Do neighborhoods matter differently for movers and non-movers? Analysis of weight gain in the longitudinal dallas heart study

Longitudinal Exposure to Neighborhood Concentrated Poverty Contributes to Differences in Adiposity in Midlife Women

Background: Neighborhood poverty is associated with adiposity in women, though longitudinal designs, annually collected residential histories, objectively collected anthropometric measures, and geographically diverse samples of midlife women remain limited. Objective: To investigate whether longitudinal exposure to neighborhood concentrated poverty is associated with differences in body mass index (BMI) and waist circumference (WC) among 2,328 midlife women (age 42-52 years at baseline) from 6 U.S. cities enrolled in the Study of Women's Health Across the Nation (SWAN) from 1996 to 2007. Methods: Residential addresses and adiposity measures were collected at approximately annual intervals from the baseline visit through a 10-year follow-up. We used census poverty data and local spatial statistics to identify hot-spots of high concentrated poverty areas and cold-spots of low concentrated poverty located within each SWAN site region, and used linear mixed-effect models to estimate percentage differences (95% confidence interval [CI]) in average BMI and WC levels between neighborhood concentrated poverty categories. Results: After adjusting for individual-level sociodemographics, health-related factors, and residential mobility, compared to residents of moderate concentrated poverty communities, women living in site-specific hot-spots of high concentrated poverty had 1.5% higher (95% CI: 0.6, 2.3) BMI and 1.3% higher (95% CI: 0.5, 2.0) WC levels, whereas women living in cold-spots of low concentrated poverty had 0.7% lower (95% CI: -1.2, -0.1) BMI and 0.3% lower (95% CI: -0.8, 0.2) WC. Site-stratified results remained in largely similar directions to overall estimates, despite wide CIs and small sample sizes. Conclusions: Longitudinal exposure to neighborhood concentrated poverty is associated with slightly higher BMI and WC among women across midlife.

Change in neighborhood socioeconomic status and childhood weight status and body composition from birth to adolescence

BACKGROUND

We aim to assess the associations between the change in neighborhood socioeconomic score (SES) between birth and 6 years and childhood weight status and body composition from 6 to 13 years.

METHODS

Data for 3909 children from the Generation R Study, a prospective population-based cohort in the Netherlands were analyzed. The change in neighborhood SES between birth and 6 years was defined as static-high, static-middle, static-low, upward, and downward mobility. Child body mass index (BMI), overweight and obesity (OWOB), fat mass index (FMI) and lean mass index (LMI) were measured at age 6, 10, and 13 years. The associations were explored using generalized estimating equations. The effect modification by child sex was examined.

RESULTS

In total, 19.5% and 18.1% of children were allocated to the upward mobility and downward mobility neighborhood SES group. The associations between the change in neighborhood SES and child weight status and body composition were moderated by child sex (p < 0.05). Compared to girls in the static-high group, girls in the static-low group had relatively higher BMI-SDS (β, 95% confidence interval (CI): 0.24, 0.09-0.40) and higher risk of OWOB (RR, 95% CI: 1.98, 1.35-2.91), together with higher FMI-SDS (β, 95% CI: 0.27, 0.14-0.41) and LMI-SDS (β, 95% CI: 0.18, 0.03-0.33). The associations in boys were not significant.

CONCLUSIONS

An increased BMI and fat mass, and higher risk of OWOB from 6 to 13 years were evident in girls living in a low-SES neighborhood or moving downward from a high- to a low-SES neighborhood. Support for children and families from low-SES neighborhoods is warranted.

