Journal of Nursing Administration:
Job Stress and Work Schedules in Relation to Nurse Obesity
Han, Kihye PhD, RN; Trinkoff, Alison M. ScD, RN; Storr, Carla L. ScD; Geiger-Brown, Jeanne PhD, RN
Author Affiliations: Postdoctoral Fellow (Dr Han), Professor (Drs Trinkoff and Storr), and Associate Professor (Dr Geiger-Brown), School of Nursing, University of Maryland, Baltimore.
The authors declare no conflict of interest.
Correspondence: Dr Trinkoff, School of Nursing, University of Maryland, 655 West Lombard St, Room 625, Baltimore, MD 21201-1579 (email@example.com).
Objectives: This study aimed to examine the relationship between job stress/work schedules (JS/WS) and obesity among nurses.
Background: Job stress and shift work are known risk factors for obesity, yet comprehensive measures of JS/WS in relation to nurse obesity have been little investigated.
Methods: Secondary data analysis used survey data from 2,103 female nurses. Obesity was measured using body mass index estimates. Binomial logistic regression models incorporated independent components of JS/WS and adjusted for demographics, nursing position, mental/emotional distress, health behaviors, and family-related covariates.
Results: Approximately 55% of the sample was overweight/obese (OW/OB). When compared with underweight/normal weight nurses, OW/OB nurses reported that their jobs had less physical exertion (odds ratio [OR] = 0.82, 95% confidence interval [CI] = 0.72-0.95, P = .01) and more limited movement (OR = 1.14, 95% CI = 1.02-1.28, P = .03). Long work hours (OR = 1.23, 95% CI = 1.08-1.40, P < .01) were significantly associated with being OW/OB as compared with underweight/normal.
Conclusions: Findings suggest interventions to limit adverse work schedules. Access to healthy food and optimal meal breaks should be investigated.
The obesity epidemic in the United States is a widely recognized major national health threat as obesity increases the risk of many health conditions and psychological impairments.1,2 Annual medical costs associated with obesity are expected to double every decade to $861 to $960 billion by 2030, or 16% to 18% of the total US healthcare costs.3 In workplaces, obese employees have more fatigue, sleepiness, and physical limitations, which lead to higher risks of occupational injury than among nonobese employees.4 Nurses' obesity and related health problems may be related to high absenteeism, retention, and high healthcare costs.5
A socioepidemiologic approach suggests that certain work characteristics and conditions may cause negative health behaviors and outcomes among employees.6 According to the Demand-Control-Support model,7 job strain occurs because of high psychological demands, combined with low control/decision latitude and lack of social support on the job. In this context, job strain is exhibited as job stress that may affect eating behavior and food choices, for example, a tendency to eat more sweet and energy-dense foods.8 In nursing, high workload, low staffing levels, and shorter work breaks have all been reported as barriers to nurses' healthy eating.9,10 Disordered eating was more prevalent among nurses with high job stress, and the relationship between disordered eating (ie, binging) and obesity was exacerbated by psychological stress.11 Moreover, Lallukka et al12 found job stress related to decreased physical activity and unhealthy diet habits (eg, low vegetable or fruit consumption, not choosing whole grains).
Work schedules also may influence nurses' health by causing job strain or altering health behaviors.13 Adverse work schedules could lead to obesity among nurses; for instance, shift work and long work hours disrupt normal eating times and reduce access to healthy food.9,10,14 Because of a lack of available food service, nightshift workers tend to eat unhealthy food (eg, high salt, sugar) from vending machines or prepackaged foods.15 Nightshift nurses reported that their work schedules affected their stamina, frequency of exercise, and social and family life more than those working other shifts.16 However, few nurses' obesity studies have incorporated work schedule variables.
There is also lack of knowledge about the prevalence of nurses' obesity and of the potential relationship between nurses' work and obesity. The prevalence of nurse overweight/obesity was 55% in 1 study,17 slightly lower than for the US population (65%). Another study found that 65% of hospital nurses were overweight/obese (OW/OB).18 However, low response rates and oversampling of minority and male nurses hamper generalization of these estimates.
