The first model with predisposing and enabling factors accounts for just over two percent of the variance in missed care. Model two, which adds the concept of need, explains more variance than Model one, but still a weak predictor at just over seven percent. The final model (three), with social support variables, is slightly better than the others at R-square =7.6%. These low R-squares may in part be due to the small overall percentage of individuals reporting missed care. It is also likely that the model does not adequately address all of the possible predictors of missed care, nor does it have a nuanced understanding of missed care, where it may represent dissatisfaction with health care access or complete inability to access any number of types of primary care. These possibilities, as well as a suggestion for an alternative model for measuring missed health care wi l l be elaborated in the upcoming discussion. In order to tease out how these different factors might relate to life course stages, the third model looking at predisposing, enabling, need, and social support variables, was run separately for different age categories (removing age as an independent variable). The model run 95 for those aged 12-17 did not include social support variables, as the l iving arrangements were too highly correlated with one another. Table 4.2.7 Logistic Regression Model 3 on for the Report of Missed Care for 5 Age groups All ages Adolescents Young Adults Older adults Seniors Ages 12-17 adults Ages31-50 Ages 51-64 Age 65+ Ages 18-30 Odds Odds Ratio Odds Ratio Odds Ratio Odds Ratio Ratio Predisposing Factors Male 0.66*** 0.74 0.62** 0.69*** 0 7 3 * * * 0.72** Immigrant 0.78*** 1.13 0.89 075*** 0.74** 1.16 (Dis)Enabling Factors: Income Adequacy: Highest (reference category) Upper Middle 1.01 1.56t 1.01 1.00 1.00 0.88 Middle 1.04 1.75* 1.26** 1.02 0.84 0.70** Lower Middle 1.21** 1.30 1.34** 1.24f ' 0.95 0.65 Lowest 1.36** 1.29 1.16 1.33t 0.99 0.82 No Prescription Insurance 1 1 4 * * 0.85 1.15* 1.14* 1.10 1.03 No Regular Doctor j 72*** 1.88** 1 4 5 * * * 1.50*** 1.95** 2.54* Rural (vs. Urban) 0.94 1.06 0.85* 1.06 0.90 1.03 Need Self-reported Health Status: Excellent (reference category) Very Good 1.55 1.75***' 1 5 4 * * * 1.48** 0.90 Good 2 2 9 * * 1.98* 2.55*** 2 38*** 2 38*** 1.86** Fair. 2 9 2 * * * 3.51** 4 gj*** 4 Q7*** 4 5 ] * * * 3 24*** Poor 8.82*** 4.21 11.34*** 8.60*** 10.36*** 7 J O * * * Social support Living Arrangement Lives unattached alone (reference category) Lives Unattached Other 1.10 0.77t 1.02 1.09 0.48 Lives with spouse/partner .0.88* 0.99 0.88 0.82 0.87 Lives with parent spouse 0.98 0.74* 0.83 0.98 0.65 and child Parent (single) with child 1.03 0.74 0.92 0.89 1.13 • Child with single parent 0.85 0.97 0.89 1.30 2.18 Child with single parent & 0.92 0.61* 0.58 0.36 0.00 sibling Child with 2 parents 0.82* 0.69* 0.51* 0.87 — Child with 2 parents and 1.01 0.60*** 0:20* 0.00 — sibling Other living arrangement 0.86 0.81 1.01 0.77 Job status Worked A Job In Past 12 0.64** 0.85 0.94 0.81* 0.96 Months Sense Of Belonging To A Local Community Somewhat or Very Weak 1 JJ*** 1.12** 1.09** 1.09* 1.03 (vs. Somewhat and Very Strong) Nagelkerke R-square 0.066 0.050 0.083 0.065 0.077 0.073 t p<0.10; * p<0.05; ** p O . O l ; *** p<0.001 96 When we look at the models by life course stage (age groupings), the most significant sociological finding is that social support variables are important for some stages of the life course and not for others in predicting missed health care. In particular, social support matters most for young adults aged 18 to 30. For young adults, l iving with a parent in any arrangement (other than a l iving with a single parent), is significantly protective against missed health care as compared to those l iving unattached alone. L iv ing unattached with others is almost significantly predictive (OR=0.740; p=0.054) against missed care compared to l iving unattached alone among young adults. Sense of belonging to a local community is most predictive for young adults (OR=1.120, p<0.01) while it is also a significant predictor for adults and older adults, but not seniors. Interestingly, working at a job is only significantly predictive of missed care for older adults. Moreover, variations in income adequacy matter most for young adults. Not having prescription drug insurance is also a significant predictor of missed care for young adults and adults, but not for adolescents, older adults or seniors. Interestingly, l iving in a rural community is significantly protective against missed care for young adults, but not for any other life course stage. We also see that being male is only significantly protective for those over the age of 17. Higher income adequacy is much more protective for young adults. Prescription drug insurance is an important predictor for young adults and adults while not having a regular physician leaves all age groups at higher risk of reporting missed care. However, we must remain conscious that overall these models are not strong predictors of missed care, with R-squares ranging from 0.05 to 0.083. 97 4.3 What Kinds of Care are People Not Receiving and What Reasons Do They Provide for Not Accessing Care? Who Does Not Have a Regular Doctor? The vast majority of Canadians who report missing care, say they should have received care for physical health problems (73.8%), while 8.4% miss care needed for emotional health problems, 7.6% miss regular check-ups, 7.3% miss care for injury, and 8% miss care for other issues (Table 4.3.1). Table 4.3.1 Type of Care Not Received (among those who report missed care) Percents Type of Care Not Being Received Frequency V a l i d Percentage Type of Care Not Physical health 2176170 73.8 Received problem Emotional health 247031 8.4 problem Regular check-up 223118 7.6 Care of injury 216207 7.3 Other 236018 8.0 There are several possibilities for the under-reporting of missed care for emotional health problems that w i l l be elaborated in the discussion. Sixteen possible reasons for missing needed health care are provided in the C C H S 2.1. These are presented below (Table 4.3.2), in order of most frequently reported to least (among those who report missed care). Among those who report missed care, the wait being too long was the most common reason given for missing care (34.6%). Other reasons were that the care was not available at the time (16.1%), the cost (11.1%), the care was not available in the area (10.6%), the care was felt to be inadequate (9.7%), they didn't get around to it (9.2%), decided not to seek care (8.7%), they were too busy (7.6%), the doctor didn't think it was necessary (5.3%), they didn't know where to go (3.6%), they dislike or are afraid of doctors (1.8%), transportation problems (1.7%), personal or family responsibilities (1.3%), unable to leave house (1%), language problems (0.5%), and 2% reported other reasons. 98 Table 4.3.2 Reasons for Care Not Being Received Percents Reporting Reasons for Care Not Being Received Frequency V a l i d Percentage Care Wait too long 1021106 34.6 Not available at the time 474236 16.1 required Cost 327402 11.1 Not available in the area 31390 10.6 Felt to be inadequate 286699 9.7 Didn' t get around to it 272353 9.2 Decided not to seek care 258791 8.7 Too busy 225609 •7.6 Doctor did not think it was 157993 5.3 necessary Didn' t know where to go 105606 3.6 Other 59782 2.0 Dislikes/afraid of doctor 52998 1.8 Transportation problems 49060 1.7 Personal/family 38161 1.3 responsibilities Unable to leave house 31056 1.0 Language problems 16136 0.5 Next, analysis of reasons given for missed care are examined for age groups, marital status, income adequacy (Table 4.3.3), sense of belonging to a local community, rural/urban residence and sex (Table 4.3.4). For age, we see that young adults who report missed care are more likely to report cost (12.5%) as a reason for missed care than other age groups (adolescents 5.1%; adults 11.0%; seniors 11.6%). Adolescents and young adults are more likely to report that they "didn't get around to it", "decided not to seek care" or were "too busy" than adults and seniors. Young adults are also slightly more likely to report that they dislike or are afraid of doctors (2.2%) compared with adolescents (1.8%), adults 1.7%, and seniors (1.1%). For the figures on marital status, see Table 4.3.3. Those who are single and in common-law relationships are most likely to report that they "didn't get around to it" and "decided not to seek care". They also, along with those who are married, are most likely to report that they are 99 "too busy" to have gotten needed health care. Cost is a bigger barrier for those separated or divorced, while transportation is a significant issue for widows and widowers. Not surprisingly, there is a significant relationship between income adequacy and reporting cost as the reason for missed care, whereby the lower one's income the more likely to report cost as a barrier. Other interesting relationships are: 1) as income increases, so does the likelihood to report care not available at the time required; 2) the lower the income the more likely to report that they felt care to be inadequate; 3) the higher income adequacy, the more likely to report that they didn't get around to accessing needed care. 100 Table 4.3.3 Age groups, Marital Status, and Income Adequacy by reason for missed care (for those reporting missed care) Percentage of those reporting reason for missed care (amonj those reporting missed care) Wait Not avail- Cost Not Felt to Didn't Dec id Too ' Doctor Didn't Other Dislikes/ Trans- Personal/ Unabl to able at avai- be get ed not busy thinks know Afraid of portation family e to long time lable inad- around to it where doctor problems responsi- leave required in area equate to it seek unnec to go bilities house care essary Age in Adolesce 25.8 11.2 5.1 5.4 6.8 15.6 20.3 12.7 4.6 1.3 1.6 1.8 2.5 0.9 0.3 four nts groups 12-17 Young 30.5 13.5 12.5 8.6 9.6 12.2 10.2 . 