Socio-economic and demographic correlates of stunting among adolescents of Assam, North-east India

Abstract

The prevalence of stunting (low height-for-age) is a key indicator of long-term chronic undernutrition which reflects an anthropometric failure to reach linear growth potentials due to prolonged food deprivation and/or disease or illness during the early stage of life. The present study assesses the prevalence and socio-economic and demographic correlates of stunting among adolescents of the North-east India. This cross-sectional study was undertaken among 1,818 (830 boys; 988 girls) adolescents (aged 10-18 years) belonging to ethnically heterogeneous populations of Karbi Anglong district of Assam, using stratified random sampling method. Anthropometric measurements of height and weight were recorded using standard procedures. Socio-economic and demographic variables were obtained using pre-structured schedule. The age-sex specific L, M and S reference values were used to calculate height-for-age Z-score (HAZ). According to WHO, HAZ found to be <−2SD was classified as stunting. The data were analysed using descriptive statistics, t-test, ANOVA, chi-square analyses, binary and step-wise multiple logistic regression analysis in SPSS (version, 17.0). The prevalence of stunting was observed to be significantly higher among boys (48.4%) than girls (37.8%) (p<0.01). Age-sex specific prevalence was found to be higher among boys than girls aged 14-18 years and contrary were observed among girls aged 10-14 years (p>0.05). The binary logistic regression analysis showed that several socio-economic and demographic variables were significantly associated with stunting (p<0.05). The step-wise multiple logistic regression analysis showed that sex (boys), age groups (13-15 years and 16-18 years), father’s occupation (cultivator) and Rupees ≤5000 household income was significantly associated with stunting (p<0.05). Appropriate nutritional intervention programmes and dissemination of knowledge at population level related to undernutrition are necessary to ameliorate their nutritional status.

Prevalence of stunting and associated factors among preschool children: A community based comparative cross sectional study in Ethiopia

“…Studies from Tigray Region, Ethiopia [38] and India [46] reported similar results. The association between large family size and stunting among preschool children can be partially explained by as the number of families increased in the household, the food consumption and expenditure will also be increased.…”

Undernutrition and Associated Factors Among Adolescent Girls in Damot Sore District, Southern Ethiopia

“…Those adolescents whose mothers attended secondary and more than secondary education were 47.0% and 75.0% less likely stunted respectively as compared to girls whose mothers have no formal education. This finding goes in line with the study conducted in different parts of Ethiopia and other developing countries [14,22,34,36,[40][41][42]. This is due to the fact that as the level of education of the mother increases, so do her finances as to increased productivity and her contribution to the total family income.…”

Use of upper arm anthropometry, upper arm muscle area-by-height (UAMAH) and midupper- arm-circumference (MUAC)-for-height as indicators of body composition and nutritional status among children

“…Therefore, high prevalence of wasting among children in the present study indicates poor physical growth attainment in terms of lower protein reserves and indicative of chronic undernutrition. The principal cause of undernutrition among these children may be attributed to, illiteracy, disease prevalence and lack of access to sufficient food and resource amenities (Mondal and Sen 2010;Sen and Mondal 2013;Rengma et al 2016). The continuation of poor muscle and adiposity pattern is probably due to their poor nutritional status as reflected in the conventional upper arm indices.…”

“…This scale allows determination of SES based on a score calculated from education, occupation and monthly income and has been used in many studies done in the field of nutritional research (e.g., Mondal and Sen 2010;Sen et al 2011;Sen and Mondal 2013;Singh and Mondal 2014;Rengma et al 2016). Data on SES was recorded from the parents through Unauthenticated Download Date | 5/11/18 3:17 PM personal interviews conducted in the schools as well as through household visits.…”

“…Using these anthropometric measurements, a considerable number of epidemiological investigations have been conducted to assess body composition and undernutrition among children (e.g., Gültekin et al 2006;Chowdhury et al 2007;Chowdhury and Ghosh 2009;Sen et al 2011;Sen and Mondal 2013;Sen et al 2015). Studies have also pointed to the fact that body composition and nutritional status were affected by a number of socio-economic variables (Sen et al 2011(Sen et al , 2015Sen and Mondal 2013;Singh and Mondal 2014;Rengma et al 2016). Upper arm anthropometry is composed of upper arm muscle area (UMA), total upper arm area (TUA), upper arm fat area (UFA), arm fat index (AFI), upper arm fat area estimate (UFE) and upper arm muscle area estimate (UME) to assess body composition.…”