Ambient Particulate Air Pollution and Blood Pressure in Peri-urban India.

BACKGROUND: Evidence linking long-term exposure to particulate air pollution to blood pressure (BP) in high-income countries may not be transportable to low- and middle-income countries. We examined cross-sectional associations between ambient fine particulate matter (PM2.5) and black carbon (BC) with BP (systolic [SBP] and diastolic [DBP]) and prevalent hypertension in adults from 28 peri-urban villages near Hyderabad, India. METHODS: We studied 5531 participants from the Andhra Pradesh Children and Parents Study (18-84 years, 54% men). We measured BP (2010-2012) in the right arm and defined hypertension as SBP ≥130 mmHg and/or DBP ≥80 mmHg. We used land-use regression models to estimate annual average PM2.5 and BC at participant's residence. We applied linear and logistic nested mixed-effect models stratified by sex and adjusted by cooking fuel type to estimate associations between within-village PM2.5 or BC and health. RESULTS: Mean (SD) PM2.5 was 33 µg/m (2.7) and BC was 2.5 µg/m (0.23). In women, a 1 µg/m increase in PM2.5 was associated with 1.4 mmHg higher SBP (95% confidence interval [CI]: 0.12, 2.7), 0.87 mmHg higher DBP (95% CI: -0.18, 1.9), and 4% higher odds of hypertension (95% CI: 0%, 9%). In men, associations with SBP (0.52 mmHg; 95% CI: -0.82, 1.8), DBP (0.41 mmHg; 95% CI: -0.69, 1.5), and hypertension (2% higher odds; 95% CI: -2%, 6%) were weaker. No associations were observed with BC. CONCLUSION: We observed a positive association between ambient PM2.5 and BP and hypertension in women. Longitudinal studies in this region are needed to corroborate our findings.

When, Where, and What? Characterizing Personal PM2.5 Exposure in Periurban India by Integrating GPS, Wearable Camera, and Ambient and Personal Monitoring Data.

Evidence identifying factors that influence personal exposure to air pollutants in low- and middle-income countries is scarce. Our objective was to identify the relative contribution of the time of the day ( when?), location ( where?), and individuals' activities ( what?) to PM2.5 personal exposure in periurban South India. We conducted a panel study in which 50 participants were monitored in up to six 24-h sessions ( n = 227). We integrated data from multiple sources: continuous personal and ambient PM2.5 concentrations; questionnaire, GPS, and wearable camera data; and modeled long-term exposure at residence. Mean 24-h personal exposure was 43.8 µg/m3 (SD 24.6) for men and 39.7 µg/m3 (SD 12.0) for women. Temporal patterns in exposure varied between women (peak exposure in the morning) and men (more exposed throughout the rest of the day). Most exposure occurred at home, 67% for men and 89% for women, which was proportional to the time spent in this location. Ambient daily PM2.5 was an important predictor of 24-h personal exposure for both genders. Among men, activities predictive of higher hourly average exposure included presence near food preparation, in the kitchen, in the vicinity of smoking, or in industry. For women, predictors of exposure were largely related to cooking.

Associations between landscape fires and child morbidity in southern Mozambique: a time-series study.

