http://repub.eur.nl/res/aut/4870/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/23315/ 2011-02-17T00:00:00Z Introduction: Lower social class has higher lung cancer incidence, largely attributable to higher smoking prevalence among the lower social classes. We assessed the magnitude and time dimension of potential impact of targeted interventions on smoking on socioeconomic inequalities in lung cancer. Methods: Using population dynamic modelling, we projected lung cancer incidence up to 2050 in lowest and highest socioeconomic groups under two intervention scenarios (annual 10% increase in cigarette prices and health advertisement) and compared this to a scenario of no intervention. For the analysis we retrieved smoking prevalence data from the General Household Survey of England and Wales between 1980 and 2006 and cancer incidence data from the national cancer registry. Results: By 2050, the model projected that lung cancer incidence inequality would almost double (Incidence Rate Ratio (IRR) = 4.2 in 2050 vs. 2.5 in 2005) in men and slightly decrease (IRR = 2.4 in 2050 vs. 2.7 in 2005) in women compared to what was observed in 2005. If annual increase in cigarette price targeting the lowest socioeconomic group was implemented, socioeconomic inequality in lung cancer incidence in 2050 might be largely reduced (IRR = 1.5 and 1.4 among men and women, respectively). If in addition to annual price increase (targeted to the lowest socioeconomic group) health advertisement was implemented and successfully reduced smoking prevalence in the highest socioeconomic group, the lung cancer gap between the socioeconomic groups would be reduced by 78% and 58% in men and women by 2050. Conclusion: Even under the best scenarios, inequality in lung cancer was not fully eliminated within 45 years period. Though the process is lengthy, rigorous interventions may reduce the expected widening of the future inequalities in lung cancer. Modelling exercise such as ours relies heavily on the quality of the input data and the assumptions, thus caution is needed in interpretation of our findings and should consider all the assumptions taken in the analysis. http://repub.eur.nl/res/pub/21996/ 2010-09-01T00:00:00Z Background: Across Europe, there are over 300,000 new cases of colorectal cancer annually. Major risk factors include excess body weight (usually expressed by a high body mass index, BMI) and physical inactivity (PA). In this study we modeled the potential long-term effects on colon cancer incidence of changes in prevalence of excess body weight and physical inactivity in 7 European countries across Europe with adequate data. Methods: We addressed the impact of interventions aimed at preventing weight gain and increasing physical activity on colon cancer incidence using the Prevent model as refined in the FP-6 Eurocadet project. Relative risk (RR) estimates were derived from meta-analyses; sex- and country-specific prevalences of BMI and PA were determined from survey data. Models were made for Czech Republic, Denmark, France, Latvia, the Netherlands, Spain and the United Kingdom. Results: In a hypothetical scenario in which a whole population had obtained an ideal weight distribution in the year 2009, up to 11 new cases per 100,000 person-years would be avoided by 2040. The population attributable fractions (PAF) for excess weight were much higher for males (between 13.5% and 18.2%) than for females (2.3%-4.6%). In contrast, using the optimum scenario where everybody in Europe would adhere to the recommended guideline of at least 30 minutes of moderate PA 5 days per week, the PAFs for PA in various countries were substantially greater in women (4.4% - 21.2%) than in men (3.2%-11.6%). Sensitivity analyses were performed assuming underreporting of BMI by using self-reports (difference of 5 and 0.8 percent-points in males and females, respectively), using different risk estimates (between 5.8 and 11.5 percent-points difference for BMI for men and women, respectively, and up to 11.6 percent-points difference for PA for women). Interpretation: Changes in lifestyle can indeed result in large health benefits, including for colon cancer. Two interesting patterns emerged: for colon cancer, achieving optimum BMI levels in the population appears to offer greatest health benefits in population attributable fractions in males, while increased physical activity might offer the greatest fraction of avoidable cancers in females. These observations suggest a sex-specific strategy to colon cancer prevention. http://repub.eur.nl/res/pub/21999/ 2010-09-01T00:00:00Z Background: Across Europe, there are over 300,000 new cases of colorectal cancer annually. Major risk factors include excess body weight (usually expressed by a high body mass index, BMI) and physical inactivity (PA). In this study we modeled the potential long-term effects on colon cancer incidence of changes in prevalence of excess body weight and physical inactivity in 7 European countries across