|Year : 2016 | Volume
| Issue : 1 | Page : 44-49
Sociodemographic correlates of nutritional status of under-five children
Hammer Singh, Varsha Chaudhary, Hari Shankar Joshi, Deepak Upadhyay, Arun Singh, Rashmi Katyal
Department of Community Medicine, Rohilkhand Medical College and Hospital, Bareilly, Uttar Pradesh, India
|Date of Web Publication||21-Jan-2016|
Hari Shankar Joshi
Department of Community Medicine, Rohilkhand Medical College and Hospital, Pilibhit Bypass Road, Bareilly - 243 006, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Background: Malnutrition is one of the most important health problems throughout the world, particularly in developing countries, and has undesirable effects on the mental and physical health of children. Objectives:The objectives of this study were to find out the prevalence of malnutrition in children under 5 years of age (under-five children) and epidemiological determinants associated with it. Materials and Methods:This community-based cross-sectional study was conducted on under-five children in Bareilly, Uttar Pradesh, India belonging to the field practice area of the Rural Health and Training Centre of the Department of Community Medicine of Rohilkhand Medical College and Hospital, Bareilly, applying multistage simple random sampling methodology. Data were collected through measuring weight and height, structural schedules, anthropometric nutritional indicators, and face-to-face interviews with mothers. Malnutrition was measured on the basis of the indices underweight, wasting, and stunting. The obtained data were entered and analyzed using SPSS. Multiple logistic regression analysis was applied as the test of significance. Results:The prevalence of underweight, wasting, and stunting was 33.11%, 46.88%, and 10.44%, respectively. The total prevalence of malnutrition was 57.11%. Malnutrition was found to be significantly associated with age (0-12 months and 25-36 months), sex, socioeconomic status, and maternal education. Conclusion:Malnutrition was found to be more in children aged less than 1 year and in those aged 2-3 years. It was more common in female children, in children of low socioeconomic status, in children from nuclear families, and among those whose mothers were illiterate.
Keywords: Cross-sectional study, epidemiological factors, malnutrition, prevalence, stunting, thinness, underweight, wasting
|How to cite this article:|
Singh H, Chaudhary V, Joshi HS, Upadhyay D, Singh A, Katyal R. Sociodemographic correlates of nutritional status of under-five children. Muller J Med Sci Res 2016;7:44-9
|How to cite this URL:|
Singh H, Chaudhary V, Joshi HS, Upadhyay D, Singh A, Katyal R. Sociodemographic correlates of nutritional status of under-five children. Muller J Med Sci Res [serial online] 2016 [cited 2021 Dec 4];7:44-9. Available from: https://www.mjmsr.net/text.asp?2016/7/1/44/174639
| Introduction|| |
Preschool children constitute the most vulnerable segment of any community. Their nutritional status is a sensitive indicator of community health and nutrition. Any major deviation in the nutrient intake, either in quality or in quantity, from its requirement can affect growth in many ways.  Undernutrition among these children aged less than 5 years (under-five children) is one of the greatest public health problems in developing countries. The devastating effects of undernutrition on child performance, health, and survival are well established today.  Attempts to reduce child mortality in developing countries through selective primary health care have focused primarily on the prevention and control of infectious diseases, with less effort being directed to improving children's underlying nutritional status. A recent global analysis report demonstrated that child undernutrition is the leading cause of the global burden of disease. , and it contributes greatly to the disability-adjusted life years worldwide.  In developing countries, undernutrition affects one out of every three preschool-age children.  During 2003-2008 more than 23% of the world's under-five children were underweight for their age. In India, almost half of the under-five children (48%) are stunted, 43% are underweight, and 20% are wasted, while in Uttar Pradesh 56.8% children are stunted, 42.4% are underweight, and 14.8% are wasted. Undernutrition is substantially higher in rural areas than in urban areas. The prevalence of underweight in children in India is almost twice as high as the average prevalence for the 26 sub-Saharan African countries that have similar data (25%).  Malnutrition among under-five children continues to be one of India's major human development challenges.
The three main indicators used to define undernutrition, i.e., underweight, stunting, and wasting, represent different histories of nutritional insult to the child. Occurring primarily in the first 2-3 years of life, linear growth retardation (stunting) is frequently associated with repeated exposure to adverse economic conditions, poor sanitation, and the interactive effects of poor energy and nutrient intakes and infection. Low weight-for-age indicates a history of poor health or nutritional insult to the child, including recurrent illness and/or starvation, while a low weight-for-height is an indicator of wasting (i.e., thinness), and is generally associated with recent illness and failure to gain weight or a loss of weight. 
