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ABSTRACTObjectiveMaternal obesity during pregnancy is a risk factor for increased childhood body mass index (BMI) and the mechanism may be causal or confounded by lifestyle common to mother and child. We studied BMI in siblings and their mothers to test the hypothesis that siblings born after maternal weight gain will have increased BMI compared to older siblings. ApproachThis was a whole population data linkage study using data from North East Scotland, UK. Databases containing details from pregnant mothers and their five-year-old children born between 1997 and 2005 were linked using the community health index number. Childhood BMI and the difference between siblings BMI were related to maternal weight gain between pregnancies. Covariates included maternal obesity, smoking, socioeconomic status and the child's birth weight.ResultsMaternal weight gain between pregnancies was determined for 5,863 mothers in whom 718 had >2 pregnancies. Childhood BMI z score was increased in association with maternal obesity (mean increase 0.47 [95% CI 0.39, 0.56]) and with ≥10% maternal weight gain between pregnancies (mean increase 0.14 [95% CI 0.06, 0.21]), independent of covariates. In contrast, increased BMI z score for younger siblings, compared to older siblings, was not associated with maternal obesity in the earlier pregnancy or maternal weight gain between pregnancies. BMI z score was higher in younger compared to older siblings in association with deprivation (mean difference between most and least affluent categories 0.29 [0.08, 0.37]), persistent or new onset maternal smoking (increased by mean of 0.10[0.00, 0.19] for always smokers and 0.20[0.03, 0.38] for those starting compared to never smoked) and increased birth weight (BMI z score increased by 0.11 for each increase in birth weight z score [0.07, 0.14]).ConclusionWhen within-family confounding is considered, poverty, persistent and new onset maternal smoking during pregnancy and increased birth weight, but not maternal obesity or weight gain, are independent predictors of increased BMI in young children.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. This study was funded by NHS Grampian. FD, LC, JC, and GMcN receive personal support from the RESAS programme of the Scottish Government Nutrition and Health. We would also like to thank Caroline Comerford of NHS Grampian and other members of the research steering group for their advice during the study; the parents for their time and input; the nursery school staff for distributing study packs for parents; Andrea Gilmartin for organising the focus groups and Dr Sandra Carlisle for the helpful comments on earlier drafts of the manuscript. ; Peer reviewed ; Publisher PDF

Objective: To develop a timeline for evaluating public health nutrition policy interventions. Design: Concept mapping, a stakeholder-driven approach for developing an evaluation framework to estimate the 'time to impact' for policy interventions. The Schools (Health Promotion and Nutrition) (Scotland) Act 2007 was used as the model to develop the evaluation timeline as it had typical characteristics of government policy. Concept mapping requires stakeholders to generate a list of the potential outcomes, sort and rate the outcomes. Multidimensional scaling and hierarchical cluster data analysis were used to develop an anticipated timeline to impact for the policy. Setting: United Kingdom. Subjects: One hundred and eleven stakeholders representing nutrition, public health, medicine, education and catering in a range of sectors: research, policy, local government, National Health Service and schools. Results: Eighty-five possible outcomes were identified and grouped into thirteen clusters describing higher-level themes (e.g. long-term health, food literacy, economics, behaviour, diet, education). Negative and unintended consequences were anticipated relatively soon after implementation of the policy, whereas positive outcomes (e.g. dietary changes, health benefits) were thought likely to take longer to emerge. Stakeholders responsible for implementing the legislation anticipated that it would take longer to observe changes than those from policy or research. Conclusions: Developing an anticipated timeline provides a realistic framework upon which to base an outcome evaluation for policy interventions and identifies positive and negative outcomes as well as considering possible unintended consequences. It offers benefit to both policy makers and researchers in mapping the progress expected towards long-term health goals and outcomes.

Acknowledgements: We thank the LBC1936 members and project staff. Study Funding: The LBC1936 and this research are supported by Age UK (Disconnected Mind project), the UK Medical Research Council [MRC; G0701120, G1001245, MR/M013111/1, MR/R024065/1], and the University of Edinburgh. SRC, MEB, and IJD were also supported by a National Institutes of Health (NIH) research grant R01AG054628. JMW, IJD are also supported by a Wellcome Trust Strategic Award (Ref 104036/Z/14/Z). MCVH is funded by the Row Fogo Charitable Trust (grant No. BROD.FID3668413). SRC was also supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant Number 221890/Z/20/Z). Imaging and image analysis was performed at the Brain Research Imaging Centre (http://www.sbirc.ed.ac.uk/), Edinburgh, supported by the Scottish Funding Council SINAPSE Collaboration. LCAC acknowledges 4 Luciano funding from the Scottish Government's Rural and Environment Science and Analytical Services (RESAS) division. MVH is funded by the Row Fogo Charitable Trust Centre for Research into Ageing and the Brain (Ref No: AD.ROW4.35. BRO-D.FID3668413). JMW received funding from the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. ; Peer reviewed ; Publisher PDF

Copyright: © 2013 Tenesa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: Genotyping of the ABC1936, LBC1921, and LBC1936 cohorts and the analyses conducted here were supported by the UK's Biotechnology and Biological Sciences Research Council (BBSRC). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the BBSRC, The Royal Society, and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Research Into Ageing (continues as part of Age UK's The Disconnected Mind project). Phenotype collection in the Aberdeen Birth Cohort 1936 was supported by the BBSRC, the Wellcome Trust, and the Alzheimer's Research Trust. SJR, AR and AT are funded by the BBSRC through the Roslin Institute's strategic programme grant and project grant BB/K000195/1. The Brain data was provided by the Division of Aging Biology and the Division of Geriatrics and Clinical Gerontology (NIA) through the NIH GWAS Data Repository (dbGaP Accession Number: phs000249.v1.p1) and funded as part of the Intramural Research Program, NIA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer reviewed ; Publisher PDF