How Much Of Our Tax Money Goes To Fruit And Vegetable Subsidies
Summary
Background
1 possible policy response to the burden of diet-related illness is nutrient taxes and subsidies, but the net wellness gains of these approaches are uncertain because of substitution effects between foods. We estimated the wellness and cost impacts of various nutrient taxes and subsidies in 1 high-income country, New Zealand.
Methods
In this modelling study, nosotros compared the effects in New Zealand of a 20% fruit and vegetable subsidy, of saturated fat, sugar and common salt taxes (each gear up at a level that increased the total food price by the same magnitude of decrease from the fruit and vegetable subsidy), and of an 8% so-called junk nutrient tax (on non-essential, energy-dumbo nutrient). We modelled the effect of price changes on food purchases, the consequent changes in fruit and vegetable and sugar-sweetened drink purchasing, food hazard factors, and body-mass index, and how these changes impact health condition and health expenditure. The pre-intervention intake for 340 food groups was taken from the New Zealand National Diet Survey and the postal service-intervention intake was estimated using cost and expenditure elasticities. The resultant changes in dietary adventure factors were so propagated through a proportional multistate lifetable (with 17 diet-related diseases) to guess the changes in health-adjusted life years (HALYs) and health system expenditure over the 2011 New Zealand population'south remaining lifespan.
Findings
Wellness gains (expressed in HALYs per 1000 people) ranged from 127 (95% dubiety interval 96–167; undiscounted) for the 8% junk food tax and 212 (102–297) for the fruit and vegetable subsidy, up to 361 (275–474) for the saturated fat revenue enhancement, 375 (272–508) for the salt taxation, and 581 (429–792) for the sugar tax. Health expenditure savings beyond the remaining lifespan per capita (at a three% discount charge per unit) ranged from US$492 (334–694) for the junk nutrient revenue enhancement to $2164 (1472–3122) for the sugar tax.
Interpretation
The big magnitude of the health gains and price savings of these modelled taxes and subsidies suggests that their use warrants serious policy consideration.
Funding
Health Enquiry Council of New Zealand.
Introduction
Many countries have now implemented taxes on sugary beverages,
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simply few accept implemented food subsidies or taxes on other products. Mexico implemented an 8% revenue enhancement on non-essential, free energy-dense foods in 2014, which yielded a six·0% reduction in purchasing of these foods.
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In 2011, Denmark implemented a €2·14 per kg tax on saturated fat for products with more than 2·three yard per 100 g of saturated fat. Although this tax was afterwards repealed in 2013, for the duration of implementation, saturated fat purchases reduced past 4·0%, and deaths owing to non-catching disease were estimated to reduce by 0·four%.
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Hungary has introduced a revenue enhancement targeting prepacked foods that are loftier in common salt, sugar, or caffeine (at varying tax rates), which has been associated with a iii·4% reduction in consumption of processed food (and a compensatory 1·ane% increase in unprocessed food).
A major challenge of estimating the long-term effects of nutrient taxes and subsidies is assuasive for exchange. For example, an increase in the cost of foods that are high in carbohydrate might but lead people to purchase more processed foods (that are high in sodium, saturated fat, or both) with no net wellness gain. Some natural experiment evaluations of existent-world interventions examine exchange furnishings (eg, substituting sugary drinks for water in Mexico
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), but well-nigh exercise non. Alternatively, one can use estimated toll elasticities, including cross-price elasticities that capture the commutation and complementary effects of a change in price of ane food on the purchasing of some other food.
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Our study builds on a platform of research into changes in food purchasing in response to price changes. We recently published the results of a virtual supermarket experiment with randomly varying food prices.
Using the food profile of purchased foods, in that study, we found an increment in the healthiness of purchased foods for three revenue enhancement policies (sugar, saturated fatty, and salt), but not for a fruit and vegetable subsidy or a saccharide-sweetened beverage tax. We also institute substitution effects; for example, both the saturated fat and salt tax increased fruit and vegetable purchases as a percent by weight of all food purchases, but they too increased sugar as a percentage of full energy. Thus, the net effect on health and the relative wellness proceeds of different policies remains unknown. The objectives of the current study therefore were to appraise the impacts of multiple food taxes and subsidy policies on the change in quantities of nutrients and food groups purchased, and to estimate associated changes in health organization expenditure and in health gains, measured in health-adjusted life-years (HALYs).
