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STUDY OBJECTIVES: Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity. METHODS: Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity. RESULTS: We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity. CONCLUSIONS: In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

Though fine particulate matter (PM2.5) has decreased in the United States (U.S.) in the past two decades, the increasing frequency, duration, and severity of wildfires significantly (though episodically) impairs air quality in wildfire-prone regions and beyond. Increasing PM2.5 concentrations derived from wildfire smoke and associated impacts on public health require dedicated epidemiological studies. Main sources of PM2.5 data are provided by government-operated monitors sparsely located across U.S., leaving several regions and potentially vulnerable populations unmonitored. Current approaches to estimate PM2.5 concentrations in unmonitored areas often rely on big data, such as satellite-derived aerosol properties and meteorological variables, apply computationally-intensive deterministic modeling, and do not distinguish wildfire-specific PM2.5 from other sources of emissions such as traffic and industrial sources. Furthermore, modelling wildfire-specific PM2.5 presents a challenge since measurements of the smoke contribution to PM2.5 pollution are not available. Here, we aim to use statistical methods to isolate wildfire-specific PM2.5 from other sources of emissions. Our study presents an ensemble model that optimally combines multiple machine learning algorithms (including gradient boosting machine, random forest and deep learning), and a large set of explanatory variables to, first, estimate daily PM2.5 concentrations at the ZIP code level, a relevant spatiotemporal resolution for epidemiological studies. Subsequently, we propose a novel implementation of an imputation approach to estimate the wildfire-specific PM2.5 concentrations that could be applied geographical regions in the US or worldwide. Our ensemble model achieved comparable results to previous machine learning studies for PM2.5 prediction while avoiding processing larger, computationally intensive datasets. Our study is the first to apply a suite of statistical models using readily available datasets to provide daily wildfire-specific PM2.5 at a fine spatial scale for a 15-year period, thus providing a relevant spatiotemporal resolution and timely contribution for epidemiological studies.

BackgroundPolicies 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.MethodsUtilizing 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.ResultsWe 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.ConclusionsThis 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.

BackgroundPrecipitation anomalies are associated with a number of poor health outcomes. One potential consequence of precipitation extremes is human geographic mobility. We evaluated the associations between precipitation anomalies (droughts and heavy rains) and short-term mobility in 23 sub-Saharan African countries by linking satellite data on precipitation to cross-sectional representative surveys.MethodsUsing data from 23 Demographic and Health Surveys from 2011 to 2017, we estimated the associations between deviations in long-term rainfall trends and short-term mobility among 294,539 women and 136,415 men over 15 years of age. We fit multivariable logistic regression models to assess potential non-linear relationships between rainfall deviations and short-term mobility, adjusting for survey month and socio-demographic covariates, and stratified by participant gender. Furthermore, we assessed whether these associations differed by marital status.ResultsRainfall deviations were associated with short-term mobility among women, but not men. The relationship between rainfall deviations and mobility among women was U-shaped, such that women had increased marginal probabilities of mobility in instances of both lower and heavier precipitation. Differences between married and unmarried women were also revealed: among married women, we found positive associations between both rainfall deviation extremes (drought and heavy rains) and mobility; however, among unmarried women, there was only a positive association for heavy rains.ConclusionPrecipitation anomalies were associated with short-term mobility among women, which may be in turn associated with poor health outcomes. More research with longitudinal data is needed to elaborate the associations between weather shocks, mobility, and downstream health impacts.

Emissions of fine particulate matter (PM2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM2.5 and the fractional contributions to PM2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM2.5 levels are among the lowest worldwide, reducing PM2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabetes, and metabolic syndrome in San Diego County, CA. As part of the Community of Mine Study, cardiometabolic outcomes of insulin resistance, hypertension, BMI, diabetes, and metabolic syndrome were collected in 570 participants. Seven census tract level characteristics of participants' residential environment were assessed and grouped as follows: economic, education, health care access, neighborhood conditions, social environment, transportation, and clean environment. Generalized estimating equation models were performed, to take into account the clustered nature of the data and to estimate β or relative risk (RR) and 95 % confidence intervals (CIs) between each of the seven environmental characteristics and cardiometabolic outcomes. Quantile g-computation was used to examine the association between the joint effect of a simultaneous increase in all environmental characteristics and cardiometabolic outcomes. Among 570 participants (mean age 58.8 ± 11 years), environmental economic, educational and health characteristics were individually associated with insulin resistance, diabetes, obesity, and metabolic syndrome. In the mixture analyses, a joint quartile increase in all environmental characteristics (i.e., improvement) was associated with decreasing insulin resistance (β, 95 %CI: -0.09, -0.18-0.01)), risk of diabetes (RR, 95 %CI: 0.59, 0.36-0.98) and obesity (RR, 95 %CI: 0.81, 0.64-1.02). Environmental characteristics synergistically contribute to cardiometabolic health and independent analysis of these determinants may not fully capture the potential health impact of social and environmental determinants of health.

