IntroductionClimate change and rapid population ageing are significant public health challenges. Understanding which health problems are affected by temperature is important for preventing heat and cold-related deaths and illnesses, particularly in the elderly. Here we present a systematic review and meta-analysis on the effects of ambient hot and cold temperature (excluding heat/cold wave only studies) on elderly (65 + years) mortality and morbidity.MethodsTime-series or case-crossover studies comprising cause-specific cases of elderly mortality (n = 3,933,398) or morbidity (n = 12,157,782) were pooled to obtain a percent change (%) in risk for temperature exposure on cause-specific disease outcomes using a random-effects meta-analysis.ResultsA 1 °C temperature rise increased cardiovascular (3.44%, 95% CI 3.10–3.78), respiratory (3.60%, 3.18–4.02), and cerebrovascular (1.40%, 0.06–2.75) mortality. A 1 °C temperature reduction increased respiratory (2.90%, 1.84–3.97) and cardiovascular (1.66%, 1.19–2.14) mortality. The greatest risk was associated with cold-induced pneumonia (6.89%, 20–12.99) and respiratory morbidity (4.93% 1.54–8.44). A 1 °C temperature rise increased cardiovascular, respiratory, diabetes mellitus, genitourinary, infectious disease and heat-related morbidity.DiscussionElevated risks for the elderly were prominent for temperature-induced cerebrovascular, cardiovascular, diabetes, genitourinary, infectious disease, heat-related, and respiratory outcomes. These risks will likely increase with climate change and global ageing.

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Improving drug availability and financial accessibility to health services have been identified as the two main priorities for health policy action. Policy-makers should respect these patient preferences to deliver effective improvement of the quality of care as a potential means to increase utilization of health care.

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IntroductionDengue is currently a major public health burden in Asia Pacific Region. This study aims to establish an association between dengue incidence, mean temperature and precipitation, and further discuss how weather predictors influence the increase in intensity and magnitude of dengue in Singapore during the period 2000–2007.Materials and methodsWeekly dengue incidence data, daily mean temperature and precipitation and the midyear population data in Singapore during 2000–2007 were retrieved and analysed. We employed a time series Poisson regression model including time factors such as time trends, lagged terms of weather predictors, considered autocorrelation, and accounted for changes in population size by offsetting.ResultsThe weekly mean temperature and cumulative precipitation were statistically significant related to the increases of dengue incidence in Singapore. Our findings showed that dengue incidence increased linearly at time lag of 5–16 and 5–20 weeks succeeding elevated temperature and precipitation, respectively. However, negative association occurred at lag week 17–20 with low weekly mean temperature as well as lag week 1–4 and 17–20 with low cumulative precipitation.DiscussionAs Singapore experienced higher weekly mean temperature and cumulative precipitation in the years 2004–2007, our results signified hazardous impacts of climate factors on the increase in intensity and magnitude of dengue cases. The ongoing global climate change might potentially increase the burden of dengue fever infection in near future.