Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-28T10:53:39.889Z Has data issue: false hasContentIssue false

To what extent could cardiovascular diseases be reduced if Germany applied fiscal policies to increase fruit and vegetable consumption? A quantitative health impact assessment

Published online by Cambridge University Press:  14 July 2020

Johanna-Katharina Schönbach*
Affiliation:
Institute of Public Health and Nursing Research, University of Bremen, Bremen, Germany Research Group for Evidence Based Public Health, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
Stefan K Lhachimi
Affiliation:
Institute of Public Health and Nursing Research, University of Bremen, Bremen, Germany Research Group for Evidence Based Public Health, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany
*
*Corresponding author:[email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objective:

This study aimed to dynamically model and quantify expected health effects of four scenarios: (i) a reference scenario with an unchanged fruit and vegetable intake, (ii) the removal of value-added tax (VAT) on fruits and vegetables, (iii) the implementation of a 20 % subsidy on fruits and vegetables and (iv) a guideline scenario with a population-wide fruit and vegetable intake of five portions per day.

Design:

Baseline fruit and vegetable intake data was derived from the GEDA 2012 study. We used price elasticities for Germany to calculate the change in fruit and vegetable consumption under the zero VAT and the 20 % subsidy scenario. All scenarios were modelled over a 10-year projection period using DYNAMO-HIA.

Setting:

Germany.

Participants:

A projected real-life population.

Results:

Cumulated over the 10-year projection period, an estimated 4450 incident ischaemic heart disease (IHD) cases, 7010 stroke cases and 13 960 deaths would be prevented under the zero VAT scenario. Under the 20 % subsidy scenario, 17 990 incident IHD cases, 27 390 stroke cases and 54 880 deaths would be averted. Although this corresponds to only a fraction of the incidents that would occur under the reference scenario, the averted cases translate to 2 % (for the zero VAT scenario) and 9 % (for the 20 % subsidy scenario) of IHD, stroke and death cases that would be prevented if the whole population consumed the recommended five portions of fruits and vegetables per day.

Conclusions:

Fiscal policies on fruits and vegetables provide a non-negligible step towards the removal of the health burden induced by low fruit and vegetable intake.

Type
Research paper
Creative Commons
Creative Common License - CCCreative Common License - BY
Published by Cambridge University Press on behalf of The Nutrition Society. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Authors 2020

Fruit and vegetable intake reduces the risk of ischaemic heart disease (IHD) and stroke(Reference Boeing, Bechthold and Bub1). For a healthy diet, the WHO recommends consuming 400 g (i.e. five 80-g portions) per day(2). Nevertheless, Eurostat data shows that only 14·3 % of the EU-28 population reach this recommendation(3).

According to the German nutrition report from 2019, 29 % of the population do not even consume fruits and vegetables on a daily basis(4). The Federal Ministry of Food and Agriculture that published the report generally emphasises an individual’s self-responsibility to eat healthily. Its National Action Plan suggests a range of programmes and projects that encourage the dissemination of information as well as the creation of structures for healthy lifestyles in schools, workplaces and the community, whereas fiscal policies are not included(5).

Notwithstanding, measures targeting informed choice (individual-based education, public information campaigns) have shown only weak effectiveness to improve diet(Reference Brambila-Macias, Shankar and Capacci6Reference Hyseni, Atkinson and Bromley8). Additionally, individual-based information and education appear to increase socioeconomic inequalities in diet(Reference McGill, Anwar and Orton9), because they build on individuals’ resources(Reference Adams, Mytton and White10). In contrast, fiscal measures have shown stronger evidence for success(Reference Brambila-Macias, Shankar and Capacci6,Reference Hyseni, Atkinson and Bromley8) and may decrease socioeconomic inequalities(Reference McGill, Anwar and Orton9).