Despite several national programs, the nutritional status of children remains almost the same as that of previous years. Lack of food is not the sole cause of malnutrition; there are many sociodemographic factors that seem to be important contributory factors in determining the nutritional status of children. Hence the present study was undertaken to study prevalence of underweight, stunting, wasting, and overall malnutrition in under-fives and to find out epidemiological determinants associated with malnutrition.
| Materials and Methods|| |
This was a community-based cross-sectional study among under-five children in Bareilly district. Bareilly district belongs to the state Uttar Pradesh in northern India. It has a population of about 44.5 lakh (2.23% of Uttar Pradesh), of which about 7 lakh are children aged less than 6 years, and 64.74% of its population lives in rural areas, of which 17.2% are under-six children (4.9 lakh).  This study was carried out in the field practice area of the Rural Health and Training Centre of the Department of Community Medicine of Rohilkhand Medical College and Hospital, Bareilly during January 2013 to December 2013. The unit of study was the child under 5 years of age residing in a rural field practice area. All the children aged 0-5 years present at the time of survey and whose mothers gave consent to participate in the study were included in the study, whereas children whose parents or guardians did not give consent, children who were temporary visitors to the house, and children who were severely ill were excluded from the study. A sample size of 450 was calculated using the formula 4PQ/L,  where P is the prevalence of malnutrition, which is taken as 48%;  Q is 100-P, and L is 10% of P. The study protocol was approved by the institutional Ethics Committee. Multistage random sampling was used. In the first stage, one block (Bithrichainpur) was selected randomly out of two blocks in the field practice area of Rural Health Training Centre. In the second stage, out of total 60 villages in the selected block, 30 villages were selected randomly. As the desired sample size was 450, therefore 15 under-five children were randomly selected from each village. In each village, first of all we numbered all the houses. The first house was chosen by lottery method. Then each consecutive house was searched for under-five children till the desired number of study subjects was obtained. After visiting a house, informed consent taken and detailed interview of the caregiver was conducted and entered in a predesigned schedule. The schedule comprised three parts:
- Personal information of child and caregiver or parents
- Detailed history of child on various aspects
- Anthropometric measurements of child.
The validity of the schedule was tested by experts (including a statistician) for language and by analyzing the pilot study, which was conducted on 50 children from the community randomly; these would be excluded from the main study sample. Data on part (a) and part (b) were gathered by different observers, who were trained beforehand. Anthropometric measurements were taken by the principal author. Blinding was ensured between the different observers. Data collection quality was supervised by all authors independently.
The age of each child was determined by reviewing the birth certificate and if the birth certificate was not present, age was listed as told by the mother. Anthropometric measurements were carried out following standard methods. The data included weight, recumbent length (for children aged less than 24 months), and height (for children agedmore than 24 months). Weight was measured to the nearest 0.1 kg and Salter weighing machine was used for weight measurement. Height was measured against a nonstretchable tape fixed to a vertical wall, with the participant standing on a firm surface, to the nearest 0.5 cm. Recumbent length was measured by using an infant measuring board. Socioeconomic status was determined by using modified B.G Prasad's classification.
The height and weight of each child was compared with the World Health Organization (WHO) child growth standards, 2006 reference data for his/her particular age and sex, to obtain weight for age, height for age, and weight for height indices. Children below two standard deviations (SDs) of the reference median on any of these indices were considered as undernourished and termed as underweight, stunted, and wasted, respectively. Children below three SDs were considered to be severely undernourished. 
The percentage of children 0-59 months old who were below minus two SDs from median weight for age according to WHO Child Growth Standards were considered underweight.
The percentage of children 0-59 months old who were below minus two SDs from median weight for height according to WHO Child Growth Standards were considered wasted.
The percentage of children 0-59 months old who were below minus two SDs from median height for age according to WHO Child Growth Standards were considered stunted.
