Extreme heat and heat waves have been established as disasters which can lead to a great loss of life. Several studies over the years, both within and outside of India, have shown how extreme heat events lead to an overall increase in mortality. However, the impact of extreme heat, similar to other disasters, depends upon the vulnerability of the population. This study aims to assess the extreme heat vulnerability of the population of four cities with different characteristics across India. This cross-sectional study included 500 households from each city across the urban localities (both slum and non-slum) of Ongole in Andhra Pradesh, Karimnagar in Telangana, Kolkata in West Bengal and Angul in Odisha. Twenty-one indicators were used to construct a household vulnerability index to understand the vulnerability of the cities. The results have shown that the majority of the households fell under moderate to high vulnerability level across all the cities. Angul and Kolkata were found to be more highly vulnerable as compared to Ongole and Karimnagar. Further analysis also revealed that household vulnerability is more significantly related to adaptive capacity than sensitivity and exposure. Heat Vulnerability Index can help in identifying the vulnerable population and scaling up adaptive practices.

Background: Extreme heat and heat illness are becoming very frequent in India. We aimed to identify the factors associated with heat illness and the coping practices among city dwellers of Odisha, India during the summer. Methods: A cross-sectional study included 766 households (HHs) in twin cities of Odisha covering a population of 1099 (slum: 404 and non-slum: 695) in the year 2017. We collected information on sociodemographic, household characteristics, coping practices to heat and the heat illness history reported during the summer. Multivariate logistic regression accounting for clustering effects at the household and slum levels was used to identify the associated factors of heat illness after adjustment of other variables. Result: Nearly, 49% of the study participants were female and the mean age was 38.36 years (95% confidence interval (CI): 37.33–39.39 years). A significant difference of living environment was seen across the groups. More than two-thirds of the study participants at least once had heat illness. In the non-slum population, males (adjusted odds ratio (aOR): 3.56; 95% CI: 2.39–5.29), persons under medication (aOR: 3.09; 95% CI: 1.15–8.29), and chronic conditions had higher association with heat illness. Whereas, in the slum population, having a kitchen outside the home (aOR: 1.63; 95% CI: 1.02–3.96) and persons with chronic conditions were positively associated with heat illness. Use of cooling practices in slum areas reduced the risk of heat illness by 60%. Conclusion: Heat illness is associated with the living environment and physical health of the individuals. Identifying the vulnerable population and scaling up adaptive practices can strengthen the public health preparedness.

High ambient temperature is a key public health problem, as it is linked to high heat-related morbidity and mortality. We intended to recognize the characteristics connected to heat vulnerability and the coping practices among Indian urbanites of Angul and Kolkata. In 2020, a cross-sectional design was applied to 500 households (HHs) each in Angul and Kolkata. Information was gathered on various characteristics including sociodemographics, household, exposure, sensitivity, and coping practices regarding heat and summer heat illness history, and these characteristics led to the computation of a heat vulnerability index (HVI). Bivariate and multivariable logistic regression analyses were used with HVI as the outcome variable to identify the determinants of high vulnerability to heat. The results show that some common and some different factors are responsible for determining the heat vulnerability of a household across different cities. For Angul, the factors that influence vulnerability are a greater number of rooms in houses, the use of cooling methods such as air conditioning, having comorbid conditions, the gender of the household head, and distance from nearby a primary health centre (PHC). For Kolkata, the factors are unemployment, income, the number of rooms, sleeping patterns, avoidance of nonvegetarian food, sources of water, comorbidities, and distance from a PHC. The study shows that every city has a different set of variables that influences vulnerability, and each factor should be considered in design plans to mitigate vulnerability to extreme heat.

Background: High ambient temperature is a significant public health problem as it is associated with high heat related morbidity and mortality. We aimed to identify the factors associated with heat vulnerability, and the coping practices among Indian urbanites of Angul, and Kolkata.Methods: A cross-sectional study included 500 households (HHs) from each city with almost equal distribution of slum and non-slum HHs in the year 2020. Information was collected on sociodemographic, household characteristics, exposure, sensitivity and coping practices to heat and the heat illness history reported during the summer. Factors were computed to a Heat Vulnerability Index (HVI). Bi-variate and multi-variable logistic regression analysis used with HVI as the outcome variable to identify the determinants of high vulnerability to heat.Result: The results have shown that some common and some different factors are responsible for determining heat vulnerability of a household across different cities. For Angul, the factors which influence vulnerability are more number of rooms in houses, use of cooling methods like ACs, having co-morbid conditions, gender of household head and distance from nearby PHC. For Kolkata, the factors are unemployment, income, number of rooms, sleeping pattern, avoidance of non-veg food, sources of water, Co-morbidities and distance from the PHC.Conclusion: The study shows that every city has different set of variables that influence vulnerability and each factor should be considered for designing plans to mitigate vulnerability to extreme heat.

Review question / Objective: Clinically, knee is the most common site of osteoarthritis (OA), followed by the hand and hip. The basic research question of our study: Is total knee replacement (TKR) associated with better clinical outcomes and quality of life among patients with OA knee aged 40 and above, not responding to non-surgical management, is? Based on this review question, the following objectives are proposed, 1. to refresh the evidence on clinical effectiveness of TKR and 2. to explore the determinants influencing its success. Population Patient aged >= 40 years with OA Knee of all Kellgren Lawrence grade. Intervention Total Knee Replacement (TKR) Comparator Pre-TKR Outcome Clinical effectiveness in terms of improvement in QoL.