Barker, D. J. P. The developmental origins of adult disease. J. Am. Coll. Nutr. 23, 588S–595S (2004).
Google Scholar
Lau, C., Rogers, J. M., Desai, M. & Ross, M. G. Fetal programming of adult disease: implications for prenatal care. Obstet. Gynecol. 117, 978–985 (2011).
Google Scholar
Gartstein, M. A. & Skinner, M. K. Prenatal influences on temperament development: the role of environmental epigenetics. Dev. Psychopathol. 30, 1269–1303 (2018).
Google Scholar
Nolvi, S. et al. Maternal prenatal stress and infant emotional reactivity six months postpartum. J. Affect. Disord. 199, 163–170 (2016).
Google Scholar
Gustafsson, H. C. et al. Maternal prenatal depression predicts infant negative affect via maternal inflammatory cytokine levels. Brain. Behav. Immun. 73, 470–481. (2018).
Google Scholar
Werner, E. et al. Higher maternal prenatal cortisol and younger age predict greater infant reactivity to novelty at 4 months: an observation-based study. Dev. Psychobiol. 55, 707–718 (2013).
Google Scholar
Baibazarova, E. et al. Influence of prenatal maternal stress, maternal plasma cortisol and cortisol in the amniotic fluid on birth outcomes and child temperament at 3 months. Psychoneuroendocrinology 38, 907–915 (2013).
Google Scholar
Gartstein, M. A. & Rothbart, M. K. Studying infant temperament via the revised infant behavior questionnaire. Infant Behav. Dev. 26, 64–86 (2003).
Google Scholar
Nigg, J. T. Temperament and developmental psychopathology. J. Child Psychol. Psychiatry. 47, 395–422 (2006).
Google Scholar
Lonigan, C. J., Phillips, B. M. & Hooe, E. S. Relations of positive and negative affectivity to anxiety and depression in children: evidence from a latent variable longitudinal study. J. Consult. Clin. Psychol. 71, 465 (2003).
Google Scholar
Gartstein, M. A. & Bateman, A. E. Early manifestations of childhood depression: influences of infant temperament and parental depressive symptoms. Infant Child. Development: Int. J. Res. Pract. 17, 223–248 (2008).
Google Scholar
Grant, V. V., Bagnell, A. L., Chambers, C. T. & Stewart, S. H. Early temperament prospectively predicts anxiety in later childhood. Can. J. Psychiatry. 54, 320–330 (2009).
Google Scholar
Keenan, K. Emotion dysregulation as a risk factor for child psychopathology. Clin. Psychol. Sci. Pract. 7, 418 (2000).
Google Scholar
Kostyrka-Allchorne, K., Wass, S. V. & Sonuga‐Barke, E. J. Research review: do parent ratings of infant negative emotionality and self‐regulation predict psychopathology in childhood and adolescence? A systematic review and meta‐analysis of prospective longitudinal studies. J. Child Psychol. Psychiatry. 61, 401–416 (2020).
Google Scholar
Edlow, A. G. Maternal obesity and neurodevelopmental and psychiatric disorders in offspring. Prenat. Diagn. 37, 95–110 (2017).
Google Scholar
Gustafsson, H. C. et al. Increased maternal prenatal adiposity, inflammation, and lower omega-3 fatty acid levels influence child negative affect. Front. NeuroSci. 13, 1035 (2019).
Google Scholar
Robinson, M. et al. Pre-pregnancy maternal overweight and obesity increase the risk for affective disorders in offspring. J. Dev. Origins Health Disease. 4, 42–48 (2013).
Google Scholar
Rodriguez, A. Maternal pre-pregnancy obesity and risk for inattention and negative emotionality in children. J. Child Psychol. Psychiatry. 51, 134–143 (2010).
Google Scholar
Kong, L., Norstedt, G., Schalling, M., Gissler, M. & Lavebratt, C. The risk of offspring psychiatric disorders in the setting of maternal obesity and diabetes. Pediatrics 142, e20180076 (2018).