Residential relocation to assess impact of changes in the living environment on cardio-respiratory health: A narrative literature review with considerations for exposome research

Residential relocation studies have become increasingly valuable tools for evaluating the effects of changing living environments on human health, but little is known about their application to multiple aspects of the living environment and the most appropriate methodology. This narrative review explores the utility of residential relocation as a natural experiment for studying the impact of changing urban exposures on cardio-metabolic health in high-income settings. It provides a comprehensive overview of the use of residential relocation studies, evaluates their methodological approaches, and synthesizes findings related to health behaviors and cardio-metabolic outcomes. Our search identified 43 relevant studies published between January 1995 and February 2023, from eight countries, predominantly the USA, Canada, and Australia. The majority of eligible studies were published between 2012 and 2021 and examined changes in various domains of the living environment, such as walkability, the built and social environments, but rarely combinations of exposures. Included studies displayed heterogeneity in design and outcomes, 25 involving only movers and 18 considering both movers and non-movers. To mitigate the issue of residential self-selection bias, most studies employed a "change-in-change" design and adjusted for baseline covariates but only a fraction of them accounted for time-varying confounding. Relocation causes simultaneous changes in various features of the living environment, which presents an opportunity for exposome research to establish causal relationships, using large datasets with increased statistical power and a wide range of health outcomes, behaviors and biomarkers. Residential relocation is not a random process. Thus, studies focusing on living environment characteristics need to carefully select time-varying covariates and reference group. Overall, this review informs future research by guiding choices in study design, data requirements, and statistical methodologies. Ultimately, it contributes to the advancement of the urban exposome field and enhances our understanding of the complex relationship between urban environments and human health.

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 β =  - 0.14 (95% CI: - 0.29, 0.02). Nineteen percent of the total association between police bias and low relatability and lower dietary quality β =  - 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.

Longitudinal profiles of neighborhood socioeconomic vulnerability influence blood pressure changes across the female midlife period

PURPOSE

To examine whether longitudinal exposure to neighborhood socioeconomic vulnerability influences blood pressure changes throughout midlife in a racially, ethnically, and geographically-diverse cohort of women transitioning through menopause.

METHODS

We used longitudinal data on 2738 women (age 42-52 at baseline) living in six United States cities from The Study of Women's Health Across the Nation. Residential histories, systolic blood pressures (SBP), and diastolic blood pressures (DBP) were collected annually for ten years. We used longitudinal latent profile analysis to identify patterns of neighborhood socioeconomic vulnerability occurring from 1996 to 2007 in participant neighborhoods. We used linear mixed-effect models to determine if a woman's neighborhood profile throughout midlife was associated with blood pressure changes.

RESULTS

We identified four unique profiles of neighborhood socioeconomic vulnerability - differentiated by residential socioeconomic status, population density, and vacant housing conditions - which remained stable across time. Women residing in the most socioeconomically vulnerable neighborhoods experienced the steepest increase in annual SBP growth by 0.93 mmHg/year (95% CI: 0.65-1.21) across ten-year follow-up.

CONCLUSIONS

Neighborhood socioeconomic vulnerability was significantly associated with accelerated SBP increases throughout midlife among women.

Associations between neighborhood built environment, residential property values, and adult BMI change: The Seattle Obesity Study III

Objective

To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI).

Methods

The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1–3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education.

Results

Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity.

Conclusion

Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

•

Strong, inverse cross-sectional relationships between the built environment, residential property values (a proxy for individual socioeconomic status), and measured BMI were observed.

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Measures of the built environment and residential property values showed modest and inconsistent associations with 1- and 2-year BMI change.

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There was suggestive evidence that age may moderate the association between urban density and 1- and 2-year BMI change while education may moderate the association between residential property values and 2-year BMI change.

Association of Neighborhood Economic Trajectories With Changes in Weight Status Among Black and White Adults in the Southeastern US

IMPORTANCE

Neighborhood environment is an important factor associated with population disparities in obesity. However, few studies have examined whether and in what ways long-term trajectories of neighborhood conditions may be associated with weight outcomes. Moreover, there is a lack of research focusing on multidimensional and nuanced measures that make distinctions between multiple types of neighborhood change (eg, gentrification vs overall growth).

OBJECTIVE

To examine the association between long-term neighborhood economic trajectories and changes in weight status among Black and White adults residing in predominantly low-income communities in the southeastern US.

