Literature DB >> 29374028

Paediatric obesity appears to lower the risk of diabetes if selection bias is ignored.

Steven D Stovitz1, Hailey R Banack2, Jay S Kaufman3.   

Abstract

BACKGROUND: Frustrated with the onslaught of articles reporting fascination with results that appear paradoxical but are merely due to selection bias, we studied the apparent effect of obesity on diabetes risk in youth who had a test for diabetes. We hypothesised that obese subjects would have lower rates of diabetes than non-obese subjects due to selection bias, and consequently, obesity would appear to lower the risk of diabetes.
METHODS: Retrospective cohort study of children (4-9 years), pre-teens (10-12 years) and teenagers (13-19 years). Participation was restricted to those who had a test of haemoglobin A1C along with measured height and weight. Body mass index percentile via the Centers for Disease Control and Prevention age and sex standards was calculated and categorised. The main outcome was A1C%, subsequently categorised at the level for diagnosis of diabetes mellitus (≥6.5%).
RESULTS: The sample consisted of 134 (2%) underweight, 1718 (30%) healthy weight, 660 (12%) overweight and 3190 (56%) obese individuals. 16% (n=936) had an A1C≥6.5%. Overall, healthy weight children had 8.2 times the risk of A1C≥6.5% (95% CI 5.3 to 12.7) compared with those in the obese category. The relative risk was 13 in pre-teens (95% CI 8.5 to 20.0) and 3.9 in teenagers (95% CI 3.3 to 4.7).
CONCLUSIONS: Healthy weight was associated with a 4-13 times higher relative risk of diabetes mellitus compared with being obese. While apparently shocking, the study's fatal flaw (selection bias) explains the 'paradoxical' finding. Ignoring selection bias can delay advances in medical science. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  epidemiological methods; obesity; research design in epidemiology; study design

Mesh:

Substances:

Year:  2018        PMID: 29374028     DOI: 10.1136/jech-2017-209985

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN: 0143-005X            Impact factor:   3.710


  2 in total

1.  Unjustified assertions regarding race and ethnicity in clinical decision-making (Re: The effect of ethnicity on semen analysis and hormones in the infertile patient, CUAJ, Feb 2020).

Authors:  Joanna Merckx; Arjumand Siddiqi; Jay S Kaufman
Journal:  Can Urol Assoc J       Date:  2020-04-01       Impact factor: 1.862

2.  Selection bias can creep into unselected cohorts and produce counterintuitive findings.

Authors:  Steven D Stovitz; Hailey R Banack; Jay S Kaufman
Journal:  Int J Obes (Lond)       Date:  2020-11-25       Impact factor: 5.095

  2 in total

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