9.5 ' 5.6 3.4 2.1 2.2 1.3 1.2 0.9 adults 18-30 Adults 36.7 17.8 11.0 11.8 9.7 7.6 7.4 7.2 5.1 3.8 1.9 1.7 1.4 1.5 0.9 • 31-64 Seniors 37.9 15.2 11.6 12.0 12.2 6.6 6.3 1.9 6.7 4.0 2.7 1.1 4.1 0.3 3.0 65+ Total 34.6 16.1 11.1 10.6 9.7 9.2 8.8 7.6 5.3 3.6 2.0 1.8 1.7 1.3 1.1 Marital Now 38.6 17.9 9.4 12.4 9.7 8.1 6.7 7.1 5.6 4.0 2.1 1.3 1.3 1.5 0.8 Status married Common 37.6 14.1 11.5 9.7 8.7 9.3 11.4 6.9 5.0 3.0 1.5 1.7 0.5 0.9 0.4 -law Widowe 32.9 16.8 12.7 10.3 10.8 8.7 6.7 4.8 5.1 3.8 1.9 1.4 6.5 2.6 3.9 a Separate A 33.0 21.3 14.9 11.3 12.3 8,7 7.1 3.0 4.1 3.1 1.8 1.4 3.1 3.5 2.5 Q Divorced 31.4 17.0 18.1 10.0 10.7 5.2 7.2 5.9 6.0 3.5 1.6 2.8 3.0 1.4 2.2 Single 28.4 13.3 11.4 8.5 9.5 11.7 11.6 9.9 5.1 3.1 2.2 2.4 1.6 0.8 0.9 Total 34.5 16.1 11.0 10.6 9.7 9.2 8.8 7.6 5.3 3.6 2.0 1.8 1.7 1.3 1.1 Income Lowest 26:5 12.8 19.2 10.3 14.3 7.8 8.5 6.5 8.9 3.6 1.4 3.5 6.2 1.7 1.9 adequacy Lower middle Middle Upper middle Highest 33.2 31.3 37.9 35.1 13.3 13.8 16.6 17.9 18.1 .8.7 17.4 10.5 5.5 10.4 11.1 10.3 10.7 10.3 9.5 8.7 8.0 8.6 9.0 11.0 9.2 7.7 10.1 5.2 7.1 7.8 8.0 6.1 7.1 4!2 5.1 4.3 3.3 3.7 3.4 2.5 1.6 1.8 2.6 2.5 1.9 1.4 4.1 1.8 1.4 0.5 1.5 1.6 1.4 2.2 2.0 0.5 0.7 Total 34.8 15.9 11.2 10.4 9.7 9.5 7.5 5.5 3.5 2.1 1.6 1.3 1.1 Table 4.3.4 Sense of Belonging, Rural-Urban and Sex by reason for missed care (among those who report missing care.) Percentage of those reporting reason for missed care (among those reporting missed care) Wait Not Cost Not Felt to Didn't Decid Too Doctor Didn't Other Dislikes/ Trans- Personal/ Unable to available avail- be in- get ed not busy thinks know Afraid of portation family to long at time able in adequa aroun to it where doctor problems responsi leave required area te d to it seek care unnec essary to go bilities house Sense of Very strong 38.2 16.6 10.6 12.4 9.1 8.0 7.6 5.6 5.9 2.4 2.9 1.3 1.7 1.3 0.8 belonging to a local community Somewhat 35.0 16.2 10.1 10.0 9.1 9.2 8.7 8.1 5.1 3.6 1.9 1.4 1.4 0.9 0.6 ' strong Somewhat 33.1 16.8 10.7 9.1 9.4 10.2 10.1 8.0 4.6 3.5 1.9 1.7 1.4 1.6 1.2 weak Very Weak 33.8 13.8 15.7 12.1 11.6 9.4 7.8 8.0 7.2 5.0 2.0 2.6 3.0 2.0 1.8 Total 34.7 16.1 11.2 10.4 9.6 14.3 8.9 7.7 5.3 3.6 2.0 1.7 1.7 1.3 1.0 Rural/ Urban 34.8 16.2 11.7 9.8 9.8 9.1 8.2 7.7 5.4 3.9 2.1 1.8 1.5 1.2 1.1 Urban Rural 33.6 15.4 8.4 14.5 9.5 9.6 11.3 7.5 ' 5.0 2.3 1.8 1.9 2.6 1.5 0.9 Sex Female 34.9 18.1 11.4 11.6 10.6 6.7 7.6 6.8 5.8 3.9 1.9 1.9 2.0 1.6 1.3 Male 34.1 13.4 10.7 9.4 8.5 12.6 10.3 8.8 4.7 3.1 2.3 1.7 1.3 0.9 0.8 . Interestingly, the weaker one's sense of belonging, the less likely to report that the wait was too long. Those with very weak sense of belonging were far more likely to report care not available in the area, felt care to be in adequate, or they didn't know where to go. Among those who missed care, urbanites are more likely than rural residents to report the wait for care was too long (34.8% vs. 33.6%), that care was unavailable at the time required (16.2% vs. 15.4%), cost was too high (11.7% vs. 8.4%) and that they didn't know where to go (3.9% vs. 2.3%). Rural residents were more likely than urban to report care not be available in the area (14.5% vs. 9.8%) and that they decided not to seek care (11.3% vs. 8.2%). For sex, women are more likely than men to report cost as a barrier (11.4% vs. 10.7%); that they feel care is inadequate (10.6% vs. 8.5%); and that the doctor felt care was not necessary (5.8% vs 4.7%). However, men are more likely than women to report that they didn't get around to seeking care (12.6% vs. 6.7%), decided not o seek care (10.3% vs. 7.6%), and that they are too busy (8.8% vs. 6.8%). 4.3.1 Predisposing Factors to Having a Regular Doctor Seeing a family physician or general practitioner is the most common way of entering the medical system in Canada. Having a regular doctor is important for continuity of care, and has been shown in this research to be a consistent predictor of reporting missed care. The following section examines predisposing, enabling, need and social support factors' relationships with having a regular doctor. Young adult status proved to be important when looking at access to care. Young adults are least likely to have a regular doctor with 24.3% of 20-24 year olds and 26% of 26-30 year olds reporting that they have no regular doctor (Table 4.3.5 presents young adults 18-30 with 24.1% not having a regular doctor). Women are far more likely (18.2%) than men (10.1%) to have a regular doctor (Table 4.3.5). Surprisingly, those who do not speak English or French are more likely (89.3%) to have a regular doctor than those who do speak English or French 103 ( 8 6 . 0 % ) . T h o s e w h o a r e i m m i g r a n t s a r e m o r e l i k e l y ( 8 8 % ) t o h a v e a r e g u l a r d o c t o r c o m p a r e d w i t h n o n - i m m i g r a n t s ( 8 5 . 6 % ) . T a b l e 4 . 3 . 5 P r e d i s p o s i n g F a c t o r s : A g e , S e x , I m m i g r a n t S t a t u s a n d C a n S p e a k E n g l i s h o r F r e n c h b y H a s a R e g u l a r D o c t o r . H a s a R e g u l a r D o c t o r Y e s N o T o t a l A g e i n F o u r A d o l e s c e n t s 1 2 - 1 7 8 7 . 1 1 2 . 9 1 0 0 G r o u p s Y o u n g A d u l t s 1 8 - 3 0 7 5 . 9 2 4 . 1 1 0 0 A d u l t s 3 1 - 6 4 8 7 . 0 1 3 . 0 1 0 0 S e n i o r s 6 5 a n d o l d e r 9 5 . 6 4 . 4 1 0 0 T o t a l 8 5 . 9 1 4 . 1 1 0 0 C h i - s q u a r e p O . O O l ; S p e a r m a n c o n - e l a t i o n - 0 . 1 3 4 , p O . O O l S e x F e m a l e 8 9 . 9 10 .1 1 0 0 M a l e 8 1 . 8 1 8 . 2 1 0 0 T o t a l 8 5 . 9 1 4 . 1 1 0 0 C h i - s q u a r e p O . O O l ; E t a 0 . 1 1 7 C a n C o n v e r s e Y e s 8 6 . 0 1 4 . 0 1 0 0 i n E n g l i s h o r N o 8 9 . 3 1 0 . 7 1 0 0 F r e n c h T o t a l 8 6 . 1 1 3 . 9 1 0 0 C h i - s q u a r e p O . O O l ; P e a r s o n ' s R - 0 . 0 1 3 I m m i g r a n t N o 8 5 . 6 1 4 . 4 1 0 0 S t a t u s Y e s 8 8 . 0 1 2 . 0 1 0 0 T o t a l 8 6 . 1 1 3 . 9 1 0 0 C h i - s q u a r e p O . O O l ; P e a r s o n ' s R - 0 . 0 2 8 4.3.2 Enabling and Need Factors for Having a Regular Doctor T h e r e i s a s i g n i f i c a n t r e l a t i o n s h i p b e t w e e n i n c o m e a d e q u a c y ( T a b l e 4 . 3 . 6 ) a n d h a v i n g a r e g u l a r d o c t o r . T h e h i g h e r o n e ' s i n c o m e , t h e m o r e l i k e l y y o u a r e t o h a v e a r e g u l a r d o c t o r . T h o s e l i v i n g i n a r u r a l c o m m u n i t y a r e m o r e l i k e l y t o h a v e a r e g u l a r d o c t o r t h a n t h o s e i n a n u r b a n c o m m u n i t y ( 8 5 . 7 % v s . 8 6 . 8 % ) ( T a b l e 4 . 3 . 6 ) . F i n a l l y , t h e r e i s a s i g n i f i c a n t r e l a t i o n s h i p b e t w e e n h e a l t h s t a t u s a n d h a v i n g a r e g u l a r d o c t o r ( T a b l e 4 . 3 . 6 ) A s o n e m i g h t e x p e c t : t h e l o w e r y o u r h e a l t h s t a t u s , t h e m o r e l i k e l y o n e i s t o h a v e a r e g u l a r d o c t o r . 1 0 4 Table 4.3.6 Enabling and Need Factors: Income Adequacy, Rural Urban and Self-Reported Health Status by Has a Regular Doctor. Has a Regular Doctor Yes No Total Income Lowest 78.7 \ L 21.3 100 Adequacy Lower middle 82.8 17.2 100 Middle 85.4 14.6 100 Upper middle 85.9 14.1 100 Highest 87.3 12.7 100 Total 85.9 14.1 100 Chi-square p O . O O l ; Eta 0.048 Rural or Urban 85.7 14.3 100 Urban Rural 86.8 13.2 100 Total S5.9 14.1 100 Chi-square p O . O O l ; Pearson's R -0.012 Self- Excellent 93.0 17.0 100 perceived Very good 85.4 14.6 100 health Good 86.4 13.6 100 Fair 91.8 8.2 100 Poor 94.1 5.9 100 Total 85.9 14.1 100 Chi-square p O . O O l ; Eta 0.075 4.3.3 Social Support and Hav ing a Regular Doctor For marital status, those in common-law relationships (24.5%) and who are single (20.6%) are most likely not to have a regular doctor (Table 4.3.7). In contrast, 90.6% of those who are married have a regular doctor. Under living arrangement, those who are unattached living with others are far more likely to report not having a regular doctor (31.8%). (Table 4.3.7) There is a significant relationship between sense of belonging (Table 4.3.7) and having a regular doctor The weaker one's sense of belonging, the more likely one is not to have a regular doctor. 105 Table 4.3.7 Social Support: Marital Status, L iv ing Arrangement, Having a Job, Sense of Belonging by Has a Regular Doctor. Has a Regular Doctor Yes N o Total Marital Status N o w married 90.6 9.4 100 Common-law 75.5 24.5 100 Widowed 94.6 5.4 100 Separated 87.4 12.6 100 Divorced 86.8 13.2 100 Single 79.4 20.6 100 Total 86.0 14.0 100 Chi-square p O . 0 0 1 ; Eta 0.174 (no doctor dependen t) L iv ing Unattached Alone 82.3 17.7 100 Arrangement Unattached other 68.2 31.8 100 Spouse/partner 89.2 10.8 100 Parent spouse child 87.9 12.1 100 Parent child 88.6 11.4 100 Chi ld parent w/w/out siblings 80.7 19.3 100 Chi ld 2 parents w/w/out siblings 86.0 14.0 100 other 86.8 13.2 100 Total 85.9 14.1 100 Chi-square p O . 0 0 1 ; Eta 0.138 Has a Regular Doctor Yes N o Total Sense of Very strong 89.6 10.4 100 Belonging Somewhat strong 87.7 12.3 100 Somewhat weak 82.6 17.4 100 Very weak 79.1 20.9 100 Total 85.8 14.2 100 Chi-square p O . 0 0 1 ; Eta 0.096 4.4 Who Accesses Primary Health Care and What Is the Relationship between Health Care Access and Reporting Missed Care? From the analysis of factors that predict the reporting of missed health care, it appears that the variable of perceived missed care, while capturing some actual missed care, has some deficits in validity i f trying to assess actual missed health care. Groups known to "miss care" such as men, those who can't speak English or French, immigrants, and people from rural communities did not report more missed care than their counterparts. Hence, the variable may be capturing perceptions of missed care rather than actual missed care, and those perceptions may be based on more than timely or adequate health care access such as variations in expectations of services. Moreover, it appears that some types of missed care (such as annual check-ups) may not be legitimate care needs. Finally, the reasons for missed care'may in fact fall into categories of 1) the care was not actually needed (e.g., decided not to seek care, the doctor didn't think it was necessary, didn't get around to it), 2) systemic issues (e.g., care was not available at the time it was required, was not available in the area, did not know where to go, transportation problems, language problems, etc.). If perceived missed care is not an adequate measure of missed care, perhaps it is now important to examine actual physician utilization. In this section the number of consultations with family doctors as they relate to many factors including age, l iving arrangement, sex, immigrant status, language ability, health status, and sense of belonging to a local community are examined. 