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

Multi-Family Housing Environment and Physical Activity: A Systematic Review of the Literature

OBJECTIVE

To identify environmental features of multi-family housing (MFH) and their surrounding neighborhoods that influence residents' physical activity (PA).

DATA SOURCE

Articles published between January 2000 and September 2023 were identified from major social science, medical, health, behavioral science, and urban studies databases.

STUDY INCLUSION AND EXCLUSION CRITERIA

Studies were included if they (a) were empirical studies published in peer-reviewed journals and written in English; (b) focused on the MFH environment or the surrounding neighborhood; and (c) had at least one PA outcome.

DATA EXTRACTION

Data was extracted regarding the study objective, location, study sample, research design, results related to MFH and neighborhood environment, and limitations.

DATA SYNTHESIS

Descriptive summary of study characteristics and analysis to identify emerging themes at three spatial scales (i.e., building, site, and neighborhood).

RESULTS

Findings from 35 identified articles revealed factors influencing MFH residents' PA. On the building level, typology (apartment, townhouse) and tenure (public, market rent) showed contrasting correlations with PA in different age groups. On the site level, the presence of PA facilities and safe, walking-friendly environments promoted PA. On the neighborhood level, safety, quality of PA and pedestrian infrastructure, upkeep, air quality, aesthetics, neighborhood satisfaction, street connectivity, walkability, land use mix, density, and public transport promoted PA.

CONCLUSION

Study findings highlight the importance of the MFH environments in promoting PA, especially in older adults and young children. With increasing housing demand, understanding diverse MFH typologies and the impact of interventions on multi-spatial scales can help promote healthy and activity-friendly communities.

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.

Neighborhoods and Cardiovascular Health: A Scientific Statement From the American Heart Association

The neighborhoods where individuals reside shape environmental exposures, access to resources, and opportunities. The inequitable distribution of resources and opportunities across neighborhoods perpetuates and exacerbates cardiovascular health inequities. Thus, interventions that address the neighborhood environment could reduce the inequitable burden of cardiovascular disease in disenfranchised populations. The objective of this scientific statement is to provide a roadmap illustrating how current knowledge regarding the effects of neighborhoods on cardiovascular disease can be used to develop and implement effective interventions to improve cardiovascular health at the population, health system, community, and individual levels. PubMed/Medline, CINAHL, Cochrane Library reviews, and ClinicalTrials.gov were used to identify observational studies and interventions examining or targeting neighborhood conditions in relation to cardiovascular health. The scientific statement summarizes how neighborhoods have been incorporated into the actions of health care systems, interventions in community settings, and policies and interventions that involve modifying the neighborhood environment. This scientific statement presents promising findings that can be expanded and implemented more broadly and identifies methodological challenges in designing studies to evaluate important neighborhood-related policies and interventions. Last, this scientific statement offers recommendations for areas that merit further research to promote a deeper understanding of the contributions of neighborhoods to cardiovascular health and health inequities and to stimulate the development of more effective interventions.

Longitudinal associations between sleep and BMI in a low-income, predominantly Black American sample

OBJECTIVE

Black individuals and those experiencing socioeconomic disadvantage are at increased risk for sleep problems and obesity. This study adds to the limited extant literature examining longitudinal associations between objectively measured sleep and changes in body mass index (BMI) in Black Americans.

DESIGN

We focused on individuals with at least 1 observation of sleep and BMI at 1 of 3 study time points (2013, 2016, and 2018). We modeled longitudinal trends in BMI as a function of time, average of each sleep variable across assessments, and within-person deviations in each sleep variable over time.

SETTING

Data were collected via interviewer-administered at-home surveys and actigraphy in Pittsburgh, PA.

PARTICIPANTS

Our sample comprised 1115 low-income, primarily Black adults, including 862 women and 253 men.

MEASUREMENTS

Sleep measures included actigraphy-measured total sleep time, sleep efficiency, and wakefulness after sleep onset, as well as self-reported sleep quality. We also included objectively measured BMI.

RESULTS

In models adjusted for age, gender, and other sociodemographic covariates (eg, income, marital status), there were no significant longitudinal associations between total sleep time, sleep efficiency, wakefulness after sleep onset, or subjective sleep quality and changes in BMI.

CONCLUSIONS

This study provides further evidence that, among a sample of low-income Black adults, sleep problems are not longitudinally predictive of BMI. Although ample cross-sectional evidence demonstrates that sleep problems and obesity commonly co-occur, longitudinal evidence is mixed. Better understanding the overlap of sleep and obesity over time may contribute to prevention and intervention efforts.

