Open Access

Vitamin D status and associated occupational factors in Korean wage workers: data from the 5th Korea national health and nutrition examination survey (KNHANES 2010–2012)

  • Harin Jeong1Email author,
  • Sujin Hong1,
  • Yunjeong Heo1,
  • Hosun Chun1,
  • Daeseong Kim1,
  • Jongtae Park1 and
  • Mo-yeol Kang2
Annals of Occupational and Environmental Medicine201426:28

DOI: 10.1186/s40557-014-0028-x

Received: 7 March 2014

Accepted: 3 September 2014

Published: 16 September 2014

Abstract

Objectives

Vitamin D deficiency is increasing worldwide. However, few studies have attempted to examine the vitamin D status of wage workers and the correlation between vitamin D deficiency and working conditions. Hence, we aimed to evaluate the prevalence of vitamin D deficiency and the association between occupational conditions and vitamin D deficiency among Korean wage workers.

Methods

Wage workers aged 20–65 years from the 5th Korea National Health and Nutrition Examination Survey (KNHANES 2010–2012; n = 5409) were included in our analysis. We measured the prevalence of vitamin D deficiency and identified the correlations with the working conditions of these subjects.

Results

The prevalence of vitamin D deficiency in male and female subjects was 69.5% and 83.1%, respectively. Among the male subjects, a significant correlation between vitamin D deficiency and working conditions was observed among shift workers, office workers, and permanent workers. No significant correlation with any type of working conditions was observed among female subjects.

Conclusion

The prevalence of vitamin D deficiency among Korean wage workers was very high and was found to correlate significantly with working conditions, likely because of insufficient exposure to sunlight associated with certain types of work. Wage workers require more frequent outdoor activity and nutrition management to maintain sufficient vitamin D level.

Keywords

Vitamin D deficiency Shift work Office work Indoor work KNHANES

1 Introduction

Vitamin D (25-hydroxyvitamin D; 25 (OH) D) deficiency is common in the general Korean population, and the increasing trend in vitamin D deficiency is a worldwide phenomenon [1]-[3]. Vitamin D deficiency is thought to be caused by lifestyle factors such as indoor confinement for a considerable period of the day, consumption of an imbalanced diet and low-quality (nutrient-poor) food, and widespread use of sunblock. Furthermore, in many big cities, air pollution and blockage of sunlight by high-rise buildings also contributes to vitamin D deficiency [4],[5].

Workers with vitamin D deficiency often present with common symptoms such as non-specific weakening of the muscles and myalgia, and these symptoms may be confused for fibromyalgia or chronic fatigue syndrome. In many cases, the musculoskeletal diseases of workers are attributed to the intensity of the work they perform or to their posture at work, whereas, unfortunately, vitamin D deficiency is seldom considered the potential cause of the symptoms [6]-[10].

Among the limited number of studies on the topic, most have focused on the prevalence of vitamin D deficiency by job, rather than on establishing a concrete correlation with working conditions [11]. Among the studies on the relationship of vitamin D deficiency and working conditions, limited studies examined miners who work underground for long hours [12]. The theoretical probability of the correlation between vitamin D deficiency and working conditions, such as shift work, has been noted. For example, the lack of vitamin D may play a role in the potential biological mechanisms of shift work as a “carcinogen” [13]. However, despite the theoretical probability of such correlations between working conditions and vitamin D deficiency, few attempts to examine their actual epidemiological correlation have been carried out [14],[15]. Clinical attention to vitamin D deficiency has been mainly focused on growth in children, fractures in the elderly, and decreased bone density [16]-[18]. Perhaps because the causes and treatment of vitamin D deficiency are simple and obvious, researchers have not considered the need to manage the working conditions of healthy workers as well [19].

Vitamin D is widely recognized as important for bone health and maintenance. Moreover, vitamin D, which is known mainly for its role in calcium homeostasis and musculoskeletal conditions such as rickets and osteomalacia, is now also thought to be involved in various disease and pathologic processes such as cancer, cardiovascular disorders, and inflammation. Recently, vitamin D has been reconceptualized as a “hormone” rather than just a “nutrient” [20],[21]. As increasing the vitamin D levels of workers may improve their musculoskeletal status and reduce the risk of chronic diseases, including some cancers, autoimmune diseases, infectious diseases, and type 2 diabetes mellitus, we investigated here the status of vitamin D deficiency and the association between serum vitamin D levels and working conditions in Korean wage workers to identify correctable occupational factors [22]-[24].

