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Self-reported physical and mental health status and quality of life in adolescents: a latent variable… Sawatzky, Richard; Ratner, Pamela A; Johnson, Joy L; Kopec, Jacek A; Zumbo, Bruno D Feb 3, 2010

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RESEARCH Open AccessSelf-reported physical and mental health statusand quality of life in adolescents: a latent variablemediation modelRichard Sawatzky1*, Pamela A Ratner2, Joy L Johnson2, Jacek A Kopec3, Bruno D Zumbo4AbstractBackground: We examined adolescents’ differentiation of their self-reported physical and mental health status, therelative importance of these variables and five important life domains (satisfaction with family, friends, livingenvironment, school and self) with respect to adolescents’ global quality of life (QOL), and the extent to which thefive life domains mediate the relationships between self-reported physical and mental health status and globalQOL.Methods: The data were obtained via a cross-sectional health survey of 8,225 adolescents in 49 schools in BritishColumbia, Canada. Structural equation modeling was applied to test the implied latent variable mediation model.The Pratt index (d) was used to evaluate variable importance.Results: Relative to one another, self-reported mental health status was found to be more strongly associated withdepressive symptoms, and self-reported physical health status more strongly associated with physical activity. Self-reported physical and mental health status and the five life domains explained 76% of the variance in global QOL.Relatively poorer mental health and physical health were significantly associated with lower satisfaction in each ofthe life domains. Global QOL was predominantly explained by three of the variables: mental health status (d =30%), satisfaction with self (d = 42%), and satisfaction with family (d = 20%). Satisfaction with self and family werethe predominant mediators of mental health and global QOL (45% total mediation), and of physical health andglobal QOL (68% total mediation).Conclusions: This study provides support for the validity and relevance of differentiating self-reported physical andmental health status in adolescent health surveys. Self-reported mental health status and, to a lesser extent, self-reported physical health status were associated with significant differences in the adolescents’ satisfaction withtheir family, friends, living environment, school experiences, self, and their global QOL. Questions aboutadolescents’ self-reported physical and mental health status and their experiences with these life domains requiremore research attention so as to target appropriate supportive services, particularly for adolescents with mental orphysical health challenges.BackgroundHealth researchers and providers increasingly recognizethe importance of obtaining information about adoles-cents’ perspectives of their quality of life (QOL) [1-10].Several instruments have been developed for the measure-ment of adolescents’ QOL to examine the impact of healthcare interventions, supportive services, and healthpromotion initiatives [e.g., [3,8,11,12]]. These instrumentstypically consist of subscales that represent experienceswith various conditions in life (a.k.a. life domains) that areof general relevance to adolescents, including their per-ceived: (a) self (e.g., self-esteem), (b) relationships withfriends and family, (c) experiences at school, and (d) livingenvironment [13,14]. Often, the subscale scores are com-bined to obtain an overall, or global, QOL score. Otherinstruments include one or more general questions for themeasurement of adolescents’ global QOL in terms of theirhappiness or satisfaction with their lives. Despite the* Correspondence: rick.sawatzky@twu.ca1School of Nursing, Trinity Western University, 7600 Glover Road, Langley,British Columbia (BC) V2Y 1Y1, CanadaSawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17© 2010 Sawatzky et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly cited.increasing availability of such instruments, the relation-ships among adolescents’ self-reported health status (a.k.a.perceived or self-rated health status), their experienceswith particular conditions in life, and their global QOLhave not been examined extensively.Several conceptual models have been developed todescribe the relationships between health and QOL inadults [15-22]. Most of these models emphasize asses-sing QOL from the perspective of the individual, andare based on the general proposition that alterations inhealth status affect other conditions in life (lifedomains), such as physical and psychological function-ing, and social and environmental conditions, that arerelevant to a person’s QOL [e.g., [15,20-22]]. For exam-ple, Wilson and Cleary [15] introduced a very usefulmodel of health and QOL wherein alterations in one’sphysiological condition (e.g., disease) result in physicaland psychological changes that affect functional status,general health perceptions, and global or overall