Browsing by Subject "Instrumental variable"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Quantifying risk of injury from usual alcohol consumption: An instrumental variable analysis
    (Wiley, 2021) Ye, Yu; Cherpitel, Cheryl J.; Terza, Joseph V.; Kerr, William C.; Economics, School of Liberal Arts
    Background: There have been numerous studies of roadside accidents among emergency room patients showing elevated risk of injury from acute alcohol consumption, i.e. recent drinking prior to the injury event, with large effect size and a dose-response relationship observed. In contrast, studies quantifying the association between injury risk and chronic consumption such as past year average volume show that relative risk estimates are low compared to those from acute consumption. Methods: Using the US National Alcohol Surveys (NAS) combining four waves for years 2000–2015 (N=29,571, 53% overall cooperation rate), risk of any past-year injury was first estimated by past-year volume using logistic regression. An instrumental variable (IV) analysis utilizing the two-stage residual inclusion (2SRI) approach was then conducted to estimate injury risk from volume, further adjusting for unobserved confounders, using state beer and spirits tax rates, zip code-level outlet and bar density, and control state status as instruments. Results: Based on the combined US population surveys and controlling for socio-demographics, odds ratios of injury from average volume of 1, 2 and 5 drinks per day were 1.12 [95% confidence interval: 1.02, 1.24], 1.10 [1.00, 1.22], and 1.04 [0.88, 1.22], respectively, using conventional logistic regression, compared to 1.67 [1.00, 2.78], 2.38 [0.87, 6.54] and 6.98 [0.57, 85.89] using the IV method. The proportion of injury attributed to alcohol also increased in magnitude, from 6.2% [0.3%, 11.9%] using the conventional approach to 17.9% [8.2%, 27.7%] using the IV method. Conclusions: Findings suggest that the association between injury and chronic alcohol consumption may be confounded by unobserved factors, with the risk estimate possibly biased downward.