Childrens nutritional status in nigeria

Determinants Of Children's Nutritional Status In Nigeria: A Multivariate Analyses.

Introduction

Worldwide, under-nutrition is said to be the leading cause of about half of all deaths occurring in children 1 and that Protein-Energy malnutrition is the most prevalent form in the developing countries with the highest incidence in the under-five children.2 Malnutrition in the form of under-nutrition is the most significant risk factor for global burden of diseases causing approximately 300,000 deaths per year directly and indirectly accountable for more than half of the deaths occurring in children in the developing countries.3;4 It has been estimated that more than one-quarter of all under-five children in the developing countries are underweight and this accounts for about 143 million children that are underweight in these countries.5 Almost three-quarters of these 143 million underweight children live in just ten countries.5 In addition, more than one-quarter of the under-five children are underweight in Sub-Saharan Africa.5 Research carried out in 1990 showed that in Nigeria 43.1% of the under-fives were stunted (short for their age), 35.7% were underweight (small for their age) and 9.1% wasted (thin for their height).6 In 2008, the Nigeria Demographic and Health Survey (NHDS) conducted indicated that 41% of Nigeria children are stunted, 23% are underweight and 14% are wasted. 7 Comparing these two studies, one would see that not much has changed in the trend and it should be obvious that malnutrition in the under-fives in Nigeria is still a major problem needing solution.

Of Nigeria's 140.4 million people, an estimated 23.5% are infants and preschool children aged 0-59 months; 8 67.8% of these children are living in the rural areas 7 while the rest 32.2% live in urban centres. Annually in Nigeria, approximately 8000 children die from malnutrition before reaching four years of age. 9 Since malnutrition leads to impaired mental and physical development of these children, it fundamentally constitutes impairment to the social and economic development of the developing countries like Nigeria. This has however persisted despite many strategies adopted to tackle it by various levels of governmental and non-governmental agencies.

From studies carried out in the past in various parts of the globe, it is clearly evident that childhood malnutrition is linked to a number of environmental and socioeconomic factors like poverty/wealth index. According to some studies 10-13, there are noticeable disparities between children from rich and those from poor families where children from poor homes suffer more from underweight and stunting compared to those from rich homes. However, interactions with covariates were not considered and at the same time, only chronic malnutrition (stunting) was used as the outcome variable. Regarding place of residence (rural/urban), 14-16 the studies found stunting and underweight to be more amongst children from rural settings than those from urban settings. The techniques used for their sample selection in these studies were not however clear to remove doubt over sample selection bias. Households headed by females having children who are stunted and underweight were also partly linked to poverty according to some studies 17;18 but the studies were relatively small and therefore the outcomes of their studies were not generalisable. In addition, it is not clear if we can replicate their results with larger samples because even in the larger of these two studies 18, various statistical methods were used ranging from multiple linear regressions to multiple logistic regressions and even multinominal ordered logistic regressions. Maternal and paternal educational levels were also found to greatly influence the nutritional status of children as those children whom their parents had high formal education were better off than those whose parents had low or no formal education and specifically maternal education was found to be more associative with malnutrition in all the studies reviewed 10;19-23 Having access to health care services was also found to be significant in determining nutritional status of children as the children who did not have access to health care facilities suffered mostly from stunting.13;24;25 Different geographic regions of Botswana exhibit different socioeconomic development as well as climatic conditions variations and food productions which were likely to have been the reasons for the significance association between regions and children's nutritional status independently of individual's household's socioeconomic status according to some studies appraised.18;26 Climatic conditions variations of regions were also linked to malnutrition in another study conducted in Tibet.27 With respect to demographic factors, mother's age at child's birth was strongly associated with stunting, underweight as well as wasting in which more of these were seen in children borne to young and adolescent mothers.13;26;28-31 Also, being a male child was linked to stunting and underweight in some studies.13;32-34 Child's age was also clearly evident to have significant effect on child's nutritional status as children under age three suffered more from stunting and underweight than those older than three years.18;32;33 A number of studies 10;12;23 linked the likelihood of having children with malnutrition to being borne from multiple births. In these studies, children borne from higher multiple births were observed to be stunted than single-born children. Breastfeeding 35;36 and duration 36;37 were also found to have influence on nutritional status as those that were not breastfed or have less than six months breastfeeding duration had stunted growth. Prolonged breastfeeding on the other hand was linked to higher malnutrition rate in some other studies.13;38-41 Birth intervals (less than 24 months) and child's birth weight (less than 2500 grams) have also been associated with malnutrition according to studies conducted by some authors.15;38;42-44 Furthermore, some studies have shown disproportional burden of malnutrition on children from deprived households.14;38 A couple of studies linked malnutrition to morbid conditions like respiratory infections,18;45, diarrhoeal infections 18;30;33;46 and diseases caused by parasites.46;47 Some studies also associated malnutrition (stunting and underweight) to poor sanitary condition of the households. 33;48 However, the confidence intervals of the research done by El Taguri and colleagues are wide and could not be relied on while there is inconsistence in the results of study conducted by Medhin et al. To provide reliable and accurate information for policy making and programme design that aims at addressing nutritional deficiencies in under-five children, studies that combine child's factors, parent's demographics, environmental and socioeconomic factors in a single analytical framework will be needed of which this study promises to do.

