Original article

Scand J Work Environ Health 2017;43(2):117-126    pdf

doi:10.5271/sjweh.3612

Shift work and overall and cause-specific mortality in the Danish nurse cohort

by Jørgensen JT, Karlsen S, Stayner L, Hansen J, Andersen ZJ

Objectives Evidence of an effect of shift work on all-cause and cause-specific mortality is inconsistent. This study aims to examine whether shift work is associated with increased all-cause and cause-specific mortality.

Methods We linked 28 731 female nurses (age ≥44 years), recruited in 1993 or 1999 from the Danish nurse cohort where they reported information on shift work (night, evening, rotating, or day), to the Danish Register of Causes of Death to identify deaths up to 2013. We used Cox regression models with age as the underlying scale to examine the associations between night, evening, and rotating shift work (compared to day shift work) and all-cause and cause-specific mortality in models adjusted for potentially confounding variables.

Results Of 18 015 nurses included in this study, 1616 died during the study time period from the following causes: cardiovascular disease (N=217), cancer (N= 945), diabetes (N=20), Alzheimer’s disease or dementia (N=33), and psychiatric diseases (N=67). We found that working night [hazard ratio (HR) 1.26, 95% confidence interval 95% CI) 1.05–1.51] or evening (HR 1.29, 95% CI 1.11–1.49) shifts was associated with a significant increase in all-cause mortality when compared to working day shift. We found a significant association of night shift work with cardiovascular disease (HR 1.71, 95% CI 1.09–2.69) and diabetes (HR 12.0, 95% CI 3.17–45.2, based on 8 cases) and none with overall cancer mortality (HR 1.05, 95% CI 0.81–1.35) or mortality from psychiatric diseases (HR 1.17, 95% CI 0.47–2.92). Finally, we found strong association between evening (HR 4.28, 95% CI 1.62–11.3) and rotating (HR 5.39, 95% CI 2.35–12.3) shift work and mortality from Alzheimer’s disease and dementia (based on 8 and 14 deaths among evening and rotating shift workers, respectively).

Conclusions Women working night and evening shifts have increased all-cause, cardiovascular, diabetes, and Alzheimer’s and dementia mortality.

This article refers to the following texts of the Journal: 1999;25(2):85-99  2005;31(1):30-35  2009;35(3):163-179  2010;36(2):96-108
The following articles refer to this text: 2017;43(2):97-98; 2017;43(6):569-577

It has been suggested that working outside normal work hours, especially at night, has negative health effects (1, 2), but evidence of an effect of shift work on all-cause mortality is inconsistent (312). Several studies (46,10), including a recent meta-analysis (13), have reported an increase in all-cause mortality among shift workers, but only a few have detected a statistically significant association (4, 6, 13) while others have found none (3, 9, 12, 14) or inverse an association (7).

In 2007, an International Agency for Research on Cancer (IARC) working group classified shift work involving circadian disruption as “probably carcinogenic” to humans (group 2A) (15). The majority of recent studies on the health effects of night shift work have focused on female breast cancer incidence (16), and only a few have examined cancer mortality (57). One study found significantly increased mortality from any cancer among female but not among male shift workers (5). Few studies have examined shift work and cancer-specific mortality (6, 7, 1719). Gu et al (6) found an association with lung cancer mortality and working shifts ≥15 years among American female nurses after adjustment for potential confounders including tobacco smoking. Yong et al (7), found no increase in lung cancer mortality among male chemical shift workers. Carter et al (19) detected an association between rotating shift work and ovarian cancer mortality, whereas Lin et al (17, 18) found no association between shift work and either pancreatic or biliary tract cancer mortality.

Shift work has been linked to an increased incidence of coronary or ischemic heart disease (IHD) (20, 21) and diabetes (2, 22), but there is limited evidence on mortality due to cardiovascular disease (CVD) (23) and diabetes (12). To date, no studies have examined the effect of shift work on Alzheimer’s disease, dementia or psychiatric diseases, despite the fact that poor sleep and sleep deprivation have been linked to increased risk of cognitive and neurodegenerative outcomes (2426). In this study, we examine the association between shift work and all-cause mortality and mortality due to CVD, cancer, diabetes, neurodegenerative and psychiatric diseases in the Danish nurse cohort (DNC).

Methods

Study population

The DNC study (27) was initiated in 1993, when 23 170 female members of the Danish Nurses Organization aged >44 years were invited to participate in this nationwide study inspired by the American Nurses’ Health Study. A total of 19 898 (86%) responded positively. In 1999, the cohort was expanded, adding an additional 10 534 nurses aged 44 years, 8833 (84%) of whom agreed to participate. Cohort participation involved answering a comprehensive self-administrated questionnaire on lifestyle, health, use of hormones and occupational characteristics, including working hours and the work environment. Using a unique personal identification number, we linked the DNC to the Danish Civil Registration System (28) in order to obtain information on cohort participants’ vital status (death, emigration, disappearance, etc) during follow-up until 2013.

Shift work definition

Shift work data was self-reported by nurses who were in the workforce at the time of recruitment (excluding those who were retired, on sick leave, or unemployed) and nurses who answered the following question on shift work status: “Do you normally work in: a) day, b) evening, c) night, or d) rotating shifts?”. Rotating shifts can be working either day (typically 07:00–15:00 hours) and evening (15:00–23:99 hours) or day, evening and night (23:00–07:00 hours).

