Associations between exposure to extreme ambient heat and neural tube defects in Georgia, USA: A population-based case-control study

INTRODUCTION

The association between extreme ambient heat exposures during pregnancy and neural tube defects (NTDs) in offspring remains unclear. This study sought to estimate the association between exposure to extreme ambient heat during periconception and NTDs.

METHODS

This population-based case-control study in Georgia, USA (1994-2017) included 825 isolated NTD cases (473 anencephaly, 352 spina bifida) and 3,300 controls matched 1:4 on county of residence and time period of delivery. Daily ambient temperature data were linked to fetal death and birth records by county of residence. Extreme ambient heat exposure was defined as the number of consecutive days the daily apparent temperature exceeded the county-specific 95th percentile (derived over 1980-2010) during an eight-week periconception period. We calculated adjusted odds ratios (aORs) and 95% confidence intervals (CI) using conditional logistic regression models adjusted for maternal age, education, and ethnicity and month and year of last menstrual period.

RESULTS

The aORs for NTDs were 1.09 (95% CI 1.01, 1.17), 1.18 (95% CI 1.03, 1.36), and 1.29 (95% CI 1.04, 1.58) for exposure to 1-2, 3-5, and 6 or more consecutive days with apparent ambient temperatures exceeding the county-specific 95th percentile during periconception, respectively, compared to no days of extreme ambient heat exposure. Weekly analysis of extreme heat exposure indicated consistently elevated odds of offspring NTDs during periconception. These results were largely driven by spina bifida cases.

CONCLUSIONS

Our results highlight potential health threats posed by increasing global average temperatures for pregnant people with implications for increased risk of neural tube defects in their offspring.

Joint effects of indoor air pollution and maternal psychosocial factors during pregnancy on trajectories of early childhood psychopathology

Prenatal indoor air pollution and maternal psychosocial factors have been associated with adverse psychopathology. We used environmental-exposure mixture methodology to investigate joint effects of both exposure classes on child behavior trajectories. For 360 children from the South African Drakenstein Child Health Study, we created trajectories of Child Behavior Checklist scores (at 24, 42, and 60 months) using latent-class linear mixed effects models. Indoor air pollutants and psychosocial factors were measured during pregnancy (second trimester). After adjusting for confounding, single-exposure effects (per natural log-1 unit increase) were assessed using polytomous logistic regression models, joint effects using self-organizing maps, and principal component analysis. Three trajectories were chosen for both internalizing and externalizing problems, with "high" (externalizing) or "increasing" (internalizing) being the most adverse trajectories. High externalizing trajectory was associated with increased exposure to particulate matter of ≤ 10 microns in diameter (PM10) (odds ratio [OR] = 1.25; 95% CI, 1.01-1.55) and self-organizing maps exposure profile most associated with smoking (OR = 2.67; 95% CI, 1.14-6.27). Medium internalizing trajectory was associated with increased emotional intimate partner violence (OR = 2.66; 95% CI, 1.17-5.57), increasing trajectory with increased benzene (OR = 1.24; 95% CI, 1.02-1.51) and toluene (1.21; 95% CI, 1.02-1.44) and the principal component most correlated with benzene and toluene (OR = 1.25; 95% CI, 1.02-1.54). Prenatal exposure to environmental pollutants and psychosocial factors was associated with internalizing and externalizing child behavior trajectories. Understanding joint effects of adverse exposure mixtures will facilitate targeted interventions to prevent childhood psychopathology. This article is part of a Special Collection on Mental Health.

Dust storms and cardiorespiratory emergency department visits in three Southwestern United States: application of a monitoring-based exposure metric

Climate change is projected to increase the risk of dust storms, particularly in subtropical dryland, including the southwestern US. Research on dust storm's health impacts in the US is limited and hindered by challenges in dust storm identification. This study assesses the potential link between dust storms and cardiorespiratory emergency department (ED) visits in the southwestern US. We acquired data for 2005-2016 from eight IMPROVE (Interagency Monitoring of PROtected Visual Environments) sites in Arizona, California, and Utah. We applied a validated algorithm to identify dust storm days at each site. We acquired patient-level ED visit data from state agencies and ascertained visits for respiratory, cardiovascular, and cause-specific subgroups among patients residing in ZIP codes within 50 km of an IMPROVE site. Using a case-crossover design, we estimated short-term associations of ED visits and dust storms, controlling for temporally varying covariates. During 2005-2016, 40 dust storm days occurred at the eight IMPROVE sites. Mean PM10 and PM2.5 levels were three to six times greater on dust storm days compared to non-dust storm days. Over the study period, there were 2 524 259 respiratory and 2 805 925 cardiovascular ED visits. At lags of 1, 2, and 3 days after a dust storm, we observed 3.7% (95% CI: 1.0%, 7.6%), 4.9% (95% CI: 1.1%, 8.9%), and 5.0% (95% CI: 1.3%, 8.9%) elevated odds of respiratory ED visits compared to non-dust storm days. Estimated associations of dust storm days and cardiovascular disease ED visits were largely consistent with the null. Using a monitoring-based exposure metric, we observed associations among dust storms and respiratory ED visits. The results add to growing evidence of the health threat posed by dust storms. The dust storm metric was limited by lack of daily data; future research should consider information from satellite and numerical models to enhance dust storm characterization.

Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

Association of household air pollution exposure and anemia among pregnant women: Analysis of baseline data from 'Household Air Pollution Intervention Network (HAPIN)' trial

BACKGROUND

Anemia is common in low- and middle-income countries (LMICs), causing significant health issues and social burdens. Exposure to household air pollution from using biomass fuels for cooking and heating has been associated with anemia, but the exposure-response association has not been studied.

OBJECTIVES

We evaluated the associations between personal exposure to air pollution and both hemoglobin levels and anemia prevalence among pregnant women in a multi-country randomized controlled trial.

METHODS

We studied 3,163 pregnant women aged 18-35 years with 9-20 weeks of gestation, recruited as part of the Household Air Pollution Intervention Network (HAPIN) randomized controlled trial in Guatemala, India, Peru, and Rwanda. We assessed 24-hour personal exposures to fine particulate matter (PM2.5), black carbon (BC), and carbon monoxide (CO), and measured hemoglobin levels at baseline (15 ± 3 weeks gestation). Linear and logistic regression models were used to examine the associations of measured pollutants with hemoglobin levels and anemia prevalence, adjusting for confounding.

RESULTS

Single-pollutant models showed associations of CO with higher hemoglobin levels and lower anemia prevalence. Bipollutant models involving CO and PM2.5 also revealed that an interquartile range (IQR) increase in CO concentrations (2.26 ppm) was associated with higher hemoglobin levels [β = 0.04; 95 % confidence interval (CI): 0.01, 0.07], and a lower odds of anemia prevalence [odds ratios (OR) = 0.90; 95 % CI: 0.83, 0.98]. PM2.5 was inversely related to hemoglobin and positively associated with anemia, but results were not statistically significant at the 0.05 alpha level. County-specific results showed that 3 of 4 countries showed a similar association between CO and hemoglobin. We found no association of BC levels with hemoglobin levels or with anemia prevalence.

CONCLUSION

Our findings suggest that exposure to CO is associated with higher hemoglobin and lower anemia prevalence among pregnant women, whereas PM2.5 showed the opposite associations.

Joint effects of prenatal exposure to indoor air pollution and psychosocial factors on early life inflammation

It is hypothesized that air pollution and stress impact the central nervous system through neuroinflammatory pathways Despite this, the association between prenatal exposure to indoor air pollution and psychosocial factors on inflammatory markers in infancy has been underexplored in epidemiology studies. This study investigates the individual and joint effects of prenatal exposure to indoor air pollution and psychosocial factors on early life inflammation (interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α)). We analyzed data from the South African Drakenstein Child Health Study (N = 225). Indoor air pollution and psychosocial factor measurements were taken in the 2nd trimester of pregnancy. Circulating inflammatory markers (IL-1β, Il-6, and TNF-α) were measured in serum in the infants at 6 weeks postnatal. Linear regression models were used to investigate associations between individual exposures and inflammatory markers. To investigate joint effects of environmental and psychosocial factors, Self-Organizing Maps (SOM) were used to create exposure profile clusters. These clusters were added to linear regression models to investigate the associations between exposure profiles and inflammatory markers. All models were adjusted for maternal age, maternal HIV status, and ancestry to control for confounding. Most indoor air pollutants were positively associated with inflammatory markers, particularly benzene and TNF-α in single pollutant models. No consistent patterns were found for psychosocial factors in single-exposure linear regression models. In joint effects analyses, the SOM profile with high indoor air pollution, low SES, and high maternal depressive symptoms were associated with higher inflammation. Indoor air pollutants were consistently associated with increased inflammation in both individual and joint effects models, particularly in combination with low SES and maternal depressive symptoms. The trend for individual psychosocial factors was not as clear, with mainly null associations. As we have observed pro- and anti-inflammatory effects, future research should investigate joint effects of these exposures on inflammation and their health effects.

Person-centered hospital discharge data: Essential existing infrastructure to enhance public health surveillance of maternal substance use disorders in the midst of a national maternal overdose crisis

OBJECTIVES

As crises of drug-related maternal harms escalate, US public health surveillance capacity remains suboptimal for drug-related maternal morbidities. Most state hospital discharge databases (HDDs) are encounter-based, and thus limit ascertainment of morbidities to delivery visits and ignoring those occurring during the 21 months spanning pregnancy and postpartum year. This study analyzes data from a state that curates person-centered HDD to compare patterns of substance use disorder (SUD) diagnoses at delivery vs. the full 21 pregnancy/postpartum months, overall and by maternal social position.