Research in context
Evidence before this study
Targeted subsidies and taxes on certain foods might be effective policies to better population health and lower health-intendance spending, and a growing number of countries accept introduced this type of policy, such as taxes on sugar-sweetened beverages that were introduced in United mexican states and the Great britain. Yet, estimating the health and wellness arrangement expenditure effects of food taxes and subsidies is complex, requiring the integration of evidence on how changes in food price change purchasing and consumption (price elasticity), on how changes in food intake change dietary chance factors and thus event affliction incidence rates and salubrious life-years gained, and on the price to the health system for each illness. A few previous simulation studies have estimated health gains (eg, wellness-adjusted life-years) and health expenditure from food taxes and subsidies. Well-nigh studies discover health gains, but these are frequently due to substitution effects, such as a fruit and vegetable subsidy existence showtime by slight increases in deleterious food intake, or a saturated fat tax leading to deleterious substitution by higher common salt intake.
Added value of this study
This report advances the methods and rigour of simulation modelling in many ways. It uses Bayesian cost elasticities estimated from previous New Zealand enquiry and experimental data with large changes in the toll of foods. It disaggregates toll elasticities to 340 nutrient groups to capture substitution effects, and it sets sugar, salt, and saturated fat taxes to beginning a 20% subsidy on fruit and vegetables. The written report likewise allows for fourth dimension lags from changes in diet to changes in disease incidence, it allows for competing diseases, and it uses many parameters (eg, affliction rates and costs) generated from high quality linked national data. The study finds the largest wellness gain for a sugar tax. All modelled food taxes and subsidies brought health gains larger than a comparably modelled 10% per annum increase in tobacco tax from 2011 to 2025. Health expenditure savings are large, ranging from US$500 to $2000 per citizen over the residue of their lives, fifty-fifty when discounted at iii% per annum.
Implications of all the available prove
Policy making at the intersection of health and food systems involves many considerations, one of them being the impact of prices on health. Nutrient taxes and subsidies are one policy lever. The large magnitude of the health gains and cost savings of the modelled taxes and subsidies in this study suggest that their employ warrants serious policy consideration.
Methods
Study design
In this modelling study, we used three steps comprising first, the effect of price changes on food purchases; second, the consequent changes in fruit and vegetable and sugar-sweetened beverage purchasing, nutrient take chances factors (sodium, polyunsaturated fat acids [PUFA], free energy intake) and body-mass index (BMI); and tertiary, how these changes touch health status, expressed as HALYs, and health expenditure, expressed as 2018 US dollars (appendix p iv). HALYS are similar to quality-adapted life-years in that they are calculated prospectively in a simulated population (not cross-sectionally as in a disability-adjusted life-year from a burden of disease study), just they apply disability weights from the Global Burden of Illness (GBD) rather than other forms of (dis)utility weights. One of our study's innovations was that we simulated the result of changes in nutrition onto 17 diseases and then the gains in HALYs with time, allowing for time lags and competing mortality and morbidity risks. Our previous direct analyses
of the virtual supermarket experiment did non find a statistically meaning impact of a fruit and vegetable subsidy on the overall healthiness of foods (nutrient profiling score), but this does not foreclose some effect on HALYs, especially given that the toll elasticities matrices used in the current written report more than comprehensively handle substitution and complementary effects. A second innovation was that we used a xx% fruit and vegetable subsidy that caused a iii·4% subtract in the food price index (ie, the toll of all foods using pretax or presubsidy purchasing quantities) as an anchor, and and so we set the level of the saturated fat, salt, and saccharide taxes each to reach an offsetting three·iv% increment in the food price index. This increase equated to Usa$1·27 per 100 thou saturated fat tax, $0·52 per 100 g sugar tax, and $0·0166 per 100 mg of sodium. This approach has three advantages: starting time, information technology gives born comparability of the magnitude of the separate taxation and subsidy policies; second, for one of the revenue enhancement policies combined with the fruit and vegetable subsidy, the probably minimal effect on net nutrient prices (ie, the subsidy and tax offset each other) might be politically and publicly more adequate; and 3rd, for combined policies, the expected minimal change in the full nutrient price alphabetize poses less risk than a 3·four% alter to the price index, which might violate the microeconomic assumptions inherent in elasticities. A third innovation of the current study is that nosotros also included an viii% revenue enhancement on non-essential energy-dense foods to emulate the Mexican junk food tax,
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generating an international criterion. A listing of foods alluring the eight% Mexican junk food revenue enhancement tin can be found elsewhere.
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Cost and expenditure elasticities
The 4th innovation of the current study was to utilize an advanced set of price elasticities in a highly disaggregated matrix of 340 food groups to let for substitution and complementary effects. A 23 past 23 food matrix was generated using a linear most-platonic need system, with Bayesian priors for demand equation coefficients generated from a New Zealand food price elasticities matrix.
