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The association between early-life greenness and child cognition is not well understood. Using prospective data from Project Viva (n = 857) from 1999–2010, we examined associations of early-life greenness exposure with mid-childhood cognition. We estimated residential greenness at birth, early childhood (median age 3.1 years), and mid-childhood (7.8 years) using 30-m resolution Landsat satellite imagery (normalized difference vegetation index). In early childhood and mid-childhood, we administered standardized assessments of verbal and nonverbal intelligence, visual-motor abilities, and visual memory. We used natural splines to examine associations of early life-course greenness with mid-childhood cognition, adjusting for age, sex, race, income, neighborhood socioeconomic status, maternal intelligence, and parental education. At lower levels of greenness (greenness

In light of recent findings on the small proportion of variance in body mass index (BMI) explained by shared environment, and growing interests in the role of genetic susceptibility, we assessed the relative contribution of socioeconomic status (SES) and genome-wide polygenic score for BMI to explaining variation in BMI. Our final analytic sample included 4,918 white and 1,546 black individuals from the US National Longitudinal Study of Adolescent to Adult Health Wave IV (2007–2008) who had complete measures on BMI, demographics, SES, genetic data, and health behaviors. We used ordinary least-squares regression to assess variation in log(BMI) as a function of the aforementioned predictors, independently and mutually adjusted. All analyses were stratified by race/ethnicity in the main analysis, and further by sex. The age-adjusted variation in log(BMI) was 0.055 among whites and 0.066 among blacks. The contribution of SES and polygenic score ranged from less than1% to 6% and from 2% to 8%, respectively, and majority of the variation (87%–96%) in log(BMI) remained unexplained. Differential distribution of socioeconomic resources, stressors, and buffers may interact to produce systematically larger variation in vulnerable populations. More understanding of the contribution of biological, genetic, and environmental factors, as well as stochastic elements, in diverse phenotypic variance is needed in population health sciences.

BACKGROUND AND OBJECTIVES: The Child Opportunity Index (ChOI) is a publicly available surveillance tool that incorporates traditional and novel attributes of neighborhood conditions that may promote or inhibit healthy child development. The extent to which ChOI relates to individual-level cardiometabolic risk remains unclear. METHODS: We geocoded residential addresses obtained from 743 participants in midchildhood (mean age 7.9 years) in Project Viva, a prebirth cohort from eastern Massachusetts, and linked each location with census tract-level ChOI data. We measured adiposity and cardiometabolic outcomes in midchildhood and early adolescence (mean age 13.1 years) and analyzed their associations with neighborhood-level ChOI in midchildhood using mixed-effects models, adjusting for individual and family sociodemographics. RESULTS: On the basis of nationwide distributions of ChOI, 11.2% (n = 83) of children resided in areas of very low overall opportunity (ChOI score CONCLUSIONS: Our findings suggest more favorable neighborhood opportunities in midchildhood predict better cardiometabolic health from midchildhood to early adolescence.

Background Recent studies suggest that greater exposure to natural vegetation, or “green space” is associated with lower diabetes risk, possibly through increasing physical activity. However, there is limited research on green space and insulin resistance in youth. We hypothesized greater green space at early-life sensitive time periods would be associated with lower insulin resistance in youth. Methods We used data from Project Viva (N = 460), a pre-birth cohort study that recruited pregnant women in eastern Massachusetts, 1999–2002, and followed offspring into adolescence. We defined residential green space exposure at infancy (median age − 1.1 years), early childhood (3.2 years), mid-childhood (7.7 years), and early adolescence (12.8 years), using 30 m resolution Landsat satellite imagery to estimate the Normalized Difference Vegetation Index [NDVI]. Our main outcome was early adolescence estimated insulin resistance (HOMA-IR). We used multiple imputation to account for missing data and multiple linear regression models adjusted for age, sex, race/ethnicity, parental education, household income, and neighborhood median household income. Results The highest green space tertile had the highest percentage of white participants (85%), college-educated mothers (87%) and fathers (85%), and households with income higher than US$70,000 (86%). Unadjusted models showed that participants living in the highest green space tertile at infancy had a 0.15 unit lower HOMA-IR (95% CI: −0.23, −0.06) in early adolescence, than those living in the lowest tertile. However, in adjusted models, we did not observe evidence of associations between green space from infancy to early adolescence and HOMA-IR in early adolescence, although some point estimates were in the hypothesized direction. For example, participants in the highest green space tertile in infancy had 0.03 units lower HOMA-IR (95%CI: −0.14, 0.08) than those living in the lowest tertile. Conclusions Exposure to green space at early life sensitive time periods was not associated with HOMA-IR in youth. Early-life longitudinal studies across diverse populations are needed to confirm or refute our results.

