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A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010

INTRODUCTION: Climate and weather variability can have significant health consequences of increased morbidity and mortality. However, today the impact of climate and weather variability, and consequentially, of climate change on population health in sub-Saharan Africa is not well understood. In this...

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Autores principales: Azongo, Daniel K., Awine, Timothy, Wak, George, Binka, Fred N., Oduro, Abraham Rexford
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Co-Action Publishing 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3508691/
https://www.ncbi.nlm.nih.gov/pubmed/23195508
http://dx.doi.org/10.3402/gha.v5i0.19073
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author Azongo, Daniel K.
Awine, Timothy
Wak, George
Binka, Fred N.
Oduro, Abraham Rexford
author_facet Azongo, Daniel K.
Awine, Timothy
Wak, George
Binka, Fred N.
Oduro, Abraham Rexford
author_sort Azongo, Daniel K.
collection PubMed
description INTRODUCTION: Climate and weather variability can have significant health consequences of increased morbidity and mortality. However, today the impact of climate and weather variability, and consequentially, of climate change on population health in sub-Saharan Africa is not well understood. In this study, we assessed the association of daily temperature and precipitation with daily mortality by age and sex groups in Northern Ghana. METHODS: We analysed daily mortality and weather data from 1995 to 2010. We adopted a time-series Poisson regression approach to examine the short-term association of daily mean temperature and daily mean precipitation with daily mortality. We included time factors and daily lagged weather predictors. The correlation between lagged weather predictors was also considered. RESULTS: For all populations, a statistically significant association of mean daily temperature with mortality at lag days 0–1 was observed below and above the 25th (27.48°C) and 75th (30.68°C) percentiles (0.19%; 95% confidence interval CI: 0.05%, 0.21%) and (1.14%; 95% CI: 0.12%, 1.54%), respectively. We also observed a statistically significant association of mean daily temperature above 75th percentile at lag days 2–6 and lag days 7–13 (0.32%; 95% CI: 0.16%, 0.25%) and (0.31% 95% CI: 0.14%, 0.26%), respectively. A 10 mm increase in precipitation was significantly associated with a 1.71% (95% CI: 0.10%, 3.34.9%) increase in mortality for all ages and sex groups at lag days 2–6. Similar results were also observed at lag days 2–6 and 14–27 for males, 2.92% (95% CI: 0.80%, 5.09%) and 2.35% (95% CI: 0.28%, 4.45%). CONCLUSION: Short-term weather variability is strongly associated with mortality in Northern Ghana. The associations appear to differ among different age and sex groups. The elderly and young children were found to be more susceptible to short-term temperature-related mortality. The association of precipitation with mortality is more pronounced at the short-term for all age and sex groups and in the medium short-term among males. Reducing exposure to extreme temperature, particularly among the elderly and young children, should reduce the number of daily deaths attributable to weather-related mortality.
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spelling pubmed-35086912012-11-28 A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010 Azongo, Daniel K. Awine, Timothy Wak, George Binka, Fred N. Oduro, Abraham Rexford Glob Health Action CLIMO Study Supplement INTRODUCTION: Climate and weather variability can have significant health consequences of increased morbidity and mortality. However, today the impact of climate and weather variability, and consequentially, of climate change on population health in sub-Saharan Africa is not well understood. In this study, we assessed the association of daily temperature and precipitation with daily mortality by age and sex groups in Northern Ghana. METHODS: We analysed daily mortality and weather data from 1995 to 2010. We adopted a time-series Poisson regression approach to examine the short-term association of daily mean temperature and daily mean precipitation with daily mortality. We included time factors and daily lagged weather predictors. The correlation between lagged weather predictors was also considered. RESULTS: For all populations, a statistically significant association of mean daily temperature with mortality at lag days 0–1 was observed below and above the 25th (27.48°C) and 75th (30.68°C) percentiles (0.19%; 95% confidence interval CI: 0.05%, 0.21%) and (1.14%; 95% CI: 0.12%, 1.54%), respectively. We also observed a statistically significant association of mean daily temperature above 75th percentile at lag days 2–6 and lag days 7–13 (0.32%; 95% CI: 0.16%, 0.25%) and (0.31% 95% CI: 0.14%, 0.26%), respectively. A 10 mm increase in precipitation was significantly associated with a 1.71% (95% CI: 0.10%, 3.34.9%) increase in mortality for all ages and sex groups at lag days 2–6. Similar results were also observed at lag days 2–6 and 14–27 for males, 2.92% (95% CI: 0.80%, 5.09%) and 2.35% (95% CI: 0.28%, 4.45%). CONCLUSION: Short-term weather variability is strongly associated with mortality in Northern Ghana. The associations appear to differ among different age and sex groups. The elderly and young children were found to be more susceptible to short-term temperature-related mortality. The association of precipitation with mortality is more pronounced at the short-term for all age and sex groups and in the medium short-term among males. Reducing exposure to extreme temperature, particularly among the elderly and young children, should reduce the number of daily deaths attributable to weather-related mortality. Co-Action Publishing 2012-11-23 /pmc/articles/PMC3508691/ /pubmed/23195508 http://dx.doi.org/10.3402/gha.v5i0.19073 Text en © 2012 Daniel K. Azongo et al. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle CLIMO Study Supplement
Azongo, Daniel K.
Awine, Timothy
Wak, George
Binka, Fred N.
Oduro, Abraham Rexford
A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010
title A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010
title_full A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010
title_fullStr A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010
title_full_unstemmed A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010
title_short A time series analysis of weather variability and all-cause mortality in the Kasena-Nankana Districts of Northern Ghana 1995–2010
title_sort time series analysis of weather variability and all-cause mortality in the kasena-nankana districts of northern ghana 1995–2010
topic CLIMO Study Supplement
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3508691/
https://www.ncbi.nlm.nih.gov/pubmed/23195508
http://dx.doi.org/10.3402/gha.v5i0.19073
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