The COVID-19 pandemic disrupted life in extraordinary ways impacting health and daily mobility. Public transit provides a strategy to improve individual and population health through increased active travel and reduced vehicle dependency, while ensuring equitable access to jobs, healthcare, education, and mitigating climate change. However, health safety concerns during the COVID-19 pandemic eroded ridership, which could have longstanding negative consequences. Research is needed to understand how mobility and health change as the pandemic recedes and how transit investments impact health and equity outcomes. The TROLLEY (TRansit Opportunities for HeaLth, Livability, Exercise and EquitY) study will prospectively investigate a diverse cohort of university employees after the opening of a new light rail transit (LRT) line and the easing of campus COVID-19 restrictions. Participants are current staff who live either  2 miles from LRT, with equal distribution across economic and racial/ethnic strata. The primary aim is to assess change in physical activity, travel mode, and vehicle miles travelled using accelerometer and GPS devices. Equity outcomes include household transportation and health-related expenditures. Change in health outcomes, including depressive symptoms, stress, quality of life, body mass index and behavior change constructs related to transit use will be assessed via self-report. Pre-pandemic variables will be retrospectively collected. Participants will be measured at 3 times over 2 years of follow up. Longitudinal changes in outcomes will be assessed using multilevel mixed effects models. Analyses will evaluate whether proximity to LRT, sociodemographic, and environmental factors modify change in outcomes over time. The TROLLEY study will utilize rigorous methods to advance our understanding of health, well-being, and equity-oriented outcomes of new LRT infrastructure through the COVID-19 recovery period, in a sample of demographically diverse adult workers whose employment location is accessed by new transit. Results will inform land use, transportation and health investments, and workplace interventions. Findings have the potential to elevate LRT as a public health priority and provide insight on how to ensure public transit meets the needs of vulnerable users and is more resilient in the face of future health pandemics. The TROLLEY study was registered at ClinicalTrials.gov ( NCT04940481 ) June 17, 2021, and OSF Registries ( https://doi.org/10.17605/OSF.IO/PGEHU ) June 24, 2021, prior to participant enrollment.

BackgroundOlder adults are the least active population in the U.S. Low-income communities have fewer physical activity (PA) resources, contributing to less PA and increased chronic disease risk. This study assessed the effect of the multilevel, peer-led, Peer Empowerment Program 4 Physical Activity (PEP4PA) on moderate-to-vigorous PA (MVPA) and health outcomes, over 2 years of follow up.MethodsIn a cluster-randomized controlled trial, 12 senior or community centers serving low-income older adults were assigned to a PA intervention (n = 6) or usual programming (n = 6) condition. PEP4PA included self-monitoring, health coaching, group walks, social support, and community advocacy to improve walking conditions. The primary outcome was daily minutes of MVPA (7-day accelerometer). Secondary outcomes included Perceived Quality of Life (PQoL), 6-Minute Walk Test (6-MWT), blood pressure (BP), and depressive symptoms at baseline, 6, 12, 18 and 24 months. Mixed effects regression models estimated the effects on outcomes between groups over time and included random effects for repeated measures and center clustering. Effect modification by sex and income status was assessed. We calculated the incremental cost per daily minute of MVPA gained in the intervention group relative to the control group to assess cost effectiveness.ResultsWe enrolled 476 older adults (50 + years). Participants were on average 71 years old, 76% female, 60% low income, and 38% identified as racial or ethnic minorities. Compared to the control group, intervention participants sustained roughly a 10 min/day increase in MVPA from baseline at all time points and increased mean PQoL scores from unsatisfied at baseline to satisfied at 12, 18 and 24 months. Males and higher-income groups had greater improvements in MVPA. No significant effects were observed for 6-MWT or depressive symptoms, and BP results were mixed. The incremental cost per minute MVPA gained per person was $0.25, $0.09, $0.06, and $0.05 at 6, 12, 18 and 24 months, respectively.ConclusionsPEP4PA achieved increases in MVPA and PQoL in low-income older adults, over 2 years of follow up. The peer-led, community-based intervention provides a sustainable and cost-effective model to improve health behaviors in underserved, aging populations.Trial registrationClinicalTrials.gov ( NCT02405325 ) March 20, 2015.

Background Long-term exposure to outdoor fine particulate matter (PM2.5) is the leading environmental risk factor for premature mortality worldwide. Characterizing important pathways through which PM2.5 increases individuals' mortality risk can clarify the PM2.5-mortality relationship and identify possible points of interventions. Recent evidence has linked PM2.5 to the onset of diabetes and cardiovascular disease, but to what extent these associations contribute to the effect of PM2.5 on mortality remains poorly understood. Methods and Results We conducted a population-based cohort study to investigate how the effect of PM2.5 on nonaccidental mortality is mediated by its impacts on incident diabetes, acute myocardial infarction, and stroke. Our study population comprised ≈200 000 individuals aged 20 to 90 years who participated in population-based health surveys in Ontario, Canada, from 1996 to 2014. Follow-up extended until December 2017. Using causal mediation analyses with Aalen additive hazards models, we decomposed the total effect of PM2.5 on mortality into a direct effect and several path-specific indirect effects mediated by diabetes, each cardiovascular event, or both combined. A series of sensitivity analyses were also conducted. After adjusting for various individual- and neighborhood-level covariates, we estimated that for every 1000 adults, each 10 μg/m3 increase in PM2.5 was associated with ≈2 incident cases of diabetes, ≈1 major cardiovascular event (acute myocardial infarction and stroke combined), and ≈2 deaths annually. Among PM2.5-related deaths, 31.7% (95% CI, 17.2%-53.2%) were attributable to diabetes and major cardiovascular events in relation to PM2.5. Specifically, 4.5% were explained by PM2.5-induced diabetes, 22.8% by PM2.5-induced major cardiovascular events, and 4.5% through their interaction. Conclusions This study suggests that a significant portion of the estimated effect of long-term exposure to PM2.5 on deaths can be attributed to its effect on diabetes and cardiovascular diseases, highlighting the significance of PM2.5 on deteriorating cardiovascular health. Our findings should raise awareness among professionals that improving metabolic and cardiovascular health may reduce mortality burden in areas with higher exposure to air pollution.