4.4.1 Predisposing Factors and Number of Consultations with Family Doctor Adolescents aged 12-17 are least likely (30.1%) to have seen their family physician in the past, year compared to young adults aged 18-30 (28.1%), adults aged 31-64 (22.1%), and seniors 65 and over (11.8%) (Table 4.4.1). M e n were more likely to have not seen a doctor in the past year (28.4%) than women (17.1%), and women had a higher percentage of visits in all numbers of visit categories (other than 0) than men (Table 4.4.1). There was very little difference in the number of visits to family physicians for immigrants and non-immigrants (Table 4.4.1). 107 Table 4.4.1 Age Groups by Number of Consultations with Family Doctor Number of Consultations with Family Doctor (in percents) 0 . 1 2 3 4 5 6 7 or Total more Age . Adolescent 12-17 30.1 23.4 18.2 9.2 5.1 4.5 2.4 7.1 100 Young Adult 18-30 28.1 20.8 17.1 9.9 6.6 4.3 3.4 9.8 100 Adult 31-64 22.1 22.8 17.9 10.4 8.2 3.7 4.8 10.1 100 Senior 65 + 11.8 15.1 16.4 10.8 15. 9 4.5 8.0 17.6 100 Sex Female 17.1 20.0 18.1 11.0 9.9 4.7 5.8 13.5 100 Male 28.4 22.7 17.0 9.5 7.4 3.3 3.7 8.0 100 Total 22.6 21.3 17.6 10.2 8.7 4.0 4.8 10.8 100 Immigrant No • .22.9 21.9 17.5 10.0 8.5 3.8 4.7 10.6 100 Status Yes 20.9 19.2 17.8 11.2 9.4 4.8 . 5.2 11.6 100 Total 22.5 21.4 17.6 10.2 8.7 4.0 4.8 10.8 100 4.4.2 Enabling and Need Factors for Number of Consultations with Family Doctor One of the strongest differences observed is between those who have a regular doctor and those who do not. Only 17.1% of those with a regular doctor did not see a doctor in the past year, while 53.7% of those with no doctor did not see any doctor in the past year (Table 4.4.2). It could be that those who needed a doctor saw one, and henceforth were more likely to report having a regular doctor. Little difference was observed between those l iving in rural and urban areas. Those in rural areas were slightly less likely to have seen a physician in the last year (24.5% vs. 22.2%) (Table 4.4.2). The better health status reported, the more likely to have not seen a doctor in the past year (excellent health (30.5%), very good health (23.5%), good health (20%), fair health (12.1%), poor health (7.8%). The same pattern holds true for having only seen the physician once in the past year (Table 4.4.2). However, i f you look at who has been to the physician 7 or more times in the past year, the pattern reverses: excellent health (4.3%), very good health (6.8%), good health (12.1%), fair health (28.1%), poor health (48.5%) (Table 4.4.2). 108 Table 4.4.2 No Regular Doctor by Number of Consultations with a Family Doctor Number of Consultations with a Family Doctor 0 1 2 3 4 5 6 7 or more Total Has a regular Yes 17.7 21.8 18.6 10.9 9.6 4.3 5.3 11.9 100 doctor N o 53.7 18.7 11.0 6.0 3.3 1.9 1.5 3.9 100 Total 22.6 21.3 17.6 10.2 8.7 4.0 4.8 10.8 100 Rural or Urban Urban 22.2 21.1 17.8 10.4 8.7 4.1 4.8 10.9 100 Rural 24.5 22.1 16.6 9.3 8.7 3.5 4.6 . 10.6 100 Total 22.6 22.3 17.6 10.2 8.7 4.0 4.8 10.8 100 Self-Perceived Excellent 30.5 28.2 18.1 8.7 5.2 2.5 2.4 4.3 100 Health Status Health Very good 23.5 23.6 19.5 10.7 8.1 3.9 3.9 6.8 100 health Good health 20.0 18.2 17.2 11.3 10.7 4.8 5.8 12.1 100 Fair health 12.1 10.1 12.9 9.6 12.5 5.5 9.3 28.1 100 Poor health 7.8 4.1 6.5 7.0 11.6 4.6 10.0 48.5 100 Total 22.6 21.3 17.6 10.2 8.7 4.0 4.7 10.8 100 4.4.3 Social Support and Number of Consultations with Family Doctor If sense of belonging to a local community is somewhat weak (24.3%) or very weak (23.7%) individuals are more likely to have not seen a physician in the past year than those with somewhat strong (22.6%) and very strong (20.1%) sense of belonging to a local community (Table 4.4.3). Table 4.4.3 Sense of Belonging to a Local Community by Number of Consultations with Family Doctor Number of Consultations with Family Doctor 0 1 2 3 4 5 6 7 or more Sense of Very 20.1 21.6 18.3 10.5 9.0 4.0 5.1 17.7 Belonging Strong to a Local Somewhat 22.6 21.6 18.2 10.5 8.7 4.0 4.7 9.7 Community Strong Somewhat 24.3 21.5 17.1 10.0 8.3 3.9 4.5 10.4 weak Very 23.7 19.9 15.1 10.0 9.0 4.1 4.6 13.5 Weak Total 22.6 21.3 17.6 10.2 8.7 4.0 4.7 10.8 Those who perceive no missed care were more likely to have not gone to the doctor in the last year (23.4%) vs. those who do perceive missed health care (17%) (Table 4.4.4). In fact, those 109 who report no missed care are less likely to have been to the doctor once or twice than those who report missed care. However, those who report missed care are more likely to have gone to the doctor 3 or more times than those who report no missed care. Furthermore, 19.1% of people report having missed health care, and have been to the doctor 7 or more times (compared to 9.7% who went 7 or more times and had no missed care.) That means that of those who report missed care, 17% did not see a family doctor in the last year, while 83% of them did, and 19.1% of them went to see the doctor seven or more times. Table 4.4.4 Self-perceived missed health care needs by number of consultations with a family doctor Number of Consultations with a Family Doctor 0 1 2 . 3 4 5 6 7 or more Total Missed No 23.4 22.1 17.8 10.1 8.6 3.8 4.5 9.7 100 Care Yes 17.0 15.3 15.4 11.1 9.3 5.8 7.0 19.1 100 Total 22.7 21.3 17.6 10.2 8.7 4.0 4.8 10.8 100 4.4.4 Reasons for Missed Care and Number of Consultations with Physicians. Finally, among those who report missed care, we can see the relationship between the number of consultations with a family physician in the past year and the reason why health care was not received (Table 4.4.5). The wait being too long increases in frequency with the number of physician visits, as does the reporting of care not available at time required. In fact, reporting the care was not available at the time required increases with the number of physician visits. Feeling the care to be inadequate jumps to 12.3% for those who have been to the doctor 4 or more times in the last year. However, those who say they didn't get around to it, decided not to see care or are too busy, are more likely to have not gone to the doctor in the past year. Also , those who report care not being available in their area are more likely to have reported not seeing their family doctor in the last year. (Keep in mind, this table reflects only those who reported missed care). Finally, feeling they didn't get adequate care is due to the doctor thinking it unnecessary is more common the more one goes to the doctor. 110 Table 4.4.5 Number of Physician Visits by Reasons Health Care Was Not Received (for those who report missed care): Percentage of those reporting reason for missed care ( imong those reporting missed care) Wait Not Cost Not Felt to be Didn't Decided Too Doctor Didn't Other Dislikes/ Trans- Personal/ Unable to available avail- in- get not to busy thinks know Afraid of portation family to leave long at time able in adequate around seek care it where doctor problems responsi house required area to it unnec essary to go bilities Number of None 29.1 11.9 9.7 12.1 8.4. 14.9 14.5 10.0 2.2 4.2 1.6 2.5 1.3 1.1 0.9 Consultations with Family Doctor 1-3 3.4.9 15.7 10.6 9.9 7.7 10.3 9.2 8.9 4.3 3.5 2.0 1.7 1.1 1.3 0.7 4 or 36.6. 18.1 12.2 10.8 12.3 5.8 5.9 5.4 •7.7 3.4 2.3 1.6 2.4 • 1.4 1.5 more Total' 34.6 16.1 11.1 10.8 9.7 9.2 8.8 7.6 • 5.3 3.6 2.0 1.8 1.7 1.3 1.1 i 4.5 Answer ing Hypotheses I n a n s w e r i n g t h e r e s e a r c h q u e s t i o n s , e a c h h y p o t h e s i s p r o p o s e d h a s b e e n a d d r e s s e d t h r o u g h a n a l y s i s . F o r h y p o t h e s i s o n e , ( H I : Y o u n g a d u l t s w i l l r e p o r t m o r e m i s s e d c a r e t h a n o t h e r a g e g r o u p s . H o : T h e r e w i l l b e n o s i g n i f i c a n t d i f f e r e n c e b e t w e e n t h e d i f f e r e n t l i t e c o u r s e s t a g e s a n d m i s s e d h e a l t h c a r e ) , y o u n g a d u l t s w e r e s h o w n t o r e p o r t m o r e m i s s e d h e a l t h c a r e t h a n t h o s e i n o t h e r s t a g e s o f t h e l i f e c o u r s e . W i t h a p - v a l u e < 0 . 0 0 0 1 , t h e n u l l - h y p o t h e s i s c a n b e r e j e c t e d . F o r h y p o t h e s i s t w o ( H 2 : S o c i a l s u p p o r t , p r e d i s p o s i n g , e n a b l i n g a n d n e e d f a c t o r s w i l l b e a s s o c i a t e d w i t h m i s s e d c a r e . F l o : S o c i a l s u p p o r t , p r e d i s p o s i n g , e n a b l i n g , a n d n e e d f a c t o r s w i l l n o t b e a s s o c i a t e d w i t h m i s s e d c a r e ) t h e n e s t e d l o g i s t i c r e g r e s s i o n m o d e l a n a l y s i s f o u n d t h a t s o c i a l s u p p o r t , p r e d i s p o s i n g , e n a b l i n g a n d n e e d f a c t o r s w e r e r e l a t e d t o m i s s e d c a r e , a n d t h e n u l l h y p o t h e s i s c a n b e r e j e c t e d b a s e d o n t h e a s s o c i a t e d p - v a l u e s . F o r h y p o t h e s i s t h r e e ( H 3 : A g e w i l l n o t r e m a i n a s i g n i f i c a n t p r e d i c t o r o f m i s s e d h e a l t h c a r e w h e n c o n t r o l l i n g f o r s o c i a l s u p p o r t , p r e d i s p o s i n g , e n a b l i n g , a n d n e e d f a c t o r s . H o : A g e w i l l r e m a i n a s i g n i f i c a n t p r e d i c t o r o f m i s s e d h e a l t h c a r e w h e n c o n t r o l l i n g f o r s o c i a l s u p p o r t , p r e d i s p o s i n g , e n a b l i n g , a n d n e e d f a c t o r s ) w e a r e u n a b l e t o r e j e c t t h e n u l l h y p o t h e s i s a s a g e g r o u p s ( o r l i f e c o u r s e s t a g e ) d i d r e m a i n a s i g n i f i c a n t p r e d i c t o r o f m i s s e d h e a l t h c a r e , e v e n w h e n c o n t r o l l i n g f o r a l l o t h e r f a c t o r s i n c l u d e d i n t h e m o d e l . H y p o t h e s i s f o u r ( H 4 : L i f e c o u r s e s t a g e w i l l a f f e c t t h e r e l a t i o n s h i p s a m o n g p r e d i s p o s i n g , e n a b l i n g , n e e d a n d s o c i a l s u p p o r t t o m i s s e d c a r e . H o : T h e r e l a t i o n s h i p s a m o n g p r e d i s p o s i n g , e n a b l i n g , n e e d a n d s o c i a l s u p p o r t t o m i s s e d c a r e w i l l n o t b e a f f e c t e d b y l i f e c o u r s e s t a g e ) w a s e x p l o r e d i n t h e c o m p a r i s o n o f t h e f u l l m o d e l f o r e a c h l i f e c o u r s e s t a g e . It w a s f o u n d t h a t t h e r e l a t i o n s h i p s a m o n g p r e d i s p o s i n g , e n a b l i n g , n e e d s a n d s o c i a l s u p p o r t f a c t o r s t o m i s s e d c a r e w e r e a f f e c t e d b y a g e , a n d t h e n u l l h y p o t h e s i s i s r e j e c t e d . F i n a l l y , t h e fifth h y p o t h e s i s ( H 5 : L i f e c o u r s e s t a g e w i l l b e r e l a t e d t o h e a l t h c a r e u t i l i z a t i o n a n d r e a s o n s f o r m i s s e d h e a l t h c a r e . H o : L i f e c o u r s e s t a g e w i l l n o t b e r e l a t e d t o h e a l t h c a r e u t i l i z a t i o n a n d r e a s o n s f o r m i s s e d h e a l t h c a r e ) f o u n d t h a t h e a l t h c a r e u t i l i z a t i o n a s m e a s u r e d b y the reporting of missed care, having a regular physician, and number of visits to a family physician are all related to stages of the life course, and the null hypothesis can be rejected. 