2 Materials and methods

2.1 Subjects

The Korea National Health and Nutrition Examination Survey (KNHANES) is one of the most representative surveys of the entire national population of the Republic of Korea. It is administered by the Ministry of Health and Welfare as a means to evaluate the status of health and nutrition of Koreans nationwide. The fifth survey (2010–2012) continued the use of the rolling sampling survey method. This survey separated the ordinary residential areas from areas containing apartments to apply two different sets of sampling frameworks (examining the residential registration data for the ordinary residential areas and surveying market price trends in the apartment areas). Based on the complex samples, each of these areas was internally stratified. Twenty households were surveyed per area, and each household participated in interviews, medical examinations, and nutritional examinations. Interview personnel with relevant training visited the sample households in the area to conduct surveys using structured questionnaires to gather demographic, socio-economic, occupational, and health status information.

Out of the total of 25,534 subjects who participated in the fifth survey (2010–2012), 5,686 subjects who identified themselves as “wage workers” and were aged 20–65 years were selected for this study. Of these subjects, those who answered the questions related to their working conditions with “I do not know” or did not answer (n = 56), those who did not undergo a vitamin D examination (n = 166), and those who did not answer the questions regarding their income, drinking habits, and smoking status (n = 55) were excluded, resulting in 5,409 subjects included in our analysis.

2.2 Classification of data

For this study, data regarding age, income, marital status, education, occupation, whether they worked in shifts, working hours, and total household income were gathered from each of the subjects. The subjects were grouped into 20–29, 30–39, 40–49, and 50–65-year age groups, and were further classified into married and unmarried groups, and into “elementary or lower education”, ”middle school”, “high school” and “college or above” groups. The income level data were calculated by classifying the subjects into quartiles by total household income.

For the question “Do you currently smoke?” the subjects who answered “Yes” were classified as “current smokers” whereas the remaining subjects were grouped as “ex-smokers and non-smokers”. With regard to drinking habits, the subjects were grouped according to whether they had consumed alcohol more than once a month in the past year. As for the nutrition- and exercise-related questions, the subjects were grouped according to whether they had consumed dietary supplements for ≥2 weeks in the past year and whether they performed medium-intensity exercise, accompanied by significant fatigue or shortness of breath, in more than two sessions that lasted for at least 20 minutes each over the past week on ≥3 days in a week.

Vitamin D deficiency is defined by most experts as serum vitamin D levels <20 ng/mL (50 nmol/L), although there is no consensus on the optimal levels of serum vitamin D [25]-[28]. Accordingly, in this study, a cutoff value of 20 ng/mL was used to divide the samples into the “deficiency” group and the “normal” group.

As for the type of occupation, the occupation classification code was used to group the subjects who worked as managers, experts/specialists, or office workers as “office workers”; those who worked in the service or sales sectors as “service workers”; and workers in the fields of agriculture or fishery, and related industries, assembly of machinery, machine operation, and simple labor as “manufacturing workers”. Those who responded that they worked between 6 a.m. and 6 p.m. were classified as “daytime workers”; and those who worked in the afternoon (2 p.m. to midnight), at night (from 9 p.m. to 8 a.m. the following day), in regular rotation of shifts between the day shifts and the night shifts, in 24-h shifts, in segmented shifts (working more than two shifts a day), and in irregular shifts, were all classified as “shift workers”. The number of hours the subjects worked was counted based on their answers to the relevant open question in the questionnaire. Based on their responses, they were grouped into <40 hours per week group (which is the legal limitation of working hours in Korea), the 40 ~ 52 hours per week group (which included the legal overtime limitation), and the 52 ~ 60 hours per week group, ≥60 hours per week group. The workers who had a permanent job were classified “permanent workers”, and the others were classified as “temporary workers”. Finally, the workers who worked on a part-time basis were classified as “part-time workers,” and those who answered that they worked full-time were classified as “full-time workers.”

2.3 Statistical analysis

The design of the samples in the national survey was based on the complex sample design method. To achieve results without biases, the samples must be analyzed using weights, stratified variables, and cluster variables, which are the primary extraction units. Thus, in this study, the statistical data extracted from the fifth national survey were analyzed similarly, using the integrated weights, stratified variables, and cluster variables.

