Nutritional Status and the Characteristics Related Malnutrition in Children Under Five Years of Age in Dhamtari District, Chhattisgarh
Som Prakash Kanwar1, Moyna Chakrawarty2
1Lab Technician, School of Studies in Anthropology, Pt. Ravishankar shukla University, Raipur CG.
2Professor (Retd.), School of Studies in Anthropology, Pt. Ravishankar shukla University, Raipur CG.
*Corresponding Author E-mail: somprakashknwr1@gmail.com, moynaanthro@gmail.com
ABSTRACT:
Malnutrition among children under five years of age is chronic problem in the most regions of India. This study estimatted that prevalence and identified the risk factors of malnutrition among children under five years of age in Dhamtari District, Chhattisgarh. 248 Kamar children aged 12-59 months comprising of 125 girls and 123 boys were selected purposively from two blocks viz Magarlod and Nagri of Dhamtari District, Chhattisgarh region of Central India. The study estimatted prevalence of malnutrition and investigated the effects demographic, socioeconomic and child birth order, birth weight, duration of exclusive breast feeding and variables of malnutrition, stunting, underweight and wasting among under five years of age of Kamar children. Logistic regression was used to identify the determinants of malnutrition in the study area.
KEYWORDS: Malnutrition under five children Dhamtari.
INTRODUCTION:
Nutritional status of children provides an indirect measurement of quality of life of an entire population. Under nutrition is a major threat to the survival, growth and development of Indian children. They are vulnerable to malnutrition due to low dietary intake, lack of child care, intrauterine growth retardation and a high rate of infectious diseases. The prevalence of underweight is extremely high in South Central Asia which accounts for almost half of the global problem.
Children below the age of 5 years constitute 15% of the total population of country and from nutritional point of view they form a vulnerable segment. The factors affecting child malnutrition is very complex and are influenced by multidimensional factors which have not yet been much explored specially among the tribes of Chhattisgarh. Child associated severe malnutrition so that appropriate nutrition. The present study was confined to Kamars which is a particularly vulnerable tribal group of Chhattisgarh. According to census 2011 the total population of Kamar is 26,530 which is almost 0.34% of the scheduled tribe of the state.
Dhamtari district of Chhattisgarh state has 342 villages. It comprises of three tahsils and four blocks viz. Dhamtari, Nagri, Kurud and Magarlod. Out of the four blocks only two blocks were selected for the present study. Predominantly Kamar inhabited villages were selected purposively from Nagri and Magarlod block of Dhamtari district. Twenty villages each having more than twenty Kamar families were selected. All the households having 12-59 months were selected for data collection. In total 198 households were selected for the present study. 248 Children (123 boys and 125 girls) aged 12-59 months and their mothers/ care takers formed the sample for the present study. It was a cross sectional population based study. Interview schedule was developed pertaining to the demographic characteristics of household, nutritional status of children, child care practices, immunization status of children, clinical signs of malnutrition, mother’s nutritional status, etc. An attempt was made to assess the magnitude of child malnutrition and the factors affecting it among Kamar tribe of Dhamtari.
Techniques of Martin and Saller (1959) was followed for taking the anthropometric measurements. Z scores for height for age (HAZ), weight for age (WAZ) and weight for height (WHZ). Children who were below the median of the reference standards for these indicators were classified as stunted, underweight and wasted respectively. SPSS version 16.0 was used for data analysis.
RESULTS:
Table 01. Percentege distribution of respondents by background characteristics of Kamars
|
Characteristics Number Percentage |
|
Age in months |
12-23 58 23.28
24-35 51 20.57
36-47 80 32.25
48-59 59 23.90
Gender
Boy 123 49.60
Girl 125 50.40
Birth order
1-2 99 50.00
3-4 81 40.91
5-6 14 7.07
7-8 4 2.02
Birth weight
Low Weight 49 19.76
Normal Weight 199 80.24
Duration of exclusive breast feeding
≥ 6 months 90 45.45
≤ 6 months 03 1.52
12 months 01 0.50
No response 104 52.53
Type of household
Pucca 8 4.04
Semipucca 172 86.88
Kachcha 15 7.57
Grass House 03 1.51
Mothers occupation
Labourer 107 54.04
Agricultural labourer 74 37.38
Basketry 10 5.05
House wife 5 2.53
Anganwadi sahayika or Cook 2 1.00
Mother’s Education
Illiterate 122 61.61
Primary 59 29.81
Middle 16 8.08
Secondary, Higher Secondary and above 1 0.05
Father’s Education
Illiterate 65 32.82
Primary 87 43.95
Middle 32 16.16
Secondary, Higher Secondary and above 14 7.06
The results in Table 1 shows that of the total 248 Kamar children in the sampled households, 50.40% and 49.60% were girls and boys respectively. The table reveals that almost half of them were of 1-2 birth order and in 40.91% the birth order was observed to be 3-4 and in 7.07% the order of birth was 5-6 and in very few i.e. 2.02% it was 7-8. The majority i.e. about 80% children are born normal and only 20% of the Kamar children were recorded to have low birth weight i.e. below 2.5 kg at the time of birth.
