Estimating health-adjusted life expectancy conditional on risk factors: results for smoking and obesity

The estimated health impact of alcohol interventions in New Zealand: A modelling study

AIMS

To estimate the health impacts of key modelled alcohol interventions among Māori (indigenous peoples) and non-Māori in New Zealand (NZ).

DESIGN

Multi-stage life-table intervention modelling study. We modelled two scenarios: (1) business-as-usual (BAU); and (2) an intervention package scenario that included a 50% alcohol tax increase, outlet density reduction from 63 to five outlets per 100 000 people, outlet hours reduction from 112 to 50 per week and a complete ban on all forms of alcohol marketing.

SETTING AND PARTICIPANTS

The model's population replicates the 2018 NZ population by ethnicity (Māori/non-Māori), age and sex.

MEASUREMENTS

Alcohol consumption was estimated using nationally representative survey data combined with sales data and corrected for tourist and unrecorded consumption. Disease incidence, prevalence and mortality were calculated using Ministry of Health data. We used dose-response relationships between alcohol and illness from the 2016 Global Burden of Disease study and calculated disability rates for each illness. Changes in consumption were based on the following effect sizes: total intervention package [-30.3%, standard deviation (SD) = 0.02); tax (-7.60%, SD = 0.01); outlet density (-8.64%, SD = 0.01); outlet hours (-9.24%, SD = 0.01); and marketing (-8.98%, SD = 0.02). We measured health gain using health-adjusted life years (HALYs) and life expectancy.

FINDINGS

Compared with the BAU scenario, the total alcohol intervention package resulted in 726 000 [95% uncertainty interval (UI) = 492 000-913 000] HALYs gained during the life-time of the modelled population. Māori experienced greater HALY gains compared with non-Māori (0.21, 95% UI = 0.14-0.26 and 0.16, 95% UI = 0.11-0.20, respectively). When modelled individually, each alcohol intervention within the intervention package produced similar health gains (~200 000 HALYs per intervention) owing to the similar effect sizes.

CONCLUSIONS

Modelled interventions for increased alcohol tax, reduced availability of alcohol and a ban on alcohol marketing among Māori and non-Māori in New Zealand (NZ) suggest substantial population-wide health gains and reduced health inequities between Māori and non-Māori.

Health outcomes in Bulgaria: Simulated effects of obesogenic environmental changes in adulthood versus childhood

OBJECTIVE

Bulgarian government efforts to tackle obesity are focused mainly on guidelines affecting children. However, it is unclear whether targeting children for obesity-related health policies yields better long-term health outcomes as opposed to changing the risk of obesity in adulthood. This study aims to evaluate where policy efforts should be directed to alleviate the health burden associated with obesity.

METHODS

We compare the impact on population health of two simulated scenarios when (a) the prevalence of obesity upon entering adulthood is lowered; (b) the risk of getting an unhealthy weight as an adult is reduced. Additionally, we run (c) combinations of the two and (d) childhood obesity prevention on the one hand, and worsening (increasing) obesity incidence later in adulthood on the other.

RESULTS

Our findings show that obesogenic environmental changes throughout adulthood have a stronger effect on life expectancy (LE), diabetes-free life expectancy (DFLE) and type 2 diabetes prevalence outcomes compared to lowering the proportion of individuals with obesity during adolescence. Nevertheless, a sizable reduction in the number of young adults with unhealthy weight has the potential to recover years of LE/DFLE that would be lost if the risk of obesity in adulthood would continue to grow in time.

CONCLUSIONS

The two types of policies' (a-b) effects are not equivalent in strength and the best way forward is dependent on future obesity incidence trends.

The Cost-Effectiveness of Nicotine Replacement Therapy Sampling in Primary Care: a Markov Cohort Simulation Model

BACKGROUND

Pharmacotherapies remain a central focus of successful tobacco control, but uptake remains very low.

OBJECTIVE

To estimate the cost effectiveness of a primary care nicotine replacement therapy (NRT) sampling intervention.

DESIGN

A Markov cohort simulation model was constructed to conduct cost-effectiveness analyses. Clinical trial results were used to initialize the Markov model. All other model parameters were derived from the literature. The study was conducted over a lifetime horizon, from the payers' budgetary perspective.

PARTICIPANTS

Smokers with a primary care visit.

INTERVENTION

Medication sampling, which provided short, starter packets of NRT (nicotine patch and lozenge) to smokers in the primary care setting.

MAIN MEASURES

Lifetime healthcare expenditures, quality-adjusted life years, and life years.

KEY RESULTS

Medication sampling was the dominant strategy compared to standard care. Our intervention cost $75, yielding a discounted lifetime savings of $1065 in healthcare expenditures, and increased both discounted quality-adjusted life years and discounted life years by 0.01. One-way sensitivity analyses showed that medication sampling remained dominant in plausible ranges except when it failed to increase cessation relative to standard care. Probabilistic sensitivity analyses confirmed that medication sampling was dominant in 94.1% of the simulated cases, with an implementation cost of $74 (95% CI $73-$76) and discounted lifetime savings in health expenditures of $1061 (- $1106 to - $1,017), increasing quality-adjusted life years by 0.008 (0.0085-0.0093) and life years by 0.008 (0.0081-0.0089).

CONCLUSION

Medication sampling, an easily implementable, scalable and low-cost intervention to encourage smoking cessation, is cost saving and improves quality of life.

Mixed evidence for the compression of morbidity hypothesis for smoking elimination-a systematic literature review

BACKGROUND

There is debate around the composition of life years gained from smoking elimination. The aim of this study was to conduct a systematic review of the literature to synthesize existing evidence on the effect of smoking status on health expectancy and to examine whether smoking elimination leads to compression of morbidity.

METHODS

Five databases were systematically searched for peer-reviewed articles. Studies that presented quantitative estimates of health expectancy for smokers and non-/never-smokers were eligible for inclusion. Studies were searched, selected and reviewed by two reviewers who extracted the relevant data and assessed the risk of bias of the included articles independently.

RESULTS

The search identified 2491 unique records, whereof 20 articles were eligible for inclusion (including 26 cohorts). The indicators used to measure health included disability/activity limitations (n=9), health-related quality of life (EQ-5D) (n=2), weighted disabilities (n=1), self-rated health (n=9), chronic diseases (n=6), cardiovascular diseases (n=4) and cognitive impairment (n=1). Available evidence showed consistently that non-/never-smokers experience more healthy life years throughout their lives than smokers. Findings were inconsistent on the effect of smoking on the absolute number of unhealthy life years. Findings concerning the time proportionally spent unhealthy were less heterogeneous: nearly all included articles reported that non-/never-smokers experience relatively less unhealthy life years (e.g. relative compression of morbidity).

CONCLUSIONS

Support for the relative compression of morbidity due to smoking elimination was evident. Further research is needed into the absolute compression of morbidity hypothesis since current evidence is mixed, and methodology of studies needs to be harmonized.

Simulating future public health benefits of tobacco control interventions: a systematic review of models

BACKGROUND

To prioritise tobacco control interventions, simulating their health impacts is valuable. We undertook a systematic review of tobacco intervention simulation models to assess model structure and input variations that may render model outputs non-comparable.

METHODS

We applied a Medline search with keywords intersecting modelling and tobacco. Papers were limited to those modelling health outputs (eg, mortality, health-adjusted life years), and at least two of cancer, cardiovascular and respiratory diseases. Data were extracted for each simulation model with ≥3 arising papers, including: model type, untimed or with time steps and trends in business-as-usual (BAU) tobacco prevalence and epidemiology.

