Association between shift work and being overweight or obese among health care workers in a clinical setting in Medellin,Colombia

Abstract

BACKGROUND: Shift work is common in health care settings and has been hypothesized as a risk factor for being overweight or obese. We examined the relation between shift work and being overweight or obese, adjusting for stress and lifestyle habits in Colombian health care workers.

OBJECTIVE: The aim of this study was to assess the association between shift work and being overweight/obese in employees of a health care setting in Medellin, Colombia.

METHODS: This cross-sectional study was carried out among 200 workers in a health care setting. Participants completed a demographic, occupational, work-related stress and life style questionnaire. Their Body Mass Index (BMI) and waist to hip ratio were also measured.

RESULTS: The study sample consisted of 160 (80%) females and 40 (20%) males. Mean age was 35.1±9.1 years and mean BMI was 25±3.9. After adjusting for potential confounders, multivariate logistic regression revealed no statistically significant association between being overweight, being obese or waist to hip ratio and shift work; 95% CI OR: 1.08 (0.62–1.89), 1.33 (0.44–3.99) and 1.2 (0.8–1.9), respectively. Day workers were statistically more likely to smoke, work more hours, and have a higher educational level than shift workers.

CONCLUSIONS: No significant associations between shift work and being overweight/obese were observed in health care workers in a Colombian setting. These findings need to be confirmed through longitudinal studies.

Keywords

Working-time arrangements body mass index stress weight waist to hip ratio

1 Introduction

Shift work is frequent in contemporary life; it is estimated that in industrialized countries, approximately 20% of jobs use this organization [1]. European and North American surveys reported that between 15 to 30% of the adult worker population are exposed to shift work [2, 3]. In Colombia, according to the first national survey of health and working conditions in 2007, 29% of people work in rotating shifts [4].

A lot of research has been done concerning the health effects of shift work. Shift work has been associated with many adverse health outcomes, including gastrointestinal disorders, cancer, diabetes, and metabolic and cardiovascular disease [5 –11].

The mechanism explaining the impact of shift work on health is not fully understood; circadian rhythm disruption [12], light at night [13], sleep deprivation [14], immune depression [15], lifestyle changes [16, 17] and stress [15] have been postulated as potential mediators.

Being overweight or obese may have deleterious health effects and are associated with chronic diseases such as stroke, hypertension, cardiovascular disease, cancer and type II diabetes [18 –22]. Being overweight/obese has been found to be more prevalent among shift workers than day workers; (42.2% vs. 34.3%; p = 0.020) [23]. and (79.1% vs. 67.3% p = 0.024) [24]. A systematic review of longitudinal studies found strong evidence for an association between shift work exposure and body weight increase [25].

Research findings suggest that the likelihood of being overweight or obese may increase by at least 39% as a result of shift work [26 –29]. Some studies have found a positive link between shift work and higher waist circumference along with BMI [30 –33]. Others were unable to see this association [27, 34].

Stress as a risk factor for weight gain has not been usually considered as a confounding factor in studies assessing the relation between shift and obesity. Research investigating an association between stress at work and an increased BMI have found inconclusive results; some found a positive relationship [35, 36], while others have encountered an inverse relationship [37, 38] or no relation [39].

We investigated this association in health care workers from a tertiary clinic, adjusting for potential confounding factors including work related stress. To our knowledge, there is no other study investigating associations between shift work and obesity among Colombian health care workers.

2 Methods

2.1 Study participants

This cross-sectional study was carried out in a tertiary clinic, in Medellin, Colombia, between January and July 2014.

Sample size calculation was performed using information found in the study conducted by Kim et al in 2013 [40]. They reported a prevalence of being overweight/obese of 23% in day nurses and 13% in rotating shift nurses, with a confidence of 95% and a power of 80%. This resulted in a sample size of 200 workers.

