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Maternal dietary practices during pregnancy and obesity of neonates: a machine learning approach towards hierarchical and nested relationships in a Tibet Plateau cohort study

Published online by Cambridge University Press:  26 September 2024

Xiao Tang ,
Bin Zhang ,
Mengzi Sun ,
Hong Xue ,
Ruihua Xu ,
Wenxiu Jian ,
Xiaomin Sun Open the ORCID record for Xiaomin Sun [Opens in a new window] ,
Pinhua Wang ,
Jiangcuo Zhaxi  and
Xuejun Wang
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Xiao Tang
Affiliation:
Nutrition and Health Promotion Center, Department of Public Health, Medical College, Qinghai University, Xining 810008, People’s Republic of China
Bin Zhang
Affiliation:
School of Mathematics and Statistics, Qinghai Minzu University, Xining 810007, People’s Republic of China
Mengzi Sun
Affiliation:
Global Health Institute, School of Public Health, Xi’an Jiaotong University, Xi’an 710061, People’s Republic of China
Hong Xue
Affiliation:
Department of Health Administration and Policy, College of Public Health, George Mason University, Fairfax, VA, USA
Ruihua Xu
Affiliation:
Nutrition and Health Promotion Center, Department of Public Health, Medical College, Qinghai University, Xining 810008, People’s Republic of China
Wenxiu Jian
Affiliation:
Nutrition and Health Promotion Center, Department of Public Health, Medical College, Qinghai University, Xining 810008, People’s Republic of China
Xiaomin Sun
Affiliation:
Global Health Institute, School of Public Health, Xi’an Jiaotong University, Xi’an 710061, People’s Republic of China
Pinhua Wang
Affiliation:
Department of Obstetrics, Qinghai Red Cross Hospital, Xining 810099, People’s Republic of China
Jiangcuo Zhaxi
Affiliation:
Nangqian People’s Hospital, Yushu 815299, People’s Republic of China
Xuejun Wang
Affiliation:
Department of Anesthesiology, Qinghai Red Cross Hospital, Xining 810099, People’s Republic of China
Liehong Wang
Affiliation:
Department of Obstetrics, Qinghai Red Cross Hospital, Xining 810099, People’s Republic of China
Xinguang Chen
Affiliation:
Global Health Institute, School of Public Health, Xi’an Jiaotong University, Xi’an 710061, People’s Republic of China
Yankai Xia
Affiliation:
State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, People’s Republic of China
Youfa Wang*
Affiliation:
Global Health Institute, School of Public Health, Xi’an Jiaotong University, Xi’an 710061, People’s Republic of China
Wen Peng*
Affiliation:
Nutrition and Health Promotion Center, Department of Public Health, Medical College, Qinghai University, Xining 810008, People’s Republic of China Qinghai Provincial Key Laboratory of Prevention and Control of Glucolipid Metabolic Diseases with Traditional Chinese Medicine, Xining, People’s Republic of China
*
*Corresponding authors: Dr Wen Peng, email [email protected]; Youfa Wang, email [email protected]
*Corresponding authors: Dr Wen Peng, email [email protected]; Youfa Wang, email [email protected]
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Abstract

Studies on obesity and risk factors from a life-course perspective among residents in the Tibet Plateau with recent economic growth and increasing obesity are important and urgently needed. The birth cohort in this area provides a unique opportunity to examine the association between maternal dietary practice and neonatal obesity. The study aims to detect the prevalence of obesity among neonates, associated with maternal diet and other factors, supporting life-course strategies for obesity control. A cohort of pregnant women was enrolled in Tibet Plateau and followed till childbirth. Dietary practice during pregnancy was assessed using the Chinese FFQ – Tibet Plateau version, food items and other variables were associated with the risk for obesity of neonates followed by logistic regression, classification and regression trees (CART) and random forest. Of the total 1226 mother–neonate pairs, 40·5 % were Tibetan and 5·4 % of neonates with obesity. Consuming fruits as a protective factor for obesity of neonates with OR (95 % CI) = 0·61 (0·43, 0·87) from logistic regression; as well as OR = 0·20 (0·12, 0·35) for consuming fruits (≥ weekly) from CART. Removing fruit consumption to avoid overshadowing effects of other factors, the following were influential from CART: maternal education (more than middle school, OR = 0·22 (0·13, 0·37)) and consumption of Tibetan food (daily, OR = 3·44 (2·08, 5·69). Obesity among neonates is prevalent in the study population. Promoting healthy diets during pregnancy and strengthening maternal education should be part of the life-course strategies for obesity control.