Lower respiratory tract infections disproportionately affect children and are one of the main causes of hospital referral and admission. COVID-19 stay-at-home orders in early 2020 led to substantial reductions in hospital admissions, but the specific contribution of changes in air quality through this natural experiment has not been examined. Capitalizing on the timing of the stay-at-home order, we quantified the specific contribution of fine-scale changes in PM2.5 concentrations to reduced respiratory emergency department (ED) visits in the pediatric population of San Diego County, California. We analyzed data on pediatric ED visits (n = 72,333) at the ZIP-code level for respiratory complaints obtained from the ED at Rady Childrens Hospital in San Diego County (2015-2020) and ZIP-code level PM2.5 from an ensemble model integrating multiple machine learning algorithms. We examined the decrease in respiratory visits in the pediatric population attributable to the stay-at-home order and quantified the contribution of changes in PM2.5 exposure using mediation analysis (inverse of odds ratio weighting). Pediatric respiratory ED visits dropped during the stay-at-home order (starting on 19 March 2020). Immediately after this period, PM2.5 concentrations, relative to the counterfactual values based in the 4-year baseline period, also decreased with important spatial variability across ZIP codes in San Diego County. Overall, we found that decreases in PM2.5 attributed to the stay-at-home order contributed to explain 4% of the decrease in pediatric respiratory ED visits. We identified important spatial inequalities in the decreased incidence of pediatric respiratory illness and found that brief decline in air pollution levels contributed to a decrease in respiratory ED visits.

Changing environmental conditions constitutes one of the greatest threats to human health by reducing agricultural yields and exacerbating the burden of undernutrition. Mozambique is a region characterized by a high dependence on agricultural productivity and an increasing prevalence of climate shocks in the form of droughts and floods. Low food availability as a result of changing environmental conditions can impair child development and long-term agricultural productivity, thus necessitating e!orts to understand and protect children’s health. Women’s empowerment is strongly associated with children’s nutritional status, such that disparities in maternal autonomy and educational attainment may explain variations in climate-related vulnerabilities in this regional context. The purpose of this research is to determine the extent climate shocks are associated with child undernutrition among di!erent populations in Mozambique by focusing on droughts and floods during the main crop growing season. In addition, this research investigates the potential of women's empowerment for mitigating climate-related vulnerabilities of children. Demographic health data is linked with regional gridded climate data using a stratified regression analysis to provide information on the impact of climate shocks on child undernutrition among livelihood subgroups of croppers and fishers. This cross-sectional study found that exposure to climate shocks during the main rainy season, from November to May, increases the risk of stunting in children under age five and that women’s empowerment may not be a mitigating factor in the protection of children’s health from climate shocks. Identifying population groups most adversely a!ected by climate change will be important for reducing social inequities and achieving the Sustainable Development Goals within Mozambique.

ObjectivesTo identify how the 2017 rapid surge in sales of JUUL e-cigarettes affected usage among US youth and young adults.MethodsAnnual surveys in the Population Assessment of Tobacco and Health Study assess tobacco use by product and brand among the US population. We identified 2 cohorts aged 14 to 34 years, 1 with baseline survey in 2014 before the rapid surge of JUUL and the other in 2017 as the surge in JUUL sales was occurring. For 5 age groups, we compared 2-year incidence of first tobacco use and of new-onset daily tobacco use by product, and report levels of dependence.ResultsSociodemographic variables and rates of experimentation with any tobacco product were similar between cohorts. Among baseline nondaily tobacco users, only those aged 14 to 17 years had an increase in the 2-year incidence of new daily tobacco use (2014 cohort = 4.8%, 95% confidence interval 4.3, 5.5 vs 2017 cohort = 6.3%, 95% confidence interval 5.8-7.0) to rates approaching those in the 1990s. In 2019, three-quarters of new daily tobacco users aged 14 to 17 vaped daily and had e-cigarette dependence scores similar to daily cigarette smokers and older adult e-cigarette vapers. We estimate that about 600 000 Americans aged

ImportanceMenthol may make cigarette smoke less aversive and could lead youth to smoke more frequently and become more dependent on nicotine.ObjectiveTo assess the association of menthol use with cigarette smoking frequency and nicotine dependence (ND) among youth cigarettes users.Design, setting, and participantsThis cohort study used a pooled sample of cohorts of US youth (aged 12-17 years at their baseline and follow-up interviews) in the Population Assessment of Tobacco and Health Study (September 2013 to November 2019). Household interviews were conducted using audio computer-assisted self-interviews. US youth who were past-30-day cigarette smokers at any of wave 2 through wave 5, completed the preceding survey (eg, wave 2 past-30-day cigarette smokers completed wave 1), and indicated whether they used menthol cigarettes were eligible. The association of menthol use with smoking frequency and ND was estimated using inverse probability of treatment weighting adjusted mean differences (aMDs), adjusted risk ratios (aRRs), and corresponding 95% CIs. Data were analyzed from December 2021 to March 2022.ExposuresMenthol use and transitions in use (switching to or from menthol cigarettes).Main outcomes and measuresMain outcomes were the number of days smoked in the past 30 days, the risk of frequent smoking (smoking ≥20 days in the past 30 days), and symptoms of ND.ResultsThere were a total of 1492 observations among 1096 US youth cigarette smokers, of whom 49.4% were female, 67.2% were non-Hispanic White, and 28.7% were aged 12 to 14 years at their baseline survey (all percentages are weighted). Among those who switched from not smoking to smoking (61% of the sample), menthol use was associated with smoking on 3.1 additional days (aMD; 95% CI, 1.9 to 4.2 days), 59% higher risk of being a frequent smoker (aRR, 1.59; 95% CI, 1.23 to 2.06), and 10% higher ND scores (aMD, 1.09; 95% CI, 1.02 to 1.17). Switching from smoking menthol to smoking nonmenthol (vs maintaining menthol use) was associated with smoking on 3.6 fewer days (aMD; 95% CI, -6.3 to -0.9 days) and 47% lower risk of being a frequent smoker (aRR, 0.68; 95% CI, 0.50 to 0.92).Conclusions and relevanceThese findings suggest that the addition of menthol to cigarettes is associated with increased smoking frequency and ND among US youth.

IntroductionExposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures.MethodsAmong the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM2.5, NO2, traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data.ResultsAmong 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM2.5 using dynamic measures. For all participants, higher dynamic exposure to PM2.5 and NO2 was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07-1.28; RR 1.21, 95% CI: 1.12-1.30, respectively). The association between dynamic PM2.5 exposure and MetS differed by Hispanic/Latino ethnicity.ConclusionThese results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.

BackgroundThe tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.MethodsWe used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ground-level ozone (O3), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals' long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.ResultsAmong the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM2.5 (1.70 μg/m3), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01-1.12), 1.09 (95% CI 0.98-1.21) and 1.00 (95% CI 0.90-1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO2. We also estimated odds ratios of 1.15 (95% CI 1.06-1.23), 1.30 (95% CI 1.12-1.50) and 1.18 (95% CI 1.02-1.36) per interquartile range increase of 5.14 ppb in O3 for hospital admission, ICU admission and death, respectively.InterpretationChronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O3.

Mineral dust is one of the largest natural constituents of coarse particulate matter (PM10). Most of these dust emissions originate from northern Africa, and several hundred tera-grams of dust are emitted annually from this region. Previous evidence has linked dust PM10 to adverse respiratory outcomes in children. However, most of these studies have been from high-income countries (HICs) or examined dust from other regions of the world, mainly Asia. Evidence from low-to-middle-income countries (LMICs) in Africa is scarce. Respiratory infections are one of the leading causes of under-five mortality across the globe. However, there is a poignant disparity in studies examining these outcomes in children in the region where most dust is emitted. This study linked remotely sensed satellite data to a nationally representative survey to examine acute exposure to dust in children living in Benin using a time-stratified case-crossover analysis. We identified acute effects of exposure to dust and increased risk of cough in children under five. The effect of increased risk is strongest within two weeks of exposure and dissipates by four weeks. Children living in rural areas and households with lower income had a greater risk of adverse respiratory outcomes when exposed to dust. We could elucidate the specific period and conditions of increased risk for respiratory problems in children living in Benin.

BackgroundThis is the first systematic review and meta-analysis assessing cardiovascular disease incidence and risk factors among refugees and asylum seekers.Methods and resultsPubMed, PsycINFO, CINAHL, and Embase databases were searched for studies in English from January 1, 1977, to March 8, 2020. Inclusion criteria were (1) observation of refugee history in participants; (2) diagnosis of CVD (coronary artery disease, heart failure, stroke, or CVD mortality) and risk factors (hypertension, diabetes, tobacco use, hyperlipidemia, obesity, psychosocial factors); (3) assessment of effect size and spread, (4) adjustment for sex; and (5) comparison with non-refugee migrants or natives. Data were extracted and evaluated by multiple reviewers for study quality. Of the 1158 screened articles, Participants from 7 studies (0.6%) involving 116.989 refugees living in Denmark, Sweden, and the United States were included in the systematic review, of which three studies synthesized the quantitative analyses. A fixed-effects model was created to pool the effect sizes of included studies. The pooled incidence of CVD in refugees was 1.71 (95% CI: 1.03, 2.83) compared with non-refugee counterparts. Pyschosocial factors were associated with increased risk of CVD in refugees but evidence on CVD risk factors varied by nativity and duration since resettlement.ConclusionsRefugee experience is an independent risk factor for CVD. Robust research on CVD in displaced populations is needed to improve the quality of evidence, clinical and preventive care, and address health equity in this marginalized population globally.

BackgroundEpidemiological findings are inconsistent regarding the associations between air pollution exposure during pregnancy and gestational diabetes mellitus (GDM). Several limitations exist in previous studies, including potential outcome and exposure misclassification, unassessed confounding, and lack of simultaneous consideration of air pollution mixtures and particulate matter (PM) constituents.ObjectivesTo assess the association between GDM and maternal residential exposure to air pollution, and the joint effect of the mixture of air pollutants and PM constituents.MethodsDetailed clinical data were obtained for 395,927 pregnancies in southern California (2008-2018) from Kaiser Permanente Southern California (KPSC) electronic health records. GDM diagnosis was based on KPSC laboratory tests. Monthly average concentrations of fine particulate matter

Limited previous work has identified a relationship between exposure to ambient air pollution and aggressive somatic lung tumor mutations. More work is needed to confirm this relationship, especially using spatially resolved air pollution. We aimed to quantify the association between different air pollution metrics and aggressive tumor biology. Among patients treated at City of Hope Comprehensive Cancer Center in Duarte, CA (2013-2018), three non-small cell lung cancer somatic tumor mutations, TP53, KRAS, and KRAS G12C/V, were documented. PM2.5 exposure was assessed using state-of-the art ensemble models five and ten years before lung cancer diagnosis. We also explored the role of NO2 using inverse-distance-weighting approaches. We fitted logistic regression models to estimate odds ratio (OR) and their 95% confidence intervals (CIs). Among 435 participants (median age: 67, female: 51%), an IQR increase in NO2 exposure (3.5 μg/m3) five years before cancer diagnosis was associated with an increased risk in TP53 mutation (OR, 95% CI: 1.30, 0.99-1.71). We found an association between highly-exposed participants to PM2.5 (>12 μg/m3) five and ten years before cancer diagnosis and TP53 mutation (OR, 95% CI: 1.61, 0.95-2.73; 1.57, 0.93-2.64, respectively). Future studies are needed to confirm this association and better understand how air pollution impacts somatic profiles and the molecular mechanisms through which they operate.

