Dana M. Alhasan

Background: Childhood residential change may affect later-life memory function and risk for Alzheimer's disease. However, few studies have examined this relationship, particularly in minoritized racial/ethnic groups. Objective: To assess the association between number of residences and moving due to financial difficulties in childhood with memory trajectories in later life. Methods: Data were from the U.S. Health and Retirement Study. Childhood residential change was measured by the self-reported number of residences before age 16 (0–1, 2, 3, 4 or more; n = 4704). Moving due to financial difficulties before age 16 was categorized as yes versus no (n = 4651). Memory function was measured using composite memory z-scores incorporating direct and proxy assessments from 1996–2016. We utilized mixed-effects linear regression models with subject-specific random slopes and intercepts adjusting for sociodemographic characteristics to estimate associations between residential change and memory overall and by race/ethnicity and parental education. Results: The mean age at baseline was 57.6 ± 6.1 years, 78.7% self-identified as non-Hispanic (NH) White, 15.7% as NH-Black, and 5.6% as Other/Unknown. Descriptively, NH-Black adults reported fewer residential changes and had lower baseline memory performance compared to NH-White participants. More frequent residential change in childhood was associated with a slower rate of memory decline but not baseline memory function. Moving due to financial difficulties during childhood was not associated with initial memory levels or rates of memory decline. We did not observe effect modification by race/ethnicity or parental education. Conclusions: Results suggest that childhood residential change may contribute to later life memory trajectories.

Background: Minoritized racial/ethnic groups and women in the United States (US) are disproportionately burdened by food insecurity, which likely contributes to disparities in cardiovascular health (CVH). Disparities are projected to widen due to the worsening climate crisis that is straining the agricultural system including food supplies. Nonetheless, studies have not investigated the relationship between food security status and ‘ideal’ CVH in a large, nationally-representative and racially/ethnically diverse US sample. Methods and results: We investigated household food security status in relation to ‘ideal’ CVH among US adults (N = 157,001) using 2014–2018/2020 National Health Interview Survey data. Food security status was defined as very low, low, marginal, or high. A summed score of 4 health behaviors and 3 clinical factors totaling 7 different measures was dichotomized (yes/no) to assess modified ‘ideal’ CVH (mICVH). Using Poisson regression with robust variance, we estimated prevalence ratios (PRs) and 95% CIs of mICVH by household food security status. We stratified models by sex/gender and race/ethnicity. Very low food security prevalence was higher among non-Hispanic (NH)-Black (8.0%) compared to Hispanic/Latinx (5.1%), NH-White (3.1%) and NH-Asian (1.7%) adults. The association between very low versus high food security and mICVH was stronger among women (PR = 0.23 [95% CI: 0.17–0.31]) than men (PR = 0.48 [95% CI: 0.35–0.66]). Compared to NH-White adults with high food security, racially/ethnically minoritized groups with very low to high food security were generally less likely (range: [PR_{very low} = 0.25[95% CI: 0.14–0.44] – [PR_high = 0.88 [95% CI: 0.79–0.97]) to meet mICVH criteria. Conclusions: Food insecurity was associated with lower mICVH prevalence and racially/ethnically minoritized groups were disproportionately burdened.