Keywords

Neonates obeseMaternal dietary practiceTibetan foodMachine learning
Type
Research Article
Information
British Journal of Nutrition , Volume 132 , Issue 5 , 14 September 2024 , pp. 667 - 677
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of The Nutrition Society

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Footnotes

†

These authors contributed equally to this work.

References

Gao, L, Bhurtyal, A, Wei, J, et al. (2020) Double burden of malnutrition and nutrition transition in Asia: a case study of 4 selected countries with different socioeconomic development. Adv Nutr 11, 1663–1670.CrossRefGoogle Scholar
Pan, XF, Wang, L & Pan, A (2021) Epidemiology and determinants of obesity in China. Lancet Diabetes Endocrinol 9, 373–392.CrossRefGoogle ScholarPubMed
Barker, DJ, Godfrey, KM, Osmond, C, et al. (1992) The relation of fetal length, ponderal index and head circumference to blood pressure and the risk of hypertension in adult life. Paediatr Perinat Epidemiol 6, 35–54.CrossRefGoogle ScholarPubMed
Howe, LD, Tilling, K, Benfield, L, et al. (2010) Changes in ponderal index and body mass index across childhood and their associations with fat mass and cardiovascular risk factors at age 15. PLoS One 5, e15186.CrossRefGoogle ScholarPubMed
Rasmussen, F & Johansson, M (1998) The relation of weight, length and ponderal index at birth to body mass index and overweight among 18-year-old males in Sweden. Eur J Epidemiol 14, 373–380.CrossRefGoogle ScholarPubMed
Moore, BF, Harrall, KK, Sauder, KA, et al. (2020) Neonatal adiposity and childhood obesity. Pediatr 146, e20200737.CrossRefGoogle ScholarPubMed
Kensara, OA, Wootton, SA, Phillips, DI, et al. (2005) Fetal programming of body composition: relation between birth weight and body composition measured with dual-energy X-ray absorptiometry and anthropometric methods in older Englishmen. Am J Clin Nutr 82, 980–987.CrossRefGoogle ScholarPubMed
Polin, RF, Fox, WW & Abman, SH (2011) Fetal and Neonatal Physiology, vol. 1, 4th ed. Amsterdam: Elsevier.Google Scholar
Chia, AR, de Seymour, JV, Colega, M, et al. (2016) A vegetable, fruit, and white rice dietary pattern during pregnancy is associated with a lower risk of preterm birth and larger birth size in a multiethnic Asian cohort: the growing up in Singapore towards healthy outcomes (GUSTO) cohort study. Am J Clin Nutr 104, 1416–1423.CrossRefGoogle Scholar
Yang, J, Chang, Q, Tian, X, et al. (2022) Dietary protein intake during pregnancy and birth weight among Chinese pregnant women with low intake of protein. Nutr Metab 19, 43.CrossRefGoogle ScholarPubMed
Geraghty, AA, O’Brien, EC, Alberdi, G, et al. (2018) Maternal protein intake during pregnancy is associated with child growth up to 5 years of age, but not through insulin-like growth factor-1: findings from the ROLO study. Br J Nutr 120, 1252–1261.CrossRefGoogle Scholar
Chen, LW, Aris, IM, Bernard, JY, et al. (2016) Associations of maternal dietary patterns during pregnancy with offspring adiposity from birth until 54 months of age. Nutrients 9, 2.CrossRefGoogle ScholarPubMed
Barchitta, M, Magnano San Lio, R, La Rosa, MC, et al. (2023) The effect of maternal dietary patterns on birth weight for gestational age: findings from the MAMI-MED cohort. Nutrients 15, 1922.CrossRefGoogle ScholarPubMed
Hajianfar, H, Esmaillzadeh, A, Feizi, A, et al. (2018) Major maternal dietary patterns during early pregnancy and their association with neonatal anthropometric measurement. Biomed Res Int 2018, 4692193.CrossRefGoogle ScholarPubMed
Pathirathna, ML, Sekijima, K, Sadakata, M, et al. (2017) Impact of second trimester maternal dietary intake on gestational weight gain and neonatal birth weight. Nutrients 9, 627.CrossRefGoogle ScholarPubMed
