Thirty Years of Prospective Nationwide Incidence of Childhood Type 1 Diabetes
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OBJECTIVE: During the past few decades, a rapidly increasing incidence of childhood type 1 diabetes (T1D) has been reported from many parts of the world. The change over time has been partly explained by changes in lifestyle causing rapid early growth and weight development. The current study models and analyzes the time trend by age, sex, and birth cohort in an exceptionally large study group. RESEARCH DESIGN AND METHODS: The present analysis involved 14,721 incident cases of T1D with an onset of 0–14.9 years that were recorded in the nationwide Swedish Childhood Diabetes Registry from 1978 to 2007. Data were analyzed using generalized additive models. RESULTS: Age- and sex-specific incidence rates varied from 21.6 (95% CI 19.4–23.9) during 1978–1980 to 43.9 (95% CI 40.7–47.3) during 2005–2007. Cumulative incidence by birth cohort shifted to a younger age at onset during the first 22 years, but from the birth year 2000 a statistically significant reversed trend (P < 0.01) was seen. CONCLUSIONS: Childhood T1D increased dramatically and shifted to a younger age at onset the first 22 years of the study period. We report a reversed trend, starting in 2000, indicating a change in nongenetic risk factors affecting specifically young children.
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In many countries, the rise in incidence of type 1 diabetes has fluctuated, although Sweden has recently seen incidence rates plateau.
“In many countries, the rise in incidence of type 1 diabetes has fluctuated, although Sweden has recently seen incidence rates plateau.12”
From Type 1 diabetes (2014) · cites this paper as [12]
The Results (Generalized additive models; page unavailable) report that Swedish childhood type 1 diabetes incidence leveled off during the last seven years studied. The paper also describes rising incidence in many countries and short-term variation, but it does not establish that the rise fluctuated in many countries. (LLM, conf=0.84)
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Self-citationDeeb, A., Abu-Awad, S., Attia, S., El-Abiary, M., Aljubeh, J. M., Yousef, H., AbdelRahman, L., Hajeri, A. A., & Mustafa, H. (2014) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2014.0224 · Cited by 23 · see citing works
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Self-citation
- Authors
- Berhan, Y., Waernbaum, I., Lind, T., Möllsten, A., Dahlquist, G., & for the Swedish Childhood Diabetes Study Group*
- Affiliations
- Umeå University (SE)
- Corresponding author
- Dahlquist, Gisela
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 2011-01-21
- Volume
- 60
- Issue
- 2
- Pages
- 577-581
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- PMC
- PMC3028358
- OpenAlex
- W2136411263
- Cited by
- 237
- References
- 24
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 12 · 2023: 23 · 2022: 6 · 2021: 10 · 2020: 21 · 2019: 12 · 2018: 17 · 2017: 16 · 2016: 17 · 2015: 18 · 2014: 33 · 2013: 23 · 2012: 15
- FWCI
- 15.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetes (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- Västerbotten Läns Landsting
- Vetenskapsrådet
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- type 1 diabetes in children, incidence trends, birth cohort, age of onset, sex differences, non-genetic risk factors, childhood obesity
- MeSH terms
- Adolescent, Child, Child, Preschool, Diabetes Mellitus, Type 1, Female, Humans, Infant, Male, Registries, Sweden, Incidence, Linear Models, Age of Onset
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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