In addition, the under-five children are of particular interest because of the pronounced effects of malnutrition in them-malnutrition is a major cause of high morbidity and mortality in them. 49 The most severe effects of malnutrition are concentrated in under-five children so that even; if nutrition improves from that time forward, they are most likely to suffer from below normal growth which would affect their physical and mental development, thereby compromising the future of these children, their communities and their countries at large.50

A recent household expenditure survey states that over 50% of the households in the country live below poverty line. 51 Poverty has been found out to be the main cause of malnutrition in Nigeria, especially in the rural settlement areas where they mostly practice subsistence agriculture with little income generation to take care of family needs.15 Malnutrition is a major concern of government of Nigeria which has been working hard to eliminate it by intervening where there is deficiency. Under-nutrition according to recent comparative risk assessments is estimated to be the largest contributor to the global burden of disease in children, 1;52 Furthermore, in most of the developing countries, malnutrition is mutually reinforced by infections which are still very common in these countries and both continue to assume an ever present and alarming threat. 53 It has been estimated that problems involving interaction of malnutrition and infection still affect three-quarters of the world's inhabitants (mostly the under-fives because of their fledgling immune system) and account for majority of deaths recorded in them. 53 Malnutrition causes an increased susceptibility to infections; also infections lead to increased requirement for nutrients by hyper-catabolism and increased loss of body constituents subsequently. Often, there is additionally a decreased dietary intake, and together, these can result in precipitation of acute deficiency states in the under-fives who are marginally compensated before the infections. A vicious cycle can be started, which if not promptly and properly treated, can result in death, 53 To break this cycle immunisation plays a vital role in protecting growth of the under-fives by preventing infectious diseases from occurring in them.

Previous literature on surveys of nutritional and health status of under-five children in Nigeria are few. Most of them examined few determinants (either socioeconomic factors singly15, cultural54, environmental factors alone or individual and community factors55); hence effects of confounding factors and/or interactions between variables were not sufficiently looked into. The studies on children's nutritional status in Nigeria were mostly carried out in urban areas with little attention being paid to rural areas, 9;54;56-59 overlooking the fact that Nigeria is a Sub-Saharan Africa developing country with diverse socio-cultural practices and with about 70% of the population living in the rural areas. The outcomes of their studies cannot therefore be said to be generalised. In addition, most of these studies were correlational studies wherein associations between variables only were looked for and no adjustment for confounding factors not to talk of models building and goodness of models tests. The 2008 NDHS have national representation covering both rural and urban settings; it is new and not yet explored by researchers specifically with respect to malnutrition in under-five children. This study is however out to cover the whole of the country since NDHS provided dataset that has national representation. Moreover, individual and parental factors, cultural and socioeconomic factors and environmental factors as possible determinants of under-nutrition in under-five children will be explored in this study to cover for some of the lapses in the previous studies carried out on Nigeria.

The discussion of this study will therefore be based on the non-clinical factors as well as some morbidity conditions that can have effect on the nutritional status of under-five children in Nigeria, using the internationally accepted anthropometric parameters such as underweight (weight for age), wasting (weight for height) and stunting (age for height).60;61

The main focus of the study will be to analyse, identify and to quantify the effect of major factors that determine nutritional status of children based on which both governmental and non governmental health agencies can use to intervene.

