Do Publicly Funded Neighborhood Investments Impact Individual-Level Health-Related Outcomes? A Longitudinal Study of Two Neighborhoods in Pittsburgh, PA from 2011 to 2018.

Research examining the relationship between a neighborhood's built-environment and resident health or health-related outcomes has largely either focused on static characteristics using a cross-sectional research design or focuses on the neighborhood in its entirety. Such an approach makes it difficult to understand how specific dynamic neighborhood characteristics are associated with individual well-being. In this analysis, we use longitudinal data from the Pittsburgh Research on Neighborhood Change and Health (PHRESH) studies to assess the relationship between publicly funded neighborhood investments occurring across seven years (2011-2018) on five health-related outcomes: food insecurity, stress, perceived neighborhood safety, neighborhood satisfaction, and dietary quality. We additionally utilize this dataset to determine whether the distance between an individual's place of residence and the investment, as measured at the neighborhood, 1 mile, and ½ mile level, effects the magnitude of associations. Using individual and year fixed effects models, we find that when measured at the neighborhood level, a one standard deviation increase in investments (about $130 million dollars) is associated with decreased food insecurity (-0.294 sd), increased safety (0.231 sd), and increased neighborhood satisfaction (0.201 sd) among adults who remain in the study for at least two waves of data collection. We also analyze specific investment types and find that commercial investments are largely driving the changes in food insecurity, safety, and neighborhood satisfaction, while business investments are correlated with the decrease in stress. We find no relationship between investments and dietary quality.

Police Bias and Low Relatability and Diet Quality: Examining the Importance of Psychosocial Factors in Predominantly Black Communities.

How police bias and low relatability may contribute to poor dietary quality is poorly understood. In this cross-sectional study, we analyzed data from 2021 from a cohort of n = 724 adults living in predominantly Black communities in Pittsburgh, Pennsylvania; these adults were mostly Black (90.6%), low-income (median household income $17,500), and women (79.3%). We estimated direct and indirect paths between police mistrust and dietary quality (measured by Healthy Eating Index (HEI)-2015) through perceived stress, community connectedness, and subjective social status. Dietary quality was poor (mean HEI-2015 score was 50) and mistrust of police was high: 78% of participants either agreed or strongly agreed that something they say might be interpreted as criminal by the police due to their race/ethnicity. Police bias and low relatability was associated with lower perceived social status [Formula: see text]= - 0.03 (95% confidence interval [CI]: - 0.05, - 0.01). Police bias and low relatability was marginally associated with low dietary quality ß = - 0.14 (95% CI: - 0.29, 0.02). Nineteen percent of the total association between police bias and low relatability and lower dietary quality ß = - 0.16 (- 0.01, - 0.31) was explained by an indirect association through lower community connectedness, or how close respondents felt with their community [Formula: see text] Police bias and low relatability may play a role in community connection, social status, and ultimately dietary disparities for Black Americans. Addressing police bias and low relatability is a continuing and pressing public health issue.

Students' consumption of high and low nutrition foods and reduced plate waste by schools' wellness-related policies and garden program participation.

BACKGROUND: Participation in school-based programs that may support children's nutritious dietary behaviours varies across schools. We examined school participation in wellness-related policies, school-based garden programs and students' dietary behaviours. METHODS: Among matching schools who did and did not participate in school-based garden programs, we analysed the lunches of 80 Pittsburgh Public Schools (PPS) students in 1st, 2nd, 6th and 7th grades during Autumn 2019 using digital food photography. We also acquired school wellness policy data. Using cross-sectional linear regression, we estimated the association between school-based garden programming, wellness-related policies and dietary outcomes, adjusting for grade. RESULTS: School's implementation of nutrition services policies was negatively associated with energy wasted from lunch ( ß = - 44.7 , p = 0.01 ${\rm{\beta }}=-44.7,{p}=0.01$ ). The number of semesters the students' school had participated in the garden program was positively associated with students' whole grain consumption ( ß = 0.07 , p < 0.001 ${\rm{\beta }}=0.07,{p}\lt 0.001$ ). CONCLUSIONS: Cross-sectional associations suggest that schools that are more engaged in wellness policies and garden programs may provide environments that are more supportive of students' nutrition than in other schools.

Improvements in Neighborhood Socioeconomic Conditions May Improve Resident Diet.

