Establishing integrated rural-urban cohorts to assess air pollution-related health effects in pregnant women, children and adults in Southern India: an overview of objectives, design and methods in the Tamil Nadu Air Pollution and Health Effects (TAPHE) study

Understanding trimester-specific miscarriage risk in Indian women: insights from the calendar data of National Family Health Survey (NFHS-5) 2019-21

BACKGROUND

The primary public health issue, especially in low- and middle-income countries, is early pregnancy loss driven by miscarriage. Understanding early pregnancy losses and the characteristics of mothers who have miscarriages is essential to creating effective reproductive health strategies. Thus, this study's primary goal is to delve into the factors which impact miscarriages that take place prior to and following the first 12 weeks of gestation.

METHODS

The bivariate analysis was employed to determine the frequency of miscarriages. The factors associated with miscarriages in the first (≤12 weeks) and second & above (> 12 weeks) trimesters of pregnancy were then examined using a generalised linear regression model, with 95% confidence intervals. Finally, we use ArcGIS to illustrate the prevalence of miscarriage in the districts of India.

RESULTS

Our result shows that miscarriages occur often in India (4.9%), with 23% of cases occurring in the first trimester (≤12 weeks). In our bivariate analysis, we identified several factors associated with a higher prevalence of miscarriages in India. It was found that mothers aged thirty years or older, residing in urban areas, with less than ten years of education, belonging to the richest wealth quantile, expressing a desire for more children, having no demand for contraception, and possessing no parity experienced a higher prevalence of miscarriage in total pregnancies in India. On the other hand, the generalised linear model's findings show that mothers who are thirty years of age or older, practise other religions, live in urban areas, are members of other castes, want more children, marry before the age of eighteen, and meet their contraceptive needs are more likely to have miscarriages in total pregnancy. However, there is a larger likelihood of miscarriage in the first trimester (≤12 weeks) for mothers who follow other religions, live in urban areas, are from Other Backward Class (OBC), get married before the age of eighteen, and fall into the middle and upper wealth quantiles. A mother is more likely to miscarriage in the second & above (> 12 weeks) trimesters if she is older than thirty, from other castes, wants more children, has moderate media exposure, marries before turning eighteen, meets her contraceptive needs, and does not feel the need for contraception. After accounting for socioeconomic characteristics, all results were statistically significant.

CONCLUSIONS

Given the substantial number of miscarriages in India, police need to improve planning and guidance in order to lower pregnancy loss due to miscarriage. Miscarriage rates may be significantly decreased by enhancing the availability and quality of reproductive health care infrastructure, particularly in rural areas.

PM2.5 exposure, glycemic markers and incidence of type 2 diabetes in two large Indian cities

INTRODUCTION

Exposure to fine particulate matter has been associated with several cardiovascular and cardiometabolic diseases. However, such evidence mostly originates from low-pollution settings or cross-sectional studies, thus necessitating evidence from regions with high air pollution levels, such as India, where the burden of non-communicable diseases is high.

RESEARCH DESIGN AND METHODS

We studied the associations between ambient PM2.5 levels and fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c) and incident type 2 diabetes mellitus (T2DM) among 12 064 participants in an adult cohort from urban Chennai and Delhi, India. A meta-analytic approach was used to combine estimates, obtained from mixed-effects models and proportional hazards models, from the two cities.

RESULTS

We observed that 10 μg/m3 differences in monthly average exposure to PM2.5 was associated with a 0.40 mg/dL increase in FPG (95% CI 0.22 to 0.58) and 0.021 unit increase in HbA1c (95% CI 0.009 to 0.032). Further, 10 μg/m3 differences in annual average PM2.5 was associated with 1.22 (95% CI 1.09 to 1.36) times increased risk of incident T2DM, with non-linear exposure response.

CONCLUSIONS

We observed evidence of temporal association between PM2.5 exposure, and higher FPG and incident T2DM in two urban environments in India, thus highlighting the potential for population-based mitigation policies to reduce the growing burden of diabetes.

Monitoring of polycyclic aromatic hydrocarbons emitted from kerosene fuel burning and assessment of health risks among women in selected rural and urban households of South India

Polycyclic aromatic hydrocarbons (PAHs) are well-known hazardous substances; nevertheless, research on their exposure and health concerns associated with kerosene fuel emissions is limited. In this study, PAH (combined gaseous and particle phase) monitoring was carried out in the kitchen and living room in selected households. Personal exposure and cooking time monitoring were also carried out, simultaneously. The study's findings revealed that BaP, BA, BbF, and Nap were the most prevalent PAHs in both the summer and winter seasons, regardless of urban or rural households. The estimated values of average incremental lifetime cancer risks were found to be greater than the USEPA level, i.e., 1 × 10^-6, in both urban and rural households, regardless of seasonal fluctuation. In both seasons, the non-carcinogenic risk for developmental and reproductive effects was higher in rural women than in urban women, and in case of developmental risk it showed greater than unity (rural: 1.11 and urban 1.03) in the winter season. On the other hand, Monte Carlo simulation model revealed that concentrations of PAHs (97.1% and 97.5%) and exposure duration (51.7% and 56.7%) were the most sensitive factors contributed for health risk estimations for urban and rural area in both seasons, respectively. Furthermore, the results clearly showed that women who were using kerosene for cooking were at a greater risk of acquiring both carcinogenic and non-carcinogenic health consequences from PAH exposure from kerosene cookstoves. It was recommended that they should utilize clean fuel, either by using LPG under the PMUY scheme or by using electricity/solar power to reduce health risks for better health.