METHODS

Among people who experienced an in-hospital birth in New York State between 9/1/2016 and 1/1/2018 (N = 330,872), we estimated SUD diagnosis (e.g., opioids, stimulants, benzodiazepines, cannabis) prevalence at delivery; across the full 9 months of pregnancy and 12 postpartum months; and by trimester and postpartum quarter. Risk ratio and risk difference estimated disparities by race/ethnicity, age, rurality, and payor.

RESULTS

The 21-month SUD prevalence rate per 100,000 was 2671 (95% CI 2616-2726), with 31% (29.5%-31.5%) missing SUD indication when ascertained at delivery only (1866; 95% CI 1820-1912). Quarterly rates followed a roughly J-shaped trajectory. Structurally marginalized individuals suffered the highest 21-month SUD prevalence (e.g., Black:White risk ratio=1.80 [CI:1.73-1.88]).

CONCLUSION

By spanning the full 21 months of pregnancy/postpartum, person-centered HDD reveal than the maternal SUD crisis is far greater than encounter-based delivery estimates had revealed. Generating person-centered HDD will improve efforts to tailor interventions to help people who use drugs survive while pregnant and postpartum, and eliminate inequities.

Impact of randomly assigned "pay-as-you-go" liquefied petroleum gas prices on energy use for cooking: Experimental pilot evidence from rural Rwanda

The disease burden related to air pollution from traditional solid-fuel cooking practices in low- and middle-income countries impacts millions of people globally. Although the use of liquefied petroleum gas (LPG) fuel for cooking can meaningfully reduce household air pollution concentrations, major barriers, including affordability and accessibility, have limited widespread adoption. Using a randomized controlled trial, our objective was to evaluate the association between the cost and use of LPG among 23 rural Rwandan households. We provided a 2-burner LPG stove with accessories and incorporated a "pay-as-you-go" (PAYG) LPG service model that included fuel delivery. PAYG services remove the large up-front cost of cylinder refills by integrating "smart meter" technology that allows participants to pay in incremental amounts, as needed. We assigned three randomized discounted prices for LPG to each household at ~4-week intervals over a 12-week period. We modeled the relationship between randomized PAYG LPG price and use (standardized to monthly periods), analyzing effect modification by relative household wealth. A 1000 Rwandan Franc (about 1 USD at the time of the study) increase in LPG price/kg was associated with a 4.1 kg/month decrease in use (95% confidence interval [CI]: -6.7, -1.6; n=69 observations). Wealth modified this association; we observed a 9.7 kg/month reduction (95% CI: -14.8, -4.5) among wealthier households and a 2.5 kg/month reduction (95% CI: -5.3, 0.3) among lower-wealth households (p-interaction=0.01). The difference in price sensitivity was driven by higher LPG use among wealthier households at more heavily discounted prices; from an 80% to 10% discount, wealthy households used 17.5 to 5.3 kg/month and less wealthy households used 6.2 to 3.1 kg/month. Our pilot-level experimental evidence of PAYG LPG in a rural low-resource setting suggests that further exploration of subsidized pricing varied by household wealth is needed to ensure future policy initiatives can achieve targets without exacerbating inequities.

Preterm and Early-Term Delivery After Heat Waves in 50 US Metropolitan Areas

Importance

Heat waves are increasing in frequency, intensity, and duration and may be acutely associated with pregnancy outcomes.

Objective

To examine changes in daily rates of preterm and early-term birth after heat waves in a 25-year nationwide study.

Design, Setting, and Participants

This cohort study of singleton births used birth records from 1993 to 2017 from the 50 most populous US metropolitan statistical areas (MSAs). The study included 53 million births, covering 52.8% of US births over the period. Data were analyzed between October 2022 and March 2023 at the National Center for Health Statistics.

Exposures

Daily temperature data from Daymet at 1-km2 resolution were averaged over each MSA using population weighting. Heat waves were defined in the 4 days (lag, 0-3 days) or 7 days (lag, 0-6 days) preceding birth.

Main Outcomes and Measures

Daily counts of preterm birth (28 to <37 weeks), early-term birth (37 to <39 weeks), and ongoing pregnancies in each gestational week on each day were enumerated in each MSA. Rate ratios for heat wave metrics were obtained from time-series models restricted to the warm season (May to September) adjusting for MSA, year, day of season, and day of week, and offset by pregnancies at risk.

