Ethnic differences in diabetes, cardiovascular risk factors and health care: the Amsterdam Health Survey of 2004

The prevalence of diabetes in inhabitants of Amsterdam (18 years and older) is 4%. The prevalence of diabetes is three times higher among Turkish people and four times higher among Moroccans in comparison to Dutch people. Turkish diabetes patients have a higher mean body mass index compared to Dutch diabetes patients, but Turkish and Moroccan diabetes patients are admitted to hospital less often than Dutch diabetes patients. It is important for policy makers to know the differences in disease prevalence and health care use between ethnic groups, considering the expected rise in the proportion of immigrants. These results formed contributions to this report that was brought out by the National Institute for Public Health and the Environment and in cooperation with the Amsterdam Health Monitor of the Amsterdam Health Service. Forty-three percent of the 4042 invited Amsterdam inhabitants participated in the study in 2004. Ethnic differences in health and health care use were analyzed for the age group of 18-70 years, standardized for age and gender. Turkish and Moroccan people without diabetes differed from Dutch people without diabetes on many counts. For example, Turkish and Moroccan people were more often overweight and had higher mean blood glucose levels. They visited their general practitioners more often and experienced their own health as being moderate or poor on a more frequent basis. Turkish people without diabetes experienced more serious cardiac problems than Dutch people. The prevalence of cardiovascular risk factors in diabetes patients was high among all ethnic groups. In general, cardiovascular risk factors were more frequent in Turkish diabetes patients, and to a lesser extent in Moroccan diabetes patients, compared to Dutch diabetes patients. Treatment of cardiovascular risk factors in diabetes patients is important for the prevention of or delay in cardiovascular complications.De prevalentie van diabetes bij inwoners van Amsterdam (18 jaar en ouder) wordt geschat op vier procent. Turken en Marokkanen hebben respectievelijk driemaal en viermaal vaker diabetes vergeleken met Nederlanders. Turkse diabeten zijn gemiddeld zwaarder dan Nederlandse diabeten. Turkse en Marokkaanse diabeten worden echter minder vaak opgenomen in een ziekenhuis dan Nederlandse diabeten. Een beschrijving van etniciteitverschillen in het voorkomen van ziekten en zorggebruik is van belang voor het beleid omdat immigranten een steeds groter deel van de bevolking zullen gaan uitmaken. De Amsterdamse Gezondheidsmonitor 2004 is uitgevoerd door de GGD Amsterdam in samenwerking met het RIVM. Drieenveertig procent van 4042 uitgenodigde Amsterdammers (18 jaar en ouder) heeft aan het onderzoek meegedaan. Etnische verschillen in gezondheid en zorg werden geanalyseerd voor de leeftijd 18-70 jaar, gestandaardiseerd naar leeftijd en geslacht. Turken en Marokkanen zonder diabetes verschilden op bijna alle uitkomsten van Nederlanders zonder diabetes. Turken en Marokkanen waren bijvoorbeeld gemiddeld zwaarder dan Nederlanders en zij hadden hogere gemiddelde bloedglucosewaarden. Zij gingen vaker naar de huisarts en waren minder tevreden over de eigen gezondheid. Acht procent van de Turken zonder diabetes heeft ooit een ernstige hartaandoening gehad, dit is bijna viermaal zo vaak als bij Nederlanders zonder diabetes. Risicofactoren voor hart- en vaatziekten kwamen veel voor bij diabeten uit alle etnische groepen. Turkse diabeten, en in mindere mate Marokkaanse diabeten, hadden over het algemeen een ongunstiger risicoprofiel dan Nederlandse diabeten. Behandeling van het risicoprofiel van diabetespatienten is belangrijk om het optreden van complicaties te voorkomen of uit te stellen