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The demand equations were offset estimated for eleven hierarchical subsets of food groups (appendix p 5), then aggregated to the 23 by 23 food group price elasticities matrix, every bit is common practice.
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This approach was chosen both for computational tractability and theoretical reasons, including that food complements and substitutes for the elasticity interpretation of cross-price elasticities are more important between foods considered to be alike (eg, poultry and pork) than for dissimilar foods (eg, poultry and beverages). The resultant price elasticities matrix is shown in the appendix (pp 9–10), and further details are published elsewhere.
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At the level of 23 food groups, at that place is still of import heterogeneity within food groups in product-level concentrations of sugar and saturated fat. For example, full-fat and low-fatty versions of dairy products should be taxed differently, and it was necessary to allow for shifts in purchasing within the dairy food grouping. Therefore, we disaggregated foods and their price elasticities into a 340 by 340 food matrix, to align with disaggregated consumption data in the 2008–09 New Zealand National Nutrition Survey (appendix p 2).
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Applying toll elasticities matrices from one context to another, where food consumption patterns and prices differ, might violate assumptions that are inherent in price elasticities matrix estimation, which could result in underestimation or overestimation of postintervention total food purchasing.
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Nosotros therefore constrained total food expenditure using a total food expenditure elasticity (appendix p 2).
Changes in diet and adventure factors
We used the 2008–09 New Zealand Nutrition Survey
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(acquired from the University of Otago'south Life in New Zealand Research Grouping who conducted the survey) to inform our specification of the business-as-usual (BAU) diet, by sex, age, and ethnicity (Māori and non-Māori) for 340 food categories. Percentage changes in purchasing were causeless to be the aforementioned every bit percentage changes in nutrient consumption. BMI alter was derived from the change in energy intake.
Epidemiological and expenditure modelling
In the proportional multistate lifetable (PMSLT
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) model, the BAU lifetables for each sex-by-ethnicity-past-age accomplice were specified for all-cause mortality and morbidity (with trends to 2026, and so rates held constant), and the incidence and case-fatality rates for the remainder of the lifespan for 17 nutrition-related diseases (coronary heart disease, stroke, osteoarthritis, diabetes, and multiple cancers: endometrial, head and neck, kidney, liver, lung, oesophageal, pancreatic, stomach, thyroid, colorectal, chest, ovarian, and gallbladder). The raw estimates of disease incidence, prevalence, and example-fatality rates were first adamant by sex, ethnicity, and age group from linked health records for all New Zealand citizens. They were then processed through an epidemiological computer (DISMOD
) to ensure complete coherence before inputting to BAU in the PMSLT.
At the center of calculating intervention impacts in the PMSLT is the conversion of intervention-induced changes in risk factors (ie, sodium, PUFA, fruits and vegetables, BMI, and sweetened sugary beverages) to changes in disease incidence rates. This conversion is made using population impact fractions (PIFs) that utilise rate ratios for each gamble factor–affliction association, to give percentage changes in affliction incidence (appendix pp 2–three). We included hazard factor–disease pairings every bit per the GBD Study 2013,
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within the constraints of the risk factors that we were able to include in the PMSLT simulation model. Time lags were incorporated past the average of the PIFs 10–30 years before modelling (each limit with probabilistic incertitude) for cancers and 0–5 years before for other conditions. To capture changes in HALYs, the differences betwixt the BAU and intervention in affliction mortality and morbidity rates (by cohort and twelvemonth into the future) were summed beyond all diseases. They were then subtracted from the all-cause mortality and morbidity rates in the main lifetable, to give an intervention lifetable. The difference in HALYs between the BAU and intervention principal lifetable is the issue size of the tax or subsidy intervention.
Disease-specific excess expenditure was assigned to the prevalent disease cases in each annual cycle of the model, and a background health expenditure was assigned to all alive simulants. Health expenditure was tallied up under both BAU and intervention scenarios, with the divergence betwixt BAU and intervention existence that ascribed to the tax or subsidy policy. Calibration and validation of the epidemiological aspects of the PMSLT is described in a technical report.
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Statistical analysis
The modelling was washed in Microsoft Excel. Nosotros used Monte Carlo simulation to guess incertitude in the HALY outputs, by cartoon randomly from probability distributions near all input parameters. A more complete list of input parameters is given in the appendix (pp 7–8) and elsewhere,
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including probability distributions for own-toll and cross-cost elasticities in the 23 by 23 nutrient matrix. 2000 iterations were used, because this leads to reasonable stability in means, medians and the 2·5th and 97·5th percentile over repeated reruns of 2000 simulations. HALYs and costs are presented both undiscounted and, as recommended,
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discounted at three%.
