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Rural-urban migration patterns and mental health diagnoses of adolescents and young adults in British… Maggi, Stefania; Ostry, Aleck; Callaghan, Kristy; Hershler, Ruth; Chen, Lisa; D'Angiulli, Amedeo; Hertzman, Clyde May 13, 2010

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Maggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Open AccessR E S E A R C HResearchRural-urban migration patterns and mental health diagnoses of adolescents and young adults in British Columbia, Canada: a case-control studyStefania Maggi*1, Aleck Ostry2, Kristy Callaghan3, Ruth Hershler4, Lisa Chen4, Amedeo D'Angiulli1 and Clyde Hertzman4AbstractBackground: The identification of mental health problems early in life can increase the well-being of children and youth. Several studies have reported that youth who experience mental health disorders are also at a greater risk of developing psychopathological conditions later in life, suggesting that the ability of researchers and clinicians to identify mental health problems early in life may help prevent adult psychopathology. Using large-scale administrative data, this study examined whether permanent settlement and within-province migration patterns may be linked to mental health diagnoses among adolescents (15 to 19 years old), young adults (20 to 30 years old), and adults (30 years old and older) who grew up in rural or urban communities or migrated between types of community (N = 8,502).Methods: We conducted a nested case-control study of the impact of rural compared to urban residence and rural-urban provincial migration patterns on diagnosis of mental health. Conditional logistic regression models were run with the following International Classification of Diseases, 9th Revision (ICD-9) mental health diagnoses as the outcomes: neurotic disorders, personality disorder, acute reaction to stress, adjustment reaction, depression, alcohol dependence, and nondependent drug abuse. Analyses were conducted controlling for paternal mental health and sociodemographic characteristics.Results: Mental health diagnoses were selectively associated with stability and migration patterns. Specifically, adolescents and young adults who were born in and grew up in the same rural community were at lower risk of being diagnosed with acute reaction to stress (OR = 0.740) and depression (OR = 0.881) compared to their matched controls who were not born in and did not grow up in the same rural community. Furthermore, adolescents and young adults migrating between rural communities were at lower risk of being diagnosed with adjustment reaction (OR = 0.571) than those not migrating between rural communities. No differences were found for diagnoses of neurotic disorders, personality disorder, alcohol dependence, and nondependent drug abuse.Conclusions: This study provides some compelling evidence of the protective role of rural environments in the development of specific mental health conditions (i.e., depression, adjustment reaction, and acute reaction to stress) among the children of sawmill workers in Western Canada.BackgroundConsiderable theoretical debate has focused on the rela-tionships between the development of mental healthproblems among youth and the role played by environ-mental stressors such as acute traumatic events, chronicstrain and adversity, accumulation of stressful life events,and daily challenges [1-4]. The most notable factorsknown to have a profound impact on youth mental healthinclude exposure to neighborhood violence [5]; parentalchronic illness [6,7], and poverty and economic hardship[8]; as well as parental unemployment, which may addfurther stress in the form of increased parental alcoholintake, home violence, and child abuse [9].* Correspondence: Stefania_Maggi@carleton.ca1 Institute of Interdisciplinary Studies and Department of Psychology, Dunton BioMed Central© 2010 Maggi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.Tower Room 2210, Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, CanadaFull list of author information is available at the end of the articleMaggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 2 of 11Much evidence shows that several of these stressorsmay vary according to where individuals live. That is, theeconomy and social environment of the communitieswhere youth live may be associated with the degree towhich parents are able to find jobs, rely on the necessarynetworks of social support to cope with challengingtimes, and provide their children with opportunities forhealthy development (for comprehensive reviews, see[10,11]). Since the extent to which these stressors arepresent may differ between rural versus urban