Identifying predictors of personal exposure to air temperature in peri-urban India

Modelling personal temperature exposure using household and outdoor temperature and questionnaire data: Implications for epidemiological studies

Non-optimal temperature is a leading risk factor for global disease burden. Most epidemiological studies assessed only outdoor temperature, with important uncertainties on personal exposure misclassification. The CKB-Air study measured personal, household (kitchen and living room), and outdoor temperatures in the summer (MAY-SEP 2017) and winter (NOV 2017-JAN 2018) in 477 participants in China. After data cleaning, ∼88,000 person-hours of data were recorded across each microenvironment. Using multivariable linear regression (MLR) and random forest (RF) models, we identified key predictors and constructed personal temperature exposure prediction models. We used generalised additive mixed effect models to examine the relationships of personal and outdoor temperatures with heart rate. The 24-hour mean (SD) personal and outdoor temperatures were 29.2 (3.8) °C and 27.6 (6.4) °C in summer, and 12.0 (4.0) °C and 7.5 (4.2) °C in winter, respectively. The temperatures across microenvironments were strongly correlated (Spearman's ρ: 0.86-0.92) in summer. In winter, personal temperature was strongly related to household temperatures (ρ: 0.74-0.79) but poorly related to outdoor temperature (ρ: 0.30). RF algorithm identified household and outdoor temperatures and study date as top predictors of personal temperature exposure for both seasons, and heating-related factors were important in winter. The final MLR and RF models incorporating questionnaire and device data performed satisfactorily in predicting personal exposure in both seasons (R2summer: 0.92; R2winter: 0.68-0.70). We found consistent U-shaped associations between measured and predicted personal temperature exposures and heart rate (lowest at ∼ 14.5 °C), but a weak positive linear association with outdoor temperature. Personal and outdoor temperatures differ substantially winter, but prediction models incorporating household and outdoor temperatures and questionnaire data performed satisfactorily. Exposure misclassification from using outdoor temperature may produce inappropriate epidemiological findings.

Heat Exposure among Adult Women in Rural Tamil Nadu, India

Exposure to heat is associated with a substantial burden of disease and is an emerging issue in the context of climate change. Heat is of particular concern in India, which is one of the world's hottest countries and also most populous, where relatively little is known about personal heat exposure, particularly in rural areas. Here, we leverage data collected as part of a randomized controlled trial to describe personal temperature exposures of adult women (40-79 years of age) in rural Tamil Nadu. We also characterize measurement error in heat exposure assessment by comparing personal exposure measurements to the nearest ambient monitoring stations and to commonly used modeled temperature data products. We find that temperatures differ across individuals in the same area on the same day, sometimes by more than 5 °C within the same hour, and that some individuals experience sharp increases in heat exposure in the early morning or evening, potentially a result of cooking with solid fuels. We find somewhat stronger correlations between the personal exposure measurements and the modeled products than with ambient monitors. We did not find evidence of systematic biases, which indicates that adjusting for discrepancies between different exposure measurement methods is not straightforward.

Reduction of household air pollution through clean fuel intervention and recovery of cellular immune balance

BACKGROUND

We conducted a clean fuel intervention trial (Bangladesh Global Environmental and Occupational Health (GEOHealth) (NCT02824237) with liquefied petroleum gas (LPG) for 26 months among rural Bangladeshi women chronically exposed to household air pollution (HAP) from biomass fuel (BMF) use. We aimed to evaluate the effect of HAP reduction following LPG intervention on immune response outcome.

METHODS

We supplied LPG cook stove and refills in cylinder in 200 households for 26 months. We measured personal exposure to HAP [particulate matter 2.5 (PM2·5), black carbon (BC) and carbon monoxide (CO)] in 200 women (main cook) by personal monitors at pre- and post-intervention. Immune function was assessed before and after intervention, in blood collected within 2 weeks of HAP measurements. Primary endpoints included reduction in HAP, lymphocyte proliferation and oxidative stress response, and alterations in T and B cell proportions.

FINDINGS

Exclusive LPG use for 26 months resulted in significant reduction in PM2·5 (43.5%), BC (13%) and CO (48%) exposure in the women. For one unit decrease in BC, Treg cells and memory B cells increased by 7% and 34% respectively, in the peripheral circulation. One unit decrease in CO was significantly associated with increase in early B cells and plasmablasts by 66% and 5% respectively. For one unit decrease in BC, percent-dividing cells, proliferation and expansion indices increased by 2%, 0.4%, and 1%, respectively.