RESULTS

Of 1911 papers, 186 met the inclusion criteria, including 13 eligible simulation models. The SimSmoke model had the largest number of publications (n=46), followed by Benefits of Smoking Cessation on Outcomes (n=12) and Tobacco Policy Model (n=10). Two of 13 models only estimated deaths averted, 1 had no time steps, 5 had no future trends in BAU tobacco prevalence, 9 had no future trends in BAU disease epidemiology and 7 had no time lags from quitting tobacco to reversal of health harm.

CONCLUSIONS

Considerable heterogeneity exists in simulation models, making outputs substantively non-comparable between models. Ranking of interventions by one model may be valid. However, this may not be true if, for example, interventions that differentially affect age groups (eg, a tobacco-free generation policy vs increased cessation among adults) do not account for plausible future trends. Greater standardisation of model structures and outputs will allow comparison across models and countries, and for comparisons of the impact of tobacco control interventions with other preventive interventions.

Prospective impact of tobacco eradication and overweight and obesity eradication on future morbidity and health-adjusted life expectancy: simulation study

BACKGROUND

Interventions that reduce morbidity, in addition to mortality, warrant prioritisation. It is important to understand the magnitude of potential morbidity and health gains from changing risk factor distributions. We quantified the impact of tobacco compared with overweight/obesity eradication on future morbidity and health-adjusted life expectancy (HALE) for the New Zealand population alive in 2011.

METHODS

Business-as-usual (BAU) future smoking rates were set based on past falling rates, but we assumed no future change in Body Mass Index (BMI) distribution, given historic trends. Population impact fractions and the percentage reduction in incidence rates for 16 tobacco-related and 14 overweight/obesity-related diseases (allowing for time lags) were calculated using the difference between BAU and eradication risk factor scenarios combined with tobacco and BMI incidence rate ratios. We used two multistate lifetable models to estimate HALE changes over the remaining lifespan and morbidity rate changes 30 years hence.

RESULTS

HALE gains always exceeded life expectancy (LE) gains for overweight/obesity eradication (ie, absolute compression of morbidity), but for eradication of tobacco, the pattern was mixed. For example, among 32-year-olds in 2011, overweight/obesity eradication increased HALE by 2.06 years and LE by 1.21 years, compared with 0.54 and 0.50 years for tobacco eradication.Morbidity rate reductions 30 years into the future were considerably greater for overweight/obesity eradication (eg, a 15.8% reduction for 72-year-olds in 2041, or the cohort that was aged 42 years in 2011) than for tobacco eradication (2.7%). The same rate of morbidity experienced at age 65 years under BAU was deferred by 5 years with overweight/obesity eradication.

CONCLUSIONS

Preventive programmes that reduce overweight and obesity have strong potential to reduce or compress morbidity, improving the average health status of ageing populations. This paper simulated eradication of tobacco and overweight/obesity; actual interventions will have lesser health impacts, but the relativities of morbidity to mortality gains should be similar.

Gut Microbiome Modulation Based on Probiotic Application for Anti-Obesity: A Review on Efficacy and Validation

The growing prevalence of obesity has become an important problem worldwide as obesity has several health risks. Notably, factors such as excessive food consumption, a sedentary way of life, high sugar consumption, a fat-rich diet, and a certain genetic profile may lead to obesity. The present review brings together recent advances regarding the significance of interventions involving intestinal gut bacteria and host metabolic phenotypes. We assess important biological molecular mechanisms underlying the impact of gut microbiota on hosts including bile salt metabolism, short-chain fatty acids, and metabolic endotoxemia. Some previous studies have shown a link between microbiota and obesity, and associated disease reports have been documented. Thus, this review focuses on obesity and gut microbiota interactions and further develops the mechanism of the gut microbiome approach related to human obesity. Specifically, we highlight several alternative diet treatments including dietary changes and supplementation with probiotics. The future direction or comparative significance of fecal transplantation, synbiotics, and metabolomics as an approach to the modulation of intestinal microbes is also discussed.

Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs

BACKGROUND

Increases in human longevity have made it critical to distinguish healthy longevity from longevity without regard to health. Current methods focus on expectations of healthy longevity, and are often limited to binary health outcomes (e.g., disabled vs. not disabled). We present a new matrix formulation for the statistics of healthy longevity, based on health prevalence data and Markov chain theory, applicable to any kind of health outcome and which provides variances and higher moments as well as expectations of healthy life.

METHOD

The model is based on a Markov chain description of the life course coupled with the moments of health outcomes ("rewards") at each age or stage. As an example, we apply the method to nine European countries using the SHARE survey data on the binary outcome of disability as measured by activities of daily living, and the continuous health outcome of hand grip strength.

RESULTS

We provide analytical formulas for the mean, variance, coefficient of variation, skewness and other statistical properties of healthy longevity. The analysis is applicable to binary, categorical, ordinal, or interval scale health outcomes. The results are easily evaluated in any matrix-oriented software. The SHARE results reveal familiar patterns for the expectation of life and of healthy life: women live longer than men but spend less time in a healthy condition. New results on the variance shows that the standard deviation of remaining healthy life declines with age, but the coefficient of variation is nearly constant. Remaining grip strength years decrease with age more dramatically than healthy years but their variability pattern is similar to the pattern of healthy years. Patterns are similar across nine European countries.

CONCLUSIONS

The method extends, in several directions, current calculations of health expectancy (HE) and disability-adjusted life years (DALYs). It applies to both categorical and continuous health outcomes, to combinations of multiple outcomes (e.g., death and disability in the formulation of DALYs) and to age- or stage-classified models. It reveals previously unreported patterns of variation among individuals in the outcomes of healthy longevity.

Health-adjusted life expectancy in HIV-positive and HIV-negative men and women in British Columbia, Canada: a population-based observational cohort study

BACKGROUND

We sought to understand whether people living with HIV (PLHIV) ever on highly active antiretroviral therapy (ART) follow a pattern where morbidity is compressed into the last years of life or lessened as people age. We aimed to estimate health-adjusted life expectancy (HALE) among adults living with and without HIV, and examine dependency between causes of comorbidities.

METHODS

The Comparative Outcomes and Service Utilization Trends (COAST) study is a retrospective cohort of adults (≥20 years) including all known PLHIV and a 10% random sample of the general population of British Columbia, and with longitudinal data spanning from April 1, 1996, to Dec 31, 2012. We determined the prevalence of select comorbidities (cardiovascular, respiratory, liver, and renal diseases, and non-AIDS defining cancers because of their high prevalence among PLHIV) by age and sex by use of case-finding algorithms. Deaths were obtained from a vital event registry from British Columbia, Canada. Comorbid-specific HALE was estimated from 20 years of age by HIV status and sex. For each comorbidity, a healthy state was defined as the proportion of life expectancy comorbid-free, and was adjusted on the probability of occurrence of other different comorbidities. The sensitivity of HALE estimates was assessed to the sequencing of select comorbidities for the dependent comorbidity adjustments.