The overall characteristics of the subjects were calculated using frequencies and percentages by gender. The average vitamin D level and the correlation between the prevalence of vitamin D deficiency and the relevant variables were calculated and verified using the t test and the chi-square test. By using logistic regression models, we calculated the odds ratios of vitamin D deficiency associated with the variables on working conditions. The variables showed statistical correlations with vitamin D deficiency in the univariate analyses, and factors already known to affect the vitamin D level (alcohol, smoking, BMI, etc.) were used in the multivariate logistic regression analysis. For the statistical analysis, SPSS version 18.0 (Chicago, IL, USA) was used for statistical analysis, and the statistical significance was set at p < 0.05.

2.4 Ethics statement

We used reconstructed dataset from the 5th Korean National Health and Nutrition Examination Survey (KNHANES 2010-2012). All participants in this survey signed an informed consent form and the survey was approved by the institutional review board of Centers for Disease Control and Prevention in Korea (IRB No. 2010-02CON-21-C, 2011-02CON-06-C, 2012-01EXP-01-2C).

3 Results

The general characteristics of the subjects without the weight applied are shown in Table 1. Of the 5409 subjects in total, 2868 (53.0%) were men, while 2541 (47.0%) were women. The subjects who reported that they worked in shifts accounted for 18.5% (532/2868) of the male subjects and 17.2% (437/2541) of the female subjects. Those who described themselves as permanent workers were 84.8% of the male and 72.1% of the female subjects. A higher proportion of the female subjects than the male subjects were part-time workers, and more women worked in the service industry. Those who worked under the legal limit for working hours (52 hours) comprised 68.8% of the male and 84.7% of the female subjects (Table 1).
Table 1

General characteristics of the subjects

 

Male

Female

Total

N*

%

N

%

N

%

Total (N)

2868

2541

5409

Age (years)

20-29

385

13.4%

548

21.6%

933

17.2%

30-39

903

31.5%

630

24.8%

1533

28.3%

40-49

793

27.6%

630

24.8%

1423

26.3%

50-65

787

27.4%

733

28.8%

1520

28.1%

Body mass index (BMI) (n = 5393)

<23

1040

36.4%

1472

58.1%

2512

46.6%

23-25

741

25.9%

489

19.3%

1230

22.8%

≥25

1077

37.7%

574

22.6%

1651

30.6%

Dietary supplementation (n = 4590)

Yes

922

40.3%

1182

51.4%

2104

45.8%

No

1368

59.7%

1118

48.6%

2486

54.2%

Physical activity

Yes

254

8.9%

223

8.8%

477

8.8%

No

2614

91.1%

2317

91.2%

4931

91.2%

Drinking

Yes

2249

78.4%

1252

49.3%

3501

64.7%

No

619

21.6%

1289

50.7%

1908

35.3%

Smoking status

None/ex-smoker

1553

54.1%

2372

93.3%

3925

72.6%

Current smoker

1315

45.9%

169

6.7%

1484

27.4%

Marital status

Married

2324

81.0%

1910

75.2%

4234

78.3%

Unmarried

544

19.0%

631

24.8%

1175

21.7%

Income (quartile)

Low

154

5.4%

216

8.5%

370

6.8%

Middle low

739

25.8%

645

25.4%

1384

25.6%

Middle high

1020

35.6%

837

32.9%

1857

34.3%

High

955

33.3%

843

33.2%

1798

33.2%

Education

Less than elementary school

121

4.2%

285

11.2%

406

7.5%

Middle school

183

6.4%

258

10.2%

441

8.2%

High school

889

31.0%

831

32.7%

1720

31.8%

More than college

1675

58.4%

1167

45.9%

2842

52.5%

Shift work

Yes

532

18.5%

437

17.2%

969

17.9%

No

2336

81.5%

2104

82.8%

4440

82.1%

Stability of work

Permanent worker

2432

84.8%

1831

72.1%

4263

78.8%

Temporary worker

436

15.2%

710

27.9%

1146

21.2%

Employment type

Part-time worker

167

5.8%

638

25.1%

805

14.9%

Full-time worker

2701

94.2%

1903

74.9%

4604

85.1%

Occupation

Office worker

1427

49.8%

1232

48.5%

2659

49.2%

Service worker

291

10.1%

598

23.5%

889

16.4%

Manufacturing worker

1150

40.1%

711

28.0%

1861

34.4%

Working hours/week

<40

413

14.4%

963

37.9%

1376

25.4%

40-52

1561

54.4%

1188

46.8%

2749

50.8%

52-60

332

11.6%

188

7.4%

520

9.6%

≥60

562

19.6%

202

7.9%

764

14.1%

*Unweighted count.