The use of economic tools, such as targeted subsidies and taxes, has been recommended by the WHO in its European Food and Nutrition Action Plan 2015–20(11). In fact, experimental and observational studies have already found that subsidies on healthier foods, such as fruits and vegetables, modify dietary behaviour in the desired direction(Reference An12Reference Thow, Downs and Jan15). However, the assessment of expected health impacts from a potential fruit and vegetable price change has relied on simulation studies so far. Health effects have previously been modelled in the form of a 1 %(Reference Cash, Sunding and Zilberman16), 10 % and a 30 % subsidy on fruits and vegetables in the United States(Reference Pearson-Stuttard, Bandosz and Rehm17Reference Penalvo, Cudhea and Micha19), a 20 % subsidy in New Zealand(Reference Ni Mhurchu, Eyles and Genc20), as well as a subsidy of $0·14 per 100 g on fruits and vegetables in Australia(Reference Cobiac, Tam and Veerman21). With regard to value-added tax (VAT) changes, it was estimated that halving the VAT rate on fruits and vegetables (from 25 to 12·5 %) would save 367·2 disability-adjusted life years in the Danish population(Reference Holm, Laursen and Koch22). Similarly, a 3·4 % reduction in VAT would avoid 363 deaths and save 5024 life-years in the French population(Reference Dallongeville, Dauchet and de Mouzon23).

For Germany, it had been estimated that reducing the German VAT rate for fruits and vegetables from the current 7 to 0 % and increasing the VAT rate of unhealthy foods from 7 to 19 % according to a traffic light system could decrease obesity by 3 % in females and 8 % in males(Reference Effertz24,25) .

The aim of this study was to further quantify the prevention potential of fiscal policies on fruits and vegetables – in this case on the health outcomes of IHD, stroke and deaths. We therefore project two specific fruit and vegetable subsidies over a period of 10 years, in comparison to a reference scenario (in which intake remains unchanged) and a guideline scenario (in which everyone in the population consumes the recommended five portions of fruits and vegetables per day).

Methods

Scenarios

We ran four scenarios: (i) In the reference scenario, we assumed the fruit and vegetable intake would remain unchanged. (ii) The zero VAT scenario hypothesised that the VAT for fruits and vegetables would be reduced from the current 7 to 0 %, translating into a price decrease of 6·54 %. (iii) In the 20 % subsidy scenario, we presumed a subsidy on fruits and vegetables of 20 %, as has previously been the subject of research for New Zealand(Reference Ni Mhurchu, Eyles and Genc20). (iv) Under the guideline scenario, the whole population is supposed to consume the recommended five portions of fruits and vegetables per day(2).

Price elasticities

Price elasticities express the percentage change in demand in response to a 1 % change in price(Reference Nghiem, Wilson and Genc26) and have likewise been applied in similar studies(Reference Penalvo, Cudhea and Micha19,Reference Cobiac, Tam and Veerman21,Reference Dallongeville, Dauchet and de Mouzon23,Reference Lhachimi, Cole and Nusselder27) . Thus, we used Germany-specific own-price elasticities taken from literature(Reference Thiele28) to estimate what impact the respective price changes induced by the zero VAT scenario and the 20 % subsidy scenario would have on fruit and vegetable demand. According to these price elasticities, the zero VAT scenario with a fruit and vegetable price reduction of 6·54 % would increase fruit intake by 5·2 % and vegetable intake by 3·6 % (see Table 1). The 20 % subsidy scenario with its 20 % price decrease would lead to a 16 % increase in fruit intake and a 11 % increase in vegetable intake (see Table 1).

Table 1 Uncompensated (Marshallian) own-price elasticities from Thiele 2008(Reference Thiele28)

Fruit and vegetable intake over scenarios

For the reference scenario, we derived individual fruit as well as vegetable intake from 19 189 persons who gave complete fruit and vegetable information in the public use file of the German Health Update study 2012 (GEDA 2012)(29). GEDA 2012 was carried out between March 2012 and March 2013 by the Robert Koch Institute(Reference Lange, Jentsch and Allen30). In the survey, fruit and vegetable intake was assessed separately. Participants were asked whether they consumed fruits and vegetables, respectively, ‘every day’, ‘at least once per week’, ‘less than once per week’ or ‘never’. If they stated they consume fruits or vegetables every day, they were asked to report the number of daily portions. If they stated they consume the respective item at least once per week, they were asked to report the number of weekly portions, which we then converted to the number of daily portions. For fruits, the weighted mean intake was 1·17 portions per day. For vegetables, the weighted mean intake was 0·93 portion per day.