FINDINGS

Our sample consisted of electronic health records from 9310 HIV-infected and 510 313 uninfected adults over the period April 1, 1996, to Dec 31, 2012. These individuals contributed 49 605 deaths and 5 576 841 person-years over the study period. At exactly age 20 years, HALE was about 31 years (SD 0·16) among men living with HIV and 27 years (0·16) among women living with HIV. In the HIV-negative population, HALE was around 58 years (SD 0·02) for men and 63 years (0·02) for women. These results seem independent of ordering. However, PLHIV, particularly women living with HIV, had much shorter overall life expectancies than did their HIV-negative counterparts in the general population [29·1 years (SD 0·1) vs 65·4 years (0·1)], and thus spent less time in a healthy state.

INTERPRETATION

Although we noted little differences in the levels of morbidity compression by HIV status, PLHIV-especially women living with HIV-spent less time in a healthy state. Expanded service delivery interventions to address complex care needs of ageing PLHIV are crucial to address shorter life expectancies, and improve their healthy states.

FUNDING

Canadian Institutes of Health Research.

Taking multi-morbidity into account when attributing DALYs to risk factors: comparing dynamic modeling with the GBD2010 calculation method

BACKGROUND

Disability Adjusted Life Years (DALYs) quantify the loss of healthy years of life due to dying prematurely and due to living with diseases and injuries. Current methods of attributing DALYs to underlying risk factors fall short on two main points. First, risk factor attribution methods often unjustly apply incidence-based population attributable fractions (PAFs) to prevalence-based data. Second, it mixes two conceptually distinct approaches targeting different goals, namely an attribution method aiming to attribute uniquely to a single cause, and an elimination method aiming to describe a counterfactual situation without exposure. In this paper we describe dynamic modeling as an alternative, completely counterfactual approach and compare this to the approach used in the Global Burden of Disease 2010 study (GBD2010).

METHODS

Using data on smoking in the Netherlands in 2011, we demonstrate how an alternative method of risk factor attribution using a pure counterfactual approach results in different estimates for DALYs. This alternative method is carried out using the dynamic multistate disease table model DYNAMO-HIA. We investigate the differences between our alternative method and the method used by the GBD2010 by doing additional analyses using data from a synthetic population in steady state.

RESULTS

We observed important differences between the outcomes of the two methods: in an artificial situation where dynamics play a limited role, DALYs are a third lower as compared to those calculated with the GBD2010 method (398,000 versus 607,000 DALYs). The most important factor is newly occurring morbidity in life years gained that is ignored in the GBD2010 approach. Age-dependent relative risks and exposures lead to additional differences between methods as they distort the results of prevalence-based DALY calculations, but the direction and magnitude of the distortions depend on the particular situation.

CONCLUSIONS

We argue that the GBD2010 approach is a hybrid of an attributional and counterfactual approach, making the end result hard to understand, while dynamic modelling uses a purely counterfactual approach and thus yields better interpretable results.

Body mass index as a predictor of healthy and disease-free life expectancy between ages 50 and 75: a multicohort study

BACKGROUND

While many studies have shown associations between obesity and increased risk of morbidity and mortality, little comparable information is available on how body mass index (BMI) impacts health expectancy. We examined associations of BMI with healthy and chronic disease-free life expectancy in four European cohort studies.

METHODS

Data were drawn from repeated waves of cohort studies in England, Finland, France and Sweden. BMI was categorized into four groups from normal weight (18.5-24.9 kg m^-2) to obesity class II (⩾35 kg m^-2). Health expectancy was estimated with two health indicators: sub-optimal self-rated health and having a chronic disease (cardiovascular disease, cancer, respiratory disease and diabetes). Multistate life table models were used to estimate sex-specific healthy life expectancy and chronic disease-free life expectancy from ages 50 to 75 years for each BMI category.

RESULTS

The proportion of life spent in good perceived health between ages 50 and 75 progressively decreased with increasing BMI from 81% in normal weight men and women to 53% in men and women with class II obesity which corresponds to an average 7-year difference in absolute terms. The proportion of life between ages 50 and 75 years without chronic diseases decreased from 62 and 65% in normal weight men and women and to 29 and 36% in men and women with class II obesity, respectively. This corresponds to an average 9 more years without chronic diseases in normal weight men and 7 more years in normal weight women between ages 50 and 75 years compared to class II obese men and women. No consistent differences were observed between cohorts.

CONCLUSIONS

Excess BMI is associated with substantially shorter healthy and chronic disease-free life expectancy, suggesting that tackling obesity would increase years lived in good health in populations.

Smoking, physical inactivity and obesity as predictors of healthy and disease-free life expectancy between ages 50 and 75: a multicohort study

Background: Smoking, physical inactivity and obesity are modifiable risk factors for morbidity and mortality. The aim of this study was to examine the extent to which the co-occurrence of these behaviour-related risk factors predict healthy life expectancy and chronic disease-free life expectancy in four European cohort studies.

Methods: Data were drawn from repeated waves of four cohort studies in England, Finland, France and Sweden. Smoking status, physical inactivity and obesity (body mass index ≥30 kg/m²) were examined separately and in combination. Health expectancy was estimated by using two health indicators: suboptimal self-rated health and having a chronic disease (cardiovascular disease, cancer, respiratory disease and diabetes). Multistate life table models were used to estimate sex-specific healthy life expectancy and chronic disease-free life expectancy from ages 50 to 75 years.

Results: Compared with men and women with at least two behaviour-related risk factors, those with no behaviour-related risk factors could expect to live on average8 years longer in good health and 6 years longer free of chronic diseases between ages 50 and 75. Having any single risk factor was also associated with reduction in healthy years. No consistent differences between cohorts were observed.

Conclusions: Data from four European countries show that persons with individual and co-occurring behaviour-related risk factors have shorter healthy life expectancy and shorter chronic disease-free life expectancy. Population level reductions in smoking, physical inactivity and obesity could increase life-years lived in good health.

Preventing dementia by promoting physical activity and the long-term impact on health and social care expenditures

BACKGROUND

Preventing dementia has been proposed to increase population health as well as reduce the demand for health and social care. Our aim was to evaluate whether preventing dementia by promoting physical activity (PA) a) improves population health or b) reduces expenditure for both health and social care if one takes into account the additional demand in health and social care caused by increased life expectancy.

METHODS

A simulation model was developed that models the relation between PA, dementia, mortality, and the use of health care and social care in England. With this model, scenarios were evaluated in which different assumptions were made about the increase in PA level in (part of) the population.

RESULTS

Lifetime spending on health and social care related to dementia was highest for the physically inactive (£28,100/£28,900 for 40-year-old males/females), but spending on other diseases was highest for those that meet PA recommendations (£55,200/£43,300 for 40-year-old males/females) due to their longer life expectancies. If the English population aged 40-65 were to increase their PA by one level, life expectancy would increase by 0.23years and health and social care expenditures would decrease by £400 per person.

CONCLUSIONS

Preventing dementia by increasing PA increases life expectancy and can result in decreased spending overall on health and social care, even after additional spending during life years gained has been taken into account. If prevention is targeted at the physically inactive, savings in dementia-related costs outweigh the additional spending in life years gained.

Prevalence of disability in Australian elderly: Impact of trends in obesity and diabetes

OBJECTIVE

We aimed to estimate the impact of past and future changes in obesity and diabetes prevalence in mid-life on disability prevalence for adult Australians.

METHODS

We analysed data from the Australian Diabetes, Obesity and Lifestyle study (AusDiab) including participants aged 45-64years, disability-free at baseline (1999/2000) with disability information at follow-up (2011/12) (n=2107). We used coefficients from multinomial logistic regression to predict 10-year probabilities of disability and death from baseline predictors (age, sex, obesity, smoking, diabetes and hypertension). We estimated the prevalence of disability attributable to past (1980) and expected future (2025) changes in obesity and diabetes prevalence using the life table approach.