Europe with adequate data. Methods: We addressed the impact of interventions aimed at preventing weight gain and increasing physical activity on colon cancer incidence using the Prevent model as refined in the FP-6 Eurocadet project. Relative risk (RR) estimates were derived from meta-analyses; sex- and country-specific prevalences of BMI and PA were determined from survey data. Models were made for Czech Republic, Denmark, France, Latvia, the Netherlands, Spain and the United Kingdom. Results: In a hypothetical scenario in which a whole population had obtained an ideal weight distribution in the year 2009, up to 11 new cases per 100,000 person-years would be avoided by 2040. The population attributable fractions (PAF) for excess weight were much higher for males (between 13.5% and 18.2%) than for females (2.3%-4.6%). In contrast, using the optimum scenario where everybody in Europe would adhere to the recommended guideline of at least 30 minutes of moderate PA 5 days per week, the PAFs for PA in various countries were substantially greater in women (4.4% - 21.2%) than in men (3.2%-11.6%). Sensitivity analyses were performed assuming underreporting of BMI by using self-reports (difference of 5 and 0.8 percent-points in males and females, respectively), using different risk estimates (between 5.8 and 11.5 percent-points difference for BMI for men and women, respectively, and up to 11.6 percent-points difference for PA for women). Interpretation: Changes in lifestyle can indeed result in large health benefits, including for colon cancer. Two interesting patterns emerged: for colon cancer, achieving optimum BMI levels in the population appears to offer greatest health benefits in population attributable fractions in males, while increased physical activity might offer the greatest fraction of avoidable cancers in females. These observations suggest a sex-specific strategy to colon cancer prevention. http://repub.eur.nl/res/pub/28192/ 2010-09-01T00:00:00Z Cancer is one of the major causes of death in western countries. Fruit and vegetable consumption may reduce the risk of cancers of the oropharynx, oesophagus, lung, stomach and colorectum. We investigated the potential effect of interventions aimed at increasing the intake of fruits and vegetables to the recommended level (500 g/d) on future cancer incidence in Europe. Data on cancer incidence and daily intake of fruit and vegetables were compiled for France, Germany, The Netherlands, Spain and Sweden. We also performed a meta-analysis of European observational studies to arrive at a quantitative estimate on the association between fruit and vegetable intake and cancer risk. Predictions on the future cancer incidence were modelled using PREVENT 3.01. Our study predicted 212,000 fruit-and vegetable-related cancer cases in these countries in 2050, out of which 398 (0.19%) might be prevented if the 500 g/d fruit and vegetable intake were achieved in the aforementioned countries. The largest absolute impact was observed for lung cancer with 257 (out of 136,517) preventable cases if the intervention was successfully implemented. Sweden would benefit the most from intervention to increase fruit and vegetable consumption with a 2% reduction in expected cases. Increasing fruit and vegetable consumption has a small impact on reducing the burden of cancer in Europe. Health impact assessment tools such as PREVENT can provide the basis for decision making in chronic disease prevention. http://repub.eur.nl/res/pub/28198/ 2010-09-01T00:00:00Z Purpose: Among the known risk factors, smoking is clearly related to the incidence of lung cancer and alcohol consumption is to breast cancer. In this manuscript we modelled the potential benefits of reductions in smoking or alcohol prevalence for the burden of these cancers. Method: We used Prevent v.3.01 to assess the changes in incidence as a result of risk factor changes. Incidence of lung and breast cancer until 2050 was predicted under two scenarios: ideal (total elimination of smoking and reduction of alcohol intake to maximum 1 units/d for women) and optimistic (decreasing prevalence of risk factors because of a 10% increase in cigarette and alcohol beverage price, repeated every 5 years). Danish data from the household surveys, cancer registration and Eurostat were used. Results: Up to 49% less new lung cancer cases can be expected in 2050 if smoking were to be completely eliminated. Five-yearly 10% price increases may prevent 521 new lung cancer cases in 2050 (21% less cases). An intervention that immediately reduces population alcohol consumption to the recommended level (below 12 g/d) may lower breast cancer by 7%, preventing 445 out of the 6060 expected new cases in 2050. Five-yearly 10% price increases in alcoholic beverages achieved a reduction of half as expected by the ideal scenario, i.e. 4% (262) preventable cases in 2050. Conclusions: The future burden of lung and breast cancer could be markedly reduced by intervening in their risk