The purposes of this article were to (a) describe overweight/obesity rates among a more representative sample of nurses and (b) examine the relationship between job stress/work schedules and nurse obesity. Demographic and work characteristics, mental/emotional distress, health behaviors, and home demands were also examined in these analyses. Study findings can provide evidence of working conditions related to obesity and could support recommendations to reduce nurses' obesity and improve their health.
Sample and Data Collection
This is a secondary data analysis using cross-sectional data from wave 1 of the Nurses' Worklife and Health Study (NWHS). The NWHS was a 3-wave longitudinal survey of nurses' working conditions and injuries,19,20 but only the baseline questionnaire contained variables necessary for this study. The NWHS randomly selected 5,000 nurses from 2 US states (Illinois and North Carolina). Wave 1 data were collected from November 2002 to March 2003. Of 4,229 RNs with valid addresses who agreed to participate, 2,624 RNs (95% women) returned questionnaires, yielding a 62% enrollment rate.19 The sample was comparable to the 2004 US nurse population in terms of demographic and job characteristics.21 The study was approved by the Institutional Review Board, University of Maryland, Baltimore.
The sample for this report was restricted to women (because of gender differences in obesity physiology22) who were working in nursing in the year before wave 1 (87%). We excluded 61 women with missing weight and height data. The characteristics of the eligible sample of 2,103 nurses (average age = 46 years, 86% white, and 58% working in hospitals) were similar to US nurses (average age = 45 years, 88% white, and 56% working in hospitals).21
Obesity was based on a derived body mass index (BMI), dividing weight in kilograms by the square of height in meters, which was then categorized into 2 weight groups: underweight/normal (UW/NW; BMI < 25.0 kg/m2) and OW/OB (BMI ≥ 25.0 kg/m2).23 Height was assessed as a continuous variable, and weight categories provided ranges to decrease nonresponse for what many consider a sensitive variable: 1 = less than 100 lb; 2 = 100 to 129 lb; 3 = 130 to 159 lb; 4 = 160 to 189 lb; 5 = 190 to 200 lb; and 6 = greater than 200 lb. Three sets of BMI estimates were calculated using the minimum, median, and maximum values of the body weight ranges for each category.
To identify the most valid BMI estimate among the minimum, median, and maximum estimates, we used data from the 2003 to 2004 National Health and Nutrition Examination Survey and found the highest level of agreement between the BMI median estimates and the exact BMI values (κ = 0.78, substantial agreement). In addition, the BMI median estimates exhibited both underestimation and overestimation, unlike for the minimum and maximum estimates, suggesting a well-balanced misclassification pattern. Because the BMI median estimates showed the strongest validity, we used the median estimates to measure BMI.
Three elements of job stress (demands, control, and support) were assessed. All items related to job stress had 4-point Likert-type responses. Psychological demands (α = .90) and physical demands (α = .83) were assessed using items adapted from the Job Content Questionnaire (JCQ),24 plus additional nurse-specific items.25 Nine items measured decision-making authority and autonomy (job control, α = 0.82): 5 from the Nursing Work Index-Revised (NWI-R),26 plus 4 from the Procedural Justice Scale.27 Job support (α = .82) was assessed by 7 items from the JCQ support domain24 and the NWI-R.26 To obtain data on workers' typical schedules, schedules were measured over the past 6 months19,28 using 13 items.28,29
To construct independent variables within job demands, control, support, and work schedules, factor analysis was conducted using principal components analysis with varimax rotation.30 The number of components was based on Kaiser's31 criterion (eigenvalues > 1), which determines components explaining enough variations in the sample: components accounted for 57% to 79% of the variances of the underlying dimensions, indicating the components as reliable measures in this sample. Component scores were calculated using the regression method (Table 1). This technique has been used similarly in studies investigating nursing work environments.29,32 When we reexamined this technique using another nurse dataset25 collected from 1999 to 2000, the findings were similar, supporting the reliability of these measures.