Neighborhood socioeconomic conditions (NSECs) are associated with resident diet, but most research has been cross-sectional. We capitalized on a natural experiment in Pittsburgh, Pennsylvania, in which 1 neighborhood experienced substantial investments and a sociodemographically similar neighborhood that did not, to examine pathways from neighborhood investments to changed NSECs and changed dietary behavior. We examined differences between renters and homeowners. Data were from a random sample of households (n = 831) in each of these low-income Pittsburgh neighborhoods that 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 multigroup testing by homeowners versus renters. Neighborhood investments were directly associated with improved dietary quality for renters (ß = 0.27, 95% confidence interval (CI): 0.05, 0.50) and homeowners (ß = 0.51, 95% CI: 0.10, 0.92). Among renters, investments also were associated with dietary quality through a positive association with commercial prices (ß = 0.34, 95% CI: 0.15, 0.54) and a negative association with residential prices (ß = -0.30, 95% 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 through improvements in neighborhood commercial environments for renters, but mechanisms appear to differ for homeowners.

Food Insecurity in a Low-Income, Predominantly African American Cohort Following the COVID-19 Pandemic.

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.

Improved Street Walkability, Incivilities, and Esthetics Are Associated with Greater Park Use in Two Low-Income Neighborhoods.

Parks may provide opportunities for people to increase their physical activity and improve health. Yet, parks are generally less plentiful and underutilized in low-income urban neighborhoods compared with more advantaged neighborhoods. Renovations within and around parks may improve park utilization but the empirical evidence supporting this relationship is scarce. This study assessed the impact of greenspace, housing, and commercial investments on street characteristics (walkability, amenities, incivilities/poor esthetics) and park use by examining park use over time in two low-income neighborhoods in Pittsburgh, PA (n = 17 parks), before and after neighborhood-based renovations that were primarily centered in one neighborhood. We used systematic observation of parks, park use, and street blocks surrounding parks to examine the impact of neighborhood changes on park use. We used difference-in-differences to test whether park use and street characteristics surrounding the parks improved more in the intervention neighborhood than in the comparison neighborhood. We also used zero-inflated negative binomial regression with interactions by time to test whether changes in street characteristics were associated with changes in park use over time. We found that improved walkability, incivilities, and esthetics surrounding parks in socioeconomically disadvantaged neighborhoods were associated with greater park use and may help increase visits to underutilized parks.

Broken Windows, Broken Zzs: Poor Housing and Neighborhood Conditions Are Associated with Objective Measures of Sleep Health.

African Americans and socioeconomically disadvantaged individuals have higher rates of a variety of sleep disturbances, including short sleep duration, poor sleep quality, and fragmented sleep. Such sleep disturbances may contribute to pervasive and widening racial and socioeconomic (SES) disparities in health. A growing body of literature demonstrates that over and above individual-level SES, indicators of neighborhood disadvantage are associated with poor sleep. However, there has been scant investigation of the association between sleep and the most proximal environments, the home and residential block. This is the first study to examine the association between objective and self-reported measures of housing and block conditions and sleep. The sample included 634 adults (mean age = 58.7 years; 95% African American) from two low-income urban neighborhoods. Study participants reported whether they experienced problems with any of seven different housing problems (e.g., broken windows) and rated the overall condition of their home. Trained data collectors rated residential block quality. Seven days of wrist actigraphy were used to measure average sleep duration, efficiency, and wakefulness after sleep onset (WASO), and a sleep diary assessed sleep quality. Multivariate regression analyses were conducted for each sleep outcome with housing or block conditions as predictors in separate models. Participants reporting "fair" or "poor" housing conditions had an adjusted average sleep duration that was 15.4 min shorter than that of participants reporting "good" or "excellent" conditions. Those reporting any home distress had 15.9 min shorter sleep and .19 units lower mean sleep quality as compared with participants who did not report home distress. Poor objectively measured block quality was associated with 14.0 min shorter sleep duration, 1.95% lower sleep efficiency, and 10.7 additional minutes of WASO. Adverse housing and proximal neighborhood conditions are independently associated with poor sleep health. Findings highlight the importance of considering strategies that target upstream determinants of sleep health disparities.

An audit tool for longitudinal assessment of the health-related characteristics of urban neighborhoods: implementation methods and reliability results.