Green space can decelerate cognitive decline by supporting physical activity, psychological restoration, or reducing exposure to air pollution. However, existing studies on the association of green space with cognitive decline are limited.To examine whether residential green space was associated with cognitive function in middle-aged women.Starting in 1989, the Nurses' Health Study II enrolled 116 429 female nurses aged 25 to 42 years residing in the US. In 2014 to 2016, 40 082 women were invited to complete an online cognitive battery. This cohort study analyzed women who had data on both green space exposure and cognitive measures. Data analysis was conducted from June to October 2021.Residential exposure to green space was assessed using the Normalized Difference Vegetation Index, a satellite-derived indicator of the quantity of ground vegetation. Landsat satellite data at 270-m and 1230-m buffers around each participants' residential addresses in 2013 were used.In 2014 to 2016, cognitive function was measured using a self-administered online battery, the Cogstate Brief Battery, consisting of 4 tasks measuring psychomotor speed, attention, learning, and working memory; 3 composite scores, averaging together all tasks, psychomotor speed/attention, and learning/working memory, were created. In addition, the study evaluated potential mediators, including air pollution, depression, and physical activity.The analytical sample included 13 594 women, of whom 13 293 (98%) were White. Mean (SD) age was 61.2 (4.6) years. In models adjusted for age at assessment, race, childhood, adulthood, and neighborhood socioeconomic status, green space was associated with higher scores on the global Cogstate composite (mean difference per IQR in green space, 0.05; 95% CI, 0.02 to 0.07), and psychomotor speed/attention (mean difference in score, 0.05 standard units; 95% CI, 0.02 to 0.08). This difference in scores is similar to the difference observed in women 1 year apart in age in the data. By contrast, there was no association between green space and learning/working memory (mean difference, 0.0300; 95% CI, -0.0003 to 0.0500).These findings suggest that increasing residential green space may be associated with modest benefits in cognition in middle-aged women.

Background Early exposure to socioeconomic disadvantage is associated with obesity. Here we investigated how early, and conducted mediation analyses to identify behavioural factors in adulthood that could explain why. Methods Among 931 participants in the New England Family Study, we investigated the associations of family socioeconomic disadvantage measured before birth and at age 7 years with the following measures of adiposity in mid-adulthood (mean age = 44.4 years): body mass index (BMI), waist circumference and, among 400 participants, body composition from dual-energy X-ray absorption scans. Results In linear regressions adjusting for age, sex, race and childhood BMI Z-score, participants in the highest tertile of socioeconomic disadvantage at birth had 2.6 additional BMI units in adulthood [95% confidence interval (CI) = 1.26, 3.96], 5.62 cm waist circumference (95% CI = 2.69, 8.55), 0.73 kg of android fat mass (95% CI = 0.25, 1.21), and 7.65 higher Fat Mass Index (95% CI = 2.22, 13.09). Conditional on disadvantage at birth, socioeconomic disadvantage at age 7 years was not associated with adult adiposity. In mediation analyses, 10-20% of these associations were explained by educational attainment and 5-10% were explained by depressive symptoms. Conclusions Infancy may be a sensitive period for exposure to socioeconomic disadvantage, as exposure in the earliest years of life confers a larger risk for overall and central adiposity in mid-adulthood than exposure during childhood. Intervention on these two adult risk factors for adiposity would, if all model assumptions were satisfied, only remediate up to one-fifth of the excess adult adiposity among individuals born into socioeconomically disadvantaged households.

This study examines the impact of ambient temperature on emotional well-being in the U.S. population aged 18+. The U.S. is an interesting test case because of its resources, technology and variation in climate across different areas, which also allows us to examine whether adaptation to different climates could weaken or even eliminate the impact of heat on well-being. Using survey responses from 1.9 million Americans over the period from 2008 to 2013, we estimate the effect of temperature on well-being from exogenous day-to-day temperature variation within respondents’ area of residence and test whether this effect varies across areas with different climates. We find that increasing temperatures significantly reduce well-being. Compared to average daily temperatures in the 50–60 °F (10–16 °C) range, temperatures above 70 °F (21 °C) reduce positive emotions (e.g. joy, happiness), increase negative emotions (e.g. stress, anger), and increase fatigue (feeling tired, low energy). These effects are particularly strong among less educated and older Americans. However, there is no consistent evidence that heat effects on well-being differ across areas with mild and hot summers, suggesting limited variation in heat adaptation.

