To examine associations of parental socioeconomic position with early-life offspring body mass index (BMI) trajectories in a middle-income country.
Overall, 12,385 Belarusian children born 1996–97 and enrolled in a randomised breastfeeding promotion trial at birth, with 3–14 measurements of BMI from birth to 7 years.
Cohort analysis in which exposures were parental education (common secondary or less; advanced secondary or partial university; completed university) and occupation (manual; non-manual) at birth, and the outcome was BMI z-score trajectories estimated using multilevel linear spline models, controlling for trial arm, location, parental BMI, maternal smoking status and number of older siblings.
Infants born to university-educated mothers were heavier at birth than those born to secondary school-educated mothers [by 0.13 BMI z-score units (95% confidence interval, CI: 0.07, 0.19) for girls and 0.11 (95% CI: 0.05, 0.17) for boys; equivalent for an infant of average birth length to 43 and 38 g, respectively]. Between the ages of 3–7 years children of the most educated mothers had larger BMI increases than children of the least educated mothers. At age 7 years, children of university-educated mothers had higher BMIs than those born to secondary school-educated mothers by 0.11 z-score (95% CI: 0.03, 0.19) among girls and 0.18 (95% CI: 0.1, 0.27) among boys, equivalent to differences in BMI for a child of average height of 0.19 and 0.26 kg/m2, respectively. After further controlling for parental BMI, these differences attenuated to 0.08 z-score (95% CI: 0, 0.16) and 0.16 z-score (95% CI: 0.07, 0.24), respectively, but changed very little after additional adjustment for number of older siblings and mother’s smoking status. Associations were similar when based on paternal educational attainment and highest household occupation.
In Belarus, consistent with some middle-income countries, higher socioeconomic position was associated with greater BMI trajectories from age 3 onwards.
We are grateful to the cohort members and their parents for their generous participation in the study, to the polyclinic paediatricians who examined all the children and ensured a very high follow-up rate and to the dedication of the members of the Belarusian team who ensured that this trial could start and who continue to support and guide the study through all stages of PROBIT.Funding
This study is supported by a grant from the Canadian Institutes of Health Research (to MSK) and from the European Union’s project on Early Nutrition Programming: Long-term Efficacy and Safety Trials (grant code: FOOD-DT-2005-007036 to RMM). The Medical Research Council/University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol is funded by the Medical Research Council (MRC) and is a partnership between the MRC and the University of Bristol. DALs contribution to this work is supported by a UK Economic and Social Research Council large grant (Grant Code: RES-060-23-0011). LDH is funded by a Career Development Award from the UK Medical Research Council (MR/M020894/1). EO is funded by the US National Institutes of Health (R01HD050758, P30 DK092924, K24 HD069408). The NIHR Bristol Nutrition Biomedical Research Unit is funded by the National Institute for Health Research (NIHR) and is a partnership between University Hospitals Bristol NHS Foundation Trust and the University of Bristol. RAH is supported by the Wellcome Trust, Institutional Strategic Support Fund and Elizabeth Blackwell Institute. None of the funding bodies influenced the data collection, analysis or its interpretation for this paper.Authors contributions
The hypotheses were developed by RP, RMM and DAL. MSK and RMM contributed to obtaining funding for PROBIT fieldwork. KT developed the methods for the multilevel models and supervised RP in completing these analyses. RP wrote the first draft and co-coordinated completion of the paper. All authors critically commented on, edited earlier drafts and approved the final version of the paper. RP had full access to all the data in the study, takes responsibility for the integrity of the data and the accuracy of the data analysis.
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