For the zero VAT and 20 % subsidy scenarios, we applied the intake change as estimated by the price elasticities to the individual fruit and vegetable intake data as observed under the reference scenario.

In order to obtain a combined fruit and vegetable variable per scenario, we added the portions of fruits and vegetables per person. This intake variable was then categorised into 0 to ≤0·5 portions, >0·5 to ≤1·5 portions, >1·5 to ≤2·5 portions, >2·5 to ≤3·5 portions, >3·5 to ≤4·5 portions and >4·5 portions for males and females and four age groups (18–29, 30–44, 45–64, 65+). For the guideline scenario, we assumed everyone to be in the category of >4·5 portions. The fruit and vegetable intake over all four scenarios is illustrated in Fig. 1. Finally, we smoothed the intake proportions over age using multinomial P-splines(Reference van de Kassteele, Hoogenveen and Engelfriet31,Reference Lhachimi, Nusselder and Lobstein32) .

Fig. 1 Fruit and vegetable intake over scenarios, before smoothing over age. , 0 to ≤0·5 portions; , >0·5 to ≤1·5 portions; , >1·5 to ≤2·5 portions; , >2·5 to ≤3·5 portions; , >3·5 to ≤4·5 portions; , >4·5 portions

Relationship between fruit and vegetable intake and health outcomes

Relative risks per 200 g of fruits and vegetables per day for all-cause mortality, IHD and stroke were based on a published meta-analysis(Reference Aune, Giovannucci and Boffetta33). Our intake category-specific relative risks (>0·5 to ≤1·5 portions, >1·5 to ≤2·5 portions, >2·5 to ≤3·5 portions, >3·5 to ≤4·5 portions and >4·5 portions) are presented in Table 2.

Table 2 Relative risks for fruits and vegetables

IHD, ischaemic heart disease.

Population and disease data

We derived Germany’s age- and sex-specific population size, mortality, projected births, as well as prevalence, incidence and excess mortality for IHD and stroke from the DYNAMO-HIA database. The database is freely available on the project’s website (https://www.dynamo-hia.eu)(Reference Lhachimi, Nusselder and Smit34) and has been used in several studies(Reference Kulik, Nusselder and Boshuizen35Reference Fischer and Kraemer37).

Health outcome assessment: DYNAMO-HIA

The DYNAMO-HIA software tool(Reference Lhachimi, Nusselder and Smit34,Reference Boshuizen, Lhachimi and van Baal38,Reference Lhachimi, Nusselder and Boshuizen39) was used to project a real-life population under all four scenarios through fruit and vegetable intake biographies and associated diseases. In our analysis, we ran a projection period of 10 years, and compared deaths as well as incident and prevalent IHD and stroke cases among males and females between the four scenarios. DYNAMO-HIA has previously been used to model health impacts following changes in risk factors, such as alcohol consumption(Reference Lhachimi, Cole and Nusselder27), smoking(Reference Kulik, Nusselder and Boshuizen35,Reference Holm, Bronnum-Hansen and Robinson40,Reference Kang41) and second-hand smoke(Reference Fischer and Kraemer37), BMI(Reference Lhachimi, Nusselder and Lobstein32), salt intake(Reference Hendriksen, van Raaij and Geleijnse36,Reference Erkoyun, Sozmen and Bennett42) and physical activity(Reference Mansfield and MacDonald Gibson43).

Results

The difference in incident and prevalent IHD and stroke cases between the reference, zero VAT, 20 % subsidy as well as the guideline scenario over the projection period is illustrated in Table 3. The difference in deaths between scenarios is illustrated in Table 4.

Table 3 Incident and prevalent cases of IHD and stroke

IHD, ischaemic heart disease; Ref, reference scenario; VAT, value-added tax.

