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Association between maternal prepregnancy body mass index with offspring cardiometabolic risk factors: analysis of three Brazilian birth cohorts

Published online by Cambridge University Press:  04 May 2021

Mariane da Silva Dias*
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
Alicia Matijasevich
Affiliation:
Departamento de Medicina Preventiva, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, SP, Brazil
Ana Maria B. Menezes
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
Fernando C. Barros
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
Fernando C. Wehrmeister
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
Helen Gonçalves
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
Iná S. Santos
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil Department of Medicine, Postgraduate Program in Pediatrics and Child Health, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
Bernardo Lessa Horta
Affiliation:
Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
*
Address for correspondence: Mariane da Silva Dias, Department of Social Medicine, Postgraduate Program in Epidemiology, Federal University of Pelotas, Marechal Deodoro, 1160 3° floor, Pelotas96020-220, Brazil. Email: [email protected]

Abstract

Evidence suggests that maternal prepregnancy body mass index (BMI) is associated with offspring cardiometabolic risk factors. This study was aimed at assessing the association of maternal prepregnancy BMI with offspring cardiometabolic risk factors in adolescence and adulthood. We also evaluated whether offspring BMI was a mediator in this association. The study included mother–offspring pairs from three Pelotas birth cohorts. Offspring cardiometabolic risk factors were collected in the last follow-up of each cohort [mean age (in years) 30.2, 22.6, 10.9]. Blood pressure was measured using an automatic device, cholesterol by using an enzymatic colorimetric method, and glucose from fingertip blood, using a portable glucose meter. In a pooled analysis of the cohorts, multiple linear regression was used to control for confounding. Mediation analysis was conducted using G-computation formula. In the adjusted model, mean systolic blood pressure of offspring from overweight and obese mothers was on average 1.25 (95% CI: 0.45; 2.05) and 2.13 (95% CI: 0.66; 3.59) mmHg higher than that of offspring from normal-weight mothers; for diastolic blood pressure, the means were 0.80 (95% CI: 0.26; 1.34) and 2.60 (95% CI: 1.62; 3.59) mmHg higher, respectively. Non-HDL cholesterol was positively associated with maternal BMI, whereas blood glucose was not associated. Mediation analyses showed that offspring BMI explained completely the association of maternal prepregnancy BMI with offspring systolic and diastolic blood pressure, and non-HDL cholesterol. Our findings suggest that maternal prepregnancy BMI is positively associated with offspring blood pressure, and blood lipids, and this association is explained by offspring BMI.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press in association with International Society for Developmental Origins of Health and Disease