Role of the funding source
The funder had no function in the report design, data collection, data analysis, information interpretation, the writing of the study, or the decision to submit the newspaper for publication. TB, CC, AM, NN, and NW had access to the raw data used in the model. The respective author had full access to all of the data and the final responsibility to submit for publication.
Results
A fresh fruit and vegetable subsidy of 20% reduced the total food toll index by three·4% (tabular array 1). The junk food tax increased the total price index past 0·9%. The percent changes in adventure cistron levels bear witness that each policy produces a notable change in the target food purchasing (tabular array 1). For example, the fruit and vegetable subsidy produced a 16·2% (95% dubiousness interval [UI] 14·seven to 17·half-dozen) increase in fruit and a 32·0% (29·viii to 34·8) increase in vegetable purchasing, the saturated fat tax gave a 10·3% (7·four to 13·half dozen) reduction in saturated fats, the sugar revenue enhancement gave a 33·3% (26·iv to 45·2) reduction in sugar, and the salt tax gave a 12·0% (9·iv to xv·nine) reduction in table salt (table 1). Benign substitution furnishings included that the fruit and vegetable subsidy decreased saturated fat and salt purchasing, the saturated fat revenue enhancement increased fruit and vegetables and reduced salt, the sugar taxation increased fruit and vegetables, and the salt tax increased fruit and vegetables and decreased saturated fat (table 1). There were too deleterious substitution effects; the fruit and vegetable subsidy increased sugar; the saturated fatty tax reduced PUFA; the sugar tax increased saturated fat and salt; and the salt tax increased sugar. The 8% junk nutrient tax had more modest effects, increasing vegetables, and decreasing saturated fat, PUFA, and sugar. All policies lowered the midpoint BMI in each category, although for the fruit and vegetable subsidy the doubt interval includes an increment in BMI (–0·8 to 0·3; table 1).
Table 1 Weighted boilerplate percentage changes in full nutrient price index, nutrient purchasing, and BMI per intervention after 2011 commencement signal
| Total price index | Fruit | Vegetables | Saturated fat | Poly-unsaturated fat acids | Saccharide | Salt | BMI | |
|---|---|---|---|---|---|---|---|---|
| Fruit and vegetable subsidy of xx% | −3·four% | 16·2% (xiv·7 to 17·6) | 32·0% (29·eight to 34·eight) | −2·1% (−2·9 to −0·nine) | −0·ii% (−0·nine to 0·9) | one·7% (0·nine to 2·9) | −1·9% (−two·8 to −0·6) | −0·4% (−0·8 to 0·3) |
| Saturated fat revenue enhancement | 3·4% | 3·three% (2·2 to 4·3) | three·5% (two·3 to 4·half dozen) | −x·3% (−xiii·half-dozen to −7·four) | −5·4% (−viii·8 to −ii·0) | 0·ane% (−ane·3 to 1·4) | −two·6% (−3·9 to −1·6) | −ii·0% (−two·eight to −i·three) |
| Sugar tax | three·4% | four·7% (3·6 to 5·vi) | five·1% (iii·9 to 6·2) | 1·six% (0·3 to 2·8) | 1·four% (−0·ane to 2·vii) | −33·three% (−45·two to −26·four) | 2·two% (0·7 to 3·9) | −3·3% (−5·0 to −2·2) |
| Salt tax | 3·4% | 3·0% (2·0 to 3·eight) | iv·0% (2·vii to v·1) | −2·i% (−three·four to −0·9) | −3·5% (−5·3 to −1·seven) | ii·1% (0·7 to 3·5) | −12·0% (−15·9 to −ix·4) | −one·9% (−two·8 to −1·2) |
| Junk food tax at viii% (equally in Mexico) | 0·9% | 0·0% (−0·three to 0·4) | 0·half-dozen% (0·2 to i·one) | −0·7% (−ane·2 to −0·4) | −ane·7% (−two·3 to −1·2) | −0·8% (−1·3 to −0·5) | −0·3% (−0·6 to 0·1) | −0·7% (−1·0 to −0·5) |
Information are n (95% dubiety interval). Percentage weighting is by proportionate sex past ethnic group distribution. Results by sex and age and for combination policies are shown in the appendix (pp 7–8). BMI=body-mass index.
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We calculated the per centum differences between the intervention and BAU scenarios for selected age-standardised disease incidence and all-cause mortality rates, at thirty years after the 2011 showtime bespeak, in 2041, to allow for time lags (table two). Diabetes incidence fell more than than any other illness for all taxation options, ranging from a 6·5% fall among women for the junk food tax upwardly to a 32·7% autumn among men for the saccharide tax (table two). For the fruit and vegetable subsidy, the largest disease incidence reduction was for stroke (16·three% for men; 11·3% for women; table 2).
