Pasquale E. Rummo

Neighborhood availability of convenience stores and diet quality: findings from 20 years of follow-up in the coronary artery risk development in young adults study.

OBJECTIVES We examined the association between neighborhood convenience stores and diet outcomes for 20 years of the Coronary Artery Risk Development in Young Adults study. METHODS We used dietary data from the Coronary Artery Risk Development in Young Adults study years 1985-1986, 1992-1993, and 2005-2006 (n = 3299; Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA) and geographically and temporally matched neighborhood-level food resource and US Census data. We used random effects repeated measures regression to estimate associations between availability of neighborhood convenience stores with diet outcomes and whether these associations differed by individual-level income. RESULTS In multivariable-adjusted analyses, greater availability of neighborhood convenience stores was associated with lower diet quality (mean score = 66.3; SD = 13.0) for participants with lower individual-level income (b = -2.40; 95% CI = -3.30, -1.51); associations at higher individual-level income were weaker. We observed similar associations with whole grain consumption across time but no statistically significant associations with consumption of sugar-sweetened beverages, artificially sweetened beverages, snacks, processed meats, fruits, or vegetables. CONCLUSIONS The presence of neighborhood convenience stores may be associated with lower quality diets. Low-income individuals may be most sensitive to convenience store availability.OBJECTIVES We examined the association between neighborhood convenience stores and diet outcomes over 20 years of the Coronary Artery Risk Development in Young Adults (CARDIA) study.

Spatial-Temporal Modeling of Neighborhood Sociodemographic Characteristics and Food Stores

The literature on food stores, neighborhood poverty, and race/ethnicity is mixed and lacks methods of accounting for complex spatial and temporal clustering of food resources. We used quarterly data on supermarket and convenience store locations from Nielsen TDLinx (Nielsen Holdings N.V., New York, New York) spanning 7 years (2006-2012) and census tract-based neighborhood sociodemographic data from the American Community Survey (2006-2010) to assess associations between neighborhood sociodemographic characteristics and food store distributions in the Metropolitan Statistical Areas (MSAs) of 4 US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and San Francisco, California). We fitted a space-time Poisson regression model that accounted for the complex spatial-temporal correlation structure of store locations by introducing space-time random effects in an intrinsic conditionally autoregressive model within a Bayesian framework. After accounting for census tract-level area, population, their interaction, and spatial and temporal variability, census tract poverty was significantly and positively associated with increasing expected numbers of supermarkets among tracts in all 4 MSAs. A similar positive association was observed for convenience stores in Birmingham, Minneapolis, and San Francisco; in Chicago, a positive association was observed only for predominantly white and predominantly black tracts. Our findings suggest a positive association between greater numbers of food stores and higher neighborhood poverty, with implications for policy approaches related to food store access by neighborhood poverty.

Fast food price, diet behavior, and cardiometabolic health: Differential associations by neighborhood SES and neighborhood fast food restaurant availability in the CARDIA study.

Little research has addressed whether neighborhood context influences associations between fast food price, diet, and cardiometabolic health. We investigated these associations using 25 years of Coronary Artery Risk Development in Young Adults (CARDIA) study data (n=4,469, observations=21,134). We found a negative association between fast food price and consumption, with stronger inverse associations in more (vs. less) deprived neighborhoods [3rd tertile: β=-0.68 (95% CI: (-0.85, -0.51); 1st tertile: β=-0.22 (95% CI: -0.42, -0.02); p-interaction-0.002], and a similar association for BMI [3rd tertile: β=-1.34 (95% CI: -1.54, -1.14); 1st tertile: β=-0.45 (95% CI: -0.66, -0.25); p-interaction<0.001], but not insulin resistance [3rd tertile: β=-0.07 (95% CI: -0.24, 0.09); 1st tertile: β=0.09 (95% CI: -0.08, 0.26); p-interaction=0.40]. We observed no modification of fast food price by fast food availability. Future research on obesity disparities should consider potential differences in the association between fast food prices and health outcomes across neighborhood socioeconomic levels.