The results of a chi-square analysis using weight are shown in Tables 2 and 3. The vitamin D deficiency prevalence of men and women, respectively, were 69.5% and 83.1%. Among the male subjects, the prevalence of vitamin D deficiency showed a significant difference depending on the use of food supplements, marital status, and education level. Furthermore, working conditions such as shift work, permanent work, and occupation contributed to significant differences as well (p < 0.05) (Table 2).
Table 2

Vitamin D status according to variables (Male)

 

Vitamin D (ng/ml)

Vitamin D

p-value

≥20 ng/ml

<20 ng/ml

Mean (S.E)°

N§

%(S.E)

N

%(S.E)

Total

17.8(0.175)

7434830

30.5(1.3)

16921262

69.5(1.3)

 

Age (years)

20-29

16.7(0.314)

1204327

22.8(2.6)

4068221

77.2(2.6)

<0.001

30-39

17.3(0.240)

2139963

27.5(1.9)

5636522

72.5(1.9)

40-49

18.3(0.284)

2230488

34.0(2.4)

4330483

66.0(2.4)

50-65

19.2(0.291)

1860052

39.2(2.3)

2886036

60.8(2.3)

Body mass index (BMI) (n = 5393)

<23

17.7(0.248)

2706131

29.7(1.8)

6390223

70.3(1.8)

0.711

23-25

18.1(0.250)

1959023

31.9(2.2)

4177771

68.1(2.2)

≥25

17.8(0.229)

2769676

30.7(1.9)

6263714

69.3(1.9)

Dietary supplementation (n = 4590)

Yes

18.4(0.226)

3515136

35.1(2.0)

8538062

64.9(2.0)

0.015

No

17.6(0.226)

2489982

29.2(1.7)

4608936

70.8(1.7)

Physical activity

Yes

18.8(0.463)

942016

38.5(3.7)

1501849

61.5(3.7)

0.17

No

17.7(0.178)

6492814

29.6(1.4)

15419414

70.4(1.6)

Drinking

Yes

17.8(0.177)

5860951

30.6(1.4)

13320375

69.4(1.4)

0.958

No

17.7(0.348)

1573879

30.4(2.6)

3600887

69.6(2.6)

Smoking status

None/ex-smoker

17.9(0.194)

3787159

30.7(1.6)

8534766

69.3(1.6)

0.828

Current smoker

17.7(0.228)

3647671

30.3(1.7)

8386496

69.3(1.7)

Marital status

Married

18.3(0.186)

5891190

33.7(1.5)

11592550

66.3(1.5)

<0.001

Unmarried

16.6(0.281)

1543640

22.5(2.0)

5328712

77.5(2.0)

Income (quartile)

Low

18.1(0.541)

549598

34.8(4.8)

1027913

65.2(4.8)

0.546

Middle low

18.0(0.299)

2183872

31.9(2.4)

4670497

68.1(2.4)

Middle high

17.6(0.232)

2641618

29.9(1.8)

6183484

70.1(1.8)

High

17.9(0.228)

2059742

29.0(1.8)

5039367

71.0(1.8)

Education

Less than elementary school

19.1(0.682)

359510

40.1(6.2)

536938

59.9(6.2)

<0.001

Middle school

19.4(0.523)

600130

43.6(4.3)

777380

56.4(4.3)

High school

18.3(0.296)

2782314

34.8(2.1)

5208570

65.2(2.1)

More than college

17.3(0.189)

3692876

26.2(1.5)

10398374

73.8(1.5)

Shift work

Yes

17.0(0.316)

1119179

24.4(2.3)

3458301

75.6(2.3)

0.004

No

18.0(0.185)

6315651

31.9(1.5)

13462961

68.1(1.5)

Stability of work

Permanent worker

17.6(0.171)

5746351

28.9(1.3)

14165812

71.1(1.3)

0.003

Temporary worker

18.8(0.379)

