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Tanoey J, Baechle C, Brenner H, Deckert A, Fricke J, Günther K, Karch A, Keil T, Kluttig A, Leitzmann M, Mikolajczyk R, Obi N, Pischon T, Schikowski T, Schipf SM, Schulze MB, Sedlmeier A, Moreno Velásquez I, Weber KS, Völzke H, Ahrens W, Gastell S, Holleczek B, Jöckel KH, Katzke V, Lieb W, Michels KB, Schmidt B, Teismann H, Becher H. Birth Order, Caesarean Section, or Daycare Attendance in Relation to Child- and Adult-Onset Type 1 Diabetes: Results from the German National Cohort. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:10880. [PMID: 36078596 PMCID: PMC9517906 DOI: 10.3390/ijerph191710880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/25/2022] [Accepted: 08/27/2022] [Indexed: 06/15/2023]
Abstract
(1) Background: Global incidence of type 1 diabetes (T1D) is rising and nearly half occurred in adults. However, it is unclear if certain early-life childhood T1D risk factors were also associated with adult-onset T1D. This study aimed to assess associations between birth order, delivery mode or daycare attendance and type 1 diabetes (T1D) risk in a population-based cohort and whether these were similar for childhood- and adult-onset T1D (cut-off age 15); (2) Methods: Data were obtained from the German National Cohort (NAKO Gesundheitsstudie) baseline assessment. Self-reported diabetes was classified as T1D if: diagnosis age ≤ 40 years and has been receiving insulin treatment since less than one year after diagnosis. Cox regression was applied for T1D risk analysis; (3) Results: Analyses included 101,411 participants (100 childhood- and 271 adult-onset T1D cases). Compared to "only-children", HRs for second- or later-born individuals were 0.70 (95% CI = 0.50-0.96) and 0.65 (95% CI = 0.45-0.94), respectively, regardless of parental diabetes, migration background, birth year and perinatal factors. In further analyses, higher birth order reduced T1D risk in children and adults born in recent decades. Caesarean section and daycare attendance showed no clear associations with T1D risk; (4) Conclusions: Birth order should be considered in both children and adults' T1D risk assessment for early detection.
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Affiliation(s)
- Justine Tanoey
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Christina Baechle
- Institute for Biometrics and Epidemiology, German Diabetes Center (DDZ), Leibniz Institute for Diabetes Research, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Hermann Brenner
- Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Andreas Deckert
- Heidelberg Institute of Global Health, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Julia Fricke
- Institute of Social Medicine, Epidemiology and Health Economics, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Kathrin Günther
- Leibniz Institute for Prevention Research and Epidemiology—BIPS, 28359 Bremen, Germany
| | - André Karch
- Institute for Epidemiology and Social Medicine, Albert-Schweitzer-Campus 1, Building D3, 48149 Münster, Germany
| | - Thomas Keil
- Institute of Social Medicine, Epidemiology and Health Economics, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
- Institute of Clinical Epidemiology and Biometry, University of Würzburg, 97080 Würzburg, Germany
- State Institute of Health, Bavarian Health and Food Safety Authority, 91058 Erlangen, Germany
| | - Alexander Kluttig
- Institute for Medical Epidemiology, Biometrics and Informatics, Interdisciplinary Center for Health Sciences, Martin Luther University Halle-Wittenberg, 06112 Halle (Saale), Germany
| | - Michael Leitzmann
- Department for Epidemiology and Preventive Medicine, Regensburg University Medical Center, 93053 Regensburg, Germany
| | - Rafael Mikolajczyk
- Institute for Medical Epidemiology, Biometrics and Informatics, Interdisciplinary Center for Health Sciences, Martin Luther University Halle-Wittenberg, 06112 Halle (Saale), Germany
| | - Nadia Obi
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
| | - Tobias Pischon
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Molecular Epidemiology Research Group, 13125 Berlin, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Biobank Technology Platform, 13125 Berlin, Germany
- Charité—Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Tamara Schikowski
- Leibniz Research Institute for Environmental Medicine—IUF, 40225 Düsseldorf, Germany
| | - Sabine M. Schipf
- Institute for Community Medicine, University Medicine Greifswald, 17489 Greifswald, Germany
| | - Matthias B. Schulze
- German Institute of Human Nutrition Potsdam-Rehbruecke, 14558 Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, 14558 Nuthetal, Germany
| | - Anja Sedlmeier
