AGE MODE: een leeftijdsafhankelijk model voor toetsing van de inneming van voedingsstoffen; geillustreerd voor foliumzuur en vitamine A

Dit rapport beschrijft de werking van het model AGE MODE. AGE MODE is een methode om de gebruikelijke inneming van microvoedingsstoffen, vitaminen en mineralen, te schatten en te toetsen aan de voedingsnorm. AGE MODE is ontwikkeld door het RIVM. AGE MODE is een kwantitatieve methode om de voorziening van microvoedingsstoffen te beoordelen. Het kan gebruikt worden om prioriteiten te stellen in beleid dat gericht is op een adequate voedingsstoffenvoorziening voor de bevolking. Het model schat de gebruikelijke inneming van microvoedingsstoffen uit inneminggegevens afkomstig uit voedselconsumptiepeilingen en zet deze af tegen de behoefte aan dergelijke microvoedingsstoffen. Zo kan het percentage individuen voor wie de voorziening onder de voedingsnorm is, worden bepaald. AGE MODE heeft een aantal voordelen ten opzichte van bestaande methoden. Het is een leeftijdsafhankelijk model. Bovendien is het een transparant model, waardoor goed inzicht kan worden gekregen in de onderliggende gegevens. Ter illustratie is AGE MODE gebruikt om een schatting te maken van de gebruikelijke inneming van foliumzuur en vitamine A en dit te vergelijken met de voedingsnormen.The 'Age dependent dietary evaluation model' (AGE MODE), described and demonstrated in this report, allows one to estimate usual intakes of micronutrients and to evaluate these intakes in relation to requirements. A quantitative evaluation of micronutrient intakes is warranted for setting policy priorities and determining the need for political measures. Habitual micronutrient intakes are estimated using AGE MODE from short-term measurements, and the prevalence of inadequate intakes is obtained by relating habitual intakes to requirements. AGE MODE has several advantages above currently used methods. Most important is the feature of age dependency. Furthermore, the model is transparent, which provides insight into the data. As case-study, AGE MODE is used to estimate the habitual intake of folate and vitamin A and to compare this to the dietary reference intakes

Quantifying health effects of nutrition

Modelsimulaties geven aan dat met een grotere consumptie van fruit, groente en vis veel gezondheidswinst te behalen is. Dit soort schattingen kunnen worden gebruikt bij de onderbouwing van het voedingsbeleid. Met behulp van het Chronische-Ziekten-Model (CZM) van het RIVM kunnen de gezondheidseffecten op de langere termijn en zorggerelateerde kosten van beleidsdoelstellingen en voedingsinterventies worden doorgerekend. De modelsimulaties geven aan dat met een verhoging van de consumptie van groenten, fruit en vis relatief veel gezondheidswinst te behalen is. Ook blijkt dat ten aanzien van de vetzuursamenstelling de meeste gezondheidswinst inmiddels al is bereikt. Als de gehele Nederlandse bevolking de aanbevelingen voor gezonde voeding zou naleven, overlijden de komende twintig jaar naar schatting 140.000 minder mensen. De totale zorgkosten die anders in 20 jaar worden uitgegeven verminderen dan ongeveer met 3%. Doordat mensen langer leven zullen in de daaropvolgende jaren hun zorgkosten wel toenemen. Het model is ook gebruikt voor doorrekening van twee concrete voedingsinterventies, te weten SchoolGruiten en Werkfruit. Een kind dat deelneemt aan SchoolGruiten zal gemiddeld langer leven (+0,37 jaar) en ook langer gezond blijven. Er worden minder medische kosten op jongere leeftijd gemaakt. Deze kosten worden echter voor een groot deel uitgesteld. Voorwaarde voor de gunstige effecten is dat kinderen na de basisschool structureel meer groenten en fruit blijven eten. Werkfruit is een interventie die zich richt op de fruitconsumptie van werknemers in Nederland. Wanneer dit wordt ingevoerd bij 1 op de 10 werknemers, stijgt naar verwachting de levensverwachting van een 20-jarige met 0,08 jaar en nemen de gezondheidszorgkosten met 0,2 procent af.Simulations show that with an elevation of fruit, vegetable and fish consumption large health gains can be achieved. Model simulation is a good method to underpin nutritional policy. The RIVM Chronic Disease Model (CZM) can be used to calculate long term health effects and health care related costs of policy targets and dietary interventions. Simulations show that with an elevation of fruit, vegetable and fish consumption large health gains can be achieved. On the other hand, most health benefits related to fatty acids composition are already achieved. If the Dutch population complies with the dietary recommendations on nutrition, in 20 years, about 140,000 deaths and about 3% of the costs of health care will be saved. As the life expectancy increases people will experience health costs later in life. Two dietary interventions, 'SchoolGruiten' and 'Werkfruit' are simulated within CZM. Children participating in 'SchoolGruiten' will see their life expectancy increased (+0.37 year). They will also, on average, stay healthy for a longer time, assuming long term effects of the intervention. In this way such a child will make less medical costs at a younger age, however most of this costs are only postponed. Introducing 'Werkfruit' in the Netherlands onto one out of 10 employers, will increase the life expectancy of an 20-year old by an estimated 0.08 year and decrease the health-related costs of the whole population with 0.2 percent

The impact of life tables adjusted for smoking on the socio-economic difference in net survival for laryngeal and lung cancer.

