Social inequities in neighborhood health amenities over time in the Wasatch Front Region of Utah: Historical inequities, population selection, or differential investment?

Socially disadvantaged groups generally are more likely to reside in areas with less desirable conditions. We examined longitudinal relationships between neighborhood resident characteristics and amenities from 1990 to 2010 in an urban area of Utah, U.S. Four temporal patterns of social inequities are described using mixed-effects models: historical inequities; differential selection into amenity-rich tracts; differential investment in amenities; and simultaneous twenty-year change. Results indicate historical differences by neighborhood socioeconomic status, with lower status tracts having fewer green/natural amenities and higher air pollution in 1990 but also greater walkability and more food stores. Differences in amenities by neighborhood socioeconomic status widened over time as aggregate socioeconomic status disproportionately increased in tracts with more green/natural amenities, less air pollution, and lower walkability in 1990, consistent with differential selection. Tract percentage non-Hispanic White did not predict historical differences, but tracts that were less walkable and had fewer healthy food stores in 1990 experienced larger subsequent increases in racial/ethnic diversity. Tracts with higher relative to lower percentage non-Hispanic White in 1990 had larger decreases in air pollution but declining green/natural amenities. This study shows how social inequities in neighborhood amenities change over time, providing evidence of historical socioeconomic differences increasing from differential resident selection.

Lean legacy, heavy heritage: family history of diabetes and its association with young adult body mass index.

Substantial intergenerational transmission of diabetes mellitus (DM) risk exists. However, less is known regarding whether parental DM and DM among extended family members relate to adult offspring's body mass index (BMI), and whether any of these associations vary by sex. Using data from the National Longitudinal Study of Youth 1997 cohort (NLSY97), we assess the sex-specific relationship between DM present in first-degree parents and second-degree relatives and BMI among the parents' young adult offspring.Multivariate regressions reveal a positive relationship between parental DM and young adults' BMI for both daughters and sons, and the magnitude of coefficients is somewhat larger for the same-sex parent. Further, we observe that the link between parental DM and young adults' BMI is strongest when both parents have diagnosed diabetes. In contrast, the relationship between second-degree relatives with DM and the respondent's BMI is weaker and appears to be sex-specific, through same-sex parent and respondent. Logistic regressions show the association is especially strong when assessing how parental DM status relates to young adults' obesity risk. These results generally persist when controlling for parental BMI. The findings of this study point to the need to better distinguish the role of shared family environments (e.g., eating and physical activity patterns) from shared genes in order to understand factors that may influence young adults' BMI. Young adult offspring of parents with diabetes should be targeted for obesity prevention efforts in order to reduce their risks of obesity and perhaps diabetes.

Tract- and county-level income inequality and individual risk of obesity in the United States.

OBJECTIVES: We tested three alternative hypotheses regarding the relationship between income inequality and individual risk of obesity at two geographical scales: U.S. Census tract and county. METHODS: Income inequality was measured by Gini coefficients, created from the 2000 U.S. Census. Obesity was clinically measured in the 2003-2008 National Health and Nutrition Examination Survey (NHANES). The individual measures and area measures were geo-linked to estimate three sets of multi-level models: tract only, county only, and tract and county simultaneously. Gender was tested as a moderator. RESULTS: At both the tract and county levels, higher income inequality was associated with lower individual risk of obesity. The size of the coefficient was larger for county-level Gini than for tract-level Gini; and controlling income inequality at one level did not reduce the impact of income inequality at the other level. Gender was not a significant moderator for the obesity-income inequality association. CONCLUSIONS: Higher tract and county income inequality was associated with lower individual risk of obesity, indicating that at least at the tract and county levels and in the context of cross-sectional data, the public health goal of reducing the rate of obesity is in line with anti-poverty policies of addressing poverty through mixed-income development where neighborhood income inequality is likely higher than homogeneous neighborhoods.

Rural-urban differences in objective and subjective measures of physical activity: findings from the National Health and Nutrition Examination Survey (NHANES) 2003-2006.