Majority i.e. 45.45% of them felt that it should be 6 months. 1.52% felt that it should be 8 months. 52.53% however failed to reply regarding their perception regarding duration of exclusive breast feeding. The type of household among the Kamars under study. The table shows that majority i.e. 86.88% of the Kamars had semipucca type of house and 7.57% of them had Kachcha type and only 4.04 had pucca type of house. 1.51% however had house made of grass.
Status of occupation of mother of the Kamar children. The table reveals that 54.04% of them were labourers. 37.38% were occupied as agricultural labourer. 5.05% of the respondents were engaged in basketry. Only 2.53% were house wives and 1.00% each was either engaged as anganwadi sahayika or cook.
The percentage frequency of level of education of parents of the Kamar children. The table reveals that 61.61% of the mothers and 32.83% of the fathers did not receive any formal education. If at all received any formal education majority of them attained only primary education i.e. 29.81% of the mothers and 43.95% of the fathers. Very few of them had secondary and higher secondary education where as only 8.08% of the mothers and 16.16% of the fathers had received middle school education. When both the sexes were combined together 47.22% of the parents had no formal education and 36.88% had primary education and very few had middle and higher education.
Table 02. Logistic regression estimate of the effect of explanatory variable of stunting
|
Variables |
B |
S.E. |
Wald |
df |
Sig. |
Exp (B) |
95.0% C.I. for EXP (B) |
|
|
Lower |
Upper |
|||||||
|
Age of child |
-0.861 |
0.498 |
2.991 |
1 |
0.084 |
0.423 |
0.159 |
1.122 |
|
Gender |
-0.480 |
0.526 |
0.834 |
1 |
0.361 |
0.619 |
0.221 |
1.733 |
|
Birth Weight |
0.737 |
0.542 |
1.847 |
1 |
0.174 |
2.090 |
0.722 |
6.053 |
|
Effected with Diarrhoea |
1.268 |
1.066 |
1.416 |
1 |
0.234 |
3.555 |
0.440 |
28.721 |
|
Symptoms of malnutrition |
1.024 |
0.533 |
3.686 |
1 |
0.055 |
2.784 |
0.979 |
7.919 |
|
Exclusive Breast feeding |
-0.066 |
1.128 |
0.003 |
1 |
0.953 |
0.936 |
0.102 |
8.546 |
|
Initiation of supplementary food |
-0.087 |
0.891 |
0.010 |
1 |
0.922 |
0.917 |
0.160 |
5.258 |
|
Constant |
-3.086 |
1.955 |
2.492 |
1 |
0.114 |
0.046 |
- |
- |
The above table explains the estimates of the logistic regression model. The values of Wald estimate shows the importance of each variable for their contribution to the model. The more important variable will have a higher value. The above analysis identified that symptoms of malnutrition (Wald=3.686) is the most important variable affecting stunting in the studied population, followed by age of child (Wald=2.991), birth weight (Wald=1.847), effected with diarrhea (Wald=1.416), gender (Wald=0.834), initiation of supplementary food (Wald=0.010), exclusive breast feeding (Wald=0.003) respectively. The Exp (B) gives the vales of odds ratios. effected with diarrhoea has the highest value (OR=3.555) followed by symptoms of malnutrition (OR=2.784), birth weight (OR=2.090) respectively.
