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Table 1 Key model variables, mean value and 95% uncertainty intervals

From: Obesity-related health impacts of fuel excise taxation- an evidence review and cost-effectiveness study

Variables Data source
Total population estimates (population numbers, mortality rates, BMI distribution) ABS Census 2011 [38]
Disease epidemiology, relative risks, disability weights, total years of life lived with disability GBD 2010 [43]
Disease healthcare costs AIHW 2004 [45]
Transport mortality data Australian Road Deaths Database [98]
Transport morbidity data Henley et al. 2012 [99, 100]
Variables Mean values and 95% UIa (where applicable) Data source and assumptions
Prevalence of using public transport for commuting purposes Males Females ABS Census 2011 [38]
18y 4.5% 18y 6.9%
19y 5.8% 19y 8%
20-24y 8.5% 20-24y 11.1%
25-29y 11.7% 25-29y 13.1%
30-34y 11.1% 30-34y 9.9%
35-39y 9.1% 35-39y 6.8%
40-44y 7.4% 40-44y 5.9%
45-49y 6.3% 45-49y 5.7%
50-54y 5.8% 50-54y 5.3%
55-59y 4.9% 55-59y 4.5%
60-64y 3.3% 60-64y 2.9%
Cost of legislation (including RIS process) AUD1,090,792
(95% UI AUD939,805–1,249,710)
Sampled from a gamma distribution, taken from estimates from Lal et al. [49].
ABS average weekly earnings AUD1,241
(95% UI AUD1,126–1361)
Sampled from a gamma distribution (mean 1530.20, s.e. 44.8) Professional, Scientific and Technical Services full time adult average half-hour time cost and 14% labour oncosts, from Government sources [48, 50, 51].
Number of businesses affected 185,959
(95% UI 172,747–199,317)
Sampled from a pert distribution (most likely = 186,097) quoted from Government source, +/−10% [48].
Total intervention cost AUD4,381,691
(95% UI AUD3882,683–4,903,984)
  1. Table notes: a95% uncertainty interval (UI) based on 2000 simulations. ABS Australian Bureau of Statistics, AIHW Australian Institute of Health and Welfare, AUD Australian dollars, GBD Global Burden of Disease, RIS Regulatory Impact Statement, s.e standard error