Published online before print July 14, 2008, doi: 10.1161/HYPERTENSIONAHA.108.114553
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(Hypertension. 2008;52:581.)
© 2008 American Heart Association, Inc.
Original Articles |
Shift Work Is a Risk Factor for Increased Blood Pressure in Japanese Men
A 14-Year Historical Cohort Study
From the Department of Occupational and Environmental Medicine, Graduate School of Medicine (Y.S., M.D., K.S., M.O., K.T., E.K., K.N.), and Center for Preventive Medical Science (Y.S.), Chiba University, Chiba, Japan; and the Health Care Center (Y.O.), University of Tokyo, Tokyo, Japan.
Correspondence to Yasushi Suwazono, Department of Occupational and Environmental Medicine (A2), Graduate School of Medicine, Chiba University, 1-8-1, Inohana, Chuoku, Chiba, 260-8670 Japan. E-mail suwa{at}faculty.chiba-u.jp
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Abstract |
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To clarify the effect of shift work on blood pressure in Japanese men, a 14-year historical cohort study was conducted in day workers (n=3963) and alternating shift workers (n=2748) who received annual health checkups between 1991 and 2005 in a Japanese steel company. The end points were a
10%, 15%, 20%, 25%, or 30% increase in systolic blood pressure or diastolic blood pressure from baseline during the period of observation. The association between shift work and an increase in blood pressure was investigated adjusting for age, body mass index, hemoglobin A1c, total serum cholesterol, creatinine, aspartate aminotransferase, 
-glutamyl transpeptidase, uric acid, drinking habit, smoking habit, and habitual exercise by multivariate pooled logistic regression analyses. Shift work was significantly associated with the various end points. The odds ratios (and 95% CIs) were as follows: 10%, 1.15 (1.07 to 1.23); 15%, 1.21 (1.12 to 1.31); 20%, 1.15 (1.04 to 1.28); 25%, 1.20 (1.06 to 1.37); and 30%, 1.23 (1.03 to 1.47) for systolic blood pressure and 10%, 1.19 (1.11 to 1.28); 15%, 1.22 (1.13 to 1.33); 20%, 1.24 (1.13 to 1.37); and 25%, 1.16 (1.03 to 1.30) for diastolic blood pressure. Our study in male Japanese workers revealed that alternating shift work was a significant independent risk factor for an increase in blood pressure. Moreover, the effect of shift work on blood pressure was more pronounced than other well-established factors, such as age and body mass index.
Key Words: shift work • blood pressure • cohort study • primary prevention • epidemiology • risk factors • Japanese
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Introduction |
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Industrialization in Japan and other countries has led to the widespread adoption of 24-hour continuous operations in a number of industries. This has resulted in an increase in the proportion of the population engaged routinely in shift work.1 The Ministry of Health, Labor, and Welfare reported that 22.7% of Japanese companies employed shift workers in 2005.1 More than half (51.2%) of large companies with
1000 employees adopted a shift work schedule that includes fixed night work and alternating shift work.1 Although the effect of shift work on health has been studied extensively in other countries, a longitudinal investigation of the effect of shift work on the health of Japanese workers is important and urgently required. An association between shift work and cardiovascular disease has been reported,2–5 with disturbed circadian rhythms, sleep and lifestyle problems, and increased stress implicated as possible risk factors for disease. Other studies have reported that elevated serum triglyceride6–8 and lower concentrations of high-density lipoprotein cholesterol6,7 tend to occur more frequently in shift workers than fixed daytime workers. Furthermore, insulin sensitivity is known to be lower at night than during the day.9,10 Two studies11,12 reported significant increases in the risk of diabetes mellitus in shift workers. In addition, sleep debt has a harmful impact on carbohydrate metabolism and endocrine function.13 Moreover, 2 cohort studies14,15 have reported an association between shift work and the risk of obesity or weight gain. It is, therefore, reasonable to expect that shift work may influence blood pressure and that alternating between day shifts and night shifts, as occurs in alternating shift work, may be particularly deleterious to the health of workers. A significant association between shift work and blood pressure has been reported in several studies,8,16–19 which used a cross-sectional study design. Recently, several longitudinal studies in Japan reported that shift work was a risk factor for the onset of hypertension20,21 and the progression from mild hypertension to severe hypertension.22 However, these previous studies excluded subjects whose blood pressure was >140/90 mm Hg20,21 or >160/100 mm Hg or <140/90 mm Hg22 at their first health examination. We think that the