QOL.Concepts pertaining to characteristics of the individual(e.g., motivation and values) and characteristics of theenvironment (e.g., social support) are also taken intoaccount. However, the relationship between self-reportedhealth status and QOL is not expounded in the model;in particular, it is not clear how self-reported health sta-tus relates to other life domains relevant to QOL.There is compelling empirical support for the associa-tions between self-reported health status and QOL in gen-eral adult populations. A meta-analysis by Smith, Avis,and Assmann [23] showed that variation in QOL isexplained by several life domains that are affected by dif-ferences in physiological health status (e.g., the presence ofdisease) and symptom severity. Their “model of the deter-minants of quality of life” (p. 448) is based on the proposi-tion that the life domains mediate the associationsbetween symptom severity and physiological health status,and QOL. Their regression analyses revealed that, relativeto physical and social function, mental health status wasby far the most important variable explaining QOL. Beckieand Hayduk [24], using structural equation modeling,similarly demonstrated that indicators of health statuscould be viewed as explanatory variables of QOL. Basedon a study of adults who underwent coronary arterybypass graft surgery, they found that the eight health indi-cators measured by the Short-Form 36-item instrument(SF-36) [25] explained 67% of the variance in QOL, andthat the effects of general health perceptions and mentalhealth status were the most substantial. They concludedthat “quality of life can be considered as a global personalassessment of a single dimension, which may be causallyresponsive to a variety of other distinct dimensions includ-ing dimensions such as health” (p. 281).Several other researchers have examined the associationsamong self-reported health status, various life domains,and global QOL in adult populations [e.g., [26-28]]. How-ever, information about these associations in adolescentpopulations is relatively sparse. The potential relevance ofself-reported health status with respect to adolescents’QOL was shown in a study by Zullig et al. [29] who foundthat, in a sample of high-school students in South Carolina(U.S.A.), adolescents’ self-reported health status was mod-estly correlated (r ranging from .09 to .22) with five lifedomains (satisfaction with family, friends, school, livingenvironment, and self) and overall life satisfaction (r =.21). Other research has shown that adolescents’ self-reported health status is associated with various healthindicators, including physical activity, nutritional status,health-risk behavior, and physical disability [29-32].Although these studies provide support for the measure-ment of adolescents’ self-reported general health status,the differentiation of adolescents’ self-reported physicaland mental health status has not been extensively exam-ined. Consequently, it is not known to what extent adoles-cents differentiate their physical and mental health statusand whether this differentiation is relevant with respect totheir global QOL and particular life domains.Study objectivesWe designed a study to: (a) validate adolescents’ differen-tiation of their self-reported physical and mental healthstatus and (b) examine the associations of these variableswith global QOL and several relevant life domains,including adolescents’ satisfaction with their family,friends, living environment, school, and self. With respectto the first objective, we hypothesized that, relative to oneanother, self-reported physical health status would bemore strongly associated with physical activity, and self-reported mental health status with depressive symptoms.Drawing on the previously mentioned conceptual modelsand empirical research on health and QOL, we furthersought to obtain information about (a) the relativeimportance of self-reported physical and mental healthstatus with respect to adolescents’ global QOL and sev-eral life domains and (b) the extent to which the relation-ships among self-reported physical and mental healthstatusand global QOL are mediated by the life domains(see Figure 1). Global QOL is viewed here as a unidimen-sional construct that pertains to individuals’ satisfactionwith, or appreciation of, their lives overall[18,30-32]. Thelife domains represent adolescents’ satisfaction with var-ious conditions in life that have the potential to contri-bute to their global QOL [33].MethodsSamplingThe data were obtained via the British Columbia YouthSurvey on Smoking and Health 2 (BCYSOSHII), a cross-sectional health survey that was conducted in 2004 toSawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 2 of 11obtain information about tobacco dependence, drug andhealth-related behavior, and quality of life in adolescentsin grades 7 to 12 in schools in the province of BritishColumbia (BC), Canada. The methods of this surveyhave been described in detail in several published stu-dies [e.g., [34-39]]. The survey avoided two regional dis-tricts within