The effect of warning signals from health check-ups on modifiable lifestyle risk factors: evidence from mandatory health check-ups for employees in Japan

Figures & data

Table 1. Baseline characteristics in the 2006 survey.

	(1)		(2)
	Not received health warnings reported in the 2007 survey (n = 3199)		Received health warnings reported in the 2007 survey (n = 1008)		(3)
Variables	Mean	(S.D.)	Mean	(S.D.)	$\mathit{p}$-value for mean differences
Panel A: Baseline individual characteristics
Age	55.66	(2.67)	55.81	(2.72)	0.12
Female	0.29	(0.45)	0.29	(0.45)	0.86
Undergraduate/postgraduate education	0.35	(0.48)	0.37	(0.48)	0.31
Married	0.86	(0.35)	0.88	(0.33)	0.26
Household size	3.27	(1.45)	3.21	(1.44)	0.29
Household monthly income (in JPY 10,000)	33.30	(53.77)	31.99	(40.52)	0.48
Executive officer	0.09	(0.29)	0.09	(0.29)	0.96
Weekly working days	5.25	(0.66)	5.26	(0.73)	0.96
Weekly working hours	44.19	(10.64)	44.60	(11.42)	0.31
Wage rate (in JPY)	2712.7	(7725.0)	2498.8	(4235.8)	0.42
Firm size fewer than 100 employees	0.46	(0.50)	0.47	(0.50)	0.53
Panel B: Baseline lifestyle variables
Current smoker	0.37	(0.48)	0.36	(0.48)	0.56
Number of cigarettes smoked	6.77	(9.75)	7.15	(10.46)	0.29
Frequency of drinking	0.31	(0.46)	0.33	(0.47)	0.23
Quantity of drinks	1.12	(1.09)	1.16	(1.06)	0.28

Household monthly income is divided by the square root of household size.

Table 2. The effects of warning signals from health check-ups on behavioural changes.

	Main	Long-term
	1 year after check-ups (2007—2006)	4 years after check-ups (2010—2006)	8 years after check-ups (2014—2006)	12 years after check-ups (2018—2006)
Outcome	(1)	(2)	(3)	(4)
Current smoker
$\hat{\beta }$	−0.023***	−0.005	−0.020	−0.012
	(0.008)	(0.012)	(0.015)	(0.017)
n	4179	3596	3167	2930
Number of cigarettes smoked
$\hat{\beta }$	−0.507***	−0.584**	−0.621*	−0.702**
	(0.149)	(0.257)	(0.317)	(0.357)
n	4169	3584	3156	2919
Frequency of drinking
$\hat{\beta }$	−0.024**	−0.032**	−0.039**	−0.044**
	(0.012)	(0.014)	(0.016)	(0.018)
n	4178	3595	3166	2927
Quantity of drinks
$\hat{\beta }$	−0.047*	−0.001	−0.004	−0.012
	(0.025)	(0.028)	(0.031)	(0.035)
n	4138	3562	3133	2907

Significance levels: ***p < 0.01, **p < 0.05, *p < 0.10.

Table 3. Heterogeneous effects (within one-year change).

	Age		Educational Attainment		Household income
	Age $\ge$ Median	Age $<$ Median	Undergraduate/ postgraduate education	High School graduation or less	Income $\ge$ Median	Income $<$ Median
Outcome	(1)	(2)	(3)	(4)	(5)	(6)
Current Smoker
$\hat{\beta }$	−0.035***	−0.012	−0.028**	−0.019**	−0.029***	−0.017
	(0.012)	(0.011)	(0.014)	(0.010)	(0.009)	(0.013)
n	2113	2066	1486	2693	2136	2043
Number of cigarettes smoked
$\hat{\beta }$	−0.716***	−0.301	−0.678***	−0.386**	−0.557***	−0.464*
	(0.225)	(0.188)	(0.247)	(0.183)	(0.182)	(0.239)
n	2107	2062	1484	2685	2131	2038
Frequency of drinking
$\hat{\beta }$	−0.046***	0.001	−0.042**	−0.013	−0.045***	−0.003
	(0.016)	(0.017)	(0.019)	(0.015)	(0.016)	(0.016)
n	2112	2066	1488	2690	2136	2042
Quantity of drinks
$\hat{\beta }$	−0.078**	−0.010	−0.030	−0.056*	−0.056	−0.036
	(0.034)	(0.037)	(0.039)	(0.032)	(0.035)	(0.036)
n	2086	2052	1478	2660	2123	2015

Significance levels: ***p < 0.01, **p < 0.05, *p < 0.10.

