Abstract
Purpose
Through this study, we assess whether night shift work increases the risk of osteoporosis, and explore the effects of age, gender, or lifestyle differences.
Methods
This cross-sectional study included the collection of data from a sample of the US adults who participated in the National Health and Nutrition Examination Survey (NHANES) over a 7.3-year period (2007–2008, 2009–2010, 2017–March2020), including 4408 participants (2351[52.8%] men and 2057[47.2%] women), with an age range of 20–80 years. The primary variables, health status, nutrition, harmful lifestyle habits, and bone mineral density (BMD), were segregated, and analyzed according to different work schedules. Linear regression models were conducted to evaluate correlations of night shift work and T-scores. Associations between night shift work and osteoporosis were examined using logistic regression analyses. All regression models were stratified by gender and age ≥50 years. Osteoporosis was defined as BMD at the femoral neck or total spine equal to or less than 2.5 standard deviations below the mean for youthful people of the same gender. All data were obtained using questionnaires and examinations collected in mobile examination center (MEC) from NHANES.
Results
After multivariate adjustment, night shift work was related to statistically significant decreases of the total spine in T-scores of females aged ≥50 years. Furthermore, night shift work of the overall population (OR = 2.31 [95% CI, 1.03–5.18]; P = 0.043) and females aged ≥50 years (OR = 4.6 [95% CI, 1.21–17.54]; P = 0.025) was related to an increased prevalence of osteoporosis.
Conclusion
Night shift work correlates with a higher risk of osteoporosis in the population of the US adults, with the combined effect of age, gender, and harmful lifestyle.
Keywords: Night work, Bone mineral density, Osteoporosis, Life style, NHANES
1. Introduction
Osteoporosis is a crucial worldwide problem of public health since it increases the risk of fracture and bone fragility [1]. Among the US adults aged ≥50 years, the prevalence of osteoporosis reported in the literature varied between 6% and 11% (approximately 7–12 million adults) [2]. Moreover, there are many risk variables for osteoporosis, including aging, gender (females more than males), ethnicity (non-Hispanic blacks > non-Hispanic whites > Hispanic > other races), low Body Mass Index (BMI), nutrient-poor status, current cigarette smoking, heavy alcohol consumption, previous major fractures, low physical activity, and many other uncontrollable or lifestyle factors [[3], [4], [5], [6]]. Besides, diseases that affect bone metabolism such as diabetes and chronic kidney disease (CKD) are also risk factors for osteoporosis [7,8]. Fracture caused by osteoporosis is a major reason for morbidity and mortality in older adults [9].
Working night shifts is a common occupational factor. About 26.5% of the working population in America are engaged in night shift work [10]. The working time of the night shift includes evening (18:00 to 22:00), night (23:00 to 3:00), and early morning (4:00 to 8:00). Literature reports have demonstrated that night shift work leads to insufficient sunlight exposure and disturbance of the endogenous circadian system [11,12]. Furthermore, some epidemiological and laboratory studies provide evidence that night shift work is related to an increased risk for some chronic illnesses, including different types of cancer, coronary heart disease (CHD), metabolic diseases, and sleep disorders [[13], [14], [15]].
Currently, the association between night shift work and the risk of osteoporosis or fracture is open to debate. Some recent researches suggest that rotating night shift work may bring about low bone mineral density (BMD), osteoporosis, and risk of hip or wrist fractures with a significantly higher bone turnover rate [[16], [17], [18], [19]]. Some other literatures have not substantiated a correlation between night shift schedule and the onset of osteoporosis [20]. From these studies, many recognized methods for osteoporosis risk include BMD obtained at femoral neck, total femur, or lumbar spine (L1–L4) using dual-energy X-ray absorptiometry (DXA), and self-reported fracture [[16], [17], [18], [19], [20]]. However, the osteoporosis clinical criteria used the BMD at total spine or femoral neck areas [21].
Most of the research was cross-sectional, community-based, and focused on a group of people restricted to gender or age so that they represented only a small portion of the population [[16], [17], [18], [19], [20]]. As the accuracy of the findings is based on the sample size, we would like to conduct our study by using nationwide population-based data from the National Health and Nutrition Examination Survey (NHANES).