Green space has been associated with better health and well-being. However, most studies have been cross-sectional with limited long-term exposure data. Further, research is limited in what type of green space is beneficial for health. We conducted a longitudinal study to assess sensitive periods (birth, childhood or adulthood) of exposure to different types of green space in association with adult blood pressure and body mass index (BMI). Using longitudinal data from the New England Family Study (1960–2000) and multilevel regression analysis, we examined associations between time-varying markers of residential exposure to green space, and adult BMI, systolic (SBP) and diastolic blood pressure (DBP) (N = 517). We created three exposure metrics: distance, average area, and green space count in the neighborhood throughout the life-course. In adjusted models, living one mile farther away from a green space at birth was associated with a 5.6 mmHg higher adult SBP (95%CI: 0.7, 10.5), and 3.5 mmHg higher DBP (95%CI: 0.3, 6.8). One more green space in the neighborhood at birth was also associated with lower DBP (−0.2 mmHg, 95%CI: −0.4, −0.02) in adulthood. Finally, average area of green space was not associated with SBP, DBP nor BMI. Analysis by type of green space suggested that parks may be more relevant than playgrounds, cemeteries or golf courses. Our study suggests that the perinatal period may be a critical time-period where living closer to green spaces may lower hypertension risk in adulthood, but not obesity.

Public health reporting, randomized trials, and epidemiologic studies of obesity tend to consider it as a homogeneous entity. However, obesity may represent a heterogeneous condition according to demographic, clinical, and behavioral factors. We assessed the heterogeneity of individuals with obesity in the United States.We analyzed data from the 2011-2012 wave of the National Health and Nutrition Examination Survey, a nationally representative sample of adults in the United States with detailed physical examination and clinical data (n = 1380). We used cluster analysis to identify subgroups classified as obese according to demographic factors, clinical conditions, and behavioral characteristics.We found significant heterogeneity among participants with obesity according to six distinct clusters (P .001): affluent men with sleep disorders (16% of sample); older smokers with cardiovascular disease (16%); older women with high comorbidity (20%); healthy white women (13%); healthy non-white women (14%); and active men who drink higher amounts of alcohol (21%).Obesity in the United States is not a homogeneous condition. Current research and treatment may fail to account for complex and interrelated factors, with implications for prevention strategies and diverse risks of obesity.

Neighborhood context may influence health and health disparities. However, most studies have been constrained by cross-sectional designs that limit causal inference due to failing to establish temporal order of exposure and disease. We tested the impact of baseline neighborhood context (neighborhood socioeconomic status factor at the block-group level, and relative income of individuals compared to their neighbors) on allostatic load two years later. We leveraged data from the Boston Puerto Rican Health Study, a prospective cohort of aging Puerto Rican adults (aged 45–75 at baseline), with change in AL modeled between baseline and the 2nd wave of follow-up using two-level hierarchical linear regression models. Puerto Rican adults with higher income, relative to their neighbors, exhibited lower AL after two years, after adjusting for NSES, age, gender, individual-level SES, length of residence, and city. After additional control for baseline AL, this association was attenuated to marginal significance. We found no significant association of NSES with AL. Longitudinal designs are an important tool to understand how neighborhood contexts influence health and health disparities.

Background— The 2013 American College of Cardiology/American Heart Association (ACC/AHA) guidelines expanded eligibility criteria for statins. We examined race and socioeconomic differences associated with these changes. Methods and Results— This was an observational study of adults between 40 and 75 years of age using data from the National Health and Nutrition Examination Surveys between 2005 and 2012. Change in eligibility for statins was assessed based on the third adult treatment panel criteria and the 2013 ACC/AHA guidelines. Differences relating to self-reported race, income, education, and insurance status were assessed in models that were adjusted for age and each of the other factors. Statin eligibility increased among all race, education, and income groups. Becoming newly eligible for statins was more likely for black people (25.8% newly eligible; adjusted odds ratio, 3.8; P P P =0.001), and those with no health insurance (17.6%; adjusted odds ratio, 1.5; P Conclusions— The 2013 ACC/AHA guidelines increase statin eligibility most among adults with nonwhite race, socioeconomic disadvantage, and no health insurance. Without improving access to healthcare, the potential gains from expanding indications for cardioprotective medications will not be realized.