Two hundred randomly selected workers, in a health care setting, were invited to participate in the study. Participants who worked less than one year in the health care setting were excluded in order to avoid the circadian adaptation period (n = 13). Pregnant women, or those within one year of the postpartum period, were excluded as the pregnancy could affect their anthropometric measurements (n = 2). Twelve workers refused to participate. Those who were excluded were replaced by randomly selected workers until all 200 workers were eligible for the study. Background characteristics between participants and those workers who refused to participate did not differ statistically.

Participants were considered to work in shifts according to their response when questioned about the current work status and time and duration of each shift. Administrative records verified this information.

To provide continuous work for 24 hours, a 12-hour shift system is common in Colombian health care institutions; daytime (7 : 00 a.m. to 7 : 00 p.m.) and night time (7 : 00 p.m. to 7 : 00 a.m.) followed by either 36 or 60 hours off.

The study was conducted in accordance with the Declaration of Helsinki’s ethical standards; subjects gave their informed consent to participate in the study. Approval for this study was obtained from CES University, Colombia Ethics Committee.

2.2 Measurements

A self-administered questionnaire was constructed to obtain information about demographics (age, gender, marital status and educational level), occupational (occupational position, daily work hours, years working in the same shift), and lifestyle characteristics (smoking status, regular exercise, regular drinking habit) of the participants.

Body Mass Index and Waist to hip ratio were assessed through a medical examination by a physician. Body Mass Index was calculated as body weight (kg) divided by height squared (m²). The BMI thresholds are ≥25 kg/m² for being overweight, and ≥30 kg/m² for obesity, according to World Health Organization (WHO) parameters [41].

Waist circumference was measured at midway between the lower-rib margin and the superior anterior iliac spine. Hip circumference was measured around the widest portion of the buttocks. Measurements were taken over light clothing and barefoot. Cut off points for obesity through waist to hip ratio measurement were ≥80 for females and ≥100 for males. Both Body Mass Index and Waist to hip ratio were assessed through a medical examination by a physician. Sleep duration was assessed through responses to this question: how many hours do you sleep per day?

Smoking status, regular drinking habits, and regular exercise were assessed through self-reports. Smoking status was categorized as never smoker, past smoker and current smoker; subjects consuming at least one cigarette per day were categorized as current smokers. A participant consuming liquor more than 3 times in a month was considered a regular drinker. Regular exercise was considered if participants performed vigorous or moderate physical activity at least once a week. Work schedule experience was categorized according to the median of the distribution in≤ 4 years and >4 years.

Work-related stress was assessed through a 31-item questionnaire designed and validated for Colombian workers by Ministerio de la Proteccion Social [42] to detect symptoms indicating stress reactions (Cronbach α= 0.889; p = 0.001). The domains are based on the following subjects: physiological symptoms (eight questions), social behavior symptoms (four questions), intellectual and occupational symptoms (10 questions), and psycho-emotional symptoms (three questions). The responses to questions were given using a four-level Likert scale (i.e. always, almost always, sometimes, never); responses of always or almost always reflect high stresssymptoms.

2.3 Statistical analysis

Background characteristics of participants were summarized for day workers and shift workers. Continuous variables are presented according to the distribution as mean±standard deviations or medians±interquartile ranges, and categorical variables as percentages. A Chi-squared test was used to calculate odds ratio (OR) with 95% confidence intervals, and independent t-tests or Mann-Whitney -tests were performed to compare means or medians between groups for normal and skewed data, respectively. Multivariable logistic regression analysis was performed to calculate adjusted ORs, taking into account potential confounding factors including gender, stress and age. Values of p < 0.05 were considered to be statistically significant. Due to the exploratory nature of this study, multiple testing was not controlled for. All data were analyzed using SPSS Statistics 21 (SPSS Inc., IBM Corp., Chicago, IL, USA).

3 Results

Background characteristics of rotating shift workers and day workers are presented in Table 1.