Table 03. Logistic regression estimate of the effect of explanatory variable of underweight
|
Variables |
B |
S.E. |
Wald |
df |
Sig. |
Exp (B) |
95.0% C.I. for EXP (B) |
|
|
Lower |
Upper |
|||||||
|
Age of child |
-2.010 |
0.544 |
13.665 |
1 |
0.000 |
0.134 |
0.046 |
0.389 |
|
Gender |
0.497 |
0.492 |
1.022 |
1 |
0.312 |
1.644 |
0.627 |
4.309 |
|
Birth Weight |
1.085 |
0.506 |
4.593 |
1 |
0.032 |
2.960 |
1.097 |
7.983 |
|
Effected with Diarrhea |
0.016 |
0.647 |
0.001 |
1 |
0.980 |
1.016 |
0.286 |
3.612 |
|
Awareness of s ymptoms of malnutrition |
1.694 |
0.522 |
10.544 |
1 |
0.001 |
5.443 |
1.958 |
15.136 |
|
Excusive Breast feeding |
-2.411 |
0.813 |
8.803 |
1 |
0.003 |
0.090 |
0.018 |
0.441 |
|
Initiation of Supplementary food |
0.201 |
0.919 |
0.048 |
1 |
0.827 |
1.223 |
0.202 |
7.406 |
|
Constant |
-1.360 |
1.524 |
0.796 |
1 |
0.372 |
0.257 |
- |
- |
The above table explains the estimates of the logistic regression model. From the above table it can be seen that age of child (Wald=13.665) is the most important variable affecting WAZ in the studied population, followed by symptoms of malnutrition (Wald=10.544), exclusive breast feeding (Wald=8.803), birth weight (Wald=4.593), gender (Wald=1.022), initiation of supplementary food (Wald=0.048), effected with diarrhea (Wald=0.001). The Exp (B) gives the values of odds ratio awareness of symptoms of malnutrition has the highest value (OR=5.443) followed by birth weight (OR=2.906), gender (OR=1.644), initiation of supplementary food (OR=1.223), effected with diarrhoea (OR=1.016), respectively.
Table 04. Logistic regression estimate of the effect of explanatory variable of wasting
|
Variables |
B |
S.E. |
Wald |
df |
Sig. |
Exp (B) |
95.0% C.I. for EXP (B) |
|
|
Lower |
Upper |
|||||||
|
Age of child |
-.378 |
.321 |
1.386 |
1 |
.239 |
.685 |
.365 |
1.285 |
|
Gender |
-.215 |
.321 |
.448 |
1 |
.503 |
.807 |
.430 |
1.514 |
|
Birth Weight |
1.056 |
.330 |
10.215 |
1 |
.001 |
2.875 |
1.504 |
5.493 |
|
Effected with Diarrhea |
-.111 |
.462 |
.058 |
1 |
.810 |
.895 |
.362 |
2.212 |
|
Symptoms of malnutrition |
.330 |
.314 |
1.107 |
1 |
.293 |
1.391 |
.752 |
2.573 |
|
Exclusive Breast feeding |
-21.275 |
1.384 |
.000 |
1 |
.999 |
.000 |
.000 |
. |
|
Initiation of Supplementary food |
.457 |
.722 |
.400 |
1 |
.527 |
1.580 |
.383 |
6.508 |
|
Constant |
20.560 |
1.384 |
.000 |
1 |
.999 |
8.496 |
|
|
The above table explains the estimates of the logistic regression model. It can be seen that birth weight (Wald=10.215) is the most important variable affecting WHZ in the studied population, followed by age of child (Wald=1.386), symptoms of malnutrition (Wald=1.107) respectively. The Exp (B) gives the values of odds ratios. The children with low birth weight were at 2 fold risk (OR=2.875) followed by initiation of supplementary food with 1.5 fold risk (OR=1.580), symptoms of malnutrition with 1.3 fold risk (OR=1.391) respectively.
DISCUSSION:
Joshi et al. (2011) observed the prevalence of malnutrition to be higher in the age group of 3-6 years. Zottarli et al. (2006) have also observed that age has a significant effect on nutritional status of children. Feahun, Wubshet and Triku (2016) has also shown the association of child’s age (12-23 months) with stunting and wasting. Ramli et al. (2009) also showed association of stunting with child’s age.
Joshi et al. (2011) showed association of sex with prevalence of malnutrition. Zottarli et al. (2006) also showed similar observations. Mitra et al. (2006) showed that Kamar boys suffered more from under nutrition as compared to girls. Saito et al. (1997) also concluded that gender is a significant factor for malnutrition. Sarghi et al. (2011) observed higher prevalence of malnutrition among females.