communi-ties, we explore whether exposure to urban or rural envi-ronments places youth and young adults at greater riskfor poor mental health outcomes.Mental health and ruralityResearch shows that youth and young adults often strug-gle with mental health problems such as depression, anxi-ety, and stress-related conditions. A recent World HealthReport estimated that 10%-20% of youth worldwide expe-rience one or more mental health disorders [12]. Severalstudies have also reported that youth who experiencemental health disorders are at greater risk of developingpsychopathological conditions later in life (e.g., [13,14]).These results suggest that in addition to increasing thewell-being of children and youth, the ability of research-ers and clinicians to identify mental health problemsearly in life may help prevent adult psychopathology.One of the issues that has stimulated much research onthe impact of community-level influences on mentalhealth is whether people living in urban environments areat greater or lesser risk than people living in rural envi-ronments. The question may have been motivated by thesocial construct of the rural idyll - a notion that has beenconsistently influential since the 1960s (see [15-17]) - thatis, the underlying discourse that rural areas promote apeaceful and harmonious lifestyle, whereas cities are gen-erally associated with chaos, noise, stress, and challeng-ing living conditions typical of large metropolitan areas[18,19]. Accordingly, one common expectation is thatexposure to peaceful rural environments should posi-tively impact people's mental health.Several studies have investigated whether or not thefeatures of rural communities that tend to evoke imagesof tranquility - such as beautiful landscapes, privacy fromneighbors, and harmony with nature - actually minimizemental health disorders [20-24]. Interestingly, older stud-ies tend to report that urban youth are at higher risk formental health problems, while more recent studies seemto suggest the opposite. For example, it has been reportedthat mental health disorders among adolescents fromrural communities are increasing to the point of equalingurban differences with regard to self-esteem of adoles-cents (with rural youth scoring lower than their urbancounterparts) and engagement with deviant leisurebehaviors such as drug and alcohol use (with rural youthbeing more likely to engage in such behaviors than urbanyouth). Despite some results indicating differences in themental health of youth from rural and urban communi-ties, many other studies have not detected significant dif-ferences [19,29-31].The contradictory results may be partly attributable tothe fact that what constitutes "rurality" versus "urbanity"is rarely explicit in studies [17]. In addition, most studiesare cross-sectional, focus on a limited number of mentalhealth conditions, or rely on self-report measures. Theseproblems reflect the practical difficulty of consideringcommunities as complex entities and, also, of dealingwith the dynamic time component involved in the devel-opment of mental health outcomes.Mental health and migration patternsIn addition to rurality or urbanity, one important butmostly neglected aspect that can also significantly impactmental health outcomes is the individual history ofmigration from one place to another, especially when theplace of origin differs significantly from the place ofarrival. In North American societies, a significant pro-portion of the population migrate at least once in a life-time, and many people change community of residencemultiple times. Some migrate from urban to rural com-munities (or vice versa), while others migrate withinurban communities or within rural communities only.For instance, census reports for 2006 indicate thatapproximately 14% of the Canadian population hadmigrated in the previous year, and 19% had migratedwithin the previous 5 years [32].The mobility of populations has been of interest toresearchers attempting to uncover the impact of migra-tion patterns on adolescent mental health. Studies havesuggested that adolescents who change residence showhigher rates of mental disorders. For example, McGeeand colleagues [18] found that adolescents who had fre-quent changes of residence were more likely to havehigher rates of mental health diagnoses and higher levelsof help-seeking, as well as lower levels of social compe-tence. These lower levels of social competence arethought to be related to difficulties in forming relation-ships with peers [18].A study conducted by Mullick and Goodman [31] on 5-10 year olds in Bangladesh found that migrating fromrural to urban communities had a negative impact onmental health. Dudley and associates [33] found thator exceeding those of urban youth [25], especially withrespect to drug and alcohol use and abuse [26,27]. Simi-larly, Gordon and Caltabiano [28] have shown rural-youth who migrate from urban to rural areas were morelikely to commit suicide than youth migrating from ruralto urban areas. Thus, there is a body of evidence that sug-Maggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 3 of 11gests that an individual's mental health can be influencedby migration.The purpose of the present study is to examinewhether, in addition to permanent settlement in urban orrural communities, migration patterns within the prov-ince of British Columbia (Canada) may also be linked tomental health diagnoses among adolescents and youngadults. We hope to contribute to the limited data and lit-erature about rural mental health among youth, since fewstudies have investigated the effects of migration in con-junction with permanent settlement. To our knowledge,this is the first Canadian population-based study to inves-tigate mental health diagnoses in adolescents and youngadults by exploring the effects of rurality-urbanity andmigration patterns through analysis of large-scale admin-istrative data.MethodThis study is based on a cohort of male sawmill workers(N = 28,794) on whom data was first gathered in the mid-1990s to study the effects of chlorophenol antisapstainexposure among British Columbian sawmill workers [34].Recently, the original study cohort has been extended toinvestigate the association between job history, workstress, and health outcomes among the cohort partici-pants and their children [35-37]. For the present study,personnel records for workers who had worked in one of14 sawmills for at least one year between 1950 and 1998were accessed and compiled. The birth files from theBritish Columbia provincial vital statistics registry wereused to identify the children of the sawmill workers whowere born between 1952 and 2000. Probabilistic linkagetechniques were used to identify the study participantsand their mental health diagnoses. More specifically, tolink records of the children to those of the fathers, weused the Medical Services Plan (MSP) number (theequivalent to a health personal number), gender of thechild, date of birth, surname, and given names. Thisprobabilistic technique yielded a success rate of 87%. Atotal of 37,827 children of sawmill workers were identi-fied, forming an offspring cohort that includes individu-als of varying age, ranging from young children to adults.Mental health information of children of sawmill work-ers was gathered from the provincial administrativehealth data. The Canadian health system is public anduniversally accessible and it is regulated at the provinciallevel. In British Columbia, individuals experiencing men-tal health problems can be evaluated by mental healthprofessionals at public hospitals or medical clinics. Everyencounter that occurs between patients and health pro-fessionals is recorded on administrative forms that arepersonal health information are recorded on such forms.This individual-level administrative health information isavailable to researchers who have obtained approval asthe result of a stringent process of review of ethical stan-dards and scientific rigor. Such data, which also includecodes for mental health diagnoses in accordance withinternational code systems, are accessed at the BritishColumbia Linked Health Database (BCLHDB). Ethicalapproval was obtained from the University of BritishColumbia (UBC) and the British Columbia Ministry ofHealth to conduct a series of studies on the health of saw-mill workers and their children.Study participantsFor the children of sawmill workers to be eligible for thisstudy, the fathers must have worked at least one year inone of the study sawmills while their children werebetween the ages of 0 and 16 years. A total of 19,833 chil-dren of sawmill workers satisfied the eligibility criteria forinclusion. Our study focuses specifically on mental healthdiagnoses that were assigned to children of sawmill work-ers at different times from early childhood to youngadulthood. Therefore, the sample for this study consistsof a total of 8,508 participants: 2,127 cases and 6,381 con-trols (3 matched controls on age and gender for eachcase). Table 1 describes the sociodemographic character-istics of this sample.Mental health outcomesInternational Classification of Diseases, 9th Revision(ICD-9) criteria and codes for children were used to diag-nose mental health problems among individuals betweenthe ages of 15 and 19, whereas adult ICD-9 criteria andcodes were used to diagnose mental health problemsamong individuals 20 years of age and older.Mental health diagnoses