BACKGROUND: Improving the neighborhood environment may help address chronic disease and mortality. To identify neighborhood features that are predictors of health, objective assessments of the environment are used. Multiple studies have reported on cross-sectional assessments of health-related neighborhood features using direct observation. As study designs expand to better understand causation and predictors of change, there is a need to test whether direct observation methods are adequate for longitudinal assessment. To our knowledge, this is the first study to report on the reliability of repeated measurements of the neighborhood environment, and their stability, over time. METHODS: The Pittsburgh Hill/Homewood Research on Neighborhood Change and Health (PHRESH) study conducted longitudinal assessments in two low-income, African American neighborhoods at three waves (years 2012, 2015, 2017). The PHRESH audit tool is a modification of earlier validated tools, with an emphasis on environment features relevant for physical activity, sleep, and obesogenic behaviors. Trained data-collector pairs conducted direct observations of a 25% sample of street segments in each neighborhood. At each wave, we audited a sub-sample of street segments twice and assessed reliability using percentage inter-observer agreement and krippendorf's alpha statistics. Stability of these items was assessed as exhibiting moderate or high agreement at every time point. RESULTS: Across waves, a majority (81%) of the items consistently demonstrated moderate to high agreement except for items such as public/communal space, amount of shade, sidewalk features, number of traffic lanes, garden/flower bed/planter, art/statue/monument, amount of trash, and physical disorder. The list of items with poor agreement includes features that are easy to miss (e.g. flower bed/planter), hard to assess from outside (e.g. public/communal space), or may change quickly (e.g. amount of trash). CONCLUSION: In this paper, we have described implementation methods, reliability results and lessons learned to inform future studies of change. We found the use of consistent methods allowed us to conduct reliable, replicable longitudinal assessments of the environment. Items that did not exhibit stability are less useful for detecting real change over time. Overall, the PHRESH direct observation tool is an effective and practical instrument to detect change in the neighborhood environment.

Food Insecurity is Associated with Objectively Measured Sleep Problems.

Objective/Background: Food Insecurity (FI) can be a profound source of stress, which may increase the risk for sleep disturbance. This is the first study to examine the association between FI and objectively and subjectively measured sleep. Participants: The sample included 785 adults living in two low-income neighborhoods (mean age = 56; 95% African American). Methods: FI was measured using a validated 10-item survey that assesses conditions and behaviors that characterize households when they lack financial resources to meet basic food needs. Sleep duration, efficiency, wakefulness after sleep onset (WASO), and variability in sleep duration were measured via actigraphy. Sleep quality was assessed via sleep diary. Sleep outcomes were analyzed as a function of FI, adjusting for covariates. Psychological distress was tested as a potential mediator. Results: Greater FI was associated with shorter actigraphy-assessed sleep duration (B = -2.44; SE = 1.24; i.e., 24 minutes shorter for the most as compared to least insecure group), poorer sleep efficiency (B = -.27; SE = .13); p's < .05), and poorer subjective sleep quality (B = -.03; SE = .01; p < .01). Greater FI was also associated with greater likelihood of short (<7 hours; OR = 1.11; CI: 1.02-1.21) and long sleep (>9 hours; OR = 1.19; CI: 1.01-1.39), compared to the recommended sleep duration of 7-9 hours. Psychological distress partially mediated the association between FI and subjective sleep quality. Conclusions: Addressing or mitigating food insecurity may present a novel opportunity for improving sleep health among low-income populations.

Results from a natural experiment: initial neighbourhood investments do not change objectively-assessed physical activity, psychological distress or perceptions of the neighbourhood.

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-in-difference 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. CONCLUSIONS: Using this rigorous study design, we observed no significant changes in the intervention neighborhood above and beyond secular trends present in the control neighborhood. Although neighborhood investment may have other benefits, we failed to see improvement in PA, psychological distress or related outcomes in the low-income African American neighborhoods in our study. This may be an indication that improvements in the physical environment may not directly translate into improvements in residents' physical activity or health outcomes without additional individual-level interventions. It is also possible that these investments were not dramatic enough to spur change within the three year period. Additional studies employing similar design with other cohorts in other settings are needed to confirm these results. TRIAL REGISTRATION: Trial Registration is not applicable since we did not prospectively assign individuals to a health-related intervention.