Low socio-economic status was associated with malnutrition by Joshi et al. 2011; Jing Zhang et al. 2011; Ramli et al. 2009; Meshram et al. 2010; Florencio de Souza et al. 2012; Stuart Gillespie, 2013; Sarghi et al. 2011; Petrou and Kupec, 2010; Fentahun, Wubshet and Triku (2016) Mother’s literacy was associated with malnutrition by Joshi et al. 2011; Jing Zhang et al. 2011; Chisti et al. 2007; Amsalu and Tigabu; 2009; Ambadkar and Jodpey, 2016; Meshram et al. 2012; Hien and Kam (2008).
Improper child feeding practices was shown to be significantly associated with malnutrition by Debnath and Bhattacharya, 2014; Chisti et al. 2007; Li et al. 1999; Fuchs et al. 2014 and Ambadekar and Jodpey, 2016; Erginet al 2007; Ramchandran, 2010; Inayati et al. 2012; Jesmin, 2011; Teshome et al. 2009; Mishra et al. 2013 and Chisti et al. 2007. Present study is also consistent with the above findings. Low status of women showed significant results with malnutrition by Shroff et al. 2008; Stuart Gillespie, 2013; Debnath and Bhattacharya, 2014.
Rayhan and Khan, 2006; Ahmed and Islam, 1984; Florencio de Souza 2012; Mishra et al. 2013; Fuchs et al. 2014; Pongon, Ezzati and Saloman, 2006; Hien and Kam. 2008 associated malnutrition with educational status of parents. Low access to health services was shown to be significantly associated with malnutrition by Florentio de Souza et al. 2012; Stuart Gillespie, 2013; Chisti et al. 2007; Pongon Ezzati and saloman, 2006. Present study also showed significant results with low access to health services.
The odds ratio of stunting with the explanatory variables considered for the present study showed that children affected with diarrhoea has the highest value (OR=3.555) followed by symptoms of malnutrition (OR=2.784) and birth weight (OR=2.090). The odds ratio of underweight with the explanatory variable showed that awareness of symptoms of malnutrition has the highest value (OR=5.443) followed by birth weight (OR=2.906), gender (OR=1.644), initiation of supplementary food (OR= 1.223), effected with diarrhoea (OR=1.016). The odds ratio of wasting of Kamar children with the explanatory variable showed that low birth weight were at 2 fold risk (OR=2.875) followed by initiation of supplementary food with 1.5 fold risk (OR=1.580), symptoms of malnutrition with 1.3 fold risk (OR=1.391).
CONCLUSION:
In conclusion the result of this study indicate that malnutrition is still an important problem among children under five years of age in Dhamtari district. In additional child birth weight, age of child, exclusive breast feeding effected with diarrhoea symptoms of malnutrition and Initiation of supplementary food factors were found to be significant factors for malnutrition among children under five.
REFERENCES:
1. Ambadekar, N. N. and Zodpey, S. P. (2016). Risk factors for severe acute malnutrition in under-five children: a case-control study in a rural part of India. Public Health, 142, 136-143.
2. Amsalu, S. and Tigabu, Z. (2008). Risk factors for severe acute malnutrition in children under the age of five: A Case Control Study. Ethiopian Journal of Health Sciences, 22(1), 21-25.
3. Chisti, M. J., Hossain, M. I., Malek, M. A., Faruque, Abu S. G., Ahmed, T. and Salam, M. A. (2007). Characteristics of severely malnourished under-five children hospitalized with diarrhoea, and their policy implications. Acta Paediatrica, 96, 693-696.
4. Debnath, A. and Bhattacharjee, N. (2014). Factors Associated with Malnutrition among Tribal Children in India: A Non-Parametric Approach. Journal of Tropical Pediatrics.doi:10.1093/tropej/fmt106.
5. Fentahun, W., Wubshet, M. and Triku, A. (2016). Undernutrition and associated factors among children aged 6-59 months in East Balesa district, N. E Ethiopia a study community based cross-sectional study. BMC Public Health. 16, 506.DOI 10.1186/s 12889-016-3180-0.
6. Frongillo, Jr. E. A., de Onis, M. and Hanson, K. M. P. (1997). Socioeconomic and Demographic Factors are Associated with Worldwide Patterns of Stunting and Wasting of Children. The Journal of Nutrition, 127, 2302-2309.
7. Fuchs, C., Sultana, T., Ahmed, T. and Hossain, M. I. (2014). Factors Associated with Acute Malnutrition among Children Admitted to a Diarrhoea Treatment Facilityin Bangladesh. International Journal of Pediatrics, Volume 2014, Article ID 267806, 5 pages http://dx.doi.org/10.1155/2014/ 267806.
