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Original Article
- Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study
- Won Ju Hwang1, Yunhee Park2
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Journal of Korean Academy of Nursing 2015;45(6):857-867.
DOI: https://doi.org/10.4040/jkan.2015.45.6.857
Published online: December 15, 2015
1College of Nursing Science· East-west Nursing Research Institute, Kyung Hee University, Seoul
2Department of Nursing, Youngdong University, Youngdong, Korea
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: March 30, 2015 • Revised: May 4, 2015 • Accepted: September 1, 2015
Copyright © 2015 Korean Society of Nursing Science
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.
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Abstract
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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.
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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.
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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%.
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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.
Table 1.Distribution of CVD Risk of Participants by Gender
Table 2.Characteristics of Individual Level Factors and CVD Risk (N=492)
Table 3.Characteristics of Organizational Level Factors and CVD Risk
| Variables | Characteristics | Categories |
Organizations |
Workers |
CVD risk |
t | p |
|---|---|---|---|---|---|---|---|
| n (%) or M±SD | n (%) or M±SD | M± SD | |||||
| 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 |
Table 4.Multilevel Model Analysis in CVD Risk Factors of Blue-collar Workers
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Figure 1. Theoretical framework of this study based on ecological model.
Figure 1.
Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study
| Variables | Total (N=492) |
Male (n=215) |
Female (n=277) |
|---|---|---|---|
| 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) |
| 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 |
| Variables | Characteristics | Categories | Organizations |
Workers |
CVD risk |
t | p |
|---|---|---|---|---|---|---|---|
| n (%) or M±SD | n (%) or M±SD | M± SD | |||||
| 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 |
| 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 | |||||
Table 1. Distribution of CVD Risk of Participants by Gender
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)
*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
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
CVD Risk=10-year likelihood of developing CVD by Framingham risk score; ICC=Intra-class correlation coefficient; t: variance of μ0j.