Time-activity and daily mobility patterns during pregnancy and early postpartum - evidence from the MADRES cohort

INTRODUCTION

Pregnant women's daily time-activity and mobility patterns determine their environmental exposures and subsequently related health effects. Most studies ignore these and assess pregnancy exposures using static residential measures.

METHODS

We conducted 4-day continuous geo-location monitoring in 62 pregnant Hispanic women, during pregnancy and early post-partum then derived trips by mode and stays, classified by context (indoor/outdoor, type). Generalized mixed-effect models were used to examine whether these patterns changed over time.

RESULTS

Women spent on average 17.3 h/day at home. Commercial and service locations were the most popular non-home destinations, while parks and open spaces were seldom visited. Women made 3.5 daily trips (63.7 min/day and approximately 25% were pedestrian-based). Women were less likely to visit commercial and services locations and make vehicle-based trips postpartum compared to the 3^rd trimester.

CONCLUSION

Our findings suggest time-activity patterns vary across pregnancy and postpartum, thus assessing exposures at stationary locations might introduce measurement error.

Implementing a ventilation index for assessing indoor air PM2.5 concentrations in biomass-using households

Biomass combustion in indoor kitchens contributes a lot to the PM_2.5 exposure burden among millions of people worldwide. Emitted potential pollutants from the biomass combustion oven may enormously degrade indoor air quality during cooking time and impact crowded rooms with inadequate indoor ventilation. The concept of developing a "ventilation index" may be a valuable alternative to assess indoor air quality. A new empirical formula of the ventilation index has been proposed recently, in which multiple studies need to be validated by various studies. This study is a part of the validation process and has ended up with supportive evidence-based insight into residential indoor air quality. Ninety-three households were selected from 25 villages of Tamil Nadu, India, to monitor the parameters required to apply in the empirical formula. However, the association between indoor air velocity and PM_2.5 (considered a surrogate component of indoor air quality) was focused on emphatically. Other important variables, e.g., used amount of biomass cooking fuel, kitchen room index, room temperature, and relative humidity, were also monitored to observe the ventilation index. Indoor PM_2.5 data were compared categorically with variable air velocities. Those who were using only biomass for cooking in indoor kitchens were recruited in the study. The air pollution exposure burden among the community population is expected to be minimized when the desired ventilation index is optimized and applied in configured kitchens and living rooms. Then, it may attract government policy to accept the ventilation index as a critical parameter for green housing schemes.

Child Survival and Early Lifetime Exposures to Ambient Fine Particulate Matter in India: A Retrospective Cohort Study

BACKGROUND

Ambient fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] is a major health risk for children, particularly in South Asia, which currently experiences the highest PM2.5 levels globally. Nevertheless, there is comparatively little epidemiological evidence from this region to quantify the effects of PM2.5 on child survival.

OBJECTIVES

We estimated the association between PM2.5 exposure and child survival in India.

METHODS

We constructed a large, retrospective, and nationally representative cohort of children <5 years of age, born between 2009-2016, from the publicly available, cross-sectional 2015-2016 Demographic Health Surveys in India. In utero and post-delivery lifetime average ambient PM2.5 exposures were estimated with data from satellite remote sensing, meteorology, and land use information (model R2= 0.82). We used Cox proportional hazards regression to estimate the association between both average in utero and post-delivery lifetime PM2.5 and all-cause child mortality, controlling for individual- and household-level covariates, seasonality, location, and meteorology.

RESULTS

Over 7,447,724 child-months of follow-up, there were 11,559 deaths at <5 years of age reported by the children's mothers. The mean concentrations of 9-month in utero and post-delivery lifetime average ambient PM2.5 exposure were 71.1 μg/m3 (range: 20.9-153.5 μg/m3) and 73.7 μg/m3 (range: 14.0-247.3 μg/m3), respectively. Estimated child mortality adjusted hazard ratios were 1.023 [95% confidence interval (CI): 1.008, 1.038] and 1.013 (95% CI: 1.001, 1.026) per 10-μg/m3 increase of in utero and post-delivery lifetime PM2.5, with both exposures in the model.

