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. 2009 Jul 13;87(9):692–699. doi: 10.2471/BLT.08.056051

Table 2. Binomial logit regressions of the participation of local governments (n = 163) in anti-smoking programme as a function of the percentage of local tax revenue comprised by TCT revenue, Republic of Korea, 2002–2003.

Variable Coefficient Coefficient
(95% CI)a (95% CI)a
Explanatory variable of main interest
TCT revenue as a % of local tax revenue –0.98**
(–1.73 to –0.22)
Quartile (dummy variable)
1st (reference)
2nd –0.43
(–1.62 to 0.76)
3rd –0.88
(–2.59 to 0.83)
4th (highest) –2.36**
(–4.58 to –0.15)
Other explanatory variables
Per capita local tax revenue (in wons of the Republic of Korea × 100 000) –0.48 –0.48
(–1.09 to 0.13) (–1.24 to 0.29)
Population (× 100 000) –0.22** –0.19
(–0.42 to –0.02) (–0.43 to 0.06)
Size of PHC staff
< 40 –1.94*** –1.86*
(–3.19 to –0.68) (–3.11 to –0.61)
40–49 –0.88* –0.74
(–1.89 to –0.12) (–1.72 to 0.24)
50–59 –1.02*** –1.02*
(–1.73 to –0.32) (–1.76 to –0.27)
≥ 60 (reference)
County 0.59 0.75
(–0.52 to 1.71) (–0.61 to 2.12)
Constant 3.58* 1.68
(0.44 to 6.72) (–1.33 to 4.68)

Pseudo R squaredb 0.0950 0.1140
Log pseudolikelihood –85.12 –83.32

PHC, public health centre; TCT, tobacco consumption tax. *P < 0.10; **P < 0.05; ***P < 0.01.
a Robust standard errors were used to allow for potential clustering between lower-level local governments from the same upper-level (provincial) local government. Five county governments from metropolitan cities were regarded as one cluster because they shared relative urbanicity.
b A measure of goodness-of-fit for non-linear models, including logistic models.