1688479

38.0(3.2)

2755451

62.0(3.2)

Employment type

Part-time worker

17.8(0.542)

493566

28.4(4.3)

1245957

71.6(4.3)

0.593

Full-time worker

17.8(0.174)

6941264

30.7(1.3)

15675306

69.3(1.3)

Occupation

Office worker

17.3(0.192)

2918874

26.2(1.6)

8205357

73.8(1.6)

<0.001

Service worker

17.1(0.375)

768684

26.2(3.4)

2164465

73.8(3.4)

Manufacturing worker

18.6(0.273)

3747272

36.4(2.0)

6551440

63.6(2.0)

Working hours/week

<40

17.9(0.365)

1188552

31.4(2.7)

2595496

68.6(2.7)

0.874

40-52

17.7(0.211)

3820692

29.8(1.7)

9001176

70.2(1.7)

52-60

18.0(0.379)

942670

32.3(3.4)

1976736

67.7(3.4)

≥60

17.9(0.290)

1482916

30.7(2.5)

3347854

69.3(2.5)

S.E; standard error, § estimated population size.

Table 3

Vitamin D status according to variables (Female)

 

Vitamin D (ng/ml)

Vitamin D

p-value

≥20 ng/ml

<20 ng/ml

Mean (S.E)°

N§

%(S.E)

N

%(S.E)

Total

15.6(0.163)

2748248

16.9(1.1)

13530639

83.1(1.1)

 

Age (years)

20-29

14.1(0.251)

383860

8.4(1.6)

4159095

91.6(1.6)

<0.001

30-39

15.3(0.283)

542108

14.9(1.9)

3098926

85.1(1.9)

40-49

15.6(0.268)

724950

16.7(2.0)

3613641

83.3(2.0)

50-65

17.5(0.271)

1097330

29.2(2.1)

2658978

70.8(2.1)

Body mass index (BMI) (n = 5393)

<23

15.3(0.195)

1457436

15.3(1.2)

8095076

84.7(1.2)

0.033

23-25

16.2(0.293)

642163

21.2(2.2)

2382941

78.8(2.2)

≥25

15.5(0.249)

631525

17.3(1.9)

3026934

82.7(1.9)

Dietary supplementation (n = 4590)

Yes

16.4(0.224)

1587530

22.1(1.6)

5583799

77.9(1.6)

<0.001

No

14.7(0.194)

874424

12.0(1.2)

6426624

88.0(1.2)

Physical activity

Yes

16.4(0.440)

260879

19.0(3.2)

1110135

81.0(3.2)

0.455

No

15.5(0.164)

2487369

16.7(1.1)

12415666

83.3(1.1)

Drinking

Yes

15.7(0.212)

1380747

16.0(1.4)

7252876

84.0(1.4)

0.298

No

15.4(0.199)

1367501

17.9(1.4)

6277763

82.1(1.4)

Smoking status

None/ex-smoker

15.5(0.161)

2495022

16.7(1.0)

12432922

83.3(1.0)

0.564

Current smoker

15.7(0.498)

253226

18.7(3.8)

1097717

81.3(3.8)

Marital status

Married

16.2(0.187)

2321272

20.4(1.3)

9058540

79.6(1.3)

<0.001

Unmarried

14.1(0.234)

426976

8.7(1.3)

4472099

91.3(1.3)

Income (quartile)

Low

16.9(0.502)

368499

27.6(3.7)

968252

72.4(3.7)

<0.001

Middle low

15.9(0.287)

932271

21.3(2.1)

3434927

78.7(2.1)

Middle high

15.3(0.234)

758403

13.7(1.5)

4762438

86.3(1.5)

High

15.3(0.234)

689075

13.6(1.5)

4365022

86.4(1.5)

Education

Less than elementary school

17.5(0.366)

467909

30.7(3.1)

1056651

69.3(3.1)

<0.001

Middle school

17.1(0.436)

370744

24.0(2.9)

1174167

76.0(2.9)

High school

15.3(0.240)

978233

17.2(1.8)

4698721

82.8(1.8)

More than college

15.0(0.198)

931362

12.4(1.2)

6601101

87.6(1.2)

Shift work

Yes

14.8(0.314)

443644

14.4(2.1)

2637092

85.6(2.1)

0.183

No

15.7(0.172)