Methods And Materials

Setting

Nigeria is a country located in West Africa around the Gulf of Guinea. It covers a total area of about 923,768 square kilometres. In the world, Nigeria is the thirty-second largest country in terms of land mass after Tanzania which is the thirty-first largest. It is the most populous country in Africa continent. The latest population and housing census conducted by Nigeria Population Commission (NPC) in 2006 puts her population at 140,431,790. The rural area has about 67.8% of the population while the urban area has about 32.2%. The population density of Nigeria is about 150 people per squared kilometre. There are more than 250 ethnic groups in Nigeria with varying languages, customs and cultures thereby creating a nation with rich ethnic diversity. The largest ethnic groups are the Yoruba, Hausa/Fulani and Igbo which account for 68% of the total population. About 27% of the population comprise of Ijaw, Kanuri, Tiv, Nupe, Edo and the Ebiras while the remaining 5% is made up of the other minority groups. The Nigeria Demographic and Health Survey carried out in 2008 puts under five children's population at 17.1% of the country's population which make every unit change in their health to have toll effect on each household's economy and by extension on Nigeria's economy and productivity.

Study Design

Cross sectional and population based study that is looking at association between socioeconomic, environmental, child and maternal factors and under five children's nutritional status using data obtained from 2008 Nigeria Demographic and Health Survey.

Data Source/Sampling Technique

This study will be based on 28,647 under five children included in Nigeria Demographic and Health Survey (NDHS) in 2008. The NDHS collected data on demographic, environmental, socioeconomic, and health issues (family planning, infertility, nutritional and health status of children, their mothers and the fathers) from a nationally representative sample of 34,596 women aged 15-49 years and 16,722 men aged 15-59 years in 36,292 households that were eligible to be interviewed. The survey included 24,880 households from rural areas and 11,418 households from urban areas. The country by stratification was divided into 36 states plus the Federal Capital Territory (FCT) which were further divided into 774 local government areas (LGAs) all within the six geopolitical zones (South West, South South, South East, North West, North Central and North East) to obtain a nationally representative sample.7 Domain was set up and each one consists of enumeration areas that was established by the general population and housing census conducted in 2006.7 The sampling frame is made up of a list of all enumeration areas (clusters).7 From each domain, a two stage probabilistic sampling method was used for the clusters selection 7. The first stage involved choosing of 888 primary sampling units (PSUs), 602 in the rural and 286 in the urban areas with a probability proportional to the size.7 The size in this context is the number of households in each cluster. A second stage of sampling followed the first stage which involved the systematic sampling of households from the selected enumeration areas.7

Ethical Consideration

Approval was granted for secondary analysis of existing data after the removal of all identifying information of the respondents by the Ethics Committee of the ICF Macro at Calverton in the USA in conjunction with the National Ethics Committee of the Federal Ministry of Health in Nigeria. The data were got by these bodies through pre test and structured questionnaires (questions and anthropometric measurements) after informed consent were obtained from mothers of the children that were eligible for the survey.

Study Variables

Outcome variables/response variables

The dependent variables of this study are (1) stunting (yes=1 or no=0) (2) wasting (yes=1 or no=0) and (3) underweight (yes=1 or no=0).

Stunting: height for age Z-score less than -2 standard deviations (HAZ <-2SD) from the median of the reference population of World Health Organisation (WHO).60;61 It indicates skeletal growth reduction due to chronic or long standing malnutrition.

Wasting: weight for height Z-score less than -2 standard deviations (WHZ <-2SD) from the median of the reference population of WHO.60;61 It reflects the inability of the child to receive adequate nutrition in the period prior to the survey which may be the consequences of recent illness or inadequate food intake. It indicates acute or short time malnutrition.

Underweight: weight for age Z-score less than -2 standard deviations (WAZ<-2SD) from the median of the reference population of WHO; 60;61 it takes into consideration both acute and chronic malnutrition (acute on chronic malnutrition) effects.

Exposure variables/predictor variables

Child's Factors

Age of child: Age of the child in months
Sex of child : refers to gender of the child (male or female)
Birth order number: position of the child among other children in the household.
Breastfeeding: refers to duration of breastfeeding of a child in months as reported by mother.
Immunisation: If the child has been vaccinated against childhood killer diseases (complete or incomplete).
Birth weight: weight of the child at birth which could be low if <2500g and normal if ≥2500g
Diarrhoea: refers to passage of loose and watery stool for ≥ 3 times in a day with signs of dehydration that occurred two weeks before the survey.
Respiratory infection: sickness associated with cough in a child two weeks before the survey.
Fever: condition in which the body temperature is more than 37.2 °C two weeks before the survey.