the province that were known to have verylow smoking prevalence rates so as to be cost-efficientin assembling a sample of adolescents that used tobacco(the primary purpose of the principal study). Nineteenof the 60 school districts in BC were sampled to achievemaximal geographic coverage of regional districts(remote and sparsely populated areas were not sur-veyed). Fourteen of the school district administratorsprovided permission for their schools to participate.This resulted in a sample of 89 eligible schools, ofwhich49 (42 secondary schools, 5 alternative schools, and 2middle schools) agreed to participate. Passive parentalconsent was obtained by providing parents with lettersthat informed them of the survey. Ethical approval wasgranted by the Behavioural Research Ethics Board of theUniversity of British Columbia.The survey questionnaire was administered byresearch assistants during class-time hours in pen andpaper format (79.6%) or through a computer-based for-mat (20.4%). The format was primarily determined bythe availability of computers in the various schools. Lessthan 1% of the students refused to participate and theresponse rate within schools was 84%, on average (non-response was mostly due to student absenteeism)[34,36]. The resulting sample consisted of 8,225 adoles-cents (smokers and non-smokers).MeasurementSelf-reported physical and mental health status weremeasured using two questions, “How would you rateyour physical health?” and “How would you rate youremotional or mental health?” with the followingresponse options, which were taken from the generalhealth status question of the SF-36 [25] and which arewidely used in the national population health surveys ofmany countries: “excellent” (coded as “5”), “very good,”“good,” “fair,” or “poor” (coded as “1”). The validity ofmeasuring adolescents’ self-reported general health sta-tus in this manner is supported by observed associationswith various other health status indicators, includingphysical activity, nutrition, health-risk behavior, andphysical disability [40-43]. Study findings have consis-tently revealed that a relative increase in adolescents’self-reported general health status is associated with lesshealth-risk behavior and fewer days of limited activity[41,43].To validate adolescents’ differentiation of their physi-cal and mental health status, we examined the relativeimportance of these variables with respect to depressivesymptoms and the frequency of physical activities.Figure 1 Structural model of the relationships between self-reported physical and mental health status, domains of life satisfaction,and global QOL. Notes: N = 6,932, WLSMV c2 (178) = 2,083.22 - 2,010.02, RMSEA = .049, CFI = .951. The variances of all latent factors were fixedat 1.0 for model identification. The measurement structures of the latent factors for each of the life domains are identical to those reported bySawatzky et al. [37] (these are not shown here because of space limitations). All parameter values are standardized. The correspondingunstandardized parameters are provided in Table 4. 1Self-reported physical and mental health status were modeled as two ordinal variables witha latent factor that accounts for their correlation (not shown here). *p < .05.Sawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 3 of 11Depressive symptoms were measured using 12 itemsfrom the Center of Epidemiologic Studies DepressionScale (CES-D) [44]. The adolescents were asked: “Howoften have you felt or behaved in the following mannerin the past week (7 days)?” (e.g., “hopeful about thefuture,” “happy,” “lonely,” “sad”). The CES-D providesfour response options ranging from “rarely or none ofthe time (less than one day)” (coded as “0”) to “most orall of the time (5-7 days)” (coded as “3”). The totalscore, with a possible range of 0 (no depressive symp-toms) to 36, was used in the analysis. The estimatedreliability of the 12 items is .87 in this sample (based onthe ordinal Cronbach alpha reliability estimate [45]).Physical activity was measured using the following ques-tion adapted from several large surveys (e.g., The USAYouth Risk Behavior Survey [46] and The Ontario DrugUse Survey [47]): “On how many of the last 7 days didyou exercise or participate in sports activities for at least20 minutes that made you sweat and breathe hard? Ifnone, enter ‘0’ days. Please include activities such as bas-ketball, jogging, swimming, cross-country skiing, hockey,or dance, that you participated in either at school oroutside of school.”An abridged version of Huebner’s MultidimensionalStudents’ Life Satisfaction Scale (MSLSS) [48] was usedto measure adolescents’ satisfaction with five lifedomains, including their family (4 items), school (4items), living environment (2 items), friends (4 items)and self (4 items) [37]. The original MSLSS consists of40 items, of which 10 are negatively worded. The psy-chometric analyses reported by Sawatzky et al. [37]revealed that the adolescents may not have interpretedand responded to all items in the same way. There wereinconsistencies in the