Numerous epidemiologic studies have documented environmental health disparities according to race/ethnicity (R/E) to inform targeted interventions aimed at reducing these disparities. Yet, the use of R/E under the potential outcomes framework implies numerous underlying assumptions for epidemiologic studies that are often not carefully considered in environmental health research. In this commentary, we describe the current state of thinking about the interpretation of R/E variables in etiologic studies. We then discuss how such variables are commonly used in environmental epidemiology. We observed three main uses for R/E: i) as a confounder, ii) as an effect measure modifier and iii) as the main exposure of interest either through descriptive analysis or under a causal framework. We identified some common methodological concerns in each case and provided some practical solutions. The use of R/E in observational studies requires particular cautions in terms of formal interpretation and this commentary aims at providing a practical resource for future studies assessing racial/ethnic health disparities in environmental research.

This study aimed to investigate the role of cardiovascular health (CVH) and vascular events as potential contributors to socioeconomic inequalities in dementia using causal mediation analyses. We used data from the Three-City Cohort, a French population-based study with 12 years of follow-up, with active search of dementia cases and validated diagnosis. Individual socioeconomic status was assessed using education, occupation and income. A CVH score as defined by the American Heart Association and incident vascular events were considered separately as mediators. We performed multi-level Cox proportional and Aalen additive hazard regression models to estimate the total effects of socioeconomic status on dementia risk. To estimate natural direct and indirect effects through CVH and vascular events, we applied two distinct weighting methods to quantify the role of CVH and vascular events: Inverse Odds Ratio Weighting (IORW) and Marginal Structural Models (MSM) respectively. Among 5581 participants, the risk of dementia was higher among participants with primary education (HR 1.60, 95%CI 1.44-1.78), blue-collar workers (HR 1.62, 95%CI 1.43-1.84) and with lower income (HR 1.23, 95%CI 1.09-1.29). Using additive models, 571 (95% CI 288-782) and 634 (95% CI 246-1020) additional cases of dementia per 100 000 person and year were estimated for primary education and blue-collar occupation, respectively. Using IORW, the CVH score mediate the relationship between education or income, and dementia (proportion mediated 17% and 26%, respectively). Yet, considering vascular events as mediator, MSM generated indirect effects that were smaller and more imprecise. Socioeconomic inequalities in dementia risk were observed but marginally explained by CVH or vascular events mediators.

ImportanceAlthough e-cigarettes are not approved as a cessation device, many who smoke believe that e-cigarettes will help them quit cigarette smoking successfully.ObjectiveTo assess whether people who recently quit smoking and who had switched to e-cigarettes or another tobacco product were less likely to relapse to cigarette smoking compared with those who remained tobacco free.Design, setting, and participantsThis cohort study analyzed a nationally representative sample of US households that participated in 4 waves of the Population Assessment of Tobacco and Health Study (conducted 2013 through 2017), combining 2 independent cohorts each with 3 annual surveys. Eligible participants were individuals who smoked at baseline, had recently quit at the first follow-up, and completed the second follow-up survey.ExposuresUse of e-cigarettes or alternate tobacco products at follow-up 1 after recently quitting smoking.Main outcomes and measuresWeighted percentage of participants with over 12 months abstinence by follow-up 2.ResultsOf a total of 13 604 participants who smoked cigarettes at baseline, 9.4% (95% CI, 8.7%-10.0%) recently had quit smoking (mean age, 41.9; 95% CI, 39.7-46.6 years; 641 [43.2%] women) Of these, 22.8% (95% CI, 19.7%-26.0%) had switched to e-cigarettes, with 17.6% (95% CI, 14.8%-20.5%) using them daily. A total of 37.1% (95% CI, 33.7%-40.4%) used a noncigarette tobacco product and 62.9% (95% CI, 59.6%-66.3%) were tobacco free. Rates of switching to e-cigarettes were highest for those who were in the top tertile of tobacco dependence (31.3%; 95% CI, 25.0%-37.7%), were non-Hispanic White (26.4%; 95% CI, 22.3%-30.4%), and had higher incomes (annual income ≥$35 000, 27.5%; 95% CI, 22.5%-32.4% vs