The data were collected, entered, and analyzed by using the Statistical Package for Social Sciences (SPSS) version 12.0. Data are presented in the form of tables and they were statistically analyzed using multiple logistic regression analysis.
| Results|| |
Out of the total of 450 children, 253 (56.2%) were males, the maximum being in the age group 0-12 months (70.0%) and 197 (43.8%) were females, the maximum (48.3%) being in the age group 49-60 months [Table 1]. It was observed that 95 (21.1%) children were underweight and 54 (12.0%) were severely underweight; 105 (23.3%) children were stunted and 106 (23.6%) were severely stunted; and 33 (7.3%) children were wasted and 14 (3.1%) were severely wasted [Table 2].
|Table 1: Age- and gender-wise distribution of study population (N = 450)|
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|Table 2: Prevalence of underweight, stunting, and wasting in study population|
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A child either underweight, stunted, wasted, or any combination of the three was considered as having malnutrition. In the present study, the prevalence of malnutrition was observed to be 57.1%. Malnutrition was found to be highest among infants (85%) and lowest among 49-60 month-old children (47.8%). Malnutrition was prevalent more among female children (60.9%), children belonging to Muslim families (64.4%), children from class V socioeconomic status (100%), children from nuclear families (58.8%), and children whose whose mothers were illiterate (62.2%) [Table 3].
On applying multiple logistic regression analysis, malnutrition was found to be significantly associated with age (0-12 months and 25-36 months), sex, socioeconomic status, and maternal education (P < 0.05). Inverse association was found for malnutrition with sex and socioeconomic status with respect to the reference. Children in the age group 0-12 months had 8.2 times and children in the age group 25-36 months had 2.9 times more chances of having malnutrition with respect to reference; males had 0.6 times less chances of having malnutrition with respect to females; children of socioeconomic class I, II, III, and IV had 1.4 times, 1.9 times, 2.0 times, and 1.5 times less chances of having malnutrition as compared to class V; and children of illiterate mother had 1.9 times more chances of having malnutrition as compared to children of literate mothers [Table 4].
|Table 4: Multivariate logistic regression analysis of predictors influencing malnutrition|
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| Discussion|| |
According to the studies done, nutritional deficiencies not only affect the physical and mental development of children but also cause the mortality of 14 million children in the world.  In the present study, the prevalence of underweight, stunting, wasting, and overall malnutrition in under-fives and the relation of malnutrion to various epidemiological factors were assessed in 450 children.
Age- and Gender-wise Distribution of Study Population
Out of total 450 children, 56.2% were male and 43.8% were female. Of the total, 8.9% were in the age group 0-12 months, 15.6% in 13-24 months and 15.56% in 37-48 months, 14.4% in 25-36 months, and 45.5% in 49-60 months.
Prevalence of Underweight, Stunting, and Wasting
In our study, the prevalence of underweight, wasting, and stunting was 33.1%, 10.4%, and 46.9%, respectively, and similar findings were observed by Kumar et al. in urban areas of Allahabad  (36.4%, 57.6%, and 10.6%) and by Bloss et al.  in western Kenya (30.0%, 47.0%, and 7.0% respectively). These findings of our study were higher than those from the studies conducted by Kumar et al. in Mysore  (21.5%, 22.5%, and 7.5%), Ergin et al.  in Turkey (4.8%, 10.9%, and 8.2%), and Wang et al.  in poor areas of China (10.2%, 30.2%, and 2.9%), but lower than those from the studies conducted by Dhatrak et al.  in Nagpur (46%, 52%, and 20.7%), Sengupta et al.  in Ludhiana (29%, 74%, and 42%), Biswas et al.  in Kolkata (64.9%, 64.9%, and 20.3%), Rao et al.  in Jabalpur (61.6%, 51.6%, and 32.9%), Sharifzadeh et al.  in south Khorasan in Iran (41.3%, 45%, and 32.2%), and Singh et al.  in rural Bareilly (53.8%, 43.22%, and 60.7%). The higher prevalence of undernutrition, stunting, and wasting observed by Singh et al.  in Bareilly may be because it was a hospital-based study, while our study was community based.