DISCUSSION

This study adds to the growing body of evidence about the adverse health effects of PM2.5 by demonstrating the association between exposure, both in utero and post-delivery, on child survival at the national level in India. Strategies to reduce ambient air pollution levels, including steps to minimize in utero and early life exposures, are urgently needed in India and other countries where exposures are above recommended guideline values. https://doi.org/10.1289/EHP8910.

Household air pollution during COVID-19 pandemic: A concern in India

Household air pollution is a serious public health concern in India with more than half of the Indian households relying on solid fuel use. The long periods of lockdown related measures to control COVID-19 pandemic in India further aggravated the adverse health effects of household air pollution as millions Indians were exposed to high level of health-damaging air pollutants inside their homes. This commentary discusses the vulnerability of the socioeconomically disadvantaged population forced to stay indoors during the pandemic. Exposure to household air pollution has detrimental effects on health, which might put individuals at higher risk for complications related to COVID-19. A large proportion of socioeconomically disadvantaged section of the population were exposed to critical levels of household air pollution and more vulnerable to severe health effects of COVID-19. There is a pressing need to understand the aggravated health consequences of household air pollution in association with COVID-19.

Effect of exposure to PM10 on child health: evidence based on a large-scale survey from 184 cities in India

Introduction

Air pollution is increasingly becoming a serious global public health concern. Prior studies examining the effect of air pollution on health have ignored the role of households’ hygienic practices and socioeconomic condition, which are key determinants of the health status of a country like India. This study examines the effects of air pollution, measured in levels of particulate matters of size below 10 µg/m³ (PM₁₀), on child-health outcomes after adjusting for hygiene practices.

Methods

Health data from the National Family Health Survey-4 (NFHS-4) and PM₁₀ levels provided by the Central Pollution Control Board were matched for 184 Indian towns/cities. Child health outcomes included neonatal mortality, post-neonatal mortality, premature births, children with symptoms of acute respiratory infections (ARI) and low birth weight. Multilevel mixed-effects models were used to estimate the risk associated with exposure to PM₁₀.

Result

Analyses based on 23 954 births found that every 10-unit increase in PM₁₀ level, increased the risk of neonatal mortality by 6% (adjusted RR (95% CI): 1.02 (1.02 to 1.09)), and the odds of symptoms of ARI among children by 7% (adjusted OR (95% CI): 1.07 (1.03 to 1.12)), and premature births by 8% (adjusted OR (95% CI): 1.08 (1.03 to 1.12)). There was no statistically significant difference in the effect of PM₁₀ on child health regardless of household’s hygienic practices. Effects of PM₁₀ on child health outcomes remained similar for cities whether or not they were part of the National Clean Air Program (NCAP).

Conclusion

Exposure to PM₁₀, regardless of hygienic practices, increases the risk of adverse child health outcomes. Study findings suggest that the focus of mitigating the effects of air pollution should be beyond the towns/cities identified under NCAP. Given the increasing industrialisation and urbanisation, a systemic, coherent approach is required to address the issue of air pollution in India.

Maternal Vitamin B12 Status and Risk of Cleft Lip and Cleft Palate Birth Defects in Tamil Nadu State, India

BACKGROUND AND OBJECTIVE

The causal role of maternal nutrition in orofacial clefts is uncertain. We tested hypotheses that low maternal vitamin B₁₂ and low folate status are each associated with an increased risk of isolated cleft lip with or without cleft palate (CL±P) in a case-control study in Tamil Nadu state, India.

METHODS

Case-mothers of CL±P children (n = 47) and control-mothers of unaffected children (n = 50) were recruited an average of 1.4 years after birth of the index child and plasma vitamin B₁₂, methylmalonic acid (MMA), total homocysteine (tHcy), and folate were measured at that time. Logistic regression analyses estimated associations between nutrient biomarkers and case-control status.

RESULTS

Odds ratios (ORs) contrasting biomarker levels showed associations between case-mothers and low versus high plasma vitamin B₁₂ (OR = 2.48, 95% CI, 1.02-6.01) and high versus low plasma MMA, an indicator of poor B₁₂ status (OR = 3.65 95% CI, 1.21-11.05). Case-control status was not consistently associated with folate or tHcy levels. Low vitamin B₁₂ status, when defined by a combination of both plasma vitamin B₁₂ and MMA levels, had an even stronger association with case-mothers (OR = 6.54, 95% CI, 1.33-32.09).

CONCLUSIONS

Mothers of CL±P children in southern India were 6.5 times more likely to have poor vitamin B₁₂ status, defined by multiple biomarkers, compared to control-mothers. Further studies in populations with diverse nutritional backgrounds are required to determine whether poor maternal vitamin B₁₂ or folate levels or their interactions are causally related to CL±P.

Regional and seasonal variations in household and personal exposures to air pollution in one urban and two rural Chinese communities: A pilot study to collect time-resolved data using static and wearable devices

BACKGROUND

Previous studies of the health impact of ambient and household air pollution (AAP/HAP) have chiefly relied on self-reported and/or address-based exposure modelling data. We assessed the feasibility of collecting and integrating detailed personal exposure data in different settings and seasons.

