we conducted a retrospective cohort study using a combination of administrative health claims and small area level data from toronto , ontario , canada . in the province of ontario , as in the rest of canada , comprehensive coverage for hospital , physician , and laboratory services is provided to all permanent residents with no deductibles or copayments . health records for each individual in our cohort were linked anonymously across datasets using an encrypted version of their health card number . neighborhood - level attributes were then assigned to individuals using their postal code of residence . the study population was identified using the registered persons database , a provincial health care registry that contains demographic , residential , and vital statistics for virtually all ontario residents . men and women living in toronto on 1 april 2005 who were free of diabetes and eligible for health care coverage for a minimum of 3 years at baseline were eligible for inclusion in our cohort . the population was restricted to adults aged 30 to 64 years because this group is experiencing the most rapid rise in diabetes incidence ( 20 ) , likely because of trends in obesity . recent immigrants were defined as those who first registered for coverage under the province s healthcare plan within 10 years of baseline ( on 1 april 1995 or later ) . recent registration has been shown to be a good proxy for recent immigration to ontario ( 21 ) . although country of origin was not available in the databases we used , previous research has shown that most recent immigrants to toronto are from asia , africa , and the middle east , with only 12% being of european descent ( 17 ) . this is in contrast to the general toronto population , in which 58% report being of european ancestry . the final sample size was 1,239,262 , consisting of 214,882 recent immigrants and 1,024,380 long - term residents . our primary covariate was the degree to which an individual s area of residence supports walking and other physical activities . we used a validated walkability index created for toronto , as described previously ( 22 ) . briefly , candidate variables were identified from the literature and were generated using geographic information systems methodology and a combination of census , land use , retail , and public services data . from these , the following area - level attributes were selected for the final index using principal components analysis : population density , dwelling density , street connectivity , and the availability of walkable destinations ( number of retail stores and services within a 10-min walk ) . index scores positively predicted rates of walking , cycling , and public transit use and were inversely associated with car ownership , driving trips , and levels of obesity ( 22 ) . for this study , walkability scores were derived for 10,535 dissemination blocks , which are small , residential parcels of land ( average population , 200 ) . dissemination blocks were subsequently divided into quintiles , from most walkable ( quintile [ q5 ] ) to least walkable ( quintile [ q1 ] ) , which were then assigned to individuals in our cohort based on their postal code of residence on 1 april 2005 . because individual - level information about income was not available for members of our cohort , we used area - level poverty as a surrogate . this was based on data collected for the 2006 canadian census , which was used to generate relative income quintiles adjusted for household and community size that were then assigned to individuals . this measure was available at the dissemination area level , a unit slightly larger than dissemination blocks . members of our cohort were followed forward in time , from 1 april 2005 to 31 march 2010 , for the development of diabetes . the ontario diabetes database is a validated electronic database that uses the following algorithm to identify persons with diagnosed diabetes : individuals with at least one hospitalization or at least two claims for physicians services ( within 2 years ) bearing a diagnosis of diabetes are included in the database . this algorithm was found to be highly sensitive ( 86% ) and specific ( 97% ) for identifying patients for whom diabetes was recorded in primary care charts ( 23 ) . the same algorithm was used to exclude individuals who had pre - existing diabetes at baseline from our study cohort . random effects poisson models were used to examine the impact of neighborhood walkability on the incidence of diabetes over the 5-year study period among members of our cohort , according to their immigration status . separate models were created for men and women on the basis of an a priori hypothesis that neighborhood effects may vary by sex ( 19 ) . random effects models were used to account for the clustering of individuals within the same area and the inherent autocorrelation between adjacent areas . we calculated the median rate ratio to quantify this variation in diabetes incidence between geographic clusters ( dissemination areas ) ( 24 ) . additional covariates included in the final models were age ( in years ) and area income quintile . tests for interaction between walkability