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The relationship between diabetes mellitus and short-term exposure to extreme temperatures remains controversial. A systematic review and meta-analysis were performed to assess the association between extreme temperatures and diabetes mellitus morbidity and mortality. PubMed, Embase, the Cochrane Library, Web of Science and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched since inception to January 1, 2019, and updated on November 17, 2020. The results were combined using random effects model and reported as relative risk (RR) with 95% confidence interval (CI). 32 studies met the included criteria. (1) Both heat and cold exposures have impact on diabetes. (2) For heat exposure, the subgroup analysis revealed that the effect on diabetes mortality (RR = 1.139, 95% CI: 1.089–1.192) was higher than morbidity (RR = 1.012, 95% CI: 1.004–1.019). (3) With the increase of definition threshold, the impact of heat exposure on diabetes rised. (4) A stronger association between heat exposure and diabetes was observed in the elderly (≥ 60 years old) (RR = 1.040, 95% CI: 1.017–1.064). In conclusion, both short-term exposure to heat and cold temperatures have impact on diabetes. The elderly is the vulnerable population of diabetes exposure to heat temperature. Developing definitions of heatwaves at the regional level are suggested.

Heatwaves and greenness have been shown to affect health, but the evidence on their joint effects is limited. We aim to assess the associations of the combined exposure to greenness and heatwaves. We utilized five waves (February 2000-October 2014) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a prospective cohort of older adults aged 65. We defined heatwaves as the daily maximum temperature ≥92.5th percentile with duration ≥3 days. We calculated the number of heatwave days in one year before death to and cumulative Normalized Difference Vegetation Index (NDVI) during follow-up to assess individual long-term exposure to heatwaves and greenness. Cox proportional hazards models were used to assess the effects of greenness, heatwaves, and their interaction on mortality, adjusted for covariates. We conducted subgroup analyses by residence, gender, and age. There were 20,758 participants in our study, totaling 67,312 person-years of follow-up. The mean NDVI was 0·41 (SD 0.13), and the mean number of heatwave days was 8.92 (2.04). In the adjusted model, the mortality hazard ratio (HR) for each 3-day increase in heatwave days was 1.04 (95% CI 1.04, 1.05), each 0.1-unit decrease in cumulative NDVI was 1.06 (1.05, 1.07). In the adjusted model with an interaction term, the HR for the interaction term was 1.01 (1.01, 1.02) with a p-value less than 0.001. In our subgroup analyses, the HR for each 3-day increase in heatwave days was higher in urban areas than in rural areas (1.06 vs. 1.03), and the HR for 0.1-unit decrease in NDVI was higher in urban areas than in rural areas (1.08 vs. 1.04). Greenness can protect against the effect of heatwaves on mortality, and heatwaves affect the health effects of greenness. Urban dwellers have a higher response to the detrimental effect of heatwaves and a higher marginal benefit from greenness exposure.

Increasingly hotter temperatures threaten the environment and pose serious risks to human health. From contending with damaged crops and loss of work due to extreme weather to working in life-threateningly hot and humid temperatures, agricultural farmworkers are on the front lines of this harsh reality.

The 2015 heat wave resulted in an estimated over 1200 deaths during the month of June. However, there were no records on the spatial distribution of the effects of this heat wave. An analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) daily data was conducted to identify regions that experienced above normal temperatures in 2015. An analysis of the monthly averages showed that in general April and May were the warmer months in Karachi, unlike the case in 2015. In addition, the general warm trends were common in the highly industrialised Sindh Industrial Trading Estate (SITE) and Liaquatabad towns, while Gadap, with its mostly barren land, and New Karachi also experience higher temperatures. Coastal towns were naturally cooler and more habitable in the given scenario. A count of the spatial presence of health facilities for the city was also extracted where Gadap and Korangi were poorly served while the more affluent towns of Defence Housing Authority (DHA) and Gulshan-e-Iqbal appeared to be better served.

Extreme summertime heat is a significant public health threat that disproportionately impacts vulnerable urban populations. Research on health impacts of climate change (including increasing intensity, duration, and frequency of hot weather) is sometimes designed and implemented without the involvement of the communities being studied, i.e., &ldquo, community-placed&rdquo, not &ldquo, community-based.&rdquo, We describe how the Heatwaves, Housing, and Health: Increasing Climate Resiliency in Detroit (HHH) partnership engaged relevant communities by integrating a community-based participatory research (CBPR) approach into an existing, academic-designed research project through a steering committee of community and academic partners. Using a case study approach, we analyze program documentation, partnership evaluation questionnaires, and HHH steering committee meeting notes. We describe the CBPR process by which we successfully collected research data in Detroit during summer 2016, engaged in collaborative analysis of data, and shared results with Detroit residents. Evaluations of the partnership over 2 years show community involvement in research, enhanced capacities, success in securing new grant funding, and ways that CBPR strengthened the validity, relevance, and translation of research. Engaging communities as equal partners using CBPR, even after a study is underway, can strengthen research to understand and address the impacts of extreme heat on health and equity in urban communities.

Weather conditions, especially temperature and precipitation, play a critical role in shaping patterns of diarrhoeal diseases. They determine the frequency of outbreaks, and the spatial and seasonal distribution of cases. Not surprisingly, it is anticipated that the burden of diarrhoeal diseases will escalate with climate change, in tandem with gradual increments in mean temperatures, but also during episodic heatwaves. The degree and nature of this escalation will, however, vary with the mix of pathogens in an area, the quality of sanitation services, food hygiene regulations and their enforcement, and the age structure of the population, among other factors. Understanding these patterns can inform the design of measures to prevent and control heat-related diarrhoea. In this editorial, we sum evidence on the heat sensitivity of enteric infections in South Africa (SA) and other parts of sub-Saharan Africa (19 studies), drawing on articles located in a systematic review (methods detailed in Manyuchi et al. [1]), and consider the implications of these findings for control of diarrhoea in SA in the context of climate change.

Objectives In this multicity study, we aimed to elucidate the city-specific factors affecting the association of high ambient temperature with ambulance dispatches due to acute illnesses. Methods We used the data of ambulance dispatches in 27 cities in Japan with more than 500,000 population excluding Tokyo, from May to September from 2012 to 2015. We included patients 20 years and older (≥20 years) and stratified them into three age groups (20-59, 60-79, and ≥80 years). We explored the city-specific pattern of the daily relative temperature (in temperature percentiles) and the risk of ambulance dispatches for each age group using a distributed lag nonlinear model and estimated the city-specific relative risks of ambulance dispatches at the 95/99 percentile temperature compared with the 77.6 percentile temperature defined as the reference temperature (Tref). Then, the estimates were combined by performing meta-analyses for each age group. We also applied meta-regression models to explore whether the city-specific characteristics modified the association of temperature with ambulance dispatches. Results The relative risks of the 95th percentile with respect to Tref were 1.14 (95% confidence interval (CI): 1.12, 1.16), 1.16 (95% CI: 1.13, 1.20), 1.13 (95% CI: 1.10, 1.16), and 1.13 (95% CI: 1.00, 1.16), for all-age (≥20) and age-stratified groups (20-59, 60-79, and ≥80 years), respectively. We observed a higher relative risk for the ≥20 years age group in the cities with higher proportions of single-elderly, single-mother, and single-father households. We also found that the relative risk for the 20-59 years age group was higher in the cities with a higher proportion of blue-collar workers. Conclusions The present study provides insights into city-specific characteristics modifying heat-related health effects.