DESIGN, SETTING, AND PARTICIPANTS

This study was a longitudinal analysis of participants in the Southern Community Cohort Study. Five types of neighborhood economic trajectories (stability, growth, displacement, abandonment, and poverty concentration) were measured using data from the US Census and the American Community Survey from 2000 to 2016. Data were analyzed from December 12, 2021, to July 16, 2022. A total of 33 621 Black and White adults in the southeastern US were included in the analytic sample.

EXPOSURE

Neighborhood economic trajectory.

MAIN OUTCOMES AND MEASURES

Substantial weight gain and substantial weight loss (ie, gaining or losing ≥10% of baseline weight) between baseline (March 2002 to September 2009) and follow-up (November 2008 to January 2013) periods were assessed using self-reported information.

RESULTS

Among 33 621 participants, the mean (SD) age was 53.4 (8.8) years; 22 116 participants (65.8%) were women, 21 782 (64.8%) were Black, and 11 839 (35.2%) were White. Compared with residents in neighborhoods with stable trajectories, those in neighborhoods with growth trajectories that did not displace original residents were less likely to experience substantial weight gain (odds ratio [OR], 0.75; 95% CI, 0.58-0.97), whereas those in neighborhoods with poverty concentration trajectories were more likely to experience substantial weight gain (OR, 1.08; 95% CI, 1.00-1.17). These patterns appeared stronger among Black participants (eg, substantial weight gain in poverty concentration group: OR, 1.10 [95% CI, 1.00-1.22]; in growth group: OR, 0.76 [95% CI, 0.56-1.02]) compared with White participants (eg, substantial weight gain in poverty concentration group: OR, 1.03 [95% CI, 0.90-1.18]; in growth group: OR, 0.84 [95% CI, 0.52-1.36]). Differences in patterns were also observed among men (eg, substantial weight gain in poverty concentration group: OR, 1.02 [95% CI, 0.88-1.17]; in growth group: OR, 0.58 [95% CI, 0.35-0.96]) compared with women (eg, substantial weight gain in poverty concentration group: OR, 1.12 [95% CI, 1.02-1.23]; in growth group: OR, 0.83 [95% CI, 0.62-1.12]). However, none of the interaction terms between Black vs White participants and men vs women were statistically significant. Neighborhood trajectory was not associated with substantial weight loss (poverty concentration group: OR, 1.00 [95% CI, 0.93-1.09]; abandonment group: OR, 1.01 [95% CI, 0.84-1.15]; displacement group: OR, 1.04 [95% CI, 0.83-1.23]; growth group: OR, 0.88 [95% CI, 0.69-1.12]).

CONCLUSIONS AND RELEVANCE

In this cohort study, neighborhood economic trajectories were associated with weight gain. These findings highlight the importance of using more nuanced and multidimensional measures of neighborhood change in public health research.

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain

OBJECTIVE

To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults.

METHODS

Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values.

RESULTS

Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg.

CONCLUSIONS

Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.

Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health

Preliminary evidence suggests that neighborhood environments, such as socioeconomic disadvantage, pedestrian and physical activity infrastructure, and availability of neighborhood destinations (e.g., parks), may be associated with late-life cognitive functioning and risk of Alzheimer’s disease and related disorders (ADRD). The supposition is that these neighborhood characteristics are associated with factors such as mental health, environmental exposures, health behaviors, and social determinants of health that in turn promote or diminish cognitive reserve and resilience in later life. However, observed associations may be biased by self-selection or reverse causation, such as when individuals with better cognition move to denser neighborhoods because they prefer many destinations within walking distance of home, or when individuals with deteriorating health choose residences offering health services in neighborhoods in rural or suburban areas (e.g., assisted living). Research on neighborhood environments and ADRD has typically focused on late-life brain health outcomes, which makes it difficult to disentangle true associations from associations that result from reverse causality. In this paper, we review study designs and methods to help reduce bias due to reverse causality and self-selection, while drawing attention to the unique aspects of these approaches when conducting research on neighborhoods and brain aging.

