Disparities in the impact of heat wave definitions on emergency department visits during the first year of life among preterm and full-term infants in California.

INTRODUCTION: Heat waves will be aggravated due to climate change, making this a critical public health threat. However, heat wave definitions to activate alert systems can be ambiguous, highlighting the need to assess a range of definitions to identify those that contribute to the most adverse health outcomes. Additionally, children are highly susceptible to the impacts of heat waves, especially infants, despite the lack of focus on this subpopulation. We aimed to assess the relationship between 30 heat wave definitions and the first all-cause emergency department (ED) visits for California infants. We also examined modification of this relationship by preterm birth status and demographic characteristics to identify possible health disparities. METHODS: Live-born, singleton deliveries from the Study of Outcomes in Mothers and Infants born in 2014-2018 were included. Thirty heat wave definitions were assessed based on temperature metrics (minimum/maximum temperatures), thresholds (90th; 92.5th; 95th; 97.5th; 99th percentiles), and duration (1-; 2-; 3-days). A time-stratified case-crossover design assessed heat wave impacts on ED visits using infants with a warm season ED visit (May-October) within the first year of life (n = 228,250). Effect modification by preterm birth status, age, sex, race/ethnicity, education, and delivery payment type was also investigated. RESULTS: Infants demonstrated increased risk of an ED visit with exposure to all heat definitions. The 3-day minimum temperature 99th percentile definition had the highest adjusted odds ratio (AOR: 1.14; 95% CI: 1.05-1.23) for the total population. Term infants were more affected by some heat waves than preterm infants. Effect modification was additionally identified, such as by maternal education. DISCUSSION: This study provides insight on the heat wave definitions that lead to adverse health outcomes and the identification of the most susceptible infants to these impacts, which has implications on heat-related interventions.

Examining the Relationship Between Extreme Temperature, Microclimate Indicators, and Gestational Diabetes Mellitus in Pregnant Women Living in Southern California.

Few studies have assessed extreme temperatures' impact on gestational diabetes mellitus (GDM). We examined the relation between GDM risk with weekly exposure to extreme high and low temperatures during the first 24 weeks of gestation and assessed potential effect modification by microclimate indicators. Methods: We utilized 2008-2018 data for pregnant women from Kaiser Permanente Southern California electronic health records. GDM screening occurred between 24 and 28 gestational weeks for most women using the Carpenter-Coustan criteria or the International Association of Diabetes and Pregnancy Study Groups criteria. Daily maximum, minimum, and mean temperature data were linked to participants' residential address. We utilized distributed lag models, which assessed the lag from the first to the corresponding week, with logistic regression models to examine the exposure-lag-response associations between the 12 weekly extreme temperature exposures and GDM risk. We used the relative risk due to interaction (RERI) to estimate the additive modification of microclimate indicators on the relation between extreme temperature and GDM risk. Results: GDM risks increased with extreme low temperature during gestational weeks 20--24 and with extreme high temperature at weeks 11-16. Microclimate indicators modified the influence of extreme temperatures on GDM risk. For example, there were positive RERIs for high-temperature extremes and less greenness, and a negative RERI for low-temperature extremes and increased impervious surface percentage. Discussion: Susceptibility windows to extreme temperatures during pregnancy were observed. Modifiable microclimate indicators were identified that may attenuate temperature exposures during these windows, which could in turn reduce the health burden from GDM.

The role of the California tier system in controlling population mobility during the COVID-19 pandemic.

BACKGROUND: Policies to restrict population mobility are a commonly used strategy to limit the transmission of contagious diseases. Among measures implemented during the COVID-19 pandemic were dynamic stay-at-home orders informed by real-time, regional-level data. California was the first state in the U.S. to implement this novel approach; however, the effectiveness of California's four-tier system on population mobility has not been quantified. METHODS: Utilizing data from mobile devices and county-level demographic data, we evaluated the impact of policy changes on population mobility and explored whether demographic characteristics explained variability in responsiveness to policy changes. For each California county, we calculated the proportion of people staying home and the average number of daily trips taken per 100 persons, across different trip distances and compared this to pre-COVID-19 levels. RESULTS: We found that overall mobility decreased when counties moved to a more restrictive tier and increased when moving to a less restrictive tier, as the policy intended. When placed in a more restrictive tier, the greatest decrease in mobility was observed for shorter and medium-range trips, while there was an unexpected increase in the longer trips. The mobility response varied by geographic region, as well as county-level median income, gross domestic product, economic, social, and educational contexts, the prevalence of farms, and recent election results. CONCLUSIONS: This analysis provides evidence of the effectiveness of the tier-based system in decreasing overall population mobility to ultimately reduce COVID-19 transmission. Results demonstrate that socio-political demographic indicators drive important variability in such patterns across counties.