RESULTS

We estimated that the prevalence of disability for those aged between 55 and 74years would have been 1697 cases per 100,000 persons less in 2010 (10.3% less) if the rates of obesity and diabetes observed in 2000 had been as low as the levels observed in 1980. However, if instead the prevalence of obesity and diabetes had been as high as the levels expected in 2025, then the prevalence of disability would have been an additional 2173 per 100,000 persons (an additional 13.2%).

CONCLUSIONS

We demonstrate, for the first time, a substantial potential impact of obesity and diabetes trends on disability amongst those aged 55-74years. In Australian adults by 2025 we estimate that around 26% of disability cases would have been avoidable if there had been no change in obesity and diabetes prevalence since 1980. A similar impact is likely around the world in developed countries.

Cost-effectiveness of extended cessation treatment for older smokers

AIMS

We examined the cost-effectiveness of extended smoking cessation treatment in older smokers.

DESIGN

Participants who completed a 12-week smoking cessation program were factorial randomized to extended cognitive behavioral treatment and extended nicotine replacement therapy.

SETTING

A free-standing smoking cessation clinic.

PARTICIPANTS

A total of 402 smokers aged 50 years and older were recruited from the community.

MEASUREMENTS

The trial measured biochemically verified abstinence from cigarettes after 2 years and the quantity of smoking cessation services utilized. Trial findings were combined with literature on changes in smoking status and the age- and gender-adjusted effect of smoking on health-care cost, mortality and quality of life over the long term in a Markov model of cost-effectiveness over a lifetime horizon.

FINDINGS

The addition of extended cognitive behavioral therapy added $83 in smoking cessation services cost [P = 0.012, confidence interval (CI) = $22-212]. At the end of follow-up, cigarette abstinence rates were 50.0% with extended cognitive behavioral therapy and 37.2% without this therapy (P < 0.05, odds ratio 1.69, CI 1.18-2.54). The model-based incremental cost-effectiveness ratio was $6324 per quality-adjusted life year (QALY). Probabilistic sensitivity analysis found that the additional $947 in lifetime cost of the intervention had a 95% confidence interval of -$331 to 2081; the 0.15 additional QALYs had a confidence interval of 0.035-0.280, and that the intervention was cost-effective against a $50 000/QALY acceptance criterion in 99.6% of the replicates. Extended nicotine replacement therapy was not cost-effective.

CONCLUSIONS

Adding extended cognitive behavior therapy to standard cessation treatment was cost-effective. Further intensification of treatment may be warranted.

Comparing life expectancy and health-adjusted life expectancy by body mass index category in adult Canadians: a descriptive study

BACKGROUND

While many studies have examined differences between body mass index (BMI) categories in terms of mortality risk and health-related quality of life (HRQL), little is known about the effect of body weight on health expectancy. We examined life expectancy (LE), health-adjusted life expectancy (HALE), and proportion of LE spent in nonoptimal (or poor) health by BMI category for the Canadian adult population (age ≥ 20).

METHODS

Respondents to the National Population Health Survey (NPHS) were followed for mortality outcomes from 1994 to 2009. Our study population at baseline (n=12,478) was 20 to 100 years old with an average age of 47. LE was produced by building abridged life tables by sex and BMI category using data from the NPHS and the Canadian Chronic Disease Surveillance System. HALE was estimated using the Health Utilities Index from the Canadian Community Health Survey as a measure of HRQL. The contribution of HRQL to loss of healthy life years for each BMI category was also assessed using two methods: by calculating differences between LE and HALE proportional to LE and by using a decomposition technique to separate out mortality and HRQL contributions to loss of HALE.

RESULTS

At age 20, for both sexes, LE is significantly lower in the underweight and obesity class 2+ categories, but significantly higher in the overweight category when compared to normal weight (obesity class 1 was nonsignificant). HALE at age 20 follows these same associations and is significantly lower for class 1 obesity in women. Proportion of life spent in nonoptimal health and decomposition of HALE demonstrate progressively higher losses of healthy life associated with lowered HRQL for BMI categories in excess of normal weight.

CONCLUSIONS

Although being in the overweight category for adults may be associated with a gain in life expectancy as compared to normal weight adults, overweight individuals also experience a higher proportion of these years of life in poorer health. Due to the descriptive nature of this study, further research is needed to explore the causal mechanisms which explain these results, including the important differences we observed between sexes and within obesity subcategories.

Development of methodology for disability-adjusted life years (DALYs) calculation based on real-life data

Background

Disability-Adjusted Life Years (DALYs) have the advantage that effects on total health instead of on a specific disease incidence or mortality can be estimated. Our aim was to address several methodological points related to the computation of DALYs at an individual level in a follow-up study.

Methods

DALYs were computed for 33,507 men and women aged 20–70 years when participating in the EPIC-NL study in 1993–7. DALYs are the sum of the Years Lost due to Disability (YLD) and the Years of Life Lost (YLL) due to premature mortality. Premature mortality was defined as death before the estimated date of individual Life Expectancy (LE). Different methods to compute LE were compared as well as the effect of different follow-up periods using a two-part model estimating the effect of smoking status on health as an example.

Results

During a mean follow-up of 12.4 years, there were 69,245 DALYs due to years lived with a disease or premature death. Current-smokers had lost 1.28 healthy years of their life (1.28 DALYs 95%CI 1.10; 1.46) compared to never-smokers. The outcome varied depending on the method used for estimating LE, completeness of disease and mortality ascertainment and notably the percentage of extinction (duration of follow-up) of the cohort.

Conclusion

We conclude that the use of DALYs in a cohort study is an appropriate way to assess total disease burden in relation to a determinant. The outcome is sensitive to the LE calculation method and the follow-up duration of the cohort.

Sexually transmitted infections screening at HIV treatment centers for MSM can be cost-effective

OBJECTIVE

To estimate the cost-effectiveness of anorectal chlamydia screening among men who have sex with men (MSM) in care at HIV treatment centers.

DESIGN

Transmission model combined with economic analysis over a 20-year period.

SETTING AND PARTICIPANTS

MSM in care at HIV treatment centers.

INTERVENTION

Once-yearly or twice-yearly screening for anorectal chlamydia among MSM in care at HIV treatment centers.

MAIN OUTCOME MEASURES

Averted HIV and chlamydia infections; discounted quality-adjusted life-years and costs; incremental cost-effectiveness ratio (ICER).

RESULTS

Costs will be saved by routine chlamydia screening of MSM in care at HIV treatment centers if these patients seek little or no screening elsewhere. Nonroutine screening is considerably more expensive than routine screening offered within a scheduled visit. Adding once-yearly chlamydia screening for MSM in care at HIV treatment centers is cost saving when 30% or fewer of those men seek once-yearly screening elsewhere (1.5 to 8.1 million euro saved). Twice-yearly routine screening at HIV treatment centers is cost-effective only when routine screening takes place without additional nonroutine screening (1.9 million euro saved).

CONCLUSIONS

Adding annual chlamydia screening to the HIV consultation will be cost saving as long as only a limited proportion of men are nonroutinely screened. The ICER was most sensitive to the percentage of MSM that continue to be screened elsewhere.