BackgroundExtreme weather events, including droughts, are expected to increase in parts of sub-Saharan Africa and are associated with a number of poor health outcomes; however, to the best of our knowledge, the link between drought and childhood vaccination remains unknown. The objective of this study was to evaluate the relationship between drought and vaccination coverage.Methods and findingsWe investigated the association between drought and vaccination coverage using a retrospective analysis of Demographic and Health Surveys data in 22 sub-Saharan African countries among 137,379 children (50.4% male) born from 2011 to 2019. Drought was defined as an established binary variable of annual rainfall less than or equal to the 15th percentile relative to the 29 previous years, using data from Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. We evaluated the association between drought at the date of birth and receipt of bacillus Calmette-Guérin (BCG), diphtheria-pertussis-tetanus (DPT), and polio vaccinations, and the association between drought at 12 months of age and receipt of measles vaccination. We specified logistic regression models with survey fixed effects and standard errors clustered at the enumeration area level, adjusting for child-, mother-, and household-level covariates and estimated marginal risk differences (RDs). The prevalence of drought at date of birth in the sample was 11.8%. Vaccination rates for each vaccination ranged from 70.6% (for 3 doses of the polio vaccine) to 86.0% (for BCG vaccination); however, only 57.6% of children 12 months and older received all recommended doses of BCG, DPT, polio, and measles vaccinations. In adjusted models, drought at date of birth was negatively associated with BCG vaccination (marginal RD = -1.5; 95% CI -2.2, -0.9), DPT vaccination (marginal RD = -1.4; 95% CI -2.2, -0.5), and polio vaccination (marginal RD = -1.3; 95% CI -2.3, -0.3). Drought at 12 months was negatively associated with measles vaccination (marginal RD = -1.9; 95% CI -2.8, -0.9). We found a dose-response relationship between drought and DPT and polio vaccinations, with the strongest associations closest to the timing of drought. Limitations include some heterogeneity in findings across countries.ConclusionsIn this study, we observed that drought was associated with lower odds of completion of childhood BCG, DPT, and polio vaccinations. These findings indicate that drought may hinder vaccination coverage, one of the most important interventions to prevent infections among children. This work adds to a growing body of literature suggesting that health programs should consider impacts of severe weather in their programming.

ObjectivesTo estimate the effect of menthol use and transitions in use (switching to or from menthol) on short-term and long-term cessation from cigarette smoking and whether this differed across demographic groups (age, sex, race).MethodsWe compared the probability of 30+ day and 12-month abstinence from cigarette smoking by menthol use status using two cohorts of US adult cigarette smokers who attempted to quit smoking in the Population Assessment of Tobacco and Health (wave 1 to wave 3 and wave 2 to wave 4; n=5759), inverse probability of treatment weighting and adjusted risk ratios (aRRs).ResultsUsing menthol (vs non-menthol) prior to a quit attempt decreased the probability of 30+ day abstinence by 28% (aRR=0.78; 95% CI 0.67 to 0.91) and the probability of 12-month abstinence by 53% (aRR=0.65; 95% CI 0.47 to 0.88). Additionally, switching from menthol (vs maintaining menthol use) increased the probability of 30+ day abstinence by 58% (aRR=1.58; 95% CI 1.00 to 2.50) and the probability of 12-month abstinence by 97% (aRR=1.86; 95% CI 0.92 to 3.74). Switching to menthol (vs maintaining non-menthol use) was associated with a lower probability of 30+ day (aRR=0.70; 95% CI 0.42 to 1.16) and 12-month abstinence (aRR=0.64; 95% CI 0.30 to 1.36), but these associations were imprecise. The effects of menthol use on impaired quitting were slightly larger for non-Hispanic Black smokers, but not different for other demographic groups.ConclusionThese results demonstrate that menthol impaired menthol smokers' attempts to quit smoking but switching from menthol improved success. This suggests that removing menthol may improve menthol smokers' success during quit attempts.

This study employed novel GPS methods to assess the effect of a multilevel physical activity (PA) intervention on device-measured walking locations in 305 community dwelling older adults, ages 65+ (mean age = 83, 73% women). Retirement communities were randomized to a 1-year PA intervention that encouraged neighborhood walking, or to a healthy aging control condition. Total time and time spent walking in four life-space domains were assessed using GPS and accelerometer devices. The intervention increased the time spent walking as a proportion of total time spent in the Campus, Neighborhood and Beyond Neighborhood domains. Intervention effects on walking location were observed in both genders and across physical and cognitive functioning groups. Results demonstrate that an intervention providing individual, social and environmental support for walking can increase PA in larger life-space domains for a broad spectrum of older adults.

Active travel (AT) provides an opportunity to alleviate the physical inactivity and climate crises contributing to the global chronic disease burden, including cardiovascular diseases (CVD). Though AT shows promising links to reduced CVD risk, prior studies relied on self-reported AT assessment. In the present study, device-measured and self-reported AT were compared across population subgroups and relationships with CVD risk biomarkers were evaluated for both measures. The study recruited an ethnically diverse sample (N = 602, mean age 59 years, 42% Hispanic/Latino ethnicity) from neighborhoods that varied by walkability and food access. AT was assessed using concurrently collected accelerometer and GPS data and self-report data from a validated survey. Relationships with body mass index (BMI), triglycerides, high-density lipoprotein (HDL) cholesterol, blood pressure (BP), and moderate-to-vigorous physical activity (MVPA) were modeled using multivariable linear regression. Devices captured more AT than did self-report. We found differences in AT measures by population subgroups, including race, ethnicity, education, income, vehicle access, and walkability. Men had more accelerometer-measured MVPA, though women self-reported more daily minutes. Both device and survey AT measures were positively associated with total accelerometer-measured MVPA, though the relationship was stronger with device-measured AT. Device-measured AT was associated with lower BMI. No other CVD risk biomarker was associated with either AT measure. No effect modification by Hispanic/Latino ethnicity was detected. Further studies with device-based measures are warranted to better understand the relationship between AT and cardiovascular health.

