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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