for which there were less than30 cases were not selected, because the ratio betweenparticipants and independent variables would have notbeen sufficient. The selected diagnoses were neurotic dis-orders (e.g., anxiety state, obsessive-compulsive disor-ders, phobic state), personality disorders, acute reactionto stress, adjustment reactions, depression, alcoholdependence, and nondependent drug abuse. Table 2 indi-cates the number of cases and controls that have beenidentified for each of the above mental health conditions.Rural-Urban Migration PatternsStatistics Canada offers different definitions of rurality -based on population size, density or proximity to urbancentres - and recommends that the selection of specificdefinitions of rurality be guided by the research questionof any given study [38]. In British Columbia there are twosent and stored at the British Columbia Ministry ofHealth. The reason for medical visit or hospitalization(which can include a diagnosis if one is provided), andlarge metropolitan centres (Vancouver and Victoria)located in the southern part of the province, and a collec-tion of medium to small towns with low density popula-Maggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 4 of 11tion distributed across the interior, the northern part ofthe province, and Vancouver Island. Therefore, weselected a definition of rurality based on population size,whereby communities with fewer than 100,000 people areconsidered rural and communities with 100,000 peopleor more are considered urban.Health information records were inspected for the peri-ods between birth and time at diagnosis to identifymigration patterns among the study participants. Defini-tions of migration patterns were based on changes to theparticipants' postal codes that were associated withrecords of health services utilization and provided by thelocal health authorities. Individuals could have been bornin and stayed in rural or urban communities within theprovince of British Columbia, or moved from rural tourban communities within British Columbia, or viceversa. The following three migration patterns have there-fore been identified to describe within province migra-tion: urban to rural (0 = no and 1 = yes); rural to rural (0 =no and 1 = yes); and rural to urban (0 = no and 1 = yes).The following two additional migration patterns wereidentified to describe participants who had moved awayfrom the province of British Columbia, and for whom wedid not have information about the place of destination:urban (0 = stayed and 1 = moved); rural (0 = stayed and 1= moved).It is worth noting that an 'urban to urban' migrationpattern could not be included in the present study. Theoriginal cohort (i.e., the fathers) was indentified amongworkers of sawmills located in British Columbia in theearly 1980s. Urban communities in British Columbia,that is, those with population over 100,000 dwellings, arethe cities of Vancouver, Victoria, and Kelowna. Of these,only Vancouver still has a sawmill, while Kelowna's saw-mill closed in the late 1980s, and Victoria never had one.Therefore the likelihood of migration for work from anurban sawmill community to another urban sawmill com-munity was largely non-existent among our study cohort.Control variablesWhile the study focuses on the effect of rural-urbanmigration patterns on mental health of the children'sTable 1: Sociodemographic Characteristics of Fathers and Children (N = 8,508)Sociodemographic CharacteristicsAge of Children at Diagnosis Mean = 27.8SD = 7.8Minimum = 14Maximum = 48Frequency (%)Gender of the ChildrenFemales 2456 (28.9)Males 6052 (71.1)Age at Diagnosis<20 years of age 1376 (16.2)20-30 years of age 4232 (49.7)>30 years of age 2900 (34.1)Marital Status of the FatherMarried 7297 (92.1)Separated, single, or widowed629 (7.9)Ethnicity of the FatherCaucasian 7332 (86.2)Sikh 955 (11.7)Asian or Chinese 181 (2.1)Mental Health of the FatherDiagnosis before children's diagnosis2135 (25.1)No diagnosis before children's diagnosis6376 (74.9)Alcoholism of the FatherDiagnosis before children's diagnosis750 (8.8)No diagnosis before children's diagnosis7758 (91.2)Suicidal Behavior of the FatherDiagnosis before children's diagnosis64 (0.8)No diagnosis before children's diagnosis8444 (99.2)Job Level of the FatherManager 664 (7.8)Tradesman 2718 (31.9)Skilled Worker 1678 (19.7)Urban 1853(22.1)Rural 1780 (21.2)Urban migrators 1215 (14.5)Rural to Urban 1956 (23.3)Rural migrators 1585 (18.9)Table 1: Sociodemographic Characteristics of Fathers and Children (N = 8,508) (Continued)cohort, there are some potential variables that need to beUnskilled Worker 3448 (40.5)Urban-Rural Migration of the Childrenaccounted for in the analysis. These variables are theMaggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 5 of 11sociodemographic characteristics, the mental health, andthe employment history of the fathers.The following sociodemographic characteristics wereobtained from the sawmill employment records: durationof employment (continuous variable); job mobility (classi-fied as upward, downward, or stable); type of employ-ment (one dummy variable for trades, one dummyvariable for skilled, and one dummy variable forunskilled; management as referent); ethnicity (onedummy variable for Chinese and one dummy variable forSikh; Caucasian as referent); and marital status of thefathers (one dummy variable; married as referent). ICD-9mental health diagnosis (father had been diagnosed withany mental health conditions; one dummy variable; nodiagnosis as referent); suicidal behaviors (father hadattempted or completed suicide; one dummy variable; nodiagnosis as the referent); and alcohol dependence (onedummy variable; no diagnosis as the referent) wereobtained from the BCLHDB.AnalysisUsing survival-time to case-control on STATA 8.0, threecontrols were selected for each mental health casematched on age and gender. Controls were chosen ran-domly with replacement from the set at risk. The set atrisk were all the offspring of the sawmill worker's cohort,born between 1952 and 2000, whose father had worked ina study sawmill for at least one year during the first 16years of the child's life. These could be anyone at risk whoalso satisfied the matching criteria who had not beendiagnosed with a mental health condition at the time ofdiagnosis of the case. Given this procedure, it is possiblethat a participant is a control in the analysis pertaining toa specific diagnosis, but a case in the analysis pertainingto another diagnosis. For example, a participant may be atStatistical analyses were conducted using conditionallogistic regression on STATA 8.0. First, a series of sevenunivariate analyses (one for each diagnosis) were con-ducted to identify associations between the five migra-tion patterns (i.e., urban, urban to rural, rural, rural tourban, rural to rural) and mental health outcomes. Sec-ond, we conducted a series of four separate multivariateanalyses, one for each of the outcomes that yield signifi-cant associations with migration patterns. In these analy-ses we controlled for the following paternalcharacteristics: duration of employment, paternal ethnic-ity, marital status, paternal alcohol dependence, mentalhealth of the father, suicidal behavior of the father, andtype of employment.ResultsResults of the univariate analyses are reported in Table 3.Four of the six mental health diagnostic groups had atleast one migration category where the 95% confidenceinterval around the odds ratio excluded 1.0: nondepen-dent drug abuse, acute reaction to stress, adjustment reac-tion, and depression. Multivariate analyses wereconducted for these diagnoses, as reported in Table 4.Odds ratio (OR) analyses revealed that after controllingfor important paternal characteristics, rural stability issignificantly associated with acute reaction to stress anddepression. Specifically, individuals who were born in andgrew up in the same rural community were approxi-mately 25% less likely to be diagnosed with acute reactionto stress (OR = 0.740; p = .004; 95%CI = .602-.910) andapproximately 10% less likely to be diagnosed withdepression (OR = 0.881; p = .044; 95%CI = .780-.996) thanthose who had not grown up in the same rural commu-nity in which they were born. Similarly, individuals whohad migrated between rural communities were approxi-Table 2: Number of Cases per IDC-9 Mental Health Diagnosis and Matched Controls (n = 8,218)IDC-9 codes Mental Health DiagnosisCases Controls Total300 Neurotic Disorders 463 1389 1852301 Personality Disorder 113 339 452308 Acute Reaction to Stress229 705 934309 Adjustment Reaction 305 915 1220311 Depression 830 2490 3320303 Alcohol Dependence 36 108 144305 Nondependent Drug Abuse74 222 296risk for depression and be used as a control in such analy-sis, but also be used as a case for nondependent drugabuse if he/she was assigned such a diagnosis.mately 50% less likely to be diagnosed with adjustmentreaction (OR = 0.571; p < .001; 95%CI = .441-.739) thanparticipants who stayed in the rural communities inMaggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 6 of 11Table 3: Risk of IDC-9 Mental Health Diagnoses Associated with Rural-Urban Migration PatternsOdds Ratio SE z 95% CINeurotic Disorders (1852)Urban 0.988 0.061 -0.20 0.876-1.11Urban to Rural 1.04 0.075 0.60 0.907-1.20Rural 0.923 0.057 -1.29 0.817-1.04Rural to Urban 1.04 0.621 0.66 0.925-1.17Rural to Rural 1.08 0.069 1.21 0.953-1.22Acute Reaction