BACKGROUND: Epidemiological evidence linking exposure to landscape fires to child health remains scarce. We assessed the association between daily landscape fire smoke and child hospital visits and admissions in the Manhiça district, Mozambique, an area characterised by frequent forest and cropland fires. METHODS: In this time-series analysis (2012-20), our primary metric for exposure to landscape fires was fire-originated PM2·5 from smoke dispersion hindcasts. We also assessed total and upwind fire exposure using daily satellite-derived fire density data. Daily numbers of hospital visits and admissions were extracted from an ongoing paediatric morbidity surveillance system (children aged ≤15 years). We applied quasi-Poisson regression models controlling for season, long-term trend, day of the week, temperature, and rainfall, and offsetting by annual population-time at risk to examine lag-specific association of fires on morbidity. FINDINGS: A 10 µg/m3 increase in fire-originated PM2·5 was associated with a 6·12% (95% CI 0·37-12·21) increase in all-cause and a 12·43% (5·07-20·31) increase in respiratory-linked hospital visits on the following day. Positive associations were also observed for lag 0 and the cumulative lag of 0-1 days. Null associations were observed for hospital admissions. Landscape fires mostly occurred in forested areas; however, associations with child morbidity were stronger for cropland than for forest fires. INTERPRETATION: Landscape fire smoke was associated with all-cause and respiratory-linked morbidity in children. Improved exposure assessment is needed to better quantify the contribution of landscape fire smoke to child health in regions with scarce air pollution monitoring. FUNDING: H2020 project EXHAUSTION, Academy of Finland, Spanish Ministry of Science and Innovation, Generalitat de Catalunya, and Government of Mozambique and Spanish Agency for International Cooperation and Development.

Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study.

BACKGROUND: A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19. METHODS: The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240 902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7 days. RESULTS: Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant. CONCLUSIONS: Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

Who is more vulnerable to effects of long-term exposure to air pollution on COVID-19 hospitalisation?

OBJECTIVE: Factors that shape individuals' vulnerability to the effects of air pollution on COVID-19 severity remain poorly understood. We evaluated whether the association between long-term exposure to ambient NO2, PM2.5, and PM10 and COVID-19 hospitalisation differs by age, sex, individual income, area-level socioeconomic status, arterial hypertension, diabetes mellitus, and chronic obstructive pulmonary disease. METHODS: We analysed a population-based cohort of 4,639,184 adults in Catalonia, Spain, during 2020. We fitted Cox proportional hazard models adjusted for several potential confounding factors and evaluated the interaction effect between vulnerability indicators and the 2019 annual average of NO2, PM2.5, and PM10. We evaluated interaction on both additive and multiplicative scales. RESULTS: Overall, the association was additive between air pollution and the vulnerable groups. Air pollution and vulnerability indicators had a synergistic (greater than additive) effect for males and individuals with low income or living in the most deprived neighbourhoods. The Relative Excess Risk due to Interaction (RERI) was 0.21, 95 % CI, 0.15 to 0.27 for NO2 and 0.16, 95 % CI, 0.11 to 0.22 for PM2.5 for males; 0.13, 95 % CI, 0.09 to 0.18 for NO2 and 0.10, 95 % CI, 0.05 to 0.14 for PM2.5 for lower individual income and 0.17, 95 % CI, 0.12 to 0.22 for NO2 and 0.09, 95 % CI, 0.05 to 0.14 for PM2.5 for lower area-level socioeconomic status. Results for PM10 were similar to PM2.5. Results on multiplicative scale were inconsistent. CONCLUSIONS: Long-term exposure to air pollution had a larger synergistic effect on COVID-19 hospitalisation for males and those with lower individual- and area-level socioeconomic status.

Estimating daily air temperature and pollution in Catalonia: A comprehensive spatiotemporal modelling of multiple exposures.