and income were performed based on our a priori hypothesis that concomitant poverty would accentuate the effect of low walkability on diabetes incidence . individuals were followed from 1 april 2005 until the development of diabetes , death , loss of health insurance eligibility because of emigration , or the end of the observation period ( 31 march 2010 ) , whichever occurred first . last , we examined whether area income modified any association between area walkability and diabetes risk . to do so , we compared 5-year age- and sex - standardized diabetes incidence rates within subgroups of our population , defined by their immigration status ( recent immigrants versus long - term residents ) and income level ( lowest , middle , and highest quintile ) . we conducted a retrospective cohort study using a combination of administrative health claims and small area level data from toronto , ontario , canada . in the province of ontario , as in the rest of canada , comprehensive coverage for hospital , physician , and laboratory services is provided to all permanent residents with no deductibles or copayments . health records for each individual in our cohort were linked anonymously across datasets using an encrypted version of their health card number . neighborhood - level attributes were then assigned to individuals using their postal code of residence . the study population was identified using the registered persons database , a provincial health care registry that contains demographic , residential , and vital statistics for virtually all ontario residents . men and women living in toronto on 1 april 2005 who were free of diabetes and eligible for health care coverage for a minimum of 3 years at baseline were eligible for inclusion in our cohort . the population was restricted to adults aged 30 to 64 years because this group is experiencing the most rapid rise in diabetes incidence ( 20 ) , likely because of trends in obesity . recent immigrants were defined as those who first registered for coverage under the province s healthcare plan within 10 years of baseline ( on 1 april 1995 or later ) . recent registration has been shown to be a good proxy for recent immigration to ontario ( 21 ) . although country of origin was not available in the databases we used , previous research has shown that most recent immigrants to toronto are from asia , africa , and the middle east , with only 12% being of european descent ( 17 ) . this is in contrast to the general toronto population , in which 58% report being of european ancestry . the final sample size was 1,239,262 , consisting of 214,882 recent immigrants and 1,024,380 long - term residents . our primary covariate was the degree to which an individual s area of residence supports walking and other physical activities . we used a validated walkability index created for toronto , as described previously ( 22 ) . briefly , candidate variables were identified from the literature and were generated using geographic information systems methodology and a combination of census , land use , retail , and public services data . from these , the following area - level attributes were selected for the final index using principal components analysis : population density , dwelling density , street connectivity , and the availability of walkable destinations ( number of retail stores and services within a 10-min walk ) . index scores positively predicted rates of walking , cycling , and public transit use and were inversely associated with car ownership , driving trips , and levels of obesity ( 22 ) . for this study , walkability scores were derived for 10,535 dissemination blocks , which are small , residential parcels of land ( average population , 200 ) . dissemination blocks were subsequently divided into quintiles , from most walkable ( quintile [ q5 ] ) to least walkable ( quintile [ q1 ] ) , which were then assigned to individuals in our cohort based on their postal code of residence on 1 april 2005 . other covariates included age , sex , and income . because individual - level information about income was not available for members of our cohort , we used area - level poverty as a surrogate . this was based on data collected for the 2006 canadian census , which was used to generate relative income quintiles adjusted for household and community size that were then assigned to individuals . this measure was available at the dissemination area level , a unit slightly larger than dissemination blocks . members of our cohort were followed forward in time , from 1 april 2005 to 31 march 2010 , for the development of diabetes . the ontario diabetes database is a validated electronic database that uses the following algorithm to identify persons with diagnosed diabetes : individuals with at least one hospitalization or at least two claims for physicians services ( within 2 years ) bearing a diagnosis of diabetes are included in the database . this algorithm was found to be highly sensitive ( 86% ) and specific ( 97% ) for identifying patients for whom diabetes was recorded in primary care charts ( 23 ) . the same algorithm was used to exclude individuals who had pre - existing diabetes at baseline