Prevalence and determinants of stunting in under-five children in central Tanzania: remaining threats to achieving Millennium Development Goal 4

Abstract

BackgroundThe Millennium Development Goal No 4 (MDG 4) requires countries to scale up interventions addressing malnutrition and other immediate determinants of burden of disease among children to reduce child mortality by two thirds by 2015, which is this year. Whereas globally some achievements have been registered, under-nourishment remains a significant problem in some developing countries such as Tanzania. This study set out to estimate the extent of stunting and its associated determinants to assess the progress made thus far towards achieving MDG 4 in Tanzania.MethodsA random sample of 678 households with under-five children was selected from two randomly selected wards of Kongwa district in Dodoma region, Tanzania. The WHO anthropometric calculator, which computes Z-scores using a reference population, was used to process the anthropometric measurement data taken from all the participants. Children with height for age Z-score of less than 2 were categorised as stunted and coded as 1 and the rest were coded as 0. Proportions of stunting were compared using the chi-square test to determine the association between stunting and the independent variables. Multivariate logistic regression analysis was carried out to determine the Adjusted Odds Ratio (AOR) of the independent determinants of stunting. The cut-off for significant association was set at p = 0.05. All these analyses used the STATA 12 software.ResultsAbout half (49.7 %) of the children were stunted. This stunting was associated with belonging to households where the head of family was young (<35 years) (AOR = 0.67, 95 % CI 0.47–0.96, p = 0.031), young age of the mothers (AOR = 1.54, 95 % CI 1.06–2.24, p = 0.023), and economic variables such as owning a cellular phone (AOR = 0.66, 96 % CI 0.46–0.94, p = 0.023).ConclusionsStunting was highly prevalent in Kongwa district despite general improvements in child nutritional status at the national level. Household characteristics and economic status were found to play a major role in child health. In this regard, disaggregated analyses are therefore important in identifying resilient areas in need of concerted efforts for the MDG 4 to be achieved nationwide.

Affecting Factors of Stunting Incidences among Children Aged 12-59 Months in West Nusa Tenggara Province Indonesia

“…The pregnant women aged <20 and >35 years old were mostly found in children with stunting, than the children who were not experienced stunting (18.8%). The result is parallel with the research that stated pregnant women aged less than 25 years old have higher risk having children with stunting than pregnant women aged more than 25 years old [6]. A research done in Ghana found that stunting also happened to older women aged 35-44 years old during pregnancy [16].…”

“…The low birth weight children were mostly found with stunting cases, than the children who were not experienced stunting (23.4%). Based on previous research, the low birth weight children have 5.5 risk to experiences stunting have [6]. The result of bivariate analysis resulted in the statistic correlation between birth length and stunting incidences.…”

“…Another factor which is assumedly contributes to the stunting incidences is the the age of the mother during pregnancy. If during pregnancy the mother is too young (less than 20 years), will lead to higher risk of pregnancy's complications as they are not ready to face both physically and emotionally difficulties of prenanncy [6]. On the other hand, if the mothers is getting older, the body fuction will not perfom well, and will cause abnormal fetus or children development [7].…”

Predictors of poor nutritional status among children aged 6–24 months in agricultural regions of Mali: a cross-sectional study

“…A number of authors in Sub-Saharan Africa, including Ethiopia [9][10][11], Kenya [12], Ghana [13], Tanzania [14], and Uganda [15,16] have investigated the predictors of childhood undernutrition. Although the predictors reported varied according to the settings, they included food insecurity and food diversity [9,11], child sex and age [10,13,15], childbirth weight [13], the parents' educational level [10,15], household socioeconomic status [13,14], breastfeeding [17], water, sanitation, hygiene [12,16], and child health among which diarrhea [10,13,17], fever, and coughing [16] were focused on.…”

The Development and Growth of Children Aged under 5 years in Northeastern Thailand: a Cross-Sectional Study

“…The Lancet series reviewing the maternal and child malnutrition in low-income and middle-income countries showed that the prevalence of stunting and wasting of children under five years was relatively higher in south Asia and subSaharan Africa [19]. Pregnant adolescents have a higher risk of malnutrition [19] which can result in growth failure [20,21] and developmental delay [14] and may subsequently reflect abnormal psychological behaviors in adolescence [4,22].…”