Table ii Percentage changes in historic period-standardised incidence rates for selected diseases and all-cause mortality rate for people older than 30 years, thirty years later the tax or subsidy intervention
| Coronary centre disease incidence | Stroke incidence | Colorectal cancer incidence | Diabetes incidence | Osteoarthritis incidence | All-cause mortality rate | |
|---|---|---|---|---|---|---|
| Fruit and vegetable subsidy of twenty% | ||||||
| Men | −ix·ii% | −16·3% | −0·6% | −3·three% | −1·six% | −two·5% |
| Women | −9·2% | −11·3% | −0·2% | −3·9% | −ane·9% | −ii·0% |
| Saturated fat taxation | ||||||
| Men | −ten·iii% | −12·5% | −3·vii% | −20·1% | −10·2% | −3·4% |
| Women | −8·8% | −10·ane% | −ane·0% | −16·4% | −8·2% | −2·two% |
| Sugar taxation | ||||||
| Men | −15·8% | −18·2% | −5·ix% | −32·seven% | −sixteen·3% | −3·vii% |
| Women | −xiii·6% | −fourteen·7% | −one·5% | −26·viii% | −12·8% | −2·3% |
| Salt tax | ||||||
| Men | −11·6% | −13·ix% | −3·6% | −20·4% | −10·2% | −iii·7% |
| Women | −9·4% | −x·7% | −1·0% | −fifteen·6% | −7·vii% | −2·3% |
| Junk nutrient revenue enhancement at eight% (equally in Mexico) | ||||||
| Men | −3·5% | −four·two% | −1·3% | −7·0% | −3·6% | −1·1% |
| Women | −3·2% | −three·5% | −0·four% | −six·5% | −3·3% | −0·8% |
Age-standardisations are to WHO World Standard.
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Undiscounted health gains were measured in HALYs gained during the get-go xx years and during the remaining lifespan of the population (figure ane). HALYs for the lifespan ranged from 127 per thou people (95% UI 96–167) for the 8% junk food tax and 212 per 1000 people (102–297) for the fruit and vegetable subsidy, upward to 361 per 1000 people (275–474) for the saturated fat revenue enhancement, 375 per grand people (272–508) for the salt tax, and 581 per 1000 people (429–792) for the sugar tax (figure one). The fruit and vegetable policy combined with the three food taxes generated merely less than the condiment effects of the separate interventions. For example, the HALYs gained for the fruit and vegetable subsidy (212) and sugar taxation (581) equate to 793 per one thousand people, which is not much greater than the estimated effect of both policies applied jointly: 751 HALYs gained per 1000 people. viii% of the undiscounted wellness gains occurred in the first xx years following implementation beyond all policies (figure 1).
To better understand the magnitude of these health gains, it is useful to quantify them every bit the per centum gain in HALYs beyond that expected for the population under BAU (173 million HALYs for the rest of the lifespan). The fruit and vegetable subsidy brought a gain of 935 000 HALYs (95% UI 448 000–one 310 000), which is a 0·54% increase on 173 million HALYs beyond BAU, and the combination of the fruit and vegetable subsidy with a carbohydrate taxation brought a proceeds of 3·31 million HALYs, which is an increase of i·91% beyond BAU (table iii).