Decomposing Indigenous life expectancy gap by risk factors: a life table analysis

Background

The estimated gap in life expectancy (LE) between Indigenous and non-Indigenous Australians was 12 years for men and 10 years for women, whereas the Northern Territory Indigenous LE gap was at least 50% greater than the national figures. This study aims to explain the Indigenous LE gap by common modifiable risk factors.

Methods

This study covered the period from 1986 to 2005. Unit record death data from the Northern Territory were used to assess the differences in LE at birth between the Indigenous and non-Indigenous populations by socioeconomic disadvantage, smoking, alcohol abuse, obesity, pollution, and intimate partner violence. The population attributable fractions were applied to estimate the numbers of deaths associated with the selected risks. The standard life table and cause decomposition technique was used to examine the individual and joint effects on health inequality.

Results

The findings from this study indicate that among the selected risk factors, socioeconomic disadvantage was the leading health risk and accounted for one-third to one-half of the Indigenous LE gap. A combination of all six selected risks explained over 60% of the Indigenous LE gap.

Conclusions

Improving socioeconomic status, smoking cessation, and overweight reduction are critical to closing the Indigenous LE gap. This paper presents a useful way to explain the impact of risk factors of health inequalities, and suggests that reducing poverty should be placed squarely at the centre of the strategies to close the Indigenous LE gap.

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010

BACKGROUND

Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs).

METHODS

Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis.

FINDINGS

Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350,000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient -0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa.

INTERPRETATION

Rates of YLDs per 100,000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world.

FUNDING

Bill & Melinda Gates Foundation.

A new prevention paradox: the trade-off between reducing incentives for risk selection and increasing the incentives for prevention for health insurers

The Dutch risk equalization scheme has been improved over the years by including health related risk adjusters. The purpose of the Dutch risk equalization scheme is to prevent risk selection and to correct for predictable losses and gains for insurers. The objective of this paper is to explore the financial incentives for risk selection under the Dutch risk equalization scheme. We used a simulation model to estimate lifetime health care costs and risk equalization contributions for three cohorts (a smoking; an obese; and a healthy living cohort). Financial differences for the three cohorts were assessed by subtracting health care costs from risk equalization contributions. Even under an elaborate risk equalization system, the healthy living cohort was still most financially attractive for insurers. Smokers were somewhat less attractive, while the obese cohort was least attractive. Lifetime differences with healthy living individuals (revenues minus costs) were modest: €4840 for obese individuals and €1101 for smokers. Under a simple form of risk equalization these differences were higher, €8542 and €4620 respectively. Improvement of the risk equalization scheme reduced the gap between costs and revenues. Incentives for undesirable risk selection were reduced, but simultaneously incentives for health promotion were weakened. This highlights a new prevention paradox: improving the level playing field for health insurers will inevitably limit their incentives for promoting the health of their clients.

The DYNAMO-HIA Model: An Efficient Implementation of a Risk Factor/Chronic Disease Markov Model for Use in Health Impact Assessment (HIA)

In Health Impact Assessment (HIA), or priority-setting for health policy, effects of risk factors (exposures) on health need to be modeled, such as with a Markov model, in which exposure influences mortality and disease incidence rates. Because many risk factors are related to a variety of chronic diseases, these Markov models potentially contain a large number of states (risk factor and disease combinations), providing a challenge both technically (keeping down execution time and memory use) and practically (estimating the model parameters and retaining transparency). To meet this challenge, we propose an approach that combines micro-simulation of the exposure information with macro-simulation of the diseases and survival. This approach allows users to simulate exposure in detail while avoiding the need for large simulated populations because of the relative rareness of chronic disease events. Further efficiency is gained by splitting the disease state space into smaller spaces, each of which contains a cluster of diseases that is independent of the other clusters. The challenge of feasible input data requirements is met by including parameter calculation routines, which use marginal population data to estimate the transitions between states. As an illustration, we present the recently developed model DYNAMO-HIA (DYNAMIC MODEL for Health Impact Assessment) that implements this approach.

Cost-effectiveness of counseling and pedometer use to increase physical activity in the Netherlands: a modeling study

Background

Counseling in combination with pedometer use has proven to be effective in increasing physical activity and improving health outcomes. We investigated the cost-effectiveness of this intervention targeted at one million insufficiently active adults who visit their general practitioner in the Netherlands.

Methods

We used the RIVM chronic disease model to estimate the long-term effects of increased physical activity on the future health care costs and quality adjusted life years (QALY) gained, from a health care perspective.

Results

The intervention resulted in almost 6000 people shifting to more favorable physical-activity levels, and in 5100 life years and 6100 QALYs gained, at an additional total cost of EUR 67.6 million. The incremental cost-effectiveness ratio (ICER) was EUR 13,200 per life year gained and EUR 11,100 per QALY gained. The intervention has a probability of 0.66 to be cost-effective if a QALY gained is valued at the Dutch informal threshold for cost-effectiveness of preventive intervention of EUR 20,000. A sensitivity analysis showed substantial uncertainty of ICER values.

Conclusion

Counseling in combination with pedometer use aiming to increase physical activity may be a cost-effective intervention. However, the intervention only yields relatively small health benefits in the Netherlands.

Impact of obesity, overweight and underweight on life expectancy and lifetime medical expenditures: the Ohsaki Cohort Study

OBJECTIVES

People who are obese have higher demands for medical care than those of the normal weight people. However, in view of their shorter life expectancy, it is unclear whether obese people have higher lifetime medical expenditure. We examined the association between body mass index, life expectancy and lifetime medical expenditure.

DESIGN

Prospective cohort study using individual data from the Ohsaki Cohort Study.

SETTING

Miyagi Prefecture, northeastern Japan.

PARTICIPANTS

The 41 965 participants aged 40-79 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

The life expectancy and lifetime medical expenditure aged from 40 years.

RESULTS

In spite of their shorter life expectancy, obese participants might require higher medical expenditure than normal weight participants. In men aged 40 years, multiadjusted life expectancy for those who were obese participants was 41.4 years (95% CI 38.28 to 44.70), which was 1.7 years non-significantly shorter than that for normal weight participants (p=0.3184). Multiadjusted lifetime medical expenditure for obese participants was £112 858.9 (94 954.1-131 840.9), being 14.7% non-significantly higher than that for normal weight participants (p=0.1141). In women aged 40 years, multiadjusted life expectancy for those who were obese participants was 49.2 years (46.14-52.59), which was 3.1 years non-significantly shorter than for normal weight participants (p=0.0724), and multiadjusted lifetime medical expenditure was £137 765.9 (123 672.9-152 970.2), being 21.6% significantly higher (p=0.0005).

CONCLUSIONS

According to the point estimate, lifetime medical expenditure might appear to be higher for obese participants, despite their short life expectancy. With weight control, more people would enjoy their longevity with lower demands for medical care.

Estimating net transition probabilities from cross-sectional data with application to risk factors in chronic disease modeling

A problem occurring in chronic disease modeling is the estimation of transition probabilities of moving from one state of a categorical risk factor to another. Transitions could be obtained from a cohort study, but often such data may not be available. However, under the assumption that transitions remain stable over time, age specific cross-sectional prevalence data could be used instead. Problems that then arise are parameter identifiability and the fact that age dependent cross-sectional data are often noisy or are given in age intervals. In this paper we propose a method to estimate so-called net annual transition probabilities from cross-sectional data, including their uncertainties. Net transitions only describe the net inflow or outflow into a certain risk factor state at a certain age. Our approach consists of two steps: first, smooth the data using multinomial P-splines, second, from these data estimate net transition probabilities. This second step can be formulated as a transportation problem, which is solved using the simplex algorithm from linear programming theory. A sensible specification of the cost matrix is crucial to get meaningful results. Uncertainties are assessed by parametric bootstrapping. We illustrate our method using data on body mass index. We conclude that this method provides a flexible way of estimating net transitions and that the use of net transitions has implications for model dynamics, for example when modeling interventions.