The study sample consisted of 160 (80%) female and 40 (20%) male participants. A total of 50.5% of participants performed their work activities in rotating shifts and 49.5% during the day. Most professionals were nurses and administrative staff. The mean age of participants was 35.1±9.1 years; 41.5% of participants were single.

Prevalence of smoking was higher for workers in rotating shifts; i.e., 14.9% compared to 10.5% for day workers (p = 0.035). This difference is statistically significant. Proportion of regular drinkers was 79%, with no statistically significant differences between current shift workers and day workers. Around 50% of participants did not perform regular physical activity, with no statistically significant differences between shift workers and day workers (49.5% vs. 52.5%; p = 0.388). The Self-reported sleep hours did not differ between current shift workers and day workers (p = 0.664)

Educational level was significantly higher in day workers, compared to shift workers.

Among shift workers, 68.4% reported medium or high job-related stress compared to 60.6% of day workers. On average, current shift workers had higher daily working hours than non-shift workers (p < 0.01), and higher shift work durations (p = 0.01).

3.1 Prevalence of overweight, obesity and high waist to hip ratio

Table 2 shows the prevalence of overweight, obesity and high waist to hip ratio according to work schedules. The prevalence of workers who were overweight (BMI between 25 and 29.9), were similar among rotating shift and day workers (40.6% vs. 40.4%; p = 0.546). Obesity prevalence (7.9%) was higher in rotating shift workers; however, the difference was not statistically significant (p = 0.407). As seen in Table 2, a high waist to hip ratio was more prevalent among day workers compared to shift workers, but this difference was not statistically significant (p = 0.191).

3.2 Multivariate logistic regression

The results of multivariate logistic regression analysis for overweightness, obesity and waist to hip ratio according to the type of shift are presented in Table 3. The unadjusted odds ratio (OR) for being overweight, obese, and waist to hip ratio were 1.08 (0.62–1.89), 1.33 (0.44–3.99) and 1.2 (0.8–1.9), respectively; with no significant associations found. Gender and age-adjusted OR for being overweight, obese, and waist to hip ratio were 1.20 (0.67–2.15), 1.36 (0.45–4.10) and 0.86 (0.63–1.19), respectively (p > 0.05).

4 Discussion

The aim of this study was to assess the association between shift work and being overweight or obese among employees of a health care setting in Medellin, Colombia. The overall prevalence of participants in our study who were overweight was 40.5%, and obese was 7%. This is lower compared to data reported in the National Nutritional Situation Survey in Colombia in 2010, for the adult population (18 to 64 years old), where 51.2% had excess body weight [43]. Our result may be explained by the healthy worker effect, reflecting that an individual must be relatively healthy in order to be employable, and/or a low mean age of participants. However, it is important to take into account that our sample is comprised mainly of women, and it has been reported in the National Nutritional Situation Survey in Colombia in 2010, that they had a higher prevalence for being overweight and obesity than in men.

Prevalence of overweightness among shift workers in our study was 40.6%, similar to Macagnan et al. reporting 42.2% of night shift workers being overweight, and a 24.9% prevalence of abdominal obesity among workers of a poultry processing plant, compared to 24.8% in our study. However, they used waist circumference instead of waist to hip ratio to measure abdominal obesity of their participants.

Some studies have not found statistically significant differences in BMI between day workers and shift workers. Nakamura et al., in a study conducted to determine if there was an association between shift work and risk factors for coronary heart disease in Japanese male blue-collar shift workers, reported a mean BMI of 23±3.2 for day workers, compared to 23.2±2.6 for two-shift workers [44]. In the same way, Geliebter et al, who assessed if weight gain was more prevalent in shift workers than in those on day shift, found no significant between-group differences in current Body Mass Index [45]. Our findings agree with the results of Ghiasvand et al in a cross-sectional study about shift work and risk of lipid disorders in rail road workers, that there were no statistical significant differences in prevalence of obesity when comparing day workers and shift workers [46]. Similarly, no differences in obesity prevalence were observed in a study conducted with female workers in a Japanese computer factory that aimed to determine the effect of shift work on nutrientintake [47].