Exposure to Air Pollution and Emergency Department Visits During the First Year of Life Among Preterm and Full-term Infants.

Importance: Previous studies have focused on exposure to fine particulate matter 2.5 µm or less in diameter (PM2.5) and on birth outcome risks; however, few studies have evaluated the health consequences of PM2.5 exposure on infants during their first year of life and whether prematurity could exacerbate such risks. Objective: To assess the association of PM2.5 exposure with emergency department (ED) visits during the first year of life and determine whether preterm birth status modifies the association. Design, Setting, and Participants: This individual-level cohort study used data from the Study of Outcomes in Mothers and Infants cohort, which includes all live-born, singleton deliveries in California. Data from infants' health records through their first birthday were included. Participants included 2 175 180 infants born between 2014 and 2018, and complete data were included for an analytic sample of 1 983 700 (91.2%). Analysis was conducted from October 2021 to September 2022. Exposures: Weekly PM2.5 exposure at the residential ZIP code at birth was estimated from an ensemble model combining multiple machine learning algorithms and several potentially associated variables. Main Outcomes and Measures: Main outcomes included the first all-cause ED visit and the first infection- and respiratory-related visits separately. Hypotheses were generated after data collection and prior to analysis. Pooled logistic regression models with a discrete time approach assessed PM2.5 exposure and time to ED visits during each week of the first year of life and across the entire year. Preterm birth status, sex, and payment type for delivery were assessed as effect modifiers. Results: Of the 1 983 700 infants, 979 038 (49.4%) were female, 966 349 (48.7%) were Hispanic, and 142 081 (7.2%) were preterm. Across the first year of life, the odds of an ED visit for any cause were greater among both preterm (AOR, 1.056; 95% CI, 1.048-1.064) and full-term (AOR, 1.051; 95% CI, 1.049-1.053) infants for each 5-µg/m3 increase in exposure to PM2.5. Elevated odds were also observed for infection-related ED visit (preterm: AOR, 1.035; 95% CI, 1.001-1.069; full-term: AOR, 1.053; 95% CI, 1.044-1.062) and first respiratory-related ED visit (preterm: AOR, 1.080; 95% CI, 1.067-1.093; full-term: AOR,1.065; 95% CI, 1.061-1.069). For both preterm and full-term infants, ages 18 to 23 weeks were associated with the greatest odds of all-cause ED visits (AORs ranged from 1.034; 95% CI, 0.976-1.094 to 1.077; 95% CI, 1.022-1.135). Conclusions and Relevance: Increasing PM2.5 exposure was associated with an increased ED visit risk for both preterm and full-term infants during the first year of life, which may have implications for interventions aimed at minimizing air pollution.

Quantitative methods for climate change and mental health research: current trends and future directions.

The quantitative literature on climate change and mental health is growing rapidly. However, the methodological quality of the evidence is heterogeneous, and there is scope for methodological improvement and innovation. The first section of this Personal View provides a snapshot of current methodological trends and issues in the quantitative literature on climate change and mental health, drawing on literature collected through a previous scoping review. The second part of this Personal View outlines opportunities for methodological innovation concerning the assessment of the relationship between climate change and mental health. We then highlight possible methodological innovations in intervention research and in the measurement of climate change and mental health-related variables. This section draws upon methods from public mental health, environmental epidemiology, and other fields. The objective is not to provide a detailed description of different methodological techniques, but rather to highlight opportunities to use diverse methods, collaborate across disciplines, and inspire methodological innovation. The reader will be referred to practical guidance on different methods when available. We hope this Personal View will constitute a roadmap and launching pad for methodological innovation for researchers interested in investigating a rapidly growing area of research.