Association of Long-Term Trajectories of Neighborhood Socioeconomic Status With Weight Change in Older Adults

IMPORTANCE

Studying long-term changes in neighborhood socioeconomic status (SES) may help to better understand the associations between neighborhood exposure and weight outcomes and provide evidence supporting neighborhood interventions. Little previous research has been done to examine associations between neighborhood SES and weight loss, a risk factor associated with poor health outcomes in the older population.

OBJECTIVE

To determine whether improvements in neighborhood SES are associated with reduced likelihoods of excessive weight gain and excessive weight loss and whether declines are associated with increased likelihoods of these weight outcomes.

DESIGN, STUDY, AND PARTICIPANTS

This cohort study was conducted using data from the National Institutes of Health-AARP (formerly known as the American Association of Retired Persons) Diet and Health study (1995-2006). The analysis included a cohort of 126 179 adults (aged 50-71 years) whose neighborhoods at baseline (1995-1996) were the same as at follow-up (2004-2006). All analyses were performed from December 2018 through December 2020.

EXPOSURES

Living in a neighborhood that experienced 1 of 8 neighborhood SES trajectories defined based on a national neighborhood SES index created using data from the US Census and American Community Survey. The 8 trajectory groups, in which high, or H, indicated rankings at or above the sample median of a specific year and low, or L, indicated rankings below the median, were HHH (ie, high in 1990 to high in 2000 to high in 2010), or stable high; HLL, or early decline; HHL, or late decline; HLH, or transient decline; LLL, or stable low; LHH, or early improvement; LLH, or late improvement; and LHL, or transient improvement.

MAIN OUTCOMES AND MEASURES

Excessive weight gain and loss were defined as gaining or losing 10% or more of baseline weight.

RESULTS

Among 126 179 adults, 76 225 (60.4%) were men and the mean (SD) age was 62.1 (5.3) years. Improvements in neighborhood SES were associated with lower likelihoods of excessive weight gain and weight loss over follow-up, while declines in neighborhood SES were associated with higher likelihoods of excessive weight gain and weight loss. Compared with the stable low group, the risk was significantly reduced for excessive weight gain in the early improvement group (odds ratio [OR], 0.87; 95% CI, 0.79-0.95) and for excessive weight loss in the late improvement group (OR, 0.89; 95% CI, 0.80-1.00). Compared with the stable high group, the risk of excessive weight gain was significantly increased for the early decline group (OR, 1.19; 95% CI, 1.08-1.31) and late decline group (OR, 1.13; 95% CI, 1.04-1.24) and for excessive weight loss in the early decline group (OR, 1.15; 95% CI, 1.02-1.28). The increases in likelihood were greater when the improvement or decline in neighborhood SES occurred early in the study period (ie, 1990-2000) and was substantiated throughout the follow-up (ie, the early decline and early improvement groups). Overall, we found a linear association between changes in neighborhood SES and weight outcomes, in which every 5 percentile decline in neighborhood SES was associated with a 1.2% to 2.4% increase in the risk of excessive weight gain or loss (excessive weight gain: OR, 1.01; 95% CI, 1.00-1.02 for women; OR, 1.02; 95% CI, 1.01-1.03 for men; excessive weight loss: OR, 1.02; 95% CI, 1.01-1.03 for women; OR, 1.02; 95% CI, 1.01-1.03 for men; P for- trend < .0001).

CONCLUSIONS AND RELEVANCE

These findings suggest that changing neighborhood environment was associated with changes in weight status in older adults.