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References

Risk, NCD, Collaboration, F. Trends in adult body-mass index in 200 countries from 1975 to 2014 : a pooled analysis of 1698 population-based measurement studies with 19 · 2 million participants. Lancet. 2014; 387, 13771396.Google Scholar
Horta, BL, Barros, FC, Lima, NP, et al. Maternal anthropometry: Trends and inequalities in four population-based birth cohorts in Pelotas, Brazil, 1982–2015. Int J Epidemiol. 2019; 48, I26I36.CrossRefGoogle Scholar
Gesink Law, DC, Maclehose, RF, Longnecker, MP. Obesity and time to pregnancy. Hum Reprod. 2007; 22, 414420.CrossRefGoogle ScholarPubMed
Marchi, J, Berg, M, Dencker, A, Olander, EK, Begley, C. Risks associated with obesity in pregnancy, for the mother and baby: A systematic review of reviews. Obes Rev. 2015; 16 CrossRefGoogle Scholar
Turcksin, R, Bel, S, Galjaard, S, Devlieger, R. Maternal obesity and breastfeeding intention, initiation, intensity and duration: A systematic review. Matern Child Nutr. 2014; 10, 166183.CrossRefGoogle ScholarPubMed
Lemas, DJ, Brinton, JT, Shapiro, ALB, et al. Associations of maternal weight status prior and during pregnancy with neonatal cardiometabolic markers at birth: the Healthy Start study. Int J Obes. 2015; 39, 14371442.CrossRefGoogle ScholarPubMed
Westberg, AP, Kautiainen, H, Salonen, MK, et al. The impact of maternal weight in pregnancy on glucose metabolism in non-diabetic offspring in late adulthood. Diabetes Res Clin Pract. 2019; 158, 107926.CrossRefGoogle ScholarPubMed
Daraki, V, Georgiou, V, Papavasiliou, S, et al. Metabolic profile in early pregnancy is associated with offspring adiposity at 4 years of age: The Rhea pregnancy cohort Crete, Greece. PLoS One. 2015; 10, 118.CrossRefGoogle ScholarPubMed
Tan, HC, Roberts, J, Catov, J, et al. Mother’s pre-pregnancy BMI is an important determinant of adverse cardiometabolic risk in childhood. Pediatr Diabetes. 2015; 16, 419426.CrossRefGoogle ScholarPubMed
Cox, B, Luyten, LJ, Dockx, Y, et al. Association Between Maternal Prepregnancy Body Mass Index and Anthropometric Parameters, Blood Pressure, and Retinal Microvasculature in Children Age 4 to 6 Years. JAMA Netw Open. 2020; 3, e204662.CrossRefGoogle ScholarPubMed
Wander, PL, Hochner, H, Sitlani, CM, et al. Maternal genetic variation accounts in part for the associations of maternal size during pregnancy with offspring cardiometabolic risk in adulthood. PLoS One. 2014; 9, 17.CrossRefGoogle ScholarPubMed
Santos Ferreira, DL, Williams, DM, Kangas, AJ, et al. Association of pre-pregnancy body mass index with offspring metabolic profile: Analyses of 3 European prospective birth cohorts. PLoS Med. 2017; 14, 119.CrossRefGoogle ScholarPubMed
Rath, SR, Marsh, JA, Newnham, JP, et al. Parental pre-pregnancy BMI is a dominant early-life risk factor influencing BMI of offspring in adulthood. Obes Sci Pract. 2016; 2, 4857.CrossRefGoogle ScholarPubMed
Stamnes Køpp, UM, Dahl-Jørgensen, K, Stigum, H, et al. The associations between maternal pre-pregnancy body mass index or gestational weight change during pregnancy and body mass index of the child at 3 years of age. Int J Obes. 2012; 36, 13251331.CrossRefGoogle ScholarPubMed
Gademan, MGJ, Vermeulen, M, Oostvogels, AJJM, et al. Maternal prepregancy BMI and lipid profile during early pregnancy are independently associated with offspring’s body composition at age 5–6 Years: The ABCD study. PLoS One. 2014; 9, 18.CrossRefGoogle ScholarPubMed
Dias, MS, Matijasevich, A, Barros, AJD, et al. Influence of maternal pre-pregnancy nutritional status on offspring anthropometric measurements and body composition in three Brazilian Birth Cohorts. Public Health Nutr. 2020; 20.CrossRefGoogle Scholar
Hochner, H, Friedlander, Y, Calderon-Margalit, R, et al. Associations of Maternal Prepregnancy Body Mass Index and Gestational Weight Gain With Adult Offspring Cardiometabolic Risk Factors. Circulation. 2012; 125, 13811389.CrossRefGoogle ScholarPubMed
Brandt, S, Moß, A, Lennerz, B, et al. Plasma insulin levels in childhood are related to maternal factors - results of the Ulm Birth Cohort Study. Pediatr Diabetes. 2014; 15, 453463.CrossRefGoogle ScholarPubMed
Lawlor, DA, Smith, GD, O’Callaghan, M, et al. Epidemiologic evidence for the fetal overnutrition hypothesis: Findings from the Mater-University study of pregnancy and its outcomes. Am J Epidemiol. 2007; 165, 418424.CrossRefGoogle ScholarPubMed
Lawlor, DA. The society for social medicine John Pembert on Lecture 2011. Developmental overnutrition-an old hypothesis with new importance. Int J Epidemiol. 2013; 42, 729.CrossRefGoogle ScholarPubMed
Farrar, D, Simmonds, M, Bryant, M, et al. Hyperglycaemia and risk of adverse perinatal outcomes: Systematic review and meta-analysis. BMJ. 2016; 354, i4694.CrossRefGoogle ScholarPubMed
Malta, DC, Bernal, RTI, Vieira Neto, E, et al. Trends in risk and protective factors for noncommunicable diseases in the population with health insurance in Brazil from 2008 to 2015. Rev Bras Epidemiol. 2018; 21.Google Scholar
Allen, L, Williams, J, Townsend, N, et al. Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: a systematic review. Lancet Glob Heal. 2017; 5, e277e289.CrossRefGoogle ScholarPubMed
Nyberg, ST, David Batty, G, Pentti, J, et al. Obesity and loss of disease-free years owing to major non-communicable diseases: a multicohort study. Lancet Public Health. 2018; 3, e490e497.CrossRefGoogle ScholarPubMed
Shrier, I, Platt, RW. Reducing bias through directed acyclic graphs. BMC Medical Research Methodology. 2008; 15, 115.Google Scholar
Morea, M, Miu, N, Morea, VF, Cornean, R. Maternal obesity - a risk factor for metabolic syndrome in children. Clujul Med. 2013; 86, 259265.Google ScholarPubMed
Discacciati, A, Bellavia, A, Lee, JJ, Mazumdar, M, Valeri, L. Med4way : a Stata command to investigate mediating and interactive mechanisms using the four-way effect decomposition. 2018; 1–6. doi: 10.1093/ije/dyy236 CrossRefGoogle Scholar
VanderWeele, TJ. Principles of confounder selection. Eur J Epidemiol. 2019; 34, 211219.CrossRefGoogle ScholarPubMed
WORLD HEALTH ORGANIZATION. Obesity: preventing and managing the global epidemic. Report of a World Health Organization Consultation, 2000. Geneva: World Health Organization. (WHO Obesity Technical Report Series, n. 894) 253.Google Scholar
Miranda, JJ, Carrillo-Larco, RM, Ferreccio, C, et al. Trends in cardiometabolic risk factors in the Americas between 1980 and 2014: A pooled analysis of population-based surveys. Lancet Glob Health. 2020; 8, e123e133.CrossRefGoogle Scholar
Jacota, M, Forhan, A, Saldanha-Gomes, C, Charles, MA, Heude, B. Maternal weight prior and during pregnancy and offspring’s BMI and adiposity at 5–6 years in the EDEN mother–child cohort. Pediatr Obes. 2017; 12, 320329.CrossRefGoogle ScholarPubMed
Langsted, A., Nordestgaard, BG. Nonfasting versus fasting lipid profile for cardiovascular risk prediction. Pathology. 2019; 51, 131141.CrossRefGoogle ScholarPubMed
Nordestgaard, BG. A Test in Context: Lipid Profile, Fasting Versus Nonfasting. J Am Coll Cardiol. 2017; 70, 16371646.CrossRefGoogle ScholarPubMed