effect of shift work on blood pressure could be established explicitly by conducting a survey on all subjects regardless of exclusion based on those cutoff values for blood pressure. As far as we know, such a survey has not yet been conducted. This issue prompted us to use the relative increase of blood pressure to minimize the initial exclusion of subjects from the cohort. Thus, we decided to conduct a historical cohort study to clarify the effect of alternating shift work on relative increases in blood pressure and to generalize the findings of previously reported studies. The study used a pooled logistic regression model, which accounted for the effects of confounding variables on blood pressure and, also, fluctuations in the confounding variables over time. |
Methods |
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Subjects
This historical cohort study included observations made over a 14-year period from 1991 to 2005 in 8251 male workers at a Japanese steel company. No female employees were engaged in alternating shift work. The cohort included only subjects who attended annual health examinations during the observation period. More than 98% of the workers in the company underwent an annual health examination. Subjects treated previously for hypertension were excluded, whereas subjects who began therapy for hypertension were classified as censored cases. The type-of-job schedule (ie, shift work or day work) was determined from the payment ledger in May of each year. Workers engaged in irregular shift work, such as 24-hour work and fixed night work, were excluded. The shifts were scheduled on a 4-team/3-shift plan with clockwise rotation (5 day shifts, 2 rest days, 5 evening shifts, 1 rest day, 5 night shifts, and 2 rest days). The day, evening, and night shifts started at 7 AM, 3 PM, and 11 PM, respectively. The following individuals were excluded from this study: those receiving a health examination for the first time in the final year (2005) of the follow up period (n=504), those who had therapy initiated for hypertension before or in the year of entry (n=213), those who had therapy initiated for hypertension in the subsequent year (n=40), those with any missing data in the year of entry (n=440), those who did not receive a health examination in the subsequent year (n=342), and those for whom the measurement of blood pressure was missing in the subsequent year (n=1). Those in the latter 3 categories (535 day workers and 248 shift workers) who were excluded because of missing data had a mean±SD age of 39.7±13.2 years, systolic blood pressure (SBP) of 128.7±15.9 mm Hg, and diastolic blood pressure (DBP) of 78.8±11.7 mm Hg. Because the actual differences in age (3.5 years), SBP (2.6 mm Hg), and DBP (1.4 mm Hg) were small, there are no major inconsistencies between the excluded and included individuals. Therefore, exclusion of these individuals would be unlikely to cause bias. There were 6711 workers (3963 day workers and 2748 alternating shift workers) that composed the cohort used for all of the analyses. The study protocol was approved by the ethics review board of the Chiba University Graduate School of Medicine.
Measurements
At the annual health examination, blood pressure was measured once in the sitting position with an automatic sphygmomanometer (BP203, Colin Medical Instruments Co, Ltd) after 5 minutes of rest. The time of health examination, including blood pressure measurement and blood sampling, was between 9 AM and 3 PM throughout the study period. None of the measurements were taken within 30 minutes after a meal or heavy physical activity. The cuff automatically adjusted to the subjects’ arm circumference, ranging from 23 cm to 32 cm. The accuracy of this automatic sphygmomanometer has been reported elsewhere.23 The workers’ medical history was recorded during the annual health examinations using a self-administered questionnaire. These responses were confirmed by individual interviews conducted by occupational physicians. The end points were 10%, 15%, 20%, 25%, or 30% increases in SBP or DBP from baseline during the period of observation. Age, body mass index (BMI), glycohemoglobin A1c (HbA1c), total serum cholesterol, creatinine, aspartate aminotransferase (AST), -glutamyl transpeptidase (GGT), and uric acid (UA) were measured during the study and entered as covariates in the analysis, along with drinking and smoking habits and regular exercise. The laboratory tests were conducted in comprehensive clinical testing laboratories that have been guaranteed by an official certification organization. There was no change in the methods of laboratory tests, which required conversion because of significant differences. Drinking and smoking habits and habitual exercise were recorded at the annual health examinations using self-administered questionnaires. The workers were classified as either "drinking every day" or "not drinking every day," smokers or nonsmokers, and subjects who did or did not exercise regularly.
