Introduction

Food insecurity, under-nutrition and ill health continue to persist in many developing countries. These problems tend to be severe in the African region with its attendant inequality in resource allocation [1]. This creates a problem for human capital development and undermines productivity since good health is a component of human capital and a key factor in the creation of wealth [2]. The situation is devastating for children under age five, who depend on their parents/caregivers for nutritional needs. According to the World Health Organization (WHO) [3], poor nutrition in the first 1,000 days of a child’s life can have irreversible consequences leading to stunting, which makes him/her more susceptible to sickness, often fall behind in education, and more prone to non-communicable diseases. Malnutrition in turn contributes to poverty and hunger. Proper feeding practices, proper nutrition and appropriate health care utilization are important channels to improve child health. Despite numerous efforts at improving child health in the Sub-Saharan Africa, under-nutrition continues to persist in most countries.

The health status of a child is important for proper development and participation in the economy as an adult. For instance, proper education and progression on the educational ladder are anchored on good health, whereas ability to participate in the labor force as an adult is hampered by poor health. These have implications for human capital development of any economy with such outcomes. Poor nutrition has been identified as a cause of under-five childhood morbidity and mortality, and accounts for about one third of under-five mortality in Africa [4]. Improving child health is, therefore, an important public health goal which can be achieved through proper nutrition and proper health care services utilization. According to WHO reports that the risk of a child dying before completing five years of age is still highest in the WHO African Region with a rate of 81 per 1000 live births, with under-nutrition accounting for 45% of such deaths [5]. Thus, a significant reduction in childhood mortality and morbidity can be achieved if appropriate nutrition is provided for the child before and after birth.

Under-nutrition is often caused by inadequate or improper food intake, poor child feeding practices, and repeated episodes of childhood diseases. This leaves the child vulnerable and increases his/her probability of poor livelihood. The Ghana Demographic and Health Survey reports that adequate nutrition is critical to children’s growth and development [6]. Poorly nourished children cannot grow and develop properly, resist infections or learn to their full potential. Malnourished adults are less capable of performing work and are severely disadvantaged in terms of their social and economic security. Thus, good nutrition makes an essential contribution to the fight against poverty. The Millennium development goals sought to eradicate extreme poverty and hunger by reducing the prevalence of underweight children. The Sustainable Development Goals (SDGs) aim to end preventable deaths of newborns and children under 5 years of age by 2030. It also aims to end hunger, achieve food security and improved nutrition and promote sustainable agriculture. The key to achieving these goals lies in identifying the household socioeconomic factors that influence the nutritional status of the under-five year old child.

Socioeconomic status can significantly enhance or hinder a person’s quality of life and nutritional status. Curie and Goodman for instance, argue that children of families with low socioeconomic status are likely to have lower health status at birth not necessarily because of worse genetic endowment, but because of the circumstances surrounding gestation and birth. Similarly, low wealth/income can adversely affects child health through malnutrition, poor hygienic conditions and improper utilization of health care services [7]. Environmental/living conditions such as place of residence, access to health services and basic social amenities like water and sanitation can help improve the health of the child. Another important contributor of a child’s development is educational status of the parent as it creates a reasonable knowledge on proper.

The empirical literature on factors that influence the nutritional status of the child have provided evidence on important factors. Factors such as maternal education [9, 10, 11, 12], maternal autonomy [1], household economic status [1, 9, 15, 16] have been reported to influence the nutritional status of the child. For instance, studies have argued that children born in educated and wealthy households get better care than their counterparts born in less educated and wealthy households. Other, child specific characteristics that have also been argued in the literature to affect child health are the age of the child, gender of the child, and birth order of the child [9, 10, 11, 12]. The studies have attempted to provide evidence on various aspects of child health outcomes in different parts of sub Saharan Africa. These studies have shown a similar pattern that maternal factors do influence health outcomes of the child. However, most of these do not include some important indicators like the health care use of the mother, the household power structure and the birth order of the child. These are factors that are also likely to influence the nutritional status of a child. This study therefore set out to investigate these effect of these factors on nutritional outcome of a child using a more recent demographic survey data and to incorporate these various aspects in a comparative approach to help us to understand the role these factors play in the three study countries. Evidence from the study will help in policy/decision making on improving child health outcomes in Africa. The study examines the effect of household socio-economic factors on the child’s nutritional outcomes in Ghana, Kenya and Zambia.