Table 4 Number of deaths

Ref, reference scenario; VAT, value-added tax.

Ischaemic heart disease, stroke and death incidents after the first year of projection

Under the reference scenario, that is, an unchanged fruit and vegetable intake, 257 090 incident IHD cases, 171 260 incident stroke cases and 748 060 deaths would occur by the end of the first year of projection. In comparison to the reference scenario, the zero VAT scenario would prevent 510 (0·2 %) IHD cases, 730 (0·4 %) stroke cases and 1570 (0·2 %) deaths. At the same time, the 20 % subsidy scenario would prevent 2010 (0·8 %) incident IHD cases, 2830 (1·7 %) stroke cases and 6130 (0·8 %) deaths. Under the assumption that the whole population would consume the recommended five portions of fruits and vegetables per day, as illustrated by the guideline scenario, the number of incident IHD and stroke cases would be reduced by 23 080 (9·0 %) and 30 510 (17·8 %), respectively, and there would be 67 560 (9·0 %) fewer deaths. Thereby, the prevented IHD, stroke and death cases under the zero VAT scenario correspond to 2·2–2·4 % of prevented cases under the guideline scenario, while the prevented IHD, stroke and death cases under the 20 % subsidy scenario correspond to 8·7–9·3 %.

Ischaemic heart disease, stroke and death incidents cumulated over 10-year projection period

Under the reference scenario, the cumulative number of incidences would sum up to 2 766 070 IHD cases, 1 894 350 stroke cases and 8 506 500 deaths over the projection period of 10 years. The zero VAT scenario would prevent 4450 (0·2 %) of these incident IHD cases, 7010 (0·4 %) of these stroke cases and 13 960 (0·2 %) of these deaths. This translates to 2·1, 2·3 and 2·2 % of IHD, stroke and death cases that could be reduced under the guideline scenario, that is, if the whole population consumed the recommended five portions of fruits and vegetables per day. The 20 % subsidy scenario would prevent 17 990 (0·7 %) incident IHD cases, 27 390 (1·4 %) incident stroke cases and 54 880 (0·6 %) deaths, compared to the reference scenario. This translates to 8·5, 9·0 and 8·7 % of IHD, stroke and death cases that could maximally be prevented, that is, if the whole population consumed the recommended five portions of fruits and vegetables per day.

Prevalent cases of ischaemic heart disease and stroke in projection year 10

In projection year 10, there would be 3 694 480 (4·6 %) prevalent IHD cases and 1 600 050 (2·0 %) prevalent stroke cases if fruit and vegetable intake remained unchanged. 1300 fewer prevalent IHD and 3410 fewer prevalent stroke cases could be expected under the zero VAT scenario, which represents 1·8 and 2·2 % of what could be achieved under the guideline scenario. Under the 20 % subsidy scenario, there would be an estimated 5780 and 13 680 fewer prevalent IHD and stroke cases, which represents 7·8 and 8·9 % of what could be achieved under the guideline scenario.

Discussion

In order to quantify the prevention potential of fiscal policies targeting fruits and vegetables, we modelled health impacts following two fruit and vegetable subsidies, in comparison to an unchanged fruit and vegetable intake and a population-wide fruit and vegetable intake of five portions per day.

Our results show that the cumulated 4450 incident IHD cases, 7010 stroke cases and 13 960 deaths that would be averted under the zero VAT scenario over the 10-year projection period only prevent a fraction of the incidents that would occur under the reference scenario. Nonetheless, they translate to around 2 % of what could be maximally be reduced if the whole population consumed the recommended five portions of fruits and vegetables per day. Similarly, the 17 990 incident IHD cases, 27 390 stroke cases and 54 880 deaths cases that would be avoided under the 20 % subsidy scenario, cumulatively over 10 years, only prevent around one in a hundred incidents that would occur under the reference scenario. Nevertheless, this translates to around 9 % of what could maximally be reduced if the whole population consumed the recommended five portions of fruits and vegetables per day.