- Department for Epidemiology and Preventive Medicine, Regensburg University Medical Center, 93053 Regensburg, Germany
| | - Ilais Moreno Velásquez
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Molecular Epidemiology Research Group, 13125 Berlin, Germany
| | | | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17489 Greifswald, Germany
| | - Wolfgang Ahrens
- Leibniz Institute for Prevention Research and Epidemiology—BIPS, 28359 Bremen, Germany
| | - Sylvia Gastell
- German Institute of Human Nutrition Potsdam-Rehbruecke, 14558 Nuthetal, Germany
| | - Bernd Holleczek
- Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Karl-Heinz Jöckel
- Institute of Medical Informatics, Biometry und Epidemiology, Essen University Hospital, 45147 Essen, Germany
| | - Verena Katzke
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology, Kiel University, 24105 Kiel, Germany
| | - Karin B. Michels
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, 79110 Freiburg, Germany
| | - Börge Schmidt
- Institute of Medical Informatics, Biometry und Epidemiology, Essen University Hospital, 45147 Essen, Germany
| | - Henning Teismann
- Institute for Epidemiology and Social Medicine, Albert-Schweitzer-Campus 1, Building D3, 48149 Münster, Germany
| | - Heiko Becher
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
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Baruah MP, Ammini AC, Khurana ML. Demographic, breast-feeding, and nutritional trends among children with type 1 diabetes mellitus. Indian J Endocrinol Metab 2011; 15:38-42. [PMID: 21584165 PMCID: PMC3079868 DOI: 10.4103/2230-8210.77583] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND The pathogenesis of type 1 diabetes mellitus (T1DM) requires a genetic predisposition to particular environmental triggers that may activate mechanisms leading to progressive loss of pancreatic beta cells. AIMS We tried to compare the impact of some demographic and environmental factors and breast-feeding on children (aged < 18 years) with recent onset diabetes mellitus (≤1 year) with that on age, sex, and socioeconomic status-matched controls. MATERIAL AND METHODS A total of 43 consecutive patients (male, 24, mean age ± SD = 12.58 ± 9.6 years) and equal number of controls without diabetes mellitus or dysglycemia were included in this hospital-based case-control study. RESULTS AND CONCLUSIONS A distinct peak in the incidence noted in the early adolescence with segregation in the winter months. Our patients did not differ significantly from the controls with regard to birth order, mode of delivery, parental age, parental education, dietary practices, breast-feeding, and migration in the family. Growth characteristics and nutritional status were also similar. A population study with more power will be better equipped to answer such queries.
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Affiliation(s)
- Manash P. Baruah
- Department of Endocrinology, Excel center, Ulubari, Guwahati, Assam-781 007, India
| | - Ariachery C. Ammini
- Department of Endocrinology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi-110 011, India
| | - Madan L. Khurana
- Department of Endocrinology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi-110 011, India
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Sipetić S, Vlajinac H, Kocev N, Radmanović S. [Characteristics and habits of parents of children with insulin-dependent diabetes mellitus]. SRP ARK CELOK LEK 2003; 131:238-43. [PMID: 14692131 DOI: 10.2298/sarh0306238s] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
The aim of this case-control study conducted in Belgrade during 1994-1997 was to investigate whether parental demographic characteristics and habits are associated with insulin-dependent diabetes mellitus (IDDM). Case group comprised 105 children up to 16 years old with IDDM and control group comprised 210 children with skin diseases. Cases and controls were individually matched by age (+/- one year), sex and place of residence (Belgrade). According to chi 2 test results, children with IDDM significantly had five or more family members and they also significantly more frequently had poor socio-economic status than their controls. Higher education of fathers was significantly more frequently reported in diabetic children, in comparison with their controls. Parents of diabetic children were significantly more frequently occupationally exposed to radiation, petroleum, and its derivates, organic solvents, dyes and lacquers. During pregnancy mothers of diabetic children significantly more frequently smoked cigarettes and consumed coffee, coca-cola, alcohol and foods containing nitrosamines. Fathers of diabetic children more frequently consumed alcohol.
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