Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach

Md Nesar Uddin Sorkar; Md. Roquib Uddin Sorkar

doi:doi:10.11648/j.wjfst.20230702.12

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Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach

Md Nesar Uddin Sorkar, Md. Roquib Uddin Sorkar

Published in World Journal of Food Science and Technology (Volume 7, Issue 2)

Received: 6 February 2023 Accepted: 23 February 2023 Published: 25 May 2023

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Abstract

Supplementary foods are foods that babies consume in addition to breast milk. Supplementary food is essential for a baby's health. Many malnutrition problems in babies are caused by a lack of supplementary feeding. However, not all supplementary foods are beneficial to a baby's health. The goal of this research was to identify the supplementary foods that cause infectious diseases in babies. Simultaneously, it attempted to predict infectious diseases in babies. This secondary data was collected from BDHS 2014. Here various methods such as percentage distribution, association test, logistic regression, and association rule mining have been used to find out the responsible factors for infectious diseases. At the same time, Decision Tree, Random Forest, Support Vector Machine, and Naiv Bays have been used to predict infectious diseases in babies. According to association test, association rule mining, and logistic regression, it can be said that babies who eat juices, pumpkin or carrot, liver or heart, lentils or nuts, other liquids, potatoes, bread or noodles, plain water, and other foods are more likely to be infected with infectious diseases. On the other hand, babies who eat tinned milk, mango or papaya, and baby formula are less likely to get an infectious disease. Furthermore, for this data, Random Forest is the best classifier. Therefore, it can be said that these significant variables may be responsible for the infectious disease of babies. The government and numerous NGOs should make people aware of this significant supplementary food so that future generations can be disease-free.

Published in	World Journal of Food Science and Technology (Volume 7, Issue 2)
DOI	10.11648/j.wjfst.20230702.12
Page(s)	24-29
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Prediction, Infectious, Disease, Supplementary, Food, Machine, Learning

References

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[2]	P. Nestel et al., “Complementary food supplements to achieve micronutrient adequacy for infants and young children,” Journal of Pediatric Gastroenterology and Nutrition. 2003. doi: 10.1097/00005176-200303000-00005.
[3]	M. P. Patel, H. L. Sandige, M. J. Ndekha, A. Briend, P. Ashorn, and M. J. Manary, “Supplemental feeding with ready-to-use therapeutic food in Malawian children at risk of malnutrition,” J. Heal. Popul. Nutr., 2005, doi: 10.3329/jhpn.v23i4.352.
[4]	R. Chander, P. Vimesh, and S. Singh, “Prevalence of Diarrhoea in Infants and its Relation to Feeding and Weaning Practices,” JMS Ski., 2011, doi: 10.33883/jms.v14i1.65.
[5]	F. O. Fauthrisna, M. Masrul, and E. Chundrayetti, “Hubungan Pemberian Makanan Tambahan Dini terhadap Status Gizi Bayi Usia 4-6 Bulan di Daerah Pantai Kota Padang Tahun 2013,” J. Kesehat. Andalas, 2015, doi: 10.25077/jka.v4i3.376.
[6]	U. Lindskog, B. Bjorksten, and M. Gebre-Medhin, “Infant care in rural Malawi. A prospective study of morbidity and growth in relation to environmental factors,” Ann. Trop. Paediatr., 1994, doi: 10.1080/02724936.1994.11747690.
[7]	E. C. Okele and U. A. Onyechi, “Factors affecting weaning in rural and urban areas of South Eastern Nigeria,” Cajanus, 1994.
[8]	A. Fenta, K. Alemu, and D. A. Angaw, “Prevalence and associated factors of acute diarrhea among under-five children in Kamashi district, western Ethiopia: Community-based study,” BMC Pediatr., 2020, doi: 10.1186/s12887-020-02138-1.
[9]	F. A. Ogbo, H. Nguyen, S. Naz, K. E. Agho, and A. Page, “The association between infant and young child feeding practices and diarrhoea in Tanzanian children,” Trop. Med. Health, 2018, doi: 10.1186/s41182-018-0084-y.
[10]	“Infant and young child feeding.” https://www.who.int/news-room/fact-sheets/detail/infant-and-young-child-feeding (accessed Aug. 15, 2021).
[11]	M. I. K. Imran, M. U. A. Inshafi, R. Sheikh, M. A. B. Chowdhury, and M. J. Uddin, “Risk factors for acute respiratory infection in children younger than five years in Bangladesh,” Public Health, 2019, doi: 10.1016/j.puhe.2019.05.011.
[12]	N. I. of P. R. and T.- NIPORT/Bangladesh, M. and Associates, and I. International, “Bangladesh Demographic and Health Survey 2014.” Mar. 01, 2016. Accessed: Aug. 15, 2021. [Online]. Available: https://dhsprogram.com/publications/publication-fr311-dhs-final-reports.cfm
[13]	F. A. Ogbo, A. Page, J. Idoko, F. Claudio, and K. E. Agho, “Diarrhoea and Suboptimal Feeding Practices in Nigeria: Evidence from the National Household Surveys,” Paediatr. Perinat. Epidemiol., 2016, doi: 10.1111/ppe.12293.
[14]	M. V. Dhami, F. A. Ogbo, T. M. O. Diallo, and K. E. Agho, “Regional analysis of associations between infant and young child feeding practices and diarrhoea in indian children,” Int. J. Environ. Res. Public Health, 2020, doi: 10.3390/ijerph17134740.
[15]	E. Kristjansson et al., “Food supplementation for improving the physical and psychosocial health of socio-economically disadvantaged children aged three months to five years,” Cochrane Database of Systematic Reviews. 2015. doi: 10.1002/14651858.CD009924.pub2.