Objectives Neighborhood characteristics are increasingly recognized as important determinants of cardiovascular disease (CVD) risk. However, longitudinal studies on the health impacts of neighborhood characteristics are rare. We sought to investigate whether neighborhood socioeconomic status (NSES) during birth, childhood and adulthood is associated with CVD risk factors in adulthood. Methods Using longitudinal data from the New England Family Study (n = 671) with 46-years of follow-up, participants' home addresses were geocoded at birth (mean age = 1.6 months), childhood (mean age = 7.1 years), and adulthood (mean age = 44.2 years) across Massachusetts and Rhode Island in the US from 1961 to 2007. We used multilevel models to evaluate associations of NSES across the life-course with systolic blood pressure, diastolic blood pressure and body mass index (BMI) in adulthood, adjusting for age, sex, race/ethnicity, mother's race, individual SES, and parental SES. Results In fully adjusted models, one standard deviation higher NSES at birth was associated with a 1.9 mmHg lower SBP (95% CI: 3.8, −0.1) and 1.3 mmHg lower DBP (95%CI: 2.6,-0.03) in adulthood; while one standard deviation of higher NSES at adulthood was associated with 0.87 kg/m2 lower BMI (95%CI: 1.7, −0.1). Conclusions We found that living in a socioeconomically disadvantaged neighborhood early in life and in adulthood was associated with blood pressure and BMI, respectively, two established risk factors for CVD. Our findings support a longitudinal association between exposure to socioeconomically disadvantaged neighborhoods in early life and CVD risk factors in adulthood.

Self-rated health (SRH) is an important indicator of overall health, predicting morbidity and mortality. This paper investigates what individuals incorporate into their self-assessments of health and how acculturation plays a part in this assessment. The relationship of acculturation to SRH and whether it moderates the association between indicators of health and SRH is also examined.The paper is based on data from adults in the Boston Puerto Rican Health Study, living in the greater Boston area (n=1357) mean age 57.2 (SD = 7.6). We used multiple regression analysis and testing for moderation effects.The strongest predictors of poor SRH were the number of existing medical conditions, functional problems, allostatic load and depressive symptoms. Poor SRH was also associated with being female, fewer years of education, heavy alcohol use, smoking, poverty, and low emotional support. More acculturated Puerto Rican adults rated their health more positively, which corresponded to better indicators of physical and psychological health. Additionally, acculturation moderated the association between some indicators of morbidity (functional status and depressive symptoms) and SRH.Self-assessments of overall health integrate diverse indicators, including psychological symptoms, functional status and objective health indicators such as chronic conditions and allostatic load. However, adults' assessments of overall health differed by acculturation, which moderated the association between health indicators and SRH. The data suggest that when in poor health, those less acculturated may understate the severity of their health problems when rating their overall health, thus SRH might thus conceal disparities. Using SRH can have implications for assessing health disparities in this population.

BackgroundIncreases in life expectancy are hypothesised to be associated with shorter proportional time spent with morbidity (compression of morbidity). We assessed whether this has occurred among older adults in the USA during the 1990s and 2000s.MethodsWe used data from the Health and Retirement Study to estimate a morbidity score based on eight chronic conditions and compare it (1) prospectively between two age-matched cohorts in 1992 and 2004 over a 6-year follow-up, and (2) retrospectively in the three waves prior to death among respondents who die in (1998-2004) and (2004-2010).ResultsProspective assessment shows significantly higher prevalence in 6 of eight chronic conditions in the 2000s, with 37% higher diabetes prevalence. A retrospective evaluation shows significantly higher prevalence in 7 of eight chronic conditions in the three waves prior to death for (2004-2010) versus (1998-2004), with 41% higher prevalence of arthritis. Importantly, the farther away from time of death, the higher the average number of chronic conditions in (2004-2010).ConclusionsUsing the largest longitudinal ageing study in the USA, we found no clear evidence of compression of morbidity as measured by self-reported chronic disease. Older adults in the USA may be experiencing greater disease burden in recent times.

Background The Korean War GI Bill provided economic benefits for veterans, thereby potentially improving their health outcomes. However potential spillover effects on veteran wives have not been evaluated. Methods Data from wives of veterans eligible for the Korean War GI Bill (N = 128) and wives of non-veterans (N = 224) from the Health and Retirement Study were matched on race and coarsened birth year and childhood health using coarsened exact matching. Number of depressive symptoms in 2010 (average age = 78) were assessed using a modified, validated Center for Epidemiologic Studies-Depression Scale. Regression analyses were stratified into low (mother < 8 years schooling / missing data, N = 95) or high (mother ≥ 8 years schooling, N = 257) childhood socio-economic status (cSES) groups, and were adjusted for birth year and childhood health, as well as respondent’s educational attainment in a subset of analyses. Results Husband’s Korean War GI Bill eligibility did not predict depressive symptoms among veteran wives in pooled analysis or cSES stratified analyses; analyses in the low cSES subgroup were underpowered (N = 95, β = -0.50, 95% Confidence Interval: (-1.35, 0.35), p = 0.248, power = 0.28). Conclusions We found no evidence of a relationship between husband’s Korean War GI Bill eligibility and wives’ mental health in these data, however there may be a true effect that our analysis was underpowered to detect.