A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery

Andriani H. Birth weight and childhood obesity: effect modification by residence and household wealth. Emerg Themes Epidemiol. 2021. https://doi.org/10.1186/s12982-021-00096-2.

Article  PubMed  PubMed Central  Google Scholar 

Ntenda PAM. Association of low birth weight with undernutrition in preschool-aged children in Malawi. Nutr J. 2019;18(1):51. https://doi.org/10.1186/s12937-019-0477-8.

Article  PubMed  PubMed Central  Google Scholar 

Woldeamanuel GG, Geta TG, Mohammed TP, Shuba MB, Bafa TA. Effect of nutritional status of pregnant women on birth weight of newborns at Butajira Referral Hospital, Butajira, Ethiopia. SAGE Open Med. 2019;7:2050312119827096. https://doi.org/10.1177/2050312119827096.

Article  PubMed  PubMed Central  Google Scholar 

Forgie AJ, Drall KM, Bourque SL, Field CJ, Kozyrskyj AL, Willing BP. The impact of maternal and early life malnutrition on health: a diet-microbe perspective. BMC Med. 2020;18(1):135. https://doi.org/10.1186/s12916-020-01584-z.

Article  PubMed  PubMed Central  Google Scholar 

Hussain Z, Borah MD. Nutritional status prediction in neonate using machine learning techniques: a comparative study. In: Bhattacharjee A, Borgohain SK, Soni B, Verma G, Gao X-Z, editors. Machine learning image processing network security and data sciences. Singapore: Springer; 2020. p. 69–83. https://doi.org/10.1007/978-981-15-6318-8_7.

Chapter  Google Scholar 

Garcia Rincon LJ, Alencar GP, Cardoso MA, Narvai PC, Frazão P. Effect of birth weight and nutritional status on transverse maxillary growth: implications for maternal and infant health. PLoS ONE. 2020;15(1):1–12. https://doi.org/10.1371/journal.pone.0228375.

Article  CAS  Google Scholar 

Aboagye RG, Ahinkorah BO, Seidu A-A, Frimpong JB, Archer AG, Adu C, Hagan JE Jr, Amu H, Yaya S. Birth weight and nutritional status of children under five in Sub-Saharan Africa. PLoS ONE. 2022;17(6):1–19. https://doi.org/10.1371/journal.pone.0269279.

Article  CAS  Google Scholar 

Moreno-Fernandez J, Ochoa JJ, Lopez-Frias M, Diaz-Castro J. Impact of early nutrition, physical activity and sleep on the fetal programming of disease in the pregnancy: a narrative review. Nutrients. 2020. https://doi.org/10.3390/nu12123900.

Article  PubMed  PubMed Central  Google Scholar 

Bhowmik B, Siddique T, Majumder A, Mdala I, Hossain IA, Hassan Z, Jahan I, Moreira NCDV, Alim A, Basit A, Hitman GA, Khan AKA, Hussain A. Maternal BMJ and nutritional status in early pregnancy and its impact on neonatal outcomes at birth in Bangladesh. BMC Pregnancy Childbirth. 2019;19(1):413. https://doi.org/10.1186/s12884-019-2571-5.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Do HJ, Moon KM, Jin HS. Machine learning models for predicting mortality in 7472 very low birth weight infants using data from a nationwide neonatal network. Diagnostics. 2022. https://doi.org/10.3390/diagnostics12030625.

Article  PubMed  PubMed Central  Google Scholar 

Islam Pollob SMA, Abedin MM, Islam MT, Islam MM, Maniruzzaman M. Predicting risks of low birth weight in Bangladesh with machine learning. PLoS ONE. 2022;17(5):1–12. https://doi.org/10.1371/journal.pone.0267190.

Article  CAS  Google Scholar 

Song IG, Kim H-S, Cho Y-M, Lim Y-N, Moon D-S, Shin SH, Kim E-K, Park J, Shin JE, Han J, Eun HS. Association between birth weight and neurodevelopmental disorders assessed using the Korean national health insurance service claims data. Sci Rep. 2022;12(1):2080. https://doi.org/10.1038/s41598-022-06094-x.

Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

Zeng P, Zhou X. Causal association between birth weight and adult diseases: evidence from a mendelian randomization analysis. Front Genet. 2019. https://doi.org/10.3389/fgene.2019.00618.

Article  PubMed  PubMed Central  Google Scholar 

Sharma V, Sharma V, Khan A, Wassmer DJ, Schoenholtz MD, Hontecillas R, Bassaganya-Riera J, Zand R, Abedi V. Malnutrition, health and the role of machine learning in clinical setting. Front Nutr. 2020. https://doi.org/10.3389/fnut.2020.00044.

Article  PubMed  PubMed Central  Google Scholar 

Kirk D, Catal C, Tekinerdogan B. Precision nutrition: a systematic literature review. Comput Biol Med. 2021;133: 104365. https://doi.org/10.1016/j.compbiomed.2021.104365.

Article  PubMed  Google Scholar 

Raphaeli O, Singer P. Towards personalized nutritional treatment for malnutrition using machine learning-based screening tools. Clin Nutr. 2021;40(10):5249–51. https://doi.org/10.1016/j.clnu.2021.08.013.

Article  PubMed  Google Scholar 

Hussain Z, Borah MD. Birth weight prediction of new born baby with application of machine learning techniques on features of mother. J Stat Manag Syst. 2020;23(6):1079–91. https://doi.org/10.1080/09720510.2020.1814499.

Article  Google Scholar 

Talukder A, Ahammed B. Machine learning algorithms for predicting malnutrition among under-five children in Bangladesh. Nutrition. 2020;78: 110861. https://doi.org/10.1016/j.nut.2020.110861.

