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. 2016 Aug 5:16:734.
doi: 10.1186/s12889-016-3299-z.

Potential health gains and health losses in eleven EU countries attainable through feasible prevalences of the life-style related risk factors alcohol, BMI, and smoking: a quantitative health impact assessment

Stefan K Lhachimi  1   2   3   4 , Wilma J Nusselder  5 , Henriette A Smit  6   7 , Paolo Baili  8 , Kathleen Bennett  9 , Esteve Fernández  10   11 , Margarete C Kulik  5   7 , Tim Lobstein  12 , Joceline Pomerleau  13 , Hendriek C Boshuizen  14   15 , Johan P Mackenbach  5
Affiliations

Potential health gains and health losses in eleven EU countries attainable through feasible prevalences of the life-style related risk factors alcohol, BMI, and smoking: a quantitative health impact assessment

Stefan K Lhachimi et al. BMC Public Health. .

Abstract

Background: Influencing the life-style risk-factors alcohol, body mass index (BMI), and smoking is an European Union (EU) wide objective of public health policy. The population-level health effects of these risk-factors depend on population specific characteristics and are difficult to quantify without dynamic population health models.

Methods: For eleven countries-approx. 80 % of the EU-27 population-we used evidence from the publicly available DYNAMO-HIA data-set. For each country the age- and sex-specific risk-factor prevalence and the incidence, prevalence, and excess mortality of nine chronic diseases are utilized; including the corresponding relative risks linking risk-factor exposure causally to disease incidence and all-cause mortality. Applying the DYNAMO-HIA tool, we dynamically project the country-wise potential health gains and losses using feasible, i.e. observed elsewhere, risk-factor prevalence rates as benchmarks. The effects of the "worst practice", "best practice", and the currently observed risk-factor prevalence on population health are quantified and expected changes in life expectancy, morbidity-free life years, disease cases, and cumulative mortality are reported.

Results: Applying the best practice smoking prevalence yields the largest gains in life expectancy with 0.4 years for males and 0.3 year for females (approx. 332,950 and 274,200 deaths postponed, respectively) while the worst practice smoking prevalence also leads to the largest losses with 0.7 years for males and 0.9 year for females (approx. 609,400 and 710,550 lives lost, respectively). Comparing morbidity-free life years, the best practice smoking prevalence shows the highest gains for males with 0.4 years (342,800 less disease cases), whereas for females the best practice BMI prevalence yields the largest gains with 0.7 years (1,075,200 less disease cases).

Conclusion: Smoking is still the risk-factor with the largest potential health gains. BMI, however, has comparatively large effects on morbidity. Future research should aim to improve knowledge of how policies can influence and shape individual and aggregated life-style-related risk-factor behavior.

Keywords: Alcohol; BMI; Health impact assessment; Life-style related risk-factors; Modeling; Smoking.

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Figures

Fig. 1
Fig. 1
Life expectancy*. a Potential gains in life expectancy. b Potential losses in life expectancy. Potential gains in life expectancy (Panel a) and potential losses in life expectancy (Panel b) as measured by the differences in period life expectancy after ten years for each country and all eleven countries (EU-11) combined by risk-factor and sex compared with the reference scenario. *No smoking data for Poland
Fig. 2
Fig. 2
Morbidity-free life years*. a Potential gains in morbidity-free life years. b Potential losses in morbidity-free life years. Potential gains in morbidity-free life years (Panel a) and potential losses in morbidity-free life years (Panel b) as measured by the differences in disease-free life years after ten years for each country and all eleven countries (EU-11) combined by risk-factor and sex compared with the reference scenario. *No smoking data for Poland
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