Improvements in Neighborhood Socioeconomic Conditions May Improve Resident Diet

Early adulthood socioeconomic trajectories contribute to inequalities in adult diet quality, independent of childhood and adulthood socioeconomic position

BACKGROUND

Diet is an important risk factor for cardiovascular disease and shows well-established socioeconomic patterning among adults. However, less clear is how socioeconomic inequalities in diet develop across the life course. This study assessed the associations of early adulthood socioeconomic trajectories (SETs) with adult diet quality, adjusting for childhood socioeconomic position (SEP) and testing for mediation by adulthood SEP.

METHODS

Participants from the 1970 British Cohort Study with socioeconomic data in early adulthood were included (n=12 434). Diet quality at age 46 years, evaluated using the Mediterranean diet pyramid, was regressed on six previously identified classes of early adulthood SETs between ages 16 and 24 years including a continued education class, four occupation-defined classes and an economically inactive class. Causal mediation analyses tested the mediation of the association via household income and neighbourhood deprivation at age 46 years separately. Models were adjusted for sex, childhood SEP, adolescent diet quality and adolescent health.

RESULTS

The continued education class showed the best diet quality at age 46 years while little difference in diet quality was found among the remaining SET classes. The association between the continued education class and adult diet quality was independent of parental SEP in childhood and was largely not mediated by household income or neighbourhood deprivation (0.7% and 3.7% of the total effect mediated, respectively) in mid-adulthood.

CONCLUSIONS

Early adulthood SETs independently contribute to adult diet quality with continuing education associated with better adherence to the Mediterranean diet. Early adulthood therefore represents a sensitive period for intervention to alleviate dietary inequalities in later life.

Socioeconomic Status, Diet, and Behavioral Factors and Cardiometabolic Diseases and Mortality

Importance

It remains unclear how socioeconomic status (SES) is related to the association between diet and health, as well as the role of behavioral factors, in explaining socioeconomic disparities in health outcomes.

Objective

To investigate the associations of neighborhood and individual SES factors, as well as behavioral factors, particularly dietary pattern, with health outcomes.

Design, Setting, and Participants

This prospective cohort study included US health professionals without chronic diseases at baseline who were enrolled in the Health Professionals Follow-Up Study (calendar years 1988-2018), the Nurses' Health Study (calendar years 1992-2018), and the Nurses' Health Study II (calendar years 2001-2019). Data analysis was performed in September 2023.

Exposures

Repeated questionnaires were used to assess neighborhood and individual SES factors and behavioral factors, including dietary pattern (assessed using the Alternative Healthy Eating Index 2010), alcohol intake, body mass index, cigarette smoking, physical activity, sedentary television-viewing time, and sleep duration.

Main Outcomes and Measures

The main outcomes were incident major cardiovascular disease (CVD), type 2 diabetes (T2D), and total mortality. The associations of SES and behavioral factors with outcomes were analyzed using multivariable Cox proportional hazards regression models with hazard ratios (HRs) per 10th- to 90th-percentile increments.

Results

The study analyzed 152 192 participants for major CVD (mean [SD] age, 52.0 [8.7] years; 125 959 female [82.8%]), 151 217 participants for T2D (mean [SD] age, 52.0 [8.6] years; 125 231 female [82.8%]), and 141 145 participants for mortality (mean [SD] age, 51.6 [8.5] years; 117 627 female [83.3%]). A healthy dietary pattern was inversely associated with risk for major CVD (HR, 0.87 [95% CI, 0.82-0.93]), T2D (HR, 0.79 [95% CI, 0.75-0.84]), and total mortality (HR, 0.84 [95% CI, 0.81-0.88]). Without adjusting for neighborhood and individual SES factors, the HRs were 0.85 (95% CI, 0.80-0.91) for risk for major CVD, 0.78 (95% CI, 0.74-0.82) for T2D, and 0.82 (95% CI, 0.79-0.85) for total mortality. Neighborhood SES was inversely associated with risk for major CVD (HR, 0.90 [95% CI, 0.85-0.95]), T2D (HR, 0.92 [95% CI, 0.88-0.97]), and total mortality (HR, 0.91 [95% CI, 0.88-0.94]). Behavioral factors accounted for a large proportion of the associations with risk for major CVD (46.3% [95% CI, 32.5%-60.6%]), T2D (77.4% [95% CI, 64.5%-86.6%]), and total mortality (42.8% [95% CI, 32.9%-53.3%]).

