Impact of heatwaves on all-cause mortality in India: A comprehensive multi-city study.

BACKGROUND: Heatwaves are expected to increase with climate change, posing a significant threat to population health. In India, with the world's largest population, heatwaves occur annually but have not been comprehensively studied. Accordingly, we evaluated the association between heatwaves and all-cause mortality and quantifying the attributable mortality fraction in India. METHODS: We obtained all-cause mortality counts for ten cities in India (2008-2019) and estimated daily mean temperatures from satellite data. Our main extreme heatwave was defined as two-consecutive days with an intensity above the 97th annual percentile. We estimated city-specific heatwave associations through generalised additive Poisson regression models, and meta-analysed the associations. We reported effects as the percentage change in daily mortality, with 95% confidence intervals (CI), comparing heatwave vs non-heatwave days. We further evaluated heatwaves using different percentiles (95th, 97th, 99th) for one, two, three and five-consecutive days. We also evaluated the influence of heatwave duration, intensity and timing in the summer season on heatwave mortality, and estimated the number of heatwave-related deaths. FINDINGS: Among âˆ¼ 3.6 million deaths, we observed that temperatures above 97th percentile for 2-consecutive days was associated with a 14.7 % (95 %CI, 10.3; 19.3) increase in daily mortality. Alternative heatwave definitions with higher percentiles and longer duration resulted in stronger relative risks. Furthermore, we observed stronger associations between heatwaves and mortality with higher heatwave intensity. We estimated that around 1116 deaths annually (95 %CI, 861; 1361) were attributed to heatwaves. Shorter and less intense definitions of heatwaves resulted in a higher estimated burden of heatwave-related deaths. CONCLUSIONS: We found strong evidence of heatwave impacts on daily mortality. Longer and more intense heatwaves were linked to an increased mortality risk, however, resulted in a lower burden of heatwave-related deaths. Both definitions and the burden associated with each heatwave definition should be incorporated into planning and decision-making processes for policymakers.

Climate Change Adaptation: Prehospital Data Facilitate the Detection of Acute Heat Illness in India.

INTRODUCTION: Extreme heat is a significant cause of morbidity and mortality, and the incidence of acute heat illness (AHI) will likely increase secondary to anthropogenic climate change. Prompt diagnosis and treatment of AHI are critical; however, relevant diagnostic and surveillance tools have received little attention. In this exploratory cross-sectional and diagnostic accuracy study, we evaluated three tools for use in the prehospital setting: 1) case definitions; 2) portable loggers to measure on-scene heat exposure; and 3) prevalence data for potential AHI risk factors. METHODS: We enrolled 480 patients who presented to emergency medical services with chief complaints consistent with AHI in Ahmedabad, India, from April-June 2016 in a cross-sectional study. We evaluated AHI case definition test characteristics in reference to trained prehospital provider impressions, compared on-scene heat index measured by portable loggers to weather station measurements, and identified AHI behavioral and environmental risk factors using logistic regression. RESULTS: The case definition for heat exhaustion was 23.8% (12.1-39.5%) sensitive and 93.6% (90.9-95.7%) specific. The positive and negative predictive values were 33.5% (20.8-49.0%) and 90.1% (88.5-91.5%), respectively. Mean scene heat index was 6.7°C higher than the mean station heat index (P < 0.001), and station data systematically underestimated heat exposure, particularly for AHI cases. Heat exhaustion cases were associated with on-scene heat index ≥ 49°C (odds ratio [OR] 2.66 [1.13-6.25], P = 0.025) and a history of recent exertion (OR 3.66 [1.30-10.29], P = 0.014), while on-scene air conditioning was protective (OR 0.29 [0.10-0.85], P = 0.024). CONCLUSION: Systematic collection of prehospital data including recent activity history and presence of air conditioning can facilitate early AHI detection, timely intervention, and surveillance. Scene temperature data can be reliably collected and improve heat exposure and AHI risk assessment. Such data may be important elements of surveillance, clinical practice, and climate change adaptation.

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017.

BACKGROUND: Studies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection. METHODS: We collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987-2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics and heat wave definitions. Using the fittest model, we estimated heat-mortality associations among general population and subpopulations. We also conducted separate analyses for 1987-2002 and 2003-2017 to evaluate temporal heterogeneity. FINDINGS: The model with maximum and minimum temperatures and without heat wave indicator gave the best performance. With this model, we found a substantial and significant increase in mortality rate starting from maximum temperature at 42 °C and from minimum temperature at 28 °C: 1 °C increase in maximum and minimum temperatures at lag 0 were associated with 9.56% (95% confidence interval [CI]: 6.64%, 12.56%) and 9.82% (95% CI: 6.33%, 13.42%) increase in mortality risk, respectively. People aged ≥65 years and lived in South residential zone where most slums were located, were more vulnerable. We observed flatter increases in mortality risk associated with high temperatures comparing the period of 2003-2017 to 1987-2002. INTERPRETATION: The analyses provided better understanding of the relationship of high temperatures with mortality in underdeveloped tropical regions and important implications in developing heat warning system for local government. The proposed CV approaches will benefit future scientific work.

Building Resilience to Climate Change: Pilot Evaluation of the Impact of India's First Heat Action Plan on All-Cause Mortality.