Pathways through which higher neighborhood crime is longitudinally associated with greater body mass index.

BACKGROUND: Although crime and perceived safety are associated with obesity and body mass index (BMI), the pathways are less clear. Two likely pathways by which crime and perceived safety may impact obesity are through distress and physical activity. METHODS: We examined data from 2013 to 2014 for 644 predominantly African-American adults (mean age 57 years; 77% female) living in low-income Pittsburgh, PA neighborhoods, including self-reported perceptions of safety and emotional distress, interviewer-measured height/weight, and physical activity measured via accelerometry. We used secondary data on neighborhood crime from 2011 to 2013. We built a structural equation model to examine the longitudinal direct and indirect pathways from crime to BMI through perceived safety, distress and physical activity. RESULTS: Long-term exposure to crime was positively associated with lack of perceived safety (ß = 0.11, p = 0.005) and lack of perceived safety was positively associated with BMI (ß = 0.08, p = 0.03). The beneficial association between physical activity and BMI (ß = -0.15, p < 0.001) was attenuated by a negative association between crime and physical activity (ß = -0.09, p = 0.01). Although crime was associated with distress we found no evidence of a path from crime to BMI via distress. CONCLUSIONS: Our findings suggest decrements in perceived safety and physical activity are important processes that might explain why neighborhood crime is associated with greater BMI.

One size doesn't fit all: cross-sectional associations between neighborhood walkability, crime and physical activity depends on age and sex of residents.

BACKGROUND: Low-income African American adults are disproportionately affected by obesity and are also least likely to engage in recommended levels of physical activity (Flegal et al. JAMA 303(3):235-41, 2010; Tucker et al. Am J Prev Med 40(4):454-61, 2011). Moderate-to-vigorous physical activity (MVPA) is an important factor for weight management and control, as well as for reducing disease risk (Andersen et al. Lancet 368(9532):299-304, 2006; Boreham and Riddoch J Sports Sci 19(12):915-29, 2001; Carson et al. PLoS One 8(8):e71417, 2013). While neighborhood greenspace and walkability have been associated with increased MVPA, evidence also suggests that living in areas with high rates of crime limits MVPA. Few studies have examined to what extent the confluence of neighborhood greenspace, walkability and crime might impact MVPA in low-income African American adults nor how associations may vary by age and sex. METHODS: In 2013 we collected self-reported data on demographics, functional limitations, objective measures of MVPA (accelerometry), neighborhood greenspace (geographic information system), and walkability (street audit) in 791 predominantly African-American adults (mean age 56 years) living in two United States (U.S.) low-income neighborhoods. We also acquired data from the City of Pittsburgh on all crime events within both neighborhoods. EXPOSURE: To examine cross-sectional associations of neighborhood-related variables (i.e., neighborhood greenspace, walkability and crime) with MVPA, we used zero-inflated negative binomial regression models. Additionally, we examined potential interactions by age (over 65 years) and sex on relationships between neighborhood variables and MVPA. RESULTS: Overall, residents engaged in very little to no MVPA regardless of where they lived. However, for women, but not men, under the age of 65 years, living in more walkable neighborhoods was associated with more time engaged in MVPA in (ß = 0.55, p = 0.007) as compared to their counterparts living in less walkable areas. Women and men age 65 years and over spent very little time participating in MVPA regardless of neighborhood walkability. Neither greenspace nor crime was associated with MVPA in age-sex subgroups. CONCLUSIONS: Neighborhood walkability may play a stronger role on MVPA than accessible greenspace or crime in low-income urban communities. Walkability may differentially impact residents depending on their age and sex, which suggests tailoring public health policy design and implementation according to neighborhood demographics to improve activity for all.

Evidence for Association between SH2B1 Gene Variants and Glycated Hemoglobin in Nondiabetic European American Young Adults: The Add Health Study.