Nutritional Status with Relation to Sociodemographic Characters
A child either underweight, stunted, wasted, or any combination of the three was considered as having malnutrition; 57.1% was the prevalence of malnutrition in our study. Similar findings were observed by Garg et al.  in slums of Ghaziabad (58.2%), while slightly lower prevalence was reported by Avachat et al.  in rural areas of Loni (50.4%) and by Banerjee et al.  in West Bengal (50.67%). In comparison to our study, a very high prevalence of malnutrition in rural Bareilly was reported by Singh et al.  (76.36%). The reason for this high prevalence was probably that it was a hospital-based study. In our study, malnutrition was found to be significantly associated with age and sex, which is comparable with the findings of studies conducted by Sengupta et al.,  Rao et al.,  Singh et al.,  Avachat et al.,  and Sharghi et al.,  and contradicts the findings of Dhatrak et al.,  which observed no association of malnutrition with age and gender. In our study, malnutrition was significantly high among children aged 0-12 months and 25-36 months, whereas Singh et al. 23] and Avachat et al.  in their study reported malnutrition to be significantly higher in children aged 13-60 months and 13-36 months. In the present study, malnutrition was found to be higher among Muslims as compared to Hindus, and higher among children from nuclear families as compared to joint families, but the association was found to be insignificant. In our study, an inverse association of malnutrition was found with socioeconomic status. Children from low socioeconomic class were significantly malnourished, and similar findings were reported by various other studies. ,,,, In our study, malnutrition was found to be significantly higher among children whose mothers were illiterate. Various other studies ,,,,, also show the relationship of malnutrition with illiteracy and low education of parents. There are two connected factors: higher knowledge of literate parents and higher income of families with higher education. Obviously, income is one of the most important factors in providing the access to health care, education, and nutrition facilities and thus among the factors precipitating malnutrition. Besides, knowledge together with enough income can improve the nutritional status of the family, compared to the inability of many illiterate parents to do so.
| Conclusion|| |
In the present study, malnutrition was observed in more than half of the study population. Malnutrition was found to be significantly high in the age group less than 1 year and among children 2-3years of age. It was more prevalent among females than males, among Muslims than Hindus, among children of low socioeconomic status groups and from nuclear families, and among children of illiterate mothers. The study strongly points toward the importance of proper infant feeding practices, proper nutrition, parental education, and improved living conditions for reducing malnutrition among under-five children. The high prevalence of malnutrition in the community requires a multipronged approach encompassing maternal and child health care, nutritional education, growth monitoring, and coordination with income generation and food production activities to make nutritional interventions more effective. More research is required in this area in order to see the effect of interventions applied to reduce the level of malnutrition.
The authors are thankful to the staff of the Rural Health Training Centre of the Department of Community Medicine for their cooperation during the study. The authors also thank all the families who participated in the study.
Financial Support and Sponsorship
Conflicts of Interest
The authors declare that they have no competing interests.
| References|| |
Mishra BK, Mishra S. Nutritional anthropometry and preschool child feeding practices in working mothers of Central Orissa. Stud Home Comm Sci 2007;1:139-44.
Pelletier DL, Frongillo EA. Changes in child survival is strongly associated with changes in malnutrition in developing countries. J Nutr 2003;133:107-19.
Rodgers A, Ezzati M, Vander Hoorn S, Lopez AD, Lin RB, Murray CJ, et al
. Distribution of major health risks: Finding from the global burden of disease study. PLoS Med 2004;1:44-55.
de Onis M, Blössner M, Borghi E, Morris R, Frongillo EA. Methodology for estimating regional and global trends of child malnutrition. Int J Epidemiol 2004;33:1260-70.
Murray CJ, Lopez AD. The Global Burden of Disease. A comprehensive assessment of mortality and disability from diseases, injuries and risk factors in 1990 and projected to 2020. GBD Series Vol. 1. Cambridge: Harvard School of Public Health on behalf of the World Health Organization and the World Bank; 1996.
UN system standing committee on Nutrition. 5 th
Report on the World Nutrition Situation: Nutrition for Improved Development Outcomes. Geneva: SCN; 2004.
Arnold F, Parasuraman S, Arokiasamy P, Kothari M. 2009. Nutrition in India. National Family Health Survey (NFHS-3), India, 2005-06. Mumbai: International Institute for Population Sciences; Calverton, Maryland, USA: ICF Macro. Available from: http://www.rchiips.org/nfhs/nutrition_report_for_website_18sep09.pdf
. [Last accessed on 2015 Jan 3].
Bloss E, Wainaina F, Bailey RC. Prevalence and predictors of underweight, stunting and wasting among children aged 5 and under in western Kenya. J Trop Pediatr 2004;50:260-70.
Park K. Park′s Text Book of Preventive and Social Medicine. 22 nd
ed. Madhya Pradesh: Jabalpur/s Banarsidas Bhanot; 2013. p. 509.
Suryakantha A. Community Medicine with Recent Advances. 2 nd
ed. New Delhi: Jaypee Brother; 2010. p. 591-658.