Osteoporosis and osteoporotic fractures are relevant to age and gender. After the age of 50, osteoporosis is significantly more prevalent in women than in males [22]. The incidence of hip fractures in the US has been reckoned at 17% for white women and 6% for white men after age 50 [23]. Besides, it is also vital for males because of a higher prevalence of secondary osteoporosis and mortality after a fracture [24]. Therefore, age 50 years and gender are two essential risk factors for bone health.
To this end, our study aimed to evaluate the association between T-scores at femoral neck or total spine, and osteoporosis risk with night shift work in a cohort representative of the US population from 3.6 cycles of the NHANES (2007–2008, 2009–2010, 2017–March2020), and explore age, gender, or lifestyle differences.
2. Methods
2.1. Participants and data acquisition
NHANES program consists of ongoing, comprehensive, cross-sectional, population-based surveys to collect data about the health, nutritional status, and health behaviors of the non-institutionalized civilian resident population of the United States conducted by the National Center for Health Statistic of the Centers for Disease Control and Prevention (CDC) since the early 1960s [25]. It was approved by the National Center for Health Statistics Research Ethics Review Board and underwent annual review. These interviews, physical exams, and laboratory testing were conducted at mobile examination center (MEC) or home.
In this cross-sectional research, initial consideration was given to 36,246 potential participants from 3.6 cycles of NHANES (2007–2008, 2009–2010, and 2017–March 2020). After excluding 31,838 participants with missing covariate data who did not meet the criteria, this study population included 2351 male and 2057 female adults, with an age range of 20–80 years. The overall work schedule was structured based on response by survey participants (“Evening or nights” and “Early mornings” for night shift work and “Traditional 9 a.m. to 5 p.m. day” for traditional shift work). The study followed related guidelines and regulations. Subjects with incomplete dietary data, examination data, or questionnaires were excluded from the study. Fig. 1 illustrates the research population selection procedure.
Fig. 1.
The selection process of the population from 2007 to 2008, 2009–2010, 2017–March2020 NHANES database.
Abbreviation: NHANES, National Health and Nutrition Examination Survey.
2.2. BMD, osteoporosis, and osteoporotic fractures criteria
BMD (g/cm2) at the femoral neck or total spine areas was examined by a DXA scan (Hologic, Bedford, MA, USA), with femoral neck testing on the left hip, unless there was a history of previous fracture or surgery in which case the right hip was used; additionally, BMD at the total spine areas was the average of measurements from L1 to L4 [26]. All DXA machines routinely conducted quality control. We define osteoporosis according to World Health Organization criteria, which is BMD at the femoral neck or total spine equal to or less than 2.5 standard deviations below the mean for youthful people of the same gender [27]. To determine the fractured history, when asked “Has a doctor ever told you that you had a broken or fractured hip/wrist/spine?“, if the participants answered “yes”, the subjects were recorded as positive. In the study, we stratified the subjects by gender and age 50 years.
2.3. Other covariates
Covariates, including epidemiological characteristics, health status, nutrition, and harmful lifestyle habits, were obtained using questionnaires and examinations collected in MEC from NHANES.
Among others, nutrition has a crucial role as a modifiable factor in influencing bone health. High ingestion of vegetables, fruits, poultry, fish, whole grains, milk, and dairy products was related to a reduced risk of low BMD and fracture [28]. Thus, energy, carbohydrate, protein, fat, calcium, and Vitamin D included in “Total Nutrient Intakes, First Day” and milk consumption included in “Diet Behavior & Nutrition” were obtained as covariates. Milk consumption was divided into five groups: often (every day or more), sometimes (weekly or more often, but less frequently than daily), rarely (less than weekly), never, and varied.
We should pay attention to the influence of harmful lifestyle habits, including alcoholic behavior, on their risk of osteoporosis, which is adaptable to some extent [29]. A high loading of alcohol consumption is related to a decrease in BMD, which results in an increased liability of fractures [30]. Alcoholic behavior included in “Alcohol Use” is categorized into three groups: every day, rarely (less than monthly), regular (monthly or more often, but less frequently than daily), and never.
Other covariates were also included: age, gender, ethnicity, BMI, blood pressure, diabetes, Hemoglobin A1C (HbA1c), CKD, estimated glomerular filtration rate (eGFR), and caffeine intake. Diabetes is categorized into three groups: yes, no, and borderline. CKD included in “Kidney Conditions - Urology” was divided into yes or no, based on response.
