Malnutrition is one of the most alarming health problems worldwide. Malnutrition is found to be the underlying contributing factor in about 45% of all child deaths, making children more vulnerable to severe diseases. The objective of the study was to identify association of Household Dietary Diversity and Mother’s nutritional knowledge with the nutritional status of under five children in selected study area. A cross sectional study was conducted for this study where about 41.4% of the children were found stunted and about 26.7% of the children were found wasted in the study area. 2% of the children belonged to families with poor food consumption score and 21.3% belonged to families with borderline food consumption score. 41.03% of the children belonged to mothers with poor nutritional knowledge and 56.41% with good nutritional knowledge. To reduce the rate of malnutrition government level measures and steps should be taken to promote nutrition.
Malnutrition is the most common nutritional disorder in developing countries and it remains one of the most common causes of morbidity and mortality among children worldwide 1. Nearly half of all deaths in children under 5 are attributable to under nutrition. Under nutrition puts children at greater risk of dying from common infections, increases the frequency and severity of such infections and contributes to delayed recovery. In addition, the interaction between under nutrition and infection can create a potentially lethal cycle of worsening illness and deteriorating nutritional status. Poor nutrition in the first 1,000 days of a child’s life can also lead to stunted growth, which is irreversible and associated with impaired cognitive ability and reduced school and work performance 2. Research shows that food insecurity is associated with poor health outcomes across the population. A study of eight low income countries found food insecurity to be associated with low height-for-age (stunting) Z-scores among under five children 3. This highlights the importance of food security as a determinant of good health and nutrition among under five children 4. Moreover, Mothers are the main caregiver for their children and the quality of their care largely depends on their nutritional knowledge and health practice. Malnutrition is found to be the underlying contributing factor in about 45% of all child deaths worldwide, making children more vulnerable to severe diseases. Over 5.9 million children under 5 years old died in 2015. Child malnutrition causes 27.9% of child deaths in developing countries in 2015 2. In Bangladesh, about 36% of children of under 5 years are stunted, 14 % are wasted, and 33% are underweight 5. In rural areas of Bangladesh, mother’s poor nutritional knowledge and family food insecurity are the most important determinants for children’s health. This study was conducted mainly to find out the magnitude of child health and association among nutritional status of the children, household dietary diversity and nutritional knowledge of their mother.
In this study relevant data were collected from selected villages of Cummilla which was designed to be the source of typical results for the rural areas of the country. One of the specific objectives of this study was to examine the nutritional status of under-five children using anthropometric measurements (weight and height).
2.2. Response variablesThe widely used measures for malnutrition, defined by three anthropometric indicators stunted (height-for-age), wasted (weight-for-height) and underweight (weight-forage) are considered as the response variables 6. Children are categorized into two groups, ‘suffering from malnutrition’ and ‘not suffering from malnutrition’, for each of the three indicators following the guidelines in the national report of Bangladesh 7 and the World Health Organization 8.
2.3. Covariates/Predictor VariablesA set of interrelated demographic, socioeconomic and environmental factors associated with child nutrition is considered which are: Age of child, sex of child (male, female), place of residence, religion (Muslim and non-Muslim), parent’s education (no education or primary, secondary or higher), father’s occupation (physical labor related, service/desk job/business, others), mother’s occupation(physical labor related, service/desk job/business, others), wealth index (poorest, poorer, middle, richer, richest), mothers nutritional knowledge, sources of drinking water (safe or unsafe), type of toilet facilities (hygienic and non-hygienic), total number of living children and Birth order number.
Table 1 shows that about 20.7% of the children were severely stunted and 20.7% were moderately stunted. About 12.6% of the children were severely thin and 13.5% were moderately thin. It also shows that about 11.7% of the children were severely wasted and 13.5% were moderately wasted.
Table 2 shows that about 2% of the children belonged to families with poor food consumption score, 21.3% belonged to families with borderline food consumption score, 48.7% in acceptable low food consumption and 28% in acceptable high food consumption.
Table 3 represents that about 41.03% of the children belonged to mothers with poor nutritional knowledge, 56.41% with good nutritional knowledge and only 2.56% of the children belonged to mothers with excellent nutritional knowledge.
Table 4 shows that the correlation coefficient between income index and BAZ category was 0.032 and p value was 0.759 which means that the correlation was not significant.
Table 5 shows that maximum percentage of severely stunted (45.4%) belonged to families with less than 5000 taka income, maximum percentage of moderately stunted (47.6%) belonged to families with income between 5000 to 8000 taka and maximum percentage of normal children (45.2%) belonged to families with income above 8000.
Table 6 shows that maximum number of severely underweight (7) belonged to borderline food consumption families, maximum number of moderately underweight (8) belonged to acceptable low food consumption families, maximum number of normal weight (40) children belonged to acceptable low food consumption families and maximum number of overweight (7) belonged to acceptable high food consumption families.
The prevalence of stunting was 41.4% in our study area, whereas it is 36% at national level, 35.8% in South Asia and 22.9% globally. The rate of wasting was 26.7% in our study area whereas it is 14% nationally, 16% in South Asia and 7.7% globally. 20.7% of the children were severely stunted and 20.7% were moderately stunted. About 12.6% of the children were severely thin and 13.5% were moderately thin. It also shows that about 11.7% of the children were severely wasted and 13.5% were moderately wasted. 41.03% of the children belonged to mothers with poor nutritional knowledge, 56.41% with good nutritional knowledge and only 2.56% of the children belonged to mothers with excellent nutritional knowledge. Maximum percentage of severely stunted (45.4%) belonged to families with less than 5000 taka income, maximum percentage of moderately stunted (47.6%) belonged to families with income between 5000 to 8000 taka and maximum percentage of normal children (45.2%) belonged to families with income above 8000.