8. Hien, N. N. and Kam, S. (2008). Nutritional Status and the Characteristics Related to Malnutrition in Children Under Five Years of Age in Nghean, Vietnam. Journal of Preventive and Medicine Public Health, 41(4), 232-240.
9. Inayati, D. A., Scherbaum, V., Purwestri, R.C., Hormann, E., Wirawan, N. N., Suryantan, J., Hartono, S., Bloem, M. A., Pangaribuan, R. V., Biesalski, H. K. Hoffmann, V. and Bellow, A. C. (2012). Infant feeding practices among mildly wasted children: a retrospective study on Nias Island, Indonesia. International Breastfeeding Journal, 7(3). http://www.internationalbreastfeedingjournal.com/content/7/1/3.
10. Jesmin, A., Yamamoto, S. S., Malik, A. A. and Haque, Md. A. (2011). Prevalence and Determinants of Chronic Malnutrition among Preschool Children: A Cross-sectional Study in Dhaka City, Bangladesh. Journal of Health Population and Nutrition, 29(5), 494-499.
11. Jing Zhang, Shi, J., Hiesh, J. H., Du, Y., Yang, S., Shi, S. and Zhang, J. (2011). Undernutrition status of children under 5 years in Chinese rural areas-data from the National Rural Children Growth Standard Survey, 2006. Asian Pictorial Journal of Clinical Nutrition, 20(4), 584- 592.
12. Joshi, H. S., Joshi, M. C., Singh, A., Joshi, P. and Khan, N. I. (2011). Determinants of Protein Energy Malnutrition (PEM) in 0-6 Year Children in Rural Community of Bareilly. Indian Journal of Preventive and Social Medicine. 42(2), 154-158.
13. Mitra, M., Kumar, P. V., Chakrabarty, S. and Bharati, P. (2007). Nutritional Status of Kamar Tribal Children in Chhattisgarh. Indian Journal of Pediatrics, 74(4), 381-384.
14. Martin, R. and Saller, K. (1959). Lehrbuchhder Anthropologic Stuttgart. German Stuttgart, Fischer, (OCoLC) 655764726.
15. Meshram, I. I. Arlappa, N., Balakrishna, N., Laxmaiah, A., Rao, K. M., Reddy, Ch. G., Ravindranath, M., Kumar, S. S. and Brahmam, G. N. V. (2012). Prevalence and Determinants of Undernutrition and its Trends among Pre-School Tribal Children of Maharashtra State, India. Journal of Tropical Pediatrics, 58 (2)125-132.
16. Mishra, K., Kumar, P., Basu, S., Rai, K. and Aneja, S. (2013). Risk Factors for Severe Acute Malnutrition in Children below 5 y of Age in India: A Case-Control Study. Indian Journal of Pediatrics, DO I10.1007/s12098-013-1127-3.
17. Petrou, S. and Kupek, E. (2010). Poverty and childhood undernutrition in developing countries: A multi-national cohort study. Social Science and Medicine, 71, 1366-1373.
18. Ramli, Agho, K. E., Inder, K. J., Bowe, S. J., Jecobs, J. and Dibley, M. J. (2009). Prevalence and risk factors for stunting and severe stunting among under-fives in North Maluku province of Indonesia. BMC Pediatrics, 9(64). Doi: 10.1186/1471-2431-9-64.
19. Ramachandran, P. (2010). Nutrition and Child Survival in India. Indian Journal of Pediatrics, 77(3), 301-305.
20. Rayhan, Md. I. and Khan, M. S. H. (2006). Factors Causing Malnutrition among under Five Children in Bangladesh. Pakistan Journal of Nutrition, 5(6), 558-562.
21. Satio, K., Korzenik, J. R., Jekel, J. F. and Bhattacharji, S. (1997). A Case-Control Study of Maternal Knowledge of Malnutrition and Health-Care-Seeking Attitudes in Rural South India. Yale Journal of Biology and Medicine, 70, 149-160.
22. Teshome, B., Makau, W. K., Getahum, Z. and Taye, G. (2009). Magnitude and determinants of stunting in children under-five years of age in food surplus region of Ethiopia: The case of West Gojam Zone. Ethiopian Journal of Health Development, 23(2), 98-106.
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Received on 20.10.2024 Revised on 17.11.2024 Accepted on 10.12.2024 Published on 16.12.2024 Available online on December 31, 2024 Research J. Engineering and Tech. 2024; 15(2):47-51. DOI: 10.52711/2321-581X.2024.00007 ©A and V Publications All right reserved
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