ObjectivesTo identify predictors of becoming a daily cigarette smoker over the course of 4 years.MethodsWe identified 12- to 24-year-olds at wave 1 of the US Population Assessment of Tobacco and Health Study and determined ever use, age at first use, and daily use through wave 4 for 12 tobacco products.ResultsSixty-two percent of 12- to 24-year-olds (95% confidence interval [CI]: 60.1% to 63.2%) tried tobacco, and 30.2% (95% CI: 28.7% to 31.6%) tried ≥5 tobacco products by wave 4. At wave 4, 12% were daily tobacco users, of whom 70% were daily cigarette smokers (95% CI: 67.4% to 73.0%); daily cigarette smoking was 20.8% in 25- to 28-year-olds (95% CI: 18.9% to 22.9%), whereas daily electronic cigarette (e-cigarette) vaping was 3.3% (95% CI: 2.4% to 4.4%). Compared with single product triers, the risk of progressing to daily cigarette smoking was 15 percentage points higher (adjusted risk difference [aRD] 15%; 95% CI: 12% to 18%) among those who tried ≥5 products. In particular, e-cigarette use increased the risk of later daily cigarette smoking by threefold (3% vs 10%; aRD 7%; 95% CI: 6% to 9%). Daily smoking was 6 percentage points lower (aRD -6%; 95% CI: -8% to -4%) for those who experimented after age 18 years.ConclusionsTrying e-cigarettes and multiple other tobacco products before age 18 years is strongly associated with later daily cigarette smoking. The recent large increase in e-cigarette use will likely reverse the decline in cigarette smoking among US young adults.

BackgroundHispanics/Latinos in the United States are more likely to live in neighborhoods with greater exposure to air pollution and are projected to have the largest increase in dementia among race/ethnic minority groups.ObjectiveWe examined the associations of air pollution with performance on cognitive function tests in Hispanic/Latino adults.MethodsWe used data from the San Diego site of the Hispanic Community Health Study/Study of Latinos, an ongoing cohort of Hispanics/Latinos. This analysis focused on individuals ≥45 years of age who completed a neurocognitive battery examining overall mental status, verbal learning, memory, verbal fluency, and executive function (n = 2,089). Air pollution (PM2.5 and O3) before study baseline was assigned to participants' zip code. Logistic and linear regression were used to estimate the associations of air pollution on overall mental status and domain-specific standardized test scores. Models accounted for complex survey design, demographic, and socioeconomic characteristics.ResultsWe found that for every 10μg/m3 increase in PM2.5, verbal fluency worsened (β: -0.21 [95%CI: -0.68, 0.25]). For every 10 ppb increase in O3, verbal fluency and executive function worsened (β: -0.19 [95%CI: -0.34, -0.03]; β: -0.01 [95%CI: -0.01, 0.09], respectively). We did not identify any detrimental effect of pollutants on other domains.ConclusionAlthough we found suggestions that air pollution may impact verbal fluency and executive function, we observed no consistent or precise evidence to suggest an adverse impact of air pollution on cognitive level among this cohort of Hispanic/Latino adults.

Access to safe water and basic sanitation and hygiene facilities (WASH) are important for childhood health globally. However, inequalities in WASH access persist, and local governments need to better understand the potential impact of scaling up WASH services on childhood health. Using 2011 Peru Demographic and Health Survey data as a case study, we applied a modified substitution estimator approach to assess the impact of scaling up access (20-100%) to WASH on diarrhea prevalence among children < 5 years. The modified substitution estimator approach can help identify population subgroups or areas where WASH interventions and sustained implementation could be most beneficial and reduce existing disparities. Using findings from a recent meta-analysis and computing bootstrapped estimates and 95% CIs, we examined inequalities in the effect of WASH on self-reported diarrhea by urbanicity, maternal education level, household wealth, and district of residence. Increasing access (100% change) to improved water sources, sanitation, and hygiene facilities reduced population-level prevalence of childhood diarrhea by 8.2% (95% CI: 4.1, 12.3), 5.5% (95% CI: 0.7, 9.8), and 5.2% (95% CI: 2.2, 8.1), respectively. In stratified analyses, increased access to improved water sources and hygiene facilities was associated with decreased prevalence of diarrhea, with the largest reduction in rural areas and households with lower maternal education and lower wealth. Our findings suggest targeted WASH implementation in Peru is needed in rural areas and among lower socioeconomic-status households. In addition, even low levels of change in overall WASH access may decrease diarrhea prevalence.

Wildfire smoke harms health. We add to this literature by evaluating the health effects of California's 2018 Carr Fire and preceding wildfire seasons in Shasta County.MethodsWith data from the Shasta County Health and Human Services Agency, we examined the link between weekly wildfire fine particulate matter (PM2.5) exposure estimated using a spatiotemporal multiple imputation approach and emergency department (ED) visits and mortality using time-series models that controlled for temporal trends and temperature.ResultsBetween 2013 and 2018, Shasta County experienced 19 weeks with average wildfire PM2.5 ≥5.5 μg/m3 (hereafter, "high wildfire PM2.5 concentration"). Among all Shasta County Zip Code Tabulation Areas (ZCTAs; n = 36), we detected no association between high wildfire PM2.5 concentrations and respiratory or circulatory disease-related ED visits or mortality. Subsequent analyses were confined to valley ZCTAs (n = 11, lower elevation, majority of population, worse air quality in general). In valley ZCTAs, high wildfire PM2.5 was associated with a 14.6% (95% confidence interval [CI] = 4.2, 24.9) increase in same-week respiratory disease-related ED visits but no increase in the subsequent 2 weeks nor on circulatory disease-related mortality or ED visits or all-cause mortality. Two weeks after high wildfire PM2.5 weeks, respiratory disease-related deaths decreased (-31.5%, 95% CI = -64.4, 1.5). The 2018 Carr Fire appeared to increase respiratory disease-related ED visits by 27.0% (95% CI = 4.0, 50.0) over expectation and possibly reduce circulatory disease-related deaths (-18.2%, 95% CI = -39.4, 2.9).ConclusionsAs climate change fuels wildfire seasons, studies must continue to evaluate their health effects, particularly in highly exposed populations.