Rivera, H. M., Christiansen, K. J. & Sullivan, E. L. The role of maternal obesity in the risk of neuropsychiatric disorders. Front. NeuroSci. 9, 194. (2015).
Google Scholar
Chen, S. et al. Rates of maternal weight gain over the course of pregnancy and offspring risk of neurodevelopmental disorders. BMC Med. 21, 108 (2023).
Google Scholar
Andersen, C. H., Thomsen, P. H., Nohr, E. A. & Lemcke, S. Maternal body mass index before pregnancy as a risk factor for ADHD and autism in children. Eur. Child Adolesc. Psychiatry. 27, 139–148 (2018).
Google Scholar
Getz, K. D., Anderka, M. T., Werler, M. M. & Jick, S. S. Maternal Pre-pregnancy body mass index and autism spectrum disorder among offspring: A Population‐Based Case–Control study. Paediatr. Perinat. Epidemiol. 30, 479–487 (2016).
Google Scholar
Su, L. et al. Association between gestational weight gain and autism spectrum disorder in offspring: a meta-analysis. Obesity 28, 2224–2231 (2020).
Google Scholar
Windham, G. C. et al. Maternal pre-pregnancy body mass index and gestational weight gain in relation to autism spectrum disorder and other developmental disorders in offspring. Autism Res. 12, 316–327 (2019).
Google Scholar
Pugh, S. et al. Gestational weight gain, prepregnancy body mass index and offspring attention-deficit hyperactivity disorder symptoms and behaviour at age 10. BJOG: Int. J. Obstet. Gynecol. 123, 2094–2103 (2016).
Google Scholar
Van Lieshout, R. J., Robinson, M. & Boyle, M. H. Maternal pre-pregnancy body mass index and internalizing and externalizing problems in offspring. Can. J. Psychiatry. 58, 151–159 (2013).
Google Scholar
Tore, E. C. et al. Gestational weight gain by maternal pre-pregnancy BMI and childhood problem behaviours in school-age years: a pooled analysis of two European birth cohorts. Matern. Child Health J. 24, 1288–1298 (2020).
Google Scholar
Bordeleau, M., Fernandez de Cossio, L., Chakravarty, M. M. & Tremblay, M. È. From maternal diet to neurodevelopmental disorders: a story of neuroinflammation. Front. Cell. Neurosci. 14, 612705 (2021).
Google Scholar
Sullivan, E. L. et al. Adipokines measured during pregnancy and at birth are associated with infant negative affect. Brain. Behav. Immun. 120, 34–43 (2024).
Google Scholar
van der Burg, J. W. et al. The role of systemic inflammation linking maternal BMI to neurodevelopment in children. Pediatr. Res. 79, 3–12 (2016).
Google Scholar
Chen, S., Zhao, S., Dalman, C., Karlsson, H. & Gardner, R. Association of maternal diabetes with neurodevelopmental disorders: autism spectrum disorders, attention-deficit/hyperactivity disorder and intellectual disability. Int. J. Epidemiol. 50, 459–474 (2021).
Google Scholar
e Silva, R. N. A. et al. Associations of maternal diabetes during pregnancy with psychiatric disorders in offspring during the first 4 decades of life in a population-based Danish birth cohort. JAMA Netw. Open. 4, e2128005–e2128005 (2021).
Google Scholar
Lotfi, N., Hami, J., Hosseini, M., Haghir, D. & Haghir, H. Diabetes during pregnancy enhanced neuronal death in the hippocampus of rat offspring. Int. J. Dev. Neurosci. 51, 28–35 (2016).
Google Scholar
Lain, K. Y. & Catalano, P. M. Metabolic changes in pregnancy. Clin. Obstet. Gynecol. 50, 938–948 (2007).
