The burden of disease and economic impact of sugar-sweetened beverages' consumption in Argentina: A modeling study.

BACKGROUND: Approximately two-thirds of Argentine adults are overweight or obese, and 11% have diabetes. Over the last two decades, all population groups have increased their consumption of ultra-processed foods and sugar-sweetened beverages (SSB). We aimed to estimate the disease burden-deaths, events, and costs to the health system-attributed to SSB consumption in Argentina. METHODS: We used a comparative risk assessment framework to estimate the health and economic impacts that would be avoided in a scenario without sugar-sweetened beverage (SSB) consumption. We calculated the direct effects on diabetes, cardiovascular disease, and BMI, and then estimated the effects of BMI on disease incidence. Finally, we applied the population attributable factor to calculate the health and economic burden avoided in Argentina in 2020. RESULTS: Our model estimated that about 4,425 deaths, 110,000 healthy life years lost to premature death and disability, more than 520,000 cases of overweight and obesity in adults, and 774,000 in children and adolescents would be attributed to SSB Consumption in Argentina. This disease burden corresponds to 23% of type-2 diabetes cases and other significant proportions of cardiovascular disease and cancer. The overweight and obesity costs attributable to SSB totaled approximately $47 million in adults and $15 million in children and adolescents. CONCLUSION: A significant number of disease cases, deaths, and health care costs could be attributed to SSB consumption in Argentina. Implementing measures to reduce the sugar content in beverages is a pending debt for the country and could lead to measurable improvements in population health, especially among children and adolescents.

Alcohol consumption's attributable disease burden and cost-effectiveness of targeted public health interventions: a systematic review of mathematical models.

BACKGROUND: Around 6% of total deaths are related to alcohol consumption worldwide. Mathematical models are important tools to estimate disease burden and to assess the cost-effectiveness of interventions to address this burden. METHODS: We carried out a systematic review on models, searching main health literature databases up to July 2017. Pairs of reviewers independently selected, extracted data and assessed the quality of the included studies. Discrepancies were resolved by consensus. We selected those models exploring: a) disease burden (main metrics being attributable deaths, disability-adjusted life years, quality-adjusted life years) or b) economic evaluations of health interventions or policies, based on models including the aforementioned outcomes. We grouped models into broad families according to their common central methodological approach. RESULTS: Out of 4295 reports identified, 63 met our inclusion criteria and were categorized in three main model families that were described in detail: 1) State transition -i.e Markov- models, 2) Life Table-based models and 3) Attributable fraction-based models. Most studies pertained to the latter one (n = 29, 48.3%). A few miscellaneous models could not be framed into these families. CONCLUSIONS: Our findings can be useful for future researchers and decision makers planning to undertake alcohol-related disease burden or cost-effectiveness studies. We found several different families of models. Countries interested in adopting relevant public health measures may choose or adapt the one deemed most convenient, based on the availability of existing data at the local level, burden of work, and public health and economic outcomes of interest.