Advancing climate change health adaptation through implementation science.

To date, there are few examples of implementation science studies that help guide climate-related health adaptation. Implementation science is the study of methods to promote the adoption and integration of evidence-based tools, interventions, and policies into practice to improve population health. These studies can provide the needed empirical evidence to prioritise and inform implementation of health adaptation efforts. This Personal View discusses five case studies that deployed disease early warning systems around the world. These cases studies illustrate challenges to deploying early warning systems and guide recommendations for implementation science approaches to enhance future research. We propose theory-informed approaches to understand multilevel barriers, design strategies to overcome those barriers, and analyse the ability of those strategies to advance the uptake and scale-up of climate-related health interventions. These findings build upon previous theoretical work by grounding implementation science recommendations and guidance in the context of real-world practice, as detailed in the case studies.

A Systematic Study of the Prevalence and Risk Factors of CKD in Uddanam, India.

INTRODUCTION: Despite reports of a high prevalence of chronic kidney disease (CKD) from the coastal Uddanam region of Andhra Pradesh, India, there are no accurate data on the distribution of kidney function abnormalities and CKD risk factors in this region. METHODS: A total of 2419 participants were recruited through multistage cluster random sampling from 67 villages. Serum creatinine and urine protein creatinine ratio were measured using validated methodologies. All abnormal estimated glomerular filtration rate (eGFR) and urine protein creatinine ratio values were reconfirmed after 3 months. A range of sociodemographic factors were evaluated for their association with CKD using Poisson regression. RESULTS: Of 2402 eligible subjects (mean ± SD age, 45.67 ± 13.29 years; 51% female), 506 (21.07%) had CKD (mean ± SD age, 51.79 ± 13.12 years; 41.3% female). A total of 246 (10.24%) had eGFR <60 ml/min/1.73 m2, whereas 371 (15.45%) had an elevated urine protein creatinine ratio (>0.15 g/g). The poststratified estimates, adjusted for age and sex distribution of the region for CKD prevalence, are 18.7% (range, 16.4%-21.0%) overall and 21.3% (range, 18.2%-24.4% ) and 16.2% (range, 13.7%-18.8%) in men and women, respectively. Older age, male sex, tobacco use, hypertension, and family history of CKD were independently associated with CKD. Compared with those with higher eGFR, those with eGFR <60 ml/min/1.73m2 were older, were more likely to be uneducated, manual laborers/farmers, or tobacco users, and were more likely to have hypertension, a family history of CKD, a diagnosis of heart disease, and a lower body mass index. Among those with low eGFR, there was no difference between those with urine protein creatinine ratio <0.15 or >0.15, except a lower frequency of males in the former. CONCLUSION: We confirmed the high prevalence of CKD in the adult population of Uddanam. The cause was not apparent in a majority. Subjects with a low eGFR with or without elevated proteinuria were phenotypically distinct from those with proteinuria and preserved eGFR. Our data suggest the need to apply a population-based approach to screening and prevention and studies to understand the causes of CKD in this region.

Study to Test and Operationalize Preventive Approaches for CKD of Undetermined Etiology in Andhra Pradesh, India.

INTRODUCTION: High prevalence of chronic kidney disease (CKD) not associated with known risk factors has been reported from coastal districts of Andhra Pradesh. The Study to Test and Operationalize Preventive Approaches for Chronic Kidney Disease of Undetermined Etiology in Andhra Pradesh (STOP CKDu AP) aims to ascertain the burden (prevalence and incidence) of CKD, the risk factor profile, and the community perceptions about the disease in the Uddanam area of Andhra Pradesh. METHODS: Study participants will be sampled from the Uddanam area using multistage cluster random sampling. Information will be collected on the demographic profile, occupational history, and presence of conventional as well as nonconventional risk factors. Glomerular filtration rate (GFR) will be estimated using the Chronic Kidney Disease Epidemiology Collaboration equation, and proteinuria will be measured. All abnormal values will be confirmed by repeat testing after 3 months. Cases of CKD not associated with identified etiologies will be identified. Biospecimens will be stored to explore future hypotheses. The entire cohort will be followed up every 6 months to determine the incidence of CKD and to identify risk factors for decline in kidney function. Qualitative studies will be performed to understand the community perceptions and expectations with respect to the interventions. IMPLICATIONS: CKD is an important public health challenge in low- and middle-income countries. This study will establish the prevalence and determine the incidence of CKD not associated with known risk factors in a reported high-burden region, and will provide insights to help design targeted health systems responses. The findings will contribute to the policy development to tackle CKD in the region and will permit international comparisons with other regions with similar high prevalence.