Results

There were 53 154 816 eligible births in the 50 MSAs from 1993 to 2017; 2 153 609 preterm births and 5 795 313 early-term births occurring in the warm season were analyzed. A total of 30.0% of mothers were younger than 25 years, 53.8% were 25 to 34 years, and 16.3% were 35 years or older. Heat waves were positively associated with daily rates of preterm and early-term births, showing a dose-response association with heat wave duration and temperatures and stronger associations in the more acute 4-day window. After 4 consecutive days of mean temperatures exceeding the local 97.5th percentile, the rate ratio for preterm birth was 1.02 (95% CI, 1.00-1.03), and the rate ratio for early-term birth was 1.01 (95% CI, 1.01-1.02). For the same exposure, among those who were 29 years of age or younger, had a high school education or less, and belonged to a racial or ethnic minority group, the rate ratios were 1.04 (95% CI, 1.02-1.06) for preterm birth and 1.03 (95% CI, 1.02-1.05) for early-term birth. Results were robust to alternative heat wave definitions, excluding medically induced deliveries, and alternative statistical model specifications.

Conclusions and Relevance

In this cohort study, preterm and early-term birth rates increased after heat waves, particularly among socioeconomically disadvantaged subgroups. Extreme heat events have implications for perinatal health.

Natural History of Type 2 Diabetes in Indians: Time to Progression

OBJECTIVE

To describe the natural history of diabetes in Indians.

RESEARCH DESIGN AND METHODS

Data are from participants older than 20 years in the Centre for Cardiometabolic Risk Reduction in South Asia longitudinal study. Glycemic states were defined per American Diabetes Association criteria. Markov models were used to estimate annual transition probabilities and sojourn time through states.

RESULTS

Among 2,714 diabetes-free participants, 641 had isolated impaired fasting glucose (iIFG), and 341 had impaired glucose tolerance (IGT). The annual transition to diabetes for those with IGT was 13.9% (95% CI 12.0, 15.9) versus 8.6% (7.3, 9.8) for iIFG. In the normoglycemia ↔ iIFG → diabetes model, mean sojourn time in normoglycemia was 40.3 (34.6, 48.2) years, and sojourn time in iIFG was 9.7 (8.4, 11.4) years. For the normoglycemia ↔ IGT → diabetes model, mean sojourn time in normoglycemia was 34.5 (29.5, 40.8) years, and sojourn time in IGT was 6.1 (5.3, 7.1) years.

CONCLUSIONS

Individuals reside in normoglycemia for 35-40 years; however, progression from prediabetes to diabetes is rapid.

Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM2.5 exposure and cardiovascular emergency department visits in Missouri

INTRODUCTION

Ambient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures of socioeconomic position (SEP) modify the relationship between PM2.5 exposure and CVDM in Missouri at the census-tract (CT) level.

METHODS

We use individual level Missouri emergency department (ED) admissions data (n=3 284 956), modelled PM2.5 data, and yearly CT data from 2012 to 2016 to conduct a two-stage analysis. Stage one uses a case-crossover approach with conditional logistic regression to establish the baseline risk of ED visits associated with IQR changes in PM2.5. In the second stage, we use multivariate metaregression to examine how CT-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM.

RESULTS

We find that overall, ambient PM2.5 exposure is associated with increased risk for CVDM. We test effect modification in statewide and urban CTs, and in the warm season only. Effect modification results suggest that among SEP measures, poverty is most consistently associated with increased risk for CVDM. For example, across Missouri, the highest poverty CTs are at an elevated risk for CVDM (OR=1.010 (95% CI 1.007 to 1.014)) compared with the lowest poverty CTs (OR=1.004 (95% CI 1.000 to 1.008)). Other SEP modifiers generally display an inconsistent or null effect.

CONCLUSION

Overall, we find some evidence that area-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM, and suggest that the relationship between air-pollution, area-level SEP and CVDM may be sensitive to spatial scale.

Associations of pollen and cardiovascular disease morbidity in Atlanta during 1993-2018

Background

Pollen exposure is associated with substantial respiratory morbidity, but its potential impact on cardiovascular disease (CVD) remains less understood. This study aimed to investigate the associations between daily levels of 13 pollen types and emergency department (ED) visits for eight CVD outcomes over a 26-year period in Atlanta, GA.

Methods

We acquired pollen data from Atlanta Allergy & Asthma, a nationally certified pollen counting station, and ED visit data from individual hospitals and the Georgia Hospital Association. We performed time-series analyses using quasi-Poisson distributed lag models, with primary analyses assessing 3-day (lag 0-2 days) pollen levels. Models controlled for temporally varying covariates, including air pollutants.

Results

During 1993-2018, there were 1,573,968 CVD ED visits. Most pairwise models of the 13 pollen types and eight CVD outcomes showed no association, with a few exceptions potentially due to chance.