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Md Nesar Uddin Sorkar, Md. Roquib Uddin Sorkar. (2023). Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach. World Journal of Food Science and Technology, 7(2), 24-29. https://doi.org/10.11648/j.wjfst.20230702.12

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ACS Style

Md Nesar Uddin Sorkar; Md. Roquib Uddin Sorkar. Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach. World J. Food Sci. Technol. 2023, 7(2), 24-29. doi: 10.11648/j.wjfst.20230702.12

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AMA Style

Md Nesar Uddin Sorkar, Md. Roquib Uddin Sorkar. Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach. World J Food Sci Technol. 2023;7(2):24-29. doi: 10.11648/j.wjfst.20230702.12

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@article{10.11648/j.wjfst.20230702.12,
  author = {Md Nesar Uddin Sorkar and Md. Roquib Uddin Sorkar},
  title = {Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach},
  journal = {World Journal of Food Science and Technology},
  volume = {7},
  number = {2},
  pages = {24-29},
  doi = {10.11648/j.wjfst.20230702.12},
  url = {https://doi.org/10.11648/j.wjfst.20230702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wjfst.20230702.12},
  abstract = {Supplementary foods are foods that babies consume in addition to breast milk. Supplementary food is essential for a baby's health. Many malnutrition problems in babies are caused by a lack of supplementary feeding. However, not all supplementary foods are beneficial to a baby's health. The goal of this research was to identify the supplementary foods that cause infectious diseases in babies. Simultaneously, it attempted to predict infectious diseases in babies. This secondary data was collected from BDHS 2014. Here various methods such as percentage distribution, association test, logistic regression, and association rule mining have been used to find out the responsible factors for infectious diseases. At the same time, Decision Tree, Random Forest, Support Vector Machine, and Naiv Bays have been used to predict infectious diseases in babies. According to association test, association rule mining, and logistic regression, it can be said that babies who eat juices, pumpkin or carrot, liver or heart, lentils or nuts, other liquids, potatoes, bread or noodles, plain water, and other foods are more likely to be infected with infectious diseases. On the other hand, babies who eat tinned milk, mango or papaya, and baby formula are less likely to get an infectious disease. Furthermore, for this data, Random Forest is the best classifier. Therefore, it can be said that these significant variables may be responsible for the infectious disease of babies. The government and numerous NGOs should make people aware of this significant supplementary food so that future generations can be disease-free.},
 year = {2023}
}

