Adapting shift work schedules for sleep quality, sleep duration, and sleepiness in shift workers.

BACKGROUND: Shift work is associated with insufficient sleep, which can compromise worker alertness with ultimate effects on occupational health and safety. Adapting shift work schedules may reduce adverse occupational outcomes. OBJECTIVES: To assess the effects of shift schedule adaptation on sleep quality, sleep duration, and sleepiness among shift workers. SEARCH METHODS: We searched CENTRAL, PubMed, Embase, and eight other databases on 13 December 2020, and again on 20 April 2022, applying no language restrictions. SELECTION CRITERIA: We included randomised controlled trials (RCTs) and non-RCTs, including controlled before-after (CBA) trials, interrupted time series, and cross-over trials. Eligible trials evaluated any of the following shift schedule components. • Permanency of shifts • Regularity of shift changes • Direction of shift rotation • Speed of rotation • Shift duration • Timing of start of shifts • Distribution of shift schedule • Time off between shifts • Split shifts • Protected sleep • Worker participation We included studies that assessed sleep quality off-shift, sleep duration off-shift, or sleepiness during shifts. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the titles and abstracts of the records recovered by the search, read through the full-text articles of potentially eligible studies, and extracted data. We assessed the risk of bias of included studies using the Cochrane risk of bias tool, with specific additional domains for non-randomised and cluster-randomised studies. For all stages, we resolved any disagreements by consulting a third review author. We presented the results by study design and combined clinically homogeneous studies in meta-analyses using random-effects models. We assessed the certainty of the evidence with GRADE. MAIN RESULTS: We included 11 studies with a total of 2125 participants. One study was conducted in a laboratory setting and was not considered for drawing conclusions on intervention effects. The included studies investigated different and often multiple changes to shift schedule, and were heterogeneous with respect to outcome measurement. Forward versus backward rotation Three CBA trials (561 participants) investigated the effects of forward rotation versus backward rotation. Only one CBA trial provided sufficient data for the quantitative analysis; it provided very low-certainty evidence that forward rotation compared with backward rotation did not affect sleep quality measured with the Basic Nordic Sleep Questionnaire (BNSQ; mean difference (MD) -0.20 points, 95% confidence interval (CI) -2.28 to 1.89; 62 participants) or sleep duration off-shift (MD -0.21 hours, 95% CI -3.29 to 2.88; 62 participants). However, there was also very low-certainty evidence that forward rotation reduced sleepiness during shifts measured with the BNSQ (MD -1.24 points, 95% CI -2.24 to -0.24; 62 participants). Faster versus slower rotation Two CBA trials and one non-randomised cross-over trial (341 participants) evaluated faster versus slower shift rotation. We were able to meta-analyse data from two studies. There was low-certainty evidence of no difference in sleep quality off-shift (standardised mean difference (SMD) -0.01, 95% CI -0.26 to 0.23) and very low-certainty evidence that faster shift rotation reduced sleep duration off-shift (SMD -0.26, 95% CI -0.51 to -0.01; 2 studies, 282 participants). The SMD for sleep duration translated to an MD of 0.38 hours' less sleep per day (95% CI -0.74 to -0.01). One study provided very low-certainty evidence that faster rotations decreased sleepiness during shifts measured with the BNSQ (MD -1.24 points, 95% CI -2.24 to -0.24; 62 participants). Limited shift duration (16 hours) versus unlimited shift duration Two RCTs (760 participants) evaluated 80-hour workweeks with maximum daily shift duration of 16 hours versus workweeks without any daily shift duration limits. There was low-certainty evidence that the 16-hour limit increased sleep duration off-shift (SMD 0.50, 95% CI 0.21 to 0.78; which translated to an MD of 0.73 hours' more sleep per day, 95% CI 0.30 to 1.13; 2 RCTs, 760 participants) and moderate-certainty evidence that the 16-hour limit reduced sleepiness during shifts, measured with the Karolinska Sleepiness Scale (SMD -0.29, 95% CI -0.44 to -0.14; which translated to an MD of 0.37 fewer points, 95% CI -0.55 to -0.17; 2 RCTs, 716 participants). Shorter versus longer shifts One RCT, one CBA trial, and one non-randomised cross-over trial (692 participants) evaluated shorter shift duration (eight to 10 hours) versus longer shift duration (two to three hours longer). There was very low-certainty evidence of no difference in sleep quality (SMD -0.23, 95% CI -0.61 to 0.15; which translated to an MD of 0.13 points lower on a scale of 1 to 5; 2 studies, 111 participants) or sleep duration off-shift (SMD 0.18, 95% CI -0.17 to 0.54; which translated to an MD of 0.26 hours' less sleep per day; 2 studies, 121 participants). The RCT and the non-randomised cross-over study found that shorter shifts reduced sleepiness during shifts, while the CBA study found no effect on sleepiness. More compressed versus more spread out shift schedules One RCT and one CBA trial (346 participants) evaluated more compressed versus more spread out shift schedules. The CBA trial provided very low-certainty evidence of no difference between the groups in sleep quality off-shift (MD 0.31 points, 95% CI -0.53 to 1.15) and sleep duration off-shift (MD 0.52 hours, 95% CI -0.52 to 1.56). AUTHORS' CONCLUSIONS: Forward and faster rotation may reduce sleepiness during shifts, and may make no difference to sleep quality, but the evidence is very uncertain. Very low-certainty evidence indicated that sleep duration off-shift decreases with faster rotation. Low-certainty evidence indicated that on-duty workweeks with shift duration limited to 16 hours increases sleep duration, with moderate-certainty evidence for minimal reductions in sleepiness. Changes in shift duration and compression of workweeks had no effect on sleep or sleepiness, but the evidence was of very low-certainty. No evidence is available for other shift schedule changes. There is a need for more high-quality studies (preferably RCTs) for all shift schedule interventions to draw conclusions on the effects of shift schedule adaptations on sleep and sleepiness in shift workers.