Conclusions and Relevance

In this prospective cohort study of health professionals, associations between diet and health outcomes remained similar without adjusting for SES factors, while health behaviors, including diet, accounted for a large proportion of the associations between neighborhood SES and health. These findings highlight the importance of health behaviors, particularly high-quality diets, in promoting individual health and possibly reducing health disparities associated with SES.

Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth-cohort geographic analyses

INTRODUCTION

Dementia risk may be elevated in socioeconomically disadvantaged neighborhoods. Reasons for this remain unclear, and this elevation has yet to be shown at a national population level.

METHODS

We tested whether dementia was more prevalent in disadvantaged neighborhoods across the New Zealand population (N = 1.41 million analytic sample) over a 20-year observation. We then tested whether premorbid dementia risk factors and MRI-measured brain-structure antecedents were more prevalent among midlife residents of disadvantaged neighborhoods in a population-representative NZ-birth-cohort (N = 938 analytic sample).

RESULTS

People residing in disadvantaged neighborhoods were at greater risk of dementia (HR per-quintile-disadvantage-increase = 1.09, 95% confidence interval [CI]:1.08-1.10) and, decades before clinical endpoints typically emerge, evidenced elevated dementia-risk scores (CAIDE, LIBRA, Lancet, ANU-ADRI, DunedinARB; β's 0.31-0.39) and displayed dementia-associated brain structural deficits and cognitive difficulties/decline.

DISCUSSION

Disadvantaged neighborhoods have more residents with dementia, and decades before dementia is diagnosed, residents have more dementia-risk factors and brain-structure antecedents. Whether or not neighborhoods causally influence risk, they may offer scalable opportunities for primary dementia prevention.

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.

"We adjusted for race": now what? A systematic review of utilization and reporting of race in American Journal of Epidemiology and Epidemiology, 2020-2021

Race is a social construct, commonly used in epidemiologic research to adjust for confounding. However, adjustment of race may mask racial disparities, thereby perpetuating structural racism. We conducted a systematic review of articles published in Epidemiology and American Journal of Epidemiology between 2020 and 2021 to (1) understand how race, ethnicity, and similar social constructs were operationalized, used, and reported; and (2) characterize good and poor practices of utilization and reporting of race data on the basis of the extent to which they reveal or mask systemic racism. Original research articles were considered for full review and data extraction if race data were used in the study analysis. We extracted how race was categorized, used-as a descriptor, confounder, or for effect measure modification (EMM)-and reported if the authors discussed racial disparities and systemic bias-related mechanisms responsible for perpetuating the disparities. Of the 561 articles, 299 had race data available and 192 (34.2%) used race data in analyses. Among the 160 US-based studies, 81 different racial categorizations were used. Race was most often used as a confounder (52%), followed by effect measure modifier (33%), and descriptive variable (12%). Fewer than 1 in 4 articles (22.9%) exhibited good practices (EMM along with discussing disparities and mechanisms), 63.5% of the articles exhibited poor practices (confounding only or not discussing mechanisms), and 13.5% were considered neither poor nor good practices. We discuss implications and provide 13 recommendations for operationalization, utilization, and reporting of race in epidemiologic and public health research.

Social and Medical Determinants of Diabetes: A Time-Constrained Multiple Mediator Analysis