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TY - JOUR
T1 - Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach
AU - Md Nesar Uddin Sorkar
AU - Md. Roquib Uddin Sorkar
Y1 - 2023/05/25
PY - 2023
N1 - https://doi.org/10.11648/j.wjfst.20230702.12
DO - 10.11648/j.wjfst.20230702.12
T2 - World Journal of Food Science and Technology
JF - World Journal of Food Science and Technology
JO - World Journal of Food Science and Technology
SP - 24
EP - 29
PB - Science Publishing Group
SN - 2637-6024
UR - https://doi.org/10.11648/j.wjfst.20230702.12
AB - Supplementary foods are foods that babies consume in addition to breast milk. Supplementary food is essential for a baby's health. Many malnutrition problems in babies are caused by a lack of supplementary feeding. However, not all supplementary foods are beneficial to a baby's health. The goal of this research was to identify the supplementary foods that cause infectious diseases in babies. Simultaneously, it attempted to predict infectious diseases in babies. This secondary data was collected from BDHS 2014. Here various methods such as percentage distribution, association test, logistic regression, and association rule mining have been used to find out the responsible factors for infectious diseases. At the same time, Decision Tree, Random Forest, Support Vector Machine, and Naiv Bays have been used to predict infectious diseases in babies. According to association test, association rule mining, and logistic regression, it can be said that babies who eat juices, pumpkin or carrot, liver or heart, lentils or nuts, other liquids, potatoes, bread or noodles, plain water, and other foods are more likely to be infected with infectious diseases. On the other hand, babies who eat tinned milk, mango or papaya, and baby formula are less likely to get an infectious disease. Furthermore, for this data, Random Forest is the best classifier. Therefore, it can be said that these significant variables may be responsible for the infectious disease of babies. The government and numerous NGOs should make people aware of this significant supplementary food so that future generations can be disease-free.
VL - 7
IS - 2
ER -

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Author Information

Md Nesar Uddin Sorkar

Department of Statistics, Shahjalal University of Science and Technology, Sylhet, Bangladesh
Md. Roquib Uddin Sorkar

Department of Civil Engineering, Southern University Bangladesh, Chittagong, Bangladesh

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APA Style

Md Nesar Uddin Sorkar, Md. Roquib Uddin Sorkar. (2023). Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach. World Journal of Food Science and Technology, 7(2), 24-29. https://doi.org/10.11648/j.wjfst.20230702.12

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ACS Style

Md Nesar Uddin Sorkar; Md. Roquib Uddin Sorkar. Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach. World J. Food Sci. Technol. 2023, 7(2), 24-29. doi: 10.11648/j.wjfst.20230702.12

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AMA Style

Md Nesar Uddin Sorkar, Md. Roquib Uddin Sorkar. Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach. World J Food Sci Technol. 2023;7(2):24-29. doi: 10.11648/j.wjfst.20230702.12

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@article{10.11648/j.wjfst.20230702.12,
  author = {Md Nesar Uddin Sorkar and Md. Roquib Uddin Sorkar},
  title = {Predicting 7-24 Months Childs Infectious Disease and Responsible Supplementary Food for Infectious Disease: A Machine Learning Approach},
  journal = {World Journal of Food Science and Technology},
  volume = {7},
  number = {2},
  pages = {24-29},
  doi = {10.11648/j.wjfst.20230702.12},
  url = {https://doi.org/10.11648/j.wjfst.20230702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wjfst.20230702.12},
  abstract = {Supplementary foods are foods that babies consume in addition to breast milk. Supplementary food is essential for a baby's health. Many malnutrition problems in babies are caused by a lack of supplementary feeding. However, not all supplementary foods are beneficial to a baby's health. The goal of this research was to identify the supplementary foods that cause infectious diseases in babies. Simultaneously, it attempted to predict infectious diseases in babies. This secondary data was collected from BDHS 2014. Here various methods such as percentage distribution, association test, logistic regression, and association rule mining have been used to find out the responsible factors for infectious diseases. At the same time, Decision Tree, Random Forest, Support Vector Machine, and Naiv Bays have been used to predict infectious diseases in babies. According to association test, association rule mining, and logistic regression, it can be said that babies who eat juices, pumpkin or carrot, liver or heart, lentils or nuts, other liquids, potatoes, bread or noodles, plain water, and other foods are more likely to be infected with infectious diseases. On the other hand, babies who eat tinned milk, mango or papaya, and baby formula are less likely to get an infectious disease. Furthermore, for this data, Random Forest is the best classifier. Therefore, it can be said that these significant variables may be responsible for the infectious disease of babies. The government and numerous NGOs should make people aware of this significant supplementary food so that future generations can be disease-free.},
 year = {2023}
}

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