Vaping products containing cannabidiol (CBD), a cannabis-derived compound used in wellness products and available in all 50 US states, were recently implicated in outbreaks of poisonings. Little is known about the commercial availability of CBD products in vape shops (i.e., stores that sell e-cigarettes). To document the availability and marketing of CBD products in online vape shops, in June 2020, we used the Google Chrome browser without cached data to collect the first two pages of search results generated by five Google queries (n = 100 search results) indicative of shopping for vaping products (e.g., "order vapes"). We then determined whether and what type of CBD products could be mail-ordered from the returned websites, and whether any explicit health claims were made about CBD. Over a third of the search results (n = 37; 37.0%) directed to vape shops that allowed visitors to also mail-order CBD. These shops sold 12 distinct categories of CBD products-some with direct analogs of tobacco or cannabis products including CBD cigarettes, edibles, flowers, pre-rolled joints, and vapes. Two vape shops made explicit health claims of the therapeutic benefits of CBD use, including in the treatment of anxiety, inflammation, pain, and stress. The abundance and placement of CBD in online vape shops suggests a growing demand and appeal for CBD products among e-cigarette users. Additional surveillance on the epidemiology of CBD use and its co-use with tobacco is warranted.

BackgroundCalifornia Proposition 56 increased cigarette excise tax by $2 per pack with equivalent increases on non-cigarette tobacco products. We estimated the changes in cigarette price, cigarette use, and non-cigarette use following the implementation of Proposition 56 in California in 2017.MethodsSeven waves of Tobacco Use Supplements to the Current Population Survey (TUS-CPS) 2011-2019 data were used to obtain state-level aggregate self-reported outcomes, including cigarette price per pack, current and daily cigarette use, cigarette consumption per day, and current and daily use of non-cigarette tobacco products (hookah, pipe, cigar, and smokeless tobacco). A modified version of a synthetic control method was used to create a "synthetic" California that best resembled pre-policy sociodemographic characteristics and outcome trends in California while correcting time-invariant pre-policy differences. Various sensitivity analyses were also conducted.ResultsThe implementation of Proposition 56 was associated with an increase in self-reported cigarette price per pack in California ($1.844, 95%CI: $0.153, $3.534; p = 0.032). No evidence suggested that Proposition 56 was associated with the changes in the prevalence of current or daily cigarette use, cigarette consumption per day, or the prevalence of current or daily use of non-cigarette tobacco products.ConclusionMost of the cigarette tax increase following Proposition 56 in California was passed on to consumers. There is a lack of evidence that the implementation of Proposition 56 was associated with the changes in the use of cigarettes and other tobacco products such as hookah, pipe, cigar, and smokeless tobacco.

Drawing on a SARS-CoV-2 vaccine trial in a Latinx community in San Diego, we show how trial designs fail to redress structural racism and may introduce new harms. While important, trial diversity alone cannot redress entrenched inequities that affect Black, Indigenous, and People of Color (BIPOC) communities.

Wildfires are becoming more frequent and destructive in a changing climate. Fine particulate matter, PM2.5, in wildfire smoke adversely impacts human health. Recent toxicological studies suggest that wildfire particulate matter may be more toxic than equal doses of ambient PM2.5. Air quality regulations however assume that the toxicity of PM2.5 does not vary across different sources of emission. Assessing whether PM2.5 from wildfires is more or less harmful than PM2.5 from other sources is a pressing public health concern. Here, we isolate the wildfire-specific PM2.5 using a series of statistical approaches and exposure definitions. We found increases in respiratory hospitalizations ranging from 1.3 to up to 10% with a 10 μg m-3 increase in wildfire-specific PM2.5, compared to 0.67 to 1.3% associated with non-wildfire PM2.5. Our conclusions point to the need for air quality policies to consider the variability in PM2.5 impacts on human health according to the sources of emission.

Santa Ana winds (SAWs) are associated with anomalous temperatures in coastal Southern California (SoCal). As dry air flows over SoCal's coastal ranges on its way from the elevated Great Basin down to sea level, all SAWs warm adiabatically. Many but not all SAWs produce coastal heat events. The strongest regionally averaged SAWs tend to be cold. In fact, some of the hottest and coldest observed temperatures in coastal SoCal are linked to SAWs. We show that hot and cold SAWs are produced by distinct synoptic dynamics. High-amplitude anticyclonic flow around a blocking high pressure aloft anchored at the California coast produces hot SAWs. Cold SAWs result from anticyclonic Rossby wave breaking over the northwestern U.S. Hot SAWs are preceded by warming in the Great Basin and dry conditions across the Southwestern U.S. Precipitation over the Southwest, including SoCal, and snow accumulation in the Great Basin usually precede cold SAWs. Both SAW flavors, but especially the hot SAWs, yield low relative humidity at the coast. Although cold SAWs tend to be associated with the strongest winds, hot SAWs tend to last longer and preferentially favor wildfire growth. Historically, out of large (> 100 acres) SAW-spread wildfires, 90% were associated with hot SAWs, accounting for 95% of burned area. As health impacts of SAW-driven coastal fall, winter and spring heat waves and impacts of smoke from wildfires have been recently identified, our results have implications for designing early warning systems. The long-term warming trend in coastal temperatures associated with SAWs is focused on January-March, when hot and cold SAW frequency and temperature intensity have been increasing and decreasing, respectively, over our 71-year record.Supplementary informationThe online version contains supplementary material available at 10.1007/s00382-021-05802-z.