113 5.0 DISCUSSION AND POLICY IMPLICATIONS Access to Canada's universal health care system is not equitable. In examining missed health care, the life course stage of young adulthood is shown to be significantly different from other life course stages with increased risk for missed care. It is not clear i f these are differences in actual missed care, or expectations of care. In particular, young adults are at increased risk of reporting missed care and of not having a regular primary care physician compared with those in other stages of the life course, even when controlling for other factors. Various factors related to predisposing, enabling and need factors, as well as social support are predictive of missed care as well. Many of these factors are related to life course stage, and some factors such as income adequacy, sex, self-reported health status, and social support remain significant predictors of missed care in multiple logistic regression analysis when controlling for all other variables including stage of the life course. Specifically, for young adults, social support is protective against missed health care, with those living with a spouse and child or l iving with both parents being significantly less likely to report missed care. Likewise, weak sense of belonging to a local community, and income adequacy are most predictive of young adults missing care. Young adults also differ from adults and seniors in the reasons they report for missed care. O f most interest in the context of a universal health care system, young adults are more likely to report cost as a barrier to health care access compared with those in other life course stages. So, what models are best for predicting missed care? 5.1 Predicting Missed Care The final logistic regression model in this study included variables related to predisposing-factors (i.e., sex, immigrant status, and age group); enabling factors (i.e., income adequacy, prescription drug insurance, having a regular doctor, and l iving in a rural or urban area); need (as represented by self-reported health status); and social support (i.e., l iving arrangement, job status, and sense of belonging to a local community). L iv ing arrangement was chosen over 114 marital status as both indicators could not be included due to multicolinearity. The variable living arrangement distinguishes being married (lives with spouse), being single and wide range of other living arrangements that have implications for life course stage and the transitions to adulthood. The final model including all variables demonstrates clearly that life course stage is an important predictor of missed health care, with the odds of reporting missed care being lower for all life course stages when compared with young adults aged 18 to 30 (when controlling for all predisposing, enabling, need, and social support variables). Other factors that remain as significant predictors of missed care in the final model are sex (men), immigrant status, lower income, and need. Also , under social support variables, l iving with parents or spouse is significantly protective against missed care; working at a job in the past year is protective, and having somewhat or very weak ties increases the odds of reporting missed care. Overall, the model based on Andersen's predisposing, enabling, and need factors with the addition of social support variables, proved to be not a very effective predictor of missed care, accounting for only 7.6% of the variance in the dependent variable. This is l ikely due in part to the small percentage of respondents who report missed care. A s Garson (2005) pointed out, in logistic regression, with a dichotomous dependent variable, "variance is at the maximum for a 50-50 split and the more lopsided the split, the lower the variance." (p.i) In this case, only 11.2% of respondents reported missed care, thus a lower percentage of variance explained is expected. Other reasons for the low percentage of variance explained could be that not all factors predicting missed care were included in the model or that missed care is an issue of perception that varies from individual to individual, and the lack of specificity in what is meant by "missed . care" does not allow for adequate prediction based on the factors selected for the model. While social support variables were added, not all of the factors called for in the various incarnations of the Andersen model were included. Some, such as emotional health (Andersen proposed this as 115 another "need" factor), were omitted due to multicolinearity issues. (These and other issues wi l l be further elucidated in the limitations section below). To further understand the role of life course stage in predicting missed care, the above final model was run separately for the age groups of adolescents (12 to 17), young adults (18 to 30), adults (41-50), older adults (51-64) and seniors (65 and older). It is important to note that social support variables were not included in the model for adolescents, which prohibits direct comparison with the other stages in the life course. (The social support variables were left out for adolescents due to multicolinearity issues.) Here substantial differences between stages in the life course are observed. First, not reporting excellent health status is a stronger predictor of missed care for young adults than any other age group at each level of health status. Also , not being in the highest income category is a stronger predictor of missed care for young adults than all other age categories. Likewise, having a somewhat or very weak sense of belonging to a local community is a stronger predictor of missed care for young adults than for those at other stages of the life course. Finally, social support, with respect to l iving with a parent or spouse is predictive of less missed care for young adults but not older adults or seniors when compared to the reference category of l iving unattached alone. Adults aged 31 to 50 were also significantly less likely to report missed care i f they lived with both parents as compared to those who live unattached alone. (Again, l iving arrangement was not run for adolescents due to intercorrelation issues.) From the analysis, the dependent variable 'missed care' appears to be a problematic measure of unmet health care needs. While missed care may capture perceptions of problems with access to health care, it is surprising that it did not capture (at the bivariate or multivariate level) increased risk for immigrants, those who can not speak English or French, men, or those from rural communities - all o f whom are cited in the literature as having difficulty accessing care compared with the counterparts. The lack of missed care reported by at-risk subpopulations 116 may be a consequence of them having fewer unmet health care needs than expected, or it could partly be due to the variable missed care itself, as it is subject to self-report bias. There is the possibility of individuals reporting what they think researchers want to hear, or what they think others might say. Some may interpret missed care as related only to their primary care physician, while others may relate it to a myriad of other health care service options (e.g., physician specialists, dentist, physiotherapists, procedures, or even diagnostic tests). There may also be different interpretations of "missed" care, as some might report delayed access as "missed" care, while others would not. Reporting bias could also be present based on the quantity and quality of care needed by individuals, and their perceptions of what care should be provided. These issues around perceptions of primary health care services might be particularly salient for populations with experiences with other health care systems (i.e., immigrants to Canada), and those in rural areas who are reported to face more health care service deficits than urban communities. It was surprising to discover that the reporting of missed care was more prevalent among non-immigrants than immigrants. This finding led to a more critical examination of the variable missed care, as well as looking for possible explanations. The lower prevalence of missed care among immigrants may be in part due to a "healthy immigrant effect", meaning that immigrants are in relatively better health on arrival in Canada compared to native-born Canadians, and that immigrant health converges with years in Canada to native-born levels (McDonald & Kennedy 2004). Another reason may be differences in the recognition of the value of health care based on cultural values with different expectations based on experiences in their home country. Differences based on classes of immigrants such as business, family, refugee and so on may also be factors as they represent different streams, each