METHODS/DESIGN

We recruited 477 participants (mean age 58 years, 72% women) from three (two rural [Gansu/Henan] and one urban [Suzhou]) study areas in the China Kadoorie Biobank, based on their previously reported fuel use patterns. A time-resolved monitor (PATS+CO) was used to measure continuously for 120-hour the concentration of fine particulate matter (PM2.5) at personal and household (kitchen and living room) levels in warm (May-September 2017) and cool (November 2017-January 2018) seasons, along with questionnaires on participants' characteristics (e.g. socio-demographic, and fuel use) and time-activity (48-hour). Parallel local ambient monitoring of particulate matter (PM1, PM2.5 and PM10) and gaseous pollutants (CO, ozone, nitrogen oxides) was conducted using regularly-calibrated devices. The air pollution exposure data were compared by study sites and seasons.

FINDINGS

Overall 76% reported cooking at least weekly (regular-cooks), and 48% (urban 1%, rural 65%) used solid fuels (wood/coal) for cooking. Winter heating was more common in rural sites than in urban site (74-91% vs 17% daily), and mainly involved solid fuels. Mixed use of clean and solid fuels was common for cooking in rural areas (38%) but not for heating (0%). Overall, the measured mean PM2.5 levels were 2-3 fold higher in the cool than warm season, and in rural (e.g. kitchen: Gansuwarm_season = 142.3 µg/m3; Gansucool_season = 508.1 µg/m3; Henanwarm_season = 77.5 µg/m3; Henancool_season = 222.3 µg/m3) than urban sites (Suzhouwarm_season = 41.6 µg/m3; Suzhoucool_season = 81.6 µg/m3). The levels recorded tended to be the highest in kitchens, followed by personal, living room and outdoor. Time-resolved data show prominent peaks consistently recorded in the kitchen at typical cooking times, and sustained elevated PM2.5 levels (> 100 µg/m3) were observed in rural areas where use of solid fuels for heating was common.

DISCUSSION

Personal air pollution exposure can be readily assessed using a low-cost time-resolved monitor in different settings, which, in combination with other personal and health outcome data, will enable reliable assessment of the long-term health effects of HAP/AAP exposures in general populations.

Insights on the biological role of ultrafine particles of size PM<0.25: A prospective study from New Delhi

When the total ambient PM_2.5 levels are several-fold higher than the recommended limit, it may be important to study the distributions of different sizes of particulate matter (PM). Here, we assess the distributions of various sizes of total PM_2.5 for 12 months (on a monthly basis) in New Delhi, India. Importantly, we found that ultrafine particles (i.e., particles <0.5 μm) contribute significantly to total PM_2.5. PM_<0.25 were the most cytotoxic particles to human lung epithelial cells in all the 12 months. In addition, PM_<0.25 were associated with significantly higher cytotoxicity per unit mass compared to other size fractions constituting PM_2.5. For any given size of PM, the amount of reactive oxygen species (ROS) generated per unit mass is higher for the month of March as compared to that for the rest of the months in the year. The higher ROS generations for all sizes of PM collected in the month of March was not explained by differences in their metal content values. Our data suggests the lack of correlation between total PM_2.5 levels and the highly cytotoxic PM_<0.25. In summary, this work establishes the need for policy changes to routinely monitor PM_<0.25 and the necessity to establish exposure limits for PM_<0.25, especially when the total PM_2.5 levels are breached.

Exposure assessment of indoor particulate matter during pregnancy: a narrative review of the literature

OBJECTIVE

The aim of this review was to summarize the evidence of the exposure assessment approaches of indoor particulate matter (PM) during pregnancy and to recommend future focus areas.

CONTENT

Exposure to indoor PM during pregnancy is associated with adverse birth outcomes. However, many questions remain about the consistency of the findings and the magnitude of this effect. This may be due to the exposure assessment methods used and the challenges of characterizing exposure during pregnancy. Exposure is unlikely to remain constant over the nine-month period. Pregnant females' mobility and activities vary - for example, employment status may be random among females, but among those employed, activities are likely to be greater in the early pregnancy than closer to the delivery of the child.

SUMMARY

Forty three studies that used one of the five categories of indoor PM exposure assessment (self-reported, personal air monitoring, household air monitoring, exposure models and integrated approaches) were assessed. Our results indicate that each of these exposure assessment approaches has unique characteristics, strengths, and weaknesses. While questionnaires and interviews are based on self-report and recall, they were a major component in the reviewed exposure assessment studies. These studies predominantly used large sample sizes. Precision and detail were observed in studies that used integrated approaches (i. e. questionnaires, measurements and exposure models).

OUTLOOK

Given the limitations presented by these studies, exposure misclassification remains possible because of personal, within and between household variability, seasonal changes, and spatiotemporal variability during pregnancy. Therefore, using integrated approaches (i. e. questionnaire, measurements and exposure models) may provide better estimates of PM levels across trimesters. This may provide precision for exposure estimates in the exposure-response relationship.