INTERPRETATION

Reduced personal exposure to HAP through clean fuel intervention was related to a return towards cellular immune balance.

Heat Exposure, Heat-Related Symptoms and Coping Strategies among Elderly Residents of Urban Slums and Rural Vilages in West Bengal, India

The impact of heat stress among the elderly in India-particularly the elderly poor-has received little or no attention. Consequently, their susceptibility to heat-related illnesses is virtually unknown, as are the strategies they use to avoid, or deal with, the heat. This study examined perceptions of comfort, heat-related symptoms, and coping behaviors of 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages south of Kolkata during a 90-day period when the average 24-h heat indexes were between 38.6 °C and 41.8 °C. Elderly participants in this study reported being comfortable under relatively warm conditions-probably explained by acclimatization to the high level of experienced heat stress. The prevalence of most heat-related symptoms was significantly greater among elderly women, who also were more likely to report multiple symptoms and more severe symptoms. Elderly women in the rural villages were exposed to significantly hotter conditions during the day than elderly men, making it likely that gender differences in symptom frequency, number and severity were related to gender differences in heat stress. Elderly men and elderly village residents made use of a greater array of heat-coping behaviors and exhibited fewer heat-related symptoms than elderly women and elderly slum residents. Overall, heat measurements and heat-related symptoms were less likely to be significant predictors of most coping strategies than personal characteristics, building structures and location. This suggests that heat-coping behaviors during hot weather were the result of complex, culturally influenced decisions based on many different considerations besides just heat stress.

Exploring a more reasonable temperature exposure calculation method based on individual exposure survey and city-scale heat exposure impact assessment

The inability to quantify the difference between ambient temperature (AT) and personal exposure temperature (PET) is a common limitation in environmental health research. The actual exposure variability is underestimated when we used measurements from fixed monitoring stations to estimate PET. The study aims to explore a more reasonable temperature exposure calculation method to relate PET to AT and links heat exposure to adverse health events. We measured hourly PET of 129 participants from July 8th to July 13th, 2021 in Xinyi City, China. The linear mixed-effects model was used to build the relationship between hourly PET and AT in rural and town. Several calculation methods that can capture the intensity, frequency and duration of daily exposure were used to calculate the daily PET and AT and establish the relationship between the two factors. A generalized linear model was used to establish the relationship between city-scale AT indicators and health endpoints from January 1st, 2013 to December 31st, 2015 in Shanghai, China. The result showed that the hourly PET was significantly related to AT, wind speed, air pressure, precipitation, outside time, and air-conditioning use. Among several daily temperature indicators, we found that AT_DHAT (Degree Hours Above Threshold (27.4 °C)) was tight with the PET_DHAT in different regions (R² > 0.99). DHAT strengthened the relationship between daily AT and health endpoint in the urban-scale heat-related health impact study, especially in respiratory diseases. The method proposed in this study can improve the accuracy of future epidemiological studies on the effects of heat exposure.

Individually experienced heat stress among elderly residents of an urban slum and rural village in India

The elderly are one of the most vulnerable groups to heat-related illnesses and mortality. In tropical countries like India, where heat waves have increased in frequency and severity, few studies have focused on the level of stress experienced by the elderly. The study presented here included 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages about 75 km south of Kolkata. It used miniature monitoring devices to continuously measure temperature, humidity, and heat index experienced during everyday activities over 24-h study periods, during hot summer months. In the Kolkata slum, construction materials and the urban heat island effect combined to create hotter indoor than outdoor conditions throughout the day, and particularly at night. As a result, elderly slum residents were 4.3 times more likely to experience dangerous heat index levels (≥ 45°C) compared to rural village elderly. In both locations, the median 24-h heat indexes of active elderly were up to 2°C higher than inactive/sedentary elderly (F = 25.479, p < 0.001). Among Kolkata slums residents, there were no significant gender differences in heat exposure during the day or night, but in the rural village, elderly women were 4 times more likely to experience dangerous heat index levels during the hottest times of the day compared to elderly men. Given the decline in thermoregulatory capacity associated with aging and the increasing severity of extreme summer heat in India, these results forecast a growing public health challenge that will require both scientific and government attention.