Background A number of studies have shown an association between social determinants of health and the emergence of obesity and diabetes, but whether the relationship is causal is not clear. Objective To test whether social, environmental, and medical determinants directly or indirectly affect population-level diabetes prevalence after controlling for mediator-mediator interactions. Methods Data were obtained from the CDC and supplemented with nine other data sources for 3,109 US counties. The dependent variable was the prevalence of diabetes in 2017. Independent variables were a given county's 30 social, environmental, and medical characteristics in 2015 and 2016. A network multiple mediation analysis was conducted. First, we used Least Absolute Shrinkage and Selection Operator (LASSO) regression to relate the 2017 diabetes rate in each county to 30 predictors measured in 2016, identifying statistically significant and robust predictors as the mediators within the network model and as direct determinants of 2017 diabetes. Second, each of the direct causes of diabetes was taken as a new response variable and LASSO-regressed on the same 30 independent variables measured in 2015, identifying the indirect (mediated) causes of diabetes. Subsequently, these direct and indirect predictors were used to construct a network model. The completed network was then employed to estimate the direct and mediated impact of variables on diabetes. Results For 2017 diabetes rates, 63% of the variation was explained by five variables measured in 2016: the percentage of residents who were (1) obese, (2) African American, (3) physically inactive, (4) in poor health condition, and (5) had a history of diabetes. These five direct predictors, measured in 2016, mediated the effect of indirect variables measured in 2015, including the percentage of residents who were (1) Hispanic, (2) physically distressed, (3) smokers, (4) living with children in poverty, (5) experiencing limited access to healthy foods, and (6) had low income. Conclusion All of the direct predictors of diabetes prevalence, except the percentage of residents who were African American, were medical conditions potentially influenced by lifestyles. Counties characterized by higher levels of obesity, inactivity, and poor health conditions exhibited increased diabetes rates in the following year. The impact of social determinants of illness, such as low income, children in poverty, and limited access to healthy foods, had an indirect effect on the health of residents and, consequently, increased the prevalence of diabetes.

Association of Living in a Food Desert and Poor Periconceptional Diet Quality in a Cohort of Nulliparous Pregnant Individuals

BACKGROUND

A poor diet can result from adverse social determinants of health and increases the risk of adverse pregnancy outcomes.

OBJECTIVE

We aimed to assess, using data from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be prospective cohort, whether nulliparous pregnant individuals who lived in a food desert were more likely to experience poorer periconceptional diet quality compared with those who did not live in a food desert.

METHODS

The exposure was living in a food desert based on a spatial overview of food access indicators by income and supermarket access per the Food Access Research Atlas. The outcome was periconceptional diet quality per the Healthy Eating Index (HEI)-2010, analyzed by quartile (Q) from the highest or best (Q4, reference) to the lowest or worst dietary quality (Q1); and secondarily, nonadherence (yes or no) to 12 key aspects of dietary quality.

RESULTS

Among 7,956 assessed individuals, 24.9% lived in a food desert. The mean HEI-2010 score was 61.1 of 100 (SD: 12.5). Poorer periconceptional dietary quality was more common among those who lived in a food desert compared with those who did not live in a food desert (Q4: 19.8%, Q3: 23.6%, Q2: 26.5%, and Q1: 30.0% vs. Q4: 26.8%, Q3: 25.8%, Q2: 24.5%, and Q1: 22.9%; overall P < 0.001). Individuals living in a food desert were more likely to report a diet in lower quartiles of the HEI-2010 (i.e., poorer dietary quality) (aOR: 1.34 per quartile; 95% CI: 1.21, 1.49). They were more likely to be nonadherent to recommended standards for 5 adequacy components of the HEI-2010, including fruit, total vegetables, greens and beans, seafood and plant proteins, and fatty acids, and less likely to report excess intake of empty calories.

CONCLUSIONS

Nulliparous pregnant individuals living in a food desert were more likely to experience poorer periconceptional diet quality compared with those who did not live in a food desert.