Glycated hemoglobin (HbA1c) is used to classify glycaemia and type 2 diabetes (T2D). Body mass index (BMI) is a predictor of HbA1c levels and T2D. We tested 43 established BMI and obesity loci for association with HbA1c in a nationally representative multiethnic sample of young adults from the National Longitudinal Study of Adolescent to Adult Health [Add Health: age 24-34 years; n = 5641 European Americans (EA); 1740 African Americans (AA); 1444 Hispanic Americans (HA)] without T2D, using two levels of covariate adjustment (Model 1: age, sex, smoking, and geographic region; Model 2: Model 1 covariates plus BMI). Bonferroni adjustment was made for 43 SNPs and we considered P < 0.0011 statistically significant. Means (SD) for HbA1c were 5.4% (0.3) in EA, 5.7% (0.4) in AA, and 5.5% (0.3) in HA. We observed significant evidence for association with HbA1c for two variants near SH2B1 in EA (rs4788102, P = 2.2 × 10(-4) ; rs7359397, P = 9.8 × 10(-4) ) for Model 1. Both results were attenuated after adjustment for BMI (rs4788102, P = 1.7 × 10(-3) ; rs7359397, P = 4.6 × 10(-3) ). No variant reached Bonferroni-corrected significance in AA or HA. These results suggest that SH2B1 polymorphisms are associated with HbA1c, largely independent of BMI, in EA young adults.

Interaction of smoking and obesity susceptibility loci on adolescent BMI: The National Longitudinal Study of Adolescent to Adult Health.

BACKGROUND: Adolescence is a sensitive period for weight gain and risky health behaviors, such as smoking. Genome-wide association studies (GWAS) have identified loci contributing to adult body mass index (BMI). Evidence suggests that many of these loci have a larger influence on adolescent BMI. However, few studies have examined interactions between smoking and obesity susceptibility loci on BMI. This study investigates the interaction of current smoking and established BMI SNPs on adolescent BMI. Using data from the National Longitudinal Study of Adolescent to Adult Health, a nationally-representative, prospective cohort of the US school-based population in grades 7 to 12 (12-20 years of age) in 1994-95 who have been followed into adulthood (Wave II 1996; ages 12-21, Wave III; ages 18-27), we assessed (in 2014) interactions of 40 BMI-related SNPs and smoking status with percent of the CDC/NCHS 2000 median BMI (%MBMI) in European Americans (n = 5075), African Americans (n = 1744) and Hispanic Americans (n = 1294). RESULTS: Two SNPs showed nominal significance for interaction (p < 0.05) between smoking and genotype with %MBMI in European Americans (EA) (rs2112347 (POC5): ß = 1.98 (0.06, 3.90), p = 0.04 and near rs571312 (MC4R): ß 2.15 (-0.03, 4.33) p = 0.05); and one SNP showed a significant interaction effect after stringent correction for multiple testing in Hispanic Americans (HA) (rs1514175 (TNNI3K): ß 8.46 (4.32, 12.60), p = 5.9E-05). Stratifying by sex, these interactions suggest a stronger effect in female smokers. CONCLUSIONS: Our study highlights potentially important sex differences in obesity risk by smoking status in adolescents, with those who may be most likely to initiate smoking (i.e., adolescent females), being at greatest risk for exacerbating genetic obesity susceptibility.

Perceived stress, unhealthy eating behaviors, and severe obesity in low-income women.

BACKGROUND: Stress has been associated with poor eating behaviors and diet quality, as well as high body mass index (BMI). Low-income women may be particularly vulnerable to stress and severe obesity. Yet it is unknown how stress increases the risk of severe obesity through disordered eating behaviors and poor diet quality or through mechanisms independent of diet. METHODS: We examined cross-sectional data from women (n = 101) with a child enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children in Cumberland County, North Carolina (spring 2012). We collected measured heights and weights to calculate BMI. Using structural equation modeling, we differentiated pathways from stress to weight status: (1) indirectly through eating behaviors (cognitive restraint, emotional eating, and uncontrolled eating) and diet quality, which we examined with the Healthy Eating Index 2010 and 24-h dietary recalls, and (2) directly through possible unmeasured risk factors independent of diet. The analysis controlled for race/ethnicity, income, age, whether the dietary recall day was typical, and whether the respondent completed one or two 24-h dietary recalls. RESULTS: Perceived stress was positively associated with uncontrolled eating (ß = 0.38, p < 0.001) and emotional eating (ß = 0.50, p < 0.001). However, higher stress was not associated with weight status through eating behaviors and diet quality. Independent of eating behaviors and diet quality, stress was positively associated with severe obesity (ß = 0.26, p = 0.007). CONCLUSIONS: Improving stress coping strategies for low-income women may improve eating behaviors and reduce severe obesity.