INTRODUCTION: Lower levels of physical activity among rural relative to urban residents have been suggested as an important contributor to rural-urban health disparity; however, empirical evidence is sparse. METHODS: We examined rural-urban differences in 4 objective physical activity measures (2 intensity thresholds by 2 bout lengths) and 4 subjective measures (total, leisure, household, and transportation) in a nationally representative sample of participants in the National Health and Nutrition Examination Survey (NHANES) 2003-2006. The sample comprised 5,056 adults aged 20 to 75 years. Rural-Urban Commuting Area (RUCA) codes were matched with NHANES subjects to identify urban status and 2 types of rural status. Rural-urban and within-rural differences in physical activity were estimated without and with controls for demographic and socioeconomic variables. RESULTS: Rural residents were less active than urban residents in high-intensity long bout (2,020 counts per minute threshold and 10 miniutes or longer bout length) accelerometer-measured physical activity (42.5 ± 6.2 min/wk vs 55.9 ± 2.8 min/wk) but the difference disappeared with a lower-intensity threshold (760 counts per minute). Rural residents reported more total physical activity than urban residents (438.3 ± 35.3min/wk vs 371.2 ± 12.5 min/wk), with differences primarily attributable to household physical activity. Within rural areas, micropolitan residents were less active than residents in smaller rural areas. Controlling for other variables reduced the size of the differences. CONCLUSION: The direction and significance of rural-urban difference in physical activity varied by the method of physical activity measurement, likely related to rural residents spending more time in low-intensity household physical activity but less time in high-intensity physical activity. Micropolitan residents were substantially less active than residents in smaller rural areas, indicating that physical activity did not vary unidirectionally with degree of urbanization.

Harvesting more than vegetables: the potential weight control benefits of community gardening.

OBJECTIVES: We examined the association of participation in community gardening with healthy body weight. METHODS: We examined body mass index (BMI) data from 198 community gardening participants in Salt Lake City, Utah, in relationship to BMI data for 3 comparison groups: neighbors, siblings, and spouses. In comparisons, we adjusted for gender, age, and the year of the BMI measurement. RESULTS: Both women and men community gardeners had significantly lower BMIs than did their neighbors who were not in the community gardening program. The estimated BMI reductions in the multivariate analyses were -1.84 for women and -2.36 for men. We also observed significantly lower BMIs for women community gardeners compared with their sisters (-1.88) and men community gardeners compared with their brothers (-1.33). Community gardeners also had lower odds of being overweight or obese than did their otherwise similar neighbors. CONCLUSIONS: The health benefits of community gardening may go beyond enhancing the gardeners' intake of fruits and vegetables. Community gardens may be a valuable element of land use diversity that merits consideration by public health officials who want to identify neighborhood features that promote health.

Re-visiting the relationship between neighbourhood environment and BMI: an instrumental variables approach to correcting for residential selection bias.

BACKGROUND: A burgeoning literature links attributes of neighbourhoods' built environments to residents' physical activity, food and transportation choices, weight, and/or obesity risk. In cross-sectional studies, non-random residential selection impedes researchers' ability to conclude that neighbourhood environments cause these outcomes. METHODS: Cross-sectional data for the current study are based on 14,689 non-Hispanic white women living in Salt Lake County, Utah, USA. Instrumental variables techniques are used to adjust for the possibility that neighbourhoods may affect weight but heavier or lighter women may also choose to live in certain neighbourhoods. All analyses control for the average BMI of siblings and thus familial predisposition for overweight/obesity, which is often an omitted variable in past studies. RESULTS: We find that cross-sectional analyses relating neighbourhood characteristics to BMI understate the strength of the relationship if they do not make statistical adjustments for the decision to live in a walkable neighbourhood. Standard cross-sectional estimation reveals no significant relationship between neighbourhood walkability and BMI. However, the instrumental variables estimates reveal statistically significant effects. CONCLUSIONS: We find evidence that residential selection leads to an understatement of the causal effects of neighbourhood walkability features on BMI. Although caution should be used in generalizing from research done with one demographic group in a single locale, our findings support the contention that public policies designed to alter neighbourhood walkability may moderately affect the BMI of large numbers of individuals.

Community and child energy balance: differential associations between neighborhood environment and overweight risk by gender.