Statistical Analysis
For the univariate analysis, the means of SBP, DBP, age, BMI, HbA1c, total serum cholesterol, creatinine, AST, GGT, and UA at baseline were calculated. Differences in these variables between alternating shift and day workers were then evaluated using a Mann-Whitney U test. Differences in drinking, smoking, and exercise habits between the 2 groups were evaluated by the 
2 test. In the multivariate analysis, a pooled logistic regression analysis was used to evaluate the effect of alternating shift work on each of the 5 SBP and DBP end points measured annually. All of the covariates were included simultaneously in the statistical model. Using this method, the derived odds ratios (ORs) for the end points were adjusted for the effects of the other covariates. We estimated the ORs for a 1-SD (SD of all of the subjects at their first health examination shown in Table 1) increase in age, BMI, HbA1c, total serum cholesterol, creatinine, AST, GGT, and UA to make the ORs for the different continuous variables comparable. We chose the covariates from the available items of the annual health examination conducted every year as much as possible, without overlapping with other measurements (such as AST and ALT for liver dysfunction) to avoid colinearity in the logistic model. Furthermore, there were significant differences in the baseline measurements between day workers and shift workers, as shown in Table 1. Therefore, we thought adjustment for all of the available covariates by including them in the model was absolutely imperative to avoid a confounding bias because of differences in baseline variables between day and shift workers. In these multivariate analyses, each yearly interval was treated as an independent observation. The analyses were performed with SPSS 12.0.1J software (SPSS Japan Inc). A P value of <0.05 was considered to be statistically significant.
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Results |
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Table 1 summarizes the baseline characteristics of the alternating shift workers and day workers at the year of entry into the study. SBP, BMI, HbA1c, creatinine, and UA were significantly higher in day workers compared with alternating shift workers, whereas the alternating shift workers were significantly older and had a higher AST. The percentage of subjects who drank or smoked everyday or who did not carry out habitual exercise was significantly higher in alternating shift workers than in day workers. The number of subjects and person-years studied are shown in Table 2. Of the subjects in the cohort, 56.8%, 38.4%, 24.1%, 14.2%, and 7.4% developed
10%, 15%, 20%, 25%, and 30% increases in SBP, respectively; and 56.6%, 40.4%, 26.7%, 16.8%, and 9.6% developed 10%, 15%, 20%, 25%, and 30% increases in DBP, respectively.
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Table 3 shows the results of the pooled logistic regression analysis for increases in SBP. The ORs and 95% CIs are grouped according to the SBP end points. The type-of-job schedule was associated significantly with all 5 of the SBP end points (10%, OR: 1.15 [95% CI: 1.07 to 1.23]; 15%, OR: 1.21 [95% CI: 1.12 to 1.31]; 20%, OR: 1.15 [95% CI: 1.04 to 1.28]; 25%, OR: 1.20 [95% CI: 1.06 to 1.37]; and 30%, OR: 1.23 [95% CI: 1.03 to 1.47]). Multiple significant ORs were obtained for age (positive: 20%, 25%, and 30%), creatinine (positive: 10% and 15%), and drinking habits (negative: 20% and 25%). No consistent relationship was observed for BMI, HbA1c, total serum cholesterol, AST, GGT, smoking, or exercise habits.
