Using Annual Data to Estimate the Public Health Impact of Extreme Temperatures

Abstract

Short-term associations between both hot and cold ambient temperatures and higher mortality have been found worldwide. Few studies have examined these associations on longer time scales. Age-standardized mortality rates (ASMRs) were calculated for 1976-2012 for Hong Kong SAR, People's Republic of China, defining "annual" time periods in 2 ways: from May through April of the following year and from November through October. Annual frequency and severity of extreme temperatures were summarized by using a degree-days approach with extreme heat expressed as annual degree-days >29.3°C and cold as annual degree-days <27.5°C. For example, a day with a mean temperature of 25.0°C contributes 2.5 cold degree-days to the annual total. Generalized additive models were used to estimate the association between annual hot and cold degree-days and the ASMR, with adjustment for long-term trends. Increases of 10 hot or 200 cold degree-days in an annual period, the approximate interquartile ranges for these variables, were significantly (all P's ≤ 0.011) associated with 1.9% or 3.1% increases, respectively, in the annual ASMR for the May-April analyses and with 2.2% or 2.8% increases, respectively, in the November-October analyses. Associations were stronger for noncancer and elderly mortality. Mortality increases associated with extreme temperature are not simply due to short-term forward displacement of deaths that would have occurred anyway within a few weeks.

Longer-Term Impact of High and Low Temperature on Mortality: An International Study to Clarify Length of Mortality Displacement

“…Broadly, statistical methods follow those of the previous single-location annual studies ( Goggins et al 2015 ; Rehill et al 2015 ). Mortality and temperature daily series were collapsed to an annual series using two different year dividers: a ) starting years at the beginning of summer (the month before that including the summer solstice, May, in the northern hemisphere) to allow maximum time for shorter-term displacement of heat-related deaths to be discounted; b ) similarly, starting years at the beginning of winter (November) for optimal cold analysis.…”

“…In model (1), a Gaussian distribution was adopted in preference to the quasi-Poisson models used in daily analysis for modeling simplicity and because the large size of annual death counts made the Gaussian approximation very good ( Goggins et al 2015 ; Rehill et al 2015 ). For presentation of results, we transform the coefficients and to percent excess relative risks (ERR%) per degree of annual high and low temperatures: .…”

“…Two published single-city studies have used this method. In both London between 1947 and 2006 ( Rehill et al 2015 ) and Hong Kong from 1976 to 2012 ( Goggins et al 2015 ), years with cold winters and those with hot summers were associated with high mortality, though in temperate London, the association with heat was not significant. Those studies were not linked to daily studies, so it was not possible to directly estimate from them whether a proportion of heat and cold deaths found in daily studies were nevertheless displaced by less than 1 y.…”

The influence of pre-existing health conditions on short-term mortality risks of temperature: Evidence from a prospective Chinese elderly cohort in Hong Kong

“…Daily mean air temperature and relative humidity in percent were measured by digital thermometers with platinum resistance sensors at the Hong Kong Observatory. The historical temperature data have been used in the previous population studies of temperature effects in Hong Kong (Goggins et al, 2015;Yi and Chan, 2014).…”

Assessment of the Effects of Severe Winter Disasters (Dzud) on Public Health in Mongolia on the Basis of Loss of Livestock

“…On the other hand, the cold environment was not influential on infant mortality, although it is said that low ambient temperature is related to many kinds of mortality. 3 This may be because the period of this cold disaster was of a relatively short duration (5 months) compared to the time before last, and we performed the analysis without the sample into rural and urban areas.…”