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Selection bias and patterns of confounding in cohort studies: the case of the NINFEA web-based birth cohort
  1. Costanza Pizzi1,2,
  2. Bianca L De Stavola2,
  3. Neil Pearce2,3,
  4. Fulvio Lazzarato1,
  5. Paola Ghiotti4,
  6. Franco Merletti1,
  7. Lorenzo Richiardi1
  1. 1Cancer Epidemiology Unit, CeRMS and CPO-Piemonte, University of Turin, Turin, Italy
  2. 2Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
  3. 3Centre for Public Health Research, Massey University, Wellington, New Zealand
  4. 4Department of Health, Piedmont Region, Turin, Italy
  1. Correspondence to Costanza Pizzi, Cancer Epidemiology Unit, CeRMS and CPO-Piemonte, University of Turin, Via Santena 7, Turin 10126, Italy; costanza.pizzi{at}lshtm.ac.uk

Abstract

Background Several studies have examined the effects of sample selection on the exposure–outcome association estimates in cohort studies, but the reasons why this selection may induce bias have not been fully explored.

Aims To investigate how sample selection of the web-based NINFEA birth cohort may change the confounding patterns present in the source population.

Methods The characteristics of the NINFEA participants (n=1105) were compared with those of the wider source population—the Piedmont Birth Registry (PBR)—(n=36 092), and the association of two exposures (parity and educational level) with two outcomes (low birth weight and birth by caesarean section), while controlling for other risk factors, was studied. Specifically the associations among measured risk factors within each dataset were examined and the exposure–outcome estimates compared in terms of relative ORs.

Results The associations of educational level with the other risk factors (alcohol consumption, folic acid intake, maternal age, pregnancy weight gain, previous miscarriages) partly differed between PBR and NINFEA. This was not observed for parity. Overall, the exposure–outcome estimates derived from NINFEA only differed moderately from those obtained in PBR, with relative ORs ranging between 0.74 and 1.03.

Conclusions Sample selection in cohort studies may alter the confounding patterns originally present in the general population. However, this does not necessarily introduce selection bias in the exposure–outcome estimates, as sample selection may reduce some of the residual confounding present in the general population.

  • Sample selection
  • selection bias
  • residual confounding
  • web-based studies
  • cohort studies
  • directed acyclic graph
  • biostatistics
  • epidemiology
  • growth
  • longitudinal studies
  • medical statistics
  • sport
  • nutrition
  • diet

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Footnotes

  • Funding This work was supported by Compagnia SanPaolo/FIRMS, the Piedmont Region, the Italian Ministry of University and Research (MIUR), the Italian Association for Research on Cancer (AIRC) and the Massey University Research Fund (MURF). The Centre for Public Health Research is supported by a Programme Grant from the Health Research Council of New Zealand.

  • Competing interests None.

  • Ethics approval The study was approved by the Ethical Committee of the San Giovanni Battista Hospital—A.S.O. C.T.O./C.R.F./Maria Adelaide, Turin, Italy.

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

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