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Household income, fetal size and birth weight: an analysis of eight populations
  1. Steve Turner1,
  2. Anke G Posthumus2,3,
  3. Eric A P Steegers2,3,
  4. Amel AlMakoshi1,4,
  5. Bahauddin Sallout5,
  6. Sheryl L Rifas-Shiman6,
  7. Emily Oken6,
  8. Ben Kumwenda1,
  9. Fatemah Alostad1,
  10. Catherine Wright-Corker1,
  11. Laura Watson1,
  12. Diane Mak1,
  13. Hiu Ching Cheung1,
  14. Alice Judge1,
  15. Lorna Aucott7,
  16. Vincent W V Jaddoe2,8,
  17. Isabella Annesi Maesano9,
  18. Munawar Hussain Soomro9,
  19. Peter Hindmarsh10,
  20. Geir Jacobsen11,
  21. Torstein Vik11,
  22. Isolina Riaño-Galan12,13,14,
  23. Ana Cristina Rodríguez-Dehli14,15,16,
  24. Aitana Lertxundi14,17,18,
  25. Loreto Santa Marina Rodriguez14,17,19,
  26. Martine Vrijheid14,20,21,
  27. Jordi Julvez22,23,24,
  28. Ana Esplugues14,25,
  29. Carmen Iñiguez14,26
  1. 1 Child Health, University of Aberdeen, Aberdeen, UK
  2. 2 The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands
  3. 3 Department of Obstetrics and Gynaecology, Erasmus MC, Rotterdam, The Netherlands
  4. 4 Maternal-Fetal medicine, Women’s Specialized Hospital, King Fahad Medical City, Riyadh, Saudi Arabia
  5. 5 Medical Service Directorate, Ministry of Defence, Riyadh, Saudi Arabia
  6. 6 Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
  7. 7 Centre for Healthcare Randomised Trial, University of Aberdeen, Aberdeen, UK
  8. 8 Department of Paediatrics, Erasmus MC, Rotterdam, The Netherlands
  9. 9 Debrest Institute of Epidemiology and Public Health, Montpellier University and INSERM, Montpellier, France
  10. 10 University College London, London, UK
  11. 11 Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
  12. 12 AGC de Pediatría, Hospital Universitario Central de Asturias, Asturias, Oviedo, Spain
  13. 13 IUOPA-Departamento de Medicina-ISPA, Universidad de Oviedo, Oviedo, Spain
  14. 14 CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
  15. 15 Pediatrics Service, Hospital Universitario San Agustín, Avilés, Spain
  16. 16 Servicio de Salud del Principado de Asturias (SESPA), IUOPA-Departamento de Medicina-ISPA, Universidad de Oviedo, Oviedo, Spain
  17. 17 Biodonostia Health Research Institute, San Sebastian, Spain
  18. 18 Department of Preventive Medicine and Public Health, Faculty of Medicine, University of the Basque Country, (UPV/EHU), Spain
  19. 19 Health Department of Basque Government, Subdirectorate of Public Health of Gipuzkoa, San Sebastian, Spain
  20. 20 ISGlobal- Instituto de Salud Global de Barcelona-Campus MAR, PRBB, Barcelona, Catalonia, Spain
  21. 21 Universitat Pompeau Fabra (UPF), Barcelona, Spain
  22. 22 Institut d'Investigació Sanitària Pere Virgili (IISPV), Hospital Universitari Sant Joan de Reus, Reus, Spain
  23. 23 Instituto de Salud Global, Barcelona, Spain
  24. 24 Hospital Universitari Sant Joan de Reus, Reus, Spain
  25. 25 Joint Research Unit of Epidemiology and Environmental Health, FISABIO, Valencia, Spain
  26. 26 Department of Statistics and Operational Research, Universitat de València, València, Spain
  1. Correspondence to Professor Steve Turner, Child Health, University of Aberdeen, Aberdeen, Aberdeen, UK; s.w.turner{at}abdn.ac.uk

Abstract

Background The age at onset of the association between poverty and poor health is not understood. Our hypothesis was that individuals from highest household income (HI), compared to those with lowest HI, will have increased fetal size in the second and third trimester and birth.

Methods. Second and third trimester fetal ultrasound measurements and birth measurements were obtained from eight cohorts. Results were analysed in cross-sectional two-stage individual patient data (IPD) analyses and also a longitudinal one-stage IPD analysis.

Results The eight cohorts included 21 714 individuals. In the two-stage (cross-sectional) IPD analysis, individuals from the highest HI category compared with those from the lowest HI category had larger head size at birth (mean difference 0.22 z score (0.07, 0.36)), in the third trimester (0.25 (0.16, 0.33)) and second trimester (0.11 (0.02, 0.19)). Weight was higher at birth in the highest HI category. In the one-stage (longitudinal) IPD analysis which included data from six cohorts (n=11 062), head size was larger (mean difference 0.13 (0.03, 0.23)) for individuals in the highest HI compared with lowest category, and this difference became greater between the second trimester and birth. Similarly, in the one-stage IPD, weight was heavier in second highest HI category compared with the lowest (mean difference 0.10 (0 .00, 0.20)) and the difference widened as pregnancy progressed. Length was not linked to HI category in the longitudinal model.

Conclusions The association between HI, an index of poverty, and fetal size is already present in the second trimester.

  • BIRTH WEIGHT
  • POVERTY
  • EMBRYONIC AND FETAL DEVELOPMENT
  • EPIDEMIOLOGY

Data availability statement

Data are available on reasonable request. Data are available on request to the data controller for each cohort (IAM for EDEN, VWVJ for Generation R, CI for the INMA cohorts, PH for the London cohort, EO for Project Viva, ST for the Saudi and SEATON cohorts and GJ for Scandinavian SGA).

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Data availability statement

Data are available on reasonable request. Data are available on request to the data controller for each cohort (IAM for EDEN, VWVJ for Generation R, CI for the INMA cohorts, PH for the London cohort, EO for Project Viva, ST for the Saudi and SEATON cohorts and GJ for Scandinavian SGA).

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Footnotes

  • Contributors ST conceived the idea, curated the data, wrote the first draft of the manuscript and is the guarantor of the work. ST, AGP, MHS and SLR-S have accessed the original data. AGP, MHS and SLR-S analysed data for the Generation R, EDEN and Project Viva cohorts respectively. AGP and EAPS contributed to the analytical approach and provided an obstetric perspective. CI provided data and made important contributions to accessing data from the INMA cohorts. BK, FA, CW-C, LW, DM, HCC and AJ contributed to data analysis. LA supervised the statistical analysis. AA, BS, EO, VWVJ, IAM, MHS, PH, GJ, TV, IRG, CR-D, AL, LSMR, MV, JJ and AE contributed data collection.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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