Potential confounders of the relationship between working conditions and obesity were demographics, work characteristics, mental/emotional distress, health behaviors, and home demands. Demographics included age, race/ethnicity, and educational level. For work characteristics, nursing position was included to control for the sedentary nature of some positions. Years of RN experience was excluded because of multicollinearity with age (r = 0.80). Mental/emotional distress was measured using the Center for Epidemiologic Studies Depression scale33 (α = .90). Health behaviors were assessed as exercise, sleep quantity, current smoking, and alcohol use. Home demands included spending time on domestic chores, regularly caring for children or dependents, and physical lifting of children or dependents.
Analysis was performed using the Predictive Analytics Software (PASW) version 17.0 (SPSS/IBM Inc, Somers, NY). To compare OW/OB and UW/NW nurses, bivariate analysis was conducted using t tests for continuous variables and χ2 contingency tables for categorical variables. To examine the relationship between job stress/work schedules and obesity, binomial logistic regression models were generated using backward entry, and all models were adjusted for the potential confounders. Components with OR greater than 1 indicated elevated odds of being OW/OB.
The prevalence of overweight (BMI ≥ 25.0 kg/m2) for the sample was 55.0%, and 27.1% of the sample were obese (BMI ≥ 30.0 kg/m2). There was no variation in these prevalences by place of employment (hospital vs nonhospital). When compared with UW/NW nurses, OW/OB nurses were about 2.5 years older (P < .01), more likely to be African American (P < .01), with less education (P < .01), worked as RNs longer (P < .01), and more likely to work full time (P = .02; Table 2). In addition, OW/OB nurses reported significantly more depressive symptoms (P < .01), perceived their health as worse (P < .01), performed less exercise (P < .01), and had more frequent restless sleep (P = .03) than UW/NW nurses did, whereas sleep quantity did not differ between the 2 groups (P = .40).
Models adjusted for the potential confounders are summarized in Table 3. For model 1, jobs with limited movement provided the only component significantly associated with being OW/OB (OR = 1.17, 95% CI = 1.06-1.29, P < .01). This did not change after adjustment for job control and support (OR = 1.15, 95% CI = 1.04-1.28, P = .01; model 2). For work schedule (model 3), nurses who reported long work hours were significantly more likely to be OW/OB (OR = 1.14, 95% CI = 1.01-1.28, P = .03). In the full model (model 4), limited movement and long work hours remained significant, although the relationship between long work hours and being OW/OB was strengthened (OR = 1.23, 95% CI = 1.08-1.40, P < .01). In addition, OW/OB nurses were significantly less likely to report jobs with high physical exertion (OR = 0.82, 95% CI = 0.72-0.95, P = .01). Nursing position (eg, staff nurse) was not associated with nurse obesity in any of the 4 models.
This study is 1 of the few to investigate nurses' obesity using population-based nurse data to assess working conditions and obesity in nurses and the first to demonstrate an association between nurses' long work hours and obesity. Shift rotation and long work hours may affect circadian rhythms, with a detrimental effect on sleep quality and quantity.13,34 Disrupted day/night cycles and sleep patterns suppress melatonin, which affects metabolic processes such as physical activity, food efficiency (ie, body weight change divided by food intake), and visceral adiposity.34 Fonken et al35 found that those working at night reported increased food consumption and body mass and decreased glucose tolerance. In addition, a reduction in leptin levels while working at night led to smaller but more frequent meals and to weight gain.36 Extended work hours also adversely affect sleep patterns. The Nurses' Sleep Study showed that nurses working successive 12-hour shifts slept 5.5 hours on average between shifts.34
Our results also found an inverse relation between obesity and job-related physical exertion. Higher physical exertion might reflect job-related exercise, which could reduce overweight and obesity among nurses. In addition, UW/NW nurses reported recreational exercising significantly more than the OW/OB ones. Occupational and leisure time physical activities have been suggested as indicators of good health,37 whereas sedentary work and low physical job demands are important risk factors for obesity.38,39 However, several studies reported that energy expenditure on the job was not related to being OW/OB, whereas leisure time activity was related.40 Another explanation is that obese nurses might avoid jobs requiring high physical exertion and prefer those with less movement.41 Physical demands were reported to be highest for staff nurses and nurses working in critical care, emergency, or operating room/post-anesthesia care units,42 and burnout or stressful work environment was reported by 45% of nurses who left nursing jobs,21 suggesting a need for additional efforts for ergonomic job design for obese nurses on these units. On the other hand, the relationship between occupational physical activity and nurse obesity was significant only after work schedule variables were controlled. Shift rotation may play a role; in 1 study, appetite-related hormone levels (eg, ghrelin, leptin) after exercise differed between day and night, indicating differing responses to activity by time of day.43 Further studies are needed to investigate the interactions of occupational activities and work schedules on obesity.