Personal exposure to particulate matter in peri-urban India: predictors and association with ambient concentration at residence

Scalable exposure assessment approaches that capture personal exposure to particles for purposes of epidemiology are currently limited, but valuable, particularly in low-/middle-income countries where sources of personal exposure are often distinct from those of ambient concentrations. We measured 2 × 24-h integrated personal exposure to PM_2.5 and black carbon in two seasons in 402 participants living in peri-urban South India. Means (sd) of PM_2.5 personal exposure were 55.1(82.8) µg/m³ for men and 58.5(58.8) µg/m³ for women; corresponding figures for black carbon were 4.6(7.0) µg/m³ and 6.1(9.6) µg/m³. Most variability in personal exposure was within participant (intra-class correlation ~20%). Personal exposure measurements were not correlated (R_spearman < 0.2) with annual ambient concentration at residence modeled by land-use regression; no subgroup with moderate or good agreement could be identified (weighted kappa ≤ 0.3 in all subgroups). We developed models to predict personal exposure in men and women separately, based on time-invariant characteristics collected at baseline (individual, household, and general time-activity) using forward stepwise model building with mixed models. Models for women included cooking activities and household socio-economic position, while models for men included smoking and occupation. Models performed moderately in terms of between-participant variance explained (38-53%) and correlations between predictions and measurements (R_spearman: 0.30-0.50). More detailed, time-varying time-activity data did not substantially improve the performance of the models. Our results demonstrate the feasibility of predicting personal exposure in support of epidemiological studies investigating long-term particulate matter exposure in settings characterized by solid fuel use and high occupational exposure to particles.

Ensemble averaging based assessment of spatiotemporal variations in ambient PM2.5 concentrations over Delhi, India, during 2010-2016

Elevated levels of ambient air pollution has been implicated as a major risk factor for morbidities and premature mortality in India, with particularly high concentrations of particulate matter in the Indo-Gangetic plain. High resolution spatiotemporal estimates of such exposures are critical to assess health effects at an individual level. This article retrospectively assesses daily average PM2.5 exposure at 1 km × 1 km grids in Delhi, India from 2010-2016, using multiple data sources and ensemble averaging approaches. We used a multi-stage modeling exercise involving satellite data, land use variables, reanalysis based meteorological variables and population density. A calibration regression was used to model PM2.5: PM10 to counter the sparsity of ground monitoring data. The relationship between PM2.5 and its spatiotemporal predictors was modeled using six learners; generalized additive models, elastic net, support vector regressions, random forests, neural networks and extreme gradient boosting. Subsequently, these predictions were combined under a generalized additive model framework using a tensor product based spatial smoothing. Overall cross-validated prediction accuracy of the model was 80% over the study period with high spatial model accuracy and predicted annual average concentrations ranging from 87 to 138 μg/m3. Annual average root mean squared errors for the ensemble averaged predictions were in the range 39.7-62.7 μg/m3 with prediction bias ranging between 4.6-11.2 μg/m3. In addition, tree based learners such as random forests and extreme gradient boosting outperformed other algorithms. Our findings indicate important seasonal and geographical differences in particulate matter concentrations within Delhi over a significant period of time, with meteorological and land use features that discriminate most and least polluted regions. This exposure assessment can be used to estimate dose response relationships more accurately over a wide range of particulate matter concentrations.

Air pollution in India and related adverse respiratory health effects: past, present, and future directions

PURPOSE OF REVIEW

The review describes current status of air pollution in India, summarizes recent research on adverse health effects of ambient and household air pollution, and outlines the ongoing efforts and future actions required to improve air quality and reduce morbidity and mortality because of air pollution in India.

RECENT FINDINGS

Global burden of disease data analysis reveals more than one million premature deaths attributable to ambient air pollution in 2015 in India. More than one million additional deaths can be attributed to household air pollution. Particulate matter with diameter 2.5 μm or less has been causatively linked with most premature deaths. Acute respiratory tract infections, asthma, chronic obstructive pulmonary disease, exacerbations of preexisting obstructive airway disease and lung cancer are proven adverse respiratory effects of air pollution. Targeting air quality standards laid by WHO can significantly reduce morbidity and mortality because of air pollution in India.

SUMMARY

India is currently exposed to high levels of ambient and household air pollutants. Respiratory adverse effects of air pollution are significant contributors to morbidity and premature mortality in India. Substantial efforts are being made at legislative, administrative, and community levels to improve air quality. However, much more needs to be done to change the 'status quo' and attain the target air quality standards. VIDEO ABSTRACT: http://links.lww.com/COPM/A24.

The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017

BACKGROUND

Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational levels in India, we estimated the exposure to air pollution and its impact on deaths, disease burden, and life expectancy in every state of India in 2017.