The number of prevented IHD, stroke and death cases over all scenarios is similar for males and females, except for the guideline scenario, which represents the health benefits that could maximally be achieved with any fruit and vegetable intervention.

DYNAMO-HIA is in established tool for health impact assessments(Reference Lhachimi, Cole and Nusselder27,Reference Lhachimi, Nusselder and Lobstein32,Reference Kulik, Nusselder and Boshuizen35Reference Fischer and Kraemer37,Reference Holm, Bronnum-Hansen and Robinson40Reference Mansfield and MacDonald Gibson43) . In the following, we discuss the input data used for this health impact assessment.

Fruit and vegetable intake data were derived from GEDA 2012, even though a more recent wave (GEDA 2014/15-EHIS) is now available. This was decided because the more recent GEDA 2014/15-EHIS public use file only reports the consumed portions for people who stated they consume fruits and vegetables at least daily. In contrast, the GEDA 2012 public use file additionally reports the consumed portions for people who stated they consume fruits and vegetables less frequently, that is, once per week.

We used price elasticities specific to the German context(Reference Thiele28). These have previously been used in a similar study, which estimated the effect that removing the VAT on fruits and vegetables would have on obesity(Reference Effertz24). The price elasticities we used (–0·80 for fruits, –0·55 for vegetables) are similar to those presented in a systematic review for the US context (–0·70 for fruits, 0·58 for vegetables)(Reference Andreyeva, Long and Brownell44) as well as to those for the UK context (–0·70 for fruits, –0·63 for vegetables)(Reference Tiffin, Balcombe and Salois45).

It was not possible to consider cross-price elasticities in this model because the DYNAMO-HIA tool only allows for the use of one risk factor at a time. Cross-price elasticities indicate that a 10 % price reduction for fruits would increase the demand for meat by 0·3 %, for vegetables by 1·3 %, for cereals by 0·8 %, and decrease the demand for potatoes/rice/noodles by 0·4 %. A 10 % price reduction for vegetables would increase the demand for meat by 0·7 %, for fruits by 0·9 %, for potatoes/rice/noodles by 0·4 %, for cereals by 0·6 %, and decrease the demand for milk products by 0·1 %(Reference Thiele28). The inclusion of cross-price elasticities is therefore unlikely to change our results.

There is possible evidence that fruit and vegetable intake prevents body weight gain(Reference Boeing, Bechthold and Bub1) and reduces overweight and obesity(Reference Schlesinger, Neuenschwander and Schwedhelm46). Further, there is convincing evidence that fruit and vegetable intake has a BP-lowering effect(Reference Boeing, Bechthold and Bub1) and reduces the risk for hypertension(Reference Schwingshackl, Schwedhelm and Hoffmann47). Even though these risk factors for IHD and stroke were not separately incorporated into our simulation, it can be expected that the VAT removal on fruits and vegetables would simultaneously contribute to lower levels of obesity and hypertension.

Finally, relative risks for cancer were not included in our simulation. Previous literature has shown that increasing the intake of fruits and vegetables to the recommended level of 500 g/d in France, Germany, the Netherlands, Spain and Sweden would prevent 398 out of 211 708 fruit- and vegetable-related cancer cases in 2050(Reference Soerjomataram, Oomen and Lemmens48). Therefore, we can assume that the VAT removal on fruits and vegetables would have additional health benefits due to prevented cancer cases.

Conclusion

Fiscal policies on fruits and vegetables provide a non-negligible step towards the removal of the health burden induced by low fruit and vegetable intake.

Acknowledgements

Acknowledgements: None. Financial support: This research received no specific grant from any funding agency, commercial or not-for-profit sectors. Conflict of interest: None. Authorship: Both authors contributed to conception and design. J.-K.S . prepared the data and conducted the health impact assessment. Both authors interpreted the results. J.-K.S. wrote the manuscript. S.K.L. critically revised the manuscript. Both authors approved the version to be published. Ethics of human subject participation: Ethical approval was not required.