BACKGROUND: Net survival is a key measure in cancer control, but estimates for cancers that are strongly associated with smoking may be biased. General population life tables represent background mortality in net survival, but may not adequately reflect the higher mortality experienced by smokers. METHODS: Life tables adjusted for smoking were developed, and their impact on net survival and inequalities in net survival for laryngeal and lung cancers was examined. RESULTS: The 5-year net survival estimated with smoking-adjusted life tables was consistently higher than the survival estimated with unadjusted life tables: 7% higher for laryngeal cancer and 1.5% higher for lung cancer. The impact of using smoking-adjusted life tables was more pronounced in affluent patients; the deprivation gap in 5-year net survival for laryngeal cancer widened by 3%, from 11% to 14%. CONCLUSIONS: Using smoking-adjusted life tables to estimate net survival has only a small impact on the deprivation gap in survival, even when inequalities are substantial. Adjusting for the higher, smoking-related background mortality did increase the estimates of net survival for all deprivation groups, and may be more important when measuring the public health impact of differences or changes in survival, such as avoidable deaths or crude probabilities of death

The development of socio-economic health differences in childhood: results of the Dutch longitudinal PIAMA birth cohort

Background: People with higher socio-economic status (SES) are generally in better health. Less is known about when these socio-economic health differences set in during childhood and how they develop over time. The goal of this study was to prospectively study the development of socio-economic health differences in the Netherlands, and to investigate possible explanations for socio-economic variation in childhood health. Methods: Data from the Dutch Prevention and Incidence of Asthma and Mite Allergy (PIAMA) birth cohort study were used for the analyses. The PIAMA study followed 3,963 Dutch children during their first eight years of life. Common childhood health problems (i.e. eczema, asthma symptoms, general health, frequent respiratory infections, overweight, and obesity) were assessed annually using questionnaires. Maternal educational level was used to indicate SES. Possible explanatory lifestyle determinants (breastfeeding, smoking during pregnancy, smoking during the first three months, and day-care centre attendance) and biological determinants (maternal age at birth, birthweight, and older siblings) were analysed using generalized estimating equations. Results: This study shows that socio-economic differences in a broad range of health problems are already present early in life, and persist during childhood. Children from families with low socio-economic backgrounds experience more asthma symptoms (odds ratio (OR) 1.27; 95% Confidence Interval (CI) 1.08-1.49), poorer general health (OR 1.36; 95% CI 1.16-1.60), more frequent respiratory infections (OR 1.57; 95% CI 1.35-1.83), more overweight (OR 1.42; 95% CI 1.16-1.73), and more obesity (OR 2.82; 95% CI 1.80-4.41). The most important contributors to the observed childhood socio-economic health disparities are socio-economic differences in maternal age at birth, breastfeeding, and day-care centre attendance. Conclusions: Socio-economic health disparities already occur very early in life. Socio-economic disadvantage takes its toll on child health before birth, and continues to do so during childhood. Therefore, action to reduce health disparities needs to start very early in life, and should also address socio-economic differences in maternal age at birth, breastfeeding habits, and day-care centre attendance

Comparing estimates of influenza-associated hospitalization and death among adults with congestive heart failure based on how influenza season is defined

<p>Abstract</p> <p>Background</p> <p>There is little consensus about how the influenza season should be defined in studies that assess influenza-attributable risk. The objective of this study was to compare estimates of influenza-associated risk in a defined clinical population using four different methods of defining the influenza season.</p> <p>Methods</p> <p>Using the Studies of Left Ventricular Dysfunction (SOLVD) clinical database and national influenza surveillance data from 1986–87 to 1990–91, four definitions were used to assess influenza-associated risk: (a) three-week moving average of positive influenza isolates is at least 5%, (b) three-week moving average of positive influenza isolates is at least 10%, (c) first and last positive influenza isolate are identified, and (d) 5% of total number of positive isolates for the season are obtained. The clinical data were from adults aged 21 to 80 with physician-diagnosed congestive heart failure. All-cause hospitalization and all-cause mortality during the influenza seasons and non-influenza seasons were compared using four definitions of the influenza season. Incidence analyses and Cox regression were used to assess the effect of exposure to influenza season on all-cause hospitalization and death using all four definitions.</p> <p>Results</p> <p>There was a higher risk of hospitalization associated with the influenza season, regardless of how the start and stop of the influenza season was defined. The adjusted risk of hospitalization was 8 to 10 percent higher during the influenza season compared to the non-influenza season when the different definitions were used. However, exposure to influenza was not consistently associated with higher risk of death when all definitions were used. When the 5% moving average and first/last positive isolate definitions were used, exposure to influenza was associated with a higher risk of death compared to non-exposure in this clinical population (adjusted hazard ratios [HR], 1.16; 95% confidence interval [CI], 1.04 to 1.29 and adjusted HR, 1.19; 95% CI, 1.06 to 1.33, respectively).</p> <p>Conclusion</p> <p>Estimates of influenza-attributable risk may vary depending on how influenza season is defined and the outcome being assessed.</p