2.4. Statistical analysis
All statistical analyses were performed using STATA, version 17.0 for Windows. Categorical data are expressed as percentage frequency (95% CI), and continuous variables as mean (95% CI). Differences in the pattern of groups were evaluated using the χ2 test for categorical data and the T-test for continuous variables. The multiple interpolation for missing values of covariates was performed using the R package mice (3.16.0, https://cran.r-project.org/web/packages/mice/mice.pdf). Because of the NHANES study's sophisticated survey design, each analysis was appropriately weighted for representation of the United States population. All cycles use the data from the sample with completed day 1 24-h dietary recall, so we use Dietary day 1 sample weights. To combine survey cycles, the survey weights of 2017–March 2020 were multiplied by 3.2/7.2, and 2007–2008 and 2009–2010 were multiplied by 2/7.2 [31]. Linear regression analyses were utilized to estimate the correlations between night shift work and T-scores at the femoral neck and total spine, and results were reported by β (95% CI). The effects of night shift work on osteoporosis were performed to evaluate by logistic regression, which was calculated as odds ratios (95% CI). All model 1 was adjusted for age, gender, ethnicity, BMI, blood pressure, HbA1c, diabetes, eGFR, and CKD, and all model 2 was further adjusted for nutrient intakes, milk or alcohol consumption, and work hours. In all tests, P < 0.05 was considered statistically significant.
3. Results
3.1. Characteristics of participants
After excluding participants with missing covariate data, 4408 adults (average age, 43.52 [95% CI, 42.98–44.06]; 2351[52.8%] men and 2057[47.2%] women) were incorporated in this study, with 671 cases of night shift work and 3737 cases of traditional shift work (Fig. 1).
Table 1 describes the basic characteristics of the study participants by overall work schedule type in adult populations of Americans. Night shift workers were predominantly Non-Hispanic Black, older, and had higher alcoholic consumption (all P < 0.001). They had elevated systolic blood pressure and HbA1c levels (all P < 0.001). However, they had less intake of calcium, milk, protein, and caffeine (all P < 0.05). There were more subjects with osteoporosis, a history of wrist fracture, and diabetes in night shift workers (all P < 0.05).
Table 1.
Characteristics of survey participants according to the overall work schedule in the adults population of NHANES (N = 4408).
| Characteristic | No. | Overall | Overall work schedule | p-value | |
|---|---|---|---|---|---|
| reported | Traditional shift work | Night shift work | |||
| Age, Mean (95% CI), year | 4408 | 43.52(42.98,44.06) | 43.45(42.89,44.01) | 43.94(42.19,45.69) | <0.0001 |
| Gender, % (95% CI) | 4408 | ||||
| Male | 2351 | 52.8(50.67,54.92) | 52.6(50.32,54.87) | 54(48.04,59.85) | 0.443 |
| Female | 2057 | 47.2(45.08,49.33) | 47.39(45.13,49.68) | 46(40.15,51.96) | |
| Ethnicity, % (95% CI) | 4408 | ||||