Community Investments and Diet-Related Outcomes: A Longitudinal Study of Residents of Two Urban Neighborhoods.

INTRODUCTION: Investments in historically oppressed neighborhoods through food retail, housing, and commercial development are hypothesized to improve residents' health, nutrition, and perceptions of their neighborhood as a place to live. Although place-based development (e.g., housing, retail, business assistance) is happening in many communities, there is little evidence of the long-term correlates of multiple investments such as health and nutrition among residents. METHODS: A quasi-experimental longitudinal study was conducted using a cohort of randomly sampled households in two low-income, predominantly African American neighborhoods in Pittsburgh, PA, with surveys assessing residents' food insecurity, perception of their neighborhood as a place to live, perception of access to healthy foods, and dietary outcomes in 2011 and seven years later (2018), with an interim assessment in 2014. Analyses conducted in 2022 compared changes among residents of one neighborhood which had 2.6 times the investments over a 7-year period with changes among residents of a socio-demographically similar neighborhood that received fewer investments. RESULTS: It was found that residents in the neighborhood receiving substantial investments demonstrated statistically significant improvements in neighborhood satisfaction (12.6% improvement compared with a 2.2% decrease) and perceived access to healthy food (52% improvement compared with 18.2% improvement), and marginally significant change in food security (14% compared with 4.8% improvement) compared with residents in the neighborhood receiving fewer investments. CONCLUSIONS: Multiple place-based investments in neighborhoods can potentially induce positive change for residents in health and nutrition outcomes.

Food Insecurity Among Aging SNAP Participants and Eligible Nonparticipants in Two Predominantly Low-Income Black Neighborhoods: Implications for SNAP Enrollment and Outreach for Older Adults.

BACKGROUND: The Supplemental Nutrition Assistance Program (SNAP) plays a critical role in alleviating poverty and food insecurity. Despite these benefits, many older Americans who are eligible for SNAP do not participate in the program. Few studies have explored household factors and food insecurity outcomes associated with nonparticipation among older Black Americans. OBJECTIVES: The study aim was to explore changes in food insecurity and related financial hardship outcomes between 2020 and 2021 among SNAP participants, eligible nonparticipants, and ineligible nonparticipants; compare reasons for not participating in SNAP; and to compare household factors associated with SNAP nonparticipation. METHODS: Longitudinal design examining data from 2020 and 2021 to assess changes in food insecurity over the course of the coronavirus disease 2019 pandemic. PARTICIPANTS/SETTING: Participants were 528 adults (aged 30 to 97 years) in households randomly selected from a listing of all residential addresses in two predominantly Black neighborhoods with lower incomes in Pittsburgh, PA, and surveyed between March to May 2020 and May to December 2021. MAIN OUTCOME MEASURES: Food security was measured using the validated 6-item US Department of Agriculture Adult Food Security Survey Module. STATISTICAL ANALYSES PERFORMED: Findings are based on a descriptive analysis of food security and related indicators. Statistical testing was performed to assess differences between SNAP participation status and individual characteristics, food security, and financial hardship using Wald F test for continuous measures and Pearson χ2 test for categorical measures. A multivariable linear model was used to assess the association of SNAP participation and eligibility status with change in food insecurity. RESULTS: In cross-sectional analyses of 2021 data, no differences were observed between SNAP participants and eligible nonparticipants for food insecurity, food bank use, mean weekly food spending per person, and difficulty paying for basics. However, with respect to changes in food insecurity over the course of the pandemic, SNAP participants experienced a greater improvement in mean food security scores between 2020 and 2021 (-0.52 reduction in mean food insecurity score or a 16% improvement in food security; P ≤ 0.05) relative to SNAP-eligible nonparticipants. Perceived ineligibility (71.3%) and perceived lack of need (23%) were the most common reasons for not participating in SNAP. CONCLUSIONS: More than one-third of SNAP participants and eligible nonparticipants experienced food insecurity and financial hardship. However, there were differences in the changes in food insecurity between these groups.

Associations of Historical Redlining With BMI and Waist Circumference in Coronary Artery Risk Development in Young Adults.