Environmental Risks of Cities in the European Region: Analyses of the Sustainable Healthy Urban Environments (SHUE) Database.

INTRODUCTION: In an increasingly urbanized world, cities are a key focus for action on health and sustainability. The Sustainable Healthy Urban Environments (SHUE) project aims to provide a shared information resource to support such action. Its aim is to test the feasibility and methods of assembling data about the characteristics of a globally distributed sample of cities and the populations within them for comparative analyses, and to use such data to assess how policies may contribute to sustainable urban development and human health. METHODS: As a first illustration of the database, we present analyses of selected parameters on climate change, air pollution and flood risk for 64 cities in the WHO European Region. RESULTS: Under a high greenhouse gas emissions trajectory (RCP8.5), the analyses suggest damaging temperature rises in European cities that are among the highest of any cities in the global database, while air pollution (PM2.5) levels are appreciably above the WHO guideline level for all but a handful of cities. In several areas, these environmental hazards are compounded by flood risk. DISCUSSION: Such evidence, though preliminary and based on limited data, underpins the need for urgent action on climate change (adaptation and mitigation) and risks relating to air pollution and other environmental hazards.

Climate Change and Women's Health: Impacts and Opportunities in India.

Climate change impacts on health, including increased exposures to heat, poor air quality, extreme weather events, and altered vector-borne disease transmission, reduced water quality, and decreased food security, affect men and women differently due to biologic, socioeconomic, and cultural factors. In India, where rapid environmental changes are taking place, climate change threatens to widen existing gender-based health disparities. Integration of a gendered perspective into existing climate, development, and disaster-risk reduction policy frameworks can decrease negative health outcomes. Modifying climate risks requires multisector coordination, improvement in data acquisition, monitoring of gender specific targets, and equitable stakeholder engagement. Empowering women as agents of social change can improve mitigation and adaptation policy interventions.

Disease burden due to biomass cooking-fuel-related household air pollution among women in India.

BACKGROUND: Household air pollution (HAP) due to biomass cooking fuel use is an important risk factor for a range of diseases, especially among adult women who are primary cooks, in India. About 80% of rural households in India use biomass fuel for cooking. The aim of this study is to estimate the attributable cases (AC) for four major diseases/conditions associated with biomass cooking fuel use among adult Indian women. METHODS: We used the population attributable fraction (PAF) method to calculate the AC of chronic bronchitis, tuberculosis (TB), cataract, and stillbirths due to exposure to biomass cooking fuel. A number of data sources were accessed to obtain population totals and disease prevalence rates. A meta-analysis was conducted to obtain adjusted pooled odds ratios (ORs) for strength of association. Using this, PAF and AC were calculated using a standard formula. Results were presented as number of AC and 95% confidence intervals (CI). RESULTS: The fixed effects pooled OR obtained from the meta-analysis were 2.37 (95% CI: 1.59, 3.54) for chronic bronchitis, 2.33 (1.65, 3.28) for TB, 2.16 (1.42, 3.26) for cataract, and 1.26 (1.12, 1.43) for stillbirths. PAF varied across conditions being maximum (53%) for chronic bronchitis in rural areas and least (1%) for cataract in older age and urban areas. About 2.4 (95% CI: 1.4, 3.1) of 5.6 m cases of chronic bronchitis, 0.3 (0.2, 0.4) of 0.76 m cases of TB, 5.0 (2.8, 6.7) of 51.4 m cases of cataract among adult Indian women and 0.02 (0.01, 0.03) of 0.15 m stillbirths across India are attributable to HAP due to biomass cooking fuel. These estimates should be cautiously interpreted in the light of limitations discussed which relate to exposure assessment, exposure characterization, and age-specific prevalence of disease. CONCLUSIONS: HAP due to biomass fuel has diverse and major impacts on women's health in India. Although challenging, incorporating the agenda of universal clean fuel access or cleaner technology within the broader framework of rural development will go a long way in reducing disease burden.

Heavy metal contamination in the Delhi segment of Yamuna basin.

