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Mexico has a population of 129 million and is considered one of the most unequal countries in the world, suffering from widespread health disparities. There is a pressing need to strengthen epidemiologic capacity in Mexico, to help solve the complex health problems the country faces and to reduce health inequities. However, the representation of Mexican epidemiologists in the largest epidemiologic society in North America is low, despite the short distance to the United States. In this commentary, we discuss the barriers to higher representation of Mexican epidemiologists within the Society for Epidemiologic Research (SER), including language barriers, costs, and regional necessities. We also discuss opportunities to expand Mexican SER representation and collaboration. Overall, we hope that this is a call towards expanding SER global participation and starting a conversation on a common agenda for epidemiologic research.

Purpose of Review We assessed the relation between environmental greenness and risk of dementia and cognitive impairment, based on a systematic review and meta-analysis up to March 30, 2022, characterizing whenever possible the shape of the association using dose–response meta-analysis. Recent Findings Twelve studies were included in this review, either using normalized difference vegetation index (NDVI) or land use/cover (LU/LC) methodology to assess greenness. Comparing the highest versus lowest exposure categories of greenness assessed using the NDVI (6 studies) or LU/LC (6 studies), we found no association with dementia. Dose–response meta-analysis of the association between greenness measured by LU/LC and dementia, based on only 3 studies, indicated a U-shaped association, but estimates were imprecise. Summary Our systematic review and meta-analysis provided some evidence of a slight inverse association between greenness and dementia at intermediate exposure levels, but not at high levels. Potential methodological limitations, such as exposure misclassification and unmeasured confounding, may have affected the results.

PurposeDemolishing abandoned buildings has been found to reduce nearby firearm violence. However, these effects might vary within cities and across time scales. We aimed to identify potential moderators of the effects of demolitions on firearm violence using a novel approach that combined machine learning and aerial imagery.MethodsOutcomes were annual counts of fatal and non-fatal shootings in Rochester, New York, from 2000 to 2020. Treatment was demolitions conducted from 2009 to 2019. Units of analysis were 152×152 m grid squares. We used a difference-in-differences approach to test effects: (A) the year after each demolition and (B) as demolitions accumulated over time. As moderators, we used a built environment typology generated by extracting information from aerial imagery using convolutional neural networks, a deep learning approach, combined withk-means clustering. We stratified our main models by built environment cluster to test for moderation.ResultsOne demolition was associated with a 14% shootings reduction (incident rate ratio (IRR)=0.86, 95% CI 0.83 to 0.90, pConclusionsThe built environment might influence the magnitude and duration of the effects of demolitions on firearm violence. Policymakers may consider complementary programmes to help sustain these effects in high-density areas.

Green space or natural vegetation may reduce obesity risk by increasing opportunities for physical activity or reducing stress and exposure to other pollutants. Obesity prevalence in Mexico is ranked among the highest in the world. However, research on the association between green space and obesity in Mexico is lacking. We used data from the National Nutrition Survey in Mexico (2018–2019), a nationally representative sample of Mexican adults. The analytical sample included participants between 20–59 years of age (n = 12,631). We assessed exposure to green space using a 30 m resolution Landsat satellite Normalized Difference Vegetation Index (NDVI) from 2018. Linear regression models examined associations between NDVI and body mass index (BMI), adjusting for confounders. The mean age of the study sample was 38 (SD 0.19) years. Participants living in areas with the highest green space exposure had the lowest education level (53.51%) and socioeconomic status (28.38%) and were located in central (33.01%), south (30.37%), and rural areas (21.05%). Higher residential exposure to green space was associated with a mean decrease in BMI of −1.1 kg/m2 (95% CI: −1.59, −0.68). This is one of the first studies in Latin America to suggest a protective association between green space and obesity among Mexican adults.