to Stress (934)Urban 1.09 0.084 1.08 0.934-1.26Urban to Rural 1.10 0.099 1.11 0.927-1.32Rural 0.756 0.064 3.29 0.64-0.893Rural to Urban 0.970 0.074 0.40 0.835-1.13Rural to Rural 1.19 0.093 2.25 1.02-1.39Depression (3320)Urban 1.07 0.051 1.33 0.970-1.17Urban to Rural 0.884 0.051 -2.12 0.789-0.99Rural 0.930 0.045 -1.47 0.845-1.02Rural to Urban 1.04 0.049 0.81 0.947-1.14Rural to Rural 1.11 0.054 2.23 1.01-1.23Personality Disorders (452)Urban 1.02 0.141 0.17 0.782-1.34Urban to Rural 1.08 0.179 0.46 0.780-1.49Rural 0.865 0.128 -0.98 0.647-1.16Rural to Urban 0.995 0.138 -0.03 0.759-1.31Rural to Rural 1.13 0.169 0.80 0.840-1.51Adjustment Reaction (1220)Urban 1.05 0.099 0.48 0.869-1.26Urban to Rural 1.35 0.140 2.89 1.10-1.65Rural 0.595 0.062 -4.97 0.485-0.73Rural to Urban 1.15 0.105 1.57 0.965-1.38Rural to Rural 1.10 0.105 1.01 0.914-1.33Alcohol Dependence (144)Urban 0.854 0.154 -0.88 0.599-1.22Urban to Rural 1.06 0.190 0.32 0.745-1.50Rural 0.889 0.145 -0.72 0.645-1.22Rural to Urban 1.00 0.155 0.00 0.738-1.35Rural to Rural 1.26 0.200 1.47 0.926-1.72Maggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 7 of 11which they were born. Interestingly, nondependent drugabuse was not significantly associated with rural stability(OR = 0.935; p > .05; 95%CI = .627-1.39) or migrationbetween rural communities (OR = 1.42; p > .05; 95%CI =.952-2.11).DiscussionThe present findings show that growing up in a ruralenvironment or migrating between rural communitiesmay protect against some mental health conditions,namely, acute reaction to stress, adjustment reaction, anddepression. More specifically, youth and adults who grewup in the same rural community were at lower risk ofbeing diagnosed with depression and adjustment reactionthan individuals who did not grow up in the same ruralcommunity in which they were born, and childrenmigrating between rural communities were at lower riskof being diagnosed with acute reaction to stress than par-ticipants who did not migrate between rural communi-ties.However, it is worth noting that for other mental healthdiagnoses we did not find a link with migration patterns.For example, we did not find significant differencesbetween rural and urban environments or migration pat-terns between these two types of environments in thediagnosis of neurotic disorder, personality disorder, alco-hol dependence, and nondependent drug abuse. There-fore we conclude that if rurality plays a protective role inthe development of mental health, it does so only for spe-cific conditions.We argue that clues to what might be protecting chil-dren living in rural communities from developing acutereactions to stress, adjustment reaction, or depressionmay be suggested by a null finding. We found that, aftercontrolling for important paternal sociodemographiccharacteristics, adolescents and young adults living inrural places are as likely to become nondependent drugabusers as individuals growing up in urban communities.We qualify this null finding as important because it isstance abuse [e.g., [28,39-41]], especially among ruralyouth [42-46], and suggesting that there may be somecharacteristics of rurality that put youth at risk for drugabuse.It has been speculated that some of the alleged risk fac-tors of rurality may be linked to the remoteness, isolation,and seclusion that generally are embedded in rural livingand attract rural youth to large cities. Paradoxically, thesefeatures may relate to a perceived sense of status quo andlack of change. The underlying rationale is that the asso-ciation between boredom and drug use in adolescentsand young adults might be stronger in rural than in urbancommunities because living in rural communities mightmake individuals within these developmental periodsmore prone to boredom and, by implication, might makethem experience less change or novelty than their coun-terparts living in urban communities.Our analyses clearly show that, when individuals arematched for a series of family and socioeconomic vari-ables, differences relative to nondependent drug abuseamong rural and urban groups disappear. Thus, we con-clude that it is possible that the differences found in rela-tion to nondependent drug abuse reported in theliterature may be due to the fact that the latent variableboredom may be confounded with uncontrolled socio-economic and family variables, which instead reflect thetypically greater availability of resources and access toservices, facilities, and amenities enjoyed by urban popu-lations.Indeed, the pattern of results in our study suggests analternative interpretation of the influence of rurality. Thatis, keeping constant the extent of access and resourcesvarying with living contexts, rurality may well play a