Job loss and psychological distress during the COVID-19 pandemic: Longitudinal Analysis from residents in nine predominantly African American low-income neighborhoods

While psychological distress is a common sequelae of job loss, how that relationship continued during the COVID-19 pandemic is unclear, for example, given higher health risk to working due to disease exposure. This paper examines changes in psychological distress depending on job loss among a cohort of randomly selected residents living in nine predominantly African American low-income neighborhoods in Pittsburgh PA across four waves between 2013 and 2020. Between 2013 and 2016, we found an increase in psychological distress after job loss in line with the literature. In contrast, between 2018 and 2020 we found change in psychological distress did not differ by employment loss. However, residents who had financial concerns and lost their jobs had the largest increases in psychological distress, while residents who did not have serious financial concerns-potentially due to public assistance-but experienced job loss had no increase in distress, a better outcome even than those that retained their jobs. Using partial identification, we find job loss during the pandemic decreased psychological distress for those without serious financial concerns. This has important policy implications for how high-risk persons within low-income communities are identified and supported, as well as what type of public assistance may help.

The association between social integration and neighborhood dissatisfaction and unsafety: a cross-sectional survey study among social housing residents in Denmark

Background

Social integration and perceived neighborhood environment are recognized as important social determinants of health. However, little is known about the association between social integration and perceived neighborhood environment among underrepresented population groups, such as residents in disadvantaged neighborhoods, in public health research. The aim of this study is to: 1) Describe the levels of social integration and 2) Investigate the association between social integration and neighborhood dissatisfaction and unsafety among middle-aged and older social housing residents.

Methods

A multilingual face-to-face interviewer-administrated survey questionnaire was conducted among 206 residents aged 45 years and above (response rate: 34.1%) of various nationalities in disadvantaged socioeconomic positions in a social housing area in Denmark. The assessment of social integration was based on cohabitation status, frequency of face-to-face and non-face-to-face interaction with social relations and participation in local association activities. Neighborhood dissatisfaction measured the level of dissatisfaction with the neighborhood, and neighborhood unsafety assessed the level of unsafety being outdoors in the neighborhood. Descriptive statistics were conducted to illustrate respondent characteristics and the distribution of social integration among the study population. Logistic regression models were applied to analyze associations between social integration and neighborhood dissatisfaction and unsafety, adjusted for age, sex, country of origin, educational attainment and employment status.

Results

In total, 23.8% of the respondents reported low levels of social integration. A medium level of social integration was associated with higher odds of neighborhood dissatisfaction (OR: 2.36; 95% CI: 1.04–5.38) compared to the highest level of integration. A low frequency of face-to-face interaction was associated with higher odds of neighborhood dissatisfaction (OR: 2.65; 95% CI: 1.16–6.06) and neighborhood unsafety (OR: 2.41; 95% CI: 1.04–5.57) compared to the highest frequency of face-to-face interaction.

Conclusions

Almost one-fourth of respondents reported low levels of social integration. A medium level of social integration was associated with neighborhood dissatisfaction. A low frequency of face-to-face interaction was associated with neighborhood dissatisfaction and unsafety. The results suggest that targeted health promotion interventions designed to foster face-to-face interaction, hold potential to reduce neighborhood dissatisfaction and unsafety among residents in disadvantaged neighborhoods.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00945-9.

Examining the impact of employment status on sleep quality during the COVID-19 pandemic in two low-income neighborhoods in Pittsburgh, PA

Study Objectives

African Americans have faced disproportionate socioeconomic and health consequences associated with the COVID-19 pandemic. The current study examines employment and its association with sleep quality during the initial months of the pandemic in a low-income, predominantly African American adult sample.

Methods

In the early months of COVID-19 (March to May 2020), we administered a survey to an ongoing, longitudinal cohort of older adults to assess the impact of COVID-related changes in employment on self-reported sleep quality (N = 460; 93.9% African American). Participants had prior sleep quality assessed in 2018 and a subset also had sleep quality assessed in 2013 and 2016. Primary analyses focused on the prevalence of poor sleep quality and changes in sleep quality between 2018 and 2020, according to employment status. Financial strain and prior income were assessed as moderators of the association between employment status and sleep quality. We plotted trend lines showing sleep quality from 2013 to 2020 in a subset (n = 339) with all four waves of sleep data available.

Results

All participants experienced increases in poor sleep quality between 2018 and 2020, with no statistical differences between the employment groups. However, we found some evidence of moderation by financial strain and income. The trend analysis demonstrated increases in poor sleep quality primarily between 2018 and 2020.

Conclusions

Sleep quality worsened during the pandemic among low-income African American adults. Policies to support the financially vulnerable and marginalized populations could benefit sleep quality.