responses to the negativelyworded items and several other items. An abridged 18-item version was developed by identifying those itemsthat were found to be most invariant (all positivelyworded). Confirmatory factor analyses (CFA) providedsupport for its construct validity when allowing for afew theoretically defensible modifications [37]. Thesame measurement structure was used to represent thefive life domains as latent factors in the study reportedherein. The ordinal Cronbach alpha reliability estimates[45] of the abridged subscales with four items were ≥.80 in this sample. A six-point ordinal response format(with response options ranging from “strongly disagree”(coded as “1”) to “strongly agree” (coded as “6”)) wasused [49].Global QOL was measured with two items. The ado-lescents were asked to appraise their QOL using a pic-ture of an eight-rung ladder (Cantril’s self-anchoringladder [50], referred to here as the QOL-ladder) (seeFigure 2). The bottom run was coded as “1” and the topas “8”. The adolescents also were asked to rate theiragreement with the statement, “I am satisfied with myquality of life” with four response options ranging from“strongly disagree” (coded as “1”) to “strongly agree”(coded as “4”). General questions of this nature, includ-ing Cantril’s self-anchoring ladder, have been widelyused in surveys for the measurement of various conceptssuch as global QOL [51-53]. A latent factor explainingthe variance in both of these variables was used torepresent global QOL.The adolescents were asked to indicate their age andsex, and to answer several questions about their ethnicidentity and living arrangements. Ethnic identity wasdetermined by asking, “How would you describe your-self?” The 12 response options were adapted from Sta-tistics Canada’s [54] classification of “visible minorities”(e.g., “white/Caucasian,” Aboriginal/First Nation, Chi-nese, South East Asian). The adolescents selected one ormore responses, which were subsequently grouped as:“white/Caucasian,” Asian (including Chinese, Japanese,Korean, South East Asian, and Filipino), Aboriginal/FirstNation, and “other.” With respect to their livingarrangements, the adolescents were asked, “Which par-ent or parents do you currently live with most of thetime?” with eight response options (i.e., mother, father,step-mother, step-father, guardian(s), foster parent(s),grandparent(s), and other please specify).Statistical methodsStructural equation modeling was used to examine thehypothesized relationships by fitting a latent variablemediation model to the sample data (see Figure 1). Thevariances of the latent factors were specified to equalone to avoid indeterminancy and to set the metric ofthe latent factors [55]. Polychoric correlations were usedto avoid obtaining biased parameter estimates due tothe ordinal distributions of the observed variables[56-58]. The MPlus 5.2 software [59] was used to esti-mate the model parameters by specifying a probit linkfunction and using a mean and variance adjustedweighted-least squares estimation method (WLSMV)suitable for ordinal data [60]. Model fit was evaluatedwith several global fit indices, and by comparing the dif-ferences between the implied and the observed polycho-ric correlation matrices. Adequate model fit was definedby a root mean square error of approximation (RMSEA)of < .06 [61] and a comparative fit index (CFI) of ≥ .95[62]. In addition, the pattern and magnitudes of the resi-dual correlations were examined to locate any specificareas of misfit [63,64]. The percentage of residual corre-lations with absolute values greater than .10 is providedas a summary of this direct comparison.The relative importance of the explanatory variableswas determined by the Pratt index (d) [65], which quan-tifies each variable’s contribution to the explainedSawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 4 of 11variance (irrespective of the magnitude of the R-squared), measured as a percentage. The extent towhich the two relationships between global QOL andphysical and mental health status were mediated by thelife domains was evaluated as the division of the indir-ect-effects (mediated by the life domains) and the totaleffect (the sum of the direct- and indirect-effects for theassociations between global QOL and physical and men-tal health status), expressed as a percentage [66]. Thestandard error of the indirect effects was calculatedusing the Delta method, which is similar to theapproach used in the Sobel test [67].Of the 8,225 adolescents, 920 did not provide responsesto any of the MSLSS questions. The analysis was limitedto those who responded to the global QOL items, theitems measuring mental or physical health status, and atleast one of the MSLSS items (N = 6,932). Multiple impu-tation (MI) [68] was used to impute any remaining miss-ing responses (2.5% imputed data). The results werecompared with those obtained using MI for the subsampleof adolescents who provided a value for at least one of theanalysis variables (N = 8,174; 13.9% imputed data). TheSAS 9.2 software package [69] was used