Methods

The study is based on the Grossman model of health capital and the demand for health care [8]. Our model specification follows Rosenzweig and Schultz (1982) as outlined in Mwabu in which child health production is embedded in the utility maximizing behavior of the mother [18]. The model assumes that the mother derives utility from the health of the child and therefore engages in child health production using market and non-market or behavioral inputs. The mother serves as the point of reference here because the child at the age depends a lot on the mother for feeding and other essential things. The utility function of the mother is specified as equation (1);

(1)

In equation 1, X is a vector of health neutral goods which yields utility to the mother, but has no direct effect on her reproductive health status; Y is a vector of health-related goods that yields utility to the mother and also affects her reproductive health; H is a vector of child health outcomes, which is embedded in the mother's utility function. H is assumed to yield positive utility to the mother. The child's health outcomes (H) is also affected by a number of maternal and child-specific characteristics. The child health production function can be specified as equation (2);

(2)

In equation 2, S is a vector of the economic status of the mother/household captured while C is a vector of social factors of the mother/household. U is a vector of child specific characteristics that can influence the child’s health. The utility of the mother is maximized subject to the household budget constraint, which is specified in equation 3 as;

(3)

P_x, P_y and P_c are the prices of the health neutral good (X), health related good (Y), and price of child health (C), respectively. M is the total income of the family made up of initial wealth, and labor and non-labor income. The left-hand side represents total expenditure while the right-hand side represents the total income of the family. We derive the demand for health function of the child by substituting equation 2 into equation 1 and forming the Lagrangean function for optimization as specified in equation (4);

(4)

Taking the first order conditions from equation 4 with respect to X, Y and H, and solving through results in the demand functions for each of the arguments in the utility function. The reduced form equations for these demand functions are as specified;

(5)

(6)

(7)

Equation 7 allows the estimation of the child's health production as a function of the socioeconomic status of the household. Unfortunately, in the DHS dataset, access to prices, particularly that of medical care are unavailable. Thus, we do not include prices in our estimations. We do not expect this to have a significant effect on the results since the economic status of the household was controlled for. For the purpose of estimation, equation (8) is specified and estimated using the ordinary least squares. β, π, δ are vector of parameters associated with Y, S and C, respectively.

(8)

The study uses data on children under age five from the 2014 Demographic and Health Survey (DHS) for Kenya, Ghana and Zambia. The dependent variable is the child's nutritional status measured by the Weight-for-Age Z-score (WAZ), which is computed as the difference between the value of an individual child and the mean value of the reference population for the same age or height, divided by the standard deviation of the reference population. The socioeconomic factors used include wealth, education, place of residence, employment, decision making structure of the household, and education of the partner. Specific characteristics of the child including age, gender and birth order were included as controls.

In our analysis, the wealth of the household was categorized into five quintiles from the poorest households to the wealthiest. We expect that wealth should have a positive effect on the nutritional status of the child. Education of the mother is also measured in categories with no education, primary education and secondary plus. We measure father’s education by years of schooling. We expect education to have a significant effect on the nutritional status of the child. Also, we use the household decision making structure has four responses; the woman alone, the partner alone, woman and partner, and someone else. Residence is measured as rural or urban. We control for the age of the mother, the educational level of the partner, and the nutritional status of the mother using the Body Mass Index (BMI). Finally, we control for specific characteristics of the child that may also affect the child’s nutritional status. These are the age of the child, gender of the child and the birth order of the child.

Results

Descriptive statistics

Table 1 shows that majority of the households are in the poorest wealth quintiles in the three countries. Majority of the mothers in Ghana had no education, with the exception of Zambia and Kenya, where we found that majority of the women had primary education. The majority of the women in our sample were also found in the informal sector with only a small fraction who reported to be in the professional fields from the three countries. With the decision making variable, majority of the decisions in the households are made by the woman and the partner with just a small percentage being made by someone else other than the woman or the partner.

Table 1: Descriptive result of some respondent’s information across the three countries