Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study

Won Ju Hwang; Yunhee Park

doi:10.4040/jkan.2015.45.6.857

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Hwang and Park: Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study

Original Article

J Korean Acad Nurs 2015;45(6):857-867.

Published online: 15 December 2015

DOI: https://doi.org/10.4040/jkan.2015.45.6.857

Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study

Won Ju Hwang¹, Yunhee Park^2,

¹College of Nursing Science· East-west Nursing Research Institute, Kyung Hee University, Seoul

²Department of Nursing, Youngdong University, Youngdong, Korea

Address reprint requests to : Park, Yunhee Department of Nursing, Youngdong University, 310 Taehak-ro, Youngdong-eup, Youndong 29131, Korea Tel: +82-43-740-1386 Fax: +82-43-740-1389 E-mail: yhpark118@gmail.com

Received 30 March 2015 Revised 4 May 2015 Accepted 1 September 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

Abstract

Purpose

The purpose of this study was to investigate individual and organizational level of cardiovascular disease (CVD) risk factors associated with CVD risk in Korean blue-collar workers working in small sized companies.

Methods

Self-report questionnaires and blood sampling for lipid and glucose were collected from 492 workers in 31 small sized companies in Korea. Multilevel modeling was conducted to estimate effects of related factors at the individual and organizational level.

Results

Multilevel regression analysis showed that workers in the workplace having a cafeteria had 1.81 times higher CVD risk after adjusting for factors at the individual level (p=.022). The explanatory power of variables related to organizational level variances in CVD risk was 17.1%.

Conclusion

The results of this study indicate that differences in the CVD risk were related to organizational factors. It is necessary to consider not only individual factors but also organizational factors when planning a CVD risk reduction program. The factors caused by having cafeteria in the workplace can be reduced by improvement in the CVD-related risk environment, therefore an organizational-level intervention approach should be available to reduce CVD risk of workers in small sized companies in Korea.

Keywords: Multilevel analysis, Cardiovascular disease, Risk factors, Workers

References

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Figure 1.

Theoretical framework of this study based on ecological model.

Table 1.

Distribution of CVD Risk of Participants by Gender

Variables	Total (N=492)	Male (n=215)	Female (n=277)
Variables	n (%) or M±SD	n (%) or M±SD	n (%) or M±SD
CVD risk	5.58±5.27	8.01±6.52	3.70±2.88
Low risk	421 (85.6)	159 (74.0)	262 (94.6)
Intermediate risk	57 (11.6)	42 (19.5)	15 (5.4)
High risk	14 (2.8)	14 (6.5)	0 (0.0)

CVD=Cardiovascular disease; CVD Risk=10~year likelihood of developing CVD by Framingham risk score.

Table 2.

Characteristics of Individual Level Factors and CVD Risk (N=492)

Variables	Characteristics	Categories	n (%) or M±SD	CVD Risk	t or F	p
Socio-demographic	Age (yr)		43.95±9.80		0.47^*	<.001
factors	Gender	Male	215 (43.7)	8.01±6.52	9.03	<.001
		Female	277 (56.3)	3.70±2.88
	Marital status	Single	107 (21.7)	4.08±3.88	8.50^†	<.001
		Married	349 (71.0)	5.86±5.24
		Divorce or bereaved	36 (7.3)	7.38±7.73
	Monthly income (10,000 KRW)		294.27±133.85		0.09^*	.037
	Education level	≤Middle school	86 (17.5)	7.51±6.73	5.11^†	.007
		Highschool	320 (65.0)	5.29±4.79
		≥College	86 (17.5)	4.72±4.92
Health-related factors	Health status		2.78±0.78		0.14	.002
	Disease history	No	426 (86.6)	5.44±5.03	− 1.22	.225
		Yes	66 (13.4)	6.48±6.61
	CVD-related family history	No	368 (74.8)	5.49±5.22	− 0.68	.496
		Yes	124 (25.2)	5.86±5.45
	Hypertension history	No	444 (90.2)	4.95±4.58	− 5.80	<.001
		Yes	48 (9.8)	11.14±7.39
	DM history	No	485 (97.4)	5.25±4.80	− 6.05	<.001
		Yes	13 (2.6)	17.75±7.41
	BMI	Underweight	16 (3.3)	4.46±5.04	1.42^†	.253
		Normal	333 (67.7)	5.35±5.29
		Overweight	126 (25.6)	6.01±5.15
		Obesity	17 (3.4)	7.48±5.57
Health behavior-related factors	Physical activity^‡	Low	163 (33.8)	5.14±4.88	0.84	.433
		Moderate	187 (38.8)	5.81±5.75
		High	132 (27.4)	5.80±5.03
	Healthy eating		18.38±5.09		0.02^*	.737
	Smoking	No	378 (76.8)	4.30±3.74	− 7.91	<.001
		Yes	114 (23.2)	9.73±7.10
	Binge drink	No	346 (70.3)	4.90±4.50	− 3.83	<.001
		Yes	146 (29.7)	7.13±6.50
Job-related factors	Overtime work (hrs)	≤60	419 (85.2)	5.41±5.24	− 1.74	.082
		> 60	73 (14.8)	6.57±5.40
	Shift work^§	No	443 (93.1)	5.63±5.44	1.33	.191
		Yes	33 (6.9)	4.86±2.98

