br Role of the authors Alex Padovano

Role of the authors Alex Padovano: Performed literature search in 13 languages, selected papers for further review, entered eligible case reports in Excel spreadsheet, performed basic statistical analyses, created Fig. 1. Ying Zhou: Chose and performed statistical tests and created Table 1 and Figs. 2–4.
Acknowledgments The authors wish to thank the Marvin and Kay Lichtman Foundation for financial support of the statistical analysis. We would also like to thank Jose Antonio Rojas Suarez MD MSc, Assistant Professor in intensive care and obstetric medicine at Universidad de Cartagena, Colombia for translation of three Spanish language articles, and Language Scientific, Inc. of Medford Massachusetts for translation work on three Portuguese and four German case reports.
Introduction Ambient temperature increase is an important public health concern, associated with substantial death and illness (Basu and Samet, 2002a). Globally, the average temperature increased by 0.85°C between 1880 and 2012 (IPCC, 2013). Across most land areas, projections indicate an increase in the magnitude and frequency of hot days in the late 21st century (IPCC, 2013). Furthermore, across many regions, low temperatures also contribute greatly to the current burden from total mortality (Gasparrini et al., 2015). Understanding the health risks associated with high and low temperatures on elderly people is vital for preventing heat and cold-related deaths and illnesses in this vulnerable population (Basu et al., 2005). Elderly vulnerability is attributable to physiological and social factors, including; living alone, multiple co-morbidities and high medication use, slow physiological Radicicol and behavioural response to thermal stress, limited access to medical care and housing with heating or cooling. Forecasts predict an unprecedented rate of population ageing driven by lengthening life expectancy, particularly in urban areas. The 60+ age group is expected to comprise 21.1% of the population by 2050 (United Nations, 2013). As people live longer, the global burden of chronic and degenerative disease will increase. The predominant contributors to the global burden of disease in the elderly are cardiovascular disease, malignant neoplasms, chronic respiratory diseases, musculoskeletal diseases and neurological and mental diseases (Prince et al., 2015). Two recent reviews describe temperature effects on elderly people\'s health. A meta-analysis by Yu et al. report greater elderly risk (65+) for all-cause heat-related mortality (2–5% per 1°C increase in temperature) compared to all-cause cold-induced mortality in the 50+ age group (1–2% per 1°C decrease in temperature) (Yu et al., 2012). The review of Astrom and colleagues asserts elderly people (65+) are at greater risk of mortality and morbidity during exposure to heat waves than younger people (Åström et al., 2011). Because heat and cold waves only contribute to a small proportion of excess deaths (Gasparrini et al., 2015), we focused on the association between exposure to non-optimum high and low temperatures rather than anomalous temperature events on health. Previous reviews have excluded critical epidemiological studies with information on the underlying cause of death. Cause-specific health impacts of temperature on the elderly have been reported sporadically, but coherent effort to integrate these has so far been lacking. Here we present a systematic review and meta-analysis with quantitative evidence on the effects of high and low ambient temperature (excluding heat and cold waves) on many cause-specific mortality and morbidity outcomes in the elderly.
Methods
Results The systematic search retrieved 4984 mortality papers and 3777 morbidity papers. Of the 25 mortality and 35 morbidity papers α-Amanitin fit the inclusion and exclusion criteria, 18 mortality and 31 morbidity publications were suitable for meta-analysis (Fig. 1). The characteristics of studies investigating the effects of high and low temperature on cause-specific mortality and morbidity in the elderly are summarised in Table 1 (see also Supplementary File 2). The locations studied were dispersed across Europe, Asia, North and South America, but not Africa. We applied the Köppen–Geiger classification (Kottek et al., 2006) to further investigate geographic spread by five climate zones; ‘A-Equatorial’, ‘B-Arid’, ‘C-Temperate’, ‘D-Snow’ and ‘E-Polar’ (Fig. 2). Two studies [study IDs 2,39] are located in equatorial areas and one [study ID 1] in the arid zone. Clustering in the snow and temperate zones reflect the uneven distribution of study locations. The duration of the time-series ranged from 3 to 26years. Studies used various forms of ambient temperature as the exposure. Mean daily ambient temperature was the most common exposure (28 studies). Apparent temperature (also termed heat index), a combined metric of temperature and humidity used to gauge human discomfort, was also common. Diurnal temperature range (DTR) an exposure accounting for temperature variability; the difference between daily maximum and minimum temperatures, was applied by six studies [study IDs 4,11,23,27,29,34]. A detailed analysis of exposure measures and study design/statistical modelling are in Supplementary Files 3 and 4.