Table three Health gain and health organization costs saved over the population's remaining lifetime for 0% and 3% discount rates, and percentage proceeds from BAU
| 0% disbelieve rate | iii% discount rate | ||||
|---|---|---|---|---|---|
| HALYs gained | Proportion of BAU | Costs saved (millions) | HALYs gained | Costs saved (millions) | |
| Fruit and vegetable subsidy of 20% | 935 000 (448 000 to 1 310 000) | 0·54% | $5130 (−116 to nine 460) | 258 000 (231 000 to 283 000) | $2210 (1830 to 2570) |
| Saturated fat tax | ane 590 000 (one 210 000 to 2 090 000) | 0·92% | $xvi 300 (11 100 to 23 400) | 436 000 (326 000 to 576 000) | $5870 (3980 to 8440) |
| Sugar tax | ii 560 000 (i 890 000 to three 490 000) | i·48% | $26 600 (17 900 to 39 400) | 697 000 (519 000 to 944 000) | $9530 (6480 to 13 800) |
| Salt tax | one 650 000 (1 200 000 to 2 240 000) | 0·95% | $16 200 (ten 600 to 23 900) | 453 000 (327 000 to 621 000) | $5900 (3920 to 8730) |
| Fruit and vegetable subsidy and saturated fat revenue enhancement | ii 390 000 (1 990 000 to 2 820 000) | 1·38% | $20 100 (14 300 to 27 000) | 647 000 (537 000 to 772 000) | $7500 (5390 to 9970) |
| Fruit and vegetable subsidy and sugar tax | 3 310 000 (2 640 000 to 4 310 000) | 1·91% | $30 100 (20 400 to 42 200) | 894 000 (704 000 to 1 160 000) | $eleven 000 (7640 to fifteen 500) |
| Fruit and vegetable subsidy and salt tax | 2 440 000 (2 010 000 to 3 010 000) | 1·41% | $20 100 (14 300 to 27 900) | 659 000 (535 000 to 816 000) | $7500 (5380 to ten 100) |
| Junk food revenue enhancement at 8% (as in United mexican states) | 561 000 (421 000 to 735 000) | 0·32% | $6060 (4080 to 8660) | 156 000 (116 000 to 204 000) | $2170 (1470 to 3060) |
Data are n (95% dubiousness interval) unless otherwise indicated. All costs are in 2018 U.s. dollars, and HALYs and costs are rounded to 3 meaning figures. HALYs=health-adjusted life-years. BAU=business-as-usual.
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Most of the health gains arose because of reductions to BMI (appendix p 6), even for the common salt taxation (loftier-common salt foods are also often energy dense). Per capita, all tax and subsidy policies generated as much or more than historic period-standardised HALYs per capita for Māori compared with non-Māori people (ranging from a ratio of 0·98 for the fruit and vegetable subsidy to one·80 for the common salt tax; appendix p 11). Reductions in health expenditure over the remaining lifespan reflected patterns of health gain. Using a 3% discount charge per unit, wellness expenditure savings during the remainder of the lifespan ranged from $2170 million (95% UI 1470–3060 million) for the junk food tax to $9530 1000000 (6480–13 800 one thousand thousand) for the carbohydrate tax (table 3). About a 3rd of cost savings were realised in the offset 20 years afterward the intervention. When health expenditure savings are expressed per capita at the 3% discount rate, they ranged from $492 (334–694) per person during the remaining lifetime for the junk nutrient tax to $2164 (1472–3122) per person for the sugar revenue enhancement (figure 2). The health gains from all food tax and subsidy policies simulated in this paper were greater than those from ten% per annum increases in tobacco taxation from 2011 to 2025 in New Zealand (effigy iii), equally simulated using a like model construction and methods (275 000 HALYs gained; 0% discount rate), and most of the policies created greater health gains than a sinking lid on tobacco (ie, linear reduction in all tobacco sales to 0% from 2011 to 2025; figure 3).
Figure 3 Comparing of food tax and subsidy interventions with selected other interventions using the same model construction and affliction inputs
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Error bars are 95% doubtfulness intervals. Disease inputs include tobacco and active send. We used a Markov model for people older than 35 years for salt interventions, which more than halves the HALYs gains considering of halving the number of people included and because those older than 35 years gain less benefit than exercise those younger (considering they have more time to accrue HALY gains with a longer life expectancy). Comparison with a greater range of interventions can be done using the Australia New Zealand-Wellness Intervention League Table. HALY=health-adjusted life-years. *Information from Nghiem and colleagues
(with 0% disbelieve rates in the appendix). †Information from Mizdrak and colleagues.
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- Mizdrak A
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‡Data from Nghiem and colleagues
24
- Nghiem N
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- Cleghorn CL
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The health gains and cost savings of dietary salt reduction interventions, with equity and age distributional aspects.
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(with 0% disbelieve rates in the appendix). §Data from Van der Deen and colleagues.
25
- Van der Deen FS
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- Cleghorn C
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Impact of five tobacco endgame strategies on hereafter smoking prevalence, population health and health system costs: ii modelling studies to inform the tobacco endgame.
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¶Data from current paper.
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All of the modelled scenarios achieved changes in their target foods and nutrients. Substitution effects that were potentially deleterious to health were not severe, every bit manifested by net improvements in disease incidence and HALYs gained beyond all scenarios. Most of the health touch on of the tax policies was through changes in BMI; energy intake changes are more important than substitution effects betwixt foods and therefore nutrient-specific effects (eg, polyunsaturated vs saturated fats). Marked changes in diabetes incidence rates occurred for all food taxation scenarios. The tax on sugar (across all foods, not only sugary drinks) produced the greatest health gain, increasing the HALYs over the remaining lifespan of the population past 1·91% compared with BAU, or 581 HALYs per k people (95% UI 429–792). The saturated fat and salt taxes each achieved nearly ii-thirds of this gain, and the fruit and vegetable subsidy nearly xl%. An 8% junk food revenue enhancement replicating that which was implemented in Mexico achieved the least gain, at 127 HALYs per 1000 people (96–167), although this was proportionate to the policy only causing a 0·nine% increase in food prices compared with the 3·4% increase of the other nutrient taxes.
