Context and disease when disease risk is low.
- 1 Lund University, Sweden;
- 2 Harvard School of Public Health, United States;
- 3 Clinical Sciences, Social Epidemiology, Sweden;
- 4 National Institute of Health and Medical Research, France;
- 5 Department of Clinicial Sciences, Sweden;
- 6 Department of Clinical Sciences in Malmö, Lund University, Sweden
- Correspondence to: Kristian F Lynch, Social Epidemiology, Clinical Sciences, Lund University, CRC, Ing 72, hus 28, plan 12, UMAS, Malmoe, 20502, Sweden; kristian.lynch{at}med.lu.se
- Received 5 November 2008
- Accepted 15 August 2009
- Published Online First 14 October 2009
Abstract
Background: Several European studies have found significant small area variation in childhood-onset (Type 1) Diabetes (T1D) risk, which has been interpreted as evidence for contextual determinants of T1D. However, this conclusion may be fallacious since the limited number of newborns and the low risk for T1D is a source of spurious variability not properly handled by usual statistical methods. This study investigates the existence of contextual effects in the genesis of T1D, confronts conclusions in previous reports with results obtained in a multilevel regression framework, and highlights analysis of variance as a useful approach in Public Health.
Methods: All singletons born in Sweden between 1987 and 1991 were identified in the Medical Birth Registry (n=560766), and followed for diabetes until age fourteen using the Hospital Discharge Registry. Area variation in cumulative incidence of T1D was estimated by different statistical methods including multilevel logistic regression.
Results: T1D risk ranged from 4.3 to 6.5 per 1000 newborns across the counties (n=24) and from 0.0 to 19.2 per 1000 newborns across the municipalities (n=284). These differences were significant in standard statistical tests (counties, p=0.02; municipalities, p=0.007). However according to multilevel analyses, T1D risk ranged from 4.7 to 5.7 and from 4.4 to 6.0 per 1000 newborns in counties and municipalities respectively and the area variation was small and without practical relevance (counties, σ2=0.006; municipalities, σ2=0.017).
Conclusion: Previous reports based on standard statistical tests are misleading. According to multilevel analysis, administrative areas have minor relevance for individual risk of Type 1 diabetes in Sweden.