A randomized cross-over trial investigating differences in 24-h personal air and skin temperatures using wearable sensors between two climatologically contrasting settings

The influence of elevated air temperatures recorded in various urban microenvironments in adversely impacting biologically relevant disease end points has not yet been extensively tackled. This study is a post hoc analysis of the TEMP pilot trial, a randomized 2 × 2 cross-over trial that examined changes in metabolic and stress hormonal profiles of healthy adults in two settings (urban vs. rural) with distinctly different climatological characteristics during the Mediterranean summer. This analysis aimed to study the association between the 24-h personal air or skin temperature sensor measurements and the diary-based location type (indoors vs. outdoors) in urban (seaside) vs. rural (higher in altitude) microenvironments. Out of 41 eligible participants, a total of 37 participants were included in this post-hoc TEMP trial analysis. Wearable sensors recorded personal air temperature, skin temperature, and activity (as a surrogate marker of physical activity) in each setting, while a time-stamped personal diary recorded the types of indoor or outdoor activities. Temperature peaks during the 24-h sampling period were detected using a peak finding algorithm. Mixed effect logistic regression models were fitted for the odds of participant location (being indoors vs. outdoors) as a function of setting (urban vs. rural) and sensor-based personal temperature data (either raw temperature values or number of temperature peaks). During the study period (July-end of September), median [interquartile range, IQR] personal air temperature in the rural (higher altitude) settings was 1.5 °C lower than that in the urban settings (27.1 °C [25.4, 29.2] vs. 28.6 °C [27.1, 30.5], p < 0.001), being consistent with the Mediterranean climate. Median [IQR] personal air temperature in indoor (micro)environments was lower than those in outdoors (28.0 °C [26.4, 30.3] vs 28.5 °C [26.8, 30.7], p < 0.001). However, median [IQR] skin temperature was higher in indoor (micro)environments vs. outdoors (34.8 °C [34.0, 35.6] and 33.9 °C [32.9, 34.8], p < 0.001) and the number of both personal air and skin temperature peaks was higher indoors compared to outdoors (median [IQR] 3.0 [2.0,4.0] vs 1.0 [1.0,1.3], p < 0.007, for the skin sensors). A significant association between the number of temperature peaks and indoor location types was observed with either the personal air sensor (OR 3.1; 95% CI 1.2-8.2; p = 0.02) or the skin sensor (OR 3.7; 95% CI 1.4-9.9; p = 0.01), suggesting higher number of indoor air temperature fluctuations. Amidst the global climate crisis, more population health studies or personalized medicine approaches that utilize continuous tracking of individual-level air/skin temperatures in both indoor/outdoor locations would be warranted, if we were to better characterize the disease phenotype in response to climate change manifestations.

Environmental exposure during travel: A research review and suggestions forward

Daily travel through the urban fabric exposes urban dwellers to a range of environmental conditions that may have an impact on their health and wellbeing. Knowledge about exposures during travel, their associations with travel behavior, and their social and health outcomes are still limited. In our review, we aim to explain how the current environmental exposure research addresses the interactions between human and environmental systems during travel through their spatial, temporal and contextual dimensions. Based on the 104 selected studies, we identify significant recent advances in addressing the spatiotemporal dynamics of exposure during travel. However, the conceptual and methodological framework for understanding the role of multiple environmental exposures in travel environments is still in an early phase, and the health and wellbeing impacts at individual or population level are not well known. Further research with greater geographical balance is needed to fill the gaps in the empirical evidence, and linking environmental exposures during travel with the causal health and wellbeing outcomes. These advancements can enable evidence-based urban and transport planning to take the next step in advancing urban livability.

Novel metrics for relating personal heat exposure to social risk factors and outdoor ambient temperature

