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BackgroundIn Latin America, where climate change and rapid urbanization converge, non-optimal ambient temperatures contribute to excess mortality. However, little is known about area-level characteristics that confer vulnerability to temperature-related mortality.ObjectivesExplore city-level socioeconomic and demographic characteristics associated with temperature-related mortality in Latin American cities.MethodsThe dependent variables quantify city-specific associations between temperature and mortality: heat- and cold-related excess death fractions (EDF, or percentages of total deaths attributed to cold/hot temperatures), and the relative mortality risk (RR) associated with 1 °C difference in temperature in 325 cities during 2002-2015. Random effects meta-regressions were used to investigate whether EDFs and RRs associated with heat and cold varied by city-level characteristics, including population size, population density, built-up area, age-standardized mortality rate, poverty, living conditions, educational attainment, income inequality, and residential segregation by education level.ResultsWe find limited effect modification of cold-related mortality by city-level demographic and socioeconomic characteristics and several unexpected associations for heat-related mortality. For example, cities in the highest compared to the lowest tertile of income inequality have all-age cold-related excess mortality that is, on average, 3.45 percentage points higher (95% CI: 0.33, 6.56). Higher poverty and higher segregation were also associated with higher cold EDF among those 65 and older. Large, densely populated cities, and cities with high levels of poverty and income inequality experience smaller heat EDFs compared to smaller and less densely populated cities, and cities with little poverty and income inequality.DiscussionEvidence of effect modification of cold-related mortality in Latin American cities was limited, and unexpected patterns of modification of heat-related mortality were observed. Socioeconomic deprivation may impact cold-related mortality, particularly among the elderly. The findings of higher levels of poverty and income inequality associated with lower heat-related mortality deserve further investigation given the increasing importance of urban adaptation to climate change.

BackgroundExtreme temperatures may lead to adverse pregnancy and birth outcomes, including low birthweight. Studies on the impact of temperature on birthweight have been inconclusive due to methodological challenges related to operationalizing temperature exposure, the definitions of exposure windows, accounting for gestational age, and a limited geographic scope.MethodsWe combined data on individual-level term live births (N≈15 million births) from urban areas in Brazil, Chile, and Mexico from 2010 to 2015 from the SALURBAL study (Urban Health in Latin America) with high-resolution daily air temperature data and computed average ambient temperature for every month of gestation for each newborn. Associations between full-term birthweight and average temperature during gestation were analyzed using multi-level distributed lag non-linear models that adjusted for newborn's sex, season of conception, and calendar year of child's birth; controlled for maternal age, education, partnership status, presence of previous births, and climate zone; and included a random term for the sub-city of mother's residence.FindingsHigher temperatures during the entire gestation are associated with lower birthweight, particularly in Mexico and Brazil. The cumulative effect of temperature on birthweight is mostly driven by exposure to higher temperatures during months 7-9 of gestation. Higher maternal education can attenuate the temperature-birthweight associations.InterpretationOur work shows that climate-health impacts are likely to be context- and place-specific and warrants research on temperature and birthweight in diverse climates to adequately anticipate global climate change. Given the high societal cost of suboptimal birthweight, public health efforts should be aimed at diminishing the detrimental effect of higher temperatures on birthweight.FundingThe Wellcome Trust.

Background/objectivesLittle is known about the separate or combined effects of state and national nutrition policies regulating food and beverages in schools on child overweight/obesity (OV/OB) and related racial/ethnic disparities. We investigated the influence of school nutrition policies enacted in California, independently and in combination with the United States' national policy "Healthy Hunger Free Kids Act" (HHFKA) on childhood OV/OB and racial/ethnic disparities.Subjects/methodsAn interrupted time series design was used with data from 12,363,089 child-level records on 5th- and 7th-graders in California public schools to estimate sex- and racial/ethnic-specific time trends in OV/OB prevalence during three periods: before the California nutrition policies (2002-2004); when only California policies were in effect (2005-2012); and when they were in effect simultaneously with HHFKA (2013-2016).ResultsBefore the state's policies, OV/OB prevalence increased annually among children in most subgroups. Improvements in OV/OB trends were observed for almost all groups after the California policies were in effect, with further improvements after the addition of HFFKA. The total change in annual log-odds of OV/OB, comparing the periods with both state and federal policies versus no policies, ranged from -0.08 to -0.01 and varied by grade, sex, and race/ethnicity. Within each sex and grade, the greatest changes were among African-American (-0.08 to -0.02, all p