Health outcomes

Information on the deceased cohort participants’ causes of death was obtained from the Danish Register of Causes of Death (29), which contains information on all deaths of Danish residents dying in Denmark. Causes of deaths are coded according to the World Health Organization’s International Classification of Diseases (ICD) version-10 (after 1994) or ICD-8 (before 1994). All death certificates have underlying cause of death and up to four contributory causes of death, which are not mandatory. We examined all-cause mortality as all deaths occurring during follow-up, including 38 deaths registered in the Civil Registration System with missing cause of death data (no record in the Register of Causes of Deaths). We examined the following cause-specific causes of death using the underlying cause of death: total CVD (ICD-10: I00-99, ICD-8: 4010, 4100, 4129, 4279, 4339, 4369, 4412, 4500), IHD (ICD-10: I20-25, ICD-8: 4100, 4129), stroke (ICD-10: I60-69, ICD-8: 4339, 4369), other CVD (ICD-10: I00-09, I26-28, I30-50, I70-99, ICD-8: 4279, 4412, 4500), all-cancer (ICD-10: C00-97 & ICD-8: 1578-79, 1538, 1740, 1621, 1830, 2022, 2041), breast cancer (ICD-10: C50, ICD-8: 1740), lung cancer (ICD-10: C33-34, ICD-8: 1621), ovarian cancer ICD-10: C56, C570-574, ICD-8: 1830), pancreatic cancer (ICD-10: C25, ICD-8: 1578-1579), and colorectal cancer (ICD-10: C18-19, C20, C21, ICD-8: 1538). Additionally, we defined the following cause-specific mortality outcomes based on underlying or contributing cause of death: hypertension (ICD-10: I10-15, ICD-8: 4010); diabetes (ICD-10: E10-14), Alzheimer’s and dementia, combined (ICD10: F00-01, F03, G30), psychiatric and behavioral diseases, combined (ICD-10: F01, F03-99, ICD-8: 2990, 3032, 3040, 5710, 9779).

Statistical analysis

Cox proportional hazard regression model with age as the underlying time scale, was used to analyze mortality (all-cause and cause-specific) as a function of shiftwork, in two different models: crude (age-adjusted as age is underlying time scale) and fully adjusted, additionally adjusted for (i) smoking (never/past/current); (ii) pack-years [defined as 20 cigarettes/day per year, calculated from smoking intensity (number of cigarettes a day) and smoking duration (years)]; (iii) leisure-time physical activity [categorized in low/medium/high and based on the following question: “Which of the following statements describes you best? (a) Exercise heavily and do competitive sports regularly or several times a week; (b) Do sports/heavy gardening or similar ≥4 hours a week; (c) walk, bike or doing other light exercise ≥4 hours a week; (d) Reading, watching television or other sedentary activities”]; (iv) body mass index (BMI) [calculated from self-reported height and weight (kg/m2)]; (v) alcohol consumption (number of drinks per week/none, moderate 1–14, heavy ≥15); (vi) diet [“How often do you eat vegetables and fruits?” (a) Rarely or never, (b) a couple of times a week, (c) daily, or (d) several times a day” and “Do you avoid fatty meat? (yes/no)”]; (vii) pre-existing diseases [based on whether or not participants reported being diagnosed or taking medication to treat the disease hypertension, diabetes or myocardial infarction (MI)]; self-reported health [“How would you evaluate your present state of health? (a) very good, (b) good, (c) moderate, (d) bad, or (e) very bad”]; (viii) work stress [“How often are you so busy that you have difficulties in doing your work tasks? (a) never, (b) rarely, (c) occasionally, (d) often, (e) almost always”]; (ix) marital status (married/separated/divorced/single/widow); (x) female reproductive factors (a) births [“How many children have you given birth to?”, dichotomized into 0/≥1], (b) use of hormone therapy [“Are you or have you previously been on hormone replacement therapy (HRT) with estrogen? (No, I have never been in hormone replacement therapy/I have previously been in hormone replacement therapy/I am currently in hormone replacement therapy)”], and (c) oral contraceptives [“Have you ever used oral contraceptives? (yes/no)”]. Analysis of breast and ovarian cancer mortality were additionally adjusted for number of births and age at first birth. Lastly, we examined whether BMI or a stressful work environment acted as a mediating factors in the association between shift work and all-cause mortality, by examining changes in risk estimates with and without adjustment for BMI and work stress in the fully adjusted model.

Results

Of the 28 731 participants in the DNC, 10 716 were excluded for the following reasons: (i) emigration prior to cohort baseline (N=4), (ii) retired, unemployed or on sick leave at the time of cohort recruitment (N=6721), (iii) missing information on shift work schedule (N=669), and (iv) missing information on ≥1 potentially confounding variable(s) (N=3322). The final analysis comprised 18 015 participants. Mean follow-up was 17.6 years, giving a total 316 644 person-years, during which 1616 nurses died, including 217 from CVD, 945 from cancer, 20 from diabetes, 33 from Alzheimer’s or dementia, and 67 from psychiatric diseases.