(Cost-)effectiveness of a personalized multidisciplinary eHealth intervention for knee arthroplasty patients to enhance return to activities of daily life, work and sports - rationale and protocol of the multicentre ACTIVE randomized controlled trial.

BACKGROUND: With the worldwide rising obesity epidemic and the aging population, it is essential to deliver (cost-)effective care that results in enhanced societal participation among knee arthroplasty patients. The purpose of this study is to describe the development, content, and protocol of our (cost-)effectiveness study that assesses a perioperative integrated care program, including a personalized eHealth app, for knee arthroplasty patients aimed to enhance societal participation post-surgery compared to care as usual. METHODS: The intervention will be tested in a multicentre randomized controlled trial with eleven participating Dutch medical centers (i.e., hospitals and clinics). Working patients on the waiting-list for a total- or unicompartmental knee arthroplasty with the intention to return to work after surgery will be included. After pre-stratification on medical centre with or without eHealth as usual care, operation procedure (total- or unicompartmental knee arthroplasty) and recovery expectations regarding return to work, randomization will take place at the patient-level. A minimum of 138 patients will be included in both the intervention and control group, 276 in total. The control group will receive usual care. On top of care as usual, patients in the intervention group will receive an intervention consisting of three components: 1) a personalized eHealth intervention called ikHerstel ('I Recover') including an activity tracker, 2) goal setting using goal attainment scaling to improve rehabilitation and 3) a referral to a case-manager. Our main outcome is quality of life, based on patient-reported physical functioning (using PROMIS-PF). (Cost-)effectiveness will be assessed from a healthcare and societal perspective. Data collection has been started in 2020 and is expected to finish in 2024. DISCUSSION: Improving societal participation for knee arthroplasty is relevant for patients, health care providers, employers and society. This multicentre randomized controlled trial will evaluate the (cost-)effectiveness of a personalized integrated care program for knee arthroplasty patients, consisting of effective intervention components based on previous studies, compared to care as usual. TRIAL REGISTRATION: Trialsearch.who.int; reference no. NL8525, reference date version 1: 14-04-2020.

Work-related physical and psychosocial risk factors cluster with obesity, smoking and physical inactivity.