2304604

17.5(1.2)

10893547

82.5(1.2)

Stability of work

Permanent worker

15.3(0.184)

1810551

15.3(1.2)

10038350

84.7(1.2)

0.01

Temporary worker

16.3(0.254)

937697

21.2(2.1)

3492290

78.8(2.1)

Employment type

Part-time worker

16.0(0.280)

830474

21.0(2.1)

3127546

79.0(2.1)

0.014

Full-time worker

15.4(0.177)

1917774

15.6(1.2)

10403093

84.4(1.2)

Occupation

Office worker

15.0(0.203)

945750

11.9(1.2)

6993107

88.1(1.2)

<0.001

Service worker

15.9(0.304)

784657

19.9(2.1)

3154425

80.1(2.1)

Manufacturing worker

16.3(0.262)

1017841

23.1(2.0)

3383107

76.9(2.0)

Working hours/week

<40

16.1(0.217)

1168254

19.9(1.7)

4701664

80.1(1.7)

0.029

40-52

15.2(0.201)

1077340

14.1(1.2)

6549011

85.9(1.2)

52-60

15.3(0.472)

243282

17.8(3.5)

1126308

82.2(3.5)

≥60

15.2(0.435)

259372

18.4(3.2)

1153657

81.6(3.2)

S.E; standard error, § estimated population size.

Among the female subjects, BMI, food supplements, marital status, family income, and education level contributed to significant differences in the prevalence of vitamin D deficiency. The permanent workers (84.7%) showed a higher prevalence of vitamin D deficiency compared to the temporary workers (78.8%), while the prevalence of vitamin D deficiency among the office workers was 88.1%, which was considerably higher than that of the manufacturing workers (79.0%) (Table 3).

The result of a logistic regression model analysis for the male subjects showed that the risk of vitamin D deficiency significantly increased with shift work, permanent work, and office work. After some variables were adjusted, the odds ratio of the shift workers (vs. daytime workers) was 1.456 (CI 1.089-1.946), while the odds ratio of the permanent workers (vs. temporary workers) was 1.420 (CI 1.019 – 1.979). The univariate analysis by occupation showed that the office workers and the service workers both showed significant correlations with vitamin D level. However, after adjustment, only the office workers showed a significant odds ratio of 1.478 (CI 1.098-1.990). Of the female subjects, the correlation between their working conditions and vitamin D deficiency disappeared, which made it impossible to identify a clear occupational factor for vitamin D deficiency (Table 4).
Table 4

Logistic regression analyses of working conditions

  

Male

Female

  

Crude OR(95% CI)

Adjusted OR(95% CI)*

Crude OR(95% CI)

Adjusted OR(95% CI)*

Shift work

Yes

1.449(1.119-1.876)

1.456(1.089-1.946)

1.258(0.893-1.773)

1.357(0.920-2.004)

No

Reference

Reference

Reference

Reference

Stability of work

Permanent worker

1.511(1.158-1.971)

1.420(1.019-1.979)

1.489(1.105-2.006)

0.977(0.685-1.392)

Temporary worker

Reference

Reference

Reference

Reference

Employment type

Part-time worker

1.118(0.740-1.688)

1.086(0.641-1.841)

0.694(0.521-0.924)

0.844(0.578-1.234)

Full-time worker

Reference

Reference

Reference

Reference

Occupation

Office worker

1.608(1.302-1.985)

1.478(1.098-1.990)

2.225(1.657-2.986)

1.141(0.752-1.730)

Service worker

1.611(1.105-2.347)

1.202(0.788-1.834)

1.209(0.882-1.659)

1.052(0.740-1.497)

Manufacturing worker

Reference

Reference

Reference

Reference

Working hours/week

<40

0.967(0.703-1.331)

1.077(0.720-1.612)

0.905(0.579-1.415)

0.965(0.564-1.652)

40-52

1.044(0.812-1.341)

0.927(0.701-1.225)

1.367(0.874-2.137)

1.025(0.601-1.746)

52-60

0.929(0.638-1.352)

0.916(0.616-1.364)

1.041(0.571-1.897)

0.684(0.348-1.344)

≥60

Reference

Reference

Reference

Reference

*OR; odds ratio, CI; confidence intervals.

Adjusted for age, BMI, socioeconomic status (income, marriage, education level).