METHODS

We estimated exposure to air pollution, including ambient particulate matter pollution, defined as the annual average gridded concentration of PM2.5, and household air pollution, defined as percentage of households using solid cooking fuels and the corresponding exposure to PM2.5, across the states of India using accessible data from multiple sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three Socio-demographic Index (SDI) levels as calculated by GBD 2017 on the basis of lag-distributed per-capita income, mean education in people aged 15 years or older, and total fertility rate in people younger than 25 years. We estimated deaths and disability-adjusted life-years (DALYs) attributable to air pollution exposure, on the basis of exposure-response relationships from the published literature, as assessed in GBD 2017; the proportion of total global air pollution DALYs in India; and what the life expectancy would have been in each state of India if air pollution levels had been less than the minimum level causing health loss.

FINDINGS

The annual population-weighted mean exposure to ambient particulate matter PM2·5 in India was 89·9 μg/m3 (95% uncertainty interval [UI] 67·0-112·0) in 2017. Most states, and 76·8% of the population of India, were exposed to annual population-weighted mean PM2·5 greater than 40 μg/m3, which is the limit recommended by the National Ambient Air Quality Standards in India. Delhi had the highest annual population-weighted mean PM2·5 in 2017, followed by Uttar Pradesh, Bihar, and Haryana in north India, all with mean values greater than 125 μg/m3. The proportion of population using solid fuels in India was 55·5% (54·8-56·2) in 2017, which exceeded 75% in the low SDI states of Bihar, Jharkhand, and Odisha. 1·24 million (1·09-1·39) deaths in India in 2017, which were 12·5% of the total deaths, were attributable to air pollution, including 0·67 million (0·55-0·79) from ambient particulate matter pollution and 0·48 million (0·39-0·58) from household air pollution. Of these deaths attributable to air pollution, 51·4% were in people younger than 70 years. India contributed 18·1% of the global population but had 26·2% of the global air pollution DALYs in 2017. The ambient particulate matter pollution DALY rate was highest in the north Indian states of Uttar Pradesh, Haryana, Delhi, Punjab, and Rajasthan, spread across the three SDI state groups, and the household air pollution DALY rate was highest in the low SDI states of Chhattisgarh, Rajasthan, Madhya Pradesh, and Assam in north and northeast India. We estimated that if the air pollution level in India were less than the minimum causing health loss, the average life expectancy in 2017 would have been higher by 1·7 years (1·6-1·9), with this increase exceeding 2 years in the north Indian states of Rajasthan, Uttar Pradesh, and Haryana.

INTERPRETATION

India has disproportionately high mortality and disease burden due to air pollution. This burden is generally highest in the low SDI states of north India. Reducing the substantial avoidable deaths and disease burden from this major environmental risk is dependent on rapid deployment of effective multisectoral policies throughout India that are commensurate with the magnitude of air pollution in each state.

FUNDING

Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

Impact of Maternal Air Pollution Exposure on Children's Lung Health: An Indian Perspective

Air pollution has become an emerging invisible killer in recent years and is a major cause of morbidity and mortality globally. More than 90% of the world’s children breathe toxic air every day. India is among the top ten most highly polluted countries with an average PM₁₀ level of 134 μg/m³ per year. It is reported that 99% of India’s population encounters air pollution levels that exceed the World Health Organization Air Quality Guideline, advising a PM_2.5 permissible level of 10 μg/m³. Maternal exposure to air pollution has serious health outcomes in offspring because it can affect embryonic phases of development during the gestation period. A fetus is more prone to effects from air pollution during embryonic developmental phases due to resulting oxidative stress as antioxidant mechanisms are lacking at that stage. Any injury during this vulnerable period (embryonic phase) will have a long-term impact on offspring health, both early and later in life. Epidemiological studies have revealed that maternal exposure to air pollution increases the risk of development of airway disease in the offspring due to impaired lung development in utero. In this review, we discuss cellular mechanisms involved in maternal exposure to air pollution and how it can impact airway disease development in offspring. A better understanding of these mechanisms in the context of maternal exposure to air pollution can offer a new avenue to prevent the development of airway disease in offspring.

Development of land-use regression models for fine particles and black carbon in peri-urban South India