Neighbourhood effects on obesity: scoping review of time-varying outcomes and exposures in longitudinal designs

CONTEXT AND OBJECTIVES

Neighbourhood effect research on obesity took off in the early 2000s and was composed of mostly cross-sectional observational studies interested in various characteristics of the built environment and the socioeconomic environment. To limit biases related to self-selection and life course exposures, many researchers apply longitudinal designs in their studies. Until now, no review has specifically and exclusively examined longitudinal studies and the specific designs of these studies. In this review, we intend to answer the following research question: how are the temporal measurements of contextual exposure and obesity outcomes integrated into longitudinal studies that explore how neighbourhood-level built and socioeconomic environments impact adult obesity?

DESIGN

A systematic search strategy was designed to address the research question. The search was performed in Embase, Web of Science and PubMed, targeting scientific papers published before 1 January 2018. The eligible studies reported results on adults, included exposure that was limited to neighbourhood characteristics at the submunicipal level, included an outcome limited to obesity proxies, and reported a design with at least two exposure measurements or two outcome measurements.

RESULTS

This scoping review identified 66 studies that fit the eligibility criteria. A wide variety of neighbourhood characteristics were also measured, making it difficult to draw general conclusions about associations between neighbourhood exposure and obesity. We applied a typology that classified studies by whether exposure and outcome were measured as varying or fixed. Using this typology, we found that 32 studies reported both neighbourhood exposure and obesity outcomes that were varying in time; 28 reported varying outcomes but fixed exposures; and 6 had fixed outcomes and varying exposures.

CONCLUSION

Our typology illustrates the variety of longitudinal designs that were used in the selected studies. In the light of our results, we make recommendations on how to better report longitudinal designs and facilitate comparisons between studies.

Residential mobility in early childhood and obesity at kindergarten age among children from the United States

BACKGROUND

Children who frequently move have poorer behavioural, emotional, and overall health. For similar reasons, the experience of changing home may contextualize children's risk for obesity. Few studies have assessed the relationship between residential mobility and obesity; even fewer explore this relationship with assessment of obesity before school age.

METHODS

We analysed data from the Early Childhood Longitudinal Study-Birth Cohort. Obesity at kindergarten age was determined from measured height and weight. Early childhood residential mobility was categorized as not moving or having moved once, twice, or three or more times. Analyses are weighted to be representative of children from the United States and variance estimates account for the complex survey design.

RESULTS

The prevalence of obesity at kindergarten age was 17.5%, and most children (71%) moved in early childhood. Compared with children who did not move, the adjusted odd ratios for obesity at kindergarten age were 0.72 (95% CI, 0.57-0.92), 0.70 (95% CI, 0.55-0.89), and 0.64 (95% CI, 0.50-0.84) for children who experienced 1, 2, or 3+ moves.

CONCLUSIONS

Our study suggests that obesity and mobility in early life are associated, but not in the way we might expect. Residential mobility may fit into a broader picture of instability and, on its own, may not elevate a child's risk for obesity.

Global physical activity levels - Need for intervention

Substantial evidence shows that physical inactivity (PI) and sedentary behavior (SB) increases the risk of many chronic diseases and shortens life expectancy. We describe evidence that certain domains of physical activity (PA) in the United States (US) population have declined substantially over 5 decades. The prevalence of PI is very high worldwide, which has contributed to 6%-10% of the burden of many chronic diseases and premature mortality. Reduction or elimination of PI would likely produce substantial increases in life expectancy of the world's population. Great efforts are needed to reduce PI and SB and increase levels of PA in the US and worldwide.

Foreclosures and weight gain: Differential associations by longer neighborhood exposure