Health behavior (smoking status, alcohol use, dietary supplement use, physical activity).

4 Discussion

This study confirmed that the prevalence of vitamin D deficiency was very high among the wage workers of Korea. Furthermore, we showed here that occupational factors such as shift work and office work were related to an increased risk of vitamin D deficiency in the male subjects. Only a few previous studies have suggested correlations between vitamin D deficiency and working conditions. In 2011, a British cohort study revealed that women, but not men, working at night and longer hours might be vulnerable to deficits in vitamin D and to the associated health hazards. According to the authors, that was the first study exploring the relationship between different occupations and vitamin D deficiency [14].

It seems that the differences in the risk for vitamin D deficiency in subjects working in shifts and according to the type of work (e.g. office work) are directly related to exposure to sunlight. Vitamin D can either be absorbed from food or naturally synthesized in the body upon skin exposure to sunlight. It is stored in the human body as a precursor vitamin D molecule, which is converted to the active and free form when it is exposed to ultraviolet B (UV-B) radiation (wavelength, 280–320 nm). Active vitamin D helps the body to absorb calcium and controls the density of calcium in our body [29].

Approximately 90% of the vitamin D in our body is generated upon exposure to sunlight, and the remaining 10% can be absorbed from ingested food. Among UV bands, only UV-B can trigger the synthesis of vitamin D. UV-B cannot penetrate glass; therefore, exposure to sunlight indoors through a window does not produce vitamin D. As a general rule, the more oblique the incidence angle at which sunlight passes, the more UV-B light is absorbed; therefore, only sunlight produced in the middle of the day (between about 10:00 and 15:00) is effective for synthesis of vitamin D, and if people are not exposed to adequate sunlight during this time, they may be at risk of developing vitamin D deficiency [30],[31].

Interestingly, among the male subjects, the permanent workers showed a higher prevalence of vitamin D deficiency than the temporary workers. The male permanent workers worked an average of 49.2 hours/a week, while the temporary male workers worked an average of 40 hours/a week (p < 0.001; data not shown in table). Since the temporary workers included daily workers or part-time workers, it would make sense that the routine activities and the standardized work patterns of permanent workers affect their outdoor activities and exposure to sunlight, rather than interpreting the permanent workers as the risk group for vitamin D deficiency.

Meanwhile, in our study, we failed to show a correlation between working hours and vitamin D deficiency. We believe that this result might have arisen from the fact that the subjects reported the number of their working hours as an answer to an open-ended question, which was subjective. Moreover, the exposure to sunlight, which is not necessarily work-related, might differ among individuals. Therefore, the number of working hours should also be investigated while taking into account other factors.

In the females, it was not possible to confirm a clear correlation between vitamin D levels and working conditions. The majority of the female workers (84.7%) reported that they worked under the maximum number of legal working hours (52 hours/week), while the proportion of those working part-time jobs, which was 25.1%, was also significantly higher than that of the male subjects. This signified that, among the female subjects, other variables beyond occupational conditions, such as quantity of housework, affect sunlight exposure and thus, in turn, vitamin D levels [32],[33].

Opinions are conflicting regarding the appropriate cut-off values for defining the optimal levels of vitamin D. Men and women differ in terms of body size, muscle mass, and body fat, so their vitamin D metabolism and storage are also different [34]-[36]. The men in our study were more actively engaged in outdoor activities, while the women used cosmetics or sunscreen, which could have added another factor explaining the differences. Broader discussion is needed on whether it is appropriate to apply the same cut-off value of 20 ng/mL vitamin D to both genders. As women have tended to show a much higher prevalence of vitamin D deficiency when the cut-off value was set at 20 ng/mL, it could be appropriate to apply a lower value for females.

Recently, many studies have supported the necessity of vitamin D management. Vitamin D plays a crucial role in preventing rickets or osteoporosis by helping to store calcium in the bones. One of the most serious forms of complications of vitamin D deficiency is osteomalacia, which is caused by low blood calcium and phosphate levels. Moreover, subclinical vitamin D deficiency could result in a non-symptomatic drop in bone density [37].