Godfrey, K, Robinson, S, Barker, DJ, et al. (1996) Maternal nutrition in early and late pregnancy in relation to placental and fetal growth. Bmj 312, 410–414.CrossRefGoogle ScholarPubMed
Fu, B (2021) Socio-Economic Data Set of Qinghai-Tibet Plateau (1982–2018). Beijing: National Tibetan Plateau Data Center.Google Scholar
De Franco, S, Lampugnani, R, Gelmetti, M, et al. (1978) Intra-operative findings and immediate results of 3 methods of termino-lateral portacaval anastomosis in the rat. Chirurgia e Patologia Sperimentale 26, 11–32.Google ScholarPubMed
Jones, JR, Smibert, JG, McCullough, CJ, et al. (1987) Tendon implantation into bone: an experimental study. J Hand Surg 12, 306–312.CrossRefGoogle ScholarPubMed
Peng, W, Liu, Y, Malowany, M, et al. (2021) Metabolic syndrome and its relation to dietary patterns among a selected urbanised and semi-urbanised Tibetan population in transition from nomadic to settled living environment. Public Health Nutr 24, 984–992.CrossRefGoogle ScholarPubMed
Wang, Z, Dang, S & Yan, H (2010) Nutrient intakes of rural Tibetan mothers: a cross-sectional survey. BMC Public Health 10, 801.CrossRefGoogle ScholarPubMed
Zhou, C, Li, M, Liu, L, et al. (2021) Food consumption and dietary patterns of local adults living on the Tibetan Plateau: results from 14 countries along the Yarlung Tsangpo river. Nutrients 13, 2444.CrossRefGoogle ScholarPubMed
Soria, R, Julian, CG, Vargas, E, et al. (2013) Graduated effects of high-altitude hypoxia and highland ancestry on birth size. Pediatr Res 74, 633–638.CrossRefGoogle ScholarPubMed
Bigham, AW, Julian, CG, Wilson, MJ, et al. (2014) Maternal PRKAA1 and EDNRA genotypes are associated with birth weight, and PRKAA1 with uterine artery diameter and metabolic homeostasis at high altitude. Physiol Genomics 46, 687–697.CrossRefGoogle ScholarPubMed
Peng, W, Chen, S, Chen, X, et al. (2024) Trends in major non-communicable diseases and related risk factors in China 2002–2019: an analysis of nationally representative survey data. Lancet Reg Health West Pac 43, 100809.Google Scholar
Gozal, D, Ndombo, PK, Ze Minkande, J, et al. (1991) Anthropometric measurements in a newborn population in west Africa: a reliable and simple tool for the identification of infants at risk for early postnatal morbidity. J Pediatr 118, 800–805.CrossRefGoogle Scholar
Persson, M, Pasupathy, D, Hanson, U, et al. (2012) Disproportionate body composition and perinatal outcome in large-for-gestational-age infants to mothers with type 1 diabetes. BJOG: Int J Gynecol 119, 565–572.CrossRefGoogle ScholarPubMed
Andreasyan, K, Ponsonby, AL, Dwyer, T, et al. (2007) Higher maternal dietary protein intake in late pregnancy is associated with a lower infant ponderal index at birth. Eur J Clin Nutr 61, 498–508.CrossRefGoogle ScholarPubMed
Zong, XN, Li, H, Zhang, YQ, et al. (2021) Reference values and growth curves of weight/length, body mass index, and ponderal index of Chinese newborns of different gestational ages. Chin J Pediatr 59, 181–188.Google ScholarPubMed
Roje, D, Banovic, I, Tadin, I, et al. (2004) Gestational age--the most important factor of neonatal ponderal index. Yonsei Med J 45, 273–280.CrossRefGoogle ScholarPubMed
Zaniqueli, D, Oliosa, PR, Neves, FS, et al. (2019) Ponderal index classifies obesity in children and adolescents more accurately than body mass index z-scores. Pediatr Res 86, 128–133.CrossRefGoogle ScholarPubMed
Zhao, L, Wang, S, Liu, M, et al. (2023) Maternal urinary metal(loid)s and risk of preterm birth: a cohort study in the Tibetan Plateau. Environ Pollut 333, 122085.CrossRefGoogle ScholarPubMed
Chen, X, Mo, Q, Yu, B, et al. (2022) Hierarchical and nested associations of suicide with marriage, social support, quality of life, and depression among the elderly in rural China: machine learning of psychological autopsy data. Front Psychiatry 13, 1000026.CrossRefGoogle ScholarPubMed