Latino immigrants have lower prevalence of depression, obesity and cardiovascular disease than US-born Latinos when they are recently arrived in the US, but this health advantage erodes with increasing duration of US residence. Cumulative exposure to psychosocial stress and its physiological sequelae may mediate the relationship between nativity and duration of US residence and poor health. We used data from Latino cohort study participants ages 45-84 to examine cross-sectional (n=558) and longitudinal (n=248) associations between nativity and duration of US residence and features of the diurnal cortisol curve including: wake-up cortisol, cortisol awakening response (CAR, wake-up to 30min post-awakening), early decline (30min to 2h post-awakening) and late decline (2h post-awakening to bed time), wake-to-bed slope, and area under the curve (AUC). In cross-sectional analyses, US-born Latinos had higher wake-up cortisol than immigrants with fewer than 30 years of US residence. In the full sample, over 5 years the CAR and early decline became flatter and AUC became larger. Over 5 years, US-born Latinos had greater increases in wake-up cortisol and less pronounced flattening of the early diurnal cortisol decline than immigrants with fewer than 30 years of US residence. Immigrants with 30 or more years of US residence also had less pronounced flattening of the early decline relative to more recent immigrants, and also had a less pronounced increase in AUC. In sum, we saw limited cross-sectional evidence that US-born Latinos have more dysregulated cortisol than recently-arrived Latino immigrants, but over time US-born Latinos had slower progression of cortisol dysregulation.

We investigated the relationships between neighborhood socio-demographic characteristics (socioeconomic status [SES], percentage of Black residents, and percentage of Hispanic residents) and survey-based measures of the social environment (social cohesion, safety) and the physical environment (healthy food environment, walking environment) in six sites from 2000 through 2011. Neighborhood environments were patterned by area SES and racial/ethnic composition, such that higher SES and lower percentage minority neighborhoods had better physical and social environments. Increasing disparities over time were observed for some neighborhood environments. Further research should explore the role of neighborhood environments in maintaining or increasing social disparities in health.

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, prespecified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children's dietary choices both through direct access to junk food and exposure to advertisement, and children's body mass index z scores.

ObjectiveThis study tested the hypothesis that patients without placement of new do-not-resuscitate (DNR) orders during the first 5 days after intracerebral hemorrhage (ICH) have lower 30-day mortality than predicted by the ICH Score without an increase in severe disability at 90 days.MethodsThis was a prospective, multicenter, observational cohort study at 4 academic medical centers and one community hospital. Adults (18 years or older) with nontraumatic spontaneous ICH, Glasgow Coma Scale score of 12 or less, who did not have preexisting DNR orders were included.ResultsOne hundred nine subjects were enrolled. Mean age was 62 years; median Glasgow Coma Scale score was 7, and mean hematoma volume was 39 cm(3). Based on ICH Score prediction, the expected overall 30-day mortality rate was 50%. Observed mortality was substantially lower at 20.2%, absolute average difference 29.8% (95% confidence interval: 21.5%-37.7%). At 90 days, 27.1% had died, 21.5% had a modified Rankin Scale score = 5 (severe disability). A good outcome (modified Rankin Scale score 0-3) was achieved by 29.9% and an additional 21.5% fell into the moderately severe disability range (modified Rankin Scale score = 4).ConclusionsAvoidance of early DNR orders along with guideline concordant ICH care results in substantially lower mortality than predicted. The observed functional outcomes in this study provide clinicians and families with data to determine the appropriate goals of treatment based on patients' wishes.