References

Boeing, H, Bechthold, A, Bub, A et al. (2012) Critical review: vegetables and fruit in the prevention of chronic diseases. Eur J Nutr 51, 637663.CrossRefGoogle ScholarPubMed
World Health Organization (2003) Diet, Nutrition and the Prevention of Chronic Diseases. WHO Technical Report. In Series. Geneva, Switzerland.Google Scholar
European Union, Eurostat (2014) Daily consumption of fruit and vegetables by sex, age and income quintile. https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=hlth_ehis_fv3i&lang=en (accessed June 2020).Google Scholar
Federal Ministry of Food and Agriculture (2019) Deutschland, wie es isst. Der BMEL-Ernährungsreport 2019 [Germany, How It Eats. The BMEL Nutrition Report 2019]. Berlin: Federal Ministry of Food and Agriculture.Google Scholar
Federal Ministry of Food Agriculture and Consumer Protection & Federal Ministry of Health (2013) IN FORM. German National Initiative to Promote Healthy Diets and Physical Activity. Berlin: Federal Ministry of Food, Agriculture and Consumer Protection.Google Scholar
Brambila-Macias, J, Shankar, B, Capacci, S et al. (2011) Policy interventions to promote healthy eating: a review of what works, what does not, and what is promising. Food Nutr Bull 32, 365375.CrossRefGoogle ScholarPubMed
Cobiac, LJ, Vos, T & Veerman, JL (2010) Cost-effectiveness of interventions to promote fruit and vegetable consumption. PLoS ONE 5, e14148.CrossRefGoogle ScholarPubMed
Hyseni, L, Atkinson, M, Bromley, H et al. (2017) The effects of policy actions to improve population dietary patterns and prevent diet-related non-communicable diseases: scoping review. Eur J Clin Nutr 71, 694711.CrossRefGoogle ScholarPubMed
McGill, R, Anwar, E, Orton, L et al. (2015) Are interventions to promote healthy eating equally effective for all? Systematic review of socioeconomic inequalities in impact. BMC Public Health 15, 457.CrossRefGoogle ScholarPubMed
Adams, J, Mytton, O, White, M et al. (2016) Why are some population interventions for diet and obesity more equitable and effective than others? The role of individual agency. PLoS Med 13, e1001990.CrossRefGoogle ScholarPubMed
World Health Organization (2015) European Food and Nutrition Action Plan 2015–2020. Copenhagen: WHO Regional office for Europe.Google Scholar
An, R (2013) Effectiveness of subsidies in promoting healthy food purchases and consumption: a review of field experiments. Public Health Nutr 16, 12151228.CrossRefGoogle ScholarPubMed
Gittelsohn, J, Trude, ACB & Kim, H (2017) Pricing strategies to encourage availability, purchase, and consumption of healthy foods and beverages: a systematic review. Prev Chronic Dis 14, E107.CrossRefGoogle ScholarPubMed
Afshin, A, Penalvo, JL, Del Gobbo, L et al. (2017) The prospective impact of food pricing on improving dietary consumption: a systematic review and meta-analysis. PLoS One 12, e0172277.CrossRefGoogle ScholarPubMed
Thow, AM, Downs, S & Jan, S (2014) A systematic review of the effectiveness of food taxes and subsidies to improve diets: understanding the recent evidence. Nutr Rev 72, 551565.CrossRefGoogle ScholarPubMed
Cash, SB, Sunding, DL & Zilberman, D (2005) Fat taxes and thin subsidies: prices, diet, and health outcomes. Acta Agric Scand Sect C Food Econ 2, 167174.Google Scholar
Pearson-Stuttard, J, Bandosz, P, Rehm, CD et al. (2017) Comparing effectiveness of mass media campaigns with price reductions targeting fruit and vegetable intake on US cardiovascular disease mortality and race disparities. Am J Clin Nutr 106, 199206.CrossRefGoogle ScholarPubMed