pro-tective role for mental health of adolescents and youngadults because it provides them with a needed sense ofstability and control.This proposed interpretation evokes a host of interest-ing questions concerning what is the optimal level of"social environment stimulation" in critical periods suchNondependent Drug Abuse (296)Urban 0.754 0.116 -1.83 0.557-1.02Urban to Rural 1.26 0.199 1.47 0.926-1.72Rural 0.684 0.102 -2.55 0.510-0.92Rural to Urban 1.05 0.143 0.34 0.802-1.37Rural to Rural 1.38 0.201 2.20 1.04-1.83*p < .05Table 3: Risk of IDC-9 Mental Health Diagnoses Associated with Rural-Urban Migration Patterns (Continued)indeed consistent with our interpretation of the protec-tive role of rurality. However, it is contrary to a literatureshowing that leisure boredom is associated with sub-as adolescence and young adulthood. Research address-ing such questions has almost exclusively focused oninfancy and early childhood, but seems to have largelyMaggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 8 of 11Table 4: Results of the Multivariate AnalysisOdds Ratio SE z P > |z| 95% CINondependent Drug Abuse (296)Duration of Employment 0.982 0.016 -1.11 0.265 0.951-1.01Trades Worker 1.22 0.325 0.73 0.463 0.721-2.05Skilled Worker 1.13 0.319 0.45 0.655 0.654-1.97Unskilled Worker 1.54 0.410 1.62 0.105 0.914-2.60Rural 0.935 0.190 -0.33 0.739 0.627-1.39Rural to Rural 1.42 0.289 1.72 0.086 0.952-2.11Chinese 0.187 0.139 -2.25 0.024* 0.043-0.80Sikh 0.384 0.091 -4.04 0.000** 0.241-0.61Paternal Mental Health 1.78 0.266 3.87 0.000** 1.33-2.39Paternal Alcoholism 1.80 0.633 1.68 0.094 0.905-3.58Paternal Suicidal Behaviors 2.01 1.09 1.30 0.195 0.698-5.80Marital Status 1.00 0.031 0.11 0.914 0.944-1.07Acute Reaction to Stress (934)Duration of Employment 0.989 0.008 -1.28 0.202 0.973-1.01Trades Worker 1.01 0.139 0.07 0.947 0.771-1.32Skilled Worker 1.37 0.200 2.17 0.030* 1.03-1.83Unskilled Worker 1.34 0.185 2.10 0.036* 1.02-1.75Rural 0.740 0.078 -2.86 0.004* 0.603-0.91Rural to Rural 1.03 0.103 0.32 0.750 0.849-1.26Chinese 0.314 0.101 -3.60 0.000** 0.167-0.59Sikh 0.649 0.077 -3.66 0.000** 0.515-0.82Paternal Mental Health 1.33 0.105 3.65 0.000** 1.14-1.55Paternal Alcoholism 1.38 0.267 1.64 0.101 0.940-2.01Paternal Suicidal Behaviors 1.23 0.360 0.72 0.470 0.697-2.19Marital Status 0.974 0.018 -1.40 0.162 0.938-1.01Adjustment Reaction (1220)Duration of Employment 0.998 0.010 -0.21 0.834 0.978-1.02Trades Worker 1.10 0.179 0.59 0.553 0.801-1.52Skilled Worker 1.59 0.269 2.76 0.006* 1.15-2.22Unskilled Worker 1.34 0.217 1.81 0.070 0.976-1.84Rural 1.05 0.134 0.40 0.688 0.814-1.36Rural to Rural 0.571 0.075 -4.27 0.000** 0.442-0.74Chinese 0.253 0.112 -3.10 0.002* 0.106-0.60Sikh 0.606 0.085 -3.55 0.000** 0.460-0.80Paternal Mental Health 0.604 0.067 -4.52 0.000** 0.485-0.75Paternal Alcoholism 0.542 0.108 -3.09 0.002* 0.368-0.80Paternal Suicidal Behaviors 2.64 0.967 2.65 0.008* 1.29-5.41Marital Status 1.04 0.022 1.63 0.104 0.993-1.08are an array of different and specific dimensions of rural-ity and urbanity that health researchers need to considerto better understand what community aspects may beassociated with mental health outcomes [47]. For exam-ple, resource-dependent rural communities can beextremely different from one another, because farming,mining, and forestry are each affected differently by shiftsin the market economy and availability of resources. Suchshifts may also be partially responsible for individualtrends in migration, which in turn represent an importantelement of the community social fabric. At the same time,the influences of rurality cannot be studied without con-trolling for individual-level characteristics that contributeto the socioeconomic profile of an entire community.The present study has highlighted the important roleplayed by stability, as opposed to migration, in contribut-ing to the mental health of members of rural and urbancommunities. Our findings also suggest that importantfamily characteristics such as sociodemographics, dura-tion of employment, and a history of mental health maybe possible confounders in previous studies in which dif-drug use reported in the literature, as the inconsistentresults could be confounded by factors such as ethnicityand familial history of mental health.There are a number of limitations to this study that areworth mentioning. First, because our outcome measureswere derived from medical records, we were not able toaddress the link between mental health and urbanity-rurality that may exist at the subclinical level, nor couldwe explore the role of potentially important contextualfactors (e.g., social capital). Second, while we controlledfor important sociodemographic and mental health char-acteristics of the fathers, we