from our study cohort . random effects poisson models were used to examine the impact of neighborhood walkability on the incidence of diabetes over the 5-year study period among members of our cohort , according to their immigration status . separate models were created for men and women on the basis of an a priori hypothesis that neighborhood effects may vary by sex ( 19 ) . random effects models were used to account for the clustering of individuals within the same area and the inherent autocorrelation between adjacent areas . we calculated the median rate ratio to quantify this variation in diabetes incidence between geographic clusters ( dissemination areas ) ( 24 ) . additional covariates included in the final models were age ( in years ) and area income quintile . tests for interaction between walkability and income were performed based on our a priori hypothesis that concomitant poverty would accentuate the effect of low walkability on diabetes incidence . individuals were followed from 1 april 2005 until the development of diabetes , death , loss of health insurance eligibility because of emigration , or the end of the observation period ( 31 march 2010 ) , whichever occurred first . last , we examined whether area income modified any association between area walkability and diabetes risk . to do so , we compared 5-year age- and sex - standardized diabetes incidence rates within subgroups of our population , defined by their immigration status ( recent immigrants versus long - term residents ) and income level ( lowest , middle , and highest quintile ) . the recent immigrant group was similar to long - term residents in terms of their demographic characteristics and the walkability of their residential area . recent immigrants , however , were more likely than long - term residents to live in low - income areas . baseline characteristics of study population by immigration status during the period of follow - up , 58,544 men and women in our cohort developed diabetes . there was a large degree of variation in the incidence of diabetes between dissemination areas in our study area on the basis of the calculated median rate ratio ( 1.44 ) . we found a strong inverse gradient between area walkability and the incidence of diabetes among both men and women in our cohort ( figs . 1 and 2 , respectively ) . recent immigrants living in the least walkable areas had diabetes incidence rates that were more than 50% higher than those living in the most walkable areas ( relative risk [ rr ] 1.58 [ 95% ci 1.421.75 ] for men ; rr 1.67 [ 95% ci 1.481.88 ] for women ) after accounting for differences in age and area poverty . in contrast , the association was less marked among long - term residents ( 1.32 [ 1.261.38 ] for men ; 1.24 [ 1.181.31 ] for women ) . parameter estimates and relative risks for all variables in our model are presented in supplementary tables 1 and 2 . diabetes risk among men aged 3064 years by walkability quintile and immigration status ( recent immigrants [ white squares ] vs. long - term residents [ black circles ] ) . . diabetes risk among women aged 3064 years by walkability quintile and immigration status ( recent immigrants [ white squares ] versus long - term residents [ black circles ] ) . there was a significant interaction between neighborhood walkability and income , with respect to their effect on diabetes incidence , both for recent immigrants ( p = 0.01 ) and long - term residents ( p = 0.02 ) . figure 3 shows the relationships between age- and sex - adjusted diabetes incidence rates and area walkability by income and immigration . low - income areas had diabetes incidence rates that were twofold greater than high - income areas at all levels of walkability . within low - income areas that were also less walkable , recent immigrants had considerably higher diabetes incidence rates than long - term residents . however , these rates converged in areas of increased walkability . a similar pattern was observed among residents living in middle - income areas ( data not shown ) . in high - income areas , diabetes incidence was low , did not differ greatly between recent immigrants and long - term residents , and declined slightly with increasing walkability . there was a more than threefold variation in diabetes incidence between recent immigrants living in low - income , low walkability areas ( 16.2 per 1,000 ) and those living in high - income , high walkability areas ( 5.1 per 1,000 ) . age- and sex - standardized 5-year diabetes incidence rates for adults aged 3064 years by walkability index quintile , income , and immigration status . white squares indicate low - income recent immigrants based on data collected in 2005 for 2006 canadian census . black circles indicate low - income long - term residents based on 2006 canadian census data . black squares indicate high - income recent immigrants and white circles indicate high - income , long - term residents . * for period from 1 april 2005 to 31 march 2010 . our findings demonstrate that residents living in less walkable areas , particularly recent immigrants in low - income neighborhoods , have an accelerated risk of developing diabetes compared with