Table A1. The effects of warning signals from health check-ups on changes in physical activity.

	Main		Long term
	1 year after check-ups		4 years after check-ups	8 years after check-ups	12 years after check-ups
Outcome	(1)		(2)	(3)	(4)
Panel A: Regular physical activity
Regular physical activity
$\hat{\beta }$	−0.016		−0.020	−0.024	−0.029
	(0.017)		(0.021)	(0.020)	(0.025)
n	4051		3525	3105	2875
Panel B: By intensity of regular physical activity
Light regular physical activity
$\hat{\beta }$	−0.012		−0.024	−0.022	−0.038
	(0.018)		(0.020)	(0.023)	(0.026)
n	4051		3525	3105	2875
Moderate or vigorous regular physical activity
$\hat{\beta }$	0.005		0.027	−0.023	0.001
	(0.014)		(0.018)	(0.023)	(0.023)
n	4051		3525	3105	2875

The dummy variable for regular physical activity takes on the value of one if individuals took part in sports more than twice a week during their leisure time, and zero otherwise. The intensity of exercise was classified as follows: light (stretch, light gymnastics), moderate (walking, jogging), or vigorous (aerobics, swimming). Following Kumagai and Ogura (2014), moderate and vigorous are combined. Significance levels: ***p < 0.01, **p < 0.05, *p < 0.10.

Table B1. Falsification test: changes in lifestyles before baseline year 2006.

	Placebo	Main
	1 year before check-ups (2006—2005)	1 year after check-ups (2007—2006)
Outcome	(1)	(2)
Current smoker
$\hat{\beta }$	−0.010	−0.023***
	(0.007)	(0.008)
n	4175	4179
Number of cigarettes smoked
$\hat{\beta }$	−0.198	−0.507***
	(0.127)	(0.149)
n	4167	4169
Frequency of drinking
$\hat{\beta }$	0.003	−0.024**
	(0.011)	(0.012)
n	4168	4178
Quantity of drinks
$\hat{\beta }$	−0.014	−0.047*
	(0.027)	(0.025)
n	4098	4138

The estimate β from Equation (1)(1) $Y_{\mathit{it}}=\mathit{\beta Warnin}{g}_{\mathit{it}}+\mathit{\pi }{X}_{\mathit{it}}+{\delta }_i+{\alpha }_t+u_{\mathit{it}}$(1) is reported with standard errors clustered at the employee level in parentheses. Significance levels: ***p < 0.01, **p < 0.05, *p < 0.10.

Table B2. The effects of health warnings from health check-ups on attrition.

	Attrition dummy for 4 years after check-ups (2006—2010)	Attrition dummy for 8 years after check-ups (2006—2014)	Attrition dummy for 12 years after check-ups (2006—2018)
Outcome	(1)	(2)	(3)
Key explanatory variable:
Health warnings dummy	−0.0036	0.0019	0.0029
	(0.0023)	(0.0022)	(0.0031)
n	4207	4207	4207

Significance levels: *** p<0.01, ** p<0.05, * p<0.10. Standard errors clustered at the employee level are reported in parentheses. In this study’s sample, the fraction of attrition between 2006–2010 is 14%, between 2006–2014 is 24%, and between 2006–2018 is 31%.

Kumagai, N., and S. Ogura. 2014. “Persistence of Physical Activity in Middle Age: A Nonlinear Dynamic Panel Approach.” The European Journal of Health Economics 15 (7): 717–735. https://doi.org/10.1007/s10198-013-0518-8.

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Data availability statement

Data used in this study cannot be shared publicly because of Article 33 of Japan’s Statistics Act (Act No. 53 of 2007). Data are available based on the criteria set by the Ministry of Health, Labour, and Welfare (contact via https://www.mhlw.go.jp/toukei/sonota/chousahyo.html) for researchers.