A majority of the nurses worked day shifts (62.6%), followed by rotating (22.0%), evening (10.0%) and permanent night (5.4%) shifts at the time of recruitment (table 1). Night and evening shift work were more prevalent among nurses who died (9.3% and 14.6%) than among those who were alive (5.1% and 9.6%) at the end of follow-up. Nurses who died were older at the recruitment (mean age 54.2 years) than nurses who were alive at the end of follow-up (mean age 49.9 years). Furthermore, nurses who died smoked more, used HRT more frequently, and less oral contraceptives than nurses who remained alive at the end of follow-up.

Table 1

Characteristics of 18 015 nurses at baseline (1993 and 1999) by status (active/dead) at end of follow-up (31 December 2012).

Total Alive Dead a P-value b



N % N % N %
Total 18 015 100 16 399 91.0 1616 9.0
Person-years 316 644 100 296 468 93.6 20 176 6.4
Work type
 Day 11 272 62.6 10 338 63.0 934 57.8 <0.001
 Evening 1805 10.0 1569 9.6 236 14.6
 Night 980 5.4 829 5.1 151 9.3
 Rotating 3958 22.0 3663 22.3 295 18.3
Body mass index (kg/m2)
 <18.5 354 2.0 291 1.8 63 3.9 <0.001
 18.5–24.9 12 688 70.4 11 593 70.7 1095 67.8
 25–29.9 3864 22.0 3613 22.0 351 21.7
 ≥30 1009 5.6 902 5.5 107 6.6
Smoking status
 Never 6725 37.3 6323 38.6 402 24.9 <0.001
 Past 5244 29.1 4877 29.7 367 22.7
 Current 6046 33.6 5199 31.7 847 52.4
Number of pack years c
 ≤10 5096 28.3 4745 28.9 351 21.7 <0.001
 11–20 2942 16.3 2695 16.4 247 15.3
 >20 3252 18.1 2636 16.1 616 38.1
 Never-smokers 6725 37.3 6323 38.6 402 24.9
Alcohol consumption (drinks/week)
 0 2190 12.2 1929 11.8 261 16.2 <0.001
 1–14 (moderate) 11 522 64.0 10 607 64.7 915 56.6
 >15 (heavy) 4303 23.9 3863 23.6 440 27.2
Physical activity
 Low 956 5.3 817 5.0 139 8.6 <0.001
 Medium 11 906 66.1 10 803 65.9 1103 68.3
 High 5153 28.6 4779 29.1 374 23.1
Diet
 Consume vegetables on daily basis 17 787 98.7 16 214 98.9 1573 97.3 <0.001
 Consume fruit on daily basis 17 387 96.5 15 856 96. 1531 94.7 <0.001
 Avoids fatty meat 16 470 91.4 15 060 91.8 1410 87.3 <0.001
Self-reported preexisting diseases
 Hypertension 1890 10.5 1619 9.9 271 16.8 <0.001
 Diabetes 158 0.9 134 0.8 24 1.5 0.006
 Myocardial infarction 47 0.3 32 0.2 15 0.9 <0.001
Self-reported health
 Very good 7994 44.4 7463 45.5 531 32.9 <0.001
 Good 7940 44.1 7170 43.7 770 47.6
 Moderate 1894 10.5 1624 9.9 270 16.7
 Bad 166 0.9 129 0.8 37 2.3
 Very bad 21 0.1 13 0.1 8 0.5
Working status
 Working 17 924 99.5 16 313 99.5 1611 99.7 0.43
 Homeworker 1 <0.1 1 <0.1 0 0.0
 Retired 9 <0.1 8 <0.1 1 0.1
 Unemployed/rehabilitation 4 <0.1 3 <0.1 1 0.1
 Other 77 0.4 74 0.5 3 0.2
Stressful work environment
 Never 251 1.4 205 1.3 46 2.8 <0.001
 Rarely 2847 15.8 2579 15.7 268 16.6
 Occasionally 7788 43.2 7072 43.1 716 44.3
 Often 5713 31.7 5245 32.0 468 29.0
 Almost always 1416 7.9 1298 7.9 118 7.3
Marital status
 Married 13 476 74.8 12 404 75.6 1072 66.3 <0.001
 Separated 328 1.8 292 1.8 36 2.2
 Divorced 2094 11.6 1876 11.4 218 13.5
 Single 1405 7.8 1230 7.5 175 10.8
 Widow 712 4.0 597 3.6 115 7.1
Use of hormone therapy
 Never-users 13 664 75.8 12 607 76.9 1057 65.4 <0.001
 Ever-users 4351 24.2 3792 23.1 559 34.6
Use of oral contraceptives
 Never-users 5788 32.1 5045 30.8 743 46.0 <0.001
 Ever-users 12 227 67.9 11 354 69.2 873 54.0
Births
 0 1978 11.0 1720 10.5 258 16.0 <0.001
 ≥1 16 037 89.0 14 679 89,5 1358 84.0

a All-cause mortality.

b Nurse who were alive and dead at end of follow-up were compared using Pearson’s Chi-squared for categorical variables.

c One pack year was defined as 20 cigarettes/year in ever-smokers.