The Sydney Diabetes Prevention Program: A community-based translational study

Background. Type 2 diabetes is a major public health problem in Australia with prevalence increasing in parallel with increasing obesity. Prevention is an essential component of strategies to reduce the diabetes burden. There is strong and consistent evidence from randomised controlled trials that type 2 diabetes can be prevented or delayed through lifestyle modification which improves diet, increases physical activity and achieves weight loss in at risk people. The current challenge is to translate this evidence into routine community settings, determine feasible and effective ways of delivering the intervention and providing on-going support to sustain successful behavioural changes. Methods/Design. The Sydney Diabetes Prevention Program (SDPP) is a translational study which will be conducted in 1,550 participants aged 50-65 years (including 100 indigenous people aged 18 years and older) at high risk of future development of diabetes. Participants will be identified through a screening and recruitment program delivered through primary care and will be offered a community-based lifestyle modification intervention. The intervention comprises an initial individual session and three group sessions based on behaviour change principles and focuses on five goals: 5% weight loss, 210 min/week physical activity (aerobic and strength training exercise), limit dietary fat and saturated fat to less than 30% and 10% of energy intake respectively, and at least 15 g/1000 kcal dietary fibre. This is followed by 3-monthly contact with participants to review progress and offer ongoing lifestyle advice for 12 months. The effectiveness and costs of the program on diabetes-related risk factors will be evaluated. Main outcomes include changes in weight, physical activity, and dietary changes (fat, saturated fat and fibre intake). Secondary outcomes include changes in waist circumference, fasting plasma glucose, blood pressure, lipids, quality of life, psychological well being, medication use and health service utilization. Discussion. This translational study will ascertain the reach, feasibility, effectiveness and cost-effectiveness of a lifestyle modification program delivered in a community setting through primary health care. If demonstrated to be effective, it will result in recommendations for policy change and practical methods for a wider community program for preventing or delaying the onset of type 2 diabetes in high risk people. © 2010 Colagiuri et al; licensee BioMed Central Ltd

Life-threatening infections in children in Europe (the EUCLIDS Project): a prospective cohort study

Background: Sepsis and severe focal infections represent a substantial disease burden in children admitted to hospital. We aimed to understand the burden of disease and outcomes in children with life-threatening bacterial infections in Europe. Methods: The European Union Childhood Life-threatening Infectious Disease Study (EUCLIDS) was a prospective, multicentre, cohort study done in six countries in Europe. Patients aged 1 month to 18 years with sepsis (or suspected sepsis) or severe focal infections, admitted to 98 participating hospitals in the UK, Austria, Germany, Lithuania, Spain, and the Netherlands were prospectively recruited between July 1, 2012, and Dec 31, 2015. To assess disease burden and outcomes, we collected demographic and clinical data using a secured web-based platform and obtained microbiological data using locally available clinical diagnostic procedures. Findings: 2844 patients were recruited and included in the analysis. 1512 (53·2%) of 2841 patients were male and median age was 39·1 months (IQR 12·4–93·9). 1229 (43·2%) patients had sepsis and 1615 (56·8%) had severe focal infections. Patients diagnosed with sepsis had a median age of 27·6 months (IQR 9·0–80·2), whereas those diagnosed with severe focal infections had a median age of 46·5 months (15·8–100·4; p<0·0001). Of 2844 patients in the entire cohort, the main clinical syndromes were pneumonia (511 [18·0%] patients), CNS infection (469 [16·5%]), and skin and soft tissue infection (247 [8·7%]). The causal microorganism was identified in 1359 (47·8%) children, with the most prevalent ones being Neisseria meningitidis (in 259 [9·1%] patients), followed by Staphylococcus aureus (in 222 [7·8%]), Streptococcus pneumoniae (in 219 [7·7%]), and group A streptococcus (in 162 [5·7%]). 1070 (37·6%) patients required admission to a paediatric intensive care unit. Of 2469 patients with outcome data, 57 (2·2%) deaths occurred: seven were in patients with severe focal infections and 50 in those with sepsis. Interpretation: Mortality in children admitted to hospital for sepsis or severe focal infections is low in Europe. The disease burden is mainly in children younger than 5 years and is largely due to vaccine-preventable meningococcal and pneumococcal infections. Despite the availability and application of clinical procedures for microbiological diagnosis, the causative organism remained unidentified in approximately 50% of patients

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics

Modelleren van chronische ziekten: de diabetes module. Verantwoording van (nieuwe) invoer