Pearson-Stuttard, J, Bandosz, P, Rehm, CD et al. (2017) Reducing US cardiovascular disease burden and disparities through national and targeted dietary policies: a modelling study. PLoS Med 14, e1002311.CrossRefGoogle ScholarPubMed
Penalvo, JL, Cudhea, F, Micha, R et al. (2017) The potential impact of food taxes and subsidies on cardiovascular disease and diabetes burden and disparities in the United States. BMC Med 15, 208.CrossRefGoogle ScholarPubMed
Ni Mhurchu, C, Eyles, H, Genc, M et al. (2015) Effects of health-related food taxes and subsidies on mortality from diet-related disease in New Zealand: an econometric-epidemiologic modelling study. PLoS ONE 10, e0128477.CrossRefGoogle ScholarPubMed
Cobiac, LJ, Tam, K, Veerman, L et al. (2017) Taxes and subsidies for improving diet and population health in Australia: a cost-effectiveness modelling study. PLoS Med 14, e1002232.CrossRefGoogle ScholarPubMed
Holm, AL, Laursen, MB, Koch, M et al. (2013) The health benefits of selective taxation as an economic instrument in relation to IHD and nutrition-related cancers. Public Health Nutr 16, 21242131.CrossRefGoogle ScholarPubMed
Dallongeville, J, Dauchet, L, de Mouzon, O et al. (2011) Increasing fruit and vegetable consumption: a cost-effectiveness analysis of public policies. Eur J Public Health 21, 6973.CrossRefGoogle ScholarPubMed
Effertz, T (2017) Die Auswirkungen der Besteuerung von Lebensmitteln auf Ernährungsverhalten, Körpergewicht und Gesundheitskosten in Deutschland [The Effects of Food Taxation on Eating Habits, Body Weight and Health Costs in Germany]. Hamburg: University of Hamburg.Google Scholar
German Alliance against Non-communicable Diseases (2018) Mehrwertsteuer nach Ampel-System: Eine wirksame Maßnahme gegen Adipositas [VAT according to the traffic light system: an effective measure against obesity]. https://adipositas-gesellschaft.de/fileadmin/PDF/Presse/180327_th012_Factsheet_Steuer_03_final.pdf (accessed October 2019).Google Scholar
Nghiem, N, Wilson, N, Genc, M et al. (2013) Understanding price elasticities to inform public health research and intervention studies: key issues. Am J Public Health 103, 19541961.CrossRefGoogle ScholarPubMed
Lhachimi, SK, Cole, KJ, Nusselder, WJ et al. (2012) Health impacts of increasing alcohol prices in the European Union: a dynamic projection. Prev Med 55, 237243.CrossRefGoogle ScholarPubMed
Thiele, S (2008) Elastizitäten der Nachfrage privater Haushalte nach Nahrungsmitteln - Schätzung eines AIDS auf Basis der Einkommens- und Verbraucherstichprobe [Food demand elasticities: an AIDS using German cross sectional date]. Ger J Agr Econ 57, 258268.Google Scholar
Robert Koch Institute – Department of Epidemiology and Health Monitoring (2014) German Health Update 2012 (GEDA 2012). Public Use File first Version.Google Scholar
Lange, C, Jentsch, F, Allen, J et al. (2015) Data resource profile: German Health Update (GEDA) – the health interview survey for adults in Germany. Int J Epidemiol 44, 442450.CrossRefGoogle ScholarPubMed
van de Kassteele, J, Hoogenveen, RT, Engelfriet, PM et al. (2012) Estimating net transition probabilities from cross-sectional data with application to risk factors in chronic disease modeling. Stat Med 31, 533543.CrossRefGoogle Scholar
Lhachimi, SK, Nusselder, WJ, Lobstein, TJ et al. (2013) Modelling obesity outcomes: reducing obesity risk in adulthood may have greater impact than reducing obesity prevalence in childhood. Obes Rev 14, 523531.CrossRefGoogle ScholarPubMed
Aune, D, Giovannucci, E, Boffetta, P et al. (2017) Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all – cause mortality – a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol 46, 10291056.CrossRefGoogle ScholarPubMed