^*Spearman's correlation coefficient; ^†Welch estimate coefficient; ^‡n=482, excluded cases by analysis; ^§n=476, excluded cases by analysis; CVD Risk=10-year likelihood of developing CVD by Framingham risk score; PA=Physical activity; SB=Sedentary behavior; KRW=Korean won.

Table 3.

Characteristics of Organizational Level Factors and CVD Risk

Variables	Characteristics	Categories	Organizations	Workers	CVD risk	t	p
Variables	Characteristics	Categories	n (%) or M±SD	n (%) or M±SD	M± SD	t	p
Occupational	Number of employee		76.87± 73.08			− 0.27^*	.145
environment	Having cafeteria in	No	10 (32.3)	62 (12.6)	5.44±5.32	− 1.61	.090
	workplace	Yes	21 (67.7)	430 (87.4)	6.58±4.88
	Having resting area in	No	18 (58.1)	461 (93.7)	6.60±3.41	1.96	.050
	workplace	Yes	13 (41.9)	31 (6.3)	5.04±1.39
Hazard exposure	Chemical hazard exposure	No	29 (93.5)	440 (89.4)	5.80±3.57	− 0.74	.581
		Yes	2 (6.5)	52 (10.6)	6.54±3.01
	Noise exposure	No	19 (61.3)	258 (52.4)	5.06±4.79	− 2.30	.022
		Yes	12 (38.7)	234 (47.6)	6.16±5.71
Health care &	Managed by occupational	No	13 (41.9)	221 (44.9)	6.20±5.86	2.31	.021
monitoring	health nurse	Yes	18 (58.1)	271 (55.1)	5.08±4.68

^* Spearman’s correlation coefficient; CVD Risk=10~year likelihood of developing CVD by Framingham risk score.

Table 4.

Multilevel Model Analysis in CVD Risk Factors of Blue-collar Workers

Parameter		Categories	Model 1		Model 2		Model 3
			Null model		Individual model		Individual-organizational model
			β	p	β	p	β	p
Fixed effect	Level 1	Intercept	6.03	< .001	8.48	<.001	8.09	<.001
		Female (ref: Man)			− 5.94	<.001	− 6.16	<.001
		Married (ref: Single)			3.36	<.001	3.38	<.001
		Divorced/separated (ref: Single)			4.46	<.001	4.46	<.001
		Highschool education (ref: Middle school)			− 2.45	<.001	− 2.58	<.001
		College education (ref: Middle school)			− 3.98	<.001	− 4.06	<.001
		Overtime work			0.53	.399	0.34	.590
		Binge drinking			0.11	.822	0.10	.834
	Level 2	Having resting area					− 0.50	.619
		Noise exposure					− 0.08	.886
		Managed by occupational health nurse					− 0.80	.164
		Having cafeteria in workplace					1.81	.022
Random effect		Level 1, δ²	23.72		18.29		18.10
		Level 2, μ₀ (τ)	4.89		1.02		0.65
		χ²	36.53		4.01		2.25
		p	<.001		.023		.066
		ICC (%)	17.10		5.31		3.45

CVD Risk=10-year likelihood of developing CVD by Framingham risk score; ICC=Intra-class correlation coefficient; t: variance of μ0j.

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