OBJECTIVE: This study investigated associations between the co-existence of multiple types of work-related psychosocial and physical risk factors, and (1) obesity; (2) smoking; and (3) leisure-time physical inactivity. It also aimed to identify sociodemographic characteristics related to clustering of work-related risk factors and lifestyle factors. METHODS: Cross-sectional data on work-related risk factors (e.g., decision authority and repetitive movements) and lifestyle was measured using a standardized questionnaire among 52,563 Dutch workers in health care, services, manufacturing and public sector. Multiple-adjusted logistic regression models assessed associations between the co-existence of multiple types of psychosocial and physical risk factors and lifestyle factors. Additionally, logistic regression models related age, gender and educational level to clustering of risk factors and lifestyle factors. RESULTS: The co-existence of multiple types of work-related psychosocial risk factors was associated with higher odds of smoking and being physically inactive. For example, workers exposed to three psychosocial risk factors had a 1.55 times higher odds of being physically inactive (95%CI: 1.42-1.70) compared to unexposed workers. A higher number of physical risk factors was also significantly associated with higher odds of smoking and obesity. The co-existence of multiple types of physical risk factors was not associated with higher odds of physical inactivity. Clustering of work-related risk factors and at least one unhealthy lifestyle factor occurred in particular among workers with low educational level. CONCLUSIONS: Results imply that interventions are needed that focus on workers with a low educational level and address work-related physical and psychosocial risk factors as well as lifestyle.

The mediating role of lifestyle in the relationship between shift work, obesity and diabetes.

PURPOSE: Shift work has been related to obesity and diabetes, but the potential mediating role of lifestyle is yet unknown. Our aim was to investigate this mediating role of physical activity, diet, smoking, and sleep quality in the relationships between shift work, and obesity and diabetes. METHODS: In this cross-sectional study, 3188 shift workers and 6395 non-shift workers participated between 2013 and 2018 in periodical occupational health checks. Weight and height were objectively measured to calculate obesity (BMI ≥ 30 kg/m2). Diabetes status, physical activity, diet, smoking, and sleep quality were assessed using standardized questionnaires. Structural equation models adjusted for relevant confounders were used to analyze the mediating role of lifestyle in the relationships between shift work, and obesity and diabetes. RESULTS: Shift workers were more often obese (OR: 1.37, 95% CI 1.16-1.61) and reported more often to have diabetes (OR:1.35, 95% CI 1.003-1.11) than non-shift workers. Shift workers had lower physical activity levels, ate fruit and vegetables less often, smoked more often, and had poorer sleep quality (p < 0.05). Mediation analysis revealed that shift workers had a higher odds of obesity (OR: 1.07, 95% CI 1.01-1.15) and diabetes (OR: 1.13, 95% CI 1.02-1.27) mediated by poorer sleep quality. Lower physical activity levels (OR: 1.11, 95% CI 1.05-1.19) and lower intake of fruit and vegetables (OR: 1.04, 95% CI 1.01-1.15) were also mediators in the relationship between shift work and obesity, but not in the relationship between shift work and diabetes (p ≥ 0.05). CONCLUSION: These results imply that interventions targeting diet, physical activity and in particular sleep problems specifically developed for shift workers could potentially reduce the adverse health effects of shift work.

Shift work, and burnout and distress among 7798 blue-collar workers.

OBJECTIVE: This study aimed to investigate the association between shift work, and burnout and distress, and differences by degree of satisfaction with shift schedule and its impact on private life. METHODS: Population 4275 non-shift factory workers and 3523 rotating 5-shift workers. Workers participated between 2009 and 2016 one to three times in the companies' periodical occupational health checks. Burnout was measured using the distance, exhaustion and competence subscales of the Dutch Maslach Burnout Inventory and distress by the subscale of the Four-Dimensional Symptom Questionnaire (scale: 0-100). Multiple-adjusted linear mixed models were used to assess between- and within-subject associations between shift work and outcomes, and differences by age, years of shift work, and satisfaction with and impact of shift schedule. RESULTS: Shift work was significantly associated with lower scores on burnout distance (B - 1.0, 95% - 1.8 to 0.3), and among those aged < 48 years with burnout exhaustion (range B - 1.3 to - 1.6). However, the effect sizes were small. Compared to non-shift workers, shift workers dissatisfied with their schedule and those experiencing a high impact on private life had significantly higher burnout (range B 1.7-6.3) and distress levels (range B 4.9-6.1). In contrast, satisfied shift workers and those experiencing a low impact of shift schedule had lower burnout (range B - 0.2 to - 2.2) and no difference in distress levels (P ≥ 0.05). No clear pattern by years of shift work was observed. CONCLUSIONS: Shift work was associated with burnout and distress in those who were dissatisfied with or who had perceived high impact on the private life of their shift schedule.