Affliction prevention can lower health expenditure by reducing future disease incidence and hence prevalence. The policies we assessed produced estimated expenditure reductions ranging from $492 per person (for the junk food tax) to $2164 per person (for the combined fruit and vegetable subsidy and saccharide tax) during the remaining lifespan of the population, fifty-fifty with a 3% almanac discount rate.
Computing the total fruit and vegetable subsidy cost and revenue enhancement revenue intakes to governments from these interventions is challenging. Nonetheless, using published estimates of the total consumption in 2008–09 from the New Zealand National Nutrition Survey,
13
Academy of Otago and New Zealand Ministry of Health
A focus on nutrition: cardinal findings of the 2008/09 New Zealand developed nutrition survey.
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the daily intake of saturated fatty was estimated at 36·v 1000 for men and 25·8 yard for women. For our modelled saturated fat tax, factoring in the ten·iii% decrease due to the tax, revenue enhancement revenue is about $260 million per annum. Likewise, for a 20% subsidy on fruit and vegetables, allowing for increased purchasing in response to a subsidy and using New Zealand Household Expenditure Survey data for 2015–16 on fruit and vegetables, the cost to the Authorities would be about $145 one thousand thousand for fruit and $220 million for vegetables annually.
Many studies have assessed targeted taxes on sweetened sugary beverages,
,
merely fewer accept simulated the wellness impacts from taxes and subsidies that human action on many foods. A 2007 study by Mytton and colleagues
raised concern that taxing saturated fat alone might create a net deleterious touch on cardiovascular disease through increased table salt intake, but they did discover wellness improvements for taxes on unhealthy foods. In 2009, Nnoaham and colleagues
estimated the effects of food taxes on crusade-specific deaths and total deaths. They found that a saturated fat-simply tax increased cancer and cardiovascular disease deaths (due to compensatory increases in salt intake), but that a package of taxing less healthy foods with all acquirement used to subsidise fruits and vegetables could pb to large reductions in deaths. In 2017, Cobiac and colleagues
examined taxes on saturated fat, salt, carbohydrate, and sugar-sweetened beverages, and a subsidy on fruits and vegetables. Their revenue enhancement amounts were similar to those that we take used, but the taxes merely applied to nutrients when they exceeded a threshold (eg, saturated fat tax just on products with more than 2·3% saturated fat), leading to lower per capita wellness gains. Moreover, they found that on its own, a fruit and vegetable subsidy generated wellness loss because of commutation furnishings. Nosotros doubtable that if an expenditure constraint had been used (every bit nosotros did with a food expenditure elasticity), this event might not have occurred.
To contextualise these results, the health gains from all nutrient tax and subsidy policies simulated in this paper were greater than those projected for a 10% per annum increases in tobacco tax from 2011 to 2025 in New Zealand and, apart from the fruit and vegetable subsidy lone and the viii% junk food revenue enhancement, the health gains across all interventions were greater than a sinking hat on tobacco.
25
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This does non mean that tobacco interventions practice not reap large health gains (especially for those people prevented from taking up smoking or quitting), but rather highlights that population-wide food interventions bear on anybody in the population. A suite of New Zealand and Australian dietary evaluations were published in 2019–twenty using similar methods.
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The health gains for food taxes and subsidies in this paper greatly exceeded those for dietary interventions, such equally restricted marketing or parcel size limits on sugary drinks, simply they are roughly equivalent to substantial alcohol taxes and food reformulation (eg, major reductions of sodium). Further comparisons can be made using the Commonwealth of australia–New Zealand Health Intervention League Tabular array.
Modelling wellness impacts is a residual of information requirements, data availability, and model parsimony, with validity assessable at two levels: uncertainty about the model structure and about the input parameters. Concerning our model structure, first of all, information technology did non include the affect of nutrient reformulation. When a tax or subsidy is imposed, new incentive structures are created that the food industry is likely to respond to. For case, when the UK introduced a tiered levy on sugary soft drinks, the industry (as the policy intended) reformulated drinks to contain lower levels of carbohydrate and introduced lower saccharide products. Ane estimate is that two-thirds of the total health gain from sugary drinks tax is via the reformulation pathway.