Previous reports on the correlation of vitamin D with cardiovascular disorders, cancers, and non-musculoskeletal disease, apart from its already-known effects on musculoskeletal systems, indicate the need for more proactive efforts to manage vitamin D deficiency [19],[23],[38]-[40]. Vitamin D has, moreover, been demonstrated to affect certain genes regulating blood pressure, increase the calcium levels in human cells, and stimulate immune cells to prevent inflammation or thrombosis in blood vessels [41],[42]. Epidemiologic studies have reported that a person with vitamin D levels ≤15 ng/mL is at twice the risk of myocardial infarction over those with vitamin D levels ≥30 ng/mL [40]. Moreover, it has also been reported that people with vitamin D levels of ≤15 ng/mL have a 2.7–8.1 times higher risk of hypertension in the following 4–8 years [43]. There have been other reports suggesting that vitamin D deficiency is related to various cancers such as stomach, colon, breast, and prostate cancer, and it is believed that active vitamin D from various local tissues is capable of inducing cellular differentiation and the death of cancer cells [44],[45].

While few studies have been conducted on the consequences of vitamin D deficiency in wage workers specifically, recent reports have confirmed the correlation between vitamin D deficiency in workers and their Framingham score, a cardiovascular risk score [46]. In a cross-sectional study of 10,646 health care workers, a correlation between vitamin D levels and presenteeism (the problem of workers’ being at their workplace but not fully functioning due to temporary illness or massive stress) was also confirmed, suggesting that vitamin D deficiency has the potential to undermine the productivity of workers [47].

It is generally sufficient to expose a portion of the body to sunlight for approximately 20 min a day to maintain sufficient levels of vitamin D [38],[48]. However, if a worker works in shifts or is in the office the whole day, the opportunity for sunlight exposure will inevitably be decreased. In addition, numerous factors affect vitamin D production, including the weather, time of day, latitude, air pollution, sunblock use, and clothing. Therefore, simply recommending outdoor activities is not a satisfactory solution. In the absence of other options, dietary supplements fortified with vitamin D could be used as an alternative solution.

Foods with a high vitamin D level include fish such as salmon, anchovies, and mackerel, as well as dairy products such as milk. However, the maximum amount of vitamin D available in food is only approximately 100 IU/day [49]. The rest of the vitamin D requirement should be obtained from vitamin D supplements or milk products with fortified with additional vitamin D. Consumption of foods fortified with vitamin D may increase the daily intake by up to 800–1000 IU [37]. Therefore, dietary supplementation should be planned based on these facts in the workplace [37],[50].

This study has a few limitations. First, since this was a cross-sectional study, it was unclear whether the working conditions were responsible for the vitamin D deficiency. Second, the lack of information on exposure to sunlight (i.e., individual outdoor activity, sun exposure during work) and the amount of vitamin D consumed by the subjects limited the drawing of firm conclusions. Third, the Korea National Health and Nutrition Examination Survey was taken over 48 weeks a year at random times from January to December over 3 years, and the date of the examination was not disclosed for privacy. However, the amount of sunlight exposure is influenced by the seasons [51], and we could not control the data for seasonal factors, which may be important confounders.

While few studies have addressed the relationship between vitamin D deficiency and working conditions, this study was based on one of the most nationally representative data sets produced in Korea, from which it was possible to demonstrate the effects of working in shifts and office work on vitamin D deficiency. This study provided reasonable evidence of the need for vitamin D management in Korean wage workers. Since this study identified only the work-related factors that showed correlations with vitamin D deficiency, further studies are needed to supplement these findings, including studies focusing on complications of vitamin D deficiency (musculoskeletal/non-musculoskeletal) and actual effects on work productivity.

5 Conclusion

The increased prevalence of vitamin D deficiency is attracting more and more attention worldwide, and reports on its correlation with diseases other than musculoskeletal disorders, such as cardiovascular disorders and diabetes, have made it a popular issue in public health. While a number of reports have shown correlations between lack of sunlight exposure and vitamin D deficiency, few studies have examined the correlation between vitamin D deficiency and working conditions. Our analysis showed an association of shift work and office work with vitamin D deficiency. It should be noted, however, that the prevalence of vitamin D deficiency in all the subjects was very high. It is essential to manage the vitamin D status of wage workers to maintain the productivity of a company’s entire workforce.

Declarations

Acknowledgements

There is no conflict of interest or financial support to declare.

Authors’ Affiliations

(1)
Department of Occupational Medicine, Korea University Hosipital
(2)
Department of Occupational Medicine, Wonjin green hospital

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