IntroductionThe burden of Alzheimer’s disease (AD) and AD-related dementias (ADRD) is increasing nationally and globally, with disproportionate impacts on lower-income, lower education and systematically marginalised older adults. Presence of inequalities in neighbourhood factors (eg, social context, physical and built environments) may affect risk of cognitive decline and be key for intervening on AD/ADRD disparities at the population level. However, existing studies are limited by a dearth of longitudinal, detailed neighbourhood measures linked to rich, prospective cohort data. Our main objective is to identify patterns of neighbourhood change related to prevalence of—and disparities in—cognitive decline and dementia.Methods and analysesWe describe the process of collecting, processing and linking extensive neighbourhood data to the Multi-Ethnic Study of Atherosclerosis (MESA), creating a 25+ years dataset. Within the MESA parent study, the MESA Neighborhoods and Aging cohort study will characterise dynamic, longitudinal neighbourhood social and built environment variables relevant to cognition for residential addresses of MESA participants. This includes administering new surveys, expanding residential address histories, calculating new measures derived from spatial data and implementing novel deep learning algorithms on street-level imagery. Applying novel statistical techniques, we will examine associations of neighbourhood environmental characteristics with cognition and clinically relevant AD/ADRD outcomes. We will investigate determinants of disparities in outcomes by socioeconomic position and race/ethnicity and assess the contribution of neighbourhood environments to these disparities. This project will provide new evidence about pathways between neighbourhood environments and cognitive outcomes, with implications for policies to support healthy ageing.Ethics and disseminationThis project was approved by the University of Washington and Drexel University Institutional Review Boards (protocols #00009029 and #00014523, and #180900605). Data will be distributed through the MESA Coordinating Center. Findings will be disseminated in peer-reviewed scientific journals, briefs, presentations and on the participant website.

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

Across the United States, cities are creating sustainability and climate action plans (CAPs) that call to increase local vegetation. These greening initiatives have the potential to not only benefit the environment but also human health. In epidemiologic literature, greenness has a protective effect on mortality through various direct and indirect pathways. We aimed to assess how an increase in greenness could decrease mortality in the largest urban areas in the United States. We conducted a nationwide quantitative health impact assessment to estimate the predicted reduction in mortality associated with an increase in greenness across two decades (2000, 2010, and 2019). Using a recently published exposure-response function, Landsat 30 m 16-day satellite imagery from April to September, and publicly available county-level mortality data from the CDC, we calculated the age-adjusted reduction in all-cause mortality for those 65 years and older within 35 of the most populated metropolitan areas. We estimated that between 34,000 and 38,000 all-cause deaths could have been reduced in 2000, 2010, and 2019 with a local increase in green vegetation by 0.1 unit across the most populated metropolitan areas. We found that overall greenness increased across time with a 2.86% increase from 2000 to 2010 to 11.11% from 2010 to 2019. These results can be used to support CAPs by providing a quantitative assessment to the impact local greening initiatives can have on mortality. Urban planners and local governments can use these findings to calculate the co-benefits of local CAPs through a public health lens and support policy development.

The Lancet Countdown is an international collaboration, established to provide an independent, global monitoring system dedicated to tracking the emerging health profile of the changing climate. The 2020 report presents 43 indicators across five sections: climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. This report represents the findings and consensus of the 35 leading academic institutions and UN agencies that make up the Lancet Countdown, and draws on the expertise of climate scientists, geographers, and engineers; of energy, food, and transport experts; and of economists, social and political scientists, data scientists, public health professionals, and doctors.

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.

Understanding and responding to adverse human health impacts of global environmental change will be a major priority of 21st century public health professionals. The emerging field of planetary health aims to face this challenge by studying and promoting policies that protect the health of humans and of the Earth's natural systems that support them. Public health, drawing on its experience of guiding policies to improve population health, has contributed to planetary health's development. Yet, few public health practitioners are familiar with planetary health's systems-oriented approaches for understanding relationships between economic development, environmental degradation, and human health. In this narrative review, we present key planetary health concepts and show how systems thinking has guided its development. We discuss historical approaches to studying impacts of economic development on human health and the environment. We then review novel conceptual frameworks adopted by planetary health scientists to study and forecast impacts of policies that influence human health and Earth's natural systems at varying spatiotemporal scales. We conclude by presenting examples of how applying the “Doughnut” model (an economic framework where the needs of people are met without overshooting the world's ecological limits) could guide policies for promoting health co-benefits to humans and natural systems.

