The effect of temperature on mortality in rural Bangladesh–a population-based time-series study. Hashizume, M., Wagatsuma, Y., Hayashi, T., Saha, S. K., Streatfield, K., & Yunus, M. International Journal of Epidemiology, 38(6):1689–1697, December, 2009. doi abstract bibtex BACKGROUND: Studies in urban cities have consistently shown evidence of increased mortality in association with hot and cold weather. However, few studies have examined temperature-mortality relationship in the rural areas of developing countries. In this study we therefore aimed to characterize the daily temperature-mortality relationships in rural Bangladesh. METHODS: A generalized linear Poisson regression model was used to regress a time-series of daily mortality for all-cause and selected causes against temperature, controlling for seasonal and interannual variations, day of week and public holidays. A total of 13 270 all-cause deaths excluding external causes for residents under demographic surveillance in Matlab, Bangladesh were available between January 1994 and December 2002. RESULTS: There was a marked increase in all-cause deaths and deaths due to cardiovascular, respiratory and perinatal causes at low temperatures over a lag of 0-13 days. Every 1 degrees C decrease in mean temperature was associated with a 3.2% (95% CI 0.9-5.5) increase in all-cause mortality. However, there was no clear heat effect on all-cause mortality for any of the lags examined. CONCLUSIONS: This study found that daily mortality increased with low temperatures in the preceding weeks, while there was no association found between high temperatures and daily mortality in rural Bangladesh. Preventive measures during low temperatures should be considered especially for young infants.
@article{hashizume_effect_2009,
title = {The effect of temperature on mortality in rural {Bangladesh}--a population-based time-series study},
volume = {38},
issn = {1464-3685},
doi = {10.1093/ije/dyn376},
abstract = {BACKGROUND: Studies in urban cities have consistently shown evidence of increased mortality in association with hot and cold weather. However, few studies have examined temperature-mortality relationship in the rural areas of developing countries. In this study we therefore aimed to characterize the daily temperature-mortality relationships in rural Bangladesh.
METHODS: A generalized linear Poisson regression model was used to regress a time-series of daily mortality for all-cause and selected causes against temperature, controlling for seasonal and interannual variations, day of week and public holidays. A total of 13 270 all-cause deaths excluding external causes for residents under demographic surveillance in Matlab, Bangladesh were available between January 1994 and December 2002.
RESULTS: There was a marked increase in all-cause deaths and deaths due to cardiovascular, respiratory and perinatal causes at low temperatures over a lag of 0-13 days. Every 1 degrees C decrease in mean temperature was associated with a 3.2\% (95\% CI 0.9-5.5) increase in all-cause mortality. However, there was no clear heat effect on all-cause mortality for any of the lags examined.
CONCLUSIONS: This study found that daily mortality increased with low temperatures in the preceding weeks, while there was no association found between high temperatures and daily mortality in rural Bangladesh. Preventive measures during low temperatures should be considered especially for young infants.},
language = {eng},
number = {6},
journal = {International Journal of Epidemiology},
author = {Hashizume, Masahiro and Wagatsuma, Yukiko and Hayashi, Taiichi and Saha, Sajal K. and Streatfield, Kim and Yunus, Mohammad},
month = dec,
year = {2009},
pmid = {19181749},
keywords = {CK, Untagged},
pages = {1689--1697},
}
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METHODS: A generalized linear Poisson regression model was used to regress a time-series of daily mortality for all-cause and selected causes against temperature, controlling for seasonal and interannual variations, day of week and public holidays. A total of 13 270 all-cause deaths excluding external causes for residents under demographic surveillance in Matlab, Bangladesh were available between January 1994 and December 2002. RESULTS: There was a marked increase in all-cause deaths and deaths due to cardiovascular, respiratory and perinatal causes at low temperatures over a lag of 0-13 days. Every 1 degrees C decrease in mean temperature was associated with a 3.2% (95% CI 0.9-5.5) increase in all-cause mortality. However, there was no clear heat effect on all-cause mortality for any of the lags examined. CONCLUSIONS: This study found that daily mortality increased with low temperatures in the preceding weeks, while there was no association found between high temperatures and daily mortality in rural Bangladesh. Preventive measures during low temperatures should be considered especially for young infants.","language":"eng","number":"6","journal":"International Journal of Epidemiology","author":[{"propositions":[],"lastnames":["Hashizume"],"firstnames":["Masahiro"],"suffixes":[]},{"propositions":[],"lastnames":["Wagatsuma"],"firstnames":["Yukiko"],"suffixes":[]},{"propositions":[],"lastnames":["Hayashi"],"firstnames":["Taiichi"],"suffixes":[]},{"propositions":[],"lastnames":["Saha"],"firstnames":["Sajal","K."],"suffixes":[]},{"propositions":[],"lastnames":["Streatfield"],"firstnames":["Kim"],"suffixes":[]},{"propositions":[],"lastnames":["Yunus"],"firstnames":["Mohammad"],"suffixes":[]}],"month":"December","year":"2009","pmid":"19181749","keywords":"CK, Untagged","pages":"1689–1697","bibtex":"@article{hashizume_effect_2009,\n\ttitle = {The effect of temperature on mortality in rural {Bangladesh}--a population-based time-series study},\n\tvolume = {38},\n\tissn = {1464-3685},\n\tdoi = {10.1093/ije/dyn376},\n\tabstract = {BACKGROUND: Studies in urban cities have consistently shown evidence of increased mortality in association with hot and cold weather. However, few studies have examined temperature-mortality relationship in the rural areas of developing countries. In this study we therefore aimed to characterize the daily temperature-mortality relationships in rural Bangladesh.\nMETHODS: A generalized linear Poisson regression model was used to regress a time-series of daily mortality for all-cause and selected causes against temperature, controlling for seasonal and interannual variations, day of week and public holidays. A total of 13 270 all-cause deaths excluding external causes for residents under demographic surveillance in Matlab, Bangladesh were available between January 1994 and December 2002.\nRESULTS: There was a marked increase in all-cause deaths and deaths due to cardiovascular, respiratory and perinatal causes at low temperatures over a lag of 0-13 days. Every 1 degrees C decrease in mean temperature was associated with a 3.2\\% (95\\% CI 0.9-5.5) increase in all-cause mortality. 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