of which passes through different 'gateways' with varying levels and kinds of selection criteria, screening and decision-making about health status. More specificity in measuring immigrant status may be required to understand this 117 phenomenon in relation to missed health care. It is likely that a more refined analysis on immigrants would find a higher prevalence of missed health care. It was also interesting that there was no difference in the reporting of missed health care when comparing those who can speak English and French from those who can not. This appears to be strong evidence that different subpopulations of individuals in Canadian society have different expectations of health care, as I would interpret this figure to be an under-representation of the missed care of those who do not speak English or French. It is possible there is a bias in participant sampling, though Statistics Canada did conduct the C C H S in Chinese, Punjabi, Cree, and Inuktitut, and found local translators where necessary for other languages. Aside from the above possibilities related to immigrant status, perhaps those who can not speak English or French are more likely to be from other countries, with fewer resources, and with increased experiences of marginalization. These factors may lead them to have lower expectations and thus report missed health care less frequently. In future research, it w i l l be important to address subpopulation characteristics in order to capture their missed health care. Measuring immigrant status, country of origin, length of time in Canada, income and language ability (perhaps incorporating interaction terms into the analysis) would considerably modify the simple statement that immigrants seem less likely than non-immigrants to report missed care. In addition, a qualitative inquiry should yield more information on the differences between immigrant and Canadian-born perceptions and expectations of health care services. The kinds of health care available in immigrants' countries of origin combined with their social status are likely to shape their expectations of the Canadian health care system and their perceptions missed care. Similar issues may explain why those in urban areas report missed health care more frequently than those in urban areas. Health services research in Canada has often focused on the issues of physician shortages and fewer services available in rural Canada as compared to urban 118 areas (e.g., Pong & Pitblado, 2006). Yet, those in urban areas were more likely to report missed care compared with rural areas. This finding has been reported by others such as Sibley (2006) who also conducted analysis of the 2003 C C H S data, with a focus on rural vs. urban experiences. Sibley (2006) found a weak relationship between level of 'ruralness' and measures of access. However, it may be that those in rural communities have different expectations of health care access than those from urban centres. Or, perhaps in a rural area, it is easier to know where and how to access care (though it may take longer to access that care), as services tend to be centralized and known. However, it should be noted that the dichotomy rural/urban in this study lacks specificity. There are likely differences between those l iving in very remote, isolated areas and those l iving closer to a larger centre. There could be many subdivisions of rural and urban that might yield different results when measuring missed care. However, this is not incorporated into the current analysis as rural and urban trends are not the focus of this study. Another explanation for the rural/urban missed care results may be found in understanding the changes in comprehensive care services offered by family doctors. A report by Tepper (2004) shows a shift in the practice of family medicine in Canada from 1992 to 2001. In five of the nine clinical areas of practice usually covered by family doctors, there has been a decrease in the number of participating family physicians (Tepper, 2004). These clinical areas include delivering babies, anaesthesia, helping in the operating room and advanced procedural skills, such as setting broken bones. A s Tepper argues, the practice of family medicine has changed dramatically in the contexts of "major changes in medical training and licensing, regionalization, amalgamation, changes in hospital care, primary health care reform and an ageing population with growing needs." (2004, p.4) The overall percentage of family doctors delivering babies went down from 28% in 1992 to 16% in 2001 (Tepper, 2004). Family physician participation rates in surgical services, surgical assistance, anaesthesia and obstetrical care have declined by 32%, 31%, 28%, and 43% respectively between 1992 and 2001 (Tepper, 119 2004). However, rural family physicians had higher rates of participation in most clinical areas, including surgical services, basic procedures, advanced procedures, and anaesthesia (Tepper, 2004). The reduced rate of comprehensive care services overall may help to explain the increase in reporting of missed care over time. At the same time, the difference between urban and rural family doctors may help explain in part why those in rural areas are not as likely to report missed care. In addition to issues of suspected under-reporting for immigrant and rural missed care, analysis of the types of care people report missing may also indicate 'missed care' not adequately representing unmet health care needs. Some types of care reported missing such as 'annual check-ups' may not be legitimate care needs. Also analysis of the reasons for missed care may fall into categories of 1) the care was not actually needed (e.g., decided not to seek care, the doctor didn't think it was necessary, and didn't get around to it), 2) systemic issues (e.g., care was not available at the time it was required, was not available in the area, did not know where to go, transportation problems, language problems and so on). A s such, a more nuanced understanding of how individuals' interpret missed care should be undertaken in order to assess i f it is a reflection of unmet health care needs in the population. Upon examination of reasons for 'missed care' by 'number of consultations with family physicians' it is also apparent that while 17% of those reporting missed care have not been to see their family doctor in the past year, a number of those reporting missed care have been in the care of doctor in the past year, with 19.1% of them having been to their family doctor 7 or more times. This difference might reflect the process-oriented nature of accessing health care. As Goldsmith (2006) reports from her qualitative research, access to health care experiences may be better characterized as a process of achieving balance, where health and interpersonal needs are met. Goldsmith (2006) found that there was a continual process requiring renegotiation as circumstances change, weighing of competing demands, occurring within different contexts. 120 This more complex, process-driven approach to understanding access to primary care may yield more informative understandings of whether health care is missed, and i f health care is more generally accessed equitably. The model to predict missed care in this study yielded interesting results. However, the dichotomous outcome of missed care is too simple to capture the complex possibilities of unmet .health care needs that may exist. Moreover, several predictors were not developed enough (i.e., immigrant status, rural/urban) to capture their various levels of risk. Finally, the model may have not included important (unknown) factors that would account for additional variance in unmet health care needs. Hence, a new model to understand unmet health care needs is called for. 5.2 Proposed M o d e l for Assessing Unmet Health Care Needs Reflecting on the adequacy of the model developed in this study points to the need for better ways to measure and predict unmet health care needs. A first step would be to engage in qualitative, in-depth research to uncover salient themes around primary health care access, perceptions of health care needs, and barriers to access that are identified by participants. This research could lead to the development of a new model to measure health care access from the public's perspective (including unmet health care needs and missed health care). This model should include more complex outcome measures and predictive independent variables that are necessary, sufficient and mutually exclusive. A better model than the one used in this study would examine one health problem that came up for individuals at a time (perhaps their most recent), and chart the course of context, need, types of care desired, barriers and facilitators to that care. A first stage of outcomes would include time from self-identification or decision to seek care and care being received, and levels of satisfaction with care. A second line of outcomes would assess consequences of health care being received or not. A prospective-retrospective study design would allow for the collection of data over time, to observe the progression and dimensions of access to care as well as the 121 p r e v a l e n c e o f m i s s e d h e a l t h c a r e . T h i s c o u l d e s t a b l i s h b e n c h m a r k s f o r f u t u r e r e s e a r c h . T h e p r o s p e c t i v e d e s i g n w o u l d a l s o h e l p t o r e d u c e r e c a l l b i a s a n d r e p o r t i n g e r r o r . M o r e o v e r , t h e r e s e a r c h f i n d i n g s c o u l d b e l i n k e d t o l a r g e r s o c i a l c o n t e x t s o f c o h o r t e f f e c t s , h i s t o r y , a n d h e a l t h c a r e p o l i c y . O n e c o u l d e n v i s i o n a s k i n g i n d i v i d u a l s t o r e p o r t t h e m o s t r e c e n t h e a l t h c o n c e r n s f o r w h i c h t h e y c o n s i d e r e d s e e k i n g m e d i c a l c a r e f r o m a p h y s i c i a n i n t h e l a s t ( d e s i g n a t e t i m e p e r i o d ) . T h e h e a l t h c o n c e r n s w o u l d b e i d e n t i f i e d a n d t h e d a t e w h e n t h e i n d i v i d u a l s b e c a m e a w a r e o f t h e p r o b l e m c o u l d b e r e c o r d e d . T h e n , a t i m e - l i n e o f e v e n t s c o u l d b e c o n s t r u c t e d , a s k i n g i f a d e c i s i o n t o s e e k c a r e w a s m a d e , i d e n t i f y i n g i f c a r e f r o m a p h y s i c i a n w a s s o u g h t , i d e n t i f y i n g o t h e r f a c t o r s t h a t w e r e i n v o l v e d a n d i f t h o s e f a c t o r s a c t e d a s b a r r i e r s o r f a c i l i t a t o r s to s e e k i n g c a r e . O n e k e y a d d i t i o n t h i s m o d e l m a k e s i s t h e n o t i o n t h a t t h e r e a r e i n f l u e n c e s o n t h e d e c i s i o n t o s e e k c a r e a s w e l l a s t h e a b i l i t y t o s e e k c a r e o n c e t h e d e c i s i o n i s m a d e . A l s o , t h i s m o d e l a s s e s s e s m u l t i p l e o u t c o m e i n d i c a t o r s f o r m e t a n d u n m e t h e a l t h c a r e n e e d s . 