Economic evaluation and the postponement of health care costs

The inclusion of medical costs in life years gained in economic evaluations of health care technologies has long been controversial. Arguments in favour of the inclusion of such costs are gaining support, which shifts the question from whether to how to include these costs. This paper elaborates on the issue how to include cost in life years gained in cost effectiveness analysis given the current practice of economic evaluations in which costs of related diseases are included. We combine insights from the theoretical literature on the inclusion of unrelated medical costs in life years gained with insights from the so-called 'red herring' literature. It is argued that for most interventions it would be incorrect to simply add all medical costs in life years gained to an ICER, even when these are corrected for postponement of the expensive last year of life. This is the case since some of the postponement mechanism is already captured in the unadjusted ICER by modelling the costs of related diseases. Using the example of smoking cessation, we illustrate the differences and similarities between different approaches. The paper concludes with a discussion about the proper way to account for medical costs in life years gained in economic evaluations.

If you try to stop smoking, should we pay for it? The cost-utility of reimbursing smoking cessation support in the Netherlands

BACKGROUND

Smoking cessation can be encouraged by reimbursing the costs of smoking cessation support (SCS). The short-term efficiency of reimbursement has been evaluated previously. However, a thorough estimate of the long-term cost-utility is lacking.

OBJECTIVES

To evaluate long-term effects of reimbursement of SCS.

METHODS

Results from a randomized controlled trial were extrapolated to long-term outcomes in terms of health care costs and (quality adjusted) life years (QALY) gained, using the Chronic Disease Model. Our first scenario was no reimbursement. In a second scenario, the short-term cessation rates from the trial were extrapolated directly. Sensitivity analyses were based on the trial's confidence intervals. In the third scenario the additional use of SCS as found in the trial was combined with cessation rates from international meta-analyses.

RESULTS

Intervention costs per QALY gained compared to the reference scenario were approximately euro1200 extrapolating the trial effects directly, and euro4200 when combining the trial's use of SCS with the cessation rates from the literature. Taking all health care effects into account, even costs in life years gained, resulted in an estimated incremental cost-utility of euro4500 and euro7400, respectively. In both scenarios costs per QALY remained below euro16 000 in sensitivity analyses using a life-time horizon.

CONCLUSIONS

Extrapolating the higher use of SCS due to reimbursement led to more successful quitters and a gain in life years and QALYs. Accounting for overheads, administration costs and the costs of SCS, these health gains could be obtained at relatively low cost, even when including costs in life years gained. Hence, reimbursement of SCS seems to be cost-effective from a health care perspective.

Forecasting the effects of obesity and smoking on U.S. life expectancy

BACKGROUND

Although increases in obesity over the past 30 years have adversely affected the health of the U.S. population, there have been concomitant improvements in health because of reductions in smoking. Having a better understanding of the joint effects of these trends on longevity and quality of life will facilitate more efficient targeting of health care resources.

METHODS

For each year from 2005 through 2020, we forecasted life expectancy and quality-adjusted life expectancy for a representative 18-year-old, assuming a continuation of past trends in smoking (based on data from the National Health Interview Survey for 1978 through 1979, 1990 through 1991, 1999 through 2001, and 2004 through 2006) and past trends in body-mass index (BMI) (based on data from the National Health and Nutrition Examination Survey for 1971 through 1975, 1988 through 1994, 1999 through 2002, and 2003 through 2006). The 2003 Medical Expenditure Panel Survey was used to examine the effects of smoking and BMI on health-related quality of life.

RESULTS

The negative effects of increasing BMI overwhelmed the positive effects of declines in smoking in multiple scenarios. In the base case, increases in the remaining life expectancy of a typical 18-year-old are held back by 0.71 years or 0.91 quality-adjusted years between 2005 and 2020. If all U.S. adults became nonsmokers of normal weight by 2020, we forecast that the life expectancy of an 18-year-old would increase by 3.76 life-years or 5.16 quality-adjusted years.

CONCLUSIONS

If past obesity trends continue unchecked, the negative effects on the health of the U.S. population will increasingly outweigh the positive effects gained from declining smoking rates. Failure to address continued increases in obesity could result in an erosion of the pattern of steady gains in health observed since early in the 20th century.

The cost-effectiveness of implementing a new guideline for cardiovascular risk management in primary care in the Netherlands

BACKGROUND

A new Dutch guideline for cardiovascular disease management substantially extends the number of individuals for whom treatment with statins and/or antihypertensive agents is recommended. We estimated the cost-effectiveness of implementing the new guideline at the national level.

METHODS

First, the number of currently untreated individuals who would become eligible for cholesterol-lowering or antihypertensive treatment under the new guideline was estimated using data from a recent population study. Cost-effectiveness of treating this group of patients was then assessed using a mathematical model.

RESULTS

Implementing the guideline in the age category 30-69 years would lead to an additional 465,000 individuals requiring treatment. Over a period of 20 years, the cumulative incidence of acute myocardial infarction in the whole population would drop by 3.0%, that of stroke by 3.9%, and all-cause mortality would drop by 0.9%. The lifetime cost-effectiveness ratio was calculated to be 15,000 Euro per quality-adjusted life year gained. In the age categories 70-79 years and 80 years or above, an additional 600,000 and 450,000 persons, respectively, would need to be treated, resulting in corresponding reductions in cumulative incidences of 14 and 18% (acute myocardial infarction), 17 and 22% (stroke), and 1.2 and 0.6% (all-cause mortality) with cost-effectiveness ratios of 20,800 and 32,300 Euro, respectively, per quality-adjusted life year.

CONCLUSION

Complete implementation of the new guideline would lead to a considerable increase in the number of individuals requiring treatment. This would be cost-effective up to the age of 70 years.

Reduction of smoking in Dutch adolescents over the past decade and its health gains: a repeated cross-sectional study

BACKGROUND

Smoking is the main preventable lifestyle-related risk factor threatening human health. In this study, time trends in smoking behaviour between 1996 and 2005 among adolescents enrolled in secondary school were assessed.

METHODS

In 1996, 2001 and 2005, a survey was conducted in the south-eastern region of the Netherlands. All students in second and fourth year of secondary education (1996: n = 20 000; 2001: n = 27 500; 2005: n = 24 000) were asked to complete a questionnaire about their smoking behaviour. A simulation model was used to estimate lifetime health gains related to the observed trends.

RESULTS

In 1996, 2001 and 2005, the number of questionnaires analysed were 13 554 (68%), 20 767 (76%) and 17 896 (75%), respectively. The results show a decrease in 'ever smoking' as well as 'current smoking' between 1996 and 2005. Among second year high school students, current smoking prevalence decreased from 22.2% in 1996 to 8.0% in 2005 (P(trend) < 0.001). Among fourth year students, current smoking declined from 37.5% in 1996 to 22.0% in 2005 (P(trend) < 0.001). Time trends were not influenced by gender or educational level. Model projections show that if these students not take up smoking later in life, 11 500 new cases of COPD, 3400 new cases of lung cancer and 1800 new cases of myocardial infarction could be prevented for the Dutch 13-year-olds.