Om effecten van verschillende preventieve maatregelen voor diabetes te kunnen berekenen, is het RIVM Chronische Ziekten Model geactualiseerd en aangepast. Het Chronische Ziekten Model is een instrument om effecten van veranderingen in het voorkomen van risicofactoren, bijvoorbeeld overgewicht en roken, voor chronische ziekten (o.a. hart- en vaatziekten) te schatten op ziektelast en sterfte. Dit rapport geeft de verantwoording van de nieuwe diabetesmodule in dit model. Met deze diabetesmodule kunnen zowel primaire preventiestrategieen als maatregelen in de zorg (=betere behandeling van diabetes en cardiovasculaire risicofactoren) worden doorgerekend en het effect op de volksgezondheid worden geschat. Dit geeft beleidsmakers en zorgverleners inzicht in hoeveel gezondheidswinst er te behalen zou zijn door preventie en het kan ondersteunen bij het prioriteren van verschillende preventiestrategieen. Alle diabetes-gerelateerde informatie in het Chronische Ziekten Model is geactualiseerd. Roken is toegevoegd als risicofactor voor diabetes. HbA1c (een maat voor het bloedglucose niveau) is toegevoegd als risicofactor voor cardiovasculaire complicaties. Nieuwe modelgegevens bij patienten met diabetes zijn het voorkomen van cardiovasculaire complicaties, het voorkomen van cardiovasculaire risicofactoren (HbA1c, hoge bloeddruk, roken, cholesterol en overgewicht) en de relaties tussen deze risicofactoren en het ontstaan van cardiovasculaire complicaties.The RIVM chronic disease model (CDM) is an instrument designed to estimate the effects of changes in the prevalence of risk factors for chronic diseases on disease burden and mortality. To enable the computation of the effects of various diabetes prevention scenarios, the CDM has been updated and adapted. The present report presents a justification of the new diabetes module and the data used. The diabetes module allows the computation of both primary prevention scenarios and care scenarios (i.e. treatment of diabetes and cardiovascular risk factors) and the assessment of the effect on public health. The outcome provides policy makers and health professionals with insight into the potential prevention-associated health gain and may aid them in prioritising prevention scenarios. All diabetes-related information in the CDM has been updated. Smoking has been added as a risk factor for diabetes. HbA1c (a measure of blood glucose level) has been added as a risk factor for cardiovascular complications. New model data regarding patients with diabetes include the prevalence of cardiovascular complications, the prevalence of cardiovascular risk factors (HbA1c, high blood pressure, smoking, cholesterol and overweight) and the relationships between these risk factors and the development of cardiovascular complications. The literature shows that in trials focusing on the prevention of diabetes, the diabetes incidence drops by 60%. Trials focusing on improved treatment of diabetes patients show that the incidence of cardiovascular diseases falls by 25-50%, depending on the type of treatment and research setting.VW

Modelleren van chronische ziekten: de diabetes module. Verantwoording van (nieuwe) invoer

The RIVM chronic disease model (CDM) is an instrument designed to estimate the effects of changes in the prevalence of risk factors for chronic diseases on disease burden and mortality. To enable the computation of the effects of various diabetes prevention scenarios, the CDM has been updated and adapted. The present report presents a justification of the new diabetes module and the data used. The diabetes module allows the computation of both primary prevention scenarios and care scenarios (i.e. treatment of diabetes and cardiovascular risk factors) and the assessment of the effect on public health. The outcome provides policy makers and health professionals with insight into the potential prevention-associated health gain and may aid them in prioritising prevention scenarios. All diabetes-related information in the CDM has been updated. Smoking has been added as a risk factor for diabetes. HbA1c (a measure of blood glucose level) has been added as a risk factor for cardiovascular complications. New model data regarding patients with diabetes include the prevalence of cardiovascular complications, the prevalence of cardiovascular risk factors (HbA1c, high blood pressure, smoking, cholesterol and overweight) and the relationships between these risk factors and the development of cardiovascular complications. The literature shows that in trials focusing on the prevention of diabetes, the diabetes incidence drops by 60%. Trials focusing on improved treatment of diabetes patients show that the incidence of cardiovascular diseases falls by 25-50%, depending on the type of treatment and research setting.Om effecten van verschillende preventieve maatregelen voor diabetes te kunnen berekenen, is het RIVM Chronische Ziekten Model geactualiseerd en aangepast. Het Chronische Ziekten Model is een instrument om effecten van veranderingen in het voorkomen van risicofactoren, bijvoorbeeld overgewicht en roken, voor chronische ziekten (o.a. hart- en vaatziekten) te schatten op ziektelast en sterfte. Dit rapport geeft de verantwoording van de nieuwe diabetesmodule in dit model. Met deze diabetesmodule kunnen zowel primaire preventiestrategieen als maatregelen in de zorg (=betere behandeling van diabetes en cardiovasculaire risicofactoren) worden doorgerekend en het effect op de volksgezondheid worden geschat. Dit geeft beleidsmakers en zorgverleners inzicht in hoeveel gezondheidswinst er te behalen zou zijn door preventie en het kan ondersteunen bij het prioriteren van verschillende preventiestrategieen. Alle diabetes-gerelateerde informatie in het Chronische Ziekten Model is geactualiseerd. Roken is toegevoegd als risicofactor voor diabetes. HbA1c (een maat voor het bloedglucose niveau) is toegevoegd als risicofactor voor cardiovasculaire complicaties. Nieuwe modelgegevens bij patiknten met diabetes zijn het voorkomen van cardiovasculaire complicaties, het voorkomen van cardiovasculaire risicofactoren (HbA1c, hoge bloeddruk, roken, cholesterol en overgewicht) en de relaties tussen deze risicofactoren en het ontstaan van cardiovasculaire complicaties