to create 10imputed datasets for the MI analyses, following the guide-lines offered by Allison [70] and Enders [71], to assessconvergence and to incorporate auxiliary variables (i.e.,demographic variables (sex, ethnicity, school grade), symp-toms of depression, and two variables pertaining to theadolescents’ experiences at school).ResultsSample descriptionThe sample consisted of an approximately equal propor-tion of boys and girls in grades 7 through 12 (see Table1). The average age was 15.2 years (SD = 1.5, n = 8,054)with 7,964 adolescents being between 12 and 18 years.Although most of the adolescents who identified theirethnicity (n = 7,882) self-identified as “white/Caucasian”(72.6%), the sample also included Aboriginal adolescents(16.5%), Asian adolescents (Chinese, Japanese, Korean,Filipino, or South-East Asian) (5.8%), and adolescentsbelonging to one or more other groups (5.1%). A size-able percentage (17.3% of 7,994 adolescents) indicatedregularly speaking a language other than English, and6.9% of 8,058 reported being born in a country otherthan Canada.Most of the adolescents agreed or strongly agreed tobeing satisfied with their QOL (82.3% of 7,606 adoles-cents) (see Table 1). The mode of the QOL-ladderresponses was at level 6 of 8 rungs (36.7%), with 11.9%of the adolescents reporting the best possible life, and14.0% providing a rating at or below the middle of thescale (≤ 4) (n = 7,675).The measurement of self-reported physical and mentalhealth statusThe joint- and marginal-distributions of self-reportedphysical and mental health status are provided in Table2. The corresponding conditional distributions providesupport for adolescents’ ability to differentiate thesevariables. For example, 9.5% of the adolescents whorated their physical health as good or better rated theirmental health as fair or poor, and 5.3% of the adoles-cents who rated their mental health as good or betterrated their physical health as fair or poor. The polycho-ric correlation was .55, indicating a shared variance ofonly 30% among these two (underlying) variables. Withrespect to the differentiation of mental and physicalFigure 2 Quality of life ladder. Notes: Derived from Cantril’s self-anchoring ladder [50]. An error resulted in 8 rungs being presented in thepaper-based version whereas 10 rungs were presented in the computer version. To remedy this, we rescaled the QOL-ladder for the computer-and paper-based versions to their common denominator by multiplying the computer-based version of the QOL-ladder by 0.8 and rounding theresulting scores to zero decimals.Sawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 5 of 11health status (see Table 3), we found that 94% (d, PrattIndex) of the explained variance in depressive symptoms(R2 = 35.5%) could be attributed to mental health status(the remaining 6% was attributed to physical health sta-tus). Conversely, relative to self-reported physical healthstatus, self-reported mental health status accounted foronly 18% of the explained variance in physical activity(R2 = 7.7%) (see Table 3).The associations between health status and quality of lifeThe hypothesized model with the life domains operatingas mediators of the relationships between self-reportedphysical and mental health status and global QOLresulted in acceptable overall fit (WLSMV c2 rangingfrom 2,083.22 to 2,010.02 for the 10 MI datasets (N =6,932), RMSEA = .049, CFI = .951, residual correlationsranging from -.07 to .07) (see Figure 1). Satisfactionwith family, friends, school, living-environment, and self,and self-reported physical and mental health statusexplained 76.1% of the variance in global QOL.Although self-reported physical and mental health statuswere bivariately significantly correlated with global QOL(r = .49 and .70, respectively), their associations weresubstantially smaller, albeit statistically significant, in themultivariate model (see Table 4). The life domains alsowere bivariately significantly correlated with globalQOL. However, relatively small and statistically non-sig-nificant regression coefficients were obtained for satis-faction with friends and satisfaction with school in themultivariate model (see Table 4). These variablesaccounted for less than 2% (d, Pratt Index) of theexplained variance relative to the other variables in themodel (see Table 4). Global QOL was mostly explainedby satisfaction with self (d = 42%), self-reported mentalhealth status (d = 30%), and satisfaction with family (d= 20%). Self-reported physical health status accountedfor only 3% of the explained variance.Self-reported physical and mental health status weresignificantly correlated with each of the life domains(rphysical health ranging from .22 to .45; rmental health ran-ging from .27 to .54), and they predominantly explainedsatisfaction with self (R2 = 33.0%), and, to a lesserextent, satisfaction with family (R2 = 16.9%), friends (R2= 11.3%), and living environment (R2 = 14.2%) (seeTable 5). Only 7.9% of the variance in satisfaction withschool was explained by self-reported physical and men-tal health