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Utilization of Healthcare Facilities Among Farming Households in Yewa South Local Government Area, Ogun State, Nigeria

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Utilization of Healthcare Facilities Among Farming Households in Yewa South Local Government Area, Ogun State, Nigeria 43 Agro-Science Journal of Tropical Agriculture, Food, Environment and Extension Volume 19 Number 1 (January 2020) pp. 43 - 48 ISSN 1119-7455 UTILIZATION OF HEALTHCARE FACILITIES AMONG FARMING HOUSEHOLDS IN YEWA SOUTH LOCAL GOVERNMENT AREA, OGUN STATE, NIGERIA *Aminu F.O. and Asogba E.O. Department of Agricultural Technology, School of Technology, Yaba College of Technology, Epe Campus, P.M.B. 2011, Yaba, Lagos State, Nigeria *Corresponding author’s email: [email protected] ABSTRACT The study investigated the utilization of healthcare facilities among farming households in Yewa South Local Government Area of Ogun State. Multi-stage sampling technique was used to select 120 farming households and primary data were collected through the use of questionnaire. The data were analyzed using descriptive statistics and multivariate probit regression model. The results indicated that the mean age of the respondents was 41 years with an average household size of five people. About 31%of the respondents had no formal education and farming is the main occupation of respondents. Most (45.8%) of the respondents travelled a distance of 5 km or less before accessing health care facilities. Primary health care was the major health care service utilized by respondents in the study area. Results further revealed that age, education, household size, income, distance to healthcare facilities, severity of ailments and belief were the major socio- economic factors determining demand for healthcare facilities in the study area. The findings call for government at all tiers to establish more healthcare facilities closer to the residence of the rural areas to increase the farming households’ accessibility to these facilities. Key words: healthcare, households, multivariate probit, trado-medicals INTRODUCTION Sound health is a basic requirement for living a (malaria) and food-borne diseases- as well as health productive life. According to World Health hazards linked with specific agricultural system and Organization (2000), “health is a state of complete practices, such as infectious animal diseases (avian physical, social and mental well-being and not flu, brucellosis), pesticide poisoning and merely an absence of a disease or infirmity”. Poor aflatoxicosis. The state of the Nigerian health health affects agricultural production as the health system is non-adoptive and grossly insufficiently status of the farmers affects their physical ability to funded. Total expenditure on health was reported as work, efficient utilization of resources as well as 3.7% of GDP in 2014 (WHO, 2016). As a result, ability to adopt innovations and thus impart Nigeria still has one of the worst health indices in negatively on the welfare of their entire household the world and sadly ranked fourth country with the (Asenso-Okyere et al., 2011). Cole (2006) found worst maternal mortality rate ahead of Sierra that the vast majority of the farmers suffered from Leone, Central African Republic and Chad (WHO, various ill health such as muscular fatigue, malaria, 2016).According to the World Bank estimates, rheumatic pains and skin disorder, forcing them to Nigeria’s Maternal Mortality Rate (MMR) is still take days off farming. Poor health will result to a as high as 814 per 100,000 live births in 2015 (CIA loss of days worked or in reduced efficiency, which World Factbook, 2018). The national health may likely reduce output especially when family management information system is weak and labour is inadequate as a coping strategy (Antle and beyond the reach of the farmers. The use of Pingali, 1994). The link between agriculture and healthcare facility in the rural areas of Nigeria is health is bi-directional (Asenso-Okyere et al., limited or restricted by inadequate healthcare 2011). According to Gallup and Sachs (1990) facilities, insufficient staff, equipment or medical agriculture supports health by providing food and training; other limitations include far distance nutrition for the world’s people by generating location of facility, method of payment, income, income that can be spent on healthcare, yet household size, years of formal education, main- agricultural production and food consumption can occupation of households and more importantly also increase the risks of water related diseases limited access to healthcare services. Please cite as: Aminu F.O. and Asogba E.O. (2020). Utilization of healthcare facilities among farming households in Yewa South Local Government Area, Ogun State, Nigeria. Agro-Science, 19 (1), 43-48. DOI: https://dx.doi.org/10.4314/as.v19i1.7 Farming Households Use of Healthcare Facilities in Yewa South LGA, Ogun State, Nigeria 44 There is evidence that the consumers choose the and utilized by the farming households were facilities in which access is easier and the payment obtained from household heads in the study area system is flexible (Nguyen et al., 2008). Bir and using an interview schedule using questionnaire. Eggleston (2002) further reported that socio- economic and demographic conditions play Data Analysis Techniques important roles in choosing healthcare facilities. Descriptive analysis Salihu and Sanni (2013) found out in their study Descriptive statistics such as frequencies, that majority of farmers used the home-based care percentages, means, standard deviation and chart of self-medication during ill health, that is, was adopted to describe the socio-economic purchasing and taking drugs without being characteristics of the respondents and their choice prescribed by a qualified medical practitioner. of healthcare services in the study area. They opined that this may be informed by the affordability of the treatment type. This study The multivariate probit regression model would therefore examine the demand for healthcare This was used to determine the factors influencing services among farming households in Ogun State, the choice of healthcare facility in the study area. Nigeria. Specifically, the study sought to (i) The model is specified as: describe the socio-economic characteristics of the respondents in the study area; (ii) identify the Yὶϳ = β0 + βXji ……………………… (1), choice of healthcare facilities available and utilized by the farming households in the study area; and where Yὶϳ is a binary dependent variable with value (iii) determine the factors influencing the choice of as 1 if the ith farmer utilizes jth health facility and 0 th healthcare facilities the study area. if otherwise. The j health facility is such that Y1 is primary health centre (PHC), Y2 is general hospital, MATERIALS AND METHODS Y3 is private hospital, Y4 is trado-medical, and Y5 is Study Area self-care. β is the regression parameters or The study was conducted in Yewa South Local coefficient; e is the error term. The Xjὶ is a vector Government Area of Ogun State, Nigeria. Its of explanatory variables and is expressed as: headquarters is in the town of Ilaro. The study area X1 - sex of household head (dummy), is located on Coordinates: 6°48′N 2°57′E. It shares X2 - age (years), boundaries with Yewa North and Ipokia Local X3 - educational status (1 for formal education Government Areas in the North and South, and 0 for otherwise), respectively and in the West and East by Ifo and X4 is marital status (1, married; 0, otherwise), Ado-Odo/Ota Local Government Areas. Yewa X5 is household size (Number of persons), South Local Government is naturally endowed with X6 is income (₦), large expanse of land area of 629 km² and a X7 is distance to health facility (km), population of 168,850 at the 2006 census. The X8 is severity of illness (1, severe; 0 otherwise), people of Yewa South Local Government Area are X9 is belief (1, spiritual; 0, otherwise) predominantly farmers while a few people engage X10 is healthcare needs (1, frequent; in craftsmanship. The main crops grown in the area 0, otherwise); include cassava, yam, oil palm, maize, cocoa, X11 is waiting time (minutes), and pepper, vegetables and fruits and poultry like eggs, X12 is cost of treatment (₦). fowls, goats, sheep, among others. RESULTS AND DISCUSSION Sample Size and Sampling Procedures Socio-Economic Characteristics of Respondents A multi-stage sampling technique was employed in Results in Table 1 reveal that majority (55.0%) of the selection of respondents for this study. The first the sampled household heads were males while stage involved the purposive selection of the two 45% were female. This implies that the farming major blocks (Ilaro and Ifekowajo) in the study households in the study area were male dominated. area to have a wider coverage of the area. In the This observation agrees with Aina et al. (2015) that second stage, two wards (Ilaro 1, Ilaro II, Oke- men, being the heads of the rural households tend Odan and Owode-Yewa) were randomly selected to have higher demand for healthcare services than from each of the blocks. The third stage involved women who are mostly submissive to the will of the use of simple random sampling technique to their husbands regarding health seeking. Majority select a village from each of the wards making a (67.5%) of the respondents were below 50 years of total of four villages. The last stage involved the age. The mean age of about 41 years implies that purposive selection of 30 farming households from the respondents were young and within their each of the selected villages making a total of 120 economic and production age and are therefore respondents for the study. Primary data on socio- conscious of the importance of good health to their economic characteristics of farming households, farming enterprise. Only 30.8% of the respondents choice of healthcare services, facilities available had no formal education. The modal education of Aminu F.O. and Asogba E.O. 45 Table 1: Socio-economic characteristics of farming The results further reveals that 66.7% of the households in the study area n = 120 respondents had between 1 and 5 people in their Variable Frequency Percentage households while 6.6% had more than 10 people as Sex their household size.
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