Environmental and Socioeconomic Correlates of Child Malnutrition in Iseyin Area of Oyo State, Nigeria

Abstract

Policy makers at global, national and local levels are more than ever concerned about the rising trend in child malnutrition in Sub-Saharan Africa and how it can be curtailed in the context of general food and basic-needs policies. To support programme setting at the local government level, this study was conducted to examine the relative importance of environmental and socio economic correlates of child malnutrition. Primary data were collected through a well structured questionnaire and analysed using Z-score indices and probit model.Our results reveal that 46% of the children are stunted, 6% under weight and 21% wasted. Our model estimation identified the age of the child, diarrhoea infection and poor sanitation as key factors that increases the likelihood of malnutrition in the study area. This reflects the relative importance of environmental factors in the study area. Socioeconomic factors were less robust but were consistent with previous empirical studies in terms of direction of association. The study recommends that government and other stakeholders should pursue sanitation/ hygiene programmes and public enlightenment programmes on the dangers of poor sanitation and diarrhoea.

Nutritional Status of Children (6-59 Months) from Food Secure and Food Insecure Households in Rural Communities of Saesie Tsaeda-Emba District, Tigray, North Ethiopia: Comparative Study

“…Even though there was no statistically significant association between educational status of father and underweight in different studies in Nigeria (16,17), in the current study, children of those fathers able to read and write were statistical significantly 73.9% at reduced risk to be underweight when compared to the children of fathers unable to read and write in the food secure households alone. This could be due to the reason that fathers who can read and write can be exposed and updated themselves to reading materials such as broachers, posters and other leaflets concerning about nutritional activities and infant and young child feeding practices; so, they can apply it to their children in order to make their children well nourished.…”

“…As to studies in Nigeria (16,17) there was no statistical significant association between the occupation of father and stunting. But, in the current study children of farmers and others (herders & others) were 3.75 and 3.5 times at higher risk to be stunted when compared to children of daily laborer fathers respectively in the food secure households.…”

“…Even if an association was not found between occupational status of father and underweight in different studies of Nigeria (16,17), children of others (herders & others) were 88.2% at reduced risk to be underweight when compared to children of daily laborer fathers for food insecure households alone. This might be straight forward that those children of herders may more frequently consume animal products and became at reduced risk to be malnourished as more or less their stable foods are animal products.…”

Factors associated with malnutrition among underfive children in developing countries: A review

“…It has been observed that, in most developing countries, the dietary practice in populations experiencing food insecurity tends to meet their energy requirements but do not provide sufficient nutrients to optimize health and prevent infection. Hence, it can be inferred that overnutrition and under-nutrition are strongly associated with food insecurity (Babatunde et al, 2007;Awoyemi et al, 2012). Factors such as poor academic performance, physical and mental ill-health, psycho-social problem and anaemia related to iron deficiency are consequences of food insecurity in children (Food and Agricultural Organization, 2008;Akinyele, 2009).…”

Use of Quantile Regression in Determining Factors Associated with BMI Among Vulnerable Adolescents in Rivers State, Nigeria

“…Several research on BMI have used the t test, Ordinary Least Squares and other generalized linear models and therefore important features of the data may have been missed with such models that average over the conditional distribution. (Omigbodun 2010, Awoyemi et al 2012, Owoaje et al 2014, Omobuwa et al 2014, Hayward et al 2014, Fokeena and Jewon 2012, Adesina et al 2012, Yetubie et al 2010, Afrifa-Anane et al 2015.…”