Nurses working night shifts were more likely to be current smokers, overweight and obese, and HRT users, but less likely to be married than nurses working other shifts (table 2). Nurses working rotating shifts were more similar to those working day shift than those working night shifts. Mean age [standard deviation (SD)] at baseline was 50.2 (4.7), 51.6 (5.5), 52.9 (5.6) and 49.2 (4.3) years for day, evening, night and rotating shift workers, respectively.

Table 2

Characteristics of 18 015 nurses by working shift type at baseline (1993 and 1999).

Day Evening Night Rotating P-value a




N % N % N % N %
Total 11 272 62.6 1805 10.0 980 5.4 3958 22.0
Number of deaths b 934 57.8 236 14.6 151 9.3 295 18.3
Person-years 199 327 62.9 32 245 10.2 17 662 5.6 67 410 21.3
Body mass index (kg/m2)
 <18.5 200 1.8 54 3.0 31 3.2 69 1.7 <0.001
 18.5–24.9 7945 70.5 1308 72.5 612 62.4 2823 71.3
 25–29.9 2494 22.1 342 18.9 257 26.2 871 22.0
 ≥30 633 5.6 101 5.6 80 8.2 195 4.9
Smoking status
 Never 4260 37.8 669 37.1 298 30.4 1498 37.8 <0.001
 Past 3390 30.1 471 26.1 238 24.3 1145 28.9
 Current 3622 32.1 665 36.8 444 45.3 1315 33.2
Number of pack years c
 ≤10 3260 28.9 460 25.5 214 21.8 1162 29.4 <0.001
 11–20 1823 16.2 287 15.9 173 17.7 659 16.6
 >20 1929 17.1 389 21.6 295 30.1 639 16.1
Alcohol consumption (drinks/week)
 0 1097 9.7 333 18.4 252 25.7 508 12.8 <0.001
 1–14 (moderate) 7312 64.9 1134 62.8 523 53.4 2553 64.5
 >15 (heavy) 2863 25.4 338 18.7 205 20.9 897 22.7
Physical activity
 Low 649 5.8 78 4.3 56 5.7 173 4.4 <0.001
 High 3157 28.0 511 28.3 309 31.5 1176 29.7
 Medium 7466 66.2 1216 67.4 615 62.8 2609 65.9
Diet
 Consume vegetables on daily basis 11 141 98.8 1773 98.2 962 98.2 3911 98.8 0.059
 Consume fruit on daily basis 10 887 96.6 1711 94.8 939 95.8 3850 97.3 <0.001
 Avoids fatty meat 10 363 91.9 1619 89.7 862 88.0 3626 91.6 <0.001
Self-reported pre-existing diseases
 Hypertension 1194 10.6 198 11.0 123 12.6 375 9.5 0.025
 Diabetes 91 0.8 23 1.3 17 1.7 27 0.7 0.003
 Myocardial infarction 26 0.2 9 0.5 5 0.5 7 0.2 0.052
Self-reported health
 Very good 5218 46.3 618 34.2 338 34.5 1820 46.0 <0.001
 Good 4868 43.2 885 49.0 466 47.6 1721 43.5
 Moderate 1075 9.5 271 15.0 169 17.2 379 9.6
 Bad 100 0.9 28 1.6 7 0.7 31 0.8
 Very bad 11 0.1 3 0.2 0 0.0 7 0.2
Working status
 Working 11 220 99.5 1797 99.6 979 99.9 3928 99.2 0.34
 Homeworker 0 0.0 0 0.0 0 0.0 1 <0.1
 Retired 6 0.1 1 0.1 0 0.0 2 0.1
 Unemployed/rehabilitation 2 <0.1 1 0.1 0 0.0 1 <0.1
 Other 44 0.4 6 0.3 1 0.1 26 0.7
Stressful work environment
 Never 141 1.3 29 1.6 41 4.2 40 1.0 <0.001
 Rarely 1530 13.6 362 20.1 383 39.1 572 14.5
 Occasionally 4643 41.2 904 50.1 433 44.2 1808 45.7
 Often 3868 34.3 445 24.7 108 11.0 1292 32.6
 Almost always 1090 9.7 65 3.6 15 1.5 246 6.2
Marital status
 Married 8602 76.3 1345 74.5 665 67.9 2864 72.4 <0.001
 Separated 185 1.6 32 1.8 18 1.8 93 2.3
 Divorced 1223 10.8 214 11.9 151 15.4 506 12.8
 Single 832 7.4 126 7.0 80 8.2 367 9.3
 Widow 430 3.8 88 4.9 66 6.7 128 3.2
Use of hormone therapy
 Never-users 8574 76.1 1293 71.6 672 68.6 3125 79.0 <0.001
 Ever-users 2698 23.9 512 28.4 308 31.4 833 21.0
Use of oral contraceptives
 Never-users 3580 31.8 723 40.1 412 42.0 1073 27.1 <0.001
 Ever-users 7692 68.2 1082 59.9 568 58.0 2885 72.9
Births
 0 1213 10.8 191 10.6 117 11.9 457 11.5 0.38
 ≥1 10 059 89.2 1614 89.4 863 88.1 3501 88.5

a Categorical groups compared using Pearson’s Chi-squared.

b All-cause mortality.

c One pack year was defined as 20 cigarettes/day/year in ever-smokers.