factors. Prevent illustrates the benefit of interventions and may serve as guidance in political decision-making. http://repub.eur.nl/res/pub/28220/ 2010-09-01T00:00:00Z Objective: To model future trends in lung cancer incidence in Denmark by education under different scenarios for cigarette smoking. Methods: Lung cancer incidence until 2050 was modelled using Prevent software. We estimated lung cancer incidence under a baseline scenario and under four alternative scenarios for smoking reduction: decreasing initiation rates among the young, increasing cessation rates among smokers, a scenario combining both changes and a levelling-up scenario in which people with low and medium levels of education acquired the smoking prevalence of the highly educated. Danish National Health Interview Surveys (1987-2005) and cancer registry data combined with individual education status from Statistics Denmark were used for empirical input. Results: Under the baseline scenario, lung cancer rates are expected to decrease for most educational groups during the next few decades, but educational inequalities will increase further. Under the alternative scenarios, an additional decrease in lung cancer rates will be observed from 2030 onwards, but only from 2050 onwards it will be observed under the initiation scenario. The cessation and the combined scenarios show the largest decrease in lung cancer rates for all educational groups. However, in none of these scenarios would the relative differences between educational groups be reduced. A modest decrease in these inequalities will be observed under the levelling-up scenario. Discussion: Our analyses show that relative inequalities in lung cancer incidence rates will tend to increase. They may be reduced to a small extent if the smoking prevalence of people with a low level of education was to converge towards those more highly educated people. An important decrease in lung cancer rates will be observed in all educational groups, however, especially when focusing on both initiation and cessation strategies. http://repub.eur.nl/res/pub/37141/ 2007-10-31T00:00:00Z Objective: Obesity is a growing problem worldwide, but there are no good methods to assess the future course of the epidemic and the potential influence of interventions. We explore the behavior change needed to stop the obesity epidemic in the U.S. Research Methods and Procedures: We modeled the population distribution of BMI as a log-normal curve of which the mean shifts upward with time due to a positive population energy balance. Interventions that decrease food intake or increase physical activity result in more favorable trends in BMI. Results: The recently observed trend in average BMI implies that the average U.S. adult over-consumes by ∼10 kcal/d. If this trend continues unaltered, obesity prevalence will exceed 40% for men and 45% for women in 2015. To stop the epidemic, it suffices to decrease caloric consumption by ∼10 kcal or walk an extra 2 to 3 minutes per day, on average. Discussion: This leads to a paradox: little behavior change seems sufficient to halt the epidemic, but in practice this proves hard to achieve. The obesogenic environment is the likely culprit. Individuals trying to maintain a healthy weight need to be supported by environments that stimulate physical activity and do not encourage over-consumption. Research should show what measures are effective. Copyright http://repub.eur.nl/res/pub/36733/ 2007-09-01T00:00:00Z Background: Cardiovascular risk management guidelines are 'risk based'; health economists' practice is 'time based'. The 'medical' risk-based allocation model maximises numbers of deaths prevented by targeting subjects at high risk, for example, elderly and smokers. The time-based model maximises numbers of life years gained by treating the young and non-smokers, or 'the one who has will be given more' (Matthew 25:29). We explored practical consequences of risk- or time-based allocation. Methods: We used epidemiological modelling to generate semi-quantitative scenarios comparing the distributional effects of allocating a fixed number of prescriptions of a (hypothetical) preventive cardiovascular drug ('CVStop') either to avert the maximum number of deaths (risk-based) or to save the maximum number of life years (time based) in the male Dutch population. We subsequently asked 123 Dutch guideline developers which distribution they preferred. Results: Time- and risk-based allocations resulted in different distributions of the drug across the population. There were also differences in absolute numbers of life years gained and deaths averted, and in the distribution of these across the population. For example, risk-based allocation of 'CVStop' resulted in preferential treatment of elderly, leading to more deaths averted (mostly among 70 and above) but fewer life years gained, if compared with time-based allocation. The guideline developers experienced the choice dilemmas as difficult. No priority choice