Google Scholar
Sonagra, A. D., Biradar, S. M., Dattatreya, K. & DS, J. M. Normal pregnancy-a state of insulin resistance. J. Clin. Diagn. Research: JCDR. 8, CC01 (2014).
Lowe, W. L. et al. Hyperglycemia and adverse pregnancy outcome Follow-up study (HAPO FUS): maternal gestational diabetes mellitus and childhood glucose metabolism. Diabetes Care. 42, 372–380. (2019).
Google Scholar
Sauder, K., Hockett, C., Ringham, B., Glueck, D. & Dabelea, D. Fetal overnutrition and offspring insulin resistance and β-cell function: the exploring perinatal outcomes among children (EPOCH) study. Diabet. Med. 34, 1392–1399 (2017).
Google Scholar
Lima, R. A. et al. The importance of maternal insulin resistance throughout pregnancy on neonatal adiposity. Paediatr. Perinat. Epidemiol. 35, 83–91 (2021).
Google Scholar
Hamilton, J. K. et al. Maternal insulin sensitivity during pregnancy predicts infant weight gain and adiposity at 1 year of age. Obesity 18, 340–346 (2010).
Google Scholar
Rodolaki, K. et al. The impact of maternal diabetes on the future health and neurodevelopment of the offspring: a review of the evidence. Front. Endocrinol. 14, 1125628 (2023).
Google Scholar
Sacks, K. N. et al. Prenatal exposure to gestational diabetes mellitus as an independent risk factor for long-term neuropsychiatric morbidity of the offspring. Am. J. Obstet. Gynecol. 215, 380 (2016). e381-380. e387.
Google Scholar
Xiang, A. H. et al. Maternal type 1 diabetes and risk of autism in offspring. Jama 320, 89–91 (2018).
Google Scholar
Nomura, Y. et al. Exposure to gestational diabetes mellitus and low socioeconomic status: effects on neurocognitive development and risk of attention-deficit/hyperactivity disorder in offspring. Arch. Pediatr. Adolesc. Med. 166, 337–343 (2012).
Google Scholar
Xiang, A. H. et al. Maternal gestational diabetes mellitus, type 1 diabetes, and type 2 diabetes during pregnancy and risk of ADHD in offspring. Diabetes Care. 41, 2502–2508 (2018).
Google Scholar
Linder, K. et al. Maternal insulin sensitivity is associated with oral glucose-induced changes in fetal brain activity. Diabetologia 57, 1192–1198 (2014).
Google Scholar
Linder, K. et al. Gestational diabetes impairs human fetal postprandial brain activity. J. Clin. Endocrinol. Metabolism. 100, 4029–4036 (2015).
Google Scholar
Pool, L. R. et al. Childhood risk factors and adulthood cardiovascular disease: a systematic review. J. Pediatr. 232, 118–126 (2021).
Google Scholar
Salam, R. A. et al. Effects of lifestyle modification interventions to prevent and manage child and adolescent obesity: a systematic review and meta-analysis. Nutrients 12, 2208 (2020).
Google Scholar
Carolan-Olah, M., Duarte‐Gardea, M. & Lechuga, J. A critical review: early life nutrition and prenatal programming for adult disease. J. Clin. Nurs. 24, 3716–3729 (2015).
Google Scholar
Monk, C., Lugo-Candelas, C. & Trumpff, C. Prenatal developmental origins of future psychopathology: mechanisms and pathways. Ann. Rev. Clin. Psychol. 15, 317–344 (2019).
Google Scholar
Sen, S. et al. Associations of prenatal and early life dietary inflammatory potential with childhood adiposity and cardiometabolic risk in project Viva. Pediatr. Obes. 13, 292–300 (2018).
Google Scholar
Sullivan, E. L. et al. Chronic consumption of a high-fat diet during pregnancy causes perturbations in the serotonergic system and increased anxiety-like behavior in nonhuman primate offspring. J. Neurosci. 30, 3826–3830 (2010).
