Improving access to healthy foods in low-income neighborhoods is a national priority. Our study evaluated the impact of opening a supermarket in a ‘food desert’ on healthy food access, availability and prices in the local food environment. We conducted 30 comprehensive in-store audits collecting information on healthy and unhealthy food availability, food prices and store environment, as well as 746 household surveys in two low-income neighborhoods before and after one of the two neighborhoods received a new supermarket. We found positive and negative changes in food availability, and an even greater influence on food prices in neighborhood stores. The supermarket opening in a ‘food desert’ caused little improvement in net availability of healthy foods, challenging the underpinnings of policies such as the Healthy Food Financing Initiative.
Objectives. To examine the impact of COVID-19 shutdowns on food insecurity among a predominantly African American cohort residing in low-income racially isolated neighborhoods. Methods. Residents of 2 low-income African American food desert neighborhoods in Pittsburgh, Pennsylvania, were surveyed from March 23 to May 22, 2020, drawing on a longitudinal cohort (n = 605) previously followed from 2011 to 2018. We examined longitudinal trends in food insecurity from 2011 to 2020 and compared them with national trends. We also assessed use of food assistance in our sample in 2018 versus 2020. Results. From 2018 to 2020, food insecurity increased from 20.7% to 36.9% (t = 7.63; P < .001) after steady declines since 2011. As a result of COVID-19, the United States has experienced a 60% increase in food insecurity, whereas this sample showed a nearly 80% increase, widening a preexisting disparity. Participation in the Supplemental Nutrition Assistance Program (52.2%) and food bank use (35.9%) did not change significantly during the early weeks of the pandemic. Conclusions. Longitudinal data highlight profound inequities that have been exacerbated by COVID-19. Existing policies appear inadequate to address the widening gap. (Am J Public Health. Published online ahead of print January 21, 2021: e1–e4. https://doi.org/10.2105/AJPH.2020.306041 )
Both how residents perceive their neighborhood and their exposure to objectively measured neighborhood disorder, lighting, and crime have implications for sleep continuity. These findings suggest that neighborhood conditions may contribute to disparities in sleep health.
Purpose Neighborhood-level socioeconomic disadvantage and lower individual-level socioeconomic status are associated with poorer sleep health in adults. However, few studies have examined the association between neighborhood-level disadvantage and sleep in adolescents, a population at high-risk for sleep disturbances. Methods The current study is the first to examine how objective (i.e. via census tract-level data) and subjective measures of neighborhood disadvantage are associated with sleep in a racially/ ethnically and socioeconomically diverse sample of 2,493 youth [Non-Hispanic White (20%), Hispanic (46%), Asian (21%), and Multiracial/ Other (13%)]. Results Findings indicated that greater perceived neighborhood-level social cohesion and lower neighborhood-level poverty were associated with better sleep outcomes in adolescents. However, there was some evidence that the magnitude of the associations differed according to family-level socioeconomic status and race/ ethnicity. Conclusions Findings suggest that subjective and objective neighborhood characteristics may affect the sleep health of older adolescents, with certain demographic subgroups being particularly vulnerable.
Background: Few studies have assessed objectively measured physical activity (PA), active transportation, psychological distress and neighborhood perceptions among residents of a neighborhood before and after substantial improvements in its physical environment. Also, most research-to-date has employed study designs subject to neighborhood selection, which may introduce bias in reported findings. We built upon a previously enrolled cohort of households from two low-income predominantly African American Pittsburgh neighborhoods, matched on socio-demographic composition including race/ethnicity, income and education. One of the two neighborhoods received substantial neighborhood investments over the course of this study including, but not limited to public housing development and greenspace/landscaping. We implemented a natural experiment using matched intervention and control neighborhoods and conducted pre-post assessments among the cohort. Our comprehensive assessments included accelerometry-based PA, active transportation, psychological distress and perceptions of the neighborhood, with assessments conducted both prior to and following the neighborhood changes. In 2013, we collected data from 1003 neighborhood participants and in 2016, we re-interviewed 676 of those participants. We conducted an intent to treat analysis, with a difference-indifference estimator using attrition weighting to account for nonresponse between 2013 and 2016. In addition, we derived an individual-level indicator of exposure to neighbourhood investment and estimated effect of exposure to investment on the same set of outcomes using covariate-adjusted models. Results: We observed no statistically significant differences in activity, psychological distress, satisfaction with one's neighborhood as a place to live or any of the other measures we observed prior to and after the neighborhood investments between the intervention and control neighborhoods or those exposed vs not exposed to investments.
Neighborhood socioeconomic conditions (NSEC) are associated with resident diet, but most research has been cross-sectional. We capitalize on a natural experiment where one neighborhood experienced substantial investments, compared to a sociodemographically similar neighborhood that did not, in order to examine pathways from neighborhood investments to changed NSEC and changed dietary behavior. We examine differences between renters and homeowners. Data are from a random sample of households (n=831) in each of these low-income Pittsburgh neighborhoods who were surveyed in 2011 and 2014. Structural equation modeling tested direct and indirect pathways from neighborhood to resident dietary quality, adjusting for individual-level sociodemographics, with multi-group testing by homeowners versus renters. Neighborhood investments were directly associated with improved dietary quality for both renters (β, 95% confidence interval [CI]) =0.27, CI: 0.05, 0.50) and homeowners (β=0.51, CI: 0.10, 0.92). Among renters, investments were also associated with dietary quality through a positive association with commercial prices (β= 0.34, CI: 0.15, 0.54) and a negative association with residential prices (β=-0.30, CI: -0.59, -0.004). Among homeowners, we did not observe any indirect pathways from investments to dietary quality through tested mediators. Investing in neighborhoods may support resident diet, doing so through improvements in neighborhood commercial environments for renters, but mechanisms appear to differ for homeowners.
Background: Perceived neighborhood characteristics, including satisfaction with one's neighborhood as a place to live, are associated with lower obesity rates and more favorable cardiovascular risk factor profiles. Yet, few studies have evaluated whether changes in perceived neighborhood characteristics over time may be associated with cardiometabolic health indicators. Methods: Changes in perception of one's neighborhood (2013)(2014)(2015)(2016) were determined from a cohort of residents who lived in one of two low-income urban neighborhoods. Changes were categorized into the following: improvement vs. no change or worsening over the three-year time-period. Multivariable linear regression was used to measure the association between perceived improvement in each of the neighborhood characteristics with cardiometabolic outcomes (BMI, SBP, DBP, HbA1c, HDL-c) that were assessed in 2016, and compared with those who perceived no change or worsening of neighborhood characteristics. Models were adjusted for age, sex, income, education, marital status, physical function, neighborhood, and years spent in neighborhood. To examine potential sex differences, follow-up models were conducted and stratified by sex. Results: Among the 622 individuals who remained in the same neighborhood during the time period, 93% were African American, 80% were female, and the mean age was 58 years. In covariate-adjusted models, those who perceived improvement in their neighborhood safety over the time period had a significantly higher BMI (kg/m 2 ) than those who perceived no improvement or worsening (β = 1.5, p = 0.0162); however, perceived improvement in safety was also significantly associated with lower SBP (mmHg) (β = − 3.8, p = 0.0361). When results were stratified by sex, the relationship between improved perceived neighborhood safety and BMI was only evident in females. Conclusions: These findings suggest that perceived neighborhood characteristics may impact cardiometabolic outcomes (BMI, SBP), but through differing pathways. This highlights the complexity of the associations between neighborhood characteristics and underscores the need for more longitudinal studies to confirm the associations with cardiometabolic health in African American populations.
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