Concentration of heavy metals (Cd, Ni, Zn, Fe, Cu, Mn, Pb, Cr, Hg and As) in the waters of River Yamuna and in the soil of agricultural fields along its course in Delhi are reported from 13 sites, spread through the Delhi stretch of Yamuna, starting from the Wazirabad barrage till the Okhla barrage. Varying concentration of heavy metals was found. Peaks were observed in samples collected downstream of Wazirabad and Okhla barrage, indicating the anthropogenic nature of the contamination. The Wazirabad section of the river receives wastewater from Najafgarh and its supplementary drains, whereas the Shahdara drain releases its pollution load upstream of the Okhla barrage. Average heavy metal concentration at different locations in the river water varied in the order of Fe>Cr>Mn>Zn>Pb>Cu>Ni>Hg>As>Cd. The river basin soil shows higher level of contamination with lesser variation than the water samples among sampling locations, thereby suggesting deposition over long periods of time through the processes of adsorption and absorption. The average heavy metal concentration at different locations in soil varied in the order of Fe>Mn>Zn>Cr>Pb>Ni>Hg>Cu>As>Cd.

Part 2. Time-series study on air pollution and mortality in Delhi.

INTRODUCTION: Air pollution concentrations in most of the megacities in India exceed the air quality guidelines recommended by the World Health Organization and may adversely affect human health in these cities. Particulate matter (PM) is the pollutant of concern in many Indian cities, particularly in the capital city of Delhi, In recent years, several actions have been taken to address the growing air pollution problem in Delhi and other Indian cities; however, few studies have been designed to assess the health effects of air pollution in Indian cities. To bridge the gap in scientific knowledge and add evidence to the ongoing studies in other Asian cities, a retrospective time-series study on air pollution and mortality in Delhi was initiated under the HEI Public Health and Air Pollution in Asia (PAPA) program. APPROACH: The study used retrospective time-series data of air quality and of naturally-occurring deaths recorded in Delhi to identify changes in the daily all-natural-cause mortality rate that could be attributed to changes in air quality. The 3-year study period included the years 2002 through 2004. The methodology involved: (1) collecting data on ambient air quality for major pollutants from all monitoring stations in Delhi; (2) collecting meteorologic data (temperature, humidity, and visibility); (3) collecting daily mortality records from the Registrar of Births and Deaths; (4) statistically analyzing the data using the common protocol for Indian PAPA studies, which included city-specific modifications. RESULTS AND IMPLICATIONS: The study findings showed that increased concentrations of PM with an aerodynamic diameter < or = 10 microg/m3 (PM10) and of nitrogen dioxide (NO2) were associated with increased all-natural-cause mortality. It was found that every 10-microg/m3 change in PM10 was associated with only a 0.15% increase in total all-natural-cause mortality. When NO2 alone was considered in the model, daily all-natural-cause mortality increased 0.84% for every 10-microg/m3 increase in NO2 concentration. No significant effect was observed for changes in sulfur dioxide (SO2) concentrations. The study provides insight into the link between air pollution and mortality in local populations and contributes information to the existing body of knowledge.

Risk to self versus risk to others: how do older drivers compare to others on the road?

BACKGROUND: The objective of this study was to assess the risk of death or nonfatal injury drivers aged >/=65 pose to themselves and to other road users as compared with drivers in younger age groups. METHODS: Crash-related deaths and injuries were separated into two categories: those occurring among the drivers themselves, and those occurring among others, such as passengers, bicyclists, or pedestrians. RESULTS: The number of deaths among others varied by driver's age, with deaths among others decreasing as the driver's age increased. The proportion of deaths among others compared with deaths among drivers also varied by age. For drivers in the youngest three age groups, about two thirds of the deaths were among others (ages 16 to 19, 63.1%; ages 20 to 34, 68.1%; and ages 35 to 59, 66.6%). This proportion declined with age, reaching a low among drivers aged >/=85 years (ages 60 to 74, 52.2%, ages 75 to 84, 37.9%, ages >/=85, 18.9%). When calculating deaths among others per 100 million miles driven, crashes among young (16 to 19) and older (aged >74) drivers were associated with more deaths to others than were crashes among drivers aged 20 to 74. The number of nonfatal injuries among others also declined as age of the driver increased. The number of injuries among others per 100 million miles driven was highest among the youngest (16 to 19) and oldest (>/=85) drivers. CONCLUSIONS: Our findings suggest that older drivers make relatively small contributions to crash-related morbidity and mortality; moreover, their contributions are generally a result of injuries to self rather than to others.