Compared to nurses working day shifts, we found a statistically significant increase in all-cause mortality among nurses working evening [hazard ratio (HR): 1.53, 95% confidence interval (95% CI) 1.33–1.77] and night (HR 1.74, 95% CI 1.48–2.07) shifts, and no increase in those working rotating shifts in the crude model. Estimates were attenuated, but remained statistically significant in the fully adjusted model for evening (HR1.29, 95% CI 1.11–1.49) and night (HR 1.26, 95% CI 1.05–1.51) shifts (table 3). These estimates were only slightly enhanced when BMI and perceived stress at work were left out of the fully adjusted model (results are available in supplemental material table C, http://www.sjweh.fi/index.php?page=data-repository). We found a statistically significant increase in CVD mortality among nurses working night shifts (HR 1.71, 95% CI 1.09–2.69) and a weaker, statistically non-significant increase among nurses working evening (HR 1.47, 95% CI 0.98–2.18) and rotating (HR 1.24, 95% CI 0.87–1.77) shifts in the fully adjusted model. We found no associations between cancer mortality and evening (HR 1.15, 0.95–1.40), night (HR 1.05, 95% CI 0.81–1.35), or rotating shift (HR 0.91, 95% CI 0.77–1.08) in the fully adjusted model. We found a strong positive, statistically significant association between night shift work (HR 12.0, 95% CI 3.17–45.2) and diabetes mortality and weaker associations with evening (HR 2.94, 95% CI 0.63–13.7) and rotating (HR 1.57, 95% CI 0.34–7.21) shifts. We found strong positive, statistically significant associations between mortality from Alzheimer’s or dementia among nurses working evening (HR 4.28, 95% CI 1.62–11.3) and rotating (HR 5.39, 95% CI 2.35–12.3) shifts in the fully adjusted model. There was no evidence of association between working night shifts and Alzheimer’s or dementia (HR 0.70, 95% CI 0.09–5.72), but this analysis was based only on a single case. Finally, we found no evidence of an increased risk in mortality from psychiatric diseases.

Table 3

Association between shift work and all-cause and cause-specific mortality among 18 015 nurses. [HR=hazard ratio; 95% CI=95% confidence intervals; ref=reference]

Mortality Cases Crude a Adjusted b



N % HR 95% CI HR 95% CI
All causes
 Day shifts (ref) 934 57.8 1.00 1.00
 Evening shifts 236 14.6 1.53 1.33–1.77 1.29 1.11–1.49
 Night shifts 151 9.3 1.74 1.48–2.07 1.26 1.05–1.51
 Rotating shifts 295 18.3 0.98 0.86–1.12 1.00 0.88–1.15
All cardiovascular
 Day shifts (ref) 114 52.5 1.00 1.00
 Evening shifts 33 15.2 1.74 1.18–2.57 1.47 0.98–2.18
 Night shifts 26 12.0 2.42 1.58–3.71 1.71 1.09–2.69
 Rotating shifts 24 20.3 1.21 0.86–1.72 1.24 0.87–1.77
All cancers
 Day shifts (ref) 578 61.2 1.00 1.00
 Evening shifts 126 13.3 1.33 1.09–1.61 1.15 0.95–1.40
 Night shifts 73 7.7 1.38 1.08–1.76 1.05 0.81–1.35
 Rotating shifts 168 17.8 0.89 0.75–1.06 0.91 0.77–1.08
Diabetes
 Day shifts (ref) 6 30.0 1.00 1.00
 Evening shifts 3 15.0 3.03 0.76–12.1 2.94 0.63–13.7
 Night shifts 8 40.0 14.4 4.99–41.6 12.0 3.17–45.2
 Rotating shifts 3 15.0 1.54 0.39–6.18 1.57 0.34–7.21
Alzheimer’s and dementia
 Day shifts (ref) 10 30.3 1.00 1.00
 Evening shifts 8 24.2 4.65 1.84–11.8 4.28 1.62–11.3
 Night shifts 1 3.0 0.99 0.13–7.72 0.70 0.09–5.72
 Rotating shifts 14 42.4 4.79 2.12–10.8 5.39 2.35–12.3
Psychiatric diseases
 Day shifts (ref) 33 49.3 1.00 1.00
 Evening shifts 11 16.4 2.02 1.02–4.01 1.66 0.82–3.34
 Night shifts 6 9.0 1.97 0.83–4.71 1.17 0.47–2.92
 Rotating shifts 17 25.4 1.58 0.88–2.84 1.57 0.87–2.84

a Model adjusted for age.

b Model adjusted for age, smoking, pack-years, physical activity, body mass index (kg/m2), alcohol consumption, diet (vegetables, fruit and fatty meat consumption), pre-existing diseases (hypertension, diabetes and myocardial infarction), self-reported health, stressful work environment, marital status, female reproductive factors (birth, use of hormone therapy and oral contraceptives).

We found no significant associations between shift work and mortality due to any of the cancer subtypes examined, including breast, ovarian, lung, colorectal and pancreatic cancer (table 4). When considering specific CVD (table 5), we found the strongest associations with night shift workers who had a statistically significant increased risk of dying from IHD (HR 2.30, 95% CI 1.07–4.92), and evening shift workers who had significantly increased risk of dying from other CVD (HR 2.25, 95% CI 1.18–4.31). We found positive but statistically non-significant association between working night shifts and mortality from hypertension (HR 2.35, 95% CI 0.86–6.37) and stroke (HR 1.98, 95% CI 0.82–4.27).