Google Scholar
Thompson, J. R. et al. Exposure to a high-fat diet during early development programs behavior and impairs the central serotonergic system in juvenile non-human primates. Front. Endocrinol. 8, 164. (2017).
Google Scholar
Thompson, J. R. et al. Maternal diet, metabolic State, and inflammatory response exert unique and long-lasting influences on offspring behavior in non-human primates. Front. Endocrinol. 9, 161. (2018).
Google Scholar
Mitchell, A. et al. Maternal Western-style diet reduces social engagement and increases idiosyncratic behavior in Japanese macaque offspring. Brain. Behav. Immun. 105, 109–121 (2022).
Google Scholar
Borge, T. C., Aase, H., Brantsæter, A. L. & Biele, G. The importance of maternal diet quality during pregnancy on cognitive and behavioural outcomes in children: a systematic review and meta-analysis. BMJ Open. 7, e016777 (2017).
Google Scholar
Gustafsson, H. C., Kuzava, S. E., Werner, E. A. & Monk, C. Maternal dietary fat intake during pregnancy is associated with infant temperament. Dev. Psychobiol. 58, 528–535 (2016).
Google Scholar
Brunst, K. J. et al. Effects of prenatal social stress and maternal dietary fatty acid ratio on infant temperament: does race matter? Epidemiol. (Sunnyvale Calif) 4. (2014).
Lipton, L. R. et al. Associations among prenatal stress, maternal antioxidant intakes in pregnancy, and child temperament at age 30 months. J. Dev. Origins Health Disease. 8, 638–648 (2017).
Google Scholar
Wolever, T. M., Jenkins, D., Jenkins, A. L. & Josse, R. G. The glycemic index: methodology and clinical implications. Am. J. Clin. Nutr. 54, 846–854 (1991).
Google Scholar
Scholl, T. O., Chen, X., Khoo, C. S. & Lenders, C. The dietary glycemic index during pregnancy: influence on infant birth weight, fetal growth, and biomarkers of carbohydrate metabolism. Am. J. Epidemiol. 159, 467–474 (2004).
Google Scholar
Hasbullah, F. Y. et al. Factors associated with dietary glycemic index and glycemic load in pregnant women and risk for gestational diabetes mellitus. Int. J. Food Sci. Nutr. 71, 516–524 (2020).
Google Scholar
Rao, P. S., Shashidhar, A. & Ashok, C. In utero fuel homeostasis: lessons for a clinician. Indian J. Endocrinol. Metabol. 17, 60 (2013).
Google Scholar
Hu, F. B. et al. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N. Engl. J. Med. 345, 790–797 (2001).
Google Scholar
Willett, W., Manson, J. & Liu, S. Glycemic index, glycemic load, and risk of type 2 diabetes. Am. J. Clin. Nutr. 76, 274S–280S (2002).
Google Scholar
Horan, M. K. et al. Maternal nutrition and glycaemic index during pregnancy impacts on offspring adiposity at 6 months of age—analysis from the ROLO randomised controlled trial. Nutrients 8, 7 (2016).
Google Scholar
Maslova, E. et al. Maternal glycemic index and glycemic load in pregnancy and offspring metabolic health in childhood and adolescence—A cohort study of 68,471 mother–Offspring dyads from the Danish National birth cohort. Eur. J. Clin. Nutr. 73, 1049–1062. (2019).
Google Scholar
Moses, R. G. et al. Effect of a low-glycemic-index diet during pregnancy on obstetric outcomes. Am. J. Clin. Nutr. 84, 807–812 (2006).
Google Scholar
Okubo, H. et al. Maternal dietary glycemic index and glycemic load in early pregnancy are associated with offspring adiposity in childhood: the Southampton women’s survey. Am. J. Clin. Nutr. 100, 676–683 (2014).
Google Scholar
Alick, C. L. et al. Periconceptional maternal diet characterized by high glycemic loading is associated with offspring behavior in NEST. Nutrients 13, 3180 (2021).