| Mexican American | 907 | 8.99(8.23,9.82) | 9.1(8.28,10) | 8.31(6.49,10.59) | <0.0001 |
| Other Hispanic | 550 | 5.69(5,6.36) | 5.42(4.79,6.14) | 7.31(5.62,9.47) | |
| Non-Hispanic White | 1834 | 69.1(67.42,70.74) | 70.61(68.84,72.32) | 59.9(54.6,64.98) | |
| Non-Hispanic Black | 808 | 9.55(8.75,10.42) | 8.33(7.53,9.19) | 17.08(14.15,20.47) | |
| Other Race | 309 | 6.66(5.75,7.7) | 6.54(5.56,7.68) | 7.39(5.2,10.41) | |
| BMI, Mean (95% CI), kg/m2 | 4408 | 27.86(27.63,28.09) | 27.84(27.59,28.09) | 27.98(27.4,28.56) | 0.1075 |
| SBP, Mean (95% CI), mmHg | 4408 | 117.71(117,118.43) | 117.311(116.54,118.09) | 120.15(118.31,121.99) | <0.0001 |
| DBP, Mean (95% CI), mmHg | 4408 | 67.19(66.58,67.79) | 67.02(66.37,67.68) | 68.22(66.64,69.79) | 0.0006 |
| Diabetes, %(95% CI) | 4408 | ||||
| Yes | 310 | 5.19(4.34,6.2) | 4.85(3.96,5.93) | 7.28(5.02,10.44) | 0.012 |
| No | 4028 | 93.50(92.40,94.44) | 93.84(92.65,94.85) | 91.36(88.08,93.81) | |
| Borderline | 70 | 1.31(0.93,1.86) | 1.31(0.89,1.92) | 1.36(o.66,2.78) | |
| HbA1c, % | 4408 | 5.52(5.49,5.55) | 5.51(5.48,5.54) | 5.61(5.52,5.7) | <0.0001 |
| CKD, %(95% CI) | 4408 | ||||
| Yes | 48 | 0.91(0.58,1.41) | 0.81(0.5,1.32) | 1.48(0.54,4) | 0.279 |
| No | 4360 | 99.09(98.59,99.42) | 99.19(98.68,99.5) | 98.52(96,99.46) | |
| eGFR, Mean (95% CI), mL/min/1.73m2 | 4408 | 92.98(92.05,93.91) | 92.74(91.75,93.73) | 94.47(91.84,97.1) | 0.1832 |
| Protein intake per day, Mean (95% CI), g/kg | 4408 | 1.12(1.1,1.14) | 1.13(1.11,1.15) | 1.06(0.98,1.13) | 0.0113 |
| Calorie intake, Mean (95% CI), kcal/day/kg | 4408 | 29.01(28.45,29.57) | 29.16(28.57,29.74) | 28.08(26.33,29.83) | 0.0941 |
| Calorie intake, Mean (95% CI), kcal/day | 4408 | 2262.95(2222.53,2303.37) | 2279.06(2236.46,2321.66) | 2164.39(2045,2283.78) | 0.0507 |
| % from carbohydrate, Mean (95% CI) | 4408 | 48.15(47.7,48.61) | 48.12(47.63,48.61) | 48.36(47.11,49.6) | 0.3009 |
| % from protein, Mean (95% CI) | 4408 | 15.82(15.62,16.01) | 15.9(15.69,16.11) | 15.32(14.76,15.87) | 0.0378 |
| % from fat, Mean (95% CI) | 4408 | 3.76(3.72,3.8) | 3.75(3.71,3.79) | 3.83(3.71,3.95) | 0.1883 |
| Vitamin D intake per day, Mean (95% CI), mcg/kg | 4408 | 4.73(4.5,4.95) | 4.79(4.55,5.03) | 4.34(3.81,4.87) | 0.0786 |
| Calcium intake per day, Mean (95% CI), mg/kg | 4408 | 13.07(12.72,13.41) | 13.16(12.81,13.52) | 12.49(11.39,13.59) | 0.0131 |
| Caffeine intake per day, Mean (95% CI), mg/kg | 4408 | 2.49(2.35,2.61) | 2.56(2.42,2.71) | 2.02(1.72,2.31) | 0.0019 |
| Alcohol intake per day, Mean (95% CI), gm/kg | 4408 | 0.16(0.14,0.17) | 0.16(0.14,0.18) | 0.14(0.11,0.18) | 0.2506 |
| Past 12 months alcoholic behavior, %(95% CI) | 2372 | ||||
| Never | 372 | 12.16(10.53,14) | 12.18(10.36,14.28) | 19.49(15.56,24.11) | <0.0001 |
| Rarely- less than monthly | 1667 | 72.23(69.32,74.96) | 74.54(71.36,77.47) | 60.29(54.38,65.92) | |
| Regular - monthly or more often, but less frequently than daily | 281 | 13.07(10.83,15.71) | 10.46(8.19,13.25) | 19.02(14.44,24.62) | |
| Everyday | 52 | 2.54(1.62,3.94) | 2.82(1.75,4.53) | 1.21(0.51,2.83) | |