Would this utilise to food taxes and subsidies that are broader than just the specific category of drinks? The answer is almost certainly yes, just the change would probably non be equally marked every bit with drinks, which are easily reformulated. A second aspect of our model is that it included key take chances factors (eg, salt, BMI, fruits and vegetables), but time to come models could extend the range to include nuts and legumes, processed and cerise meat, and fibre. 3rd, and relatedly, i could include additional causal links in the model, such as directly from carbohydrate to diabetes, given the evidence that some of the event of sugar is through mechanisms other than bodyweight.
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- Te Morenga LA
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Quaternary, our modelling explicitly allowed for substitution effects between foods, just non, for example, how physical activity or other take a chance factors impacting on the same diseases might change with a change in free energy intake.
Regarding the input parameters, dietary intake was sourced from the well-nigh recent national nutrition survey,
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University of Otago and New Zealand Ministry of Health
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which had a weighted response rate of 61%, similar to those accomplished in population diet surveys in Australia, the UK, and Ireland.
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Rate ratios associating risk factors to disease rates came from the GBD 2013
19
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Global, regional, and national comparative risk assessment of 79 behavioural, ecology and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Illness Written report 2013.
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and are of comparatively loftier quality. Even so, determining the associations of individual dietary components with illness rates is notoriously difficult; for example, measurement error and rest confounding across many, if non all of the separate studies included in meta-analyses will exist nowadays. Although we used uncertainty intervals about the inputs, this difficulty is a source of uncertainty beyond confidence intervals. For many run a risk factors, there is uncertainty about the threshold above or below which health impairment occurs. Notwithstanding, nosotros explicitly allowed for this past including uncertainty about the theoretical minimum take chances exposure level in the probabilistic dubiety analyses. A 2nd concern with input parameters is the obvious uncertainty about future affliction rates. We partially addressed this by extending past trends out to 2026, and so allowing no further modify. 3rd, there is inevitable dubiousness about cost elasticities and the extent to which they tin predict future changes in purchasing. The toll elasticities matrix that we used was generated from a New Zealand prior, with a Bayesian affiliation with experimental data that was deliberately designed for assessing food tax and subsidy effects.
There have been concerns about the unintended substitution furnishings of nutrient taxes and subsidies, whereby, for example, a sugar tax might lead to increased saturated fatty consumption and limit health gains, or even lead to wellness harm. Our simulations suggest that although there will be substitution, the cyberspace wellness gains are still highly probable (eg, our 95% uncertainty intervals all excluded the goose egg), at least for the specific fiscal policies modelled in this detail high-income land. Whether the same patterns would be observed in countries with markedly different dietary patterns remains to be investigated, and models such every bit ours provide a mechanism for doing so.
Decisions on food taxes and subsidies should non be made based just on simulation modelling studies. In that location are multiple other considerations, such as political and social acceptability, food industry perspectives, deadweight costs of any tax or subsidy, added complication and hierarchy in administering taxes and subsidies, and intervention options other than taxes or subsides (eg, mandatory reformulation of food). All the same, our report and those earlier it
23
- Mizdrak A
- Blakely T
- Cleghorn CL
- Cobiac LJ
Potential of active transport to improve wellness, reduce healthcare costs, and reduce greenhouse gas emissions: a modelling study.
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,
,
clearly point to the probably big and positive wellness gains that could arise from changing the price signals. Moreover, taxes could prompt nutrient industry production reformulation to avert tax, farther enhancing wellness gains over and above the directly effects that we modelled.
Contributors
TB led the conceptualisation and design of the study. CC, BS, NW, and CNM contributed to the conceptualisation and design of the report. CC and AM contributed to building models, WW led and NN contributed to the conceptualisation and design of the virtual supermarket that generated the toll elasticities. TB oversaw the analysis and led the interpretation, CC and AM contributed to the assay, and all other authors contributed to the interpretation. TB led, and all other authors contributed to the drafting and revision of the manuscript.
Announcement of interests
All authors report grants from Health Inquiry Council of New Zealand, during the conduct of the study.
Acknowledgments
We admit funding from the Wellness Research Council of New Zealand ( grants/724 and 16/443 ). Nosotros acknowledge Liana Jacobi and Andres Ramirez Hassan equally collaborators in the generation of the price elasticities used in this electric current report, and Laxman Bablani for assisting with checks on tax revenue. Dietary intake data used in this modelling was supplied by Otago University Life in New Zealand staff (personal communication, Blakey, Smith and Parnell, 2014).
Supplementary Material
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DOI: https://doi.org/10.1016/S2468-2667(20)30116-X
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