Article  PubMed  Google Scholar 

Khan W, Zaki N, Masud MM, Ahmad A, Ali L, Ali N, Ahmed LA. Infant birth weight estimation and low birth weight classification in united Arab emirates using machine learning algorithms. Sci Rep. 2022;12(1):12110. https://doi.org/10.1038/s41598-022-14393-6.

Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

Fenta HM, Zewotir T, Muluneh EK. A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones. BMC Med Inform Decis Mak. 2021;21(1):291. https://doi.org/10.1186/s12911-021-01652-1.

Article  PubMed  PubMed Central  Google Scholar 

Bekele WT. Machine learning algorithms for predicting low birth weight in Ethiopia. BMC Med Inform Decis Mak. 2022;22(1):232. https://doi.org/10.1186/s12911-022-01981-9.

Article  PubMed  PubMed Central  Google Scholar 

Sousa CM, Santana E, Lopes MV, Lima G, Azoubel L, Carneiro E, Barros AK, Pires N. Development of a computational model to predict excess body fat in adolescents through low cost variables. Int J Environ Res Public Health. 2019. https://doi.org/10.3390/ijerph16162962.

Article  PubMed  PubMed Central  Google Scholar 

Wei J, Fan L, Zhang Y, Li S, Partridge J, Claytor L, Sulo S. Association between malnutrition and depression among community-dwelling older Chinese adults. Asia Pac J Public Health. 2018;30(2):107–17. https://doi.org/10.1177/1010539518760632.

Article  PubMed  Google Scholar 

Sgkdddd B-GBSW. Association of birth weight with type 2 diabetes and glycemic traits: a mendelian randomization study. JAMA Netw Open. 2019;2(9):1910915–1910915. https://doi.org/10.1001/jamanetworkopen.2019.10915.

Article  Google Scholar 

Riad A, Knight SR, Ghosh D, Kingsley PA, Lapitan MC, Parreno-Sacdalan MDEA. Impact of malnutrition on early outcomes after cancer surgery: an international, multicentre, prospective cohort study. Lancet Global Health. 2023;11(3):341–9. https://doi.org/10.1016/S2214-109X(22)00550-2.

Article  Google Scholar 

Sousa-Catita D, Ferreira-Santos C, Mascarenhas P, Oliveira C, Madeira R, Santos CA, André C, Godinho C, Antunes L, Fonseca J. Malnutrition, cancer stage and gastrostomy timing as markers of poor outcomes in gastrostomy-fed head and neck cancer patients. Nutrients. 2023. https://doi.org/10.3390/nu15030662.

Article  PubMed  PubMed Central  Google Scholar 

Tchoumi SY, Njintang NY, Kamgang JC, Tchuenche JM. Malaria and malnutrition in children: a mathematical model. Franklin Open. 2023;3: 100013. https://doi.org/10.1016/j.fraope.2023.100013.

Article  Google Scholar 

Hussain Z, Borah MD. Nicov: a model to analyse impact of nutritional status and immunity on COVID-19. Med Biol Eng Comput. 2022;60(5):1481–96. https://doi.org/10.1007/s11517-022-02545-9.

Article  PubMed  PubMed Central  Google Scholar 

Hussain Z, Borah MD. Predicting mental health and nutritional status from social media profile using deep learning. In: Hong T-P, Serrano-Estrada L, Saxena A, Biswas A, editors. Deep learning for social media data analytics. Cham: Springer; 2022. p. 177–93.

Chapter  Google Scholar 

Jana A, Dey D, Ghosh R. Contribution of low birth weight to childhood undernutrition in India: evidence from the national family health survey 2019–2021. BMC Public Health. 2023;23(1):1336. https://doi.org/10.1186/s12889-023-16160-2.

Article  PubMed  PubMed Central  Google Scholar 

Bianchi ME, Restrepo JM. Low birthweight as a risk factor for non-communicable diseases in adults. Front Med. 2022. https://doi.org/10.3389/fmed.2021.793990.

Article  Google Scholar 

Bernhardsen GP, Stensrud T, Hansen BH, Steene-Johannesen J, Kolle E, Nystad W, Anderssen SA, Hallal PC, Janz KF, Kriemler S, Andersen LB, Northstone K, Resaland GK, Sardinha LB, van Sluijs EMF, Ried-Larsen M, Ekelund U. Birth weight, cardiometabolic risk factors and effect modification of physical activity in children and adolescents: pooled data from 12 international studies. Int J Obes. 2020;44(10):2052–63. https://doi.org/10.1038/s41366-020-0612-9.

Article  Google Scholar 

Doorduijn AS, de van der Schueren MAE, van de Rest O, de Leeuw FA, Hendriksen HMA, Teunissen CE, Scheltens P, van der Flier WM, Visser M. Nutritional status is associated with clinical progression in alzheimer’s disease: the nudad project. J Am Med Direct Assoc. 2023;24(5):638–6441. https://doi.org/10.1016/j.jamda.2020.10.020.

Schneider EB. The effect of nutritional status on historical infectious disease morbidity: evidence from the London foundling hospital, 1892–1919. Hist Fam. 2023;28(2):198–228. https://doi.org/10.1080/1081602X.2021.2007499.

Article  Google Scholar 

Borah MD, Hussain Z. Ein System zur Analyse der Auswirkungen des Geburtsgewichts Auf Krankheitsspezifische Folgen des Ernährungszustands. 202022101981.9, German Patent and Trade Mark Office 2022. https://register.dpma.de/DPMAregister/pat/register?AKZ=2020221019819

Hussain Z, Borah MD. Child birth weight dataset IEEE Dataport. 2022. https://doi.org/10.21227/dvd4-3232.

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