A more precise understanding of individual-level heat exposure may be helpful to advance knowledge about heat-health impacts and effective intervention strategies, especially in light of projected increases in the severity and frequency of extreme heat events. We developed and interrogated different metrics for quantifying personal heat exposure and explored their association with social risk factors. To do so, we collected simultaneous personal heat exposure data from 64 residents of metropolitan Phoenix, Arizona. From these data, we derived five exposure metrics: Mean Individually Experienced Temperature (IET), Maximum IET, Longest Exposure Period (LEP), Percentage Minutes Above Threshold (PMAT), and Degree Minutes Above Threshold (DMAT), and calculated each for Day Hours, Night Hours, and All Hours of the study period. We then calculated effect sizes for the associations between those metrics and four social risk factors: neighborhood vulnerability, income, home cooling type, and time spent outside. We also investigated exposure misclassification by constructing linear regression models of observations from a regional weather station and hourly IET for each participant. Our analysis revealed that metric choice and timeframe added depth and nuance to our understanding of differences in exposure within and between populations. We found that time spent outside and income were the two risk factors most strongly associated with personal heat exposure. We also found evidence that Mean IET is a good, but perhaps not optimal, measure for assessing group differences in exposure. Most participants' IETs were poorly correlated with regional weather station observations and the slope and correlation coefficient for linear regression models between regional weather station data and IETs varied widely among participants. We recommend continued efforts to investigate personal heat exposure, especially in combination with physiological indicators, to improve our understanding of links between ambient temperatures, social risk factors, and health outcomes.

Association between ambient temperature and heat waves with mortality in South Asia: Systematic review and meta-analysis

BACKGROUND

South Asia is highly vulnerable to climate change and is projected to experience some of the highest increases in average annual temperatures throughout the century. Although the adverse impacts of ambient temperature on human health have been extensively documented in the literature, only a limited number of studies have focused on populations in this region.

OBJECTIVES

Our aim was to systematically review the current state and quality of available evidence on the direct relationship between ambient temperature and heat waves and all-cause mortality in South Asia.

METHODS

The databases Pubmed, Web of Science, Scopus and Embase were searched from 1990 to 2020 for relevant observational quantitative studies. We applied the Navigation Guide methodology to assess the strength of the evidence and performed a meta-analysis based on a novel approach that allows for combining nonlinear exposure-response associations without access to data from individual studies.

RESULTS

From the 6,759 screened papers, 27 were included in the qualitative synthesis and five in a meta-analysis. Studies reported an association of all-cause mortality with heat wave episodes and both high and low daily temperatures. The meta-analysis showed a U-shaped pattern, with increasing mortality for both high and low temperatures, but a statistically significant association was found only at higher temperatures - above 31° C for lag 0-1 days and above 34° C for lag 0-13 days. Effects were found to vary with cause of death, age, sex, location (urban vs. rural), level of education and socio-economic status, but the profile of vulnerabilities was somewhat inconsistent and based on a limited number of studies. Overall, the strength of the evidence for ambient temperature as a risk factor for all-cause mortality was judged as limited and for heat wave episodes as inadequate.

CONCLUSIONS

The evidence base on temperature impacts on mortality in South Asia is limited due to the small number of studies, their skewed geographical distribution and methodological weaknesses. Understanding the main determinants of the temperature-mortality association as well as how these may evolve in the future in a dynamic region such as South Asia will be an important area for future research. Studies on viable adaptation options to high temperatures for a region that is a hotspot for climate vulnerability, urbanisation and population growth are also needed.

Temperature and cardiovascular mortality in Rio de Janeiro, Brazil: effect modification by individual-level and neighbourhood-level factors

BACKGROUND

Many factors related to susceptibility or vulnerability to temperature effects on mortality have been proposed in the literature. However, there is limited evidence of effect modification by some individual-level factors such as occupation, colour/race, education level and community-level factors. We investigated the effect modification of the temperature-cardiovascular mortality relationship by individual-level and neighbourhood-level factors in the city of Rio de Janeiro, Brazil.

METHODS

We used a case-crossover study to estimate the total effect of temperature on cardiovascular mortality in Rio de Janeiro between 2001 and 2018, and the effect modification by individual-level and neighbourhood-level factors. Individual-level factors included sex, age, colour/race, education, and place of death. Neighbourhood-level characteristics included social development index (SDI), income, electricity consumption and demographic change. We used conditional Poisson regression models combined with distributed lag non-linear models, adjusted for humidity and public holidays.

RESULTS

Our results suggest a higher vulnerability to high temperatures among the elderly, women, non-hospitalised deaths, and people with a lower education level. Vulnerability to low temperatures was higher among the elderly, men, non-white people, and for primary education level. As for neighbourhood-level factors, we identified greater vulnerability to low and high temperatures in places with lower SDI, lower income, lower consumption of electricity, and higher demographic growth.

CONCLUSION

The effects of temperature on cardiovascular disease mortality in Rio de Janeiro vary according to individual-level and neighbourhood-level factors. These findings are valuable to inform policymakers about the most vulnerable groups and places, in order to develop more effective and equitable public policies.