Using data from the 2003 to 2004 continuous National Health Nutrition Examination Survey merged with the 2000 census and other geographic information systems-based neighborhood data, this study conducted gender-specific analyses to examine the influence of neighborhood characteristics on child risk for overweight (defined as gender-specific body mass index which is greater than the 85 percentile). Models of neighborhood influence that include institutional factors, built environment factors, and social modeling dynamics were tested. The study sample included 1753 (915 girls and 838 boys) children aged 2-11 years. Results indicate that institutional neighborhood features such as poverty in the census tract and rurality are associated with higher odds of risk of child overweight. Built environment factors also have connections to child risk of overweight, with long commute times within the census tract associated with higher overweight risk. Higher prevalence of physical activity is associated with lower risk of child overweight. Gender-specific analyses reveal that a higher prevalence of obesity (defined as BMI of greater than 30) within a census tract has a protective association with girls' risk of overweight. Boys' risk of overweight is associated with living in rural areas. These findings point to the importance of examining environmental aspects of child risk of overweight.

The changing food environment and neighborhood prevalence of type 2 diabetes.

In this ecological study, we used longitudinal data to assess if changes in neighborhood food environments were associated with type 2 diabetes mellitus (T2DM) prevalence, controlling for a host of neighborhood characteristics and spatial error correlation. We found that the population-adjusted prevalence of fast-food and pizza restaurants, grocery stores, and full-service restaurants along with changes in their numbers from 1990 to 2010 were associated with 2015 T2DM prevalence. The results suggested that neighborhoods where fast-food restaurants have increased and neighborhoods where full-service restaurants have decreased over time may be especially important targets for educational campaigns or other public health-related T2DM interventions.

Sex and ethnic differences in validity of self-reported adult height, weight and body mass index.

OBJECTIVES: Describe self-reported and measured height, weight, and body mass index (BMI) stratified by sex and ethnicity in the United States, explore ethnic variations in the likelihood of under-reporting BMI, and investigate pathways linking race/ethnicity to the underassessment of BMI. DESIGN: An observational study. SETTING: The entire United States. PATIENTS OR PARTICIPANTS: Data were from the 2007-2008 National Health and Nutrition Examination Survey, a nationally representative sample of non-institutionalized civilian Americans. MAIN OUTCOME: Objectively measured and subjectively reported BMI. MEASURES: Independent variables include race/ethnicity (non-Hispanic Whites, non-Hispanic Blacks, Hispanics, and others), sex, age groups (age 20-29, 30-49, 50-69, and > or =70), marital status (currently married vs other marital categories), education (less than high school, high school graduate or equivalent, some college, college graduate or above), and poverty income ratio (PIR). RESULTS: This study confirmed that the use of reported BMI led to underestimates of the population prevalence of overweight and obesity due to the general tendency towards over-reporting height and under-reporting weight. Women were more likely than men to under-report BMI. And whites were more likely than Blacks and Hispanics to under-report BMI. Other factors positively associated with higher likelihood of under-reporting of BMI included overweight and obese weight status, aged > or =60 years, and college education. Among women, family income was an additional positive covariate. CONCLUSIONS: The results from this study underscore the need for frequently monitoring ethnic differences in validity of reported BMI and highlight the care which needs to be taken in making comparisons across sociodemographic groups based on reported BMI.

Effects of neighborhood walkability on healthy weight: assessing selection and causal influences.

Studies that examine the relationship between neighborhood characteristics and weight are limited because residents are not randomly distributed into neighborhoods. If associations are found between neighborhood characteristics and weight in observational studies, one cannot confidently draw conclusions about causality. We use data from the Utah Population Database (UPDB) that contain body mass index (BMI) information from all drivers holding a Utah driver license to undertake a cross-sectional analysis that compares the neighborhood determinants of BMI for youth and young adults. This analysis assumes that youth have little choice in their residential location while young adults have more choice. Our analysis makes use of data on 53,476 males and 47,069 females living in Salt Lake County in 2000. We find evidence of residential selection among both males and females when BMI is the outcome. The evidence is weaker when the outcomes are overweight or obesity. We conclude that studies that ignore the role of residential selection may be overstating the causal influence of neighborhood features in altering residents' BMI.

Are you what your mother weighs? Evaluating the impact of maternal weight trajectories on youth overweight.

