Impact of population distribution shifts in sugar-sweetened beverage consumption on type II diabetes incidence in Ireland.

Annals of Epidemiology(2020)

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摘要
Purpose: We simulate population shifts in the distribution of sugar-sweetened beverage (SSB) consumption and address previous methodological limitations to provide valid and reliable estimates of the potential impact of public health interventions on type II diabetes incidence in Ireland. Methods: A comparative risk assessment was conducted, using distribution shift calculations to estimate potential impact fractions (PIFs) for percentage reductions in SSB consumption. Data from the Survey of Lifestyle, Attitudes and Nutrition was analyzed. Individual risk of developing type H diabetes was estimated using a risk prediction algorithm. PIFs were calculated using risk estimates, changes in SSB consumption, and an appropriately specified relative risk. The impact of a 20% levy on SSB5 was explored. Monte-Carlo simulation with 150,000 iterations estimated uncertainty intervals (UIs). PIFs were applied to 2016 census data, estimating the absolute incident cases that may potentially be avoided through reduced SSB consumption. Results: Of the 7272 Survey of Lifestyle, Attitudes and Nutrition participants, 53.3% consumed SSBs. The 10-year rate of type II diabetes was estimated at 4.3% (95% confidence interval: 4.2%, 4.4%). Simulating a 100% reduction in SSB consumption, the population attributable fraction was 1.8% (95%UI: 0.1%, 3.3%). Population shifts in consumption after a 20% levy results in a PIF of 0.37% (95%UI: 0.02%, 0.7%). We estimate 135,850 incident type II diabetes cases over a 10-year period. Of these, 2446 (95% UI: 136, 4483) cases may be attributable to SSB consumption. Conclusions: Overcoming previous methodological limitations, unbiased estimates demonstrate that a population shift in SSB consumption can potentially play a role in the primary prevention of type II diabetes. (C) 2019 Elsevier Inc. All rights reserved.
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关键词
Type II diabetes,Sugar sweetened beverages,Population attributable fraction,Potential impact fraction,Attributable fraction methodology
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