World Health Organization. WHO Multicentre Growth Reference Study Group. WHO Child Growth Standards: Length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: Methods and development. Geneva: World Health Organization; 2006. p. 312.
Mahan LK. Medical nutrition therapy. In: Mahan LK, editor. Escott-Stumps. Food Nutrition and Diet Therapy. 11 th
ed. Philadelphia: Saunders; 2004. p. 74-6.
Kumar D, Goel NK, Mittle P, Misra P. Influence of Infant-feeding practices on nutritional status of Under- five children. Indian J Pediatr 2006;73:417-21.
Kumar AS, Koppad R, Ashok NC, Madhu B, Kumar DS, Dham M, et al
. Mother literacy status and its association with feeding practices and PEM among 1-5 year aged children in southern part of India, Mysore. Asian Pac J Trop Dis 2012;2:S624-8.
Ergin F, Okyay P, Atasoylu G, Beşer E. Nutritional status and risk factors of chronic malnutrition in children under-fives of age in Aydin, A western city of Turkey. Turk J Pediatr 2007;49:283-9.
Wang X, Höjer B, Guo S, Luo S, Zhou W, Wang Y. Stunting and ′overweight′ in the WHO child growth standards. Malnutrition among children in a poor area of China. Public Health Nutr 2009;12:1991-8.
Dhatrak PP, Pitale S, Kasturwar NB, Nayse J, Relwani N. Prevalence and Epidemiological determinants of malnutrition among under-fives in an urban slum, Nagpur. Natl J Community Med 2013;4:91-5.
Sengupta P, Philip N, Benjamin AI. Epidemiological correlates of under-nutrition in under -5years children in an urban slum of Ludhiana. HPPI 2010;33:1-9.
Biswas T, Mandal PK, Biswas S. Assessment of health, nutrition and immunization status amongst under 5 children in migratory brick kiln population of periurban Kolkata, India. SJPH 2011;6:7-13.
Rao VG, Yadav R, Dolla CK, Kumar S, Bhondeley MK, Ukey M. Undernutrition and childhood morbidities among tribal preschool children. Indian J Med Res 2005;122:43-7.
Sharifzadeh G, Mehrjoofard H, Raghebi S. Prevalence of malnutrition in under 6-years olds in South Khorasan, Iran. Iran J Pediatr 2010;20:435-41.
Singh JP, Gupta SB, Shrotriya VP, Singh PN. Study of nutritional status among under five children attending outpatient department at a primary care rural hospital. Bareilly Sch J App Med Sci 2013;1:769-73.
Garg SK, Singh JV, Bhatnagar M, Chopra H. Nutritional status of children in slums of Ghaziabad. IJCM 1997;22:70-3.
Avachat SS, Phalke VD, Phalke DB. Epidemiological study of malnutrition (under nutrition) among under five children in a section of rural area. Pravara Med Rev 2009;1:20-2.
Banerjee B, Mandal ON. An interventional study in malnutrition among infants in tribal community of West Bengal. Indian J Community Med 2005;30:27-9.
Sapkota VP, Gurung CK. Prevalence and predictors of underweight, stunting and wasting in under-five children. J Nepal Health Res Counc 2009;7:120-6.
Khattak M, Ali S. Malnutrition and associate risk factors in pre-school children (2-5 years) in district Swabi (NWFP)-Pakistan. J Med Sci 2010;10:34-9.
Dhakal MM, Rai A, Singh CM, Mahapatra SC. Health impact assessment: A futuristic approach in under - Five care. Indian J Community Med 2005;36:114-20.
Deshmukh PR, Dongre AR, Gupta SS, Garg BS. Newly developed WHO growth standards: Implications for demographic surveys and child health programs. Indian J Pediatr 2007;74:987-90.
Nojomi M, Tehrani A, Najm-Abadi S. Risk analysis of growth failure in under-5-year children. Arch Iranian Med 2004;7:195-200.
Yarparvar A, Omidvar N, Golestani B, Kalantari N. Assessing the nutritional status of the preschool 6-59 months children and some related factors in earthquake affected areas of Bam. Iran J Nutr Sci Food Technol 2006;1:33-43.
Senbenjo IO, Adeodu OO, Adjuyigbe EA. Low prevalence of malnutrition in rural Nigerian community. Trop Doct 2007;37:214-6.
[Table 1], [Table 2], [Table 3], [Table 4]