Google Scholar
Chen, X. et al. Maternal dietary patterns and pregnancy outcome. Nutrients 8, 351 (2016).
Google Scholar
Abu-Saad, K. & Fraser, D. Maternal nutrition and birth outcomes. Epidemiol. Rev. 32, 5–25 (2010).
Google Scholar
Stifter, C. A., Willoughby, M. T. & Towe-Goodman, N. Agree or agree to disagree? Assessing the convergence between parents and observers on infant temperament. Infant Child. Development: Int. J. Res. Pract. 17, 407–426 (2008).
Google Scholar
Gartstein, M. A. & Hancock, G. R. Temperamental growth in infancy: demographic, maternal symptom, and stress contributions to overarching and fine-grained dimensions. Merrill-Palmer Q. 65, 121–157 (2019).
Google Scholar
Gustafsson, H. C. et al. Innovative methods for remote assessment of neurobehavioral development. Dev. Cogn. Neurosci. 52, 101015 (2021).
Google Scholar
Wood, E. K. et al. The association between food desert severity, socioeconomic status, and metabolic state during pregnancy in a prospective longitudinal cohort. Sci. Rep. 13, 7197 (2023).
Google Scholar
Conway, J. M., Ingwersen, L. M. & Moshfegh, A. J. Acurracy of dietary recal using the USDA 5-step multiple pass method in a multi-ethnic Populaiton: an observational validation study. J. Am. Diet. Assoc. 104(4), 595–603 (2003).
Foster-Powell, K., Holt, S. H. & Brand-Miller, J. C. International table of glycemic index and glycemic load values: 2002. Am. J. Clin. Nutr. 76, 5–56 (2002).
Google Scholar
Flood, A. et al. Methodology for adding glycemic load values to the National Cancer Institute diet history questionnaire database. J. Am. Diet. Assoc. 106, 393–402 (2006).
Google Scholar
Olendzki, B. C. et al. Methodology for adding glycemic index and glycemic load values to 24-hour dietary recall database. Nutrition 22, 1087–1095 (2006).
Google Scholar
Fields, D. A., Hunter, G. & Goran, M. I. Validation of the BOD POD with hydrostatic weighing: influence of body clothing. Int. J. Obes. 24, 200–205 (2000).
Google Scholar
Fields, D. A., Higgins, P. B. & Radley, D. Air-displacement plethysmography: Here to stay. Curr. Opin. Clin. Nutr. Metabolic Care. 8, 624–629 (2005).
Google Scholar
Marshall, N. E. et al. Comparison of multiple methods to measure maternal fat mass in late gestation. Am. J. Clin. Nutr. 103, 1055–1063. (2016).
Google Scholar
Van Raaij, J., Peek, M., Vermaat-Miedema, S. H., Schonk, C. M. & Hautvast, J. New equations for estimating body fat mass in pregnancy from body density or total body water. Am. J. Clin. Nutr. 48, 24–29. (1988).
Google Scholar
Wallace, T. M., Levy, J. C. & Matthews, D. R. Use and abuse of HOMA modeling. Diabetes Care. 27, 1487–1495 (2004).
Google Scholar
Mesman, J., van IJzendoorn, M. H. & Bakermans-Kranenburg, M. J. The many faces of the Still-Face paradigm: A review and meta-analysis. Dev. Rev. 29, 120–162 (2009).
Google Scholar
Tronick, E., Als, H., Adamson, L., Wise, S. & Brazelton, T. B. The infant’s response to entrapment between contradictory messages in face-to-face interaction. J. Am. Acad. Child. Psychiatry. 17, 1–13 (1978).
Google Scholar
Wagner, N. J. et al. Parenting and cortisol in infancy interactively predict conduct problems and callous–unemotional behaviors in childhood. Child Dev. 90, 279–297 (2019).
Google Scholar
Hankin, B. L. et al. Understanding comorbidity among internalizing problems: integrating latent structural models of psychopathology and risk mechanisms. Dev. Psychopathol. 28, 987–1012 (2016).
