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Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou.

ABSTRACT: BACKGROUND: Although many studies have documented health effects of ambient temperature, little evidence is available in subtropical or tropical regions, and effect modifiers remain uncertain. We examined the effects of daily mean temperature on mortality and effect modification in the subtropical city of Guangzhou, China. METHODS: A Poisson regression model combined with distributed lag non-linear model was applied to assess the non-linear and lag patterns of the association between daily mean temperature and mortality from 2003 to 2007 in Guangzhou. The case-only approach was used to determine whether the effect of temperature was modified by individual characteristics, including sex, age, educational attainment and occupation class. RESULTS: Hot effect was immediate and limited to the first 5 days, with an overall increase of 15.46% (95% confidence interval: 10.05% to 20.87%) in mortality risk comparing the 99th and the 90th percentile temperature. Cold effect persisted for approximately 12 days, with a 20.39% (11.78% to 29.01%) increase in risk comparing the first and the 10th percentile temperature. The effects were especially remarkable for cardiovascular and respiratory mortality. The effects of both hot and cold temperatures were greater among the elderly. Females suffered more from hot-associated mortality than males. We also found significant effect modification by educational attainment and occupation class. CONCLUSIONS: There are significant mortality effects of hot and cold temperatures in Guangzhou. The elderly, females and subjects with low socioeconomic status have been identified as especially vulnerable to the effect of ambient temperatures.

SUBMITTER: Yang J

PROVIDER: S-EPMC3511876 | biostudies-other | 2012

REPOSITORIES: biostudies-other

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Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou.

Yang Jun J Ou Chun-Quan CQ Ding Yan Y Zhou Ying-Xue YX Chen Ping-Yan PY

Environmental health : a global access science source 20120914

<h4>Background</h4>Although many studies have documented health effects of ambient temperature, little evidence is available in subtropical or tropical regions, and effect modifiers remain uncertain. We examined the effects of daily mean temperature on mortality and effect modification in the subtropical city of Guangzhou, China.<h4>Methods</h4>A Poisson regression model combined with distributed lag non-linear model was applied to assess the non-linear and lag patterns of the association betwee ...[more]

PMID: 22974173

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Project description:Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature) on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang'an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM) were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0-21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08) increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69) increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22) increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38) increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26) increase in ischemic heart disease (IHD) mortality. For hot effects over lag 0-7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96) increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16) increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59) increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5) increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87) increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and that mean temperature had better predictive ability than minimum and maximum temperature in the association between temperature and mortality.

Project description:BackgroundMalaria transmission is strongly determined by the environmental temperature and the environment is rarely constant. Therefore, mosquitoes and parasites are not only exposed to the mean temperature, but also to daily temperature variation. Recently, both theoretical and laboratory work has shown, in addition to mean temperatures, daily fluctuations in temperature can affect essential mosquito and parasite traits that determine malaria transmission intensity. However, so far there is no epidemiological evidence at the population level to this problem.MethodsThirty counties in southwest China were selected, and corresponding weekly malaria cases and weekly meteorological variables were collected from 2004 to 2009. Particularly, maximum, mean and minimum temperatures were collected. The daily temperature fluctuation was measured by the diurnal temperature range (DTR), the difference between the maximum and minimum temperature. The distributed lag non-linear model (MDLNM) was used to study the correlation between weekly malaria incidences and weekly mean temperatures, and the correlation pattern was allowed to vary over different levels of daily temperature fluctuations.ResultsThe overall non-linear patterns for mean temperatures are distinct across different levels of DTR. When under cooler temperature conditions, the larger mean temperature effect on malaria incidences is found in the groups of higher DTR, suggesting that large daily temperature fluctuations act to speed up the malaria incidence in cooler environmental conditions. In contrast, high daily fluctuations under warmer conditions will lead to slow down the mean temperature effect. Furthermore, in the group of highest DTR, 24-25°C or 21-23°C are detected as the optimal temperature for the malaria transmission.ConclusionThe environment is rarely constant, and the result highlights the need to consider temperature fluctuations as well as mean temperatures, when trying to understand or predict malaria transmission. This work may be the first epidemiological study confirming that the effect of the mean temperature depends on temperature fluctuations, resulting in relevant evidence at the population level.

Dataset Information

Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou.

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Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou.

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