Background

The United States Department of Agriculture’s Supplemental Nutrition Assistance Program (SNAP) is the country’s largest nutrition assistance program for low-income populations. Although SNAP has been shown to reduce food insecurity, research findings on the diet quality of program participants are inconsistent.

Objective

This study evaluated whether the community food environment is a potential moderator of the association between SNAP participation and eating behaviors.

Design

This cross-sectional study used participant data from a telephone survey of 2,211 households in four cities in New Jersey. Data were collected from two cross-sectional panels from 2009 to 2010 and 2014. Food outlet data were purchased from commercial sources and classified as supermarkets, small grocery stores, convenience stores, or limited service restaurants.

Participants/setting

Analysis is limited to 983 respondents (588 SNAP participants) with household incomes below 130% of the federal poverty level.

Main outcome measures

Eating behaviors were assessed as frequency of consumption of fruit, vegetables, salad, and sugar-sweetened beverages.

Statistical analyses performed

Interaction and stratified analyses using gamma regression determined the differences in the association between SNAP participation and eating behaviors by the presence or absence of food outlets adjusted for covariates.

Results

SNAP participation was associated with a higher frequency of consuming sugar-sweetened beverages (P<0.05) when respondents lived within ¼ to ½ mile of a small grocery store, supermarket, and limited service restaurant. SNAP participants who did not live close to a convenience store reported a lower frequency of sugar-sweetened beverage consumption (P=0.01), and those living more than ½ mile away from a supermarket reported a lower frequency of fruit consumption (P=0.03).

Conclusions

The findings from this study suggest that the community food environment may play a role in moderating the association between SNAP participation and eating behaviors. Although SNAP participation is associated with some unhealthy behaviors, this association may only hold true when respondents live in certain food environments.

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

Disparities in healthy food access are well documented in cross-sectional studies in communities across the United States. However, longitudinal studies examining changes in food environments within various neighborhood contexts are scarce. In a sample of 142 census tracts in four low-income, high-minority cities in New Jersey, United States, we examined the availability of different types of food stores by census tract characteristics over time (2009–2017). Outlets were classified as supermarkets, small grocery stores, convenience stores, and pharmacies using multiple sources of data and a rigorous protocol. Census tracts were categorized by median household income and race/ethnicity of the population each year. Significant declines were observed in convenience store prevalence in lower- and medium-income and majority black tracts (p for trend: 0.004, 0.031, and 0.006 respectively), while a slight increase was observed in the prevalence of supermarkets in medium-income tracts (p for trend: 0.059). The decline in prevalence of convenience stores in lower-income and minority neighborhoods is likely attributable to declining incomes in these already poor communities. Compared to non-Hispanic neighborhoods, Hispanic communities had a higher prevalence of small groceries and convenience stores. This higher prevalence of smaller stores, coupled with shopping practices of Hispanic consumers, suggests that efforts to upgrade smaller stores in Hispanic communities may be more sustainable.

Introduction

The US Preventive Services Task Force recommends that all patients be screened for obesity and, if needed, be provided weight-loss advice. However, the prevalence of such advice is low and varies by patient demographics. This study aimed to describe the determinants of receiving weight-loss advice among a sample with a high proportion of low-income, racial/ethnic minority individuals.

Methods

Data were collected from a telephone survey of 1,708 households in 2009 and 2010 in 5 cities in New Jersey. Analyses were limited to 1,109 overweight or obese adults. Multivariate logistic regression determined the association of participants’ characteristics with receiving weight-loss advice from their health care provider. Two models were used to determine differences by income and insurance status.

Results

Of all overweight or obese respondents, 35% reported receiving advice to lose weight. Receiving advice was significantly associated with income in multivariate analysis. Compared with those with an income at or below 100% of the federal poverty level (FPL), those within 200% to 399% of the FPL had 1.60 higher odds of receiving advice (P = .02), and those with an income of 400% or more of the FPL had 1.73 higher odds of receiving advice (P = .03). The strength of the association did not change after adjusting for health insurance.

Conclusion

Income is a significant predictor of whether or not overweight or obese adults receive weight-loss advice after adjustment for demographic variables, health status, and insurance status. Further work is needed to examine why disparities exist in who receives weight-loss advice. Health care providers should provide weight-loss advice to all patients, regardless of income.