Sleep Disturbances, Changes in Sleep, and Cognitive Function in Low-Income African Americans

BACKGROUND

Sleep problems may contribute to the disproportionate burden of Alzheimer's disease and related dementias (ADRD) among African Americans (AAs).

OBJECTIVE

To examine the role of sleep problems in contributing to cognitive function and clinically adjudicated cognitive impairment in a predominantly AA sample.

METHODS

This study (n = 216, 78.8% female; mean age = 67.7 years) examined associations between 1) the level (i.e., measured in 2018) and 2) change over time (from 2013 to 2018; n = 168) in actigraphy-assessed sleep with domain-specific cognitive function and clinically adjudicated cognitive impairment (2018) in a community-dwelling, predominantly AA (96.9%) sample. A comprehensive cognitive battery assessed global cognitive function (3MS) and domain-specific cognitive function (attention, visuo-spatial ability, language, delayed recall, immediate recall, and executive function) in 2018. Sleep was measured in 2013 and 2018 via actigraphy.

RESULTS

Higher sleep efficiency and less wakefulness after sleep onset (WASO; measured in 2018) were associated with greater attention, executive function, and visuospatial ability. Increases in sleep efficiency between 2013 and 2018 were associated with better executive function, language, immediate recall, and visuospatial ability, whereas increases in WASO (2013-2018) were associated with poorer attention, executive function, and visuospatial ability. Level or change in sleep duration were not associated with domain-specific cognitive function, nor were any sleep measures associated with clinically adjudicated cognitive impairment.

CONCLUSION

In a predominantly AA sample of older adults, both the level and change (i.e., worsening) of sleep efficiency and WASO were associated with poorer cognitive function. Improving sleep health may support ADRD prevention and reduce health disparities.

Mixed Effects of Neighborhood Revitalization on Residents' Cardiometabolic Health

INTRODUCTION

Despite the growing recognition of the importance of neighborhood conditions for cardiometabolic health, causal relationships have been difficult to establish owing to a reliance on cross-sectional designs and selection bias. This is the first natural experiment to examine the impact of neighborhood revitalization on cardiometabolic outcomes in residents from 2 predominantly African American neighborhoods, one of which has experienced significant revitalization (intervention), whereas the other has not (comparison).

METHODS

The sample included 532 adults (95% African American, 80% female, mean age=58.9 years) from 2 sociodemographically similar, low-income neighborhoods in Pittsburgh, PA, with preintervention and postintervention measures (2016 and 2018) of BMI, diastolic and systolic blood pressure, HbA1c, and high-density lipoprotein cholesterol and covariates. Data were collected in 2016 and 2018 and analyzed in 2020.

RESULTS

Difference-in-difference analyses showed significant improvement in high-density lipoprotein cholesterol in intervention residents relative to that in the comparison neighborhood (β=3.88, 95% CI=0.47, 7.29). There was also a significant difference-in-difference estimate in diastolic blood pressure (β=3.00, 95% CI=0.57, 5.43), with residents of the intervention neighborhood showing a greater increase in diastolic blood pressure than those in the comparison neighborhood. No statistically significant differences were found for other outcomes.

CONCLUSIONS

Investing in disadvantaged neighborhoods has been suggested as a strategy to reduce health disparities. Using a natural experiment, findings suggest that improving neighborhood conditions may have a mixed impact on certain aspects of cardiometabolic health. Findings underscore the importance of examining the upstream causes of health disparities using rigorous designs and longer follow-up periods that provide more powerful tests of causality.

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.

Does investing in low-income urban neighborhoods improve sleep?

STUDY OBJECTIVES

Neighborhood disadvantage is associated with poor sleep, which may contribute to and exacerbate racial and socioeconomic health disparities. Most prior work has been cross-sectional and thus it has not been possible to estimate causal effects.

METHODS

We leveraged a natural experiment opportunity in two low-income, predominantly African American Pittsburgh, PA neighborhoods, following a randomly selected cohort of households (n = 676) between 2013 and 2016. One of the neighborhoods received substantial public and private investments (housing, commercial) over the study period, while the other socio-demographically similar neighborhood received far fewer investments. Primary analyses used a difference-in-difference analysis based on neighborhood, to examine changes in actigraphy-assessed sleep duration, efficiency, and wakefulness after sleep onset (WASO), and self-reported sleep quality. Secondary analyses examined whether residents' proximity to investments, regardless of neighborhood, was associated with changes in sleep outcomes.

RESULTS

Resident sleep worsened over time in both neighborhoods with no significant differences among residents between the two neighborhoods. Secondary analyses, including covariate adjustment and propensity score weighting to improve comparability, indicated that regardless of neighborhood, those who lived in closer proximity to investments (<0.1 mile) were significantly less likely to experience decreases in sleep duration, efficiency, and quality, or increases in WASO, compared to those who lived farther away.