Productivity costs of smoking for Dutch employers in 1999

In opdracht van de ministeries van VWS en EZ, worden de door roken veroorzaakte productiviteitskosten voor Nederlandse werkgevers in 1999 geschat. Berekend wordt de waarde van het productieverlies (=productiviteitskosten) als gevolg van -aan roken toe te schrijven- ziekteverzuim, arbeidsongeschiktheid en overlijden van werk-nemers. Niet berekend worden kosten als gevolg van productieverlies door rookpauzes onder werktijd of vervroegde uittreding van rokers, omdat hierover geen betrouwbare gegevens beschikbaar zijn. Kosten van een speciale indeling van gebouwen (rookruimten) en kosten van afval en brand door roken, vallen buiten het bestek van dit onderzoek. Vanuit de internationale literatuur zijn de relatieve risico's op overlijden voor rokers ten opzichte van niet-rokers aan kanker, hart- en vaatziekten en ademhalingsziekten bekend. Het - aan roken toe te schrijven - productieverlies in Nederland werd berekend, gebruikmakend van deze internationale kennis in combinatie met nationale ziektespecifieke gegevens over ziekteverzuim, arbeidsongeschiktheid en sterfte. Omdat werknemers kunnen worden vervangen, blijft het productieverlies beperkt tot de periode van afwezigheid tot vervanging, de frictieperiode. We zijn uitgegaan van een frictieperiode van zes maanden. In een vergelijkende analyse hebben we de - aan roken toe te schrijven - kosten geschat op basis van directe werkgeverskosten bij afwezigheid van werknemers zoals loonkosten, wervings- en vervangingskosten, overlijdensuitkeringen en verhogingen van verzekeringspremies. In 1999 konden naar schatting 1,9% van de ziekteverzuimdagen, 3,3% van de nieuwe arbeidsongeschiktheidsuitkeringen en 22% van de sterfgevallen onder werknemers, aan roken worden toegeschreven. De hiermee gepaard gaande kosten voor werkgevers werden geschat op 305 miljoen Euro, ofwel 105 Euro per rokende werknemer. De analyse gebaseerd op directe werkgeverskosten resulteerde in een vergelijkbare schatting (met beide methoden werden dezelfde kosten geschat, de productiviteitskosten en directe kosten mogen dus niet worden opgeteld). Als een werknemer met roken stopt, levert dit voor de werkgever een besparing op van 27 Euro per jaar op de korte termijn. Dit komt doordat de negatieve gezondheidseffecten van het roken niet van de ene op de andere dag verdwijnen. De gemaakte schattingen zijn conservatief mede omdat niet alle roken-gerelateerde ziekten in de berekeningen zijn meegenomen. Ook werden er geen kosten toegeschreven aan passief roken. We concluderen dat er, naast het bevorderen van de gezondheid, voor werkgevers ook economische redenen kunnen zijn om het roken te ontmoedigen.The productivity costs to Dutch employers attributable to smoking are estimated here for 1999. Included are productivity costs (value of lost production) due to absenteeism, and disability and death of employees due to smoking. Costs associated with smoking breaks during working hours or early retirement were not included due to lacking data. Costs connected with a special organisation of the space in buildings, and garbage or fire due to smoking fall outside the scope of this report. Production loss due to smoking was estimated on the basis of published information on disease-specific relative risks of death applicable to smokers, as compared to non smokers, combined with national disease-specific data on absenteeism, disability and deaths. Considering that employees can be replaced, production loss is restricted to the period from absence to replacement, the friction period. In the primary analysis in this report we estimated productivity costs, assuming a friction period of 6 months. In a comparative analysis we estimated the same costs with a different method, where the estimate was based on direct costs to employers such as salary payment, costs for replacement, death benefits and increased insurance contributions, resulting from employee absence. In 1999, 1.9% absenteeism, 3.3% new disability and 22% deaths among employees could be attributed to smoking. The associated costs were estimated at 305 million Euro or 105 Euro per employed smoker. The estimate based on direct costs to the employer was comparable (both methods estimate the same costs, so the productivity costs and direct costs should not be added up). Considering that health hazards of smoking do not disappear immediately after stopping, the employer saves 27 Euro per year in the short term on an employee who stops smoking. The estimates are conservative because not all smoking-related diseases are included in the calculations. Furthermore, no costs were attributed to passive smoking. Apart from pointing out the advantages to health, employers can also promote a smoking stop for economic reasons.VWSE