Does unmeasured confounding influence associations between the retail food environment and body mass index over time? The Coronary Artery Risk Development in Young Adults (CARDIA) study

Background Findings in the observational retail food environment and obesity literature are inconsistent, potentially due to a lack of adjustment for residual confounding. Methods Using data from the CARDIA study (n = 12 174 person-observations; 6 examinations; 1985-2011) across four US cities (Birmingham, AL; Chicago, IL; Minneapolis, MN; Oakland, CA), we used instrumental-variables (IV) regression to obtain causal estimates of the longitudinal associations between the percentage of neighbourhood food stores or restaurants (per total food outlets within 1 km network distance of respondent residence) with body mass index (BMI), adjusting for individual-level socio-demographics, health behaviours, city, year, total food outlets and market-level prices. To determine the presence and extent of bias, we compared the magnitude and direction of results with ordinary least squares (OLS) and random effects (RE) regression, which do not control for residual confounding, and with fixed effects (FE) regression, which does not control for time-varying residual confounding. Results Relative to neighbourhood supermarkets (which tend to be larger and have healthier options than grocery stores), a higher percentage of grocery stores [mean = 53.4%; standard deviation (SD) = 31.8%] was positively associated with BMI [β = 0.05; 95% confidence interval (CI) = 0.01, 0.10] using IV regression. However, associations were negligible or null using OLS (β = -0.001; 95% CI = -0.01, 0.01), RE (β = -0.003; 95% CI = -0.01, 0.0001) and FE (β = -0.003; 95% CI = -0.01, 0.0002) regression. Neighbourhood convenience stores and fast-food restaurants were not associated with BMI in any model. Conclusions Longitudinal associations between neighbourhood food outlets and BMI were greater in magnitude using a causal model, suggesting that weak findings in the literature may be due to residual confounding.

Understanding bias in relationships between the food environment and diet quality: the Coronary Artery Risk Development in Young Adults (CARDIA) study

Background The relationship between food environment exposures and diet behaviours is unclear, possibly because the majority of studies ignore potential residual confounding. Methods We used 20 years (1985–1986, 1992–1993 2005–2006) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study across four US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California) and instrumental variables (IV) regression to obtain causal estimates of longitudinal associations between the percentage of neighbourhood food outlets (per total food outlets within 1 km network distance of respondent residence) and an a priori diet quality score, with higher scores indicating higher diet quality. To assess the presence and magnitude of bias related to residual confounding, we compared results from causal models (IV regression) to non-causal models, including ordinary least squares regression, which does not account for residual confounding at all and fixed-effects regression, which only controls for time-invariant unmeasured characteristics. Results The mean diet quality score across follow-up was 63.4 (SD=12.7). A 10% increase in fast food restaurants (relative to full-service restaurants) was associated with a lower diet quality score over time using IV regression (β=−1.01, 95% CI −1.99 to –0.04); estimates were attenuated using non-causal models. The percentage of neighbourhood convenience and grocery stores (relative to supermarkets) was not associated with diet quality in any model, but estimates from non-causal models were similarly attenuated compared with causal models. Conclusion Ignoring residual confounding may generate biased estimated effects of neighbourhood food outlets on diet outcomes and may have contributed to weak findings in the food environment literature.

How do individual-level sociodemographics and neighbourhood-level characteristics influence residential location behaviour in the context of the food and built environment? Findings from 25 years of follow-up in the CARDIA Study

Background Little is known about how diet-related and activity-related amenities relate to residential location behaviour. Understanding these relationships is essential for addressing residential self-selection bias. Methods Using 25 years (6 examinations) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study (n=11 013 observations) and linked neighbourhood-level data from the 4 CARDIA baseline cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California, USA), we characterised participants’ neighbourhoods as having low, average or high road connectivity and amenities using non-hierarchical cluster analysis. We then used repeated measures multinomial logistic regression with random effects to examine the associations between individual-level sociodemographics and neighbourhood-level characteristics with residential neighbourhood types over the 25-year period, and whether these associations differed by individual-level income. Results Being female was positively associated with living in neighbourhoods with low (vs high) road connectivity and activity-related and diet-related amenities among high-income individuals only. At all income levels, a higher percentage of neighbourhood white population and neighbourhood population <18 years were associated with living in neighbourhoods with low (vs high) connectivity and amenities. Individual-level race; age; and educational attainment, neighbourhood socioeconomic status and housing prices did not influence residential location behaviour related to neighbourhood connectivity and amenities at any income level. Conclusions Neighbourhood-level factors appeared to play a comparatively greater role in shaping residential location behaviour than individual-level sociodemographics. Our study is an important step in understanding how residential locational behaviour relates to amenities and physical activity opportunities, and may help mitigate residential self-selection bias in built environment studies.