Table 4

Association between shift work and cancer-specific mortality. [HR=hazard ratio; 95% CI=95% confidence intervals; ref=reference].

Mortality Cases Crude a Adjusted b



N % HR 95% CI HR 95% CI
Breast cancer c
 Day shifts (ref) 119 58.3 1.00 1.00
 Evening shifts 31 15.2 1.60 1.08–2.38 1.36 0.90 –2.03
 Night shifts 16 7.8 1.50 0.89–2.53 1.20 0.70–2.08
 Rotating shifts 38 18.6 0.96 0.66–1.38 0.95 0.66–1.37
Ovarian cancer c
 Day shifts (ref) 64 68.8 1.00 1.00
 Evening shifts 12 12.9 1.14 0.62–2.12 1.00 0.54–1.89
 Night shifts 4 4.3 0.69 0.25–1.88 0.63 0.22–1.78
 Rotating shifts 13 14.0 0.62 0.34–1.12 0.64 0.35–1.16
Lung cancer
 Day shifts (ref) 111 57.2 1.00 1.00
 Evening shifts 31 16.0 1.69 1.13–2.52 1.31 0.87–1.98
 Night shifts 19 9.8 1.84 1.13–3.00 1.09 0.65–1.82
 Rotating shifts 33 17.0 0.92 0.63–1.36 0.96 0.65–1.42
Colorectal cancer
 Day shifts (ref) 76 65.0 1.00 1.00
 Evening shifts 12 10.3 0.96 0.52–1.76 0.85 0.46–1.59
 Night shifts 9 7.7 1.29 0.65–2.57 1.02 0.50–2.11
 Rotating shifts 20 17.1 0.81 0.49–1.32 0.83 0.50–1.36
Pancreatic cancer
 Day shifts (ref) 45 69.2 1.00 1.00
 Evening shifts 8 12.3 1.08 0.51–2.28 0.96 0.44–2.07
 Night shifts 2 3.1 0.48 0.12–1.98 0.37 0.09–1.58
 Rotating shifts 10 15.4 0.69 0.35–1.37 0.67 0.34–1.36
All other cancers
 Day shifts (ref) 163 59.9 1.00 1.00
 Evening shifts 32 11.8 1.19 0.82–1.75 1.09 0.74–1.61
 Night shifts 23 8.5 1.54 0.99–2.38 1.29 0.82–2.04
 Rotating shifts 54 19.9 1.02 0.75–1.38 1.05 0.77–1.43

a Model adjusted for age.

b Model adjusted for age, smoking, pack-years, physical activity, body mass index (kg/m2), alcohol consumption, diet (vegetables, fruit and fatty meat consumption), pre-existing diseases (hypertension, diabetes and myocardial infarction), self-reported health, stressful work environment, marital status, female reproductive factors (birth, use of hormone therapy and oral contraceptives).

c Fully adjusted analysis on breast and ovarian cancer mortality was additionally adjusted for number of births and age at first birth (N=17 919).

Table 5

Association between shift work and cause-specific mortality. [HR=hazard ratio; 95% CI=95% confidence intervals; ref=reference]

Mortality Cases Crude a Adjusted b



N % HR 95% CI HR 95% CI
Ischemic heart disease
 Day shifts (ref) 29 46.0 1.00 1.00
 Evening shifts 11 17.5 2.30 1.15–4.60 1.71 0.84–3.50
 Night shifts 11 17.5 4.10 2.05–8.22 2.30 1.07–4.92
 Rotating shifts 12 19.1 1.28 0.65–2.51 1.22 0.61–2.41
Hypertension
 Day shifts (ref) 19 47.5 1.00 1.00
 Evening shifts 5 12.5 1.57 0.59–4.22 1.60 0.57–4.51
 Night shifts 6 15.0 3.30 1.32–8.28 2.35 0.86–6.37
 Rotating shifts 10 25.0 1.68 0.78–3.62 2.04 0.92–4.50
Stroke
 Day shifts (ref) 42 56.8 1.00 1.00
 Evening shifts 7 9.5 1.00 0.45–2.23 0.91 0.40–2.05
 Night shifts 9 12.2 2.27 1.10–4.67 1.98 0.92–4.27
 Rotating shifts 16 2.6 1.20 0.68–2.14 1.24 0.70–2.22
Other cardiovascular
 Day shifts (ref) 33 53.2 1.00 1.00
 Evening shifts 14 22.6 2.55 1.37–4.77 2.25 1.18–4.31
 Night shifts 4 6.5 1.29 0.46–3.64 0.95 0.32–2.80
 Rotating shifts 11 17.7 1.05 0.53–2.08 1.19 0.59–2.38

a Model adjusted for age.

b Model adjusted for age, smoking, pack-years, physical activity, body mass index (kg/m2), alcohol consumption, diet (vegetables, fruit and fatty meat consumption), pre-existing diseases (hypertension, diabetes and myocardial infarction), self-reported health, stressful work environment, marital status, female reproductive factors (birth, use of hormone therapy, and oral contraceptives).