In this study, we investigate how three alternative measures of maternal body mass index (BMI) relate to youth overweight. We contrast the typical cross-sectional measure of maternal BMI with a longitudinal mean and a standard deviation in maternal BMI. Using National Longitudinal Survey of Youth data, we estimate logistic regressions that relate maternal BMI to the risk of a youth being overweight while controlling for other familial characteristics. Participants in this study are 918 males and 841 females who were age 16-21 and either healthy weight or overweight in 2006. To be eligible for inclusion, teens were 15 years old by December 2006. After comparing several measures of maternal weight, we find that higher mean maternal BMI measured over the life of the adolescent has the strongest relationship with the odds of youth overweight for both male and female adolescents. For boys, a one unit increase in mother's mean BMI increases the odds of being overweight by 16% (OR = 1.16, 95% CI 1.11-1.20) while for girls the increase in the odds of being overweight is 13% (OR = 1.13, 95% CI 1.09-1.18). Our findings suggest that researchers should move beyond static measures of maternal weight when examining the correlates of youth BMI. Maternal weight histories offer additional insights about the youth's home environment that are associated with the risk of a youth being overweight.

Mixed land use and walkability: Variations in land use measures and relationships with BMI, overweight, and obesity.

Few studies compare alternative measures of land use diversity or mix in relationship to body mass index. We compare four types of diversity measures: entropy scores (measures of equal distributions of walkable land use categories), distances to walkable destinations (parks and transit stops), proxy measures of mixed use (walk to work measures and neighborhood housing ages), and land use categories used in entropy scores. Generalized estimating equations, conducted on 5000 randomly chosen licensed drivers aged 25-64 in Salt Lake County, Utah, relate lower BMIs to older neighborhoods, components of a 6-category land use entropy score, and nearby light rail stops. Thus the presence of walkable land uses, rather than their equal mixture, relates to healthy weight.

Walkability and body mass index density, design, and new diversity measures.

BACKGROUND: Rising rates of overweight and obesity in the U.S. have increased interest in community designs that encourage healthy weight. This study relates neighborhood walkability-density, pedestrian-friendly design, and two novel measures of land-use diversity-to residents' excess weight. METHODS: Walkable-environment measures include two established predictors, higher density and pedestrian-friendly design (intersections within 0.25 mile of each address), and two new census-based, land-use diversity measures: the proportion of residents walking to work and the median age of housing. In 2006, weight, height, age, and address data from 453,927 Salt Lake County driver licenses for persons aged 25-64 years were linked to 2000 Census and GIS street-network information that was analyzed in 2007-2008. Linear regressions of BMI and logistic regressions of overweight and obesity include controls for individual-level age and neighborhood-level racial/ethnic composition, median age of residents, and median family income. RESULTS: Increasing levels of walkability decrease the risks of excess weight. Approximately doubling the proportion of neighborhood residents walking to work decreases an individual's risk of obesity by almost 10%. Adding a decade to the average age of neighborhood housing decreases women's risk of obesity by about 8% and men's by 13%. Population density is unrelated to weight in four of six models, and inconsistently related to weight measures in two models. Pedestrian-friendly street networks are unrelated to BMI but related to lower risks of overweight and obesity in three of four models. CONCLUSIONS: Walkability indicators, particularly the two land-use diversity measures, are important predictors of body weight. Driver licenses should be considered as a source of data for community studies of BMI, as they provide extensive coverage at low cost.

Rural-Urban Disparities in Obesity Prevalence Among Working Age Adults in the United States: Exploring the Mechanisms.

PURPOSE: Higher prevalence rates of overweight and obesity in rural America have been consistently reported, but sources of these disparities are not well known. This study presented patterns and mechanisms of these disparities among working age Americans. DESIGN: Cross-sectional study. SETTING: United States of America. PARTICIPANTS: The study included 10 302 participants of the 2003-2008 National Health and Nutrition Examination Survey (NHANES) who were 20 to 64 years old, not pregnant, and with a body mass index ranging from 18.5 to 60. MEASURES: Individual-level data were from NHANES including age, gender, race/ethnicity, immigrant status, education, and family income. The outcomes were prevalence of obesity and prevalence of overweight and obesity combined. Neighborhood data were constructed from the 2000 US Census providing tract-level information on family median income and built environmental features and from the 2006 ESRI ArcGIS 9.3 Data DVD providing tract-level park location information. ANALYSIS: Geographic information system (GIS) methods were used to create a measure of spatial distance to local parks capturing park accessibility. Random intercept logistic and ordinal logit regression analyses were performed. FINDINGS: Multivariate regression results showed that the odds of obesity was higher in rural areas compared to urban areas (odds ratio = 1.358, P < .001) net of demographic controls and that this gap was largely attributable to individual educational attainment and neighborhood median household income and neighborhood built environmental features. After controlling for these hypothesized mediators, the elevated odds associated with rural residence was reduced by nearly 94% and rendered statistically insignificant. CONCLUSIONS: In this nationally representative cross-sectional sample, rural-urban obesity disparities were large and explained by rural-urban educational differences at the individual level and economic and built environmental differences at the neighborhood level.