Some studies have also evaluated the relationship between shift work and abdominal obesity. De Bacquer et al. assessed the incidence of metabolic syndrome in workers in rotating shifts through a prospective design, found a greater risk of abdominal obesity among them compared to day workers (p < 0.0001) [48]. Van Amelsvoort reported a positive relationship between years worked in shifts with waist to hip ratio and BMI, for both males and females, adjusting for age [49]. A cross-sectional study of 6,676 Japanese workers in a metal product factory reported an association between shift work and waist to hip ratio [31]; and Sookoian et al compared rotating shift workers and day workers found an elevated waist-hip ratio (0.95 +/–0.01 vs. 0.93 +/–0.01, p < 0.00024) [50]. In contrast to the results of our study, among a cohort of Italian workers rotating shift nurses had greater waist circumference than day workers, and among them healthcare providers had greater waist circumference [51].

It is well known that lifestyle characteristics may act as potential mediators in the relationship between shift work and weight gain [5]. Assessing differences in physical activity, our study found that rotating shift workers are not less likely to exercise regularly when compared with day workers; in contrast with results from a systematic review about modifiable lifestyle factors and shift work [52].

Regarding the current smoking status among our participants, a significant difference was observed between shift workers and day workers (p = 0.035). The number of current smokers who were shift workers was more than twice of that of day workers; showing a similar pattern reported in a prospective cohort study of Japanese male workers by Fujino et al. in [53], and in a study by Pimenta et al. to assess cardiovascular risk among employees from a public university in Brazil [54]. Furthermore, shift workers showed a higher prevalence of current smoking than daytime workers (58.8% vs 47.6%, respectively) in a study by Kubo et al. [55].

Age has previously been reported as being associated with body composition and shift work duration [49], is likely an important confounding factor; however, after adjusting for age, and shift work duration, the relationship between current shift work and overweight/obesity and waist to hip ratio remained not statistically significant in our study. These results are consistent with Kim et al, who evaluated the association between shift work and obesity among female nurses and found no statistically significant association between current shift work andBMI [40].

Work-related stress (medium and high stress symptoms) was found to be more prevalent in our study among the current shift workers compared to day workers; 68.4% vs. 60.6% respectively. This is consistent with the findings of Pimenta et al, who evaluated demand-control and social support at work and observed that shift workers reported higher demands and lower job control compared to day workers [54]. Additionally, Coffey et al. examined the influence of rotating shift schedules on job-related stress of registered nurses in five hospitals. They found that rotating shift nurses experience the most job-related stress [56]. Buja et al. investigated whether working schedules in nurses were associated with different levels of job-related stress, and concluded that those working night shifts showed higher odds of having a high job demand [57].

Some studies have reported a positive relationship between work-related stress and weight gain [58 –60], while others were unable to observe that association [61]. Work-related stress may act as a potential risk factor for weight gain by affecting eating behaviors and food choices and by establishing barriers to healthy eating [62].

This study has some limitations that need to be considered. First, the sample size is relatively small when it is compared with most of the studies. In addition, the cross-sectional design limits the evidence about the relationship between shift work and overweightness/obesity, which impedes an understanding of the causal pathway and the temporal antecedence of the exposure. Moreover, our data were collected from self-reported questionnaires, and are susceptible to random misclassification by participants. Additionally, shift work exposure must be explored in depth, including measures such as speed, direction and frequency of night shifts and any correlations with body weight.

5 Conclusion

The results show that no statistically significant association was found between shift work and overweight/obesity, assessed using BMI and waist to hip circumference measurements. These findings need to be confirmed in longitudinal prospective studies.

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Acknowledgments

Authors warmly thank Clinica CES, Medellin, Colombia, for all the logistic support given to this study.

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