Discussion

We found that, compared to female nurses working day shifts, nurses working night or evening shifts had statistically significantly elevated all-cause mortality. We found a significant increase in mortality due to CVD and diabetes with night shift work. We also observed a significantly increased risk of Alzheimer’s and dementia with rotating and evening shifts. There was no evidence in our study of an increased risk of overall or cause-specific cancer mortality with evening, night or rotating shift work.

Our results confirm the previous findings of Nätti et al (5) and Gu et al of an association between night shift work and all-cause mortality (6). We report a 26% increased risk for all-cause mortality among night shift compared to day shift workers, which is somewhat greater than the 11% increase in all-cause mortality reported by Gu et al among nurses who worked night shifts for ≥5 years, compared to all other schedules (6). Nätti et al reported a 125% increase in all-cause mortality among females with weekly night work as compared to those with day work (5). Notably, Nätti et al found no association with all-cause mortality among male night shift workers, which may suggest different susceptibility by gender. Nätti et al’s observed gender differences were consistent with Åkerstedt et al’s results, where a significant association with mortality was limited to female white-collar night shift workers, whereas none was found among male night workers or female blue-collar workers (10). Gender variation in susceptibility to night work may also explain why our results conflict with studies based on male participants (3, 4, 7, 8, 12).

Work schedule is dependent on age, and it has previously been documented that nurses in younger age groups are more likely to work in rotating shifts, whereas nurses >40 years more often work in day or evening shifts (30). However, 90% of nurses working in Denmark have worked night shifts at some point, typically early in their career after completing their training. We found a similar increase in all-cause mortality for night (26%) and evening (29%) shift workers. This might be explained by the fact that a large number of nurses who worked evening shifts at the time of cohort recruitment have worked night shifts earlier in their career. Another possible explanation for the increased mortality among evening workers might be that this work schedule is associated with an increase in social stress and more work-family related conflicts. Furthermore, other unmeasured potentially confounding variables such as weekly working hours could explain these findings.

The lack of association between rotating shift work and all-cause mortality is possibly explained by the fact that rotating shift work involves day, evening and night shifts or only day and evening shifts and few night shifts in a sequence, probably resulting in minor circadian disturbance. A Danish report on occupational health among nurses from the Danish Nurses Organization, reveals that 43% of nurses aged 20–29 years work rotating 3-shifts, while this attenuates to 20% among nurses aged 40–49 years and 12% among those aged 50–59 years, indicating that 3-shift rotating work is more prevalent early in the career, and thus making it less prevalent in our cohort (30). Alternatively, the lack of association between rotating shifts and all-cause mortality might be explained if a high proportion of previous rotating shift workers changed to day shifts positions. This could result in increased mortality rate among day workers and an underestimation of the impact of shift work (30).

The IARC has classified shift work that involves circadian disruption as “probably carcinogenic to humans” (group 2A) due to increased risk of breast cancer incidence among women (31). We found no association between shift work and all-cancer mortality, in agreement with Gu et al (6), and in contrast to Nätti et al (5). Furthermore, no evidence of an increase in mortality related to shift work was found for any specific cancers including cancer of the breast, which is in agreement with some of the previous studies (6, 7, 17). However our findings are in conflict with increased mortality due to ovarian cancer reported by Carter et al (19) and increased mortality due to lung cancer (≥15 years of rotating night shift work) and breast cancer reported by Gu et al (6). Gu et al. found an association with breast cancer mortality only among those working night shifts ≥30 years (HR 1.47, 95% CI 0.94–2.32), and none with more recent exposures, suggesting the relevance of early exposure for the development for breast cancer (6). This in line with Menegaux et al (32) who found the strongest risk of developing breast cancer among women who worked night shifts for >4 years before their first full-term pregnancy, a period where mammary glands are not completely differentiated and possibly more susceptible to circadian disruption effects. Thus lack of effects of shift work on breast cancer mortality in our study may be due, at least in part, to lack of information on shift work duration and shift work schedules, before the first childbirth.

We found a 71% increase in CVD mortality among nurses working night shifts, which was considerably higher than the 19% and 23% detected in American nurses with ≥5 and ≥15 years of night shift work, respectively (6). We furthermore found the highest increased rate (130%) related to night shift work for IHD mortality, which is consistent with some studies (6, 33, 34), however is inconsistent with others (8, 35, 36). Inconsistencies are likely explained by differences in study populations in terms of the gender and age of included subjects. Knutsson et al’s case–control study of MI incidence detected associations with both male and female shift workers, but found substantially higher risk [odds ratio (OR) 3.0, 95% CI 1.4–6.5] among females aged 45–55 years than males of the same age (OR 1.6, 95% C 1.1–2.4) (37). Since the majority (~80%) of participants included were 44–55 years of age at the time of recruitment, a large proportion of the shift-working nurses in our study might, based on the results of Knutsson et al, be at particularly high risk of developing MI due to shift work, possibly explaining strong effects observed in our study and the lack of association between shift work and IHD mortality in most studies based on male participants (8, 35, 36). We also found statistically non-significant associations between night shift work and risk of dying from hypertension and stroke and increased risk of dying from other CVD among evening shift workers. These findings agree with Vyas et al’s recent meta-analysis that has linked shift work to increases in the incidence of various vascular events including, MI (23%), ischemic stroke (5%) and coronary events (24%) (20). Disruption of circadian rhythms is thought to be the plausible mechanisms linking shift work with CVD through multifactorial pathways (38, 39), involving weight gain, physical inactivity, development of type II diabetes, and other pathways (38).