Change in Geographic Accessibility to Dental Clinics Affects Access to Care

Access to dental clinics is a feature of the neighborhood service environment that may influence oral health care utilization. However, residential selection poses a challenge to causal inference. By studying the involuntary relocation of survivors of the 2011 Great East Japan Earthquake and Tsunami (GEJE), we examined the association between changes in geographic distance to dental clinics and dental visits. Longitudinal data from a cohort of older residents in Iwanuma City directly impacted by the GEJE were analyzed in this study. The baseline survey was conducted in 2010, 7 mo before the occurrence of GEJE, and a follow-up was conducted in 2016. Using Poisson regression models, we estimated the incidence rate ratios (IRR) and 95% confidence intervals (CIs) for the uptake of denture use (as a proxy for dental visits) according to changes in distance from the nearest dental clinic to their house. Age at baseline, housing damage by the disaster, deteriorating economic conditions, and worsened physical activity were used as confounders. Among the 1,098 participants who had not worn dentures before the GEJE, 495 were men (45.1%), with a mean ± SD age at baseline of 74.0 ± 6.9 y. During the 6-year follow-up, 372 (33.9%) participants initiated denture use. Compared to those who experienced a large increase in distance to dental clinics (>370.0-6,299.1 m), a large decrease in distance to dental clinics (>429.0-5,382.6 m) was associated with a marginally significantly higher initiation of denture use among disaster survivors (IRR = 1.28; 95% CI, 0.99-1.66). The experience of major housing damage was independently associated with higher initiation of denture use (IRR = 1.77; 95% CI, 1.47-2.14). Improved geographic access to dental clinics may increase dental visits of disaster survivors. Further studies in non-disaster-affected areas are needed to generalize these findings.

Neighborhood socioeconomic status and mortality in the nurses' health study (NHS) and the nurses' health study II (NHSII)

Few studies have prospectively examined long-term associations between neighborhood socioeconomic status (nSES) and mortality risk, independent of demographic and lifestyle risk factors.

Methods

We assessed associations between nSES and all-cause, nonaccidental mortality among women in the Nurses' Health Study (NHS) 1986-2014 (N = 101,701) and Nurses' Health Study II (NHSII) 1989-2015 (N = 101,230). Mortality was ascertained from the National Death Index (NHS: 19,228 deaths; NHSII: 1556 deaths). Time-varying nSES was determined for the Census tract of each residential address. We used principal component analysis (PCA) to identify nSES variable groups. Multivariable Cox proportional hazards models were conditioned on age and calendar period and included time-varying demographic, lifestyle, and individual SES factors.

Results

For NHS, hazard ratios (HRs) comparing the fifth to first nSES quintiles ranged from 0.89 (95% confidence interval [CI] = 0.84, 0.94) for percent of households receiving interest/dividends, to 1.11 (95% CI = 1.06, 1.17) for percent of households receiving public assistance income. In NHSII, HRs ranged from 0.72 (95% CI: 0.58, 0.88) for the percent of households receiving interest/dividends, to 1.27 (95% CI: 1.07, 1.49) for the proportion of households headed by a single female. PCA revealed three constructs: education/income, poverty/wealth, and racial composition. The racial composition construct was associated with mortality (HRNHS: 1.03; 95% CI = 1.01, 1.04).

Conclusion

In two cohorts with extensive follow-up, individual nSES variables and PCA component scores were associated with mortality. nSES is an important population-level predictor of mortality, even among a cohort of women with little individual-level variability in SES.

Neighbourhood socioeconomic improvement, residential mobility and premature death: a population-based cohort study and inverse probability of treatment weighting analysis

BACKGROUND

Causal inference using area-level socioeconomic measures is challenging due to risks of residual confounding and imprecise specification of the neighbourhood-level social exposure. By using multi-linked longitudinal data to address these common limitations, our study aimed to identify protective effects of neighbourhood socioeconomic improvement on premature mortality risk.

METHODS

We used data from the Canadian Community Health Survey, linked to health administrative data, including longitudinal residential history. Individuals aged 25-69, living in low-socioeconomic status (SES) areas at survey date (n = 8335), were followed up for neighbourhood socioeconomic improvement within 5 years. We captured premature mortality (death before age 75) until 2016. We estimated protective effects of neighbourhood socioeconomic improvement exposures using Cox proportional hazards models. Stabilized inverse probability of treatment weights (IPTW) were used to account for confounding by baseline health, social and behavioural characteristics. Separate analyses were carried out for three exposure specifications: any improvement, improvement by residential mobility (i.e. movers) or improvement in place (non-movers).

RESULTS

Overall, 36.9% of the study cohort experienced neighbourhood socioeconomic improvement either by residential mobility or improvement in place. There were noted differences in baseline health status, demographics and individual SES between exposure groups. IPTW survival models showed a modest protective effect on premature mortality risk of socioeconomic improvement overall (HR = 0.86; 95% CI 0.63, 1.18). Effects were stronger for improvement in place (HR = 0.67; 95% CI 0.48, 0.93) than for improvement by residential mobility (HR = 1.07, 95% 0.67, 1.51).