| Milk consumption, %(95% CI) | 4408 | ||||
| Never | 782 | 16.45(14.98,18.03) | 16.46(14.87,18.17) | 16.42(12.8,20.82) | 0.004 |
| Rarely - less than weekly | 722 | 15.29(13.82,16.89) | 14.51(13.02,16.15) | 20.07(15.43,25.69) | |
| Sometimes - weekly or more often, but less frequently than daily | 1317 | 31.44(29.44,33.51) | 31.27(29.13,33.5) | 32.44(27.1,38.27) | |
| Often - every day or more | 1579 | 36.59(34.58,38.64) | 37.49(35.32,39.71) | 31.07(25.96,36.68) | |
| Varied | 8 | 0.23(0.09,0.59) | 0.27(0.1,0.69) | NA | |
| Working hours per week, Mean (95% CI), h | 4408 | 40.48(39.93,41.03) | 40.69(40.09,41.3) | 39.17(37.85,40.5) | 0.0507 |
| Femoral neck BMD, Mean (95% CI) | 4408 | 0.85(0.85,0.86) | 0.85(0.85,0.86) | 0.86(0.84,0.87) | 0.2701 |
| Femoral neck T-score, Mean (95% CI) | 4408 | −0.28(-0.33,-0.23) | −0.28(-0.33,-0.23) | −0.27(-0.42,-0.13) | 0.2701 |
| Total spine BMD, Mean (95% CI) | 4408 | 1.04(1.04,1.05) | 1.04(1.04,1.05) | 1.03(1.02,1.05) | 0.2923 |
| Total spine T-score, Mean (95% CI) | 4408 | −0.18(-0.23,-0.13) | −0.16(-0.21,-0.11) | −0.26(-0.41,-0.12) | 0.2923 |
| Osteoporosis, %(95% CI) | 4408 | ||||
| Yes | 162 | 3.14(2.48,3.97) | 2.59(2.02,3.31) | 6.5(3.81,10.9) | 0.012 |
| No | 4246 | 96.6(96.03,97.52) | 97.41(96.69,97.98) | 93.5(89.1,96.19) | |
| Broken or fractured | 400 | ||||
| Hip, %(95% CI) | 22 | 0.65(0.36,1.16) | 0.72(0.39,1.31) | 0.23(0.07,0.8) | 0.836 |
| Wrist, %(95% CI) | 326 | 9.3(8.01,10.79) | 9.19(7.77,10.84) | 10.04(7.38,13.54) | 0.047 |
| Spine, %(95% CI) | 52 | 1.6(1.07,2.4) | 1.26(1.03,2.54) | 1.47(0.68,3.15) | 0.674 |
Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA1c, Hemoglobin A1C; CKD, Chronic kidney disease; eGFR, estimated glomerular filtration rate; BMD, bone mineral density; NHANES, National Health and Nutrition Examination Survey; CI, confidence interval.
3.2. Associations bone parameters with night shift work
Linear regression models demonstrating the association of night shift work and T-scores at total spine and the femoral neck are summarized in Table 2. In all models, night shift work was correlated with statistically significant decreases in total spine T-scores of females and females aged ≥50, but not females aged <50. At the same time, night shift work was associated with statistically significant decreases in total spine T-scores of females aged ≥50 years and statistically significant increases in femoral neck T-scores of females aged <50 years in unadjusted models. After the multiple adjustments of basic characteristics for potential confounders, these associations did not fade. Besides, the decreases in femoral neck T-scores of females aged ≥50 years and total spine in T-scores became statistically significant associated with night shift work. Nevertheless, these associations mostly faded following the multivariate adjustments of living habits except total spine in T-scores of females aged ≥50 years.
Table 2.
Association of night shift work with T-Scores in NHANES 2007–2008, 2009–2010, and 2017–March.