status. Relative to self-reported physical healthstatus, most of the variance in each of the life satisfac-tion dimensions could be attributed to the adolescents’self-reported mental health status (d ranging from 68%to 87% for each of the life domains) (see Table 5).The parameters for the relationships between physicaland mental health status, the life domains, and globalQOL were used to determine the magnitude of the totaland the indirect relationships between physical andmental health status and global QOL as mediated byeach of the life domains (see Table 6). The standardizedtotal effect on global QOL was larger for self-reportedmental health status (b = .61), while adjusting for self-reported physical health status, than for self-reportedphysical health status (b = .17), while adjusting for self-reported mental health status. These relationships werepartially mediated by the life domains (67.8% total med-iation for physical health and 45.4% total mediation formental health status). The relationships between the twohealth status variables and global QOL were primarilymediated by satisfaction with self (54.0% mediation forself-reported physical health and 29.1% mediation forself-reported mental health) and, to a lesser extent, bysatisfaction with family (10.8% mediation for self-reported physical health and 13.7% mediation for self-reported mental health).DiscussionThis study provides support for (a) the notion that ado-lescents can differentiate between physical and mentalhealth when they provide reports of their health statusand (b) the relevance of this differentiation with respectto five life domains and global QOL. The resultsTable 1 Sample descriptionVariable PercentageMinority status (N = 7,882)No, “white” 72.6%Yes, Asian 5.8%Yes, Aboriginal 16.5%Other or mixed 5.1%Sex (N = 8,163)Male 49.8%Female 50.2%Grade (N = 8,074)Grades 7 or 8 23.2%Grade 9 19.4%Grade 10 23.7%Grade 11 21.1%Grade 12 or “other” 12.6%Living arrangements (N = 7,582)Lives with mother and father 59.9%Lives with mother and not father 25.7%Lives with father and not mother 7.8%Does not live with mother or father 6.7%Satisfied with quality of life (N = 7,606)Strongly disagree 4.6%Disagree 13.0%Agree 52.7%Strongly agree 29.6%Percentages may not sum to exactly 100% due to rounding.Sawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 6 of 11revealed that relatively poorer self-reported physical andmental health status were significantly associated withlower global QOL and lower satisfaction with each ofthe life domains. The adolescents’ global QOL was pre-dominantly explained by mental health status and bytheir satisfaction with self and family. Satisfaction withself and family were the main mediating variables forthe relationships between mental health status (45.4%total mediation) and physical health status (67.8% totalmediation) and global QOL.Other studies have shown that self-reported generalhealth status is significantly associated with health-pro-moting and health-risk behavior [40-43] and with var-ious life domains and global QOL [29]. Our studycontributes to this area of research by providing preli-minary support for the validity and the relevance of dis-tinguishing between adolescents’ self-reports of theirphysical and mental health status. The findings suggestthat, relative to one another, self-reported mental healthstatus is more strongly associated with depressive symp-toms and physical health status with physical activity.Although further research is needed to examine thevalidity and relevance of these variables with respect toother research objectives (e.g., their associations withparticular health-risk behavior), the current findingssuggest that the use of two self-report items for themeasurement of adolescents’ physical and mental healthstatus could contribute valuable information in popula-tion-based adolescent health surveys.There were substantial differences in the associationsbetween self-reported physical and mental health statusand adolescents’ global QOL and the five life domains.The correlations with self-reported mental health statuswere greater than were those with physical health status.This finding is congruent with a study by Zullig et al.[29] who found that, relative to the self-reported numberof days with poor physical health, the number of poormental health days was more strongly correlated withadolescents’ overall life satisfaction (r = -.27 versus -.15)and their satisfaction with their family (r = -.25 versus-.14), friends (r = -.10 versus -.07), living environment(r = -.15 versus -.10), school (r = -.15 versus -.12) andtheir self perception (r = -.29 versus -.21). However, inour study, the correlations with global QOL (rphysical health= .49; rmental health = .70), and each of the life domains(rphysical health ranging from .22 to .45; rmental health rangingfrom .27 to .54;) were relatively stronger. It is possiblethat the measurement of self-reported physical and men-tal health status (rather than the number of poor physicaland mental health days), and the use of the abridgedMSLSS for the five life