CONCLUSIONS

Our study provides robust evidence that specific neighbourhood socioeconomic improvement exposures are important for determining mortality risks.

Obesogenic environments and cardiovascular disease: a path analysis using US nationally representative data

INTRODUCTION

People living in obesogenic environments, with limited access to healthful food outlets and exercise facilities, generally have poor health. Previous research suggests that behavioral risk factors and indicators of physiological functioning may mediate this link; however, no studies to date have had the requisite data to investigate multi-level behavioral and physiological risk factors simultaneously. The present study conducted serial and parallel mediation analyses to examine behavioral and physiological pathways explaining the association between environmental obesogenicity and cardiovascular disease (CVD).

METHODS

This cross-sectional observational study used data from the 2012-2016 Health and Retirement Study, a representative survey of US older adults (n = 12,482, mean age 65.9). Environmental obesogenicity was operationalized as a combined score consisting of nine environmental measures of food and physical activity. CVD and health-compromising behaviors (diet, alcohol consumption, smoking, and exercise) were self-reported. Physiological dysregulation was assessed with measured blood pressure, heart rate, HbA1c, cholesterol levels, BMI, and C-reactive protein. The Hayes Process Macro was used to examine serial and parallel paths through health-compromising behaviors and physiological dysregulation in the environmental obesogenicity-CVD link.

RESULTS

People living in more obesogenic environments had greater odds of self-reported CVD (odds ratio = 1.074, 95% confidence interval (CI): 1.028, 1.122), engaged in more health-compromising behaviors (β = 0.026, 95% CI: 0.008, 0.044), and had greater physiological dysregulation (β = 0.035, 95% CI: 0.017, 0.054). Combined, health-compromising behaviors and physiological dysregulation accounted for 7% of the total effects of environmental obesogenicity on CVD.

CONCLUSION

Behavioral and physiological pathways partially explain the environmental obesogenicity-CVD association. Obesogenic environments may stymie the success of cardiovascular health-promotion programs by reducing access to resources supporting healthy lifestyles.

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.

Association of community socioeconomic deprivation with evidence of reduced kidney function at time of type 2 diabetes diagnosis

BACKGROUND

While there are known individual-level risk factors for kidney disease at time of type 2 diabetes diagnosis, little is known regarding the role of community context. We evaluated the association of community socioeconomic deprivation (CSD) and community type with estimated glomerular filtration rate (eGFR) when type 2 diabetes is diagnosed.

METHODS

This was a retrospective cohort study of 13,144 adults with newly diagnosed type 2 diabetes in Pennsylvania. The outcome was the closest eGFR measurement within one year prior to and two weeks after type 2 diabetes diagnosis, calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation. We used adjusted multinomial regression models to estimate associations of CSD (quartile 1, least deprivation) and community type (township, borough, city) with eGFR and used adjusted generalized estimating equation models to evaluate whether community features were associated with the absence of diabetes screening in the years prior to type 2 diabetes diagnosis.

RESULTS

Of the participants, 1279 (9.7%) had hyperfiltration and 1377 (10.5%) had reduced eGFR. Women were less likely to have hyperfiltration and more likely to have reduced eGFR. Black (versus White) race was positively associated with hyperfiltration when the eGFR calculation was corrected for race but inversely associated without the correction. Medical Assistance (ever versus never) was positively associated with reduced eGFR. Higher CSD and living in a city were each positively associated (odds ratio [95% confidence interval]) with reduced eGFR (CSD quartiles 3 and 4 versus quartile 1, 1.23 [1.04, 1.46], 1.32 [1.11, 1.58], respectively; city versus township, 1.38 [1.15, 1.65]). These features were also positively associated with the absence of a type 2 diabetes screening measure.

CONCLUSIONS

In a population-based sample, more than twenty percent had hyperfiltration or reduced eGFR at time of type 2 diabetes diagnosis. Individual- and community-level factors were associated with these outcomes.