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The case of diabetes in the Netherlands Kath Bennett 19 th Jan 2009.

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Presentation on theme: "The case of diabetes in the Netherlands Kath Bennett 19 th Jan 2009."— Presentation transcript:

1 The case of diabetes in the Netherlands Kath Bennett 19 th Jan 2009

2 Data sources General sources of data for diabetes in EUROPE –Diabetes ATLAS –EUCID project –Global Burden of disease project 2000 (Wild et al ). Table 3.1 gives table of prevalence data for all countries including Netherlands. (Mooy et al HOORN study, Diabetes care 1995;18- Old data) Incidence data less widely available according to GBD 2000.

3 EUCID Project The aim of the European Core Indicators in Diabetes (EUCID) project is to collect and compare data about risk factors for diabetes, complications and quality of care indicators in EU countries or future member states. 19 countries provided data for a list of indicators by age band which were representative at a regional or a national level for 2004, 2005 or 2006. The indicators for this project were designed during the EUropean Diabetes Indicators Project - EUDIP. Data were age- standardized for comparisons performed in the general population. Recently EUCID's final report was published at the DG SANCO website.EUCID's final report www.eucid.eu

4 The final list of collaborating institutes of the contract Country Organisation AustriaUniversitätsklinik für Kinder- und Jugendheilkunde Belgium Scientific Institute of Public Health, WIV-ISP Brussels Cyprus Ministry of Health, Health Monitoring Unit Denmark Danish Diabetes Database England Yorkshire and Humber Public Health Observatory, University of York Finland KTL, National Public Health Institute France Institut de Veille Sanitaire Germany Hospital GK Havelhoehe Greece Hippocrateion Hospital Ireland The Adelaide & Meath Hospital Italy Associazione Medice Diabetologi LuxembourgCentre Hospitalier de Luxembourg PortugalDireccão-General da Saúde, Ministerio da Saude RomaniaInstitute of Diabetes N. Paulescu Scotland University of Dundee, Ninewells Hospital and Medical School Spain Consejería Salud, Delegacíon Provincial de Málaga Sweden NEPI Foundation Netherlands Dutch Institute of Health Care Improvement CBO Turkey Turkish Diabetes Foundation

5 Data selection Both incidence and prevalence from same data source Most recent data at the time (year 2003, but 2004 has since become available Dec 2008) As representative of the population as possible (national) Registries recording all patients

6 Particular problems with diabetes Under-reporting of diabetes as cause of death on death cerificates Those with diabetes often die of CVD

7 Mortality data - Diabetes Numbers of deaths caused by diabetes from Statistics NL database for 2006. Denominators (pop 2006) provided by Wilma (statline CBS NL). Calculated rates from the dividing number of deaths by population. Same as numbers of deaths from WHO HFA for 2006

8 Prevalence/incidence - Diabetes Literature identified different sources of data: HOORN study in elderly (50-74 yrs); 8.30% (Mooy et al) Rotterdam study (55+ years); 11.30% (Stock et al) Different registries: CMR Nijmegen (I/P, Nijmegen, available since 1971) RNH Limburg (I/P, Limburg region, 1998 on) Transition project (Incidence, multi-region 85-95) Often both types of diabetes combined as not possible to distinguish. Sources from report by Hoogeveen et al RIVM March 2000,

9 Prevalence - diabetes Other studies – Zodiac-I

10 Using DISMOD Prevalence, incidence and cause-specific data entered into MS access (as for GBD2000) as input tables Import data into DISMOD II. Population data and all-cause mortality data imported into DISMOD II. Smooth input Incidence and prevalence data within DISMOD and then calculate output estimates. Apply age at one year intervals and also to saved tables from output.

11 Outputs from DISMOD

12 Mortality- DM calculated and reported

13 Different approaches GBD 2000 Smooth incidence and prevalence curves generated within DISMOD. Hoogeveen 2000: Smooths data first and interpolate over age before estimating model parameters. Uses penalty functions for smoothing with smoothing coefficients specified for each disease, in this case 0.5).

14 Suggestions Different smoothing approaches Consistency with other data sources, existing evidence (age patterns, gender differences)? Approach/source similar for other member states? –Can apply similar approach –WHO HFA combined source for mortality, not the case for morbidity –? Link with EUCID project for consistent approach?


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