Search

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.

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.

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.

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.

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.