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The study investigated the nutritional status of under-five children of farm households. The study utilized primary data from 352 farm households with 140 under-five children. Household crop commercialization index (CCI) was used to estimate cassava farm household crop sale ratio and categorize the households into four commercialization levels while WHO Anthro software was employed to analyze under-five children anthropometric indices such as weight-for-age z-score (WAZ), height-for-age z-score (HAZ) and weight-for-height z-score (WHZ). Logit regression model (LRM) was used to examine the drivers of under-five children’s nutritional status of farm households. The study found that 42.9%, 7.9% and 3.6% of the children are stunted, underweight and wasted respectively. The highest stunting level was recorded in zero level households (CCI 1). Although, some higher CCI households (medium-high and very-high level) recorded increased percent of stunted children. This revealed that being a member of low or high-level commercialization households may not guarantee better nutritional status of young children of farm households. The results of LRM indicated that the predictors of children nutritional status were child’s age, farm size, access to electricity, healthcare and commercialization variables. Moreover, weak positive and negative relationships exist between CCI and children’s nutrition outcomes as measured by the z-scores. The study recommended maternal nutrition-sensitive education intervention that can improve nutrition knowledge of mothers and provision of infrastructure that enhance increased farm production and promote healthy living among farm households.
The study was carried out in Ogun and Oyo states (South-West) of Nigeria. However, Nigeria is located in West Africa within the land mass of 923,768 square kilometer with latitude 10° 00ˡ N and 8° and 00ˡ E (Maps of World, 2021). It is a multi-ethnic nation where Igbo, Hausa and Yoruba are regarded as the most common ethnic groups. South-West is one of the six geo-political zones in Nigeria. There are 6 states in South-West. Agriculture is regarded as the major occupation of about 70% of the rural population (Lawal & Samuel, 2010; Otekunrin et al., 2021b). This study utilized primary data which was collected through multi-stage sampling procedure. Firstly, two (2) from six (6) cassava producing States in the Southwestern Nigeria was randomly selected. Secondly, the selection of five (5) Local Government area (LGAs) from Oyo State and three LGAs from Ogun state giving a total of eight (8) LGAs in the two states. In stage 3, 24 villages from the 8 LGAs was selected while the fourth stage included the selection of 16 cassava farming households resulting in 384 farm households. The data were gathered using structured questionnaire which include; the household socioeconomic factors, nutrition, child-centred factors, expenditure on food and other salient household and child-centred issues. Thirty-two of the questionnaires were unusable after data cleaning. In the 352 farm households, there were 140 under 5-year members. However, anthropometric measurements such as age of child, gender, height and weight were measured and recorded. These measurement details were used in obtaining malnutrition indices such WAZ, HAZ and WHZ. The CCI levels of cassava farm households in the study areas were estimated, while making use of Crop Commercialization Index (CCI) by Strasberg et al., 1999; Carletto et al., 2017 and Otekunrin et al., 2019b; Otekunrin et al., 2022a, b which is expressed as: We have as the household in year j. Using this method, agricultural commercialization can be expressed as a continuum spanning complete subsistence () to full commercialization (). Using this this method, cassava farm households were grouped on the basis of their cassava commercialization levels. From non-participant farm household which are grouped as (i) zero commercialization households (CCI = 0%) to participating households which are classified into; (ii) low commercialization (CCI=1–49%) (iii) medium-high commercialization (CCI = 50–75%) and (iv) very-high commercialization (CCI = > 75%) levels (Otekunrin, 2021b; Otekunrin & Otekunrin, 2021b). Anthropometry is a human body measurements that are mainly used to obtain important nutrition details concerning a sample or population (Babatunde et al., 2011). Past farm household studies have applied anthropometric data to under 5-year children in Nigeria (Babatunde et al., 2011; Ogunnaike et al., 2020; Adeyonu et al., 2022; Ashagidigbi et al., 2022). The anthropometric measurements are used in obtaining indices such as HAZ, WAZ and WHZ (Babatunde et al., 2011; Slavchevska, 2015; Fadare et al., 2019; Bhargava et al., 2020; Otekunrin,2021b ). Empirical studies on anthropometric measurements (using WHO Anthro software) of under 5-year members of rural farm households are scarce. The anthropometric measurements for under-five were measured using stunting (HAZ), wasting (WHZ) and underweight (WAZ). The anthropometric indices of under-five members of cassava farm households were obtained for this study using WHO Anthro software. These are stunting, wasting and underweight. However, children (> 5years) having HAZ < -2 Standard Deviation (SD) and < -3SD compared to 2007 WHO reference were classified as stunted and severe stunting, WAZ < -2SD and < -3SD referred to as underweight and severe underweight while WHZ < -2SD and < -3SD referred to as wasting and severe wasting respectively (WHO, 1995, 1997; de Onis et al., 2007; Babatunde et al., 2011; Slavchevska, 2015; Bhargava et al., 2020). The drivers of under 5-year children’s malnutrition (stunting, wasting and underweight) of farm households were analyzed using LRM as expressed in Eq.(2) below. However, the regressand (dependent variables) are the malnutrition status of the children members of the farm households and are presented in separate regression models. In each case, one (1) is for malnourished child and zero (0) otherwise (i.e. stunted = 1, 0 otherwise; wasted = 1, 0 otherwise; and underweight = 1 and 0 otherwise) as expressed as a function of a vector of explanatory variables assumed to affect the malnutrition of farm under 5-year children. This indicated that in each case, the parameter estimate indicates the likelihood that a child will be malnourished. However, the positive sign on the parameters shows high-level of malnutrition while the negative sign reveals low-level of malnutrition (Babatunde et al., 2011). The explanatory variables included in the model are; child age, child gender, age of mother, education level of mothers, household size, farm size, household head educational level, farm income, non-farm income, food expenditure, mothers’ access to nutrition training, healthcare access, toilet access, access to electricity, piped water access and crop sold ratio. Following Gujarati & Porter 2009 and Otekunrin et al., 2022a, b, the logit regression model is expressed as: Where denotes the probability of a child being stunted, wasted and/or underweight, are the parameter estimates of the explanatory variables, the represent the explanatory variables and are the stochastic error terms.
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