did not have access to mater-nal characteristics and therefore could not include themin this study. Third, the participants in the study repre-sent a very specific population - that is, the children ofmale sawmill workers in British Columbia, Canada - andtherefore findings from this study cannot be generalized.Finally, rural health researchers may be critical of our def-inition of rurality, which was solely based on populationsize (centers with less than 100,000 people), and our clas-sification of migration patterns is reductive in that it didMaggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 9 of 11Depression (3320)Duration of Employment 0.983 0.005 -3.33 0.001* 0.973-0.99Trades Worker 1.07 0.087 0.83 0.407 0.912-1.25Skilled Worker 1.22 0.104 2.30 0.021* 1.03-1.44Unskilled Worker 1.16 0.095 1.83 0.068 0.989-1.36Rural 0.806 0.057 -3.06 0.002* 0.702-0.93Rural to Rural 0.980 0.062 -0.32 0.753 0.867-1.11Chinese 0.348 0.068 -5.37 0.000** 0.237-0.51Sikh 0.743 0.051 -4.36 0.000** 0.650-0.85Paternal Mental Health 1.28 0.064 4.98 0.000** 1.16-1.41Paternal Alcoholism 1.69 0.216 4.06 0.000** 1.31-2.17Paternal Suicidal Behaviors 1.16 0.235 0.71 0.478 0.776-1.72Marital Status 0.989 0.011 -1.02 0.308 0.968-1.01*p < .05**p < .01Table 4: Results of the Multivariate Analysis (Continued)neglected other developmental periods in the life span,and to have underestimated the role played by the contextin which individuals live. Clearly, given the potentialimportant links with lifestyle, well-being, and health out-comes, this should be an area of priority for futureresearch.While approaches to health policy tend to treat ruralareas as uniform entities, mental health differencesbetween rural areas may be as pronounced as thoseobserved between urban and rural communities. ThereWhile in this study we treated paternal characteristics(e.g., mental health diagnosis, work history, and ethnicity)as control variables, it is worth noting that these wereconsistently associated with increased risk of mentalhealth diagnosis among the children. More specifically,paternal mental health diagnosis and Caucasian origins(compared to Chinese and Sikh) were associated withgreater odds of mental health diagnosis among the chil-dren. These findings may explain in part some of theinconsistencies between rural and urban communities inferences between rural and urban communities havebeen identified.not divide urban migrators into those who migrated toother urban places and those who migrated from urbanto rural places.Maggi et al. Child and Adolescent Psychiatry and Mental Health 2010, 4:13http://www.capmh.com/content/4/1/13Page 10 of 11Because of the limitations of this study, further researchon this topic needs to be conducted before recommenda-tions for clinical practice can be extrapolated. Nonethe-less, it is reasonable to advocate for a clinical practice thattakes into consideration not only the individual historiesof patients, but also the influence that broader socialenvironments exert on the etiology of mental health con-ditions. This is a critical concept since it may have impli-cations for treatment of the individual, but also for theidentification of large-scale public mental health preven-tion programs.ConclusionsThanks to the use of a relatively homogeneous sample,this study provides some compelling evidence of the pro-tective role of rural environments in the development ofsome mental health conditions (i.e., depression, adjust-ment reaction, and acute reaction to stress) but not oth-ers (e.g., nondependent drug abuse).AbbreviationsBC: British Columbia; BCLHDB: British Columbia Linked Health Database; ICD:International Classification of Disease; OR: Odds Ratio; CI: 95% ConfidenceInterval.Competing interestsThe authors declare that they have no competing interests.Authors' contributionsSM directed the analysis, and was the lead writer. AO was PI for purposes ofobtaining funding for this research, and reviewed drafts. KC assisted with theliterature review. RH conducted the analysis, and LC managed the database.AD contributed conceptually and reviewed drafts. CH conducted the research,helped direct the analysis, and read drafts of the paper. All authors read andapproved the final manuscript.AcknowledgementsThis work was funded by the Canadian Population Health Initiative. Dr. Maggi was funded through a New Investigator Award from the Canadian Institutes for Health Research and was a Michael Smith Foundation for Health Research Scholar. Dr. Ostry was funded through a New Investigator Award from the Canadian Institutes for Health Research and holds a Scholar Award from the Michael Smith Foundation for Health Research. Drs. 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