The moderating role of lifestyle, age, and years working in shifts in the relationship between shift work and being overweight.

PURPOSE: This study aimed to investigate the relationship between the moderating role of lifestyle, age, and years working in shifts and, shift work and being overweight. METHODS: Cross-sectional data were used of 2569 shift and 4848 non-shift production workers who participated between 2013 and 2018 in an occupational health check. Overweight (BMI ≥ 25 kg/m2) was calculated using measured weight and height; lifestyle was assessed by questionnaires. Multiple-adjusted logistic regression with interaction terms between shift work and potential moderators assessed multiplicative interaction; the relative excess risk due to interaction assessed additive interaction (synergism). RESULTS: Shift work was significantly related to being overweight (OR 1.53, 95% CI 1.33 1.76). The strength of this association did not differ by level of sleep quality, fruit and vegetable intake, and physical activity (p ≥ 0.05). Additive and multiplicative interaction by smoking status was present (p < 0.01), with a stronger relationship between shift work and being overweight among non-smokers compared to smokers. Older age as well as more years of exposure to shift work were, independently from each other, related to a stronger relationship between shift work and being overweight (multiplicative interaction p < 0.05). CONCLUSION: Shift work was to a similar extent related to being overweight among those with a healthy and unhealthy lifestyle. This does, however, not imply that shift workers can behave unhealthy without any harm. Based on the evident health benefits of a healthy lifestyle, it is still recommended to get sufficient quality of sleep and to meet the recommended level of daily physical activity and, fruit and vegetable intake.

Shift work, sleep disturbances and social jetlag in healthcare workers.

The aim of this study was to compare chronotype- and age-dependent sleep disturbances and social jetlag between rotating shift workers and non-shift workers, and between different types of shifts. In the Klokwerk+ cohort study, we included 120 rotating shift workers and 74 non-shift workers who were recruited from six Dutch hospitals. Participants wore Actigraph GT3X accelerometers for 24 hr for 7 days. From the Actigraph data, we predicted the sleep duration and social jetlag (measure of circadian misalignment). Mixed models and generalized estimation equations were used to compare the sleep parameters between shift and non-shift workers. Within shift workers, sleep on different shifts was compared with sleep on work-free days. Differences by chronotype and age were investigated using interaction terms. On workdays, shift workers had 3.5 times (95% confidence interval: 2.2-5.4) more often a short (< 7 hr per day) and 4.1 times (95% confidence interval: 2.5-6.8) more often a long (≥ 9 hr per day) sleep duration compared with non-shift workers. This increased odds ratio was present in morning chronotypes, but not in evening chronotypes (interaction p-value < .05). Older shift workers (≥ 50 years) had 7.3 times (95% confidence interval: 2.5-21.8) more often shorter sleep duration between night shifts compared with work-free days, while this was not the case in younger shift workers (< 50 years). Social jetlag due to night shifts increased with increasing age (interaction p-value < .05), but did not differ by chronotype (interaction p-value ≥ .05). In conclusion, shift workers, in particular older workers and morning chronotypes, experienced more sleep disturbances than non-shift workers. Future research should elucidate whether these sleep disturbances contribute to shift work-related health problems.

Shift work, chronotype and the risk of cardiometabolic risk factors.