Conclusion

We found limited evidence of the impact of pollen on cardiovascular morbidity in Atlanta. Further study on pollen exposures in different climactic zones and exploration of pollen-pollution mixture effects is warranted.

Effects of a liquefied petroleum gas stove intervention on stillbirth, congenital anomalies and neonatal mortality: A multi-country household air pollution intervention network trial

Household air pollution (HAP) from cooking with solid fuels used during pregnancy has been associated with adverse pregnancy outcomes. The Household Air Pollution Intervention Network (HAPIN) trial was a randomized controlled trial that assessed the impact of a liquefied petroleum gas (LPG) stove and fuel intervention on health in Guatemala, India, Peru, and Rwanda. Here we investigated the effects of the LPG stove and fuel intervention on stillbirth, congenital anomalies and neonatal mortality and characterized exposure-response relationships between personal exposures to fine particulate matter (PM2.5), black carbon (BC) and carbon monoxide (CO) and these outcomes. Pregnant women (18 to <35 years of age; gestation confirmed by ultrasound at 9 to <20 weeks) were randomly assigned to intervention or control arms. We monitored these fetal and neonatal outcomes and personal exposure to PM2.5, BC and CO three times during pregnancy, we conducted intention-to-treat (ITT) and exposure-response (E-R) analyses to determine if the HAPIN intervention and corresponding HAP exposure was associated with the risk of fetal/neonatal outcomes. A total of 3200 women (mean age 25.4 ± 4.4 years, mean gestational age at randomization 15.4 ± 3.1 weeks) were included in this analysis. Relative risks for stillbirth, congenital anomaly and neonatal mortality were 0.99 (0.60, 1.66), 0.92 (95 % CI 0.52, 1.61), and 0.99 (0.54, 1.85), respectively, among women in the intervention arm compared to controls in an ITT analysis. Higher mean personal exposures to PM2.5, CO and BC during pregnancy were associated with a higher, but statistically non-significant, incidence of adverse outcomes. The LPG stove and fuel intervention did not reduce the risk of these outcomes nor did we find evidence supporting an association between personal exposures to HAP and stillbirth, congenital anomalies and neonatal mortality.

Evaluating bias with loss to follow-up in a community-based cohort: empirical investigation from the CARRS Study

BACKGROUND

Retention of participants is a challenge in community-based longitudinal cohort studies. We aim to evaluate the factors associated with loss to follow-up and estimate attrition bias.

METHODS

Data are from an ongoing cohort study, Center for cArdiometabolic Risk Reduction in South Asia (CARRS) in India (Delhi and Chennai). Multinomial logistic regression analysis was used to identify sociodemographic factors associated with partial (at least one follow-up) or no follow-up (loss to follow-up). We also examined the impact of participant attrition on the magnitude of observed associations using relative ORs (RORs) of hypertension and diabetes (prevalent cases) with baseline sociodemographic factors.

RESULTS

There were 12 270 CARRS cohort members enrolled in Chennai and Delhi at baseline in 2010, and subsequently six follow-ups were conducted between 2011 and 2022. The median follow-up time was 9.5 years (IQR: 9.3-9.8) and 1048 deaths occurred. Approximately 3.1% of participants had no follow-up after the baseline visit. Younger (relative risk ratio (RRR): 1.14; 1.04 to 1.24), unmarried participants (RRR: 1.75; 1.45 to 2.11) and those with low household assets (RRR: 1.63; 1.44 to 1.85) had higher odds of being lost to follow-up. The RORs of sociodemographic factors with diabetes and hypertension did not statistically differ between baseline and sixth follow-up, suggesting minimal potential for bias in inference at follow-up.

CONCLUSION

In this representative cohort of urban Indians, we found low attrition and minimal bias due to the loss to follow-up. Our cohort's inconsistent participation bias shows our retention strategies like open communication, providing health profiles, etc have potential benefits.

A scalar-on-quantile-function approach for estimating short-term health effects of environmental exposures

Environmental epidemiologic studies routinely utilize aggregate health outcomes to estimate effects of short-term (eg, daily) exposures that are available at increasingly fine spatial resolutions. However, areal averages are typically used to derive population-level exposure, which cannot capture the spatial variation and individual heterogeneity in exposures that may occur within the spatial and temporal unit of interest (eg, within a day or ZIP code). We propose a general modeling approach to incorporate within-unit exposure heterogeneity in health analyses via exposure quantile functions. Furthermore, by viewing the exposure quantile function as a functional covariate, our approach provides additional flexibility in characterizing associations at different quantile levels. We apply the proposed approach to an analysis of air pollution and emergency department (ED) visits in Atlanta over 4 years. The analysis utilizes daily ZIP code-level distributions of personal exposures to 4 traffic-related ambient air pollutants simulated from the Stochastic Human Exposure and Dose Simulator. Our analyses find that effects of carbon monoxide on respiratory and cardiovascular disease ED visits are more pronounced with changes in lower quantiles of the population's exposure. Software for implement is provided in the R package nbRegQF.

Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period

BACKGROUND

Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD.

METHODS

For the period of 1993-2019, we analyzed over 12 million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade.

RESULTS

All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes.

CONCLUSIONS

Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.

Liquefied Petroleum Gas or Biomass Cooking and Severe Infant Pneumonia

BACKGROUND

Exposure to household air pollution is a risk factor for severe pneumonia. The effect of replacing biomass cookstoves with liquefied petroleum gas (LPG) cookstoves on the incidence of severe infant pneumonia is uncertain.

METHODS

We conducted a randomized, controlled trial involving pregnant women 18 to 34 years of age and between 9 to less than 20 weeks' gestation in India, Guatemala, Peru, and Rwanda from May 2018 through September 2021. The women were assigned to cook with unvented LPG stoves and fuel (intervention group) or to continue cooking with biomass fuel (control group). In each trial group, we monitored adherence to the use of the assigned cookstove and measured 24-hour personal exposure to fine particulate matter (particles with an aerodynamic diameter of ≤2.5 μm [PM2.5]) in the women and their offspring. The trial had four primary outcomes; the primary outcome for which data are presented in the current report was severe pneumonia in the first year of life, as identified through facility surveillance or on verbal autopsy.

RESULTS

Among 3200 pregnant women who had undergone randomization, 3195 remained eligible and gave birth to 3061 infants (1536 in the intervention group and 1525 in the control group). High uptake of the intervention led to a reduction in personal exposure to PM2.5 among the children, with a median exposure of 24.2 μg per cubic meter (interquartile range, 17.8 to 36.4) in the intervention group and 66.0 μg per cubic meter (interquartile range, 35.2 to 132.0) in the control group. A total of 175 episodes of severe pneumonia were identified during the first year of life, with an incidence of 5.67 cases per 100 child-years (95% confidence interval [CI], 4.55 to 7.07) in the intervention group and 6.06 cases per 100 child-years (95% CI, 4.81 to 7.62) in the control group (incidence rate ratio, 0.96; 98.75% CI, 0.64 to 1.44; P = 0.81). No severe adverse events were reported to be associated with the intervention, as determined by the trial investigators.

CONCLUSIONS

The incidence of severe pneumonia among infants did not differ significantly between those whose mothers were assigned to cook with LPG stoves and fuel and those whose mothers were assigned to continue cooking with biomass stoves. (Funded by the National Institutes of Health and the Bill and Melinda Gates Foundation; HAPIN ClinicalTrials.gov number, NCT02944682.).

Effects of Cooking with Liquefied Petroleum Gas or Biomass on Stunting in Infants

BACKGROUND

Household air pollution is associated with stunted growth in infants. Whether the replacement of biomass fuel (e.g., wood, dung, or agricultural crop waste) with liquefied petroleum gas (LPG) for cooking can reduce the risk of stunting is unknown.

METHODS

We conducted a randomized trial involving 3200 pregnant women 18 to 34 years of age in four low- and middle-income countries. Women at 9 to less than 20 weeks' gestation were randomly assigned to use a free LPG cookstove with continuous free fuel delivery for 18 months (intervention group) or to continue using a biomass cookstove (control group). The length of each infant was measured at 12 months of age, and personal exposures to fine particulate matter (particles with an aerodynamic diameter of ≤2.5 μm) were monitored starting at pregnancy and continuing until the infants were 1 year of age. The primary outcome for which data are presented in the current report - stunting (defined as a length-for-age z score that was more than two standard deviations below the median of a growth standard) at 12 months of age - was one of four primary outcomes of the trial. Intention-to-treat analyses were performed to estimate the relative risk of stunting.

RESULTS

Adherence to the intervention was high, and the intervention resulted in lower prenatal and postnatal 24-hour personal exposures to fine particulate matter than the control (mean prenatal exposure, 35.0 μg per cubic meter vs. 103.3 μg per cubic meter; mean postnatal exposure, 37.9 μg per cubic meter vs. 109.2 μg per cubic meter). Among 3061 live births, 1171 (76.2%) of the 1536 infants born to women in the intervention group and 1186 (77.8%) of the 1525 infants born to women in the control group had a valid length measurement at 12 months of age. Stunting occurred in 321 of the 1171 infants included in the analysis (27.4%) of the infants born to women in the intervention group and in 299 of the 1186 infants included in the analysis (25.2%) of those born to women in the control group (relative risk, 1.10; 98.75% confidence interval, 0.94 to 1.29; P = 0.12).