The hormone cortisol is likely to be a key mediator of the stress response that influences multiple physiologic systems that are involved in common chronic disease, including the cardiovascular system, the immune system, and metabolism. In this paper, a candidate gene approach was used to investigate genetic contributions to variability in multiple correlated features of the daily cortisol profile in a sample of European Americans, African Americans, and Hispanic Americans from the Multi-Ethnic Study of Atherosclerosis (MESA). We proposed and applied a new gene-level multiple-phenotype analysis and carried out a meta-analysis to combine the ethnicity specific results. This new analysis, instead of a more routine single marker-single phenotype approach identified a significant association between one gene (ADRB2) and cortisol features (meta-analysis p-value=0.0025), which was not identified by three other commonly used existing analytic strategies: 1. Single marker association tests involving each single cortisol feature separately; 2. Single marker association tests jointly testing for multiple cortisol features; 3. Gene-level association tests separately carried out for each single cortisol feature. The analytic strategies presented consider different hypotheses regarding genotype-phenotype association and imply different costs of multiple testing. The proposed gene-level analysis integrating multiple cortisol features across multiple ethnic groups provides new insights into the gene-cortisol association.

A major challenge in characterizing features of the daily cortisol curve is variability in features over time. Few studies have examined the stability of daily features of the cortisol curve over long periods or the predictors of long term changes. Repeated salivary cortisol measures on 580 adults from the MESA Stress study were used to examine the stability of various features of the daily cortisol curve (wakeup value, the cortisol awakening response (CAR), the early and late decline slope and the area under the curve (AUC)), over short periods (several days) and long periods (approximately 6-years) and to investigate the association of demographic factors with the changes. Intraclass correlation coefficients (ICCs) were used to estimate the short and long term stability. Piecewise linear mixed models were used to assess factors associated with changes in features over time. For most features, short term stability (ICCs: 0.17-0.74) was higher than long term stability (ICCs: 0.05-0.42), and long term stability was highest when several days were averaged for each time point. The decline over the day showed the highest long term stability: when several days for each wave were averaged the stability of the daily decline slope across 6 years was similar (or higher) than the stability across short periods. AUC had high stability over short periods (ICCs: 0.65-0.74) but much lower stability across long periods (ICC: 0.05). All features of daily cortisol curve investigated changed significantly over the approximately 6 year follow-up period. The wakeup cortisol became higher; the CAR became smaller; both the early and late decline became flatter; and the AUC became larger. Hispanics experienced significantly larger increases in the wakeup value; and African-Americans and Hispanics showed less flattening over time of the early decline slope than Non-Hispanic Whites. Our findings have implications for characterization of features in studies linking cortisol to health outcomes. The presence of variability over time suggests opportunities for future investigation of the predictors of changes over time as well as the links between these changes and health outcomes.

Summary: Prior studies identified variable associations between competitive food and beverage policies (CF&B) and youth obesity, potentially due to differences across population subgroups. This review summarizes the evidence on associations between CF&B policies and childhood obesity within gender, grade level/ age, race/ethnicity, and/or socioeconomic levels. PubMed, EMBASE, CINAHL, and ERIC database searches identified studies published in English in Canada and the United States between January 1, 2000, and February 28, 2022. Of the 18 selected studies, six were cross‐sectional, two correlational, nine were before/after designs, and one study utilized both a cross‐sectional and pre–post design. Twelve studies reported findings stratified by a single sociodemographic factor, with grade level/age as the most frequently reported. Although the evidence varied, greater consistency in direction of associations and strengths of evidence were seen among middle school students. Six studies reported findings jointly by multiple sociodemographic subgroups with evidence suggesting CF&B associations with slower rate of increase or plateaus or declines in obesity among multiple subgroups, though the strengths of evidence varied. Over the past two decades, there have been relatively limited subgroup analyses on studies about CF&B policies and childhood obesity. Studies are needed with stronger designs and analyses disaggregated, particularly by race/ethnicities and socioeconomic factors, across places and time. [ABSTRACT FROM AUTHOR]