Background: The relation between shift work and a large variety of cardiometabolic risk factors is unclear. Also, the role of chronotype is understudied. We examined relations between shift work and cardiometabolic risk factors, and explored these relations in different chronotypes. Methods: Cardiometabolic risk factors (anthropometry, blood pressure, lipids, diabetes, γ-glutamyltransferase, C-reactive protein, uric acid and estimated glomerular filtration rate) were assessed among 1334 adults in 1987-91, with repeated measurements every 5 years. Using shift work history data collected in 2013-15, we identified shift work status 1 year prior to all six waves. Linear mixed models and logistic generalized estimating equations were used to estimate the longitudinal relations between shift work and risk factors 1 year later. Results: Shift work was not significantly related with cardiometabolic risk factors (P ≥ 0.05), except for overweight/body mass index. Shift workers had more often overweight (OR: 1.44, 95% CI 1.06-1.95) and a higher body mass index (BMI) (ß: 0.56 kg m-2, 95% CI 0.10-1.03) than day workers. A significant difference in BMI between day and shift workers was observed among evening chronotypes (ß: 0.97 kg m-2, 95% CI 0.21-1.73), but not among morning chronotypes (ß: 0.04 kg m-2, 95% CI -0.85 to 0.93). No differences by frequency of night shifts and duration of shift work were observed. Conclusion: Shift workers did not have an increased risk of cardiometabolic risk factors compared with day workers, but, in particular shift working evening chronotypes, had an increased risk of overweight. More research is needed to verify our results, and establish whether tailored interventions by chronotype are wanted.

Non-occupational physical activity levels of shift workers compared with non-shift workers.

OBJECTIVES: Lack of physical activity (PA) has been hypothesised as an underlying mechanism in the adverse health effects of shift work. Therefore, our aim was to compare non-occupational PA levels between shift workers and non-shift workers. Furthermore, exposure-response relationships for frequency of night shifts and years of shift work regarding non-occupational PA levels were studied. METHODS: Data of 5980 non-shift workers and 532 shift workers from the European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL) were used in these cross-sectional analyses. Time spent (hours/week) in different PA types (walking/cycling/exercise/chores) and intensities (moderate/vigorous) were calculated based on self-reported PA. Furthermore, sports were operationalised as: playing sports (no/yes), individual versus non-individual sports, and non-vigorous-intensity versus vigorous-intensity sports. PA levels were compared between shift workers and non-shift workers using Generalized Estimating Equations and logistic regression. RESULTS: Shift workers reported spending more time walking than non-shift workers (B=2.3 (95% CI 1.2 to 3.4)), but shift work was not associated with other PA types and any of the sports activities. Shift workers who worked 1-4 night shifts/month (B=2.4 (95% CI 0.6 to 4.3)) and ≥5 night shifts/month (B=3.7 (95% CI 1.8 to 5.6)) spent more time walking than non-shift workers. No exposure-response relationships were found between years of shift work and PA levels. CONCLUSIONS: Shift workers spent more time walking than non-shift workers, but we observed no differences in other non-occupational PA levels. To better understand if and how PA plays a role in the negative health consequences of shift work, our findings need to be confirmed in future studies.

Determinants of attaining and maintaining a low cardiovascular risk profile--the Doetinchem Cohort Study.

BACKGROUND: While maintenance of a low cardiovascular risk profile is essential for cardiovascular disease (CVD) prevention, few people maintain a low CVD risk profile throughout their life. We studied the association of demographic, lifestyle, psychological factors and family history of CVD with attainment and maintenance of a low risk profile over three subsequent 5-year periods. METHODS: Measurements of 6390 adults aged 26-65 years at baseline were completed from 1993 to 97 and subsequently at 5-year intervals until 2013. At each wave, participants were categorized into low risk profile (ideal levels of blood pressure, cholesterol and body mass index, non-smoking and no diabetes) and medium/high risk profile (all others). Multivariable-adjusted modified Poisson regression analyses were used to examine determinants of attainment and maintenance of low risk; risk ratios (RR) and 95% confidence intervals (95% CI) were obtained. Generalized estimating equations were used to combine multiple 5-year comparisons. RESULTS: Younger age, female gender and high educational level were associated with higher likelihood of both maintaining and attaining low risk profile (P < 0.05). In addition, likelihood of attaining low risk was 9% higher with each 1-unit increment in Mediterranean diet score (RR: 1.09, 95% CI: 1.02-1.16), twice as high with any physical activity versus none (RR: 2.17, 95% CI: 1.16-4.04) and 35% higher with moderate alcohol consumption versus heavy consumption (RR: 1.35, 95% CI: 1.06-1.73). CONCLUSION: Healthy lifestyle factors such as adherence to a Mediterranean diet, physical activity and moderate as opposed to heavy alcohol consumption were associated with a higher likelihood of attaining a low risk profile.