Environmental epidemiology studies require models of multiple exposures to adjust for co-exposure and explore interactions. We estimated spatiotemporal exposure to surface air temperature and pollution (PM2.5, PM10, NO2, O3) at high spatiotemporal resolution (daily, 250 m) for 2018-2020 in Catalonia. Innovations include the use of TROPOMI products, a data split for remote sensing gap-filling evaluation, estimation of prediction uncertainty, and use of explainable machine learning. We compiled meteorological and air quality station measurements, climate and atmospheric composition reanalyses, remote sensing products, and other spatiotemporal data. We performed gap-filling of remotely-sensed products using Random Forest (RF) models and validated them using Out-Of-Bag (OOB) samples and a structured data split. The exposure modelling workflow consisted of: 1) PM2.5 station imputation with PM10 data; 2) quantile RF (QRF) model fitting; and 3) geostatistical residual spatial interpolation. Prediction uncertainty was estimated using QRF. SHAP values were used to examine variable importance and the fitted relationships. Model performance was assessed via nested CV at the station level. Evaluation of the gap-filling models using the structured split showed error underestimation when using OOB. Temperature models had the best performance (R2 =0.98) followed by the gaseous air pollutants (R2 =0.81 for NO2 and 0.86 for O3), while the performance of the PM2.5 and PM10 models was lower (R2 =0.57 and 0.63 respectively). Predicted exposure patterns captured urban heat island effects, dust advection events, and NO2 hotspots. SHAP values estimated a high importance of TROPOMI tropospheric NO2 columns in PM and NO2 models, and confirmed that the fitted associations conformed to prior knowledge. Our work highlights the importance of correctly validating gap-filling models and the potential of TROPOMI measurements. Moderate performance in PM models can be partly explained by the poor station coverage. Our exposure estimates can be used in epidemiological studies potentially accounting for exposure uncertainty.

Long-term exposure to air pollution and severe COVID-19 in Catalonia: a population-based cohort study.

The association between long-term exposure to ambient air pollutants and severe COVID-19 is uncertain. We followed 4,660,502 adults from the general population in 2020 in Catalonia, Spain. Cox proportional models were fit to evaluate the association between annual averages of PM2.5, NO2, BC, and O3 at each participant's residential address and severe COVID-19. Higher exposure to PM2.5, NO2, and BC was associated with an increased risk of COVID-19 hospitalization, ICU admission, death, and hospital length of stay. An increase of 3.2 µg/m3 of PM2.5 was associated with a 19% (95% CI, 16-21) increase in hospitalizations. An increase of 16.1 µg/m3 of NO2 was associated with a 42% (95% CI, 30-55) increase in ICU admissions. An increase of 0.7 µg/m3 of BC was associated with a 6% (95% CI, 0-13) increase in deaths. O3 was positively associated with severe outcomes when adjusted by NO2. Our study contributes robust evidence that long-term exposure to air pollutants is associated with severe COVID-19.

Association of ambient and household air pollution with lung function in young adults in an peri-urban area of South-India: A cross-sectional study.

OBJECTIVE: Although there is evidence for the association between air pollution and decreased lung function in children, evidence for adolescents and young adults is scarce. For a peri-urban area in India, we evaluated the association of ambient PM2.5 and household air pollution with lung function for young adults who had recently attained their expected maximum lung function. METHODS: We measured, using a standardized protocol, forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) in participants aged 20-26 years from the third follow-up of the population-based APCAPCS cohort (2010-2012) in 28 Indian villages. We estimated annual average PM2.5outdoors at residence using land-use regression. Biomass cooking fuel (a proxy for levels of household air pollution) was self-reported. We fitted a within-between linear-mixed model with random intercepts by village, adjusting for potential confounders. RESULTS: We evaluated 1,044 participants with mean age of 22.8 (SD = 1) years (range 20-26 years); 327 participants (31%) were female. Only males reported use of tobacco smoking (9% of all participants, 13% of males). The mean ambient PM2.5 exposure was 32.9 (SD = 2.8) µg/m3; 76% reported use of biomass as cooking fuel. The adjusted association between 1 µg/m3 increase in PM2.5 was -27 ml (95% CI, -89 to 34) for FEV1 and -5 ml (95% CI, -93 to 76) for FVC. The adjusted association between use of biomass was -112 ml (95% CI, -211 to -13) for FEV1 and -142 ml (95% CI, -285 to 0) for FVC. The adjusted association was of greater magnitude for those with unvented stove (-158 ml, 95% CI, -279 to -36 for FEV1 and -211 ml, 95% CI, -386 to -36 for FVC). CONCLUSIONS: We observed negative associations between ambient PM2.5 and household air pollution and lung function in young adults who had recently attained their maximum lung function.