those living in more walkable areas . although diabetes can be prevented through physical activity , healthy eating , and weight loss ( 25 ) , the environment in which one lives may pose barriers to achieving these measures that are difficult to overcome . lessons learned from successful antismoking campaigns in the past suggest that population - level strategies can play a key role in promoting healthy behaviors ( 26 ) . moreover , public policies that target whole populations may prevent as many cases of diabetes as those targeting high - risk individuals alone ( 27,28 ) . our findings support the concept that neighborhood design potentially could influence the health of urban populations through the opportunities it provides for residents to undertake healthy behaviors . europe , recent immigrants in our setting are most often of south asian , east asian , or african descent , groups that are particularly susceptible to the development of diabetes ( 7,29 ) . recent immigrants are often underemployed relative to their occupational roles in their home country and therefore experience low socioeconomic status relative to the host country population , leading to their residence in less desirable areas of major urban centers . although the prevalence of chronic conditions is often lower among recent immigrants , a phenomenon known as the  healthy migrant  effect ( 30 ) , this was not the case for diabetes among recent arrivals in our setting , especially for those living in low - income and low walkability areas . the growing trend of rapid urbanization in developing countries , together with rich diets and sedentary lifestyles in those settings , may have resulted in less healthy migrant populations to canada in recent years , especially with regard to their risk of obesity - related conditions such as diabetes ( 5,6,31 ) . the role of poverty in accentuating the risk of diabetes in recent immigrants is likely multifactorial . lower - income populations may rely more on local , low - cost opportunities for physical activity within their neighborhood than their wealthier counterparts because of limited financial resources . moreover , for complex diseases , such as diabetes , the cumulative effect of multiple environmental insults ( e.g. , poverty , lack of opportunities for physical activity , and greater exposure to inexpensive , unhealthy foods ) may dramatically heighten the risk of disease in genetically susceptible individuals ( 18,19,32 ) . our findings are supported by other studies demonstrating an association between neighborhood features that discourage physical activity and risk factors for diabetes such as physical inactivity , insulin resistance , and obesity ( 915,33 ) . ( 34 ) , which noted several neighborhood characteristics that predicted long - term weight gain , including area poverty and higher levels of perceived traffic . relatively few studies have examined the relationship between neighborhood features and discrete health outcomes such as diabetes . in the multiethnic study of atherosclerosis , participants who reported having better neighborhood resources for physical activity and healthy foods were 38% less likely to develop diabetes over a 5-year period ( 35 ) . our study adds to this literature by suggesting that neighborhood walkability is also a significant risk factor for the development of diabetes among young and middle - aged adults living in urban settings and that recent immigrants are particularly susceptible to its influence . in many cities around the world , the walkability of a neighborhood is tied to the era in which it was first developed . in toronto , as in other north american cities , the older neighborhoods , built predominantly before world war ii , have characteristics that enhance their walkability , including higher residential densities , shorter block lengths , and the coexistence of residential and commercial areas in the same neighborhood . the latter provides residents with a choice between walking and other modes of travel to reach routine destinations . during the period after world war ii , this style of urban design was largely replaced by a shift toward sprawling developments and the separation of land uses through legislated changes in zoning . suburban living dramatically reduces the opportunities residents have to engage in transportation - related physical activity , such as walking or bicycling to work or school or to run errands ( 912,36 ) . the automobile - oriented planning practices of the 1960s and 1970s have been contested by the new urbanism  movement , which promotes a return to pre  world war ii styles of urban design . many cities are now setting limits on further suburban sprawl , instead favoring high - density development in major employment and retail areas and along major transportation corridors . in this way one limitation of this work is that it included a single municipality ; therefore , our findings may not apply to other settings . however , historical trends in urban development that occurred in toronto are typical of those that occurred in other cities in north america and elsewhere in the world . our setting is also one of the most multicultural