The study findings should be interpreted cautiously. First, because all data were self-reported, nurses' responses might be affected by recall bias or denial of a problem. On the other hand, work environments and demands measured in survey questionnaires have been found to be reliable when compared with direct observations.44 Although body weight is often self-reported in large epidemiologic studies, respondents tend to underreport their weight.45 Because of this concern about inaccurate self-reported body weight data, plus the sensitivity of weight data in females, the NWHS measured weight using a categorical variable. As our prevalence estimates were congruent with other studies, this suggests that bias from the variable construction was minimal. Another limitation was that secondary data analysis does not permit collection of additional items, such as diet quality or behaviors and familial obesity,46 which were not measured in the original survey. We did include many variables related to demographics, mental/emotional distress, health behaviors, and home demands, a strength compared to previous research. Finally, as this was a cross-sectional design, it was not possible to determine the temporal order of relationships between working conditions and obesity. Our results may reflect that being OW/OB led nurses to avoid jobs with exertion, but it is less likely that nurses' weight affected their work schedules.
The study results provide evidence-based information for nurse executives and administrators. Long work hours and shift work adversely affect quantity and quality of sleep, which often interferes with adherence to healthy behavior13,16,47 and increases obesity.48 Therefore, educational interventions about sleep hygiene and strategies for adapting work schedules should be offered. A favorable organizational climate that supports napping in the workplace can help to prevent work-related sleep deprivation, reduce fatigue, and increase energy for healthy lifestyle behaviors.49 As shown in the 2004 National Sample Survey of Registered Nurses, more than 40% of nurses who left nursing pointed out the reason for leaving their nursing jobs as scheduling or working too many hours.21 To restrict unhealthful scheduling and help nurse retention, state regulations related to total work hours or mandatory overtime may play an important role in improving nurse scheduling and retention.50
In addition, to decrease nurse obesity rates, collective action is needed. Considering that more than half of nurses are overweight or obese, increasing availability of healthy food and providing sufficient time to consume it may reduce the risk of obesity and future health problems. Organizational support for offering healthier food choices and meal breaks to eat a proper meal instead of non-nutritious snacks can help to decrease obesity risks. For instance, several hospitals have introduced on-site farmer's markets to increase access to healthy food for healthcare workers who work nonstandard hours. Providing healthy vending machine choices and delivering food services to the work unit can also increase food quality and access for nightshift nurses.
This study incorporated a variety of work-related variables, including both job stress and work schedules, and found that long work hours and activity on the job were related to obesity. Further studies investigating nurses' obesity using objective measures and developing solutions to improve nurse health and safety are needed. Findings relating nurse obesity to long work hours provide yet another reason to consider altering nurses' work schedules. Adverse health impact of work schedules on nurses should be given careful attention by administrators and other nursing stakeholders.
The authors gratefully acknowledge Dr Karen Johnson, University of Maryland School of Nursing, and Dr Sungae Park, Seoul National University College of Nursing, for thoroughly reviewing our article.
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