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.

The Lancet Countdown is an international collaboration that independently monitors the health consequences of a changing climate. Publishing updated, new, and improved indicators each year, the Lancet Countdown represents the consensus of leading researchers from 43 academic institutions and UN agencies. The 44 indicators of this report expose an unabated rise in the health impacts of climate change and the current health consequences of the delayed and inconsistent response of countries around the globe—providing a clear imperative for accelerated action that puts the health of people and planet above all else.\ud \ud The 2021 report coincides with the UN Framework Convention on Climate Change 26th Conference of the Parties (COP26), at which countries are facing pressure to realise the ambition of the Paris Agreement to keep the global average temperature rise to 1·5°C and to mobilise the financial resources required for all countries to have an effective climate response. These negotiations unfold in the context of the COVID-19 pandemic—a global health crisis that has claimed millions of lives, affected livelihoods and communities around the globe, and exposed deep fissures and inequities in the world's capacity to cope with, and respond to, health emergencies. Yet, in its response to both crises, the world is faced with an unprecedented opportunity to ensure a healthy future for all.

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.

The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) “Indicators” Tiger Team collaboration between NASA‐supported scientists and civil society stakeholders aimed to develop satellite‐derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge., Key Points The NASA Health and Air Quality Applied Science Team “Indicators” Tiger Team developed satellite‐based air quality and climate indicatorsParticipatory knowledge production can lead to more useful information for stakeholders but requires continuous engagement and flexibilityGround measurements are still needed, and sustained collaboration between the researchers and stakeholders over time remains a challenge

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.

Increasingly, studies suggest benefits of natural environments or greenness on children's health. However, little is known about cumulative exposure or windows of susceptibility to greenness exposure. Using inverse probability weighting of marginal structural models (IPW/MSM), we estimated effects of greenness exposure from birth through adolescence on executive function and behavior. We analyzed data of 908 children from Project Viva enrolled at birth in 1999–2002 and followed up until early adolescence. In mid-childhood (median 7.7 years) and early adolescence (13.1 years), executive function and behavior were assessed using the Behavior Rating Inventory of Executive Function and the Strengths and Difficulties Questionnaire (SDQ). Greenness was measured at birth, early childhood, mid-childhood, and early adolescence, using the Normalized Difference Vegetation Index. We used inverse probability weighting of marginal structural models to estimate effects of interventions that ensure maximum greenness exposure versus minimum through all intervals; and that ensure maximum greenness only in early childhood (vs. minimum through all intervals). Results of the effects of “maximum (vs. minimum) greenness at all timepoints” did not suggest associations with mid-childhood outcomes. Estimates of “maximum greenness only in early childhood (vs. minimum)” suggested a beneficial association with mid-childhood SDQ (−3.21, 99 %CI: −6.71,0.29 mother-rated; −4.02, 99 %CI: −7.87,-0.17 teacher-rated). No associations were observed with early adolescent outcomes. Our results for “persistent” maximum greenness exposure on behavior, were not conclusive with confidence intervals containing the null. The results for maximum greenness “only in early childhood” may shed light on sensitive periods of greenness exposure for behavior regulation.