| Variable |
Unadjusted model |
Model 1a |
Model 2b |
|||
|---|---|---|---|---|---|---|
| β (95% CI) | p-value | β (95% CI) | p-value | β (95% CI) | p-value | |
| Femoral neck t score | ||||||
| Overall | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.01(-0.14,0.16) | 0.905 | −0.04(-0.16,0.09) | 0.543 | −0.04(-0.2,0.12) | 0.615 |
| Male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.01(-0.18,0.2) | 0.901 | −0.02(-0.19,0.16) | 0.808 | 0.02(-0.16,0.2) | 0.842 |
| Female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.01(-0.24,0.22) | 0.926 | −0.06(-0.23,0.11) | 0.02 | −0.18(-0.48,0.12) | 0.248 |
| Age<50, male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.16(-0.07,0.4) | 0.166 | 0.11(-0.12,0.34) | 0.345 | 0.13(-0.11,0.37) | 0.296 |
| Age<50, female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.32(0.08,0.57) | 0.01 | 0.27(0.04,0.49) | 0.022 | NA | NA |
| Age ≥ 50, male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.08(-0.36,0.2) | 0.587 | −0.05(-0.3,0.19) | 0.667 | −0.05(-0.32,0.21) | 0.703 |
| Age ≥ 50, female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.19(-0.44,0.07) | 0.153 | −0.28(-0.52,-0.04) | 0.021 | −0.22(-0.51,0.08) | 0.144 |
| Total spine t score | ||||||
| Overall | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.1(-0.25,0.05) | 0.202 | −0.13(-0.27,0.02) | 0.08 | −0.05(-0.23,0.12) | 0.553 |
| Male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.04(-0.14,0.22) | 0.66 | 0.02(-0.16,0.2) | 0.818 | 0.1(-0.07,0.28) | 0.253 |
| Female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.27(-0.51,-0.03) | 0.025 | −0.29(-0.48,-0.1) | 0.003 | −0.44(-0.76,-0.12) | 0.008 |
| Age<50, male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.01(-0.21,0.22) | 0.941 | 0(-0.2,0.2) | 0.987 | 0.08(-0.12,0.29) | 0.424 |
| Age<50, female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.02(-0.27,0.22) | 0.852 | −0.03(-0.23,0.18) | 0.776 | NA | NA |
| Age ≥ 50, male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.07(-0.25,0.39) | 0.663 | 0.18(-0.13,0.49) | 0.268 | 0.27(-0.04,0.59) | 0.09 |
| Age ≥ 50, female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | −0.37(-0.68,-0.07) | 0.016 | −0.45(-0.75,-0.16) | 0.003 | −0.53(-0.85,-0.21) | 0.001 |
Abbreviations: NHANES, National Health and Nutrition Examination Survey; NA, not applicable; REF, reference; CI, confidence interval.
Unreliable estimates are due to insufficient result observations.
Adjusted for age, sex, ethnicity, BMI, blood pressure, HbA1c, diabetes, eGFR, and CKD.
Adjusted for nutrient intakes, milk or alcohol consumption, and work hours.
Across the entire study, gender (β = −0.53 [95% CI, −0.75 to −0.3]; P < 0.001), advancing age (β = −0.03 [95% CI, −0.04 to −0.03]; P < 0.001), less protein intake (β = −0.54 [95% CI, −0.89 to −0.2]; P = 0.002), and CKD (β = −0.97 [95% CI, −1.45 to −0.48]; P < 0.001) were the statistically significant covariates related to diminished femoral neck T-scores. Besides, lower total spine in T-scores did not correlate with advancing age but diabetes (β = −1.22 [95% CI, −1.69 to −0.75]; P < 0.001).
3.3. Associations osteoporosis with night shift work
Table 3 summarizes the correlation between night shift work and the prevalence of osteoporosis within the research population. In the unadjusted investigation, night shift work was associated with a higher prevalence of osteoporosis (OR = 2.62 [95% CI, 1.41–4.85]; P = 0.002). Besides, male night shift workers aged ≥50 years had the highest-odds of osteoporosis (OR = 5.64 [95% CI, 1.75–18.23]; P = 0.004). In model 1, there were statistically significant associations of night shift work with adding odds of osteoporosis (OR = 2.57 [95% CI, 1.25–5.28]; P = 0.01). Moreover, males aged ≥50 years had a higher odds of osteoporosis (OR = 4.93 [95% CI, 1.28–19.04]; P = 0.021). With the multivariate adjustment of living habits in model 2, night shift work was correlated with a higher prevalence of osteoporosis (OR = 2.31 [95% CI, 1.03–5.18]; P = 0.043). Furthermore, females aged ≥50 had the greatest-odds of osteoporosis (OR = 4.6 [95% CI, 1.21–17.54]; P = 0.025). In univariate or multivariate analyses, night shift workers of males aged <50 years were not related to heightened risk of osteoporosis (Table 3). Moreover, no increased risk of osteoporotic fractures was observed as a result (data not shown).
Table 3.