domains (rather than the use ofsingle items for each of the life domains), resulted ingreater sensitivity to detect these associations.In addition to these bivariate associations, our studyprovides information about the relative importance ofself-reported physical and mental health status and thefive life domains in explaining global QOL inTable 2 Joint and marginal distributions of self-reported physical and mental health statusMental healthPhysical health Excellent Very good Good Fair Poor Totalexcellent 1,367 (17.6%) 502 (6.4%) 156 (2.0%) 49 (0.6%) 30 (0.4%) 2,104 (27.0%)very good 876 (11.3%) 1,333 (17.1%) 563 (7.2%) 160 (2.1%) 39 (0.5%) 2,971 (38.2%)good 316 (4.1%) 615 (7.9%) 739 (9.5%) 315 (4.0%) 82 (1.1%) 2,067 (26.6%)fair 53 (0.7%) 89 (1.1%) 181 (2.3%) 167 (2.1%) 52 (0.7%) 542 (7.0%)poor 15 (0.2%) 7 (0.1%) 18 (0.2%) 25 (0.3%) 35 (0.5%) 100 (1.3%)total 2,627 (33.7%) 2,546 (32.7%) 1,657 (21.3%) 716 (9.2%) 238 (3.1%) 7,784All percentages are of the total sample.Table 3 Relationships between self-reported physical andmental health status and depressive symptoms andfrequency of physical activityVariable b SE b b r dDepressive symptoms (N = 7,985; R2 = 35.5%)Physical health -0.46 0.09 -.06 -.33 6%Mental health -3.73 0.08 -.56 -.59 94%Physical activity (N = 7,033; R2 = 7.7%)Physical health 0.68 0.04 .24 .27 82%Mental health 0.18 0.03 .07 .19 18%Notes: r = bivariate polyserial correlations, d = Pratt Index. All parameterestimates are statistically significant (p < .05).Table 4 Relative importance of variables explainingglobal QOLVariable b SE B b r dFamily 0.29* 0.03 .23* .66* 20%Friends -0.02* 0.02 -.02* .51* 0%School 0.02* 0.01 .02* .40* 1%Living environment 0.05* 0.02 .05* .56* 4%Self 0.62* 0.03 .41* .78* 42%Mental health 0.26* 0.01 .33* .70* 30%Physical health 0.04* 0.01 .05* .49* 3%Notes: r = bivariate correlation with the latent global QOL variable, d = Prattindex. N = 6,932. R2 = 76%. * p < .05.Sawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 7 of 11adolescents. The results revealed that self-reported phy-sical health status contributed minimally to global QOLwhen controlling for the other variables in the model;its association with global QOL was significantly con-founded by self-reported mental health status and thefive life domains. Self-reported mental health status wasrelatively more important with respect to each of thelife domains, and it was the second most importantexplanatory variable for global QOL. These findings pro-vide support for attending to the mental health needs ofadolescents.With respect to each of the life domains, we foundthat most of the variance in global QOL could be attrib-uted to the adolescents’ satisfaction with themselves andtheir families. The associations between satisfaction withfriends and school and global QOL were not statisticallysignificant in the multivariate model. These findings arecongruent with a study by Gilman [72] who found that,in a sample of 321 high-school students in a Southeast-ern US state, the associations between satisfaction withfriends and school and global QOL were relatively smallwhen controlling for the other life domains. It is possi-ble that adolescents’ satisfaction with their friends andtheir school is associated with their satisfaction withtheir family, and that these associations are thereforeconfounded in the multivariate model. This is an impor-tant area for further study.An important theoretical conclusion to be drawn fromthese findings is that self-reported physical and mentalhealth status and the life domains can be viewed as con-ditions that contribute to global QOL in adolescents.These relationships are fundamentally different fromthose implied by the common practice of deriving globalQOL scores from the combined scores of particular lifedomains. Many multidimensional instruments designedto measure QOL are based on the assumption thatscores pertaining to various life domains can be com-bined so as to obtain an overall (general) QOL score.For instance, it has been argued that an overall QOLscore could be obtained by averaging the scores of thefive life domain subscales of the MSLSS [49,73,74]. Thetheoretical premise of this approach is that the experi-ences in the various life domains reflect, or arise from, acommon source, labeled global QOL. This premise isnot congruent with the previously noted conceptualiza-tion of life domains as conditions that contribute toQOL. Our analyses demonstrate a different approachthat is congruent with the conceptualization of QOL asa global concept that is partially explained by variouscontributing conditions, such as health status and peo-ple’s experiences with various other aspects of life (lifedomains) [23,24,26-28,32,33].There are several limitations to this study that mustbe taken into account. First, the cross-sectional natureof this analysis does not warrant conclusive statementsabout the causal nature of the relationships. ClaimsTable 5 Relative importance of variables explaining thedimensions of life satisfactionVariable b SE B b r dExplaining satisfaction with