was dominant among the respondents. Conclusion: In evidence-based resource allocation the choice to save time or to avert deaths may introduce moral choices because of the various origins of increased disease risk. Evidence-based guideline development inevitably has moral implications. http://repub.eur.nl/res/pub/36912/ 2007-05-23T00:00:00Z Background. The effects of socio-demographic characteristics of the respondent, including age, on valuation scores of hypothetical health states remain inconclusive. Therefore, we analyzed data from a study designed to discriminate between the effects of respondents' age and time preference on valuations of health states to gain insight in the contribution of individual response patterns to the variance in valuation scores. Methods. A total of 212 respondents from three age groups valued the same six hypothetical health states using three different methods: a Visual Analogue Scale (VAS) and two variants of the Time trade-off (TTO). Analyses included a generalizability study, principal components analysis, and cluster analysis. Results. Valuation scores differed significantly, but not systematically, between valuation methods. A total of 36.8% of variance was explained by health states, 1.6% by the elicitation method, and 0.2% by age group. Individual differences in the use of the response scales (e.g. a tendency to give either high or low TTO scores, or a high or low scoring tendency on the VAS) were the main source of remaining variance. These response patterns were not related to age or other identifiable respondent characteristics. Conclusion. Individual response patterns in this study were more important determinants of TTO or VAS valuations of health states than age or other respondent characteristics measured. Further valuation research should focus on explaining individual response patterns as a possible key to understanding the determinants of health state valuations. http://repub.eur.nl/res/pub/35826/ 2007-04-01T00:00:00Z Background: An essential characteristic of health impact assessment (HIA) is that it seeks to predict the future consequences of possible decisions for health. These predictions have to be valid, but as yet it is unclear how validity should be defined in HIA. Aims: To examine the philosophical basis for predictions and the relevance of different forms of validity to HIA. Conclusions: HIA is valid if formal validity, plausibility and predictive validity are in order. Both formal validity and plausibility can usually be established, but establishing predictive validity implies outcome evaluation of HIA. This is seldom feasible owing to long time lags, migration, measurement problems, a lack of data and sensitive indicators, and the fact that predictions may influence subsequent events. Predictive validity most often is not attainable in HIA and we have to make do with formal validity and plausibility However, in political science, this is by no means exceptional. http://repub.eur.nl/res/pub/8393/ 2005-01-01T00:00:00Z STUDY OBJECTIVE: To assess what methods are used in quantitative health impact assessment (HIA), and to identify areas for future research and development. DESIGN: HIA reports were assessed for (1) methods used to quantify effects of policy on determinants of health (exposure impact assessment) and (2) methods used to quantify health outcomes resulting from changes in exposure to determinants (outcome assessment). MAIN RESULTS: Of 98 prospective HIA studies, 17 reported quantitative estimates of change in exposure to determinants, and 16 gave quantified health outcomes. Eleven (categories of) determinants were quantified up to the level of health outcomes. Methods for exposure impact assessment were: estimation on the basis of routine data and measurements, and various kinds of modelling of traffic related and environmental factors, supplemented with experts' estimates and author's assumptions. Some studies used estimates from other documents pertaining to the policy. For the calculation of health outcomes, variants of epidemiological and toxicological risk assessment were used, in some cases in mathematical models. CONCLUSIONS: Quantification is comparatively rare in HIA. Methods are available in the areas of environmental health and, to a lesser extent, traffic accidents, infectious diseases, and behavioural factors. The methods are diverse and their reliability and validity are uncertain. Research and development in the following areas could benefit quantitative HIA: methods to quantify the effect of socioeconomic and behavioural determinants; user friendly simulation models; the use of summary measures of public health, expert opinion and scenario building; and empirical research into validity and reliability. http://repub.eur.nl/res/pub/10356/ 2004-01-01T00:00:00Z OBJECTIVE: To analyze the prevalence of disability throughout life and life expectancy free of disability, associated with obesity at ages 30 to 49 years. RESEARCH METHODS AND PROCEDURES: We used 46 and 20 years of mortality follow-up, respectively, for 3521 Original and 3013 Offspring Framingham Heart Study participants 30 to 49 years and classified as normal weight, overweight, or obese at baseline. Disability measures were available between 36 and 46 years of follow-up for 1352 Original participants and at 20 years of follow-up for 2268 Offspring participants. We measured the odds of disability in the Original cohort after 46 years follow-up, and we estimated life expectancy with and without disability from age 50. Two disability measures were used, one representing limitations with mobility only and the second representing limitations with activities of daily living (ADL). RESULTS: Obesity at ages 30 to 49 years was associated with a 2.01-fold increase in the odds of ADL limitations 46 years later. Nonsmoking adults who were obese between 30 and 49 years lived 5.70 (95% confidence interval, 4.11 to 7.35) (men) and 5.02 (95% confidence interval, 3.36 to 6.61) (women) fewer years free of ADL limitations from age 50 than their normal-weight counterparts. There was no significant difference in the total number of years lived with disability throughout life between those obese or normal weight, due to both higher disability prevalence and higher mortality in the obese population. DISCUSSION: Obesity in adulthood is associated with an increased risk of disability throughout life and a reduction in the length of time spent free of disability, but no substantial change in the length of time spent with disability. http://repub.eur.nl/res/pub/13171/ 2003-07-01T00:00:00Z BACKGROUND AND PURPOSE: Many countries observed rapidly declining stroke mortality rates during 1970-1990, followed by a slowing or a cessation of this decline. This slowing was seen for both sexes and all ages. Here we test the hypothesis that improvements in coronary heart disease (CHD) survival can explain this slowing through an increase in the number of CHD survivors at an increased risk for stroke. METHODS: We created multistate life-table models based on the survival experience of 46 years of follow-up of the Framingham Heart Study cohort. Improvements in survival after CHD were modeled by decreasing mortality rates for those with CHD. We analyzed whether improved CHD survival could result in a >3% increase in annual stroke mortality rates, which would be enough to eliminate the previously observed decline. RESULTS: CHD survival improvements led to an increase in the number of stroke deaths but also a concomitant increase in the total population size. Under no circumstances was there an annual increase in stroke mortality rates approaching 3% for both sexes and for younger and older age groups. CONCLUSIONS: The hypothesis that increases in the numbers of people with CHD, as a consequence of improvements in CHD survival, explain the observed slowing of the stroke mortality rate decline must be rejected. The true explanation is also likely to be a factor that changed markedly around 1990, but with more direct effects on stroke mortality. http://repub.eur.nl/res/pub/10043/ 2003-01-01T00:00:00Z BACKGROUND: Overweight and obesity in adulthood are linked to an increased risk for death and disease. Their potential effect on life expectancy and premature death has not yet been described. OBJECTIVE: To analyze reductions in life expectancy and increases in premature death associated with overweight and obesity at 40 years of age. DESIGN: Prospective cohort study. SETTING: The Framingham Heart Study with follow-up from 1948 to 1990. PARTICIPANTS: 3457 Framingham Heart Study participants who were 30 to 49 years of age at baseline. MEASUREMENTS: Mortality rates specific for age and body mass index group (normal weight, overweight, or obese at baseline) were derived within sex and smoking status strata. Life expectancy and the probability of death before 70 years of age were analyzed by using life tables. RESULTS: Large decreases in life expectancy were associated with overweight and obesity. Forty-year-old female nonsmokers lost 3.3 years and 40-year-old male nonsmokers lost 3.1 years of life expectancy because of overweight. Forty-year-old female nonsmokers lost 7.1 years and 40-year-old male nonsmokers lost 5.8 years because of obesity. Obese female smokers lost 7.2 years and obese male smokers lost 6.7 years of life expectancy compared with normal-weight smokers. Obese female smokers lost 13.3 years and obese male smokers lost 13.7 years compared with normal-weight nonsmokers. Body mass index at ages 30 to 49 years predicted mortality after ages 50 to 69 years, even after adjustment for body mass index at age 50 to 69 years. CONCLUSIONS: Obesity and overweight in adulthood are associated with large decreases in life expectancy and increases in early mortality. These decreases are similar to those seen with smoking. Obesity in adulthood is a powerful predictor of death at older ages. Because of the increasing prevalence of obesity, more efficient prevention