Walkable neighborhoods and obesity: Evaluating effects with a propensity score approach.

BACKGROUND: Research investigating the connection between neighborhood walkability and obesity often overlooks the issue of nonrandom residential selection. METHODS: We use propensity score methods to adjust for the nonrandom selection into residential neighborhoods in this cross-sectional, observational study. The sample includes 103,912 women residing in Salt Lake County, Utah age 20 or older. We measured percentage living in neighborhoods with more walkability, area level measures of neighborhood characteristics, and obesity (body mass index (BMI) > 30). RESULTS: Our findings confirm previous work that observes an association between living in more walkable neighborhoods and lower obesity. After adjusting for nonrandom selection, the odds of being obese when living in a less walkable neighborhood increase. Specifically, the odds ratio for being obese without the propensity score correction is 1.12. After adjusting for nonrandom selection, the odds ratio for being obese is 1.19, an increase of six percent. CONCLUSION: Results demonstrate that residential selection bias inherent in cross-sectional analysis slightly attenuates the true association between neighborhood walkability and obesity. Results lend support to the growing body of research suggesting that more walkable neighborhoods have residents with a lower prevalence of obesity. Absent propensity score controls, the causal relationship between environment and obesity would be underestimated by 6%. Our analysis suggests there is an association between neighborhood walkability and obesity.

Neighborhood Context and Youth Physical Activity: Differential Associations by Gender and Age.

PURPOSE: The goal of this research is to examine the extent to which facets of neighborhood sociodemographic contexts influence individual-level physical activity (PA) among youth. DESIGN: Using National Health and Nutrition Examination Survey (NHANES), geographic information systems (GIS), and census data sources, we explicitly test whether built environment factors have differential associations depending on the age and gender of the youth living in urban census tracts. SETTING: Participants are from the NHANES 2003 to 2006 waves. PARTICIPANTS: The study sample for this article was 2706 youth aged 6 to 17 years with valid PA accelerometer measures. MEASURES: A measure of park accessibility was constructed from the 2006 park GIS layer in Environmental System Research Institute ArcGIS 9.3 data. Average daily minutes of moderate to vigorous PA in bouts equal to or longer than 1 minute were recorded using accelerometers over 4 to 7 days. ANALYSIS: Analysis was conducted with SAS 9.2, including descriptive analyses and linear regression for PA. RESULTS: Findings suggest that built environment features are especially salient for adolescents and youth living in urban areas. Vigorous activity varied by the age and gender of the youth. For example, greater distance to parks is associated with a decrease in PA among girls and boys aged 6 to 11 years. Among teens, distance to parks is significantly associated with decreases in PA among the total sample and among male teens. However, an increase in population density is associated with less time spent in PA among youth aged 6 to 11 years but more PA among teens. CONCLUSION: These analyses represent an important step to considering the implications of modifiable environmental features for youth and contrast with existing literature for adults. Results speak to the efficacy of built environment measures in urban communities and the importance of considering the possibility of differing patterns of associations in childhood and adolescence and by gender. Results from this research inform policy efforts to interdict in the growing trend of youth inactivity in the United States.

The joint effects of family risk of obesity and neighborhood environment on obesity among women.

Obesity is a significant health problem in the United States that has encouraged a search for modifiable risk factors, such as walkable neighborhood designs. Prior research has shown linkages between a family history of obesity (i.e., due to either genetic or non-genetic factors) and an individual's risk of elevated body mass index (BMI). Yet, we know little about the possible interactions between neighborhood walkability and family susceptibility to unhealthy BMI in predicting individual BMI. This paper addresses this important research gap using a sample of 9918 women, derived from vital and administrative data in the Utah Population Database. We use a novel indicator of familial risk (a summary measure of siblings' BMI) and a neighborhood walkability score to capture familial susceptibility and environmental exposures, respectively. The analysis focuses on distinct risk combinations of familial susceptibility and neighborhood walkability. Compared with the "best" combination of lean family BMI history and more walkable neighborhoods, women in all of the other three family weight history/neighborhood categories show greater risks of obesity. Our results also indicate that the neighborhood environment has a strong association with individual obesity among women with higher family risk of obesity but that the association between neighborhood environment and individual obesity is even stronger for women with a lower family risk of obesity.