CONCLUSIONS

While we did not observe sleep differences among residents between neighborhoods, living closer to a neighborhood investment was associated with better sleep outcomes. Findings have relevance for public health and policy efforts focused on investing in historically disinvested neighborhoods.

Do investments in low-income neighborhoods produce objective change in health-related neighborhood conditions?

This study examined the effect of neighborhood investments on neighborhood walkability, presence of incivilities, and crime in two low-income, primarily African American neighborhoods in Pittsburgh, USA. During the study period, one of the neighborhoods (the intervention neighborhood) received substantially more publicly-funded investments than a demographically matched comparison neighborhood. Comparisons between the neighborhoods showed a significant difference-in-difference for all three outcomes. The intervention neighborhood experienced significantly more change related to improved walkability and decreased incivilities. However, the control neighborhood experienced better crime-related outcomes. Analyses that focused on resident proximity to investments found similar results. This highlights the nuances of neighborhood investment, which is important to consider when thinking about public policy.

Prevalence and correlates of obstructive sleep apnea in urban-dwelling, low-income, predominantly African-American women

STUDY OBJECTIVES

The current study examined the prevalence and correlates of obstructive sleep apnea in a sample of low-income, predominantly African-American women using two waves of data.

METHODS

Participants were adults from two urban neighborhoods who enrolled in the PHRESH Zzz Study (N = 828; Pittsburgh Hill/Homewood Research on Neighborhoods, Sleep, and Health). A subsample who reported never receiving OSA diagnosis completed home sleep apnea testing in 2016 (n = 269, mean age 55.0 years, 79.6% female) and again in 2018 (n = 135). Correlates of OSA tested included demographic and anthropometric variables, health behavior/conditions, psychological distress and general health, smoking status, actigraphy-measured sleep, and neighborhood factors measured at baseline.

RESULTS

18.0% of all 2016 participants reported receiving physician diagnoses of OSA. Among those who completed in-home assessment, 19.3% had AHI ≥15 and 33.8% had AHI ≥5 plus one or more sleep symptoms. Estimates of the prevalence of OSA in all 2016 participants were 33.8%-45.7% based on physician diagnoses and AHI results, depending on the criteria used. Age, gender, BMI, blood pressure, habitual snoring, neighborhood walkability, actigraphy-measured sleep characteristics, and smoking were concurrently associated with OSA in 2016. Changes in AHI categories from 2016 to 2018 were documented.

CONCLUSIONS

Low-income African Americans, including women, are a high-risk group for OSA, but remain under-diagnosed and under-treated. The current findings show a high prevalence of OSA in African-American women and are among the first to demonstrate that both individual and neighborhood factors are implicated in OSA prevalence.

Associations between body mass index, physical activity and the built environment in disadvantaged, minority neighborhoods: Predictive validity of GigaPan® imagery

BACKGROUND

The built environment has been shown to influence health in studies of disadvantaged populations using different measurement methods. This study determined whether environmental exposures derived from GigaPan® images could serve as valid predictors of body mass index (BMI), walking and moderate to vigorous physical activity (MVPA) in a longitudinal study of low-income adults living in two primarily African American neighborhoods in Pittsburgh, Pennsylvania, USA. GigaPan® is a robotic system used to obtain high-resolution, panoramic images of environments.

METHODS

Microscale environmental features along 481 streets were audited in 2015-2016 using an audit form. Environmental exposures were estimated for 731 adult participants, using a sample of street segments within a 0.4 km (0.25 mile) network distance from each participant's residential address. Summary environmental exposures were constructed using factor analysis. We tested associations between participant-level environmental exposures and objectively measured BMI, self-reported walking and objectively measured MVPA in regression models controlling for baseline health and demographic variables.

RESULTS

Three factors representing participants' environmental exposures were constructed: pedestrian bicycle-amenities; hilly-vacant-boarded; physical activity-recreation/low housing density. Environments with infrastructure and amenities supportive of walking and bicycling were associated with lower BMI (Coef. = ‒0.47, p = 0.02). Frequent walking was less likely in environments with more physical activity and recreation venues/low housing density (OR = 0.81, 95% CI [0.67, 0.96]). MVPA was not associated with any of the environmental measures and the hilly-vacant-boarded factor was not associated with any of the outcomes.

CONCLUSIONS

Predictive validity was demonstrated for an environmental exposure factor that captured features supportive of walking and cycling in a model predicting BMI, using built environment audit data from GigaPan® imagery. A complementary analysis found lower odds of frequent walking in the neighborhood among participants with exposure to more physical activity and recreational features, but fewer types and lower density of housing.