The Los Angeles Family and Neighborhood Survey (L.A.FANS) is a longitudinal study that was undertaken to understand how neighborhoods affect a variety of outcomes, including health in adults. We used data from L.A.FANS 2000–2001, the first wave of the study, a stratified random sample of 65 neighborhoods (census tracts from the 1990 Census) in Los Angeles County designed to oversample poor neighborhoods or those census tracts with a high proportion of residents living below the poverty line. Twenty tracts were selected from the very poor group (the top 10% of the poverty distribution in Los Angeles County), 20 from the poor strata (tracts in the 60th–89th percentile) and the remaining 25 tracts comprise the non-poor (tracts in the bottom 60% of the distribution). The choice of three strata and the specific cutoffs were based on analysis that examined the trade-off under different schemes between likely yield of welfare recipients and the concentration of the sample in a small number of high poverty areas.24 The household survey asked adults about household economic status, education, employment, income, marital history, and neighborhoods of residence. We eliminated respondents for whom either income (n = 37) or BMI (n = 273) was missing and for whom BMI was >47 (n = 10) as well as those who listed their income as “0” but who were also employed (n = 23). We also eliminated “other race/ethnicity” (n = 74) because of small sample size. Our final sample size was 2,156 after eliminating two very large census tracts (n = 88) that differed substantially from other tracts that were sampled, with areas larger than 126,000 acres and roadway miles greater than 350 miles. With these two tracts deleted, the largest census tract was 2,467 acres and contained 79 roadway miles.
Residential neighborhoods were identified at the census-tract level. The L.A.FANS sampling strategy was based on census tract boundaries identified from the 1990 Census (before data from the 2000 Census was available). When the survey was undertaken, in 2000–2001, data were extracted from the 2000 decennial census file. Because the 2000 census tract boundaries were somewhat different from the 1990 census tract boundaries, we computed census tract values for the old boundaries as a population-weighted average of all new census tracts falling within the old boundaries (only the population of the new census tract that falls within the old boundaries is used in constructing weights). For example, if a 1990 census tract was split into two 2000 census tracts, we computed a weighted average of the two census tracts where the weights are proportional to the 2000 tract population.
Respondents were asked to provide their height and weight; from this information, each respondent's BMI was calculated in kilograms per square meter. BMI was analyzed as a continuous outcome.
Fast Food Restaurants
We obtained a list of all restaurants in Los Angeles County from the L.A. County Department of Public Health, Environmental Health Division and used the 1997 North American Industry Classification system codes to identify fast food restaurants (limited-service restaurants considered chains or franchises). Data on the fast food outlets were merged with individual-level data using census tracts (see Appendix A for complete list of outlets included). The number of fast food outlets within a census tract was divided by census tract roadway miles to create a fast food density measure for each census tract. Roadway miles came from Department of Commerce-2000 Census boundary files.
The fast food density measure was divided into three groups. The reference group included all census tracts with no fast food outlets. The second and third groups were created by dividing the remaining census tracts at the midpoint, defined as “low fast food density” (range, 0.025–0.15 fast food outlets/roadway miles) and “high fast food density” (range, 0.16–0.43 fast food outlets/roadway miles).
Other Food Outlets
Total food outlets per roadway miles within the census tract were also calculated using the list of all restaurants provided by the L.A. County Department of Public Health, Environmental Health Division. We specifically excluded restaurants that did not have public access, such as catering businesses, and those that were located within sports arenas, private clubs, cinemas, senior citizen centers, airports and hotels; we also excluded restaurants that were located in bars, pool halls, stores such as Kmart and Target, and restaurants within supermarkets (i.e., delis and bakeries).
The total restaurant measure was divided into three groups. The reference group included all census tracts with no restaurants. The second and third groups were created by dividing the remaining census tracts at the midpoint, defined as “total restaurants: low density” (range, 0.04–0.57 restaurants/roadway miles) and “total restaurants: high density” (range, 0.59–9.93 restaurants/roadway miles). The total restaurant measure included fast food outlets.
Residential Neighborhood Disadvantage
Four summary statistics of census tracts in Los Angeles County were each standardized and combined to create a neighborhood “disadvantage score,” a well-described and often-used measure of socioeconomic status (SES)25: (1) percent living below the poverty line, (2) percent of households that are headed by a woman, (3) percent male unemployment, and (4) percent of families receiving public assistance. The continuous disadvantage score of residential neighborhoods was used for regression analysis, lower scores referring to higher SES areas. The score was categorized into four quartiles based on the distribution of all census tracts in Los Angeles and referred to as Very Low (the most disadvantaged), Lower Middle, Upper Middle, and Very High SES areas for Tables 1 and 2.
Respondents were asked in the survey whether or not they or their spouse/partner had one or more working cars. Car ownership was separated into two categories, those who had access to a working car and those who did not; the reference category refers to those respondents who did not have access to a working car.
Models were controlled for (1) gender; (2) age (logged); (3) education; (4) race/ethnicity (Latino, African-American, Asian, white); (5) employment; (6) marital status; (7) annual household income (logged); (8) immigrant status; and (9) car ownership (respondent or spouse/partner owns one or more working cars).
The study used a multistage stratified sample design in which tracts, blocks within tracts, and households within tracts were sampled. Tracts were stratified by the percentage of the population in the tract who were in high poverty and by whether household included children under age 18. Sampling weights provided by L.A.FANS reflect both unequal probabilities of sample selection and household nonresponse.24 Weights were used as probability weights in HLM 6.02 (2004).26
Multilevel weighted linear regression models using HLM 6.02 (2004)26 were used to estimate simultaneously the association between BMI and the individual sociodemographic variables and residential neighborhood characteristics.
Cross level interactions between fast food/total restaurant concentration (level 2) and car ownership (level 1) were examined to determine whether car ownership moderated the effect of fast food concentration on BMI.