Sociodemographic and environmental correlates of active commuting in rural America.

PURPOSE: This research investigated participation rates in 3 modes of active commuting (AC) and their sociodemographic and physical environmental correlates in rural America. METHODS: The 2000 Census supplemented with other data sets were used to analyze AC rates in percentage of workers walking, biking, and taking public transportation to work in 14,209 nonmetropolitan rural tracts identified by RUCA codes, including 4,067 small rural and 10,142 town-micropolitan rural tracts. Sociodemographic and physical environmental variables were correlated with 3 AC modes simultaneously using Seemingly Unrelated Regression for nonmetro rural, and for small rural and town-micropolitan rural separately. FINDINGS: The average AC rates in rural tracts were 3.63%, 0.26%, and 0.56% for walking, biking, and public transportation to work, respectively, with small rural tracts having a higher rate of walking but lower rates of biking and public transportation to work than town-micropolitan tracts. In general, better economic well-being was negatively associated with AC but percentage of college-educated was a positive correlate. Population density was positively associated with AC but greenness and proximity to parks were negative correlates. However, significant differences existed for different AC modes, and between small rural and town-micropolitan rural tracts. CONCLUSIONS: Sociodemographic factors explained more variance in AC than physical environmental factors but the detailed relationships were complex, varying by AC mode and by degree of rurality. Any strategy to promote AC in rural America needs to be sensitive to the population size of the area and assessed in a comprehensive manner to avoid a "one size fits all" approach.

An ecological analysis of environmental correlates of active commuting in urban U.S.

We conduct a cross-sectional ecological analysis to examine environmental correlates of active commuting in 39,660 urban tracts using data from the 2010 Census, 2007-2011 American Community Survey, and other sources. The five-year average (2007-2011) prevalence is 3.05% for walking, 0.63% for biking, and 7.28% for public transportation to work, with higher prevalence for all modes in lower-income tracts. Environmental factors account for more variances in public transportation to work but economic and demographic factors account for more variances in walking and biking to work. Population density, median housing age, street connectivity, tree canopy, distance to parks, air quality, and county sprawl index are associated with active commuting, but the association can vary in size and direction for different transportation mode and for higher-income and lower-income tracts.

Geographic scale matters in detecting the relationship between neighbourhood food environments and obesity risk: an analysis of driver license records in Salt Lake County, Utah.

OBJECTIVES: Empirical studies of the association between neighbourhood food environments and individual obesity risk have found mixed results. One possible cause of these mixed findings is the variation in neighbourhood geographic scale used. The purpose of this paper was to examine how various neighbourhood geographic scales affected the estimated relationship between food environments and obesity risk. DESIGN: Cross-sectional secondary data analysis. SETTING: Salt Lake County, Utah, USA. PARTICIPANTS: 403,305 Salt Lake County adults 25-64 in the Utah driver license database between 1995 and 2008. ANALYSIS: Utah driver license data were geo-linked to 2000 US Census data and Dun & Bradstreet business data. Food outlets were classified into the categories of large grocery stores, convenience stores, limited-service restaurants and full-service restaurants, and measured at four neighbourhood geographic scales: Census block group, Census tract, ZIP code and a 1 km buffer around the resident's house. These measures were regressed on individual obesity status using multilevel random intercept regressions. OUTCOME: Obesity. RESULTS: Food environment was important for obesity but the scale of the relevant neighbourhood differs for different type of outlets: large grocery stores were not significant at all four geographic scales, limited-service restaurants at the medium-to-large scale (Census tract or larger) and convenience stores and full-service restaurants at the smallest scale (Census tract or smaller). CONCLUSIONS: The choice of neighbourhood geographic scale can affect the estimated significance of the association between neighbourhood food environments and individual obesity risk. However, variations in geographic scale alone do not explain the mixed findings in the literature. If researchers are constrained to use one geographic scale with multiple categories of food outlets, using Census tract or 1 km buffer as the neighbourhood geographic unit is likely to allow researchers to detect most significant relationships.