Open Access
Determinants of Nutritional Status among School Girls in Chittagong Metropolitan Area
Author(s) -
Abdul Karim,
Jesmin Akter
Publication year - 2021
Publication title -
the chittagong university journal of science
Language(s) - English
Resource type - Journals
ISSN - 1561-1167
DOI - 10.3329/cujs.v41i1.51914
Subject(s) - underweight , demography , overweight , residence , body mass index , family income , medicine , socioeconomic status , geography , population , pathology , sociology , economics , economic growth
This study aims to investigate the determinants of nutritional status (BMI) of school girls, selected randomly from the schools of Chittagong metropolitan area because good nutritional status is a prerequisite for good health, fertility and national productivity. The results of this study show that more than one-third (38.6%) school girls belong to underweight, 47.9% normal and 13.5% overweight. The overall mean BMI of the selected girls is found 20.03±4.06 kg/m2 with considerable variations by their background characteristics. The co-efficient of variation (20.27%) indicates that there exists extreme heterogeneity in BMI of the respondents. Co-efficient of skewness (β1=0.85) and excess of kurtosis (γ2=1.05) reflect that the distribution of BMI is positively skewed and leptokurtic. The mean BMI is found relatively high among the respondents living in the metropolitan area (21.18 kg/m2). The highest mean BMI is found among the girls belong to high family income group (21.62 kg/m2) and low (18.69 kg/m2) in lower family income group. Bivariate analysis indicates that religion, place of origin, place of residence, respondents’ education, arm circumference, fathers and mothers education and occupation, family income, family size, sibling size, skipping and cycling, duration of sporting activity and sleeping, and food intake are found to have significant association with nutritional status of the girls. The study also shows that BMI is significantly positively correlated with family income and negatively with duration of sporting activities. Multinomial logistic regression analysis illustrates that place of residence, arm circumference, mothers’ occupation, duration of sleeping and food intake is found significant predictors of BMI.
The Chittagong Univ. J. Sci. 40(1) : 39-67, 2019