Associations of night shift works with osteoporosis in NHANES, 2007–2008, 2009–2010, and 2017–March2020.
| Variable |
Unadjusted model |
Model 1a |
Model 2b |
|||
|---|---|---|---|---|---|---|
| OR(95% CI) | p-value | OR(95% CI) | p-value | OR(95% CI) | p-value | |
| Overall | ||||||
| Traditional shift works | REF | |||||
| Night shift works | 2.62(1.41,4.85) | 0.002 | 2.57(1.25,5.28) | 0.01 | 2.31(1.03,5.18) | 0.043 |
| Male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 4.03(1.48,10.95) | 0.006 | 2.76(0.85,8.95) | 0.092 | 2.04(0.77,5.37) | 0.151 |
| Female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 2.31(1.06,5.06) | 0.036 | 2.33(0.91,5.94) | 0.077 | 4.52(1.07,19.16) | 0.041 |
| Age<50, male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 0.7(0.19,2.67) | 0.605 | 0.59(0.15,2.31) | 0.446 | 0.15(0.01,2.04) | 0.155 |
| Age<50, female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 1.41(0.18,11.12) | 0.741 | 1.41(0.13,15.24) | 0.777 | NA | NA |
| Age ≥ 50, male | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 5.64(1.75,18.23) | 0.004 | 4.93(1.28,19.04) | 0.021 | 3.26(0.93,11.49) | 0.065 |
| Age ≥ 50, female | ||||||
| Traditional shift works | REF | REF | REF | |||
| Night shift works | 2.16(0.9,5.18) | 0.084 | 2.52(0.99,6.47) | 0.054 | 4.6(1.21,17.54) | 0.025 |
Abbreviations: NHANES, National Health and Nutrition Examination Survey; OR, odds ratio; NA, not applicable; REF, reference; CI, confidence interval.
Unreliable estimates are due to insufficient result observations.
Adjusted for age, sex, ethnicity, BMI, blood pressure, HbA1c, diabetes, eGFR, and CKD.
Adjusted for nutrient intakes, milk or alcohol consumption, and work hours.
4. Discussion
In our study, we revealed that night shift work, especially for females aged ≥50 years, substantially raised the risk of osteoporosis compared with traditional shift work. Despite statistically significant associations of advancing-age and gender with lower total spine BMD or osteoporosis, our findings draw emphasis on the effect of harmful lifestyles.
The correlation between night shift schedule, BMD, and osteoporosis differs in literatures. In an investigation, a cohort of postmenopausal nurses aged ≥50 in Chile showed that the rotating shift work was relevant to the decrease of BMD in femoral neck or lumbar spine, and the increased prevalence of osteopenia, compared with the traditional shift work [16]. The consequences of our research are in line with these findings. In order to explore age or gender differences, we expanded the survey population to defined adults. However other studies did not reveal an effect of the same outcome as mentioned. Two of them were cross-sectional and population-based. One involved 3005 adults aged ≤50 analyzing the data from Fourth Korea National Health and Nutrition Examination Survey 2009 [17]. The other was carried out among 500 adults aged ≥50 from the NHANES (2010–2011) [32]. A cross-sectional study of 194 female blue-collar workers aged >40 years with subgroups of premenopausal and postmenopausal women also revealed negative results [20]. The sample size, population, lifetime duration for night shift work, work type, and measurement have contributed to these different outcomes. To clarify the impact of the night shift work on bone health, a sizable population foundation with standard measurements such as NHANES and more cycles combinations are provided to prevent this type of partiality. This is the first report to evaluate the associations among night shift work, BMD, and osteoporosis in a cross-sectional, population-based survey, especially for the US adult population, and to explore age, gender, or lifestyle differences.
There is a great deal of evidence that indicates a significant necessity to consider age and gender when assessing bone health [2,[33], [34], [35]]. With advancing age, the intricate balance between bone formation and bone resorption went into disorder, related to osteoporosis [33]. The loss of hormonal and increase in oxygen species were crucial drivers of bone loss [34,35]. Because of menopause, females suffer more than males. Epidemiologic research demonstrated that women (16.5%) have a higher prevalence of femoral neck and/or lumbar spine osteoporosis than men (5.1%) based on NHANES (2013–2014) data [2]. Consequently, we led a subgroup analysis of age and gender. Our research did not find night shift work correlated with either total femoral neck or total spine T-score in the overall population but with total spine T-score in females. Besides, compared to the overall female group, females aged ≥50 years make a greater contribution to low BMD in the total spine, while females aged <50 years reveal no effect. Furthermore, the relationship between night shift work and osteoporosis is significant in females aged ≥50 years after the full adjustment, but not in females aged <50 years or males. These findings may support the explanation for the effect of age or gender on bone health.