cities globally , making it an ideal setting for this type of research . although our analysis was based on individuals , socioeconomic status could be measured at only the area level . that measure was based on very small residential units , which have been shown to be a good proxy for individual income ( 37 ) . our data did not include country or region of origin or timing of immigration , and for that reason we used a proxy measure for recent immigration : recent registration for ontario health care . previous research showed that most individuals ( > 80% ) captured using this method are new immigrants ; however , the remainder include both immigrants and nonimmigrants who migrate between provinces ( 21 ) . this misclassification would tend to reduce the differences between the recent immigrant and long - term resident groups studied . the recent immigrant group is likely to be heterogeneous with respect to factors influencing their rate of assimilation , including their country of origin , prior westernization ,  and the presence of family members in canada , which we were not able to account for in our analysis . in addition , ethnoracial composition was not available in our data , but most immigrants to ontario are from populations that carry a high genetic predisposition for developing diabetes ( 7,29 ) . furthermore , recent immigrants are well distributed across toronto , with few ethnic enclaves ( 38 ) ; thus , clustering of ethnic populations should not account for our findings . differences in the retail food environment potentially could influence rates of obesity and insulin resistance ( 32,33,35 ) ; however , a previous study found higher concentrations of convenience stores and fast food outlets in the more walkable neighborhoods of toronto ( 38 ) . last , unmeasured confounders could have contributed to the association between neighborhood walkability and diabetes incidence ; therefore , we can not prove definitively that this relationship was directly causal . we hypothesize that living in a less walkable neighborhood increases one s risk of diabetes through its effects on physical activity and obesity , based on the vast literature supporting the association between neighborhood environments and these entities , including research conducted in toronto using our index and similar measures elsewhere ( 915,38,39 ) . however , information about bmi , physical activity levels , and travel behaviors was lacking in our datasets . collectively , this line of research supports the notion that where one live has a profound influence on one s health . this is a fundamental shift in the paradigm in which we view the etiology of chronic diseases such as diabetes  from a purely biomedical one to one that incorporates the larger world in which we live . moreover , it opens up other avenues for the prevention of obesity - related diseases that include changes in the way communities are designed ( 40 ) . as the fast pace of urbanization continues , particularly in developing countries , lessons learned from industrialized nations will be increasingly valuable . further research is needed to establish the consistency of these findings in other settings , to identify the world regions and ethnoracial groups most susceptible to these effects , and , most importantly , to more fully understand what impact interventions targeting the built environment might have on levels of obesity and diabetes .
objectivethis study was designed to examine whether residents living in neighborhoods that are less conducive to walking or other physical activities are more likely to develop diabetes and , if so , whether recent immigrants are particularly susceptible to such effects.research design and methodswe conducted a population - based , retrospective cohort study to assess the impact of neighborhood walkability on diabetes incidence among recent immigrants ( n = 214,882 ) relative to long - term residents ( n = 1,024,380 ) . 
 adults aged 3064 years who were free of diabetes and living in toronto , canada , on 31 march 2005 were identified from administrative health databases and followed until 31 march 2010 for the development of diabetes , using a validated algorithm . 
 neighborhood characteristics , including walkability and income , were derived from the canadian census and other sources.resultsneighborhood walkability was a strong predictor of diabetes incidence independent of age and area income , particularly among recent immigrants ( lowest [ quintile 1 { q1 } ] vs. highest [ quintile 5 { q5 } ] walkability quintile : relative risk [ rr ] 1.58 [ 95% ci 1.421.75 ] for men ; 1.67 [ 1.481.88 ] for women ) compared with long - term residents ( q1 to q5 ) 1.32 [ 1.261.38 ] for men ; 1.24 [ 1.181.31 ] for women ) . 
 coexisting poverty accentuated these effects ; diabetes incidence varied threefold between recent immigrants living in low - income / low walkability areas ( 16.2 per 1,000 ) and those living in high - income / high walkability areas ( 5.1 per 1,000).conclusionsneighborhood walkability was inversely associated with the development of diabetes in our setting , particularly among recent immigrants living in low - income areas .