122 Figure 5.1 Time-line for Model of Unmet Health Care Needs Influences on decision to seek care (-/+) 7 T T Influences on ability to seek care <-/+) 7T~T Outcome 1: Received -primary care or changed decision Self-identification of health problem Decision to seek primary health care, alternative, or no care. Outcomes 2, 3, & 4: 2) Timing 3) Satisfaction; 4) Health 5) Cost for individual and system Time Line Outcome 1 includes whether the individual received care from a physician, other formal or informal source, or not at all. Outcome 2 measures how long they had to wait for care from a primary care provider; and the third outcome, their satisfaction with that care could be assessed with Likert-scale variables. The fourth outcome then involves assessing whether there were health consequences to seeking or not seeking care (as the case may be.) In order to influence policy, it wi l l also be necessary to include a fifth outcome, economic indicators that assess individual costs of seeking or missing health care, as well as the costs to the health care system for missed care vs. care accessed. Finally, the findings should be assessed in social and historical context. The benefits of this multi-dimensional model proposed here are that it views access to primary care as a process with multiple moderators, is grounded in qualitative emergent themes, assesses multiple influences on access to primary care at two critical stages, and is embedded in social and historical context. 123 5.3 Why Young Adults Matter Young adults were found to have a higher prevalence of missed health care than those in other life course stages. However, while age is a predictor, it is not an explanation for the correlation. Others have found that entry into adulthood has extended beyond the age of 18 (Feldman & Elliott, 1990; Shanahan, 2000), with increased age at first marriage, birth of first child and leaving the parental home. The changes in the timing of these transitions to adulthood will leave many individuals in situations where the live out of the parental home, but unmarried, for longer periods of time. This likely reduces the number people they live with who could provide the necessary close social support that would facilitate timely use of health care services. Fewer social supports may lead young adults to lack encouragement to seek medical attention and due to their inexperience, they may be ill-equipped to know where and how to access care. With the increased years spent in education, and less stability in the labour market, young adults also find themselves with less employment security, lower wages and higher mobility (Arnett, 2000; Shanahan, 2000) and in more dependent economic situations (Arnett, 2004). Young adults may also find their time taken up with multiple responsibilities for education and employment. Their lack of financial and time resources leave them more vulnerable than others to not being able to access timely care, or to be able to afford uninsured services and treatments including prescription medication. Many young adults in Canada do not have prescription drug insurance. As young adults lack financial resources to receive the health care they feel they need, they are more likely to report missed care. Likewise, i f young adults are too busy to access health care, they are more likely to report they missed care. Young adults are also in a time of great instability illustrated by the fact that they have • the highest rates of residential change and interprovincial migration of any age group in Canada (Statistics Canada, 2002). Moving in general requires finding health care provision in one's new home area. This requires finding out about services and finding primary care physicians who are 124 accepting new patients. A s health care in Canada is provincially administered, young adults moving to a new province need to navigate their way to accessing health care in their new province, often entailing complex application processes, and involving fees. There many also be interprovincial differences in what services are covered in the public system, and where and how care can be accessed. If a young adult does not have a reason to seek care, or an expectation that care wi l l be needed, they may delay finding a source for primary care or transferring their coverage to their new province. A s a result, young adults may be more likely to miss care, or be delayed in accessing care, when they need it. From a developmental perspective, young adults may lack the skills to access health care. Moving out of the parental home may be the first time that they would have to self-identify the need for care, know where to seek care, and make arrangements to receive that care. Young adults may lack the input from parents that most adolescents have access to, thus having to rely on their own knowledge, experience and networks for accessing care. It has been argued that Arnett's construct of "emerging adulthood" could be a result of a cohort effect, whereby in this particular historical space and time, there are large numbers of young adults delaying their entry into adulthood who share some common characteristics of instability, self-focus, and identify exploration and formation. Likewise, the findings around missed health care could also be subject to historical, political and social realities that may change over time. Just as the age of marriage has increased, it may again decline. While young adults are reporting lower sense of belonging to a local community than those in other stages of the life course, they are also the first to adopt new communication technologies such as internet messaging and online communities. They may find and use alternative sources of support and information that have not been accounted for in this study, and the use of these may grow for young adults in future. We may also see policy changes around access to health care and service provision that might change the prevalence of missed care for everyone including young adults. 125 In addition, labour markets might change in response to the predicted labour shortage with the baby-boomer generation reaching retirement age, resulting in a more stable employment market for young adults where employers w i l l have to provide better pay and benefits including health benefits in order to attract employees. Moreover, there is the significance of the relative risk versus attributable risk associated with young adults having a higher prevalence of missed care. Relative risk estimates the magnitude of an association between exposure and outcome (i.e., young adulthood and missed care) (Hennekens & Buring, 1987). The logistic regression analysis in this study found that all life course stages had a statistically significant lower relative risk for missed care when compared with young adults. But what about the attributable risk associated with young adulthood? Attributable risk is a measure of association that provides information about the absolute effect of the exposure or the excess risk of disease (in this case missed care), in those exposed (young adults) compared with those non-exposed (Hennekens & Buring, 1987). In other words, i f we were to eliminate all the missed care attributable to young adulthood, what would the population prevalence be? In this study, young adults aged 18 to 30 make-up 20.3% of the population, and only around 15% of them report missed care. However, it is during young adulthood that we set up patterns for future health care utilization. A s the trends for young <f adulthood are influencing the current cohort of young adults to miss health care more frequently, there may be consequences for the access and health outcomes in the future. If patterns established in young adulthood are perpetuated in later life, this may foretell undesirable consequences for the health of the Canadian population. A s such, this study points to further research that should be done as well as important policy implications. 