Background: Ahmedabad implemented South Asia's first heat action plan (HAP) after a 2010 heatwave. This study evaluates the HAP's impact on all-cause mortality in 2014-2015 relative to a 2007-2010 baseline. Methods: We analyzed daily maximum temperature (T max)-mortality relationships before and after HAP. We estimated rate ratios (RRs) for daily mortality using distributed lag nonlinear models and mortality incidence rates (IRs) for HAP warning days, comparing pre- and post-HAP periods, and calculated incidence rate ratios (IRRs). We estimated the number of deaths avoided after HAP implementation using pre- and post-HAP IRs. Results: The maximum pre-HAP RR was 2.34 (95%CI 1.98-2.76) at 47°C (lag 0), and the maximum post-HAP RR was 1.25 (1.02-1.53) estimated at 47°C (lag 0). Post-to-pre-HAP nonlagged mortality IRR for T max over 40°C was 0.95 (0.73-1.22) and 0.73 (0.29-1.81) for T max over 45°C. An estimated 1,190 (95%CI 162-2,218) average annualized deaths were avoided in the post-HAP period. Conclusion: Extreme heat and HAP warnings after implementation were associated with decreased summertime all-cause mortality rates, with largest declines at highest temperatures. Ahmedabad's plan can serve as a guide for other cities attempting to increase resilience to extreme heat.

Development of Ahmedabad's Air Information and Response (AIR) Plan to Protect Public Health.

Indian cities struggle with some of the highest ambient air pollution levels in the world. While national efforts are building momentum towards concerted action to reduce air pollution, individual cities are taking action on this challenge to protect communities from the many health problems caused by this harmful environmental exposure. In 2017, the city of Ahmedabad launched a regional air pollution monitoring and risk communication project, the Air Information and Response (AIR) Plan. The centerpiece of the plan is an air quality index developed by the Indian Institute of Tropical Meteorology’s System for Air Quality and Weather Forecasting and Research program that summarizes information from 10 new continuous air pollution monitoring stations in the region, each reporting data that can help people avoid harmful exposures and inform policy strategies to achieve cleaner air. This paper focuses on the motivation, development, and implementation of Ahmedabad’s AIR Plan. The project is discussed in terms of its collaborative roots, public health purpose in addressing the grave threat of air pollution (particularly to vulnerable groups), technical aspects in deploying air monitoring technology, and broader goals for the dissemination of an air quality index linked to specific health messages and suggested actions to reduce harmful exposures. The city of Ahmedabad is among the first cities in India where city leaders, state government, and civil society are proactively working together to address the country’s air pollution challenge with a focus on public health. The lessons learned from the development of the AIR Plan serve as a template for other cities aiming to address the heavy burden of air pollution on public health. Effective working relationships are vital since they form the foundation for long-term success and useful knowledge sharing beyond a single city.

Effects of Occupational Heat Exposure on Traffic Police Workers in Ahmedabad, Gujarat.

One of the most concerning environmental effects of climate change is rising levels of extreme heat, which already poses serious risks in many parts of the world. In June and July 2015, we collected weekly heat exposure data using area and personal temperature monitoring in Ahmedabad, Gujarat. The study was conducted at four different traffic junctions with a cohort of 16 traffic police. For information on health effects, we administered a baseline survey at the start of the study and prospectively followed up with the officers on prevalence of heat-related symptoms. Wet bulb globe temperature (WBGT) levels ranged from 28.2°C to 36.1°C during the study period. Traffic police workers who participated in this study were exposed to WBGT levels higher than the recommended threshold limit value as per American Conference of Governmental Industrial Hygienists guidelines even beyond the hottest months of the season. Our findings suggest that airport measurements by the Indian Meteorological Department may not accurately capture heat exposures among individuals who work in and alongside high-density traffic junctions. Based on our temperature estimates, traffic police are at risk for heat stress. India is likely to experience warmer temperatures and increased heat waves in the coming decades, fueled by climate change. Therefore, it is important to reduce current and future heat-related risks for traffic police workers and similar occupational risk groups by establishing protection strategies. The protocol established in this study for occupational heat exposure assessment could be applied to a larger cohort.

Perceived heat stress and health effects on construction workers.

INTRODUCTION: Increasing heat waves-particularly in urban areas where construction is most prevalent, highlight a need for heat exposure assessment of construction workers. This study aims to characterize the effects of heat on construction workers from a site in Gandhinagar. MATERIALS AND METHODS: This study involved a mixed methods approach consisting of a cross sectional survey with anthropometric measurements (n = 219) and four focus groups with construction workers, as well as environmental measurements of heat stress exposure at a construction site. Survey data was collected in two seasons i.e., summer and winter months, and heat illness and symptoms were compared between the two time periods. Thematic coding of focus group data was used to identify vulnerability factors and coping mechanisms of the workers. Heat stress, recorded using a wet bulb globe temperature monitor, was compared to international safety standards. RESULTS: The survey findings suggest that heat-related symptoms increased in summer; 59% of all reports in summer were positive for symptoms (from Mild to Severe) as compared to 41% in winter. Focus groups revealed four dominant themes: (1) Non-occupational stressors compound work stressors; (2) workers were particularly attuned to the impact of heat on their health; (3) workers were aware of heat-related preventive measures; and (4) few resources were currently available to protect workers from heat stress. Working conditions often exceed international heat stress safety thresholds. Female workers and new employees might be at increased risk of illness or injury. CONCLUSION: This study suggests significant health impacts on construction workers from heat stress exposure in the workplace, showed that heat stress levels were higher than those prescribed by international standards and highlights the need for revision of work practices, increased protective measures, and possible development of indigenous work safety standards for heat exposure.