CONCLUSIONS

An intervention strategy starting in pregnancy and aimed at mitigating household air pollution by replacing biomass fuel with LPG for cooking did not reduce the risk of stunting in infants. (Funded by the National Institutes of Health and the Bill and Melinda Gates Foundation; HAPIN ClinicalTrials.gov number, NCT02944682.).

Ambient traffic related air pollution in relation to ovarian reserve and oocyte quality in young, healthy oocyte donors

Studies in mice and older, subfertile women have found that air pollution exposure may compromise female reproduction. Our objective was to evaluate the effects of air pollution on ovarian reserve and outcomes of ovarian stimulation among young, healthy females. We included 472 oocyte donors who underwent 781 ovarian stimulation cycles at a fertility clinic in Atlanta, Georgia, USA (2008-2019). Antral follicle count (AFC) was assessed with transvaginal ultrasonography and total and mature oocyte count was assessed following oocyte retrieval. Ovarian sensitivity index (OSI) was calculated as the total number of oocytes divided by total gonadotrophin dose × 1000. Daily ambient exposure to nitric oxide (NOx), carbon monoxide (CO), and particulate matter ≤ 2.5 (PM2.5) was estimated using a fused regional + line-source model for near-surface releases at a 250 m resolution based on residential address. Generalized estimating equations were used to evaluate the associations of an interquartile range (IQR) increase in pollutant exposure with outcomes adjusted for donor characteristics, census-level poverty, and meteorological factors. The median (IQR) age among oocyte donors was 25.0 (5.0) years, and 31% of the donors were racial/ethnic minorities. The median (IQR) exposure to NOx, CO, and PM2.5 in the 3 months prior to stimulation was 37.7 (32.0) ppb, 612 (317) ppb, and 9.8 (2.9) µg/m3, respectively. Ambient air pollution exposure in the 3 months before AFC was not associated with AFC. An IQR increase in PM2.5 in the 3 months before AFC and during stimulation was associated with -7.5% (95% CI -14.1, -0.4) and -6.4% (95% CI -11.0, -1.6) fewer mature oocytes, and a -1.9 (95% CI -3.2, -0.5) and -1.0 (95% CI -1.8, -0.2) lower OSI, respectively. Our results suggest that lowering the current 24-h PM2.5 standard in the US to 25 µg/m3 may still not adequately protect against the reprotoxic effects of short-term PM2.5 exposure.

A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth

Studies of the relationships between environmental exposures and adverse health outcomes often rely on a two-stage statistical modeling approach, where exposure is modeled/predicted in the first stage and used as input to a separately fit health outcome analysis in the second stage. Uncertainty in these predictions is frequently ignored, or accounted for in an overly simplistic manner when estimating the associations of interest. Working in the Bayesian setting, we propose a flexible kernel density estimation (KDE) approach for fully utilizing posterior output from the first stage modeling/prediction to make accurate inference on the association between exposure and health in the second stage, derive the full conditional distributions needed for efficient model fitting, detail its connections with existing approaches, and compare its performance through simulation. Our KDE approach is shown to generally have improved performance across several settings and model comparison metrics. Using competing approaches, we investigate the association between lagged daily ambient fine particulate matter levels and stillbirth counts in New Jersey (2011-2015), observing an increase in risk with elevated exposure 3 days prior to delivery. The newly developed methods are available in the R package KDExp.

Effects of air pollution on adverse birth outcomes and pregnancy complications in the U.S. state of Kansas (2000-2015)

Neonatal mortality and morbidity are often caused by preterm birth and lower birth weight. Gestational diabetes mellitus (GDM) and gestational hypertension (GH) are the most prevalent maternal medical complications during pregnancy. However, evidence on effects of air pollution on adverse birth outcomes and pregnancy complications is mixed. Singleton live births conceived between January 1st, 2000, and December 31st, 2015, and reached at least 27 weeks of pregnancy in Kansas were included in the study. Trimester-specific and total pregnancy exposures to nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), and ozone (O3) were estimated using spatiotemporal ensemble models and assigned to maternal residential census tracts. Logistic regression, discrete-time survival, and linear models were applied to assess the associations. After adjustment for demographics and socio-economic status (SES) factors, we found increases in the second and third trimesters and total pregnancy O3 exposures were significantly linked to preterm birth. Exposure to the second and third trimesters O3 was significantly associated with lower birth weight, and exposure to NO2 during the first trimester was linked to an increased risk of GDM. O3 exposures in the first trimester were connected to an elevated risk of GH. We didn't observe consistent associations between adverse pregnancy and birth outcomes with PM2.5 exposure. Our findings indicate there is a positive link between increased O3 exposure during pregnancy and a higher risk of preterm birth, GH, and decreased birth weight. Our work supports limiting population exposure to air pollution, which may lower the likelihood of adverse birth and pregnancy outcomes.