126 5.4 Limitations of the Study and Research Opportunities There are several limitations in the analysis offered in this study. The current analysis did not examine provincial or regional differences in health care access. A s universal health care in Canada is a provincial responsibility, and usually administered regionally, one might expect to find significant differences when looking at provincial and regional level analysis of health care access. Also, while the sample size is very large and nationally representative with a high response rate, the analysis is based on cross-sectional data. Also , C C H S only collected data from Canadians living in private dwellings. Those living on Indian Reserves, residents of institutions, full-time members of the Canadian Armed Forces, residents of certain remote regions and the homeless are excluded. These exclusions may influence the generalizability of the results for the Canadian population as a whole, and does misses important subpopulation analysis of particular at-risk groups. For example, it is well-documented that there are significant health disparities among Canada's First Nation, Metis and Inuit populations (Health Canada, 2002b). Not including those l iving on Native reserves is problematic in understanding their health access issues. Not sampling among the homeless would provide a similar underestimation of missed care for an at-risk population. Another source of potential bias in the logistic regression analysis is the 30% of missing cases. The missing cases were largely due to lower response rates for income adequacy. Income is a question that commonly has a lower response rate due to respondents' desires to maintain confidentiality. This lower response rate may indicate under-reporting in one or more income brackets, or the percentage of non-responders could be evenly distributed. It is also possible that for a question where so many did not want to respond there may be others who answered incorrectly, not wanting to reveal their actual income. In any case, the missing cases for the logistic regression may have consequences for bias in the results assessing the relationships between income, and all other variables including missed health care. 127 There are limitations when trying to assess causality. According to Gray and Guppy (2003), four conditions must be met in order to establish that something causes another. First, there must be a relationship between both variables (i.e., they must co-vary). Second, temporal ordering must be established (i.e., the variable being affected must come after the one doing the affecting.). Third, spurious linkages must be accounted for. Fourth, there must be an explanatory rationale for the causal link (Gray & Guppy, 2003). While data collected at one point in time (cross-sectional) may have limitations, it is possible to establish the time order of many variables (such as gender and income). Thus, it is possible to draw causal inferences from cross-sectional data, provided that third variables (or spurious linkages) can be accounted for and explanatory rationale can be drawn. In this study, it is not possible to eliminate the possibility for third variables, and the time order of some relationships can not be established (e.g., does health status come before health service access or the other direction?). A s a result, the relationships found in this study are correlations, and no causal inferences are argued. Another issue with interpreting the data is that cross-sectional data analysis comes with limitations for examining changes that might occur over time. When addressing the issues around transitions to adulthood, many of the stages of transition, (e.g., out of parental home, from school to employment, from being single to being married) are best viewed with respect to their relative timing and sequencing. These nuances are not addressed in the current analysis. In addition, some individuals may transition back and forth (out of parental home, then back again.). Indeed there are data to show that this has become more common (Shanahan, 2000; Furstenberg, 2005). The fluctuating nature of the transitions to adulthood as discussed by Shanahan (2000), are not addressed or taken into account in this analysis. Likewise, seeking medical care itself is a more complex process of sickness recognition, deciding whether to seek legitimization as being i l l through informal (often interpersonal relationships) and/or formal medical care. A s discussed by Goldsmith (2006, 20006a), these complex processes are not well 128 captured by Andersen's model nor through quantitative cross-sectional data. N o w that this study has established questions regarding missed care as being particularly relevant for young adults, a more complex longitudinal design and qualitative inquiries are called for. To reiterate, the variable of missed care, sometimes referred to as 'unmet health care needs', used in this and many other studies is based on a self-report question that may be more related to perceptions than the reality of missed health care, as argued by Samartin and colleagues (2002). This might in part explain why subpopulations that were expected to report higher rates of missed health care did not (e.g., those in rural communities compared to urban, men compared to women, immigrants compared to non-immigrants, and those who can not speak English or French as compared to those who do). Self-report brings two kinds of problems: 1) its meaning; and 2) its relation to any measure of actual health care needs. More in-depth research is required, l ikely using a qualitative methodology, to understand how different subpopulations may relate to, and respond to, the concept of missed care. To date, to the best of my knowledge, no one has conducted such research. Also, the question measuring missed health care and related follow-up questions regarding the type of missed care do not allow enough specificity in understanding i f the missed care in question is for primary care from a family physician, general or nurse practitioner, for specialized physician referral services, for related non-physician health services (such as physiotherapy), or alternative health care. Another limitation is in relation to the consequences of missed care. The response categories were only 'yes' or 'no' . It would have been interesting to , differentiate possible help-seeking consequences. For example, we could differentiate i f various barriers identified each played a role in stopped them from seeing a physician altogether, delayed them a lot, a little, or only made them uncomfortable. Perhaps some individuals who felt they had "missed care" realized after not accessing care that they were not in need of physician services at all (e.g., having a bad cold, that clears up on its own for which a physician is of 129 limited use in treatment). Future research should collect more information on the type of care that was missed, and the consequences of that missed health care. There is also the question of recall accuracy when using self-report survey questions in general. A recent comparison of the self-reported health care utilization variable "number of contacts with a general practitioner during the 12 month period before the survey interview" from the C C H S Cycle 1.1 and the provincial health records of British Columbia found that the administrative data (health records) yielded a substantially higher number of general practitioner contacts than were reported by respondents in the survey (Palin, 2006). However, the direction and magnitude of the disagreement varied according to personal characteristics, and some subpopulations reported more contacts than were found in their administrative record (Palin, 2006). If similar problems occurred for the variable measuring number of health care visits to your family doctor in the C C H S 2.1, one must be wary of over-interpretation of the data without acknowledging the possibility of recall bias. Some of the other problems with self-report could be concerns on the part of respondents about the confidentiality of the data provided, wanting to give the answers that the respondent feels the interviewer desires, answering the way they think others would, fear that they might be judged by their answers, or not understanding the question (Bailey, 1994). Hence, all of the other variables in this study may be subject to self-report bias. The variable 'sex' only included two categories, and may miss those who do not fall into male or female biological categories (i.e., hermaphrodites). For some, age may be considered confidential or embarrassing information, as would income (discussed above). People may not want to reveal their immigrant status or job history. When responding about health status or access to care, there may be a desire to respond in the way that they feel researchers expect them to. As a result, all analysis must be humble about conclusions, acknowledging the potential for bias. • / ' 130 A s with any analysis of secondary data, there were limitations based on what questions were asked in the CCHS Cycle 2 .1, and what response categories were used. Further limitations occurred due to Statistics Canada's regulations on the releasing of data analysis based on maintaining confidentiality of respondents. In some cases, response categories had to be collapsed and in a few cases related to income variables, tables could not be released at all. However, the final work was able to address all of the proposed research questions and hypotheses. 5.5 Strengths of the Study This study extends and ref ines the evidence pointing to the distinctiveness of young adulthood as a stage in the life course. We can see that young adulthood constitutes a stage in the life course that is distinct with respect to several variables examined including income, living arrangement, marital status, job status, sense of belonging to a local community, and most importantly, missed care. This work establishes that being a young adult has consequences for increased risk of missed health care. This study furthers the literature by taking a well-respected model (Andersen's behavioural model) of health care utilization and looks at its ability to predict missed care. This analysis ultimately led to the development of a new proposed model to study unmet health care needs. Other strengths of this study include the nationally representative sample with high response rate to allow for generalizability to the Canadian population. The particularly large sample size allowed for sub-group analysis on many variables of interest. Also, sophisticated multivariate analysis allowed for greater understanding of the relationships among variables. This study did not only look at the outcome of missed care, but also examined the reasons reported for missed care and physician utilization by several socio-demographic characteristics including life course stage. This broader scope of analysis provided additional information that leads to stronger policy recommendations. Finally, this study identified young adults as having a 131 higher prevalence for reporting missed care, and different factors increasing their risk for missed care. As a result, a number of recommendations can be made both for policy change and future research. 