Maternal Factors

Maternal age: Age of mother in years.
Educational level of mother: this can be no formal education, primary, secondary or higher education.
Mother's BMI: ratio of mother's weight in kilogram to height in metre squared (kg/m²)
Occupation: type of job the mother does (White collar, Manual or Not working)
Birth Interval: the period between a birth and the next (short if <24 months)
Maternal health seeking behaviour: Health seeking attitude (healthcare card for the child, oral rehydration salt, antenatal care, goes to hospital, tetanus injection vaccination during pregnancy) of mothers in quantiles.

Environmental Health Conditions

Source of drinking water: talks about if the household has access to safe drinking water which could be pipe borne water or water from covered and protected well.
Toilet facility: presence of toilet which could be flush toilet ventilated improved latrine or traditional pit toilet.

Household and Socioeconomic factors

Number of children: indicating number of under-five children in the household.
Ethnicity: Tribe to which the child belongs (Major or Minor ethnic group).
Type of family: talks about the structure of the family (monogamous or polygamous).
Head of the household: whether the house is headed by a male or female.
Religion: the faith the parents and hence the child practise (Christianity, Islam or Traditional)
Father's educational level: this can be no education, primary, secondary or higher institution
Wealth index: income level of the family in quintile
Whom child lives with: child's caretaker.
Residence: where the child lives (rural or urban)
Geographic region: refers to zones of Nigeria where the child resides (North Central, North East, North West, South South, South West and South east). Nigeria is geographically divided into six regions.

Statistical Analysis

The analytical approach involves descriptive, bivariate and multivariate analyses. The descriptive statistics with the use of numbers and proportions for categorical variables was employed to show the distribution of children by the predictor variables. The bivariate analysis with crude (unadjusted) odds ratios (OR), 95% confidence intervals (95%CI) and corresponding p-values were calculated for each variable in every dimension as deem fit. This helps to examine the association between each predictor variable and each dependent variable. The analysis will also include exploration of interactions among the explanatory variables and correlation estimations. In order to get the best predictive model for the outcome variables of underweight, stunting and wasting, all statistically significant independent variables within each category will be included in an unconditional multivariate logistic regression analysis. Derivation of models process follows which will start from construction of a saturated model until the best predictor model is found. Thereafter, assessment of significance of each covariate of interest will be done by adjusting for major potential confounders like age and sex of the child, educational level of the mother, region and income level (wealth index) of the household. Regression diagnostic tests like hosmer-lemeshow goodness of fit test and tolerance test for multicollinearity will be used to test the goodness of fit of the models as soon as the best explanatory models are got. Other tests like log likelihood test, estimates of adjusted R squared and reciprocal of variance inflation factors (VIF) will all be used to judge the goodness of fit of the models. The statistical analysis on the data was carried out with the use of STATA statistical software version 11 up till this stage and will also be used for the remaining part of the analysis.

Measurement of determinants of under-five nutritional status

For several predictor variables; the outcome variable zi=0 (no) or 1 (yes).

zi=Logpi1-pi=b0+b1x1i+b2 x2i+b3x3i+…bkxki

It should be noted that outcomes zi for different individuals are statistically independent. pi stands for likelihood of zi being equals to 1.

Where zi in this case can be height for age z-score (stunting), weight for height z-score (wasting) or weight for age z-score (underweight). zi represents the log odds of outcome variables, b0 is the constant. k indicates number of independent x factors among which there may be interaction situations. b in this saturated model is the coefficient of logistic regression. Exponential of b (natural logarithm base e of b) gives the odd ratio of predictor variables. In like manner, exponential of zi gives the odd ratio (estimate of odds) for the outcome variable and in this case, the outcome of interest which is 1 rather than the reference which is 0. The putting together of the predictor variables in a single analytical framework would help in having a reliable and accurate information that would help and guide policy makers when designing their interventional and control programmes for childhood under-nutrition.

Prevalence of under-nutrition at various levels of explanatory variables

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