CONCLUSION

This study found that, in the past decade, smoking prevalence among adolescents has declined by almost 50%, potentially resulting in a considerable reduction in new cases of COPD or lung cancer.

Cost-effectiveness of lifestyle modification in diabetic patients

OBJECTIVE To explore the potential long-term health and economic consequences of lifestyle interventions for diabetic patients. RESEARCH DESIGN AND METHODS A literature search was performed to identify interventions for diabetic patients in which lifestyle issues were addressed. We selected recent (2003-2008), randomized controlled trials with a minimum follow-up of 12 months. The long-term outcomes for these interventions, if implemented in the Dutch diabetic population, were simulated with a computer-based model. Costs and effects were discounted at, respectively, 4 and 1.5% annually. A lifelong time horizon was applied. Probabilistic sensitivity analyses were performed, taking account of variability in intervention costs and (long-term) treatment effects. RESULTS Seven trials with 147-5,145 participants met our predefined criteria. All interventions improved cardiovascular risk factors at > or =1 year follow-up and were projected to reduce cardiovascular morbidity over lifetime. The interventions resulted in an average gain of 0.01-0.14 quality-adjusted life-years (QALYs) per participant. Health benefits were generally achieved at reasonable costs (< or =euro50,000/QALY). A self-management education program (X-PERT) and physical activity counseling achieved the best results with > or =0.10 QALYs gained and > or =99% probability to be very cost-effective (< or =euro20,000/QALY). CONCLUSIONS Implementation of lifestyle interventions would probably yield important health benefits at reasonable costs. However, essential evidence for long-term maintenance of health benefits was limited. Future research should be focused on long-term effectiveness and multiple treatment strategies should be compared to determine incremental costs and benefits of one over the other.

Cost-effectiveness of an opportunistic screening programme and brief intervention for excessive alcohol use in primary care

BACKGROUND

Effective prevention of excessive alcohol use has the potential to reduce the public burden of disease considerably. We investigated the cost-effectiveness of Screening and Brief Intervention (SBI) for excessive alcohol use in primary care in the Netherlands, which is targeted at early detection and treatment of 'at-risk' drinkers.

METHODOLOGY AND RESULTS

We compared a SBI scenario (opportunistic screening and brief intervention for 'at-risk' drinkers) in general practices with the current practice scenario (no SBI) in The Netherlands. We used the RIVM Chronic Disease Model (CDM) to extrapolate from decreased alcohol consumption to effects on health care costs and Quality Adjusted Life Years (QALYs) gained. Probabilistic sensitivity analysis was employed to study the effect of uncertainty in the model parameters. In total, 56,000 QALYs were gained at an additional cost of 298,000,000 euros due to providing alcohol SBI in the target population, resulting in a cost-effectiveness ratio of 5,400 euros per QALY gained.

CONCLUSION

Prevention of excessive alcohol use by implementing SBI for excessive alcohol use in primary care settings appears to be cost-effective.

Lipid-lowering treatment for all could substantially reduce the burden of macrovascular complications of diabetes patients in the Netherlands

BACKGROUND

We aimed to quantify the potential health benefits of increased use of lipid-lowering treatment (LLT), according to current guidelines, for the Dutch diabetes population.

DESIGN

Simulation study.

METHODS

We compared the long-term health outcomes for a scenario in which all diabetes patients received LLT to those in a 'current practice' scenario, in which 28% received LLT. The model reflected the Dutch diabetes population 40-80 years of age, in 2003. Sensitivity analyses were performed, using more conservative assumptions.

RESULTS

Over the lifetime, LLT for all diabetes patients reduced the expected cumulative incidences of coronary heart disease (CHD) and stroke by, respectively, 6 and 9%. Average life expectancy of Dutch diabetes patients would increase by 0.33 years, ranging from 0.14 years for patients aged 70-79 years, to 0.84 years for patients aged 40-49 years at the start of the simulation. Life-long treatment for patients aged 50-59 contributed most to the life years gained (55,000 out of 146,000). With reduced effectiveness of LLT and fewer patients starting LLT, the cumulative incidences of both CHD and stroke would decrease by approximately 2%. The number needed to treat to prevent one incident case of cardiovascular disease over lifetime was 20 for CHD and 44 for stroke.

CONCLUSION

This simulation study shows that increased use of LLT can substantially reduce the expected future burden of CHD and stroke in the Dutch diabetes population.

Healthcare costs and obesity prevention: drug costs and other sector-specific consequences

BACKGROUND

Obesity is a major contributor to the overall burden of disease (also reducing life expectancy) and associated with high medical costs due to obesity-related diseases. However, obesity prevention, while reducing obesity-related morbidity and mortality, may not result in overall healthcare cost savings because of additional costs in life-years gained. Sector-specific financial consequences of preventing obesity are less well documented, for pharmaceutical spending as well as for other healthcare segments.

OBJECTIVE

To estimate the effect of obesity prevention on annual and lifetime drug spending as well as other sector-specific expenditures, i.e. the hospital segment, long-term care segment and primary healthcare.

METHODS

The RIVM (Dutch National Institute for Public Health and the Environment) Chronic Disease Model and Dutch cost of illness data were used to simulate, using a Markov-type model approach, the lifetime expenditures in the pharmaceutical segment and three other healthcare segments for a hypothetical cohort of obese (body mass index [BMI] >or=30 kg/m2), non-smoking people with a starting age of 20 years. In order to assess the sector-specific consequences of obesity prevention, these costs were compared with the costs of two other similar cohorts, i.e. a 'healthy-living' cohort (non-smoking and a BMI >or=18.5 and <25 kg/m2) and a smoking cohort. To assert whether preventing obesity results in cost savings in any of the segments, net present values were estimated using different discount rates. Sensitivity analyses were conducted across key input values and using a broader definition of healthcare.

RESULTS

Lifetime drug expenditures are higher for obese people than for 'healthy-living' people, despite shorter life expectancy for the obese. Obesity prevention results in savings on drugs for obesity-related diseases until the age of 74 years, which outweigh additional drug costs for diseases unrelated to obesity in life-years gained. Furthermore, obesity prevention will increase long-term care expenditures substantially, while savings in the other healthcare segments are small or non-existent. Discounting costs more heavily or using lower relative mortality risks for obesity would make obesity prevention a relatively more attractive strategy in terms of healthcare costs, especially for the long-term care segment. Application of a broader definition of healthcare costs has the opposite effect.

CONCLUSIONS

Obesity prevention will likely result in savings in the pharmaceutical segment, but substantial additional costs for long-term care. These are important considerations for policy makers concerned with the future sustainability of the healthcare system.

Cost-effectiveness of a low-calorie diet and orlistat for obese persons: modeling long-term health gains through prevention of obesity-related chronic diseases

OBJECTIVE

Our study estimated the cost-effectiveness of pharmacologic treatment of obesity in combination with a low-calorie diet in The Netherlands.

METHODS

Costs and effects of a low-calorie diet-only intervention and of a low-calorie diet in combination with 1 year of orlistat were compared to no treatment. The RIVM Chronic Disease Model was used to project the differences in quality adjusted life years (QALYs) and lifetime health-care costs because of the effects of the interventions on body mass index (BMI) status. This was done by linking BMI status to the occurrence of obesity-related diseases and by relating quality of life to disease status. Probabilistic sensitivity analysis was employed to study the effect of uncertainty in the model parameters. In univariate sensitivity analysis, we assessed how sensitive the results were to several key assumptions.