Background: Increasing empirical evidence suggests that exposure to nature (natural vegetation, or “greenness”) influences health. Studies have shown that greenness is related to lower diabetes risk possibly through mediation of physical activity, harmful environmental exposures, or mental health. However, to our knowledge, no previous study has reported on associations between greenness and insulin resistance in children. We hypothesize that children are more sensitive to environmental exposures particularly during critical windows of susceptibility. Our research aims to evaluate the early life association between greenness and insulin resistance and assess vulnerable life-periods in which individuals are more susceptible to their surroundings. Methods: We use data from Project Viva, a longitudinal cohort study designed to study prenatal factors, pregnancy outcomes, and child health. From 1999 to 2002, we recruited pregnant women from a multispecialty group practice in Massachusetts. Of the 1,036 who attended the early teen research visit, we considered 460 participants who provided fasting blood and had complete data for all covariates and exposure at infancy (less than one year), early childhood (median age 3.3 years), mid-childhood (median age 7.7 years) and early teens (median age 13.2). We defined greenness exposure surrounding each participant’s address using 30m resolution Landsat satellite imagery [Normalized Difference Vegetation Index] at infancy (under one year of age), early childhood, mid-childhood, and early teens. Our main outcome measurement was the homeostatic model assessment to estimate insulin resistance (HOMA-IR) at the early teen visit. Results: In models adjusted for age, race, sex, mother’s education, father’s education, household income and median household income from the census tract at delivery, living in the highest quintile of greenness in the 90-m area at the early teen visit was associated with 0.65 lower HOMA-IR (95%CI: -1.52, -0.40) than those in the lowest quintile. The observed association between higher greenness exposure and lower HOMA-IR in early teens was consistent for the 270-m area, although slightly attenuated, and no longer significant for the 1230-m area (mean HOMA-IR was 3.06, SD=2.08). We found no associations of exposure to greenness in the 90-m, 270-m or 1230-m areas around participants’ home at infancy, early childhood, or mid-childhood with early teenage HOMA-IR. Conclusions: Higher levels of green vegetation, especially closer to the home, at the early teen visit were associated with lower insulin resistance at the same time period. Early exposure to green space during infancy, early childhood and mid-childhood was not associated with HOMA-IR as an early teenager. Early childhood longitudinal studies including geographic contextual factors across diverse populations are needed to confirm or refute these findings.

There is extensive empirical literature on the association between exposure to nature and health. In this narrative review, we discuss the strength of evidence from recent (i.e., the last decade) experimental and observational studies on nature exposure and health, highlighting research on children and youth where possible. We found evidence for associations between nature exposure and improved cognitive function, brain activity, blood pressure, mental health, physical activity, and sleep. Results from experimental studies provide evidence of protective effects of exposure to natural environments on mental health outcomes and cognitive function. Cross-sectional observational studies provide evidence of positive associations between nature exposure and increased levels of physical activity and decreased risk of cardiovascular disease, and longitudinal observational studies are beginning to assess long-term effects of nature exposure on depression, anxiety, cognitive function, and chronic disease. Limitations of current knowledge include inconsistent measures of exposure to nature, the impacts of the type and quality of green space, and health effects of duration and frequency of exposure. Future directions include incorporation of more rigorous study designs, investigation of the underlying mechanisms of the association between green space and health, advancement of exposure assessment, and evaluation of sensitive periods in the early life-course.

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.

Background: Blood pressure treatment strategies and targets are generally similar for most patients with hypertension, apart from individuals with certain specific comorbidities such as diabetes. We hypothesize that there is latent heterogeneity in the population of adults with hypertension and that this may be associated with differential risk of mortality and might suggest opportunities for more tailored treatment strategies. Our study of adults with hypertension in the US explores whether clusters of social and health-related characteristics exist, how trends in clusters have varied between 1999 and 2012, and how risk of mortality varies between clusters. Methods: In a nationally representative sample of adults (&gt 18 years) with hypertension (physician diagnosed, systolic &ge 140 mmHg or diastolic &ge 90 mmHg, or taking hypertension -related medication) from the National Health and Nutrition Examination Survey from 1999 to 2012 (Total N=16,855), we used a hierarchical cluster analysis approach to identify hypertension sub-groups according to chronic diseases, social factors, and health behaviors. Results: We found significant heterogeneity among hypertensive participants across time, according to 7 distinct clusters: Young Mexican-Americans with good health (55% of sample); Low-income non-White elderly with good health behaviors (7%); Elderly obese who smoke (18%); Men with poor health who drink and smoke (1%); Normal weight individuals with high prevalence of cancer (16%); Low-income and fit individuals with poor health (1%); and Obese and morbidly obese with high prevalence of chronic conditions (2%). The prevalence of each of these clusters remained relatively constant throughout the last decade, although there was an increase in the “Elderly obese who smoke” cluster from 14% to 18%. Mortality risk varied by subgroup. For example, the odds of dying for “Obese and morbidly obese with high prevalence of chronic conditions” were 1.73 times higher compared to “Young Mexican-Americans with good health” (p-value Conclusions: Sociodemographic and clinical clusters among hypertensive individuals in the U.S. remained stable over a decade, with higher risk of mortality associated with specific clusters. Recognizing these clinically-identifiable phenotypes may highlight opportunities to develop and evaluate targeted interventions that account for complex and inter-related clinical and social factors. Further, there is an opportunity through clinical trials to determine whether these clusters merit different blood pressure treatment strategies.