Generation shifts in smoking over 20 years in two Dutch population-based cohorts aged 20-100 years.

BACKGROUND: Younger and older generations may differ substantially in their lifetime smoking habits, which may result in generation-specific health challenges. We aimed to quantify generation shifts in smoking over a period of 25 years. METHODS: We used the Doetinchem Cohort Study (baseline 1987-1991; 7768 individuals; 20-60 years; follow-up 1993-2012) and the Longitudinal Aging Study Amsterdam (baseline 1992-1993; 3017 individuals; 55-85 years; follow-up 1995-2009). Generation shifts were studied between 10-year generations (age range: 20-100 years). Generation shifts were examined graphically and by using logistic random effect models for men and women. RESULTS: Among men, significant generation shifts in current smoking were found between two non-successive generations: for instance men in their 40s at baseline smoked much more than men in their 40s at follow-up (33.6% vs. 23.1%, p < 0.05). Among women, the most recently born generation showed a favourable significant generation shift in current smoking (-7.3%) and ever smoking (-10.1%). For all other generations, the prevalence of ever smoking among women was significantly higher in every more recently born generation, whereas no other generation shifts were observed for current smoking. The unfavourable generation shifts were mainly found among the lower educated. CONCLUSIONS: The future burden of disease due to smoking is expected to be reduced among men, but not yet among women. Educational differences in smoking-related health problems are expected to increase.

Fundamental movement skills, physical fitness and physical activity among Australian children with juvenile idiopathic arthritis.

AIM: To describe fundamental movement skills (FMS), physical fitness and level of physical activity among Australian children with juvenile idiopathic arthritis (JIA) and compare this with healthy peers. METHODS: Children aged 6-16 years with JIA were recruited from hospital rheumatology clinics and private rheumatology rooms in Sydney, Australia. All children attended an assessment day, where FMS were assessed by a senior paediatric physiotherapist, physical fitness was assessed using the multistage 20-metre shuttle run test, and physical activity and physical and psychosocial well-being were assessed with questionnaires. These results were compared with age- and gender-matched peers from the NSW Schools Physical Activity and Nutrition Survey and the Health of Young Victorians Study using logistic regression analysis. RESULTS: Twenty-eight children with JIA participated in this study. There were no differences in the proportion of children who had mastered FMS between children with JIA and their healthy peers (P > 0.05). However, there was a trend for children with JIA to have poorer physical fitness and be less physically active than healthy peers. Parents of children with JIA indicated more physical and psychosocial impairments among their children and themselves compared with parents of healthy children (P < 0.05). CONCLUSIONS: This is the first study in Australia to compare FMS, physical activity and fitness in children with JIA and their peers. While older children with JIA appear to have poorer physical fitness and physical activity levels than their peers, there is no difference in FMS.

More 50+ Workers Means More 50+ Policy-Until it Doesn't. The Non-Linear Relation Between Proportion of Older Workers and Implementation of Policies for Older Workers.

Personnel policies specifically for older workers can benefit both the older workers and their organization. It is often assumed that a higher percentage of older workers in an organization is associated with more policies for older workers. We hypothesize that policies accommodating older workers, such as extra leave or a reduced workload, become unfeasible if the proportion of older workers is high. We pooled data from five datasets to study eleven older-worker policies in 7330 Dutch establishments. The results show that the number of implemented personnel policies for older workers is highest in establishments where 30-50% of the workers are 50 years and older. The number of implemented policies is lower in establishments with more older than younger workers. This pattern is found for most phasing out policies.

Impact of Simulated Rotating Shift Work on Mammary Tumor Development in the p53R270H©/+WAPCre Mouse Model for Breast Cancer.

