Literature DB >> 10784243

An indirect estimate of the incidence of non-insulin-dependent diabetes mellitus.

J J Barendregt1, C A Baan, L Bonneux.   

Abstract

Our goal was to estimate non-insulin-dependent diabetes mellitus incidence in the Netherlands in the absence of equivocal empirical data. Incidence can be expressed as a function of age, sex, prevalence, and mortality. We obtained prevalence data from a study that pooled existing prevalence estimates. We calculated diabetes-related mortality using relative risks on all-cause mortality. Sensitivity for the rate of excess mortality was determined using the 95% confidence intervals (95% CI) of the relative risks. The estimated incidence increases exponentially with age, with a doubling time of 10 years for men and 9 years for women. The rate increases from 8.1 per 10,000 (95% CI = 7.7-8.8) for men ages 40-44 years and 7.0 (95% CI = 6.8-8.0) for women to 79.7 per 10,000 (95% CI = 69.5-90.9) for men ages 75-79 years and 85.8 (95% CI = 80.6-91.0) for women. When empirical estimates of incidence are largely lacking, the methodology described offers a useful alternative, in particular for the assessment of potential intervention effects.

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Year:  2000        PMID: 10784243     DOI: 10.1097/00001648-200005000-00008

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  9 in total

1.  Relationship between incidence and prevalence in psychotic disorders: An incidence-prevalence-mortality model.

Authors:  Baptiste Pignon; Franck Schürhoff; Grégoire Baudin; Andrea Tortelli; Aziz Ferchiou; Ghassen Saba; Jean-Romain Richard; Antoine Pelissolo; Marion Leboyer; Andrei Szöke
Journal:  Int J Methods Psychiatr Res       Date:  2018-05-22       Impact factor: 4.035

2.  Modeling and forecasting health expectancy: theoretical framework and application.

Authors:  Istvan M Majer; Ralph Stevens; Wilma J Nusselder; Johan P Mackenbach; Pieter H M van Baal
Journal:  Demography       Date:  2013-04

3.  Forecasting Tunisian type 2 diabetes prevalence to 2027: validation of a simple model.

Authors:  Olfa Saidi; Martin O'Flaherty; Nadia Ben Mansour; Wafa Aissi; Olfa Lassoued; Simon Capewell; Julia A Critchley; Dhafer Malouche; Habiba Ben Romdhane
Journal:  BMC Public Health       Date:  2015-02-07       Impact factor: 3.295

4.  Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities.

Authors:  Patrick Andersen; Anja Mizdrak; Nick Wilson; Anna Davies; Laxman Bablani; Tony Blakely
Journal:  Popul Health Metr       Date:  2022-01-15

5.  Estimating the prevalence of breast cancer using a disease model: data problems and trends.

Authors:  Michelle E Kruijshaar; Jan J Barendregt; Lonneke V Van De Poll-Franse
Journal:  Popul Health Metr       Date:  2003-04-14

6.  PopMod: a longitudinal population model with two interacting disease states.

Authors:  Jeremy A Lauer; Klaus Röhrich; Harald Wirth; Claude Charette; Steve Gribble; Christopher JL Murray
Journal:  Cost Eff Resour Alloc       Date:  2003-02-26

7.  A generic model for the assessment of disease epidemiology: the computational basis of DisMod II.

Authors:  Jan J Barendregt; Gerrit J Van Oortmarssen; Theo Vos; Christopher JL Murray
Journal:  Popul Health Metr       Date:  2003-04-14

8.  Preventing type 2 diabetes among Palestinians: comparing five future policy scenarios.

Authors:  Niveen M E Abu-Rmeileh; Abdullatif Husseini; Simon Capewell; Martin O'Flaherty
Journal:  BMJ Open       Date:  2013-12-20       Impact factor: 2.692

9.  Forecasting future prevalence of type 2 diabetes mellitus in Syria.

Authors:  Radwan Al Ali; Fawaz Mzayek; Samer Rastam; Fouad M Fouad; Martin O'Flaherty; Simon Capewell; Wasim Maziak
Journal:  BMC Public Health       Date:  2013-05-25       Impact factor: 3.295

  9 in total

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