Logistic Regression Analysis of Mortality Among Fishermen in the Riperian Counties of Lake Victoria, Kenya
Central African Journal of Public Health
Volume 5, Issue 1, February 2019, Pages: 46-51
Received: Dec. 3, 2018; Accepted: Jan. 10, 2019; Published: Jan. 31, 2019
Views 107      Downloads 18
Authors
Opemo Damian Otieno, School of Nursing, Kibabii University, Bungoma, Kenya
Juma Shem Godfrey, Department of Mathematics, Kibabii University, Bungoma, Kenya
Article Tools
Follow on us
Abstract
Fishing as an economic activity has gainful implications to National Development. Mortality instigated by occupational hazards is a current subject of research significance globally. This study made attempts to assess the associations between categorical variables using Logistic Regression. Logistic regression analysis targeting 3058 deceased fishermen was carried out spanning 1998-2000. Associative relationships among categorical variables were determined using Statistical Analysis System (SAS). The findings reveal that the major causes of death were: HIV - related infections (33.8%), drowning (14.3%), pulmonary tuberculosis (12.4%), and malaria (10.4%). Factors influencing HIV - related mortality were: age group (p = 0.0025), Counties of residence (Busia, Kisumu, Migori and Siaya) all of which had similar p value (0.0001). The risk factors associated with deaths due to drowning were: age group (p =<0.0001), use of a combination of sails and paddles (p = <0.0001), use of paddle (p = 0.0003), Secondary education (p = <0.0001) and drinking of alcohol (p = 0.0012).The study concluded that the probability of death occurrence was closely related to HIV infections over the area of study.
Keywords
Fishermen, Mortality, Lake Victoria, Logistic Regression
To cite this article
Opemo Damian Otieno, Juma Shem Godfrey, Logistic Regression Analysis of Mortality Among Fishermen in the Riperian Counties of Lake Victoria, Kenya, Central African Journal of Public Health. Vol. 5, No. 1, 2019, pp. 46-51. doi: 10.11648/j.cajph.20190501.17
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Queiroz, N. M. B., Sampaio, D. D. A., Santos, E. D. S., & Bezerra, A. C. D. S. (2012). Logistic model for determining factors associated with HIV infection among blood donor candidates at the Fundação HEMOPE. Revista brasileira de hematologia e hemoterapia, 34(3), 217-221.
[2]
Ali, M. (2015). Logistic Regression to Determine the Relationship between HIV Testing, HIV Knowledge and Attitude among Adults in Kenya (Doctoral dissertation, University of Nairobi).
[3]
Zafar, M., Nisar, N., Kadir, M., Fatmi, Z., Ahmed, Z., & Shafique, K. (2014). Knowledge, attitude and practices regarding HIV/AIDS among adult fishermen in coastal areas of Karachi. BMC public health, 14(1), 437.
[4]
Shetty, S. B., Divakar, D. D., Dalati, M. H. N., Vellappally, S., Anil, S., Alshehry, M. A., & Alshahrani, O. A. (2016). AIDS awareness: Indispensible prerequisite among fishermen population. Osong public health and research perspectives, 7(5), 327-333.
[5]
Mafigiri, R., Matovu, J. K., Makumbi, F. E., Ndyanabo, A., Nabukalu, D., Sakor, M., & Wanyenze, R. K. (2017). HIV prevalence and uptake of HIV/AIDS services among youths (15–24 years) in fishing and neighboring communities of Kasensero, Rakai District, south western Uganda. BMC public health, 17(1), 251.
[6]
Samnang, P., Leng, H. B., Kim, A., Canchola, A., Moss, A., Mandel, J. S., & Page-Shafer, K. (2004). HIV prevalence and risk factors among fishermen in Sihanouk Ville, Cambodia. International journal of STD & AIDS, 15(7), 479-483.
[7]
Entz, A. T., Ruffolo, V. P., Chinveschakitvanich, V., Soskolne, V., & Van Griensven, G. J. P. (2000). HIV-1 prevalence, HIV-1 subtypes and risk factors among fishermen in the Gulf of Thailand and the Andaman Sea. Aids, 14(8), 1027-1034.
[8]
Béné, C., & Merten, S. (2008). Women and fish-for-sex: transactional sex, HIV/AIDS and gender in African fisheries. World development, 36(5), 875-899.
[9]
Gordon, A. (2005). Food and Agriculture Organization. HIV/AIDS in the fisheries sector in Africa.
[10]
Merten, S., & Haller, T. (2007). Culture, changing livelihoods, and HIV/AIDS discourse: Reframing the institutionalization of fish‐for‐sex exchange in the Zambian Kafue Flats. Culture, health & sexuality, 9(1), 69-83.
[11]
Kissling, E., Allison, E. H., Seeley, J. A., Russell, S., Bachmann, M., Musgrave, S. D., & Heck, S. (2005). Fisherfolk are among groups most at risk of HIV: cross-country analysis of prevalence and numbers infected. Aids, 19(17), 1939-1946.
[12]
Seeley, J., Tumwekwase, G., & Grosskurth, H. (2009). Fishing for a living but catching HIV: AIDS and changing patterns of the organization of work in fisheries in Uganda. Anthropology of Work Review, 30(2), 66-76.
[13]
Mojola, S. A. (2011). Fishing in dangerous waters: Ecology, gender and economy in HIV risk. Social science & medicine, 72(2), 149-156.
[14]
Opemo, D. O., Mbithi, J. N., & Aloo, P. A. (2004). Causes of mortality among the fishermen in lake Victoria, Kenya. In Proceedings of the Second National Zoological Postgraduate Students Conference: 3rd-6th August, 2004: Theme, Zoological Research for Community Development and Poverty Alleviation in Africa (p. 147). Kenyatta University, Department of Biological Sciences.
[15]
Otieno, M. J. (2011). Fishery value chain analysis. Background report Kenya. FAO, Rome, IT,2-10.
[16]
G.o.K.(2000). Fisheries Annual Statistical Bulletin. Fisheries Department, Ministry of Livestock and Fisheries, Nairobi, Kenya.
[17]
KNBS (2009). Kenya National Bureau of Statistics (KNBS), Kenya population and housing census highlights.
[18]
Peat, J. (2001). Health science research: A handbook of quantitative methods. Sage.
[19]
Murray, C. J., Lopez, A. D., Black, R., Ahuja, R., Ali, S. M., Baqui, A., & Dutta, A. (2011). Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets. Population health metrics, 9(1), 27.
[20]
Greene, W. H. (2003). Econometric analysis. Pearson Education India.
[21]
Seeley, J., Tumwekwase, G., & Grosskurth, H. (2009). Fishing for a living but catching HIV: AIDS and changing patterns of the organization of work in fisheries in Uganda. Anthropology of Work Review, 30(2), 66-76.
ADDRESS
Science Publishing Group
548 FASHION AVENUE
NEW YORK, NY 10018
U.S.A.
Tel: (001)347-983-5186