A Longitudinal Study on the Impact of Indoor Temperature on Heat-Related Symptoms in Older Adults Living in Non-Air-Conditioned Households.

BACKGROUND: Both chronic and acute heat result in a substantial health burden globally, causing particular concern for at-risk populations, such as older adults. Outdoor temperatures are often assessed as the exposure and are used for heat warning systems despite individuals spending most of their time indoors. Many studies use ecological designs, with death or hospitalizations rates. Individual-level outcomes that are directly related to heat-symptoms should also be considered to refine prevention efforts. OBJECTIVES: In this longitudinal study, we assessed the association between indoor temperature and proximal symptoms in individuals ≥60 years of age living in non-air-conditioned households in Montérégie, Quebec, during the 2017-2018 summer months. METHODS: We gathered continuously measured indoor temperature and humidity from HOBO sensors and repeated health-related questionnaires about health-related symptoms administered across three periods of increasing outdoor temperatures, where the reference measurement (T1) occurred during a cool period with a target temperature of 18-22°C and two measurements (T2 and T3) occurred during warmer periods with target temperatures of 28-30°C and 30-33°C, respectively. We used generalized estimating equations with Poisson regression models and estimated risk ratios (RRs) between temperature, humidity, and each heat-related symptom. RESULTS: Participants (n=277) had an average age (mean±standard deviation) of 72.8±7.02y. Higher indoor temperatures were associated with increased risk of dry mouth (T3 RR=2.5; 95% CI: 1.8, 3.5), fatigue (RR=2.3; 95% CI: 1.8, 3.0), thirst (RR=3.4; 95% CI: 2.5, 4.5), less frequent urination (RR=3.7; 95% CI: 1.8, 7.3), and trouble sleeping (RR=2.2; 95% CI: 1.6, 3.2) compared with T1. We identified a nonlinear relationship with indoor temperatures across most symptoms of interest. DISCUSSION: This study identified that increasing indoor temperatures were associated with various health symptoms. By considering the prevalence of these early stage outcomes and indoor temperature exposures, adaptation strategies may be improved to minimize the burden of heat among vulnerable communities. https://doi.org/10.1289/EHP10291.

The Formation of Belief: An Examination of Factors That Influence Climate Change Belief Among Hurricane Katrina Survivors.

Differences in population-level climate change beliefs have been identified, which are often attributable to coastline proximity, urban-rural classifications, race, ethnicity, political affiliation, gender, education, socioeconomic status, and age. This study assessed the impact of spatial, experiential, and demographic-related characteristics on climate change beliefs among a population of Hurricane Katrina survivors. Participants from the Gulf Coast Child and Family Health Study who answered climate change belief questions were included in this analysis. Race was found to be the most critical contributor to climate change belief, where the adjusted odds of white individuals believing in climate change were 0.2 times the odds of Black individuals believing in climate change (confidence interval: 0.1-0.4). Other sociodemographic factors, such as age, gender, income, and education, were not found to be significant. Several theoretical perspectives were considered to explain the variation in climate change beliefs, including social vulnerability, environmental deprivation, and political ideology. Future research as to why these racial differences exist should be conducted. By doing so, climate change communication, education, and mitigation and adaptation strategies may be improved.

The identification of the endogenous ligands of natural killer T cells reveals the presence of mammalian α-linked glycosylceramides.

Glycosylceramides in mammalian species are thought to be present in the form of ß-anomers. This conclusion was reinforced by the identification of only one glucosylceramide and one galactosylceramide synthase, both ß-transferases, in mammalian genomes. Thus, the possibility that small amounts of α-anomers could be produced by an alternative enzymatic pathway, by an unfaithful enzyme, or spontaneously in unusual cellular compartments has not been examined in detail. We approached the question by taking advantage of the exquisite specificity of T and B lymphocytes and combined it with the specificity of catabolic enzymes of the sphingolipid pathway. Here, we demonstrate that mammalian immune cells produce constitutively very small quantities of α-glycosylceramides, which are the major endogenous ligands of natural killer T cells. Catabolic enzymes of the ceramide and glycolipid pathway tightly control the amount of these α-glycosylceramides. The exploitation of this pathway to manipulate the immune response will create new therapeutic opportunities.