Google Scholar
Polanska, K. et al. Maternal stress during pregnancy and neurodevelopmental outcomes of children during the first 2 years of life. J. Paediatr. Child Health. 53, 263–270 (2017).
Google Scholar
Attali, E. & Yogev, Y. The impact of advanced maternal age on pregnancy outcome. Best Pract. Res. Clin. Obstet. Gynecol. 70, 2–9 (2021).
Google Scholar
Cohen, A., Pieper, C. F., Brown, A. J. & Bastian, L. A. Number of children and risk of metabolic syndrome in women. J. Women’s Health. 15, 763–773 (2006).
Google Scholar
Bentley-Lewis, R. et al. Effect of race/ethnicity on hypertension risk subsequent to gestational diabetes mellitus. Am. J. Cardiol. 113, 1364–1370. (2014).
Google Scholar
Feldman, R. et al. Maternal depression and anxiety across the postpartum year and infant social engagement, fear regulation, and stress reactivity. J. Am. Acad. Child. Adolesc. Psychiatry. 48, 919–927 (2009).
Google Scholar
Weissman, M. M. et al. Depressed mothers coming to primary care: maternal reports of problems with their children. J. Affect. Disord. 78, 93–100 (2004).
Google Scholar
Cohen, S., Kamarck, T. & Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 24(4), 385–396 (1983).
World Health Organization. WHO child growth standards based on length/height, weight and age. Acta Paediatr. Suppl. 450, 76–85 (2006).
Radloff, L. S. The CES-D scale: A self-report depression scale for research in the general population. Appl. Psychol. Meas. 1, 385–401 (1977).
Google Scholar
Thompson, A. L. et al. Development and validation of the infant feeding style questionnaire. Appetite 53, 210–221 (2009).
Google Scholar
The American College of Obstetricians and Gynecologists. Gestational diabetes mellitus. Obstet. Gynecol. 130, e17–e37. (2017).
Google Scholar
Graham, J. W. Missing data analysis: making it work in the real world. Ann. Rev. Psychol. 60, 549–576. (2009).
Google Scholar
Browne, M. W. & Cudeck, R. Alternative ways of assessing model fit. Sociol. Methods Res. 21, 230–258 (1992).
Google Scholar
Hu, L. T. & Bentler, P. M. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equation Modeling: Multidisciplinary J. 6, 1–55 (1999).
Google Scholar
Li, M., Francis, E., Hinkle, S. N., Ajjarapu, A. S. & Zhang, C. Preconception and prenatal nutrition and neurodevelopmental disorders: a systematic review and meta-analysis. Nutrients 11, 1628 (2019).
Google Scholar
Gustafsson, H. C. et al. Early development of negative and positive affect: implications for ADHD symptomatology across three birth cohorts. Dev. Psychopathol. 33, 1837–1848 (2021).
Google Scholar
Jaimes, C. et al. In vivo characterization of emerging white matter microstructure in the fetal brain in the third trimester. Hum. Brain. Mapp. 41, 3177–3185 (2020).
Google Scholar
Wilson, S. et al. Development of human white matter pathways in utero over the second and third trimester. Proceedings of the National Academy of Sciences 118, e2023598118 (2021).
Wang, Q. et al. Metabolic profiling of pregnancy: cross-sectional and longitudinal evidence. BMC Med. 14, 1–14 (2016).
Google Scholar
Ouyang, M., Dubois, J., Yu, Q., Mukherjee, P. & Huang, H. Delineation of early brain development from fetuses to infants with diffusion MRI and beyond. Neuroimage 185, 836–850 (2019).
Google Scholar
Tau, G. Z. & Peterson, B. S. Normal development of brain circuits. Neuropsychopharmacology 35, 147–168 (2010).