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Table 4 shows the ORs and 95% CIs grouped according to the DBP end points using pooled logistic regression analysis. The type-of-job schedule was associated significantly with 4 DBP end points (10%, OR: 1.19 [95% CI: 1.11 to 1.28]; 15%, OR: 1.22 [95% CI: 1.13 to 1.33]; 20%, OR: 1.24 [95% CI: 1.13 to 1.37]; and 25%, OR: 1.16 [95% CI: 1.03 to 1.30]). Age was negatively associated with all 5 of the DBP end points. Multiple significant ORs were obtained for HbA1c (negative: 10% and 15%) and UA (negative: 10% and 15%). No consistent relationship was observed for BMI, total serum cholesterol, creatinine, AST, GGT, drinking, smoking, or exercise habits.
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Discussion |
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In this 14-year historical cohort study, we examined whether alternating shift work increases blood pressure. The main finding of this study was that alternating shift work had a significant adverse effect on a wide range of SBP and DBP end points.
This finding is consistent with 2 cross-sectional studies that reported higher blood pressure in shift workers than in daytime workers.16,17 However, these earlier studies may have been influenced by subjects dropping out of shift work, resulting in retention of only healthy adaptable persons in the shift-worker groups. To overcome this bias, it is necessary to carry out a longitudinal study on a cohort of subjects over an extended period of time, which takes into account the effect of dropouts. In the present longitudinal study, >98% of the workers underwent an annual health examination carried out by the company. None of the subjects changed from alternating shift work to day shift work during the observation period because of an increase in blood pressure. This meant that there was only minimal loss of critical data and no selection bias for compliant versus noncompliant subjects. Therefore, retention bias was not likely to have affected the results of our study.
Longitudinal studies investigating the effects of alternating shift work on worker’s health are sparse, although a few such studies have reported an increased risk of hypertension in shift workers. Morikawa et al20 conducted a 5-year cohort study using multiple logistic regression analysis and found that the OR for hypertension in shift workers relative to daytime workers was 3.6 in the group aged 18 to 29 years. We also reported a significant relationship between alternating shift work and hypertension based on a prospective cohort study of 5338 workers over a 10-year period.21 Furthermore, we reported that alternating shift work was significantly associated with progression of mild hypertension to severe hypertension in a cohort study of 2911 to 2941 workers over a 10-year period.22 In our 2 previous studies21,22 and the present study, each annual examination was treated as a miniature follow-up study in the pooled logistic regression analysis. D’Agostino et al24 described pooled logistic regression analysis in detail. We consider a hypothetical study of 1000 persons at risk of a disease. All of these subjects have risk factors measured at time t0 (or examination 1). We follow them through the first interval of observation. During that time period 40 subjects develop the disease and 10 others are lost to follow-up. We remove these 50 subjects from the population at risk. At time t1 (examination 2) there are 950 subjects in whom risk factors are measured. Of these, 25 develop the disease and 5 are lost to follow-up. The remaining 920 subjects have risk factors measured at time t2 (examination 3), of whom 20 develop the disease in the next period and 10 are lost to follow-up. This method pools the subjects at risk in each interval to yield 2870 (1000+950+920) person-exams and pools the 85 (40+25+20) disease events. A logistic regression with 2870 observations and 85 events constitutes a pooled logistic regression analysis.
Mathematically, the logistic regression model is written as follows24: equation
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where qi[X(ti–1)] is the conditional probability of observing an event by time ti given that the individual is event-free at time ti–1, and: equation
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is the vector of risk factors measured at time ti–1. The parameters obtained are adjusted for the effects of other time-varying (lifestyle and BMI) covariates. Each examination interval of 1 year was treated as a miniature follow-up study. This pooled logistic regression analysis is equivalent to a Cox time-dependent regression analysis.24 The strength of this method is that the OR obtained is adjusted for the covariates in the multivariate model, and the covariates are updated at each annual examination. In the present study, the extended follow-up period and increased number of subjects should improve the quality and accuracy of the epidemiological data compared with earlier studies.20–22
In the present study, age was negatively associated with all of the end points for an increase in DBP, whereas it was positively associated with 3 end points for an increase in SBP. Previous large epidemiological studies25–27 reported an age-dependent rise in SBP, whereas DBP was found to rise only until 50 years of age, level off from age 50 to 60 years, and decline thereafter. Lakatta and Levy28 noted in their review that arterial pressure is determined by the interplay of peripheral resistance and central artery stiffness; the former increases both systolic and diastolic pressure to a similar degree, whereas the latter increases systolic but lowers diastolic pressure. They also found that the age-dependent changes in SBP and DBP are consistent with the notion that, in younger people, blood pressure is determined largely by peripheral vascular resistance, whereas it is determined to a greater extent by central conduit vessel stiffness in older individuals.28 Therefore, the results of the present study agree with those previous findings.
