Dataset Information

Developing an integrated microsimulation model for the impact of fiscal policies on child health in Europe: the example of childhood obesity in Italy.

ABSTRACT:

Background

We developed an integrated model called Microsimulation for Income and Child Health (MICH) that provides a tool for analysing the prospective effects of fiscal policies on childhood health in European countries. The aim of this first MICH study is to evaluate the impact of alternative fiscal policies on childhood overweight and obesity in Italy.

Methods

MICH model is composed of three integrated modules. Firstly, module 1 (M1) simulates the effects of fiscal policies on disposable household income using the tax-benefit microsimulation program EUROMOD fed with the Italian EU-SILC 2010 data. Secondly, module 2 (M2) exploits data provided by the Italian birth cohort called Nascita e Infanzia: gli Effetti dell'Ambiente (NINFEA), translated as Birth and Childhood: the Effects of the Environment study, and runs a series of concatenated regressions in order to estimate the prospective effects of income on child body mass index (BMI) at different ages. Finally, module 3 (M3) uses dynamic microsimulation techniques that combine the population structure and incomes obtained by M1, with regression model specifications and estimated effect sizes provided by M2, projecting BMI distributions according to the simulated policy scenarios.

Results

Both universal benefits, such as universal basic income (BI), and targeted interventions, such as child benefit (CB) for poorer households, have a significant effect on childhood overweight, with a prevalence ratio (PR) in 10-year-old children-in comparison with the baseline fiscal system-of 0.88 (95%CI 0.82-0.93) and 0.89 (95%CI 0.83-0.94), respectively. The impact of the fiscal reforms was even larger for child obesity, reaching a PR of 0.67 (95%CI 0·50-0.83) for the simulated BI and 0.64 (95%CI 0.44-0.84) for CB at the same age. While both types of policies show similar effects, the estimated costs for a 1% prevalence reduction in overweight and obesity with respect to the baseline scenario is much lower with a more focalised benefit policy than with universal ones.

Conclusions

Our results show that fiscal policies can have a strong impact on childhood health conditions. Focalised interventions that increase family income, especially in the most vulnerable populations, can help to prevent child overweight and obesity. Robust microsimulation models to forecast the effects of fiscal policies on health should be considered as one of the instruments to reach the Health in All Policies (HiAP) goals.

SUBMITTER: Rasella D

PROVIDER: S-EPMC8629597 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:INTRODUCTION:Smoking remains the leading cause of preventable death in the USA but can be reduced through policy interventions. Computational models of smoking can provide estimates of the projected impact of tobacco control policies and can be used to inform public health decision making. We outline a protocol for simulating the effects of tobacco policies on population health outcomes. METHODS AND ANALYSIS:We extend the Smoking History Generator (SHG), a microsimulation model based on data from the National Health Interview Surveys, to evaluate the effects of tobacco control policies on projections of smoking prevalence and mortality in the USA. The SHG simulates individual life trajectories including smoking initiation, cessation and mortality. We illustrate the application of the SHG policy module for four types of tobacco control policies at the national and state levels: smoke-free air laws, cigarette taxes, increasing tobacco control programme expenditures and raising the minimum age of legal access to tobacco. Smoking initiation and cessation rates are modified by age, birth cohort, gender and years since policy implementation. Initiation and cessation rate modifiers are adjusted for differences across age groups and the level of existing policy coverage. Smoking prevalence, the number of population deaths avoided, and life-years gained are calculated for each policy scenario at the national and state levels. The model only considers direct individual benefits through reduced smoking and does not consider benefits through reduced exposure to secondhand smoke. ETHICS AND DISSEMINATION:A web-based interface is being developed to integrate the results of the simulations into a format that allows the user to explore the projected effects of tobacco control policies in the USA. Usability testing is being conducted in which experts provide feedback on the interface. Development of this tool is under way, and a publicly accessible website is available at http://www.tobaccopolicyeffects.org.

Project description:BackgroundBrazil's Estratégia Saúde da Família (ESF) is one of the largest and most robustly evaluated primary healthcare programmes of the world, but it could be affected by fiscal austerity measures and by the possible end of the Mais Médicos programme (MMP)-a major intervention to increase primary care doctors in underserved areas. We forecast the impact of alternative scenarios of ESF coverage changes on under-70 mortality from ambulatory care-sensitive conditions (ACSCs) until 2030, the date for achievement of the Sustainable Development Goals (SDGs).MethodA synthetic cohort of 5507 Brazilian municipalities was created for the period 2017-2030. A municipal-level microsimulation model was developed and validated using longitudinal data and estimates from a previous retrospective study evaluating the effects of municipal ESF coverage on mortality rates. Reductions in ESF coverage, and its effects on ACSC mortality, were forecast based on two probable austerity scenarios, compared with the maintenance of the current coverage or the expansion to 100%. Fixed effects longitudinal regression models were employed to account for secular trends, demographic and socioeconomic changes, healthcare-related variables, and programme duration effects.ResultsUnder austerity scenarios of decreasing ESF coverage with and without the MMP termination, mean ACSC mortality rates would be 8.60% (95% CI 7.03-10.21%; 48,546 excess premature/under-70 deaths along 2017-2030) and 5.80% (95% CI 4.23-7.35%; 27,685 excess premature deaths) higher respectively in 2030 compared to maintaining the current ESF coverage. Comparing decreasing ESF coverage and MMP termination with achieving 100% ESF coverage (Universal Health Coverage scenario) in 2030, mortality rates would be 11.12% higher (95% CI 9.47-12.76%; 83,937 premature deaths). Reductions in ESF coverage would have stronger effects on mortality from infectious diseases and nutritional deficiencies and would disproportionately impact poorer municipalities, with the concentration index for ACSC mortality 11.77% higher (95% CI 0.31-22.32%) and also ending historical declines in racial health inequalities between white and black/pardo Brazilians.ConclusionsReductions in primary healthcare coverage due to austerity measures are likely to be responsible for many avoidable deaths and may preclude achievement of SDGs for health and inequality in Brazil and in other low- and middle-income countries.