5.6 Recommendations It is an important policy consideration to try to reduce the perceptions of missed care as well as improve the equity in access of primary care in Canada. A t this point, a deeper reflection on the nature of some of the reasons reported for missed care can be expressed, as these are most likely to lead to solutions for inequitable access through policy change. First, there is the reporting of wait times as the reason for missed care by 34.6% of those reporting missed care. Other studies (e.g., Chen et al., 2002) have found that ' long wait times' and 'care not being available in the area' were strongly associated with an individual's health. The authors argue that "since people with medical problems are most in need of health care services, they are more likely than others to recognize deficiencies in the delivery of those services, particularly i f their health problems remain unresolved." (p.20). However, in this study, other factors remained salient predictors of missed care even when accounting for health status. Should the correlation between health status and missed care diminish the importance of their reporting missed care? If one only misses care when one needs care, it does not invalidate one's experiences. We all hope that i f we need health care it w i l l be available for us to access in a timely way. The extensive media attention given, and deliberate politicization of reported delays in the delivery of particular kinds of health care (e.g., replacement surgery for hips and knees; or access to diagnostic tests) in Canada may have also had an unintentional effect of increasing the awareness of patients as to how long they are waiting to see a physician or specialist. This increased awareness may cause them to be more apt to use reporting of 'missed care' as a way of describing the fact that they need to wait. A n interesting study might be to compare the numbers of newspaper stories provincially over time with the rates of reporting missed care. 132 The reporting of cost as a barrier to health care is of great concern. In Canada, we purport to have a universal health care system that requires no out of pocket expenses for the patient. Yet, cost is reported as a reason for missed care by 11.1% of those who report missed health care. Cost is most likely to be reported by young adults (12.5%) then seniors (11.6%), followed closely by adults (11.0%) among those who miss care. The reporting of cost as a reason for missed care is also directly related to income adequacy, with 19.2% of those in the lowest income adequacy category, 18.1% of the lower middle, 17.4% of the upper middle, 10.5% of the upper middle, and 5.5% of the highest income adequacy groups reporting it as a reason for missed care. It is discouraging that people of all income categories are reporting cost as a barrier to health care, and more so that it disproportionately affects those in the lower income adequacy categories. It is unclear from the available data what costs are problematic. What kinds of costs are being referred to? How large or small are these costs? H o w accurate are the perceptions of anticipated costs on the part of young adults-or any other age group? Are they fearful of physician costs or medication costs? Since the question regarding missed care only refers to "health care", it may have been interpreted to include uninsured services such as prescription drug medication, physiotherapy, dentistry and so on. It is of the utmost importance that more research is done to understand how cost is a barrier to health care access, and to find ways to reduce inequity in access based on income. Wait times can be considered a systemic issue for concern, as can the 16.1% of people who missed care reporting care not being available at the time required, and the 10.6% reporting that the care they needed was not available in their area. Improvement to the hours and days of service availability to include evenings and weekends could go a long way to reduce this barrier. Also, providing more services to remote areas, or funded transportation options to access needed services from remote locations would reduce missed care as well . This may also reduce the prevalence of missed care for those who report they didn't get around to it, were too busy, or 133 have personal or family obligations that prevent them from seeking care- issues particularly salient for young adults due to their less stable and work and responsibility-filled time. As other studies have suggested (Sanmartin et al., 2004; Dubow et al., 1990; Kapphahn, Wilson, & Klein, 1999) several barriers to adequate health care can be attributed to the physician-patient relationship. Improvements in doctor patient relations and communication would assist in reducing the prevalence of missed care among the 9.7% of those who miss care because they 'felt the care was inadequate', the 5.3% who said they missed care that was 'thought unnecessary by their doctor', and the 0.5% who have language problems leading to missed care. It has been shown that from a patient's perspective, the most significant expressions from physicians include: "exploring the presenting problem thoroughly, expressing empathy and caring, handling patients' feelings, using comforting and listening skills, being attentive to verbal cues, using open-ended questions, involving patients in decisions, inspiring trust, and expressing interest in patients' opinions." (LindenSmith, 1998). Studies have further indicated that patient satisfaction with their physician leads to increased compliance, less physician changing, and a higher likelihood of seeking care at an appropriate time (Wolliscroft et al., 1994). On the other hand, poor communication has been cited as one the leading causes of problems in the physician-patient relationship (LindenSmith, 1998). It is likely that improvements in physician-patient communication would also substantially reduce the proportion of individuals reporting missed health care. It would be prudent to begin to address the needs of young adults (and others) in terms of their access to care. A deliberate focus on the health of young adults- to determine their real or perceived needs is called for. There may be ways to promote social support and sense of belonging to a local community for young adults. Regional health authorities could do more to advertise lists of available primary care physicians accepting new patients, and begin campaigns to encourage continuity of care. Physician training should also stress the importance of 134 continuity of care, encouraging physicians to maintain relationships with patients over time. Bi l l ing practices should move away from a "one problem at a time" model to a salaried system (now being practiced more commonly in Quebec and Ontario) to facilitate better care and relationship building with patients. A "treat-them-when-you-see-them" approach, meaning that a physician should treat all presenting issues at one visit rather than requesting the patient to return again, would surely reduce the rate of missed health care being reported. Universities, colleges, and places of employment could also help their students and new employees in learning where to access primary care. Also , young adults (and others) should not be reporting cost as a barrier to needed health care. It is also of the utmost importance to address the systemic issues that are reported for missed care. Concerns have been raised about the narrowing of services provided by family doctors in Canada (Tepper, 2004). There is a great deal of literature addressing wait times and it is still rather a murky business to assess wait times in Canada (Canadian Institute for Health Information, 2006). There is a growing body of research trying to understand, and consolidate definitions of wait times, but the debate is too large and complex to address here. Yet, wait times must be addressed as they are consistently the most common reason given for missed health care. Moreover, issues of cost for primary care need attention. Ensuring that cost is not a barrier to primary care should be provincial and federal government priorities. Therefore, research into what costs respondents are referring to is imperative, and monitoring of costs associated with primary care is essential. Finally, the use of "missed care" or "unmet health care needs" should be used with some scepticism as a way to measure whether the health care needs of the population are being addressed. While the client perspective is essential to understanding health care services access, and the data presented in this study and others should not go unnoticed, there should also be an awareness that for many subpopulations (such as those l iving in rural communities, immigrants, 135 and men), there may be under-reporting of missed care (or conversely, there may be "over-reporting" by their counterparts) due to different expectations. More research must be done to understand these phenomena and better ways to assess missed health care need to be developed. 136 6.0 C O N C L U S I O N While Canada does have a universal health care system, access to that system is not equitably distributed amongst the population. Inequity in access occurs on the basis of income, sex, health status, social support, and life course stage. It's evident that young adults are different from adolescents, older adults, and seniors in access to primary care as they have a higher prevalence of missed care. It's not clear i f these are differences in actual missed health care, or expectations of primary care. Yet, research on the demographic changes for young adults, and the literature on emerging adulthood, show that delayed adulthood, and changes in timing and sequencing of the transitions to adulthood leave young adults in less stable, financially insecure, and socially and institutionally isolated situations. This study suggests that those characteristics of young adulthood today have consequences for young adults' access of primary care. Changes in models of primary care services have led to a decline in comprehensive care models, and moves towards drop-in clinics that are supposed to increase access. However, not having a regular doctor is associated with reporting missed care. In conclusion, we may be seeing evidence of young adults at risk of not receiving timely or adequate primary care. 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