Epidemiological studies associate night shift work with increased breast cancer risk. However, the underlying mechanisms are not clearly understood. To better understand these mechanisms, animal models that mimic the human situation of different aspects of shift work are needed. In this study, we used "timed sleep restriction" (TSR) cages to simulate clockwise and counterclockwise rotating shift work schedules and investigated predicted sleep patterns and mammary tumor development in breast tumor-prone female p53R270H©/+WAPCre mice. We show that TSR cages are effective in disturbing normal activity and estimated sleep patterns. Although circadian rhythms were not shifted, we observed effects of the rotating schedules on sleep timing and sleep duration. Sleep loss during a simulated shift was partly compensated after the shift and also partly during the free days. No effects were observed on body weight gain and latency time of breast cancer development. In summary, our study shows that the TSR cages can be used to model shift work in mice and affect patterns of activity and sleep. The effect of disturbing sleep patterns on carcinogenesis needs to be further investigated.

Musculoskeletal complaints among 11-year-old children and associated factors: the PIAMA birth cohort study.

Musculoskeletal complaints (MSC) are common among children, often persist into adolescence, and increase the risk of MSC in adulthood. Knowledge regarding determinants of MSC among children is limited. The aim of this study was to determine the prevalence of MSC at age 11 years and to examine associations with sociodemographic factors, growth and development factors, mental health, tiredness, and lifestyle. Data from a Netherlands birth cohort study, the Prevention and Incidence of Asthma and Mite Allergy (PIAMA) Study (n = 2,638), were used (1996-2009). MSC were defined as complaints about the back, an upper extremity, a lower extremity, or any of these sites. Logistic regression analyses using a forward stepwise procedure were performed on multiply imputed data. The 1-year period prevalences of back, upper extremity, and lower extremity complaints that lasted at least 1 month were 2.8%, 4.8%, and 10.9%, respectively. Only poorer mental health was consistently associated with all 3 types of complaints. Poorer mental health, daytime tiredness, early pubertal development, being physically active at age 11 years, and weight-for-height z score were associated with having any MSC. This study showed that MSC, especially lower extremity complaints, are common among 11-year old-children and that only poorer mental health status is associated with MSC at all anatomic sites.

The potential of using hair cortisol to measure chronic stress in occupational healthcare; a scoping review.

OBJECTIVES: Workplace-based selective prevention of mental health problems currently relies on subjective evaluation of stress complaints. Hair cortisol captures chronic stress responses and could be a promising biomarker for the early identification of mental health problems. The objective was to provide an overview of the state-of-the-art knowledge on the practical value of hair cortisol in the occupational setting. METHODS: We performed a scoping review of cross-sectional and longitudinal studies in PubMed, Embase, and PsycINFO up to November 2019 assessing the relations of hair cortisol with work-related stressors, perceived stress, and mental health outcomes in healthy workers. RESULTS: We found five longitudinal studies, of which two observed an increase in work-related stressors to be associated with higher hair cortisol, one found a relation with lower hair cortisol and one did not find a relationship. Findings of cross-sectional studies were also mixed. The one available longitudinal study regarding mental health showed that hair cortisol was not related to depressive symptoms. CONCLUSIONS: Hair cortisol measurement within occupational health research is still in its early stage and more longitudinal studies are urgently needed to clarify its relationship with work-related stressors and perceived stress before hair cortisol can be used to identify workers at risk for mental health problems.

The acute effects of working time patterns on fatigue and sleep quality using daily measurements of 6195 observations among 223 shift workers.