Introduction: Historical maps of racialized evaluation of mortgage lending risk (i.e., redlined neighborhoods) have been linked to adverse health outcomes. Little research has examined whether living in historically redlined neighborhoods is associated with obesity, differentially by race or gender. Methods: This is a cross-sectional study to examine whether living in historically redlined neighborhoods is associated with BMI and waist circumference among Black and White adults in 1985-1986. Participants' addresses were linked to the 1930s Home Owners' Loan Corporation maps that evaluated mortgage lending risk across neighborhoods. The authors used multilevel linear regression models clustered on Census tract, adjusted for confounders to estimate main effects, and stratified, and interaction models by (1) race, (2) gender, and (3) race by gender with redlining differentially for Black versus White adults and men versus women. To better understand strata differences, they compared Census tract-level median household income across race and gender groups within Home Owners' Loan Corporation grade. Results: Black adults (n=2,103) were more likely than White adults (n=1,767) to live in historically rated hazardous areas and to have higher BMI and waist circumference. Redlining and race and redlining and gender interactions for BMI and waist circumference were statistically significant (p<0.10). However, in stratified analyses, the only statistically significant associations were among White participants. White participants living in historically rated hazardous areas had lower BMI (ß=-0.63 [95% CI= -1.11, -0.15]) and lower waist circumference (ß=-1.50 [95% CI= -2.62, -0.38]) than those living in declining areas. Within each Home Owners' Loan Corporation grade, residents in White participants' neighborhoods had higher incomes than those living in Black participants' neighborhoods (p<0.0001). The difference was largest within historically redlined areas. Covariate associations differed for men, women, Black, and White adults, explaining the difference between the interaction and the stratified models. Race by redlining interaction did not vary by gender. Conclusions: White adults may have benefitted from historical redlining, which may have reinforced neighborhood processes that generated racial inequality in BMI and waist circumference 50 years later.

Multi-dimensional Profiles of Risk and Their Association with Obesity-Severity in Low-Income Black Women.

Multi-level risk factors underlie disproportionate obesity rates among Black women. Latent class analysis of multi-level risk and protective factors among low-income Black women (n = 917) in 2011 (Pittsburgh, PA). Data were collected via in-person survey, interviewer-assisted online dietary recalls, and from 2011 crime records. Multinomial logistic regression estimated cross-sectional associations between latent classes and obesity severity derived from measured anthropometry. Latent class analysis identified four groups of women according to their motivations and intentions to be healthy, socioeconomic and health burden, and neighborhood risk: Class 1 = Very high burden (n = 283), Class 2 = Health motivated, low burden, low neighborhood risk (n = 231), Class 3 = High burden and high neighborhood risk (n = 106), and Class 4 = Low burden and low neighborhood risk (n = 297). Class 3 = High burden and high neighborhood risk women had the highest severe obesity risk. Multi-level strategies may support low-income Black women women's resilience to obesity who face neighborhood-level and socioeconomic stressors.

Microsimulation projections of obesity interventions on cardiometabolic health disparities in the United States.

OBJECTIVE: The aim of this study was to estimate long-term impacts of health education interventions on cardiometabolic health disparities. METHODS: The model simulates how health education implemented in the United States throughout 2019 to 2049 would lead to changes in adult BMI and consequent hypertension and type 2 diabetes. Health outcome changes by sex, racial/ethnic (non-Hispanic White, non-Hispanic Black, and Hispanic), and weight status (normal: 18.5 ≤ BMI < 25; overweight: 25 ≤ BMI < 30; and obesity: 30 ≤ BMI) subpopulations were compared under a scenario with and one without health education. RESULTS: By 2049, the intervention would reduce average BMI of women with obesity to 27.7 kg/m2 (CI: 27.4-27.9), which would be 2.9 kg/m2 lower than the expected average BMI without an intervention. Education campaigns would reduce type 2 diabetes prevalence, but it would remain highest among women with obesity at 27.7% (CI: 26.2%-29.2%). The intervention would reduce hypertension prevalence among White women by 4.7 percentage points to 38.0% (CI: 36.4%-39.7%). For Black women in the intervention, the 2049 hypertension prevalence would be 52.6% (CI: 50.7%-54.5%). Results for men and women were similar. CONCLUSIONS: Long-term health education campaigns can reduce obesity-related disease. All population groups benefit, but they would not substantially narrow cardiometabolic health disparities.