Assignment: The Chronic Disease Division

Assignment: The Chronic Disease Division
Assignment: The Chronic Disease Division
The Chronic Disease Division of the New Illabamafornica Department of Health reviewed 47 articles, including predictive models, systematic reviews, program evaluations, public perception, and policy- and news-related commentaries. We analyze four key articles (two peer-reviewed articles and two policy-related/commentary articles) below. Here we set those articles into broad context.
The literature generally supported taxes on sugar-sweetened beverages (SSBs): SSB taxes reduced purchase and consumption of those items across socioeconomic strata. In addition, some researchers suggest that SSB taxes as part of a more comprehensive approach may amplify the positive effects on obesity reduction and other health-related morbidities (Cobiac, Tam, Veerman, and Blakely, 2017). For example, an SSB tax combined with sugar, salt, alcohol, and tobacco taxes combined with subsidies for purchasing healthful foods may be most beneficial. However, we found several policy papers comparing the idea of a tax on SSBs to existing taxes on tobacco and alcohol. Those taxes not only have been important means of reducing consumption but also have generated significant negative responses from industry, antigovernment groups, and civil liberty–focused organizations (Wright, Smith, and Hellowell, 2017).
According to evidence from predictive models, SSB taxes could reduce obesity and prevent the loss of nearly 12,000 disability-adjusted life years (DALYs). Combining SSB taxes with a broader sugar tax might avert the loss of another 270,000 DALYs (Cobiac, Tam, Veerman, and Blakely, 2017). Models measured significant gains from health care savings achieved through reduced morbidity and mortality due to obesity and obesity-related conditions (Peñalvo, Cudhea, Micha, Rehm, Afshin et al., 2017; Veerman, Sacks, Antonopoulos, and Martin, 2016).
Because SSB taxation is a relatively new policy approach, the literature is just beginning to establish evidence that taxation programs are sustainable. Mexico passed a tax on SSBs in 2014. The Mexican program, as a case study and program evaluation, demonstrated not only a decrease in consumption/purchase of SSBs but also an increased purchase of water, addressing some critics’ concern that an SSB tax will simply shift demand to another sugary product. The case suggests that SSB taxation is a sustainable model (Colchero, Molina, and Guerrero-López, 2017; Colchero, Rivera- Dommarco, Popkin, and Ming, 2017). Initiatives in Australia, Germany, and the United Kingdom—and, in the United States, West Virginia and California—support that conclusion (Cobiac, Tam, Veerman, and Blakely, 2017; Schwendicke and Stolpe, 2017; Scalise and Young, 2017; Wetter and Hodge, 2016; Falbe, Rojas, Grummon, and Madsen, 2016; Tiffin, Kehlbacher, and Salois, 2015).
Some critics have suggested that an SSB tax is bad for businesses, particularly small businesses. Yet researchers have identified productivity gains in the private sector in locales that have taxed SSBs. Small-scale programs have been evaluated in multiple settings to determine the long-term impacts of an SSB tax, such as sustainable health benefits and worker productivity (Baker, Jones, and Throw, 2017; Le Bodo and De Wals, 2017; Roache and Gostin, 2017; Nomaguchi, Cunich, Zapata-Diomedi, and Veerman, 2017; Powell, Wada, Persky, and Chaloupka, 2014).
Any policy approach involving a fundamental coercive measure such as taxation demands particular attention to policy framing. The literature underscores that policy framing will shape industry reaction (such as, lobbying against taxes) (Hawkes, 2016; Blecher, 2015; Pomeranz, 2014). Equity is another central policy concern. Regressive taxes—that is, taxes that disproportionately burden people who can least afford them—inevitably raise the question of whether the risks outweigh the benefits (Backholer, Blake, and Vandevijvere, 2016; Sharma, Hauck, Hollingsworth, and Siciliani, 2014).
We highlight the findings from four articles and summarize the overall findings.
SOPH603-Fall2018 Page | 2
Peer-Reviewed Article #1 Backholer, K., D. Sarink, A. Beauchamp, C. Keating, V. Loh, K. Ball, J. Martin, and A. Peeters. 2016. The
impact of a tax on sugar-sweetened beverages according to socio-economic position: A systematic review of the evidence. Public Health Nutrition 19(17):3070–3084. doi:10.1017/S136898001600104X.
? Question: Will an SSB tax have the same impact on weight gain across socioeconomic strata?
? Methods: A systematic review of the grey literature (included 11 articles).
? Major Finding(s)/Argument(s): o Although the tax is slightly regressive, it “will deliver similar population weight gain
benefits across socioeconomic strata.” Indeed, some of the lower-SES (socioeconomic status) study populations benefited the most. Taxes on SSBs are often implemented to generate revenue rather than to improve health-related outcomes.
o The amount of the tax matters, but researchers disagree about how heavily the tax burden affects lower versus higher incomes.
o Improvement in health outcomes may outweigh any negative increased tax burden on the lower-income population.
o Evidence links consumption of SSBs to excess weight gain and other comorbidities. o In 2012, approximately 26.3% of U.S. adults consumed SSBs at least once daily.
? Key Quotes: o “Individuals from socio-economic groups commonly consume more SSBs than their
higher socio-economic counterparts, potentially contributing to the observed inequalities in excess weight and associated disease.”
o “Recent evaluation of the tax [in Mexico] revealed a reduction in the purchase of sugary drinks of 12%, 12 months post policy implementation . . . the greatest declines were observed among households of a lower socio-economic position (SEP), with a 12-month decline in sugary drinks of 17% compared with pre-tax trends.”
? Feasibility/Scalability: o Small number of studies, which limited the variability in study types. o The tax elasticity studies were limited by low tax rate variability and modeling
methods that relied on household survey, scanner data, and assumptions. o The studies reviewed don’t consider social norms, unintended consequences,

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