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Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems
BACKGROUND: Estimates of the burden of disease in adults in sub-Saharan Africa largely rely on models of sparse data. We aimed to measure the burden of disease in adults living in a rural area of coastal Kenya with use of linked clinical and demographic surveillance data. METHODS: We used data from...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986034/ https://www.ncbi.nlm.nih.gov/pubmed/24782954 http://dx.doi.org/10.1016/S2214-109X(14)70023-3 |
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author | Etyang, Anthony O Munge, Kenneth Bunyasi, Erick W Matata, Lena Ndila, Carolyne Kapesa, Sailoki Owiti, Maureen Khandwalla, Iqbal Brent, Andrew J Tsofa, Benjamin Kabibu, Pamela Morpeth, Susan Bauni, Evasius Otiende, Mark Ojal, John Ayieko, Philip Knoll, Maria D Smeeth, Liam Williams, Thomas N Griffiths, Ulla K Scott, J Anthony G |
author_facet | Etyang, Anthony O Munge, Kenneth Bunyasi, Erick W Matata, Lena Ndila, Carolyne Kapesa, Sailoki Owiti, Maureen Khandwalla, Iqbal Brent, Andrew J Tsofa, Benjamin Kabibu, Pamela Morpeth, Susan Bauni, Evasius Otiende, Mark Ojal, John Ayieko, Philip Knoll, Maria D Smeeth, Liam Williams, Thomas N Griffiths, Ulla K Scott, J Anthony G |
author_sort | Etyang, Anthony O |
collection | PubMed |
description | BACKGROUND: Estimates of the burden of disease in adults in sub-Saharan Africa largely rely on models of sparse data. We aimed to measure the burden of disease in adults living in a rural area of coastal Kenya with use of linked clinical and demographic surveillance data. METHODS: We used data from 18 712 adults admitted to Kilifi District Hospital (Kilifi, Kenya) between Jan 1, 2007, and Dec 31, 2012, linked to 790 635 person-years of observation within the Kilifi Health and Demographic Surveillance System, to establish the rates and major causes of admission to hospital. These data were also used to model disease-specific disability-adjusted life-years lost in the population. We used geographical mapping software to calculate admission rates stratified by distance from the hospital. FINDINGS: The main causes of admission to hospital in women living within 5 km of the hospital were infectious and parasitic diseases (303 per 100 000 person-years of observation), pregnancy-related disorders (239 per 100 000 person-years of observation), and circulatory illnesses (105 per 100 000 person-years of observation). Leading causes of hospital admission in men living within 5 km of the hospital were infectious and parasitic diseases (169 per 100 000 person-years of observation), injuries (135 per 100 000 person-years of observation), and digestive system disorders (112 per 100 000 person-years of observation). HIV-related diseases were the leading cause of disability-adjusted life-years lost (2050 per 100 000 person-years of observation), followed by non-communicable diseases (741 per 100 000 person-years of observation). For every 5 km increase in distance from the hospital, all-cause admission rates decreased by 11% (95% CI 7–14) in men and 20% (17–23) in women. The magnitude of this decline was highest for endocrine disorders in women (35%; 95% CI 22–46) and neoplasms in men (30%; 9–45). INTERPRETATION: Adults in rural Kenya face a combined burden of infectious diseases, pregnancy-related disorders, cardiovascular illnesses, and injuries. Disease burden estimates based on hospital data are affected by distance from the hospital, and the amount of underestimation of disease burden differs by both disease and sex. FUNDING: The Wellcome Trust, GAVI Alliance. |
format | Online Article Text |
id | pubmed-3986034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Elsevier Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-39860342014-04-27 Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems Etyang, Anthony O Munge, Kenneth Bunyasi, Erick W Matata, Lena Ndila, Carolyne Kapesa, Sailoki Owiti, Maureen Khandwalla, Iqbal Brent, Andrew J Tsofa, Benjamin Kabibu, Pamela Morpeth, Susan Bauni, Evasius Otiende, Mark Ojal, John Ayieko, Philip Knoll, Maria D Smeeth, Liam Williams, Thomas N Griffiths, Ulla K Scott, J Anthony G Lancet Glob Health Articles BACKGROUND: Estimates of the burden of disease in adults in sub-Saharan Africa largely rely on models of sparse data. We aimed to measure the burden of disease in adults living in a rural area of coastal Kenya with use of linked clinical and demographic surveillance data. METHODS: We used data from 18 712 adults admitted to Kilifi District Hospital (Kilifi, Kenya) between Jan 1, 2007, and Dec 31, 2012, linked to 790 635 person-years of observation within the Kilifi Health and Demographic Surveillance System, to establish the rates and major causes of admission to hospital. These data were also used to model disease-specific disability-adjusted life-years lost in the population. We used geographical mapping software to calculate admission rates stratified by distance from the hospital. FINDINGS: The main causes of admission to hospital in women living within 5 km of the hospital were infectious and parasitic diseases (303 per 100 000 person-years of observation), pregnancy-related disorders (239 per 100 000 person-years of observation), and circulatory illnesses (105 per 100 000 person-years of observation). Leading causes of hospital admission in men living within 5 km of the hospital were infectious and parasitic diseases (169 per 100 000 person-years of observation), injuries (135 per 100 000 person-years of observation), and digestive system disorders (112 per 100 000 person-years of observation). HIV-related diseases were the leading cause of disability-adjusted life-years lost (2050 per 100 000 person-years of observation), followed by non-communicable diseases (741 per 100 000 person-years of observation). For every 5 km increase in distance from the hospital, all-cause admission rates decreased by 11% (95% CI 7–14) in men and 20% (17–23) in women. The magnitude of this decline was highest for endocrine disorders in women (35%; 95% CI 22–46) and neoplasms in men (30%; 9–45). INTERPRETATION: Adults in rural Kenya face a combined burden of infectious diseases, pregnancy-related disorders, cardiovascular illnesses, and injuries. Disease burden estimates based on hospital data are affected by distance from the hospital, and the amount of underestimation of disease burden differs by both disease and sex. FUNDING: The Wellcome Trust, GAVI Alliance. Elsevier Ltd 2014-04-27 /pmc/articles/PMC3986034/ /pubmed/24782954 http://dx.doi.org/10.1016/S2214-109X(14)70023-3 Text en © 2014 Etyang et al. Open Access article distributed under the terms of CC BY https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Articles Etyang, Anthony O Munge, Kenneth Bunyasi, Erick W Matata, Lena Ndila, Carolyne Kapesa, Sailoki Owiti, Maureen Khandwalla, Iqbal Brent, Andrew J Tsofa, Benjamin Kabibu, Pamela Morpeth, Susan Bauni, Evasius Otiende, Mark Ojal, John Ayieko, Philip Knoll, Maria D Smeeth, Liam Williams, Thomas N Griffiths, Ulla K Scott, J Anthony G Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems |
title | Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems |
title_full | Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems |
title_fullStr | Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems |
title_full_unstemmed | Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems |
title_short | Burden of disease in adults admitted to hospital in a rural region of coastal Kenya: an analysis of data from linked clinical and demographic surveillance systems |
title_sort | burden of disease in adults admitted to hospital in a rural region of coastal kenya: an analysis of data from linked clinical and demographic surveillance systems |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986034/ https://www.ncbi.nlm.nih.gov/pubmed/24782954 http://dx.doi.org/10.1016/S2214-109X(14)70023-3 |
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