Food insecurity, poised to increase with burgeoning concerns related to climate change, may influence sleep, yet few studies examined the food security-sleep association among racially/ethnically diverse populations with multiple sleep dimensions. We determined overall and racial/ethnic-specific associations between food security and sleep health. Using National Health Interview Survey data, we categorised food security as very low, low, marginal and high. Sleep duration was categorised as very short, short, recommended and long. Sleep disturbances included trouble falling/staying asleep, insomnia symptoms, waking up feeling unrested and using sleep medication (all ≥3 d/times in the previous week). Adjusting for socio-demographic characteristics and other confounders, we used Poisson regression with robust variance to estimate prevalence ratios (PRs) and 95 % confidence intervals (95 % CIs) for sleep dimensions by food security. Among 177 435 participants, the mean age of 47⋅2 ± 0⋅1 years, 52⋅0 % were women, and 68⋅4 % were non-Hispanic (NH)-White. A higher percent of NH-Black (7⋅9 %) and Hispanic/Latinx (5⋅1 %) lived in very low food security households than NH-White (3⋅1 %) participants. Very low v. high food security was associated with a higher prevalence of very short (PR = 2⋅61 [95 % CI 2⋅44–2⋅80]) sleep duration as well as trouble falling asleep (PR = 2⋅21 [95 % CI 2⋅12–2⋅30]). Very low v. high food security was associated with a higher prevalence of very short sleep duration among Asian (PR = 3⋅64 [95 % CI 2⋅67–4⋅97]) and NH-White (PR = 2⋅73 [95 % CI 2⋅50–2⋅99]) participants compared with NH-Black (PR = 2⋅03 [95 % CI 1⋅80–2⋅31]) and Hispanic/Latinx (PR = 2⋅65 [95 % CI 2⋅30–3⋅07]) participants. Food insecurity was associated with poorer sleep in a racially/ethnically diverse US sample.

Urban planning for health equity should be guided by an intersectional approach. Intersectionality is an essential framework for understanding the multiple overlapping factors, such as social and economic inequalities, that produce health disparities. We offer four strategies that planning researchers and practitioners can use to develop and integrate an intersectional approach into planning for health equity: challenging implicit and explicit assumptions, building cross-sectoral coalitions united by a shared vision for social and environmental justice, applying transdisciplinary and co-designing approaches throughout the planning process, and using existing tools to evaluate the impact of programs and policies on advancing health equity.

Occupational characteristics may influence serious psychological distress (SPD) and contribute to health inequities; yet, few studies have examined multiple employment industries and occupational classes in a large, racially diverse sample of the United States. Using data from the National Health Interview Survey, we investigated employment industry and occupational class in relation to SPD in the overall population and by race/ethnicity, gender, age, household income, and health status. We created eight employment industry categories: professional/administrative/management, agricultural/manufacturing/construction, retail trade, finance/information/real estate, educational services, health care/social assistance, accommodation/food services, and public administration/arts/other services. We also created three occupational class categories: professional/management, support services, and laborers. SPD was measured using the Kessler Psychological Distress Scale and scores ≥13 indicated SPD. We adjusted for confounders and used Poisson regression to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs). Among the 245,038 participants, the mean age was 41.7 ± 0.1 years, 73% were Non-Hispanic (NH)-White, and 1.5% were categorized as having SPD. Compared to the professional/administrative/management industry, working in other industries (e.g., manufacturing/construction (PR = 0.82 [95% CI: 0.70–0.95]) and educational services (PR = 0.79 [95% CI: 0.66–0.94])) was associated with lower SPD. Working in support services and laborer versus professional/management positions were both associated with 19% higher prevalence of SPD (95% CI: 1.04–1.35; 95% CI: 1.04–1.38, respectively). Furthermore, working in a support services or laborer versus professional/management position was associated with higher SPD in most employment industries. Industry-specific workplace interventions to equitably improve mental health are warranted.

The “neighborhood environment and health” literature is burgeoning and has demonstrated that features of the neighborhood social environment, such as lower neighborhood social cohesion, are associated with higher psychological distress [ 1] including depression [ 2], and that psychological distress has been connected to compromised sleep health [ 3]. Further, the neighborhood social environment, psychological distress, and sleep health all vary by race/ethnicity [ 4–7]. For instance, we previously reported—using nationally representative data from the National Health Interview Survey—low versus high neighborhood social cohesion was associated with a higher prevalence of shorter sleep duration and more sleep disturbances, which varied by race/ethnicity [ 8]. In a separate study, poor sleep health was associated with higher psychological distress, as measured by the Kessler-6 scale, and the magnitude of the association was generally stronger among minoritized racial/ethnic groups [ 9]. These studies—like most—have relied on self-reported, cross-sectional data.