Google Scholar
Butte, N. F., Wong, W. W., Treuth, M. S., Ellis, K. J. & Smith, E. O. B. Energy requirements during pregnancy based on total energy expenditure and energy deposition. Am. J. Clin. Nutr. 79, 1078–1087 (2004).
Google Scholar
Cortés-Albornoz, M. C., García-Guáqueta, D. P., Velez-van-Meerbeke, A. & Talero-Gutiérrez, C. Maternal nutrition and neurodevelopment: A scoping review. Nutrients 13, 3530 (2021).
Google Scholar
Caudill, M. A., Strupp, B. J., Muscalu, L., Nevins, J. E. & Canfield, R. L. Maternal choline supplementation during the third trimester of pregnancy improves infant information processing speed: a randomized, double-blind, controlled feeding study. FASEB J. 32, 2172 (2018).
Google Scholar
Andescavage, N. N. et al. Complex trajectories of brain development in the healthy human fetus. Cereb. Cortex. 27, 5274–5283 (2017).
Google Scholar
Wilcox, G. Insulin and insulin resistance. Clin. Biochemist Reviews. 26, 19 (2005).
Google Scholar
Levitan, E. B. et al. Dietary glycemic index, dietary glycemic load, blood lipids, and C-reactive protein. Metabolism 57, 437–443 (2008).
Google Scholar
Galgani, J., Aguirre, C. & Díaz, E. Acute effect of meal glycemic index and glycemic load on blood glucose and insulin responses in humans. Nutr. J. 5, 1–7 (2006).
Google Scholar
Gawlińska, K. et al. Maternal dietary patterns are associated with susceptibility to a depressive-like phenotype in rat offspring. Dev. Cogn. Neurosci. 47, 100879 (2021).
Google Scholar
Eyth, E. & Naik, R. Hemoglobin A1c. (2019).
Fabricatore, A. N., Ebbeling, C. B., Wadden, T. A. & Ludwig, D. S. Continuous glucose monitoring to assess the Ecologic validity of dietary glycemic index and glycemic load. Am. J. Clin. Nutr. 94, 1519–1524 (2011).
Google Scholar
McGowan, C. & McAuliffe, F. Maternal nutrient intakes and levels of energy underreporting during early pregnancy. Eur. J. Clin. Nutr. 66, 906–913 (2012).
Google Scholar
Nowicki, E. et al. Predictors of measurement error in energy intake during pregnancy. Am. J. Epidemiol. 173, 560–568 (2011).
Google Scholar
Küpers, L. K. et al. Maternal dietary glycemic index and glycemic load in pregnancy and offspring cord blood DNA methylation. Diabetes Care. 45, 1822–1832 (2022).
Google Scholar
Kim, Y., Chen, J., Wirth, M. D., Shivappa, N. & Hebert, J. R. Lower dietary inflammatory index scores are associated with lower glycemic index scores among college students. Nutrients 10, 182 (2018).
Google Scholar
Quagliaro, L. et al. Intermittent high glucose enhances apoptosis related to oxidative stress in human umbilical vein endothelial cells: the role of protein kinase C and NAD (P) H-oxidase activation. Diabetes 52, 2795–2804 (2003).
Google Scholar
Wright, E. Jr, Scism-Bacon, J. & Glass, L. Oxidative stress in type 2 diabetes: the role of fasting and postprandial glycaemia. Int. J. Clin. Pract. 60, 308–314 (2006).
Google Scholar
Dawson, S. L. et al. Maternal prenatal gut microbiota composition predicts child behaviour. EBioMedicine 68, 103400 (2021).
Cao, Y. et al. Prenatal gut microbiota predicts temperament in offspring at 1–2 years. Biol. Res. Nurs. 26(4), 569–583 (2024).
Kline, R. B. Principles and Practice of Structural Equation Modeling (Guilford, 2023).
Marshall, N. E. et al. The importance of nutrition in pregnancy and lactation: lifelong consequences. Am. J. Obstet. Gynecol. 226, 607–632 (2022).
Google Scholar
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