In Which Neighborhoods Are Older Adult Populations Expanding? Sociodemographic and Built Environment Characteristics Across Neighborhood Trajectory Classes of Older Adult Populations in Four U.S. Cities Over 30 Years

Objective: We sought to examine characteristics of neighborhoods with changing older adult populations. Method: We used 30 years (1980-2011) of data from four U.S. cities (n = 392 neighborhoods; Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California) and finite mixture modeling to identify trajectory classes: neighborhoods with “stable,” declining, or increasing older adult populations (≥65 years). We then compared mean baseline and change in their characteristics. Results: Neighborhoods with an increasing (vs. “stable”) percentage of older adult populations had lower initial poverty and greater increases in education and income, with lower increases in road connectivity, population density, and housing prices/debt over time. The same was true for neighborhoods with declining older adult populations, with the exception of having higher increases in housing prices/debt. We observed few significant differences in neighborhood amenities or parks across classes. Conclusion: Our results emphasize the need to consider built and social environments when planning communities for older adults.

Food environment does not predict self-reported SSB consumption in New York City: A cross sectional study

The purpose of this research was to examine whether the local food environment, specifically the distance to the nearest sugar sweetened beverage (SSB) vendor, a measure of SSB availability and accessibility, was correlated with the likelihood of self-reported SSB consumption among a sample of fast food consumers. As part of a broader SSB behavior study in 2013–2014, respondents were surveyed outside of major chain fast food restaurants in New York City (NYC). Respondents were asked for the intersection closest to their home and how frequently they consume SSBs. Comprehensive, administrative food outlet databases were used to geo-locate the SSB vendor closest to the respondents’ home intersections. We then used a logistic regression model to estimate the association between the distance to the nearest SSB vendor (overall and by type) and the likelihood of daily SSB consumption. Our results show that proximity to the nearest SSB vendor was not statistically significantly associated with the likelihood of daily SSB consumption, regardless of type of vendor. Our results are robust to alternative model specifications, including replacing the linear minimum distance measure with count of the total number of SSB vendors or presence of a SSB vendor within a buffer around respondents’ home intersections. We conclude that there is not a strong relationship between proximity to nearest SSB vendor, or proximity to a specific type of SSB vendor, and frequency of self-reported SSB consumption among fast food consumers in NYC. This suggests that policymakers focus on alternative strategies to curtail SSB consumption, such as improving the within-store food environment or taxing SSBs.

Correction to: Change in Obesity Prevalence among New York City Adults: the NYC Health and Nutrition Examination Survey, 2004 and 2013–2014

Readers should note the following two typographical errors in this article.

Neighborhood availability of convenience stores and diet quality: findings from 20 years of follow-up in CARDIA

OBJECTIVES We examined the association between neighborhood convenience stores and diet outcomes for 20 years of the Coronary Artery Risk Development in Young Adults study. METHODS We used dietary data from the Coronary Artery Risk Development in Young Adults study years 1985-1986, 1992-1993, and 2005-2006 (n = 3299; Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA) and geographically and temporally matched neighborhood-level food resource and US Census data. We used random effects repeated measures regression to estimate associations between availability of neighborhood convenience stores with diet outcomes and whether these associations differed by individual-level income. RESULTS In multivariable-adjusted analyses, greater availability of neighborhood convenience stores was associated with lower diet quality (mean score = 66.3; SD = 13.0) for participants with lower individual-level income (b = -2.40; 95% CI = -3.30, -1.51); associations at higher individual-level income were weaker. We observed similar associations with whole grain consumption across time but no statistically significant associations with consumption of sugar-sweetened beverages, artificially sweetened beverages, snacks, processed meats, fruits, or vegetables. CONCLUSIONS The presence of neighborhood convenience stores may be associated with lower quality diets. Low-income individuals may be most sensitive to convenience store availability.OBJECTIVES We examined the association between neighborhood convenience stores and diet outcomes over 20 years of the Coronary Artery Risk Development in Young Adults (CARDIA) study.