Lhachimi, SK, Nusselder, WJ, Smit, HA et al. (2012) DYNAMO-HIA – a dynamic modeling tool for generic health impact assessments. PLoS ONE 7, e33317.CrossRefGoogle ScholarPubMed
Kulik, MC, Nusselder, WJ, Boshuizen, HC et al. (2012) Comparison of tobacco control scenarios: quantifying estimates of long-term health impact using the DYNAMO-HIA modeling tool. PLoS ONE 7, e32363.CrossRefGoogle ScholarPubMed
Hendriksen, MA, van Raaij, JM, Geleijnse, JM et al. (2015) Health gain by salt reduction in europe: a modelling study. PLoS ONE 10, e0118873.CrossRefGoogle ScholarPubMed
Fischer, F & Kraemer, A (2016) Health impact assessment for second-hand smoke exposure in Germany-quantifying estimates for ischaemic heart diseases, COPD, and stroke. Int J Environ Res Public Health 13, 198.CrossRefGoogle Scholar
Boshuizen, HC, Lhachimi, SK, van Baal, PH et al. (2012) The DYNAMO-HIA model: an efficient implementation of a risk factor/chronic disease Markov model for use in Health Impact Assessment (HIA). Demography 49, 12591283.CrossRefGoogle Scholar
Lhachimi, SK, Nusselder, WJ, Boshuizen, HC et al. (2010) Standard tool for quantification in health impact assessment a review. Am J Prev Med 38, 7884.CrossRefGoogle ScholarPubMed
Holm, AL, Bronnum-Hansen, H, Robinson, KM et al. (2014) Assessment of health impacts of decreased smoking prevalence in Copenhagen: application of the DYNAMO-HIA model. Scand J Public Health 42, 409416.CrossRefGoogle ScholarPubMed
Kang, E (2017) Assessing health impacts of pictorial health warning labels on cigarette packs in Korea Using DYNAMO-HIA. J Prev Med Public Health 50, 251261.CrossRefGoogle ScholarPubMed
Erkoyun, E, Sozmen, K, Bennett, K et al. (2016) Predicting the health impact of lowering salt consumption in Turkey using the DYNAMO health impact assessment tool. Public Health 140, 228234.CrossRefGoogle ScholarPubMed
Mansfield, TJ & MacDonald Gibson, J (2015) Health impacts of increased physical activity from changes in transportation infrastructure: quantitative estimates for three communities. Biomed Res Int 2015, 812325.CrossRefGoogle ScholarPubMed
Andreyeva, T, Long, MW & Brownell, KD (2010) The impact of food prices on consumption: a systematic review of research on the price elasticity of demand for food. Am J Public Health 100, 216222.CrossRefGoogle Scholar
Tiffin, R, Balcombe, K, Salois, M et al. (2011) Estimating Food and Drink Elasticities. Reading: University of Reading.Google Scholar
Schlesinger, S, Neuenschwander, M, Schwedhelm, C et al. (2019) Food groups and risk of overweight, obesity, and weight gain: a systematic review and dose-response meta-analysis of prospective studies. Adv Nutr 10, 205218.CrossRefGoogle ScholarPubMed
Schwingshackl, L, Schwedhelm, C, Hoffmann, G et al. (2017) Food groups and risk of hypertension: a systematic review and dose-response meta-analysis of prospective studies. Adv Nutr 8, 793803.CrossRefGoogle ScholarPubMed
Soerjomataram, I, Oomen, D, Lemmens, V et al. (2010) Increased consumption of fruit and vegetables and future cancer incidence in selected European countries. Eur J Cancer 46, 25632580.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Uncompensated (Marshallian) own-price elasticities from Thiele 2008(28)

Figure 1

Fig. 1 Fruit and vegetable intake over scenarios, before smoothing over age. , 0 to ≤0·5 portions; , >0·5 to ≤1·5 portions; , >1·5 to ≤2·5 portions; , >2·5 to ≤3·5 portions; , >3·5 to ≤4·5 portions; , >4·5 portions

Figure 2

Table 2 Relative risks for fruits and vegetables

Figure 3

Table 3 Incident and prevalent cases of IHD and stroke

Figure 4

Table 4 Number of deaths