family (R2 = 16.9%)Physical health 0.05 0.01 .08 .27 13%Mental health 0.23 0.01 .36 .41 87%Explaining satisfaction with friends (R2 = 11.3%)Physical health 0.07 0.02 .09 .24 19%Mental health 0.24 0.01 .28 .33 81%Explaining satisfaction with school (R2 = 7.9%)Physical health 0.09 0.01 .11 .22 32%Mental health 0.17 0.01 .21 .27 68%Explaining satisfaction with living environment (R2 = 14.2%)Physical health 0.07 0.01 .09 .26 16%Mental health 0.28 0.02 .32 .37 84%Explaining satisfaction with self (R2 = 33.0%)Physical health 0.11 0.01 .22 .45 30%Mental health 0.22 0.01 .43 .54 70%Notes: r = bivariate correlation with the latent variable, d = Pratt index. N =6,932. All parameter estimates are statistically significant (p < .05).Table 6 Mediation effects for physical and mental health status and global QOLEffect of self-reported physicalhealth status on global QOLEffect of self-reported mentalhealth status on global QOLMediating variable Bindirect SE B % mediation Bindirect SE B % mediationFamily1 0.01 0.00 10.8% 0.07 0.01 13.7%Friends1 -0.00 0.00 -1.0% -0.00 0.00 -0.8%Living1 0.00 0.00 2.8% 0.01 0.01 2.8%School1 0.00 0.00 1.2% 0.00 0.00 0.6%Self1 0.07 0.01 54.0% 0.14 0.01 29.1%Total indirect effects2 0.08 67.8% 0.22 45.4%Notes: Degree of mediation attributed to each satisfaction variable was calculated as the indirect effect for that variable divided by the total effect for physical ormental health status. N = 6,932.1 Indirect effect of physical or mental health status on global quality of life as mediated by one of the life domains.2 Sum of all indirect effects for physical and mental health status explaining global quality of life.Sawatzky et al. Health and Quality of Life Outcomes 2010, 8:17http://www.hqlo.com/content/8/1/17Page 8 of 11pertaining to the direction and causal nature of theserelationships require further investigation. Second,although care was taken to limit the bias that may haveresulted from missing data, it is possible that there weresystematic differences between the adolescents who didnot respond to all the items in comparison with thosewho did. Third, it is possible that different magnitudesof the observed relationships would be obtained in dif-ferent populations, or groups, of adolescents. Forinstance, the relative importance of the life domainsmay be different for boys and girls or for adolescentsfrom different age-groups or cultural or socio-economicbackgrounds. We therefore recommend further researchto examine the differences in the magnitudes of theassociations between health status, important lifedomains, and global QOL in different adolescentpopulations.ConclusionsThis study provides support for a conceptual model ofself-reported physical and mental health status and sev-eral life domains that contribute to adolescents’ globalQOL. Support is also provided for the use of distinctitems to measure self-reported physical and mentalhealth status in adolescent population health surveys.Mental health status and, to a lesser extent, physicalhealth status were associated with significant differencesin the adolescents’ appraisals of their family, friends, liv-ing environment, school experiences, self, and their glo-bal QOL. Questions pertaining to these important lifedomains require more attention in health assessmentsand in population health research so as to target appro-priate supportive services for adolescents with mental orphysical health challenges.List of abbreviationsBCYSOSH II: British Columbia Youth Survey on Smok-ing and Health 2; MSLSS: Multidimensional Students’Life Satisfaction Scale; QOL: Quality of life; b: Standar-dized regression coefficient; b: Unstandardized regres-sion coefficient; CFI: Comparative fit index; d: Prattindex; LR: Likelihood ratio; OR: Odds ratio; RMSEA:Root mean square error of approximation; r: Correla-tion; SE: Standard error; SD: Standard deviation;WLSMV: Weighted least squared, mean and varianceadjusted.AcknowledgementsThis research was completed with support for doctoral research from theCanadian Institutes of Health Research (CIHR), the Michael Smith Foundationfor Health Research (MSHFR), and the Canadian Nurses Foundation. Dr.Kopec and Dr. Ratner hold Senior Scholar Awards from the MSFHR and Dr.Johnson holds a CIHR Investigator Award. Funding for the survey researchwas provided by the CIHR (grant #: MOP-62980).Author details1School of Nursing, Trinity Western University, 7600 Glover Road, Langley,British Columbia (BC) V2Y 1Y1, Canada. 2School of Nursing, University ofBritish Columbia, 302-6190 Agronomy Road, Vancouver, BC V6T 1Z3, Canada.3School of Population and Public Health, University of British Columbia, 5804Fairview Avenue, Vancouver, BC V6T 1Z3, Canada. 4Department of ECPS,Measurement, Evaluation & Research Methodology, Scarfe Building, 2125Main Mall, Vancouver, BC V6T 1Z4, Canada.Authors’ contributionsRS and PR designed and carried out the statistical analyses and drafted themanuscript. JJ was the principal investigator for the British Columbia YouthSurvey on Smoking and Health 2. 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