The result clearly shows that the prevalence of malnutrition is higher in our study area (stunting 41.4% and wasting 26.7%) than national and international level. To reduce the rate of malnutrition, it will require accumulate action at Government and non-Government level. It requires to focus on social and environmental determinants like equitable economic growth, stable and low food prices which have great effect over nutrition. Essential multi-sectoral approaches need be addressed at national level to strengthen policies to promote nutrition. Adequate and effective nutrition sensitive and nutrition specific approaches and programs are required at national level to promote household security, health services and care giving practices.
[1] | Musa, T.H., Musa, H.H., Ali, E.A. and Musa, N.E., 2014. Prevalence of malnutrition among children under five years old in Khartoum State, Sudan. Polish Annals of Medicine, 21(1), pp.1-7. | ||
In article | View Article | ||
[2] | Hoque, M.A., Sayeed, M.A., Ahsan, M.R., Al Mamun, M.A. and Salim, F., 2016. Nutritional Status among under-5 Children of a selected slum in Dhaka city. Northern International Medical College Journal, 7(2), pp.143-145. | ||
In article | View Article | ||
[3] | Seligman, H.K., Bindman, A.B., Vittinghoff, E., Kanaya, A.M. and Kushel, M.B., 2007. Food insecurity is associated with diabetes mellitus: results from the National Health Examination and Nutrition Examination Survey (NHANES) 1999-2002. Journal of general internal medicine, 22(7), pp.1018-1023. | ||
In article | View Article PubMed | ||
[4] | Psaki, S., Bhutta, Z.A., Ahmed, T., Ahmed, S., Bessong, P., Islam, M., John, S., Kosek, M., Lima, A., Nesamvuni, C. and Shrestha, P., 2012. Household food access and child malnutrition: results from the eight-country MAL-ED study. Population health metrics, 10(1), p.24. | ||
In article | View Article PubMed | ||
[5] | NIPORT, M., 2014. Bangladesh Demographic and Health Survey BDHS 2014: Key Indicators. Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training (NIPORT), Mitra and Associates, and ICF International. | ||
In article | |||
[6] | Alam, N., Wojtyniak, B. and Rahaman, M.M., 1989. Anthropometric indicators and risk of death. The American journal of clinical nutrition, 49(5), pp.884-888. | ||
In article | View Article PubMed | ||
[7] | Calverton, M., 2005. National Institute of Population Research and Training (NIPORT). Mitra and Associate and ORC Macro. | ||
In article | |||
[8] | Hayashi, C., Krasevec, J., Kumapley, R., Mehra, V., de Onis, M., Borghi, E., Blössner, M., Urrutia, M.F., Prydz, E.B. and Serajuddin, U., 2017. Levels and trends in child malnutrition. UNICEF/WHO/World Bank Group joint child malnutrition estimates: key findings of the 2017 edition. | ||
In article | |||
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[1] | Musa, T.H., Musa, H.H., Ali, E.A. and Musa, N.E., 2014. Prevalence of malnutrition among children under five years old in Khartoum State, Sudan. Polish Annals of Medicine, 21(1), pp.1-7. | ||
In article | View Article | ||
[2] | Hoque, M.A., Sayeed, M.A., Ahsan, M.R., Al Mamun, M.A. and Salim, F., 2016. Nutritional Status among under-5 Children of a selected slum in Dhaka city. Northern International Medical College Journal, 7(2), pp.143-145. | ||
In article | View Article | ||
[3] | Seligman, H.K., Bindman, A.B., Vittinghoff, E., Kanaya, A.M. and Kushel, M.B., 2007. Food insecurity is associated with diabetes mellitus: results from the National Health Examination and Nutrition Examination Survey (NHANES) 1999-2002. Journal of general internal medicine, 22(7), pp.1018-1023. | ||
In article | View Article PubMed | ||
[4] | Psaki, S., Bhutta, Z.A., Ahmed, T., Ahmed, S., Bessong, P., Islam, M., John, S., Kosek, M., Lima, A., Nesamvuni, C. and Shrestha, P., 2012. Household food access and child malnutrition: results from the eight-country MAL-ED study. Population health metrics, 10(1), p.24. | ||
In article | View Article PubMed | ||
[5] | NIPORT, M., 2014. Bangladesh Demographic and Health Survey BDHS 2014: Key Indicators. Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training (NIPORT), Mitra and Associates, and ICF International. | ||
In article | |||
[6] | Alam, N., Wojtyniak, B. and Rahaman, M.M., 1989. Anthropometric indicators and risk of death. The American journal of clinical nutrition, 49(5), pp.884-888. | ||
In article | View Article PubMed | ||
[7] | Calverton, M., 2005. National Institute of Population Research and Training (NIPORT). Mitra and Associate and ORC Macro. | ||
In article | |||
[8] | Hayashi, C., Krasevec, J., Kumapley, R., Mehra, V., de Onis, M., Borghi, E., Blössner, M., Urrutia, M.F., Prydz, E.B. and Serajuddin, U., 2017. Levels and trends in child malnutrition. UNICEF/WHO/World Bank Group joint child malnutrition estimates: key findings of the 2017 edition. | ||
In article | |||