One interesting point in our study is that female night shift workers aged ≥50 years encounter a tremendously higher risk of osteoporosis after adjusting from the covariates of lifestyle habits. Still, we did not see this phenomenon in the unadjusted model and model 1. Contrary to females, male night shift workers had countervailing manifestations. In the group of adults aged <50 years, we did not observe this distinction. Most of females suffer from postmenopausal after aged 50 years, which led to the reduced protection of estrogen for bone health [36]. Besides, the bone loss increase in bone turnover in females with age is quite as much as males [37]. In our study, night shift work is significantly associated with decreased femoral neck or total spine T-score in females aged ≥50 years. That is more than enough to justify the close relationship between night shift work and osteoporosis in females aged ≥50. Furthermore, there is distinction in lifestyle habits by gender. In comparison to men, a higher percentage of women choose not to drink alcohol throughout their lifetime, drink less, and are less prone to problematic drinking behaviors [38]. More intake of vitamin D, calcium, protein, and dairy is good for protecting bone mass [39]. To our consideration, women aged ≥50 years seem to care more about their health status, so they have healthier lifestyles than men, which would be a protective factor. After changing lifestyle habits from harmful to healthy, males aged ≥50 may decrease the osteoporosis risk.
Night shift work results in harmful lifestyles and interferes with circadian rhythm. Moreover, it leads to more exposure to artificial light at night, which may decrease melatonin production resulting in bone loss [40,41]. The lack of sunlight exposure is common in night shift workers. Moreover, it may cause a low vitamin D level, contributing to osteoporosis or even osteoporotic fractures [42,43]. In addition, unhealthy lifestyles and night shift work were related to an increased probability of Diabetes mellitus type 2 and hypertension [44,45]. In our work, night shift workers tend to be more diabetic, and have higher blood pressure and HbA1c. A previous study showed that postmenopausal nurses who worked in rotating-shift schedules for over 10 years had a greater proportion of current smokers (48.7% vs. 32.2%) and coffee intake (66.6% vs. 16.4%). We found that less protein intake and diabetes separately or together accelerate bone mass loss. Therefore, it is imperative to address the necessity for lifestyle improvement in reducing the probability of low BMD or osteoporosis. In other words, more protein or calcium intake, regular milk consumption, and quitting alcoholic or smoking behavior presumably provide counteracting effects to the lifestyle risk factors depending on the results above.
5. Limitations
There are some limitations to our study. Because of the cross-sectional nature of the NHANES, neither long-term data on the participants nor a causal relationship could be determined. We didn't know the lifetime duration for night shift work, current daily work duration, and work type, so the cumulative effect or working intensity has not been discerned. Future studies require a validated questionnaire assessment of night shift work status, as such biases may result in an underestimation of the relationship between night shift work and BMD of osteoporosis. Owing to the missing data, we did not adjust lifestyle habits of physical activity, smoking behavior, osteoporotic parameters or sun-protective behaviors and examined serum 25-hydroxyvitamin D levels in the models. Moreover, nutrition data were collected from “Total Nutrient Intakes, First Day” taken at a point in time from NHANES, which wasn't the representative of the average nutrient intake and may have influenced study findings.
6. Conclusions
Results of this cross-sectional study indicated that night shift work was associated with a higher risk of osteoporosis in US adults, especially for women aged ≥50 years. Besides, night shift schedule was significantly related to an increased risk of low BMD among American women aged ≥50 years. Furthermore, harmful lifestyles have a combined impact on osteoporosis risk for male night-shift workers aged ≥50 years. Our findings contribute to the existing understanding of the relationships between bone health and the integrated effect of night shift work, age, gender, and lifestyle. Future research should pay attention to assessing the possible causal effects of this relationship accounting for lifetime duration of night shift work, current daily work duration, and work type.
Data availability statement
The datasets presented in this study are available at NHANES website: https://www.cdc.gov/nchs/nhanes/index.htm.
Ethics approval
Review and approval by an ethics committee was not needed for this study because the data in this study are from public databases.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
CRediT authorship contribution statement
Yu Qian: Writing – original draft, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Jianchun Mao: Writing – review & editing, Supervision, Project administration, Conceptualization.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
We would like to give our heartfelt thanks to the editors and reviewers for their valuable comments.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e28240.
Appendix A. Supplementary data
The following is/are the supplementary data to this article:
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets presented in this study are available at NHANES website: https://www.cdc.gov/nchs/nhanes/index.htm.