Avendaño-Alvarez, F, Monterrubio-Flores, E, Omaña-Guzmán, I, et al. (2022) Incidence of macrosomia in Mexico: national and subnational estimations. PLoS One 17, e0276518.CrossRefGoogle ScholarPubMed
Shen, L, Wang, J, Duan, Y, et al. (2021) Prevalence of low birth weight and macrosomia estimates based on heaping adjustment method in China. Sci Rep 11, 15016.CrossRefGoogle ScholarPubMed
Jones-Smith, JC, Dow, WH & Oddo, VM (2017) Association between Native American-owned casinos and the prevalence of large-for-gestational-age births. Int J Epidemiol 46, 1202–1210.CrossRefGoogle ScholarPubMed
Zhang, YQ, Li, H, Zong, XN, et al. (2023) Comparison of updated birth weight, length and head circumference charts by gestational age in China with the INTERGROWTH-21st NCSS charts: a population-based study. World J Pediatr 19, 96–105.CrossRefGoogle Scholar
Bao, C, Zhou, Y, Jiang, L, et al. (2011) Reasons for the increasing incidence of macrosomia in Harbin, China. BJOG: Int J Gynecol 118, 93–98.CrossRefGoogle ScholarPubMed
Tu, S, Wang, AL, Tan, MZ, et al. (2019) Family socioeconomic position and abnormal birth weight: evidence from a Chinese birth cohort. World J Pediatr 15, 483–491.CrossRefGoogle ScholarPubMed
National Burean of Statistical of China (2021) Statistical Communiqué of the People’s Republic of China on the 2021 National Economic and Social Development. Beijing: China Statistics Press.Google Scholar
Pérez-Escamilla, R & Kac, G (2013) Childhood obesity prevention: a life-course framework. Int J Obes Suppl 3, S3–S5.CrossRefGoogle ScholarPubMed
Yacamán-Méndez, D, Trolle-Lagerros, Y, Zhou, M, et al. (2021) Life-course trajectories of weight and their impact on the incidence of type 2 diabetes. Sci Rep 11, 12494.CrossRefGoogle ScholarPubMed
Jang, W, Kim, H, Lee, BE, et al. (2018) Maternal fruit and vegetable or vitamin C consumption during pregnancy is associated with fetal growth and infant growth up to 6 months: results from the Korean mothers and children’s environmental health (MOCEH) cohort study. Nutr J 17, 105.CrossRefGoogle ScholarPubMed
Bi, WG, Nuyt, AM, Weiler, H, et al. (2018) Association between vitamin D supplementation during pregnancy and offspring growth, morbidity, and mortality: a systematic review and meta-analysis. JAMA Pediatr 172, 635–645.CrossRefGoogle ScholarPubMed
Brahams, D (1988) Lessons from an anaesthetic accident. Lancet 1, 1408–1409.CrossRefGoogle ScholarPubMed
Da Silva Lopes, K, Ota, E, Shakya, P, et al. (2017) Effects of nutrition interventions during pregnancy on low birth weight: an overview of systematic reviews. BMJ Glob Health 2, e000389.CrossRefGoogle ScholarPubMed
Ramakrishnan, U (2004) Nutrition and low birth weight: from research to practice. Am J Clin Nutr 79, 17–21.CrossRefGoogle ScholarPubMed
Andreasyan, K, Ponsonby, AL, Dwyer, T, et al. (2007) Higher maternal dietary protein intake in late pregnancy is associated with a lower infant ponderal index at birth. Eur J Clin Nutr 61, 498–508.CrossRefGoogle ScholarPubMed
Assari, S (2020) Protective effects of maternal education against low birth weight deliveries: blacks’ diminished returns. Res Health Sci 5, 1–17.CrossRefGoogle ScholarPubMed
Gage, TB, Fang, F, O’Neill, E, et al. (2013) Maternal education, birth weight, and infant mortality in the United States. Demography 50, 615–635.CrossRefGoogle ScholarPubMed
Ashwin, D, Gibson, L, Hagemann, E, et al. (2022) The impact a Mediterranean diet in the third trimester of pregnancy has on neonatal body fat percentage. J Dev Origins Health Dis 13, 500–507.CrossRefGoogle ScholarPubMed
Sun, Y, Shen, Z, Zhan, Y, et al. (2020) Effects of pre-pregnancy body mass index and gestational weight gain on maternal and infant complications. BMC Pregnancy Childb 20, 390.CrossRefGoogle ScholarPubMed
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