RESULTS

Incremental costs per QALY gained were Euro 17,900 for the low-calorie diet-only intervention compared to no intervention and Euro 58,800 for the low-calorie diet + orlistat compared to the low-calorie diet only. Assuming a direct relation between BMI and quality of life, these ratios decreased to Euro 6000 per QALY gained and Euro 24,100 per QALY gained. Costs per QALY gained were also sensitive to assumptions about long-term weight loss maintenance.

CONCLUSIONS

Cost-effectiveness ratios of interventions aiming at weight reduction depend strongly on assumptions regarding the relation between BMI and quality of life. We recommend that a low-calorie diet should be the first option for policymakers in combating obesity.

The cost-effectiveness of increasing alcohol taxes: a modelling study

BACKGROUND

Excessive alcohol use increases risks of chronic diseases such as coronary heart disease and several types of cancer, with associated losses of quality of life and life-years. Alcohol taxes can be considered as a public health instrument as they are known to be able to decrease alcohol consumption. In this paper, we estimate the cost-effectiveness of an alcohol tax increase for the entire Dutch population from a health-care perspective focusing on health benefits and health-care costs in alcohol users.

METHODS

The chronic disease model of the National Institute for Public Health and the Environment was used to extrapolate from decreased alcohol consumption due to tax increases to effects on health-care costs, life-years gained and quality-adjusted life-years gained, A Dutch scenario in which tax increases for beer are planned, and a Swedish scenario representing one of the highest alcohol taxes in Europe, were compared with current practice in the Netherlands. To estimate cost-effectiveness ratios, yearly differences in model outcomes between intervention and current practice scenarios were discounted and added over the time horizon of 100 years to find net present values for incremental life-years gained, quality-adjusted life-years gained, and health-care costs.

RESULTS

In the Swedish scenario, many more quality-adjusted life-years were gained than in the Dutch scenario, but both scenarios had almost equal incremental cost-effectiveness ratios: 5100 euros per quality-adjusted life-year and 5300 euros per quality-adjusted life-year, respectively.

CONCLUSION

Focusing on health-care costs and health consequences for drinkers, an alcohol tax increase is a cost-effective policy instrument.

Cost-effectiveness of pharmacological anti-obesity treatments: a systematic review

AIM

To review economic evaluations of weight loss drugs and compare reported incremental cost-effectiveness ratios (ICERs).

METHODS

A literature search was conducted for cost-effectiveness (CEAs) and cost-utility analyses (CUAs) of sibutramine, orlistat and rimonabant.

RESULTS

Fourteen unique articles were identified (11 CUAs and 3 CEAs; 9 orlistat, 4 sibutramine and 1 rimonabant). All used diet and exercise as comparator, whereas none included indirect costs. Time horizons varied from treatment period only (1-4 years) to 80 years (median 7.5 years). Longer studies modeled effects on diabetes, micro- and macrovascular complications, coronary heart disease and death. Of the CUAs, the median ICER was 16,000 euro(2007)/QALY (quality-adjusted life-year; range 10,000-88,000), with the worst cost-effectiveness when recommended stop rules for non-responding patients were not applied. All studies but three were funded by the manufacturing company, and the median ICER was considerably higher for independent than for sponsored analyses (62,000 euro vs 15,000 euro/QALY). However, two of the three independent CUAs did not use recommended stop rules, as compared with one of eight manufacturer-sponsored analyses. The results were most sensitive to assumptions regarding weight loss sustainability and utility per kilogram lost. Side effects and dropout because of reasons other than lack of efficacy were generally not incorporated.

CONCLUSION

Published economic evaluations indicate that orlistat, sibutramine and rimonabant are within the range of what is generally regarded as cost-effective. Uncertainty remains about weight loss sustainability, utility gain associated with weight loss and extrapolations from transient weight loss to long-term health benefits. Modeling of head-to-head comparisons and attrition is needed, as are analyses conducted independently of manufacturing companies.

Lifetime medical costs of obesity: prevention no cure for increasing health expenditure

BACKGROUND

Obesity is a major cause of morbidity and mortality and is associated with high medical expenditures. It has been suggested that obesity prevention could result in cost savings. The objective of this study was to estimate the annual and lifetime medical costs attributable to obesity, to compare those to similar costs attributable to smoking, and to discuss the implications for prevention.

METHODS AND FINDINGS

With a simulation model, lifetime health-care costs were estimated for a cohort of obese people aged 20 y at baseline. To assess the impact of obesity, comparisons were made with similar cohorts of smokers and "healthy-living" persons (defined as nonsmokers with a body mass index between 18.5 and 25). Except for relative risk values, all input parameters of the simulation model were based on data from The Netherlands. In sensitivity analyses the effects of epidemiologic parameters and cost definitions were assessed. Until age 56 y, annual health expenditure was highest for obese people. At older ages, smokers incurred higher costs. Because of differences in life expectancy, however, lifetime health expenditure was highest among healthy-living people and lowest for smokers. Obese individuals held an intermediate position. Alternative values of epidemiologic parameters and cost definitions did not alter these conclusions.

CONCLUSIONS

Although effective obesity prevention leads to a decrease in costs of obesity-related diseases, this decrease is offset by cost increases due to diseases unrelated to obesity in life-years gained. Obesity prevention may be an important and cost-effective way of improving public health, but it is not a cure for increasing health expenditures.

Dynamic effects of smoking cessation on disease incidence, mortality and quality of life: The role of time since cessation

Background

To support health policy makers in setting priorities, quantifying the potential effects of tobacco control on the burden of disease is useful. However, smoking is related to a variety of diseases and the dynamic effects of smoking cessation on the incidence of these diseases differ. Furthermore, many people who quit smoking relapse, most of them within a relatively short period.

Methods

In this paper, a method is presented for calculating the effects of smoking cessation interventions on disease incidence that allows to deal with relapse and the effect of time since quitting. A simulation model is described that links smoking to the incidence of 14 smoking related diseases. To demonstrate the model, health effects are estimated of two interventions in which part of current smokers in the Netherlands quits smoking.

To illustrate the advantages of the model its results are compared with those of two simpler versions of the model. In one version we assumed no relapse after quitting and equal incidence rates for all former smokers. In the second version, incidence rates depend on time since cessation, but we assumed still no relapse after quitting.

Results

Not taking into account time since smoking cessation on disease incidence rates results in biased estimates of the effects of interventions. The immediate public health effects are overestimated, since the health risk of quitters immediately drops to the mean level of all former smokers. However, the long-term public health effects are underestimated since after longer periods of time the effects of past smoking disappear and so surviving quitters start to resemble never smokers. On balance, total health gains of smoking cessation are underestimated if one does not account for the effect of time since cessation on disease incidence rates. Not taking into account relapse of quitters overestimates health gains substantially.

Conclusion

The results show that simulation models are sensitive to assumptions made in specifying the model. The model should be specified carefully in accordance with the questions it is supposed to answer. If the aim of the model is to estimate effects of smoking cessation interventions on mortality and morbidity, one should include relapse of quitters and dependency on time since cessation of incidence rates of smoking-related chronic diseases. A drawback of such models is that data requirements are extensive.