The highest rate ratio associated with night shift work in this study was observed for diabetes mortality, however, the results are based on a limited number of diabetes deaths (N=8) and therefore somewhat unstable. Our results are considerably stronger than the effect in the Karlsson et al (12) study of Swedish male workers from the pulp and paper industry (HR 1.24, 95% CI 0.91–1.70). Karlsson et al included males enrolled at age 10 in 1952 and used shift work as a dichotomized exposure (all shift versus day worker), but, on the other hand, included data on duration of shift work and found strong indication of a positive dose–response relationship with diabetes mortality. We have recently reported a strong significant association between night shift work and diabetes incidence (HR 1.58, 95% CI 1.25–1.99) in the DNC (12). Results based on the Nurses’ Health Study I and II (40) and the Black Women’s Health Study (41) also detected an association between night shift work and diabetes incidence.

We provided novel results of the strong increase in mortality from Alzheimer’s and dementia among nurses working evening and rotating shifts. To our knowledge this is the first study to report such an association. However, our results are based on a limited number of cases (33 deaths in total), and further studies of this issue are clearly warranted. Studies have put forth plausible biological mechanisms suggesting that sleep disturbance results in substantial detrimental cognitive effects (26). Unlike for all-cause mortality where no effect of rotating shifts was observed, we found the strongest associations for Alzheimer’s and dementia among rotating shifts workers. This result may suggest relevance of other mechanisms, possibly stress-related for Alzheimer’s and dementia than for all-cause mortality where circadian disruption may be more relevant. Furthermore, recent studies have shown an association between short sleep duration with greater β-amyloid (Aβ) burden, a biomarker of Alzheimer’s progression (25), and that better sleep consolidation substantially attenuated the negative effects of the apolipoprotein E ε4 allele, a common genetic risk factor for Alzheimer’s (24).

Strengths and limitations

A major strength of this study is the utilization of a nationwide prospective cohort of 18 015 female nurses, with detailed information on work schedules (night, evening, rotating, day), lifestyle, BMI, history of diseases, and reproductive factors at the time of cohort enrolment, and long follow-up for overall and cause-specific mortality in a national registry. In contrast to the commonly used shift work definition as a dichotomous exposure, typically comparing day to shift workers and combining evening, night and rotating shifts, in this study we were able to separate effect of night, evening and rotating shift in comparison to day shift work for the first time in a study of mortality. We excluded 10 716 (~37%) of the participants due to missing values. A majority of the participants (6721) were excluded because the question about work schedule was aimed at nurses working (74%) at the time of recruitment only. We found that the age-adjusted mortality was significantly higher among excluded nurses (HR 4.07, 95% CI 3.84–4.31) compared to included nurses, as expected since excluded nurses were on average 10 years older (mean age 60.0 years versus 50.2 years) at the time of recruitment. This is explained by the fact that a majority of excluded nurses were retired or on sick leave or disability retirement at the time of recruitment, and were therefore not included in the assessment of shift work. We found no major differences in lifestyle, BMI, or other characteristics between included and excluded nurses (supplemental material tables A and B, http://www.sjweh.fi/index.php?page=data-repository).

A major limitation of this study is the lack of data on intensity and duration of shift work in terms of the number of shifts per week or month, number of working hours per shift, and number of years working in shift work. The exposure was only assessed at baseline with no follow-up on changes in work schedule, potentially introducing exposure misclassification. However the nurses were followed from age 44 years when in general it is less likely for nurses to change work schedule than earlier in their careers. We also lacked information on duration of recovery periods and work schedules early in their career (from completion of professional training to cohort recruitment) and information on different types of rotating shift schedule, particularly whether or not rotating shifts involved night shifts. Another limitation is the small number of deaths for some of the examined outcomes (eg, diabetes and Alzheimer’s and dementia), resulting in wide confidence intervals, and our findings need to be replicated in larger studies. Furthermore, the registration of underlying and contributory causes of death relies entirely on the physician responsible for completing the death certificate, without central validation, which together with increasing diagnostic facilities influence the accuracy and correctness of the register and changes in mortality rates over the years (29).

Healthcare professionals are generally considered to be healthier than the general population, and a “healthy worker effect” might have biased our results. Nurses participating in this cohort have been found to be healthier than Danish women in general, as they smoked less and had higher levels of physical activity, but on average they consumed more alcohol (27, 42). However, there were no major health differences between nurses and the rest of Danish female population in use of healthcare and disease occurrence (27, 42).

In conclusion, we found evidence of an increased all-cause mortality risk among female nurses working in night or evening shifts, compared to those working in day shifts. We further found evidence of increased mortality due to CVD and diabetes, and Alzheimer’s and dementia, while there was no evidence of an increased risk in mortality from psychiatric diseases and overall or cause specific cancer. Additional studies of mortality among shift workers are warranted.

Acknowledgements

The authors declare no conflicts of interest.

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Notes

[14] Ethical approval

Relevant Danish ethical committees and Danish Data Protection Agency approved this study (j.nr. 2015-41-4307), and participants provided written informed consent at recruitment.


Additional material