OBJECTIVES: This study aimed to estimate acute effects of roster characteristics on fatigue and sleep quality and investigated whether these effects differed by individual characteristics. METHODS: Using an ecological measurement assessment survey, fatigue and sleep quality were daily measured among 223 shift workers for up to eight weeks. A questionnaire assessed baseline characteristics, and roster data were retrieved from the company registers to determine roster parameters. The effects between each shift parameter on fatigue and sleep quality were estimated with random- and fixed-effects models. RESULTS: Compared to day shifts, night shifts were related to fatigue [ß=0.22; 95% confidence interval (CI) 0.05-0.39] and poorer sleep quality (ß=0.64; 95% CI 0.47-0.80), and more successive night shifts with more fatigue (up to ß=0.68; 95% CI 0.49-0.87 for ≥2 nights). Fatigue was increased after a quick return (<11 hours) (ß=1.94; 95% CI 1.57-2.31) or 11-16 hours (ß=0.43; 95% CI 0.26-0.61) compared to >16 hours between shifts. Compared to forward rotation, stable (ß=0.22; 95% CI 0.01-0.43) and backward rotation (ß=0.49; 95% CI 0.23-0.74) were also associated with more fatigue. Workers with a morning or intermediate chronotype had poorer sleep quality after a night shift, while workers with poor health reported poor sleep quality as well as more fatigue after a night shift. CONCLUSIONS: To alleviate acute effects of shift work on fatigue, shift schedules should be optimized by ensuring more time to recover and rotate forwards.

Shift work and its relation with meal and snack patterns among healthcare workers.

Objective Unfavorable eating patterns might contribute to the adverse health effects of shift work. Our objective was to examine differences in meal and snack frequency, as well as the quality of snacks, between shift and day workers and between different types of shifts. Methods Cross-sectional data from 485 healthcare workers aged 18-65 years of the Klokwerk+ cohort study was used. Dietary intake was assessed using 3-day food diaries, and meals and snacks were classified by the food-based classification of eating episodes method. Using multivariable-adjusted regression analyses, we estimated differences in meal and snack frequency and the quality of snacks between shift and day workers. Within the shift working group, eating frequency on day, evening, and night shifts were compared to work-free days. Results Meal and snack frequency as well as the quality of snacks showed no significant differences between shift and day workers (P≥0.05). Shift workers had a higher frequency of high-quality snacks [ß 0.29, 95% confidence interval (CI) 0.12-0.46] and a lower frequency of low-quality snacks (ß -0.29, 95% CI -0.49- -0.09) on evening shifts compared to their work-free days. Compared to work-free days, shift workers had a higher frequency of high-quality snacks on days shifts (ß 0.24, 95% CI 0.10-0.38), and only those aged ≤40 years had a higher frequency of snacks on night shifts (ß 0.53, 95% CI 0.06-1.00) (interaction by age P<0.05). Conclusion This study observed no differences between day and shift workers either in meal and snack frequency or in the quality of snacks. However, snacking patterns differed across shifts. Future research should investigate whether these snacking patterns contribute to the adverse health effects of shift work.

The mediating role of sleep, physical activity, and diet in the association between shift work and respiratory infections.

Objectives Shift work may be associated with an increased incidence of respiratory infections. However, underlying mechanisms are unclear. Therefore, our aim was to examine the mediating role of sleep, physical activity, and diet in the association between shift work and respiratory infections. Methods This prospective cohort study included 396 shift and non-shift workers employed in hospitals. At baseline, sleep duration and physical activity were measured using actigraphy and sleep/activity diaries, sleep quality was reported, and frequency of meal and snack consumption was measured using food diaries. In the following six months, participants used a smartphone application to report their influenza-like illness/acute respiratory infection (ILI/ARI) symptoms daily. Mediation analysis of sleep, physical activity, and diet as potential mediators of the effect of shift work on ILI/ARI incidence rate was performed using structural equation modeling with negative binomial and logistic regression. Results Shift workers had a 23% [incidence rate ratio (IRR) 1.23, 95% CI 1.01-1.49] higher incidence rate of ILI/ARI than non-shift workers. After adding the potential mediators to the model, this reduced to 15% (IRR 1.15, 95% CI 0.94-1.40). The largest mediating (ie, indirect) effect was found for poor sleep quality, with shift workers having 29% more ILI/ARI episodes via the pathway of poorer sleep quality (IRR 1.29, 95% CI 1.02-1.95). Conclusions Compared to non-shift workers, shift workers had a higher incidence rate of ILI/ARI that was partly mediated by poorer sleep quality. Therefore, it may be relevant for future research to focus on perceived sleep quality as an underlying mechanism in the relation between shift work and increased infection susceptibility.