Land-use regression (LUR) has been used to model local spatial variability of particulate matter in cities of high-income countries. Performance of LUR models is unknown in less urbanized areas of low-/middle-income countries (LMICs) experiencing complex sources of ambient air pollution and which typically have limited land use data. To address these concerns, we developed LUR models using satellite imagery (e.g., vegetation, urbanicity) and manually-collected data from a comprehensive built-environment survey (e.g., roads, industries, non-residential places) for a peri-urban area outside Hyderabad, India. As part of the CHAI (Cardiovascular Health effects of Air pollution in Telangana, India) project, concentrations of fine particulate matter (PM_2.5) and black carbon were measured over two seasons at 23 sites. Annual mean (sd) was 34.1 (3.2) μg/m³ for PM_2.5 and 2.7 (0.5) μg/m³ for black carbon. The LUR model for annual black carbon explained 78% of total variance and included both local-scale (energy supply places) and regional-scale (roads) predictors. Explained variance was 58% for annual PM_2.5 and the included predictors were only regional (urbanicity, vegetation). During leave-one-out cross-validation and cross-holdout validation, only the black carbon model showed consistent performance. The LUR model for black carbon explained a substantial proportion of the spatial variability that could not be captured by simpler interpolation technique (ordinary kriging). This is the first study to develop a LUR model for ambient concentrations of PM_2.5 and black carbon in a non-urban area of LMICs, supporting the applicability of the LUR approach in such settings. Our results provide insights on the added value of manually-collected built-environment data to improve the performance of LUR models in settings with limited data availability. For both pollutants, LUR models predicted substantial within-village variability, an important feature for future epidemiological studies.

Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India

Exposure to high concentrations of ambient fine particulate matter (PM2.5) is a leading risk factor for public health in India causing a large burden of disease. Business-as-usual economic and industrial growth in India is predicted to increase emissions, worsen air quality, and increase the associated disease burden in future decades. Here we use a high-resolution online-coupled model to estimate the impacts of different air pollution control pathways on ambient PM2.5 concentrations and human health in India. We find that with no change in emissions, the disease burden from exposure to ambient PM2.5 in 2050 will increase by 75% relative to 2015, due to population aging and growth increasing the number of people susceptible to air pollution. We estimate that the International Energy Agencies New Policy Scenario (NPS) and Clean Air Scenario (CAS) in 2050 can reduce ambient PM2.5 concentrations below 2015 levels by 9% and 68%, respectively, offsetting 61,000 and 610,000 premature mortalities a year, which is 9% and 91% of the projected increase in premature mortalities due to population growth and aging. Throughout India, the CAS stands out as the most effective scenario to reduce ambient PM2.5 concentrations and the associated disease burden, reducing the 2050 mortality rate per 100,000 below 2015 control levels by 15%. However, even under such stringent emission control policies, population growth and aging results in premature mortality estimates from exposure to particulate air pollution to increase by 7% compared to 2015, highlighting the challenge facing efforts to improve public health in India.

Characterizing exposure to household air pollution within the Prospective Urban Rural Epidemiology (PURE) study

BACKGROUND

Household air pollution (HAP) from combustion of solid fuels is an important contributor to disease burden in low- and middle-income countries (LIC, and MIC). However, current HAP disease burden estimates are based on integrated exposure response curves that are not currently informed by quantitative HAP studies in LIC and MIC. While there is adequate evidence supporting causal relationships between HAP and respiratory disease, large cohort studies specifically examining relationships between quantitative measures of HAP exposure with cardiovascular disease are lacking.

OBJECTIVE

We aim to improve upon exposure proxies based on fuel type, and to reduce exposure misclassification by quantitatively measuring exposure across varying cooking fuel types and conditions in diverse geographies and socioeconomic settings. We leverage technology advancements to estimate household and personal PM2.5 (particles below 2.5 μm in aerodynamic diameter) exposure within the large (N~250,000) multi-country (N~26) Prospective Urban and Rural Epidemiological (PURE) cohort study. Here, we detail the study protocol and the innovative methodologies being used to characterize HAP exposures, and their application in epidemiologic analyses.

METHODS/DESIGN

This study characterizes HAP PM2.5 exposures for participants in rural communities in ten PURE countries with >10% solid fuel use at baseline (Bangladesh, Brazil, Chile, China, Colombia, India, Pakistan, South Africa, Tanzania, and Zimbabwe). PM2.5 monitoring includes 48-h cooking area measurements in 4500 households and simultaneous personal monitoring of male and female pairs from 20% of the selected households. Repeat measurements occur in 20% of households to assess impacts of seasonality. Monitoring began in 2017, and will continue through 2019. The Ultrasonic Personal Aerosol Sampler (UPAS), a novel, robust, and inexpensive filter based monitor that is programmable through a dedicated mobile phone application is used for sampling. Pilot study field evaluation of cooking area measurements indicated high correlation between the UPAS and reference Harvard Impactors (r = 0.91; 95% CI: 0.84, 0.95; slope = 0.95). To facilitate tracking and to minimize contamination and analytical error, the samplers utilize barcoded filters and filter cartridges that are weighed pre- and post-sampling using a fully automated weighing system. Pump flow and pressure measurements, temperature and RH, GPS coordinates and semi-quantitative continuous particle mass concentrations based on filter differential pressure are uploaded to a central server automatically whenever the mobile phone is connected to the internet, with sampled data automatically screened for quality control parameters. A short survey is administered during the 48-h monitoring period. Post-weighed filters are further analyzed to estimate black carbon concentrations through a semi-automated, rapid, cost-effective image analysis approach. The measured PM2.5 data will then be combined with PURE survey information on household characteristics and behaviours collected at baseline and during follow-up to develop quantitative HAP models for PM2.5 exposures for all rural PURE participants (~50,000) and across different cooking fuel types within the 10 index countries. Both the measured (in the subset) and the modelled exposures will be used in separate longitudinal epidemiologic analyses to assess associations with cardiopulmonary mortality, and disease incidence.

DISCUSSION

The collected data and resulting characterization of cooking area and personal PM2.5 exposures in multiple rural communities from 10 countries will better inform exposure assessment as well as future epidemiologic analyses assessing the relationships between quantitative estimates of chronic HAP exposure with adult mortality and incident cardiovascular and respiratory disease. This will provide refined and more accurate exposure estimates in global CVD related exposure-response analyses.

Exposures to fine particulate matter (PM2.5) and birthweight in a rural-urban, mother-child cohort in Tamil Nadu, India

BACKGROUND

Exposure to PM_2.5 (fine particulate matter <less than 2.5µm in aerodynamic diameter) related to ambient and household air pollution has been associated with low birthweight. Few of these studies, however, have been conducted in high exposure settings that are commonly encountered in low and middle income countries (LMICs).

OBJECTIVES

We examined whether PM_2.5 exposures during pregnancy were associated with birthweight in an integrated rural-urban, mother-child cohort in the state of Tamil Nadu, India.

METHODS

We recruited 1285 pregnant women in the first trimester of pregnancy from primary health care centers and urban health posts and followed them until birth to collect antenatal care data and birthweight. We estimated pregnancy period PM _2.5 exposures through direct serial measurements of 24-h household PM_2.5 concentrations, performed across each trimester. Mothers also completed detailed questionnaires to provide data on covariates related to household, socio-economic, demographic and maternal health characteristics. The association between PM_2.5 exposures and birth weight was assessed using linear and logistic regression models that controlled for potential confounders.

RESULTS

A 10-μg/m³ increase in pregnancy period PM_2.5 exposures was associated with a 4g (95% CI: 1.08g, 6.76g) decrease in birthweight and 2% increase in prevalence of low birthweight [odds ratio(OR) = 1.02; 95%CI:1.005,1.041] after adjusting for gestational age, infant sex, maternal BMI, maternal age, history of a previous low birth weight child, birth order and season of conception.

CONCLUSIONS

The study provides some of the first quantitative effects estimates for linking rural-urban PM_2.5 exposures and birthweight in India, adding important evidence for this association from high exposure settings in LMICs, that also experience dual health burdens from ambient and household air pollution. Study results also point to the need for considering maternal PM_2.5 exposures alongside other risk factors for low birthweight in India.

Evaluating spatial distribution and seasonal variation of phthalates using passive air sampling in southern India

Usage of phthalates as plasticizers has resulted in worldwide occurrence and is becoming a serious concern to human health and environment. However, studies on phthalates in Indian atmosphere are lacking. Therefore, we studied the spatio-temporal trends of six major phthalates in Tamil Nadu, southern India, using passive air samplers. Phthalates were ubiquitously detected in all the samples and the average total phthalates found in decreasing order is pre-monsoon (61 ng m^-3) > summer (52 ng m^-3) > monsoon (17 ng m^-3). Largely used phthalates, dibutylphthalate (DBP) and diethylhexlphthalate (DEHP) were predominantly found in all the seasons with contribution of 11-31% and 59-68%, respectively. The highest total phthalates was observed in summer at an urban location (836 ng m^-3). Furthermore, through principal component analysis, potential sources were identified as emissions from additives of plasticizers in the polymer industry and the productions of adhesives, building materials and vinyl flooring. Although inhalation exposure of infants was higher than other population segments (toddlers, children and adults), exposure levels were found to be safe for people belonging to all ages based on reference dose (RfD) and tolerable daily intake (TDI) values. This study first attempted to report seasonal trend based on atmospheric monitoring using passive air sampling technique and exposure risk together.

Exposure to particulate matter in India: A synthesis of findings and future directions

Air pollution poses a critical threat to human health with ambient and household air pollution identified as key health risks in India. While there are many studies investigating concentration, composition, and health effects of air pollution, investigators are only beginning to focus on estimating or measuring personal exposure. Further, the relevance of exposures studies from the developed countries in developing countries is uncertain. This review summarizes existing research on exposure to particulate matter (PM) in India, identifies gaps and offers recommendations for future research. There are a limited number of studies focused on exposure to PM and/or associated health effects in India, but it is evident that levels of exposure are much higher than those reported in developed countries. Most studies have focused on coarse aerosols, with a few studies on fine aerosols. Additionally, most studies have focused on a handful of cities, and there are many unknowns in terms of ambient levels of PM as well as personal exposure. Given the high mortality burden associated with air pollution exposure in India, a deeper understanding of ambient pollutant levels as well as source strengths is crucial, both in urban and rural areas. Further, the attention needs to expand beyond the handful large cities that have been studied in detail.