and treatment should become high priorities in public health. http://repub.eur.nl/res/pub/10140/ 2003-01-01T00:00:00Z BACKGROUND: Health policy and planning depend on quantitative data of disease epidemiology. However, empirical data are often incomplete or are of questionable validity. Disease models describing the relationship between incidence, prevalence and mortality are used to detect data problems or supplement missing data. Because time trends in the data affect their outcome, we compared the extent to which trends and known data problems affected model outcome for breast cancer. METHODS: We calculated breast cancer prevalence from Dutch incidence and mortality data (the Netherlands Cancer Registry and Statistics Netherlands) and compared this to regionally available prevalence data (Eindhoven Cancer Registry, IKZ). Subsequently, we recalculated the model adjusting for 1) limitations of the prevalence data, 2) a trend in incidence, 3) secondary primaries, and 4) excess mortality due to non-breast cancer deaths. RESULTS: There was a large discrepancy between calculated and IKZ prevalence, which could be explained for 60% by the limitations of the prevalence data plus the trend in incidence. Secondary primaries and excess mortality had relatively small effects only (explaining 17% and 6%, respectively), leaving a smaller part of the difference unexplained. CONCLUSION: IPM models can be useful both for checking data inconsistencies and for supplementing incomplete data, but their results should be interpreted with caution. Unknown data problems and trends may affect the outcome and in the absence of additional data, expert opinion is the only available judge. http://repub.eur.nl/res/pub/10141/ 2003-01-01T00:00:00Z Epidemiology as an empirical science has developed sophisticated methods to measure the causes and patterns of disease in populations. Nevertheless, for many diseases in many countries only partial data are available. When the partial data are insufficient, but data collection is not an option, it is possible to supplement the data by exploiting the causal relations between the various variables that describe a disease process. We present a simple generic disease model with incidence, one prevalent state, and case fatality and remission. We derive a set of equations that describes this disease process and allows calculation of the complete epidemiology of a disease given a minimum of three input variables. We give the example of asthma with age-specific prevalence, remission, and mortality as inputs. Outputs are incidence and case fatality, among others. The set of equations is embedded in a software package called 'DisMod II', which is made available to the public domain by the World Health Organization. http://repub.eur.nl/res/pub/9061/ 1999-01-01T00:00:00Z OBJECTIVES: This study quantified the consequences for prevalence of increased survival of coronary heart disease (CHD) in the Netherlands from 1980 to 1993. METHODS: A multistage life table fitted observed mortality and registration rates from the nationwide hospital register. The outcome was prevalence by age, sex, period, and disease state. RESULTS: The prevalence of CHD from 1980 to 1993 was 4.4% (men, aged 25 to 84 years) and 1.4% (women, aged 25 to 84 years). Between 1980-1983 and 1990-1993, the incidence changed little, but age-adjusted prevalence increased by 19% (men) and 59% (women). CONCLUSIONS: Sharply decreasing mortality but near-constant attack rates of CHD caused distinct increases in prevalence, particularly among the elderly. http://repub.eur.nl/res/pub/16984/ 1998-01-14T00:00:00Z This PhD thesis is rootcd in a mnltidisciplinary project, ca lied Technology Assessment lvlethods (TAM). The (ambitious) aim of the TAM project was to develop a comprehcllsive method of evalnating medical tcchnology in the perspective of multiple risk factors, multiple diseascs and multiple causes of death (Bonneux & Bai'endregt, 1991). Thc project was an attempt to bettel' llllderstand the dynamics of populatioll health status, in particnlar in relation to medical intervclltions, but it was "lso lllotivated by thc rapidly rising health care costs of the past decades, whieh fueled the feal' that ever expanding casts might become economically unsllstainahle in the future (van der Maas & Habbema, 1986). The TAM project would provide a better lUlderstanding of the consequcllces for beth casts and popt!lation hcalth status of a \\Vide array of preventivc aud therapeutic health care interventions, and through that offer the tools for policy makers to huy the better investments in health with a sustaillahle health carc budget. Two factors arc commanly held responsible for the increase in health care costs: aging and health care technology. http://repub.eur.nl/res/pub/8766/ 1998-01-01T00:00:00Z OBJECTIVES: To examine whether elimination of fatal diseases will increase healthcare costs. DESIGN: Mortality data from vital statistics combined with healthcare spending