While home foreclosure can lead to mental and physical health declines in persons experiencing the foreclosure, whether neighborhood foreclosures can affect the health of other residents is debatable. Using a racially/ethnically diverse sample of Chicago metropolitan area residents linked to foreclosure data from 2008 to 2014, we assessed whether exposure to neighborhood foreclosure fillings was associated with changes in objectively measured body mass index (BMI) over time. Using a retrospective longitudinal design, we employed fixed-effects regression models that controlled for individual- and neighborhood-level covariates to test the association of neighborhood foreclosures and BMI in >60,000 individuals and for individuals who did not move during the follow-up period. We also adjusted for the non-linear association of age and BMI and comorbidities and employed a series of sensitivity analysis to test for robustness. In fully adjusted models, a standard-deviation increase in neighborhood foreclosure filings within 500 m was associated with increases in BMI for individuals who did not move (nonmovers) (mean = 0.03 BMI units, 95% confidence interval: 0.01, 0.06). Neighborhood foreclosure rates were not associated with changes in BMI for the full sample. Given the potential deleterious effects of neighborhood foreclosure on individuals with longer exposure to the local vicinity, clarifying the potential health effects of neighborhood foreclosures would help policymakers when planning actions to prevent home losses, predatory home loans, and that aim to more efficiently return foreclosure properties to productive uses.

Ten-Year Change in Neighborhood Socioeconomic Deprivation and Rates of Total, Cardiovascular Disease, and Cancer Mortality in Older US Adults

Low neighborhood socioeconomic status has been linked to adverse health outcomes. However, it is unclear whether changing the neighborhood may influence health. We examined 10-year change in neighborhood socioeconomic deprivation in relation to mortality rate among 288,555 participants aged 51-70 years who enrolled in the National Institutes of Health-AARP Diet and Health Study in 1995-1996 (baseline) and did not move during the study. Changes in neighborhood socioeconomic deprivation between 1990 and 2000 were measured by US Census data at the census tract level. All-cause, cardiovascular disease, and cancer deaths were ascertained through annual linkage to the Social Security Administration Death Master File between 2000 and 2011. Overall, our results suggested that improvement in neighborhood socioeconomic status was associated with a lower mortality rate, while deterioration was associated with a higher mortality rate. More specially, a 30-percentile-point reduction in neighborhood deprivation among more deprived neighborhoods was associated with 11% and 19% reductions in the total mortality rate among men and women, respectively. On the other hand, a 30-point increase in neighborhood deprivation in less deprived neighborhoods was associated with an 11% increase in the mortality rate among men. Our findings support a longitudinal association between changing neighborhood conditions and mortality.

Association between neighborhood-level socioeconomic deprivation and incident hypertension: A longitudinal analysis of data from the Dallas heart study

BACKGROUND

Cardiovascular disease is a leading economic and medical burden in the United States (US). As an important risk factor for cardiovascular disease, hypertension represents a critical point of intervention. Less is known about longitudinal effects of neighborhood deprivation on blood pressure outcomes, especially in light of new hypertension guidelines.

METHODS

Longitudinal data from the Dallas Heart Study facilitated multilevel regression analysis of the relationship between neighborhood deprivation, blood pressure change, and incident hypertension over a 9-year period. Factor analysis explored neighborhood perception, which was controlled for in all analyses. Neighborhood deprivation was derived from US Census data and divided into tertiles for analysis. Hypertension status was compared using pre-2017 and 2017 hypertension guidelines.

RESULTS

After adjusting for covariates, including moving status and residential self-selection, we observed significant associations between residing in the more deprived neighborhoods and 1) increasing blood pressure over time and 2) incident hypertension. In the fully adjusted model of continuous blood pressure change, significant relationships were seen for both medium (SBP: β = 4.81, SE = 1.39, P = .0005; DBP: β = 2.61, SE = 0.71, P = .0003) and high deprivation (SBP: β = 7.64, SE = 1.55, P < .0001; DBP: β = 4.64, SE = 0.78, P < .0001). In the fully adjusted model of incident hypertension, participants in areas of high deprivation had 1.69 higher odds of developing HTN (OR 1.69; 95% CI 1.02, 2.82), as defined by 2017 hypertension guidelines. Results varied based on definition of hypertension used (pre-2017 vs. 2017 guidelines).

CONCLUSION

These findings highlight the potential impact of adverse neighborhood conditions on cardiometabolic outcomes, such as hypertension.