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.

Health and environmental impacts of drinking water choices in Barcelona, Spain: A modelling study.

Quantitative evidence of health and environmental tradeoffs between individuals' drinking water choices is needed to inform decision-making. We evaluated health and environmental impacts of drinking water choices using health impact and life cycle assessment (HIA, LCA) methodologies applied to data from Barcelona, Spain. We estimated the health and environmental impacts of four drinking water scenarios for the Barcelona population: 1) currently observed drinking water sources; a complete shift to 2) tap water; 3) bottled water; or 4) filtered tap water. We estimated the local bladder cancer incidence attributable to trihalomethane (THM) exposure, based on survey data on drinking water sources, THM levels, published exposure-response functions, and disability-adjusted life years (DALYs) from the Global Burden of Disease 2017. We estimated the environmental impacts (species lost/year, and resources use) from waste generation and disposal, use of electricity, chemicals, and plastic to produce tap or bottled drinking water using LCA. The scenario where the entire population consumed tap water yielded the lowest environmental impact on ecosystems and resources, while the scenario where the entire population drank bottled water yielded the highest impacts (1400 and 3500 times higher for species lost and resource use, respectively). Meeting drinking water needs using bottled or filtered tap water led to the lowest bladder cancer DALYs (respectively, 140 and 9 times lower than using tap water) in the Barcelona population. Our study provides the first attempt to integrate HIA and LCA to compare health and environmental impacts of individual water consumption choices. Our results suggest that the sustainability gain from consuming water from public supply relative to bottled water may exceed the reduced risk of bladder cancer due to THM exposure from consuming bottled water in Barcelona. Our analysis highlights several critical data gaps and methodological challenges in quantifying integrated health and environmental impacts of drinking water choices.

Association of Ambient and Household Air Pollution With Bone Mineral Content Among Adults in Peri-urban South India.

Importance: Air pollution is a major threat to global health. Osteoporosis is responsible for a substantial burden of disease globally and is expected to increase in prevalence because of population aging. Few studies have investigated the association between air pollution and bone health, and their findings were inconclusive. Objective: To quantify the association between ambient and household air pollution and bone mass in a sample of the general population in peri-urban India. Design, Setting, and Participants: This was a population-based cross-sectional analysis of the Andhra Pradesh Children and Parents Study cohort, which recruited participants from 28 villages near Hyderabad, South India, during 2009 to 2012. Separate linear mixed models were fitted with nested random intercepts (household within villages) for each exposure-outcome pair and were sequentially adjusted for potential confounders. Data analysis was conducted between April 2019 and July 2019. Exposures: Annual mean ambient particulate matter air pollution less than 2.5 µm in aerodynamic diameter (PM2.5) and black carbon (BC) levels at the residence estimated by land-use regression and self-reported use of biomass cooking fuel. Main Outcomes and Measures: The primary outcome was bone mineral content (BMC) measured in grams, corrected by bone area at the lumbar spine and left hip, as measured by dual-energy x-ray absorptiometry. The secondary outcome was bone mineral density measured in grams per centimeters squared. Results: A total of 3717 participants were analyzed (mean [SD] age, 35.7 [14.0] years; 1711 [46.0%] women). The annual mean (SD) PM2.5 exposure was 32.8 (2.5) µg/m3, and the annual mean (SD) BC exposure was 2.5 (0.2) µg/m3; 57.8% of participants used biomass cooking fuels. In fully adjusted models, PM2.5 was associated with lower BMC in the spine (mean difference, -0.57 g per 3 µg/m3 increase in PM2.5; 95% CI, -1.06 to -0.07 g per 3 µg/m3 increase in PM2.5) and hip (mean difference, -0.13 g per 3 µg/m3 increase in PM2.5; 95% CI, -0.3 to 0.03 g per 3 µg/m3 increase in PM2.5). After confounder adjustment, exposure to PM2.5 was also associated with lower bone mineral density in the spine (mean difference, -0.011 g/cm2 per 3 µg/m3 increase in PM2.5; 95% CI, -0.021 to 0 g/cm2 per 3 µg/m3 increase in PM2.5) and hip (mean difference, -0.004 g/cm2 per 3 µg/m3 increase in PM2.5; 95% CI, -0.008 to 0.001 g/cm2 per 3 µg/m3 increase in PM2.5). Exposure to BC was associated with lower BMC in the spine (mean difference, -1.13 g per 1 µg/m3 increase in BC; 95% CI, -2.81 to 0.54 g per 1 µg/m3 increase in BC) and hip (mean difference, -0.35 g per 1 µg/m3 increase in BC; 95% CI, -0.96 to 0.25 g per 1 µg/m3 increase in BC), although the confidence intervals were wider. There was no association between biomass fuel use and spine BMC (mean difference, 0.12 g; 95% CI, -0.45 to 0.68 g). Conclusions and Relevance: In a cross-sectional analysis of a population-based cohort, ambient air pollution was associated with lower BMC in a young adult population in a peri-urban area of South India.

Land-Use Change and Cardiometabolic Risk Factors in an Urbanizing Area of South India: A Population-Based Cohort Study.

BACKGROUND: Land-use changes in city fringes due to urbanization can lead to a reduction of greenspace that may reduce its associated health benefits. OBJECTIVES: We evaluated the association between changes in residential surrounding built-up land use and cardiometabolic risk factors in an urbanizing peri-urban area of south India and explored the mediating roles of air pollution, physical activity, and stress in these associations. METHODS: We analyzed data on 6,039 adults from the third follow-up of the Andhra Pradesh Children and Parent Study (APCAPS) cohort (2010-2012). We generated trajectories of change in residential surrounding built-up land use (buffer areas) from 1995-2009 (stable, slow increase, fast increase) using remote sensing data and image classification methods. We estimated associations between built-up land use trajectories and natural log-transformed blood pressure, waist circumference, triglycerides, fasting glucose, and non-high-density lipoprotein (non-HDL) cholesterol using linear mixed models. We accounted for multiple mediators and the multilevel structure of the data in mediation analyses. RESULTS: We observed positive associations between a fast increase in built-up land use within 300m of the home and all cardiometabolic risk factors. Compared with participants with stable trajectories, those with the largest increase in built-up land use had 1.5% (95% CI: 0.1, 2.9) higher systolic blood pressure, 2.4% (95% CI: 0.6, 4.3) higher diastolic blood pressure, 2.1% (95% CI: 0.5, 3.8) higher waist circumference, and 1.6% (95% CI: -0.6, 3.8) higher fasting glucose in fully adjusted models. Associations were positive, but not statistically significant, for triglycerides, fasting glucose, and non-HDL cholesterol. Physical activity and ambient particulate matter ≤2.5µm in aerodynamic diameter (PM2.5) partially mediated the estimated associations. Associations between fast build-up and all cardiometabolic risk factors except non-HDL cholesterol were stronger in women than men. DISCUSSION: Increases in built-up land use surrounding residences were consistently associated with higher levels of cardiometabolic risk factors. Our findings support the need for better integration of health considerations in urban planning in rapidly urbanizing settings. https://doi.org/10.1289/EHP5445.

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 PM2.5 and black carbon in two seasons in 402 participants living in peri-urban South India. Means (sd) of PM2.5 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 (Rspearman < 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 (Rspearman: 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.

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

Characterizing personal exposure to air temperature is critical to understanding exposure measurement error in epidemiologic studies using fixed-site exposure data and to identify strategies to protect public health. To date, no study evaluating personal air temperature in the general population has been conducted in a low-and-middle income country. We used data from the CHAI study consisting of 50 adults monitored in up to six non-consecutive 24 h sessions in peri-urban south India. We quantified the agreement and association between fixed-site ambient and personal air temperature, and identified predictors of personal air temperature based on housing assessment, self-reported, GPS, remote sensing, and wearable camera data. Mean (SD) daytime (6 am-10 pm) average personal air temperature was 31.2 (2.6) °C and mean nighttime (10 pm-6 am) average temperature was 28.8 (2.8) °C. Agreement between average personal air and fixed-site ambient temperatures was limited, especially at night when personal air temperatures were underestimated by fixed-site temperatures (MBE = -5.6 °C). The proportion of average personal nighttime temperature variability explained by ambient fixed-site temperatures was moderate (R2mar = 0.39); daytime associations were stronger for women (R2mar = 0.51) than for men (R2mar = 0.3). Other predictors of average nighttime personal air temperature included residential altitude, ceiling height, and household income. Predictors of average daytime personal air temperature included roof materials, GPS-tracked altitude, time working in agriculture (for women), and time travelling (for men). No biomass cooking, urban heat island, or greenspace effects were identified. R2mar between ambient fixed-site and personal air temperature indicate that ambient fixed-site temperature is only a moderately useful proxy of personal air temperature in the context of peri-urban India. Our findings suggest that people living in houses at lower altitude, with lower ceiling height and asbestos roofing sheets might be more vulnerable to heat. We also identified households with higher income, women working in agriculture and men with long commutes as disproportionately exposed to high temperatures.

Personal exposure to particulate air pollution and vascular damage in peri-urban South India.

OBJECTIVE: Air pollution is a leading preventable risk factor for cardiovascular diseases. Previous studies mostly relied on concentrations at residence, which might not represent personal exposure. Personal air pollution exposure has a greater variability compared with levels of ambient air pollution, facilitating evaluation of exposure-response functions and vascular pathophysiology. We aimed to evaluate the association between predicted annual personal exposure to PM2.5 and black carbon (BC) and three vascular damage markers in peri-urban South India. METHODS: We analyzed the third wave of the APCAPS cohort (2010-2012), which recruited participants from 28 villages. We used predicted personal exposure to PM2.5 and BC derived from 610 participant-days of 24 h average gravimetric PM2.5 and BC measurements and predictors related to usual time-activity. Outcomes included carotid intima-media thickness (CIMT), carotid-femoral pulse wave velocity (cf-PWV) and augmentation index (AIx). We fit linear mixed models, adjusting for potential confounders and accounting for the clustered data structure. We evaluated nonlinear associations using generalized additive mixed models. RESULTS: Of the 3017 participants (mean age 38 years), 1453 (48%) were women. The average PM2.5 exposure was 51 µg/m3 (range 13-85) for men, and 61 µg/m3 (range 40-120) for women, while the average BC was 4 µg/m3 (range 3-7) for men and 8 µg/m3 (range 3-22) for women. A 10 µg/m3 increase of PM2.5 was positively associated with CIMT (0.026 mm, 95% CI 0.014, 0.037), cf-PWV (0.069 m/s, 95% CI 0.008, 0.131) and AIx (0.8%, 95% CI 0.3, 1.3) among men. The exposure-response function for PM2.5 and AIx among men showed non-linearity, particularly within the exposure range dominated by tobacco smoking and occupational exposures. Both PM2.5 and BC were positively associated with AIx among women (0.6%, 95% CI 0.2, 1.0, per 10 µg/m3 PM2.5; 0.5%, 95% CI 0.1, 0.8, per 2 µg/m3 BC). CONCLUSIONS: Personal exposure to particulate matter was associated with vascular damage in a peri-urban population in South India. Personal exposure to particulate matter appears to have gender-specific effects on the type of vascular damage, potentially reflecting differences in sources of personal exposure by gender.

Association between ambient and household air pollution with carotid intima-media thickness in peri-urban South India: CHAI-Project.

BACKGROUND: Evidence linking ambient air pollution with atherosclerosis is lacking from low- and middle-income countries. Additionally, evidence regarding the association between household air pollution and atherosclerosis is limited. We evaluated the association between ambient fine particulate matter [particulate matter with an aerodynamic diameter of ≤2.5 µm (PM2.5)] and biomass fuel use on carotid intima-media thickness (CIMT), a surrogate of atherosclerosis, in India. METHODS: We analysed the third follow-up of the Andhra Pradesh Children and Parent Study cohort (2010-2012), which recruited participants from 28 peri-urban villages. Our primary outcome was mean CIMT, measured using a standardized protocol. We estimated annual average PM2.5 outdoors at residence using land-use regression. Biomass cooking fuel was self-reported. We fitted a within-between linear-mixed model adjusting for potential confounders. RESULTS: Among 3278 participants (48% women, mean age 38 years), mean PM2.5 was 32.7 [range 24.4-38.2] µg/m3, and 60% used biomass. After confounder adjustment, we observed positive associations between within-village variation in PM2.5 and CIMT in all participants [1.79%, 95% confidence interval (CI), -0.31 to 3.90 per 1 µg/m3 of PM2.5] and in men (2.98%, 95% CI, 0.23-5.72, per 1 µg/m3 of PM2.5). Use of biomass cooking fuel was associated with CIMT in all participants (1.60%, 95% CI, -0.46 to 3.65), especially in women with an unvented stove (6.14%, 95% CI, 1.40-10.89). The point-estimate for the PM2.5 association was larger in sub-groups with higher cardiometabolic risk profile. CONCLUSIONS: Ambient and household air pollution were positively associated with CIMT in a peri-urban population of India, although with limited precision for some estimates. We observed differences in the association between ambient and household air pollution and CIMT by gender.

Changing the urban design of cities for health: The superblock model.

BACKGROUND: Car-dependent city planning has resulted in high levels of environmental pollution, sedentary lifestyles and increased vulnerability to the effects of climate change. The Barcelona Superblock model is an innovative urban and transport planning strategy that aims to reclaim public space for people, reduce motorized transport, promote sustainable mobility and active lifestyles, provide urban greening and mitigate effects of climate change. We estimated the health impacts of implementing this urban model across Barcelona. METHODS: We carried out a quantitative health impact assessment (HIA) study for Barcelona residents ≥20 years (N = 1,301,827) on the projected Superblock area level (N = 503), following the comparative risk assessment methodology. We 1) estimated expected changes in (a) transport-related physical activity (PA), (b) air pollution (NO2), (c) road traffic noise, (d) green space, and (e) reduction of the urban heat island (UHI) effect through heat reductions; 2) scaled available risk estimates; and 3) calculated attributable health impact fractions. Estimated endpoints were preventable premature mortality, changes in life expectancy and economic impacts. RESULTS: We estimated that 667 premature deaths (95% CI: 235-1,098) could be prevented annually through implementing the 503 Superblocks. The greatest number of preventable deaths could be attributed to reductions in NO2 (291, 95% PI: 0-838), followed by noise (163, 95% CI: 83-246), heat (117, 95% CI: 101-137), and green space development (60, 95% CI: 0-119). Increased PA for an estimated 65,000 persons shifting car/motorcycle trips to public and active transport resulted in 36 preventable deaths (95% CI: 26-50). The Superblocks were estimated to result in an average increase in life expectancy for the Barcelona adult population of almost 200 days (95% CI: 99-297), and result in an annual economic impact of 1.7 billion EUR (95% CI: 0.6-2.8). DISCUSSION: The Barcelona Superblocks were estimated to help reduce harmful environmental exposures (i.e. air pollution, noise, and heat) while simultaneously increase PA levels and access to green space, and thereby provide substantial health benefits. For an equitable distribution of health benefits, the Superblocks should be implemented consistently across the entire city. Similar health benefits are expected for other cities that face similar challenges of environmental pollution, climate change vulnerability and low PA levels, by adopting the Barcelona Superblock model.

Lack of association between particulate air pollution and blood glucose levels and diabetic status in peri-urban India.

BACKGROUND: Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM2.5) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban villages in South India. METHODS: We used cross-sectional data from 5065 adults (≥18 years, 54% men) included in the Andhra Pradesh Children and Parents Study. Fasting plasma glucose was measured once in 2010-2012 and prevalent prediabetes and diabetes were defined following the American Diabetes Association criteria. We estimated annual ambient PM2.5 and BC levels at residence using land-use regression models and annual personal exposure to PM2.5 and BC using prediction models based on direct measurements from a subsample of 402 participants. We used linear and logistic nested mixed-effect models to assess the association between exposure metrics and health outcomes. For personal exposures, we stratified analyses by sex. RESULTS: Mean (SD) residential PM2.5 and BC were 32.9 (2.6) µg/m3 and 2.5 (2.6) µg/m3, respectively; personal exposures to PM2.5 and BC were 54.5 (11.5) µg/m3 and 5.8 (2.5) µg/m3, respectively. Average (SD) fasting blood glucose was 5.3 (1.3) mmol/l, 16% of participants had prediabetes, and 5.5% had diabetes. Residential PM2.5 and BC were not associated with higher blood glucose levels. Personal PM2.5 (20 µg/m3 increase) and BC (1 µg/m3 increase) were negatively associated with blood glucose levels in women (PM2.5: -1.93, 95%CI: -3.12, -0.73; BC: -0.63, 95%CI: -0.90, -0.37). In men, associations were negative for personal PM2.5 (-1.99, 95%CI: -3.56, -0.39) and positive for personal BC (0.49, 95%CI: -0.44, 1.43). We observed no evidence of associations between any exposure and prevalence of prediabetes/diabetes. CONCLUSIONS: Our results do not provide evidence that residential exposures to PM2.5 or BC are associated with blood glucose or prevalence of prediabetes/diabetes in this population. Associations with personal exposure may have been affected by unmeasured confounding, highlighting a challenge in using personal exposure estimates in air pollution epidemiology. These associations should be further examined in longitudinal studies.

Associations between landscape fires and child morbidity in southern Mozambique: a time-series study

Background: Epidemiological evidence linking exposure to landscape fires to child health remains scarce. We assessed the association between daily landscape fire smoke and child hospital visits and admissions in the Manhiça district, Mozambique, an area characterised by frequent forest and cropland fires. Methods: In this time-series analysis (2012-20), our primary metric for exposure to landscape fires was fire-originated PM2·5 from smoke dispersion hindcasts. We also assessed total and upwind fire exposure using daily satellite-derived fire density data. Daily numbers of hospital visits and admissions were extracted from an ongoing paediatric morbidity surveillance system (children aged ≤15 years). We applied quasi-Poisson regression models controlling for season, long-term trend, day of the week, temperature, and rainfall, and offsetting by annual population-time at risk to examine lag-specific association of fires on morbidity. Findings: A 10 µg/m3 increase in fire-originated PM2·5 was associated with a 6·12% (95% CI 0·37-12·21) increase in all-cause and a 12·43% (5·07-20·31) increase in respiratory-linked hospital visits on the following day. Positive associations were also observed for lag 0 and the cumulative lag of 0-1 days. Null associations were observed for hospital admissions. Landscape fires mostly occurred in forested areas; however, associations with child morbidity were stronger for cropland than for forest fires. Interpretation: Landscape fire smoke was associated with all-cause and respiratory-linked morbidity in children. Improved exposure assessment is needed to better quantify the contribution of landscape fire smoke to child health in regions with scarce air pollution monitoring. Funding: H2020 project EXHAUSTION, Academy of Finland, Spanish Ministry of Science and Innovation, Generalitat de Catalunya, and Government of Mozambique and Spanish Agency for International Cooperation and Development.