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.

Pakistan is one of three countries in which endemic transmission of poliovirus has never been stopped. Insecurity is often cited but poorly studied as a barrier to eradicating polio. We analyzed routinely collected health data from 32 districts of northwest Pakistan and constructed an index of insecurity based on journalistic reports of the monthly number of deaths and injuries resulting from conflict-related security incidents. The primary outcomes were the monthly incidence of paralytic polio cases within each district between 2007 and 2014 and the polio vaccination percentage from 666 district-level vaccination campaigns between 2007 and 2009, targeting ∼5.7 million children. Multilevel Poisson regression controlling for time and district fixed effects was used to model the association between insecurity, vaccinator access, vaccination rates, and polio incidence. The number of children inaccessible to vaccinators was 19.7% greater (95% CI: 19.2-20.2%), and vaccination rates were 5.3% lower (95% CI: 5.2-5.3%) in "high-insecurity" campaigns compared with "secure" campaigns. The unadjusted mean vaccination rate was 96.3% (SD = 8.6) in secure campaigns and 88.3% (SD = 19.2) in high-insecurity campaigns. Polio incidence was 73.0% greater (95% CI: 30-131%) during high-insecurity months (unadjusted mean = 0.13 cases per million people, SD = 0.71) compared with secure months (unadjusted mean = 1.23 cases per million people, SD = 4.28). Thus, insecurity was associated with reduced vaccinator access, reduced polio vaccination, and increased polio incidence in northwest Pakistan. These findings demonstrate that insecurity is an important obstacle to global polio eradication.

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.

The Korean War GI Bill provided socioeconomic benefits to veterans; however, its association with health is unclear; we hypothesize GI Bill eligibility is associated with fewer depressive symptoms and smaller disparities.Data from 246 Korean War GI Bill eligible veterans and 240 nonveterans from the Health and Retirement Study were matched on birth year, southern birth, race, height, and childhood health using coarsened exact matching. Number of depressive symptoms in 2010 (average age = 78 years) was assessed using a modified, validated Center for Epidemiologic Studies-Depression Scale, dichotomized to reflect elevated depressive symptoms. Regression analyses were stratified into low (at least one parent8 years schooling/missing data, n = 167) or high (both parents ≥ 8 years schooling, n = 319) childhood socioeconomic status (cSES) groups.Korean War GI Bill eligibility predicted fewer depressive symptoms among individuals from low cSES backgrounds [β = -0.64, 95% confidence interval (CI) = (-1.18, -0.09), P = .022]. Socioeconomic disparities were smaller among veterans than nonveterans for number of depressive symptoms [β = -0.76, 95% CI = (-1.33, -0.18), P = .010] and elevated depressive symptoms [β = -11.7, 95% CI = (-8.2, -22.6), P = .035].Korean War GI Bill eligibility predicted smaller socioeconomic disparities in depression markers.

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.

Childhood adversity, characterized by abuse, neglect, and household dysfunction, is a problem that exerts a significant impact on individuals, families, and society. Growing evidence suggests that adverse childhood experiences (ACEs) are associated with health decline in adulthood, including cardiovascular disease (CVD). In the current review, we first provide an overview of the association between ACEs and CVD risk, with updates on the latest epidemiological evidence. Second, we briefly review plausible pathways by which ACEs could influence CVD risk, including traditional risk factors and novel mechanisms. Finally, we highlight the potential implications of ACEs in clinical and public health. Information gleaned from this review should help physicians and researchers in better understanding potential long-term consequences of ACEs and considering adapting current strategies in treatment or intervention for patients with ACEs.

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.