Association between outdoor temperature and fatal police shootings in the United States, 2015-2021

Background

Here, we investigate the association between outdoor temperature and fatal police shootings in the United States between 2015 and 2021.

Methods

We conducted a time-stratified case-crossover study. Data on fatal police shootings were from the Washington Post's Fatal Force database and temperature data were from Daymet.

Results

A 5°C increase in maximum same-day temperature was associated with a 1.033 (95% CI = 1.002, 1.065) increased odds of a fatal police shooting. In stratified analyses, the strongest associations were observed in victims who were armed (OR, 1.052 [95% CI = 1.017, 1.088), White (OR, 1.052 [95% CI = 1.006, 1.100), or aged 45+ (OR, 1.110 [95% CI = 1.044, 1.181]). In additional subgroup analyses, relative risks were also generally higher among those who were armed.

Conclusions

There is evidence of an association between outdoor temperature and fatal police shootings in the United States, particularly when the victims were reported as armed. This study cannot determine if the associations are a result of any specific causes (e.g., increased police aggression or other factors).

Evidence Synthesis of Observational Studies in Environmental Health: Lessons Learned from a Systematic Review on Traffic-Related Air Pollution

BACKGROUND

There is a long tradition in environmental health of using frameworks for evidence synthesis, such as those of the U.S. Environmental Protection Agency for its Integrated Science Assessments and the International Agency for Research on Cancer Monographs. The framework, Grading of Recommendations Assessment, Development, and Evaluation (GRADE), was developed for evidence synthesis in clinical medicine. The U.S. Office of Health Assessment and Translation (OHAT) elaborated an approach for evidence synthesis in environmental health building on GRADE.

METHODS

We applied a modified OHAT approach and a broader "narrative" assessment to assess the level of confidence in a large systematic review on traffic-related air pollution and health outcomes.

DISCUSSION

We discuss several challenges with the OHAT approach and its implementation and suggest improvements for synthesizing evidence from observational studies in environmental health. We consider the determination of confidence using a formal rating scheme of up- and downgrading of certain factors, the treatment of every factor as equally important, and the lower initial confidence rating of observational studies to be fundamental issues in the OHAT approach. We argue that some observational studies can offer high-confidence evidence in environmental health. We note that heterogeneity in magnitude of effect estimates should generally not weaken the confidence in the evidence, and consistency of associations across study designs, populations, and exposure assessment methods may strengthen confidence in the evidence. We mention that publication bias should be explored beyond statistical methods and is likely limited when large and collaborative studies comprise most of the evidence and when accrued over several decades. We propose to identify possible key biases, their most likely direction, and their potential impacts on the results. We think that the OHAT approach and other GRADE-type frameworks require substantial modification to align better with features of environmental health questions and the studies that address them. We emphasize that a broader, "narrative" evidence assessment based on the systematic review may complement a formal GRADE-type evaluation. https://doi.org/10.1289/EHP11532.

Associations between short-term ambient temperature exposure and emergency department visits for amphetamine, cocaine, and opioid use in California from 2005 to 2019

Substance use disorder is a growing public health challenge in the United States. People who use drugs may be more vulnerable to ambient heat due to the effects of drugs on thermoregulation and their risk environment. There have been limited population-based studies of ambient temperature and drug-related morbidity. We examined short-term associations between daily ambient temperature and emergency department (ED) visits for use or overdose of amphetamine, cocaine and opioids in California during the period 2005 to 2019. Daily ZIP code-level maximum, mean, and minimum temperature exposures were derived from 1-km data Daymet products. A time-stratified case-crossover design was used to estimate cumulative non-linear associations of daily temperature for lag days 0 to 3. Stratified analyses by patient sex, race, and ethnicity were also conducted. The study included over 3.4 million drug-related ED visits. We found positive associations between daily temperature and ED visits for all outcomes examined. An increase in daily mean temperature from the 50th to the 95th percentile was associated with ED visits for amphetamine use (OR = 1.072, 95% CI: 1.058, 1.086), cocaine use (OR = 1.044, 95% CI: 1.021, 1.068 and opioid use (OR = 1.041, 95% CI: 1.025, 1.057). Stronger positive associations were also observed for overdose: amphetamine overdose (OR = 1.150, 95% CI: 1.085, 1.218), cocaine overdose (OR = 1.159, 95% CI: 1.053, 1.276), and opioid overdose (OR = 1.079, 95% CI: 1.054, 1.106). In summary, people who use stimulants and opioids may be a subpopulation sensitive to short-term higher ambient temperature. Mitigating heat exposure can be considered in harm reduction strategies in response to the substance use epidemic and global climate change.