in a cause elimination life table. Costs were allocated to specific diseases through the various healthcare registers. SETTING AND SUBJECTS: The population of the Netherlands, 1988. MAIN OUTCOME MEASURES: Healthcare costs of a synthetic life table cohort, expressed as life time expected costs. RESULTS: The life time expected healthcare costs for 1988 in the Netherlands were 56,600 Pounds for men and 80,900 Pounds for women. Elimination of fatal diseases--such as coronary heart disease, cancer, or chronic obstructive lung disease--increases healthcare costs. Major savings will be achieved only by elimination of non-fatal disease--such as musculoskeletal diseases and mental disorders. CONCLUSION: The aim of prevention is to spare people from avoidable misery and death not to save money on the healthcare system. In countries with low mortality, elimination of fatal diseases by successful prevention increases healthcare spending because of the medical expenses during added life years. http://repub.eur.nl/res/pub/9046/ 1998-01-01T00:00:00Z In industrialised countries, mortality and morbidity are dominated by age related chronic degenerative diseases. The health and health care needs of future populations will be heavily determined by these conditions of old age. Two opposite scenarios of future morbidity exist: morbidity might decrease ("compress"), because life span is limited, and the incidence of disease is postponed. Or morbidity might increase ("expand"), because death is delayed more than disease incidence. Optimality theory in evolutionary biology explains senescence as a by product of an optimised life history. The theory clarifies how senescence is timed by the competing needs for reproduction and survival, and why this leads to a generalised deterioration of many functions at many levels. As death and disease are not independent, future morbidity will depend on duration and severity of the process of senescence, partly determined by health care, palliating the disease severity but increasing the disease duration by postponing death. Even if morbidity might be compressed, health care needs will surely expand. http://repub.eur.nl/res/pub/8722/ 1997-01-01T00:00:00Z BACKGROUND: Although smoking cessation is desirable from a public health perspective, its consequences with respect to health care costs are still debated. Smokers have more disease than nonsmokers, but nonsmokers live longer and can incur more health costs at advanced ages. We analyzed health care costs for smokers and nonsmokers and estimated the economic consequences of smoking cessation. METHODS: We used three life tables to examine the effect of smoking on health care costs - one for a mixed population of smokers and nonsmokers, one for a population of smokers, and one for a population of nonsmokers. We also used a dynamic method to estimate the effects of smoking cessation on health care costs over time. RESULTS: Health care costs for smokers at a given age are as much as 40 percent higher than those for nonsmokers, but in a population in which no one smoked the costs would be 7 percent higher among men and 4 percent higher among women than the costs in the current mixed population of smokers and nonsmokers. If all smokers quit, health care costs would be lower at first, but after 15 years they would become higher than at present. In the long term, complete smoking cessation would produce a net increase in health care costs, but it could still be seen as economically favorable under reasonable assumptions of discount rate and evaluation period. CONCLUSIONS: If people stopped smoking, there would be a savings in health care costs, but only in the short term. Eventually, smoking cessation would lead to increased health care costs. http://repub.eur.nl/res/pub/8596/ 1994-01-01T00:00:00Z OBJECTIVES. Many developed countries have seen declining mortality rates for heart disease, together with an alleged decline in incidence and a seemingly paradoxical increase in health care demands. This paper presents a model for forecasting the plausible evolution of heart disease morbidity. METHODS. The simulation model combines data from different sources. It generates acute coronary event and mortality rates from published data on incidences, recurrences, and lethalities of different heart disease conditions and interventions. Forecasts are based on plausible scenarios for declining incidence and increasing survival. RESULTS. Mortality is postponed more than incidence. Prevalence rates of morbidity will decrease among the young and middle-aged but increase among the elderly. As the milder disease states act as risk factors for the more severe states, effects will culminate in the most severe disease states with a disproportionate increase in older people. CONCLUSIONS. Increasing health care needs in the face of declining mortality rates are no contradiction, but reflect a tradeoff of mortality for morbidity. The aging of the population will accentuate this morbidity increase.