A notable feature of our study was that the end points were defined as a 10%, 15%, 20%, 25%, or 30% increase in SBP or DBP relative to the values measured at entry to the study. This differs from previous studies20–22 in which end points were normally defined as blood pressure exceeding a certain threshold value, such as 140/90 mm Hg. When a threshold value for blood pressure is used, some subjects will be excluded at the time of entry, and this may introduce bias. However, only subjects who were being treated for hypertension at the time of entry were excluded from the present study. Thus, we obtained information on the effect of alternating shift work on relative changes in blood pressure over time regardless of the absolute blood pressure at baseline. Furthermore, the results of the present study showed that none of the covariates except for job schedule type were significantly associated with all of the end points. This indicates the strength of the results of the present study. However, because the dependent variable was dichotomized, the present study could not identify an increase in blood pressure below the end point, although the same was true for previous studies20–22 in which blood pressure end points were defined based on a clinical classification. It is difficult to say whether a relative increase in blood pressure within the normal range had the same meaning as those adverse clinical responses in previous studies.20–22 Nevertheless, the end points in the present study could detect a subclinical effect of shift work on blood pressure, which was not detected in previous studies.20–22 From the viewpoint of preventive medicine, it is important to detect subclinical, as well as clinical, changes in blood pressure. Therefore, the results of the present study can be considered as complementary to the results of previous studies.20–22 Despite the differences in methodology, the findings of our study and previous studies20–22 are in general agreement and clearly establish the adverse effects of alternating shift work on blood pressure.
Although we did not investigate other factors, such as the type of work, during all of the follow-up periods, an extensive questionnaire was administered in 2002. On the basis of our results29 on the type of work, the percentage of onsite workers was 90% for alternating shift workers and 40% for day workers. Of the day workers, 20% were engaged in office work and 22% in research and technical work. In this company, onsite workers are engaged in activities related to steel production and equipment maintenance and usually monitor and operate the production process remotely in a safe and comfortable operations room, without the demand for heavy physical labor. Occasionally, these workers enter the production site to carry out equipment maintenance while the production process is suspended. Therefore, work type was probably not a major confounding factor in our study. An additional limitation is that blood pressure was measured only once at each examination. The single measurement of blood pressure might reduce the accuracy of the blood pressure value that could result in a loss of statistical power to detect relationships between the variables. Because the blood pressure was measured in a parallel manner throughout the observation period, we believe the single blood pressure measurement was uniformly distributed without bias. To overcome any loss of statistical power because of a single blood pressure measurement, we used a large sample size.
Perspectives
Our study in male Japanese workers revealed that alternating shift work is a significant and independent risk factor for an increase in blood pressure over time. We did not define a threshold value for an elevation of blood pressure but rather used relative increases in blood pressure from baseline as end points. This method is novel and has not been used in other longitudinal studies. The company under study adopted an alternating shift work schedule that is representative of well-ordered Japanese factories. This schedule involved a 4-team/3-shift system with a clockwise rotation. The ORs of alternating shift work for increased blood pressure were 
1.2. From an industrial health viewpoint, these results do not provide definite proof that hypertensive workers should not carry out alternating shift work. Based on our findings, efficient health screening and regular checkups, combined with support to control unhealthy lifestyle factors, may be of considerable benefit in maintaining the health of alternating shift workers.
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Acknowledgments |
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Source of Funding
This study was supported by a grant from the Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research No. 17590508).
Disclosures
None.
Received April 8, 2008; first decision May 2, 2008; accepted June 18, 2008.
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