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Occupational Medicine Advance Access published online on December 13, 2007
Occupational Medicine, doi:10.1093/occmed/kqm135
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© The Author 2007. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Physical activity, weight gain and occupational health among call centre employees

Robert W. Boyce1, Edward L. Boone2, Brian W. Cioci3 and Albert H. Lee2

1 Department of Health and Applied Human Sciences, University of North Carolina at Wilmington, 601 S. College Road, Wilmington, NC 28403, USA
2 Department of Statistical Sciences, Virginia Common Wealth University, 1001 West Main Street, Richmond, VA 23284, USA
3 University of North Carolina at Wilmington-Alumni, 8915 West Creek Road, Berkshire, NY 13736, USA

Correspondence to: Robert W. Boyce, Department of Health and Applied Human Sciences, University of North Carolina at Wilmington, 601 S. College Road, Wilmington, NC 28403, USA. Tel: +1 910 962 7824; fax: +1 910 962 7073; e-mail: boycer{at}uncw.edu


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
 References
 
Background A need exists to address ergonomic, weight gain and obesity risks in sedentary occupations.

Aim To determine relationships between body mass index (BMI), weight gain, ergonomic and exercise variables in sedentary workers.

Methods An anonymous questionnaire was administered regarding body weight, height, weight gained since employment, body part discomfort, shift fatigue, time to achieve job adaptation, physical activity, fitness centre membership, previous employment type and previous injury.

Results Subjects were 393 volunteers (mean age 34 years, 71% female) employed in a call centre. Sixty-eight per cent of participants gained weight averaging 0.9 kg/month for 8 months. Significant findings (P < 0.05) were as follows: non-obese individuals gained less weight than obese individuals, fitness club members had higher BMIs and weight gains than non-members, previously injured individuals gained more weight than non-injured individuals, non-weight gainers reported higher metabolic equivalent-min/week expenditure in relation to vigorous exercise.

Conclusions Participants reported substantial weight gain over a period of 8 months. In contrast to walking and moderate exercise, only vigorous exercise was significantly associated with non-weight gain. Three risk factors were identified for weight gain: obese when hired, history of previous injury and lack of vigorous exercise.

Keywords      BMI; body weight; call centre; discomfort; ergonomics; exercise; fatigue; obesity; occupations; safety; sedentary


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Conflicts of interest
 References
 
Over the past century there has been a large decline in individual physical activity [1,2]. Computer-related occupations have become more commonplace and they involve high levels of sitting time and lower demand for physical activity. These types of jobs may play a role in the growing problem of overweight and obesity [3].

Obesity-related diseases constitute a significant cost to an organization [4]. Costs result from known risk factors such as diabetes [5] and coronary heart disease [6] as well as musculoskeletal disorders [7] raising issues regarding productivity and safety within the workplace.

Weight gain also has an impact on disease factors. Weight gain in women has been associated with worsening health status [8], decreased physical function and vitality and increased bodily pain [9], as well as increased risk in coronary heart disease [6]. Sedentary occupations have been associated with weight gain and obesity in men [3]. Furthermore, increasing increments of work sitting time have been associated with diabetes and weight gain risk in women [10]. Mummery et al. [3] suggested ‘further research is needed to clearly understand the association between sitting time at work with overweight and obesity in women.’

A study of 15 occupations that utilized computers found female call centre operators reported the highest prevalence of musculoskeletal symptoms [11]. Toomingas et al. [12] reported that call centre operators exhibited more musculoskeletal symptoms than other professional computer users. They indicated few studies have been conducted regarding incidence of symptom data with call centre operators and suggested more extensive research was needed to examine working conditions and health status among call centre operators. Our literature review also found little research regarding body mass index (BMI) and weight gain in call centre operators and its relationship to occupational safety and health promotion variables. Furthermore, the National Institute for Occupational Safety and Health encourages simultaneously addressing occupational safety and health and worksite health promotion to create a ‘synergism of prevention’ to improve employee health through risk reduction [13,14]. Therefore, the purpose of our study was to report BMI and weight gain in call centre employees and to investigate their relationships with occupational safety variables to include body part discomfort, fatigue, job adaptation and history of previous injury.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Conflicts of interest
 References
 
An anonymous ergonomic, exercise and wellness questionnaire was administered to ~1100 employees at a call centre located in the southeastern United States. This new facility had been operational for 8 months and had an on-site exercise centre. The population was estimated to be evenly divided between African American and non-Hispanic Caucasians. The job required strong verbal and written communication skills and computer literacy. The socio-economic status of employees was primarily middle class in a range from lower-middle to upper-middle class.

The University of North Carolina at Wilmington Institutional Review Board approved this study following the United States National Institutes of Health guidelines concerning rights of human subjects. Participation was voluntary and each participant signed a written consent form. The questionnaire included self-reported assessments of age, gender, body weight, body part discomfort levels, shift fatigue, how many days to become physically adapted to job, previous musculoskeletal injury (yes/no), similar job duties in previous job (yes/no), if gained weight since starting job (yes/no), if so, how much, exercise club membership (yes/no) and exercise level using International Physical Activity Questionnaire [15].

Body part discomfort scale was rated 0–5 (0 = no discomfort to 5 = very uncomfortable). Shift fatigue was estimated at beginning of shift (first 5 min) and 8 h into shift (0 = no fatigue to 5 = very fatigued). Questions concerning body part discomfort, injury and job adaptation came from an ergonomic assessment form provided by the Ergonomic Centre of North Carolina [16].

The International Physical Activity Questionnaire (IPAQ) short form was used to evaluate energy expenditure of three levels of activities: vigorous, moderate and walking. The unit of measure for the IPAQ short form is MET-minutes used per week. Metabolic equivalents (METs) are multiples of resting metