Effect of residential relocation on environmental exposures in European cohorts: An exposome-wide approach.

Residential relocation is increasingly used as a natural experiment in epidemiological studies to assess the health impact of changes in environmental exposures. Since the likelihood of relocation can be influenced by individual characteristics that also influence health, studies may be biased if the predictors of relocation are not appropriately accounted for. Using data from Swedish and Dutch adults (SDPP, AMIGO), and birth cohorts (BAMSE, PIAMA), we investigated factors associated with relocation and changes in multiple environmental exposures across life stages. We used logistic regression to identify baseline predictors of moving, including sociodemographic and household characteristics, health behaviors and health. We identified exposure clusters reflecting three domains of the urban exposome (air pollution, grey surface, and socioeconomic deprivation) and conducted multinomial logistic regression to identify predictors of exposome trajectories among movers. On average, 7 % of the participants relocated each year. Before relocating, movers were consistently exposed to higher levels of air pollution than non-movers. Predictors of moving differed between the adult and birth cohorts, highlighting the importance of life stages. In the adult cohorts, moving was associated with younger age, smoking, and lower education and was independent of cardio-respiratory health indicators (hypertension, BMI, asthma, COPD). Contrary to adult cohorts, higher parental education and household socioeconomic position were associated with a higher probability of relocation in birth cohorts, alongside being the first child and living in a multi-unit dwelling. Among movers in all cohorts, those with a higher socioeconomic position at baseline were more likely to move towards healthier levels of the urban exposome. We provide new insights into predictors of relocation and subsequent changes in multiple aspects of the urban exposome in four cohorts covering different life stages in Sweden and the Netherlands. These results inform strategies to limit bias due to residential self-selection in epidemiological studies using relocation as a natural experiment.

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.

Determinants of carbon load in airway macrophages in pregnant women.

The airway macrophages carbon loading (AMCL) has been suggested to be a biomarker of the long-term exposure to air pollution; however, to date no study has characterized AMCL for the pregnancy period. Therefore, this study aimed to assess the determinants of AMCL during pregnancy in Iran, a middle-income country. This study was based on a sample of 234 pregnant women with term and normal vaginal delivery who were residing in Sabzevar, Iran (2019). We characterized 35 potential determinants of personal exposure to air pollution for each participant, including six personal, nine indoor, and 20 home-outdoor factors. We applied Deletion/Substitution/Addition algorithm to identify the most relevant determinants that could predict AMCL levels. The median (IQR) of AMCL level was 0.12 (0.30) µm2 with a successful sputum induction in 82.9% (194) of participants. Ambient residential PM2.5 levels were positively associated with higher AMCL levels. On the other hand, increased residential distance to the traffic lights, squares and ring-roads, the duration of opening window per day, and opening window during cooking were inversely associated with AMCL levels. Our findings provide novel insights on the different personal, indoor, and outdoor determinants of personal exposure to air pollution during pregnancy in a middle-income country.

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 Between Outdoor Light-at-night Exposure and Colorectal Cancer in Spain.

BACKGROUND: Night-shift work, exposure to artificial light-at-night (ALAN) and particularly blue light spectrum, and the consequent circadian disruption may increase the risk of breast and prostate cancer. Colorectal cancer risk may also be increased among night-shift workers. We investigated the association between exposure to ALAN according to light spectrum and colorectal cancer among subjects who had never worked at night in a general population case-control study in Spain. METHODS: We examined information on 661 incident histologically verified colorectal cancer cases and 1,322 controls from Barcelona and Madrid, 2007-2013. Outdoor ALAN exposure was based on images from the International Space Station (ISS) including data on remotely sensed upward light intensity. We derived adjusted odds ratio (OR) estimates and confidence intervals (CI) for visual light, blue light, and spectral sensitivities of the five human photopigments assigned to participant's geocoded longest residence. RESULTS: Exposure to blue light spectrum was positively associated with colorectal cancer (OR = 1.6; 95% CI: 1.2-2.2; highest vs. lowest tertile). ORs were similar (OR = 1.7; 95% CI: 1.3-2.3) when further adjusting for area socioeconomic status, diet patterns, smoking, sleep, and family history. We observed no association for outdoor visual light (full spectrum) (OR = 1.0; 95% CI, 0.7-1.2; highest vs. lowest tertile). Analysis of the five photopigments gave similar results with increased risks for shorter wavelengths overlapping with the blue spectrum and no association for longer wavelengths. CONCLUSIONS: Outdoor blue light spectrum exposure that is increasingly prevalent in recent years may be associated with colorectal cancer risk. See video abstract: http://links.lww.com/EDE/B708.

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.

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.

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.

Predictors of personal exposure to black carbon among women in southern semi-rural Mozambique.

Sub-Saharan Africa (SSA) has the highest proportion of people using unclean fuels for household energy, which can result in products of incomplete combustion that are damaging for health. Black carbon (BC) is a useful marker of inefficient combustion-related particles; however, ambient air quality data and temporal patterns of personal exposure to BC in SSA are scarce. We measured ambient elemental carbon (EC), comparable to BC, and personal exposure to BC in women of childbearing age from a semi-rural area of southern Mozambique. We measured ambient EC over one year (2014-2015) using a high-volume sampler and an off-line thermo-optical-transmission method. We simultaneously measured 5-min resolved 24-h personal BC using a portable MicroAeth (AE51) in 202 women. We used backwards stepwise linear regression to identify predictors of log-transformed 24-h mean and peak (90th percentile) personal BC exposure. We analyzed data from 187 non-smoking women aged 16-46 years. While daily mean ambient EC reached moderate levels (0.9 µg/m3, Standard Deviation, SD: 0.6 µg/m3), daily mean personal BC reached high levels (15 µg/m3, SD: 19 µg/m3). Daily patterns of personal exposure revealed a peak between 6 and 7 pm (>35 µg/m3), attributable to kerosene-based lighting. Key determinants of mean and peak personal exposure to BC were lighting source, kitchen type, ambient EC levels, and temperature. This study highlights the important contribution of lighting sources to personal exposure to combustion particles in populations that lack access to clean household energy.

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.

Wearable camera-derived microenvironments in relation to personal exposure to PM2.5.

Data regarding which microenvironments drive exposure to air pollution in low and middle income countries are scarce. Our objective was to identify sources of time-resolved personal PM2.5 exposure in peri-urban India using wearable camera-derived microenvironmental information. We conducted a panel study with up to 6 repeated non-consecutive 24 h measurements on 45 participants (186 participant-days). Camera images were manually annotated to derive visual concepts indicative of microenvironments and activities. Men had slightly higher daily mean PM2.5 exposure (43 µg/m3) compared to women (39 µg/m3). Cameras helped identify that men also had higher exposures when near a biomass cooking unit (mean (sd) µg/m3: 119 (383) for men vs 83 (196) for women) and presence in the kitchen (133 (311) for men vs 48 (94) for women). Visual concepts associated in regression analysis with higher 5-minute PM2.5 for both sexes included: smoking (+93% (95% confidence interval: 63%, 129%) in men, +29% (95% CI: 2%, 63%) in women), biomass cooking unit (+57% (95% CI: 28%, 93%) in men, +69% (95% CI: 48%, 93%) in women), visible flame or smoke (+90% (95% CI: 48%, 144%) in men, +39% (95% CI: 6%, 83%) in women), and presence in the kitchen (+49% (95% CI: 27%, 75%) in men, +14% (95% CI: 7%, 20%) in women). Our results indicate wearable cameras can provide objective, high time-resolution microenvironmental data useful for identifying peak exposures and providing insights not evident using standard self-reported time-activity.

Associations of night-time road traffic noise with carotid intima-media thickness and blood pressure: The Whitehall II and SABRE study cohorts.

BACKGROUND: Road traffic noise has been linked to increased risk of stroke, for which hypertension and carotid intima-media thickness (cIMT) are risk factors. A link between traffic noise and hypertension has been established, but there are few studies on blood pressure and no studies on cIMT. OBJECTIVES: To examine cross-sectional associations for long-term exposure to night-time noise with cIMT, systolic blood pressure (SBP), diastolic blood pressure (DBP) and hypertension. METHODS: The study population consisted of 2592 adults from the Whitehall II and SABRE cohort studies living within Greater London who had cIMT, SBP and DBP measured. Exposure to night-time road traffic noise (A-weighted dB, referred to as dBA) was estimated at each participant's residential postcode centroid. RESULTS: Mean night-time road noise levels were 52dBA (SD=4). In the pooled analysis adjusted for cohort, sex, age, ethnicity, marital status, smoking, area-level deprivation and NOx there was a 9.1µm (95% CI: -7.1, 25.2) increase in cIMT in association with 10dBA increase in night-time noise. Analyses by noise categories of 55-60dBA (16.2µm, 95% CI: -8.7, 41.2), and >60dBA (21.2µm, 95% CI: -2.5, 44.9) vs. <55dBA were also positive but non-significant, expect among those not using antihypertensive medication and exposed to >60dBA vs. <55dBA (32.6µm, 95% CI: 6.2, 59.0). Associations for SBP, DPB and hypertension were close to null. CONCLUSIONS: After adjustments, including for air pollution, the association between night-time road traffic noise and cIMT was only observed among non-medication users but associations with blood pressure and hypertension were largely null.

Road traffic noise is associated with increased cardiovascular morbidity and mortality and all-cause mortality in London.

AIMS: Road traffic noise has been associated with hypertension but evidence for the long-term effects on hospital admissions and mortality is limited. We examined the effects of long-term exposure to road traffic noise on hospital admissions and mortality in the general population. METHODS AND RESULTS: The study population consisted of 8.6 million inhabitants of London, one of Europe's largest cities. We assessed small-area-level associations of day- (7:00-22:59) and nighttime (23:00-06:59) road traffic noise with cardiovascular hospital admissions and all-cause and cardiovascular mortality in all adults (≥25 years) and elderly (≥75 years) through Poisson regression models. We adjusted models for age, sex, area-level socioeconomic deprivation, ethnicity, smoking, air pollution, and neighbourhood spatial structure. Median daytime exposure to road traffic noise was 55.6 dB. Daytime road traffic noise increased the risk of hospital admission for stroke with relative risk (RR) 1.05 [95% confidence interval (CI): 1.02-1.09] in adults, and 1.09 (95% CI: 1.04-1.14) in the elderly in areas >60 vs. <55 dB. Nighttime noise was associated with stroke admissions only among the elderly. Daytime noise was significantly associated with all-cause mortality in adults [RR 1.04 (95% CI: 1.00-1.07) in areas >60 vs. <55 dB]. Positive but non-significant associations were seen with mortality for cardiovascular and ischaemic heart disease, and stroke. Results were similar for the elderly. CONCLUSIONS: Long-term exposure to road traffic noise was associated with small increased risks of all-cause mortality and cardiovascular mortality and morbidity in the general population, particularly for stroke in the elderly.

Modeling exposures to the oxidative potential of PM10.

Differences in the toxicity of ambient particulate matter (PM) due to varying particle composition across locations may contribute to variability in results from air pollution epidemiologic studies. Though most studies have used PM mass concentration as the exposure metric, an alternative which accounts for particle toxicity due to varying particle composition may better elucidate whether PM from specific sources is responsible for observed health effects. The oxidative potential (OP) of PM < 10 µm (PM(10)) was measured as the rate of depletion of the antioxidant reduced glutathione (GSH) in a model of human respiratory tract lining fluid. Using a database of GSH OP measures collected in greater London, U.K. from 2002 to 2006, we developed and validated a predictive spatiotemporal model of the weekly GSH OP of PM(10) that included geographic predictors. Predicted levels of OP were then used in combination with those of weekly PM(10) mass to estimate exposure to PM(10) weighted by its OP. Using cross-validation (CV), brake and tire wear emissions of PM(10) from traffic within 50 m and tailpipe emissions of nitrogen oxides from heavy-goods vehicles within 100 m were important predictors of GSH OP levels. Predictive accuracy of the models was high for PM(10) (CV R(2)=0.83) but only moderate for GSH OP (CV R(2) = 0.44) when comparing weekly levels; however, the GSH OP model predicted spatial trends well (spatial CV R(2) = 0.73). Results suggest that PM(10) emitted from traffic sources, specifically brake and tire wear, has a higher OP than that from other sources, and that this effect is very local, occurring within 50-100 m of roadways.

Characterising socio-economic inequalities in exposure to air pollution: a comparison of socio-economic markers and scales of measurement.

This study examines traffic-related air pollution in London in relation to area- and individual-level socio-economic position (SEP). Mean air pollution concentrations were generally higher in postcodes of low SEP as classified by small-area markers of deprivation (Index of Multiple Deprivation (IMD) domains) and by the postcode-level ACORN geodemographic marker. There were exceptions, however, including reversed directions of associations in central London and for SEP markers relating to education. ACORN predicted air pollution independently of IMD and explained additional variation at the postcode level, indicating the potential value of using both markers in air pollution epidemiology studies. By contrast, after including IMD and ACORN there remained little relationship between air pollution and individual-level SEP or smoking, suggesting limited residual socio-economic confounding in epidemiological studies with comprehensive area-level adjustment.

Public health benefits of strategies to reduce greenhouse-gas emissions: household energy.

Energy used in dwellings is an important target for actions to avert climate change. Properly designed and implemented, such actions could have major co-benefits for public health. To investigate, we examined the effect of hypothetical strategies to improve energy efficiency in UK housing stock and to introduce 150 million low-emission household cookstoves in India. Methods similar to those of WHO's Comparative Risk Assessment exercise were applied to assess the effect on health that changes in the indoor environment could have. For UK housing, the magnitude and even direction of the changes in health depended on details of the intervention, but interventions were generally beneficial for health. For a strategy of combined fabric, ventilation, fuel switching, and behavioural changes, we estimated 850 fewer disability-adjusted life-years (DALYs), and a saving of 0.6 megatonnes of carbon dioxide (CO(2)), per million population in 1 year (on the basis of calculations comparing the health of the 2010 population with and without the specified outcome measures). The cookstove programme in India showed substantial benefits for acute lower respiratory infection in children, chronic obstructive pulmonary disease, and ischaemic heart disease. Calculated on a similar basis to the UK case study, the avoided burden of these outcomes was estimated to be 12 500 fewer DALYs and a saving of 0.1-0.2 megatonnes CO(2)-equivalent per million population in 1 year, mostly in short-lived greenhouse pollutants. Household energy interventions have potential for important co-benefits in pursuit of health and climate goals.

Public health benefits of strategies to reduce greenhouse-gas emissions: urban land transport.

We used Comparative Risk Assessment methods to estimate the health effects of alternative urban land transport scenarios for two settings-London, UK, and Delhi, India. For each setting, we compared a business-as-usual 2030 projection (without policies for reduction of greenhouse gases) with alternative scenarios-lower-carbon-emission motor vehicles, increased active travel, and a combination of the two. We developed separate models that linked transport scenarios with physical activity, air pollution, and risk of road traffic injury. In both cities, we noted that reduction in carbon dioxide emissions through an increase in active travel and less use of motor vehicles had larger health benefits per million population (7332 disability-adjusted life-years [DALYs] in London, and 12 516 in Delhi in 1 year) than from the increased use of lower-emission motor vehicles (160 DALYs in London, and 1696 in Delhi). However, combination of active travel and lower-emission motor vehicles would give the largest benefits (7439 DALYs in London, 12 995 in Delhi), notably from a reduction in the number of years of life lost from ischaemic heart disease (10-19% in London, 11-25% in Delhi). Although uncertainties remain, climate change mitigation in transport should benefit public health substantially. Policies to increase the acceptability, appeal, and safety of active urban travel, and discourage travel in private motor vehicles would provide larger health benefits than would policies that focus solely on lower-emission motor vehicles.

Public health benefits of strategies to reduce greenhouse-gas emissions: low-carbon electricity generation.

In this report, the third in this Series on health and climate change, we assess the changes in particle air pollution emissions and consequent effects on health that are likely to result from greenhouse-gas mitigation measures in the electricity generation sector in the European Union (EU), China, and India. We model the effect in 2030 of policies that aim to reduce total carbon dioxide (CO(2)) emissions by 50% by 2050 globally compared with the effect of emissions in 1990. We use three models: the POLES model, which identifies the distribution of production modes that give the desired CO(2) reductions and associated costs; the GAINS model, which estimates fine particulate matter with aerodynamic diameter 2.5 microm or less (PM(2.5)) concentrations; and a model to estimate the effect of PM(2.5) on mortality on the basis of the WHO's Comparative Risk Assessment methods. Changes in modes of production of electricity to reduce CO(2) emissions would, in all regions, reduce PM(2.5) and deaths caused by it, with the greatest effect in India and the smallest in the EU. Health benefits greatly offset costs of greenhouse-gas mitigation, especially in India where pollution is high and costs of mitigation are low. Our estimates are approximations but suggest clear health gains (co-benefits) through decarbonising electricity production, and provide additional information about the extent of such gains.

Public health benefits of strategies to reduce greenhouse-gas emissions: overview and implications for policy makers.

This Series has examined the health implications of policies aimed at tackling climate change. Assessments of mitigation strategies in four domains-household energy, transport, food and agriculture, and electricity generation-suggest an important message: that actions to reduce greenhouse-gas emissions often, although not always, entail net benefits for health. In some cases, the potential benefits seem to be substantial. This evidence provides an additional and immediate rationale for reductions in greenhouse-gas emissions beyond that of climate change mitigation alone. Climate change is an increasing and evolving threat to the health of populations worldwide. At the same time, major public health burdens remain in many regions. Climate change therefore adds further urgency to the task of addressing international health priorities, such as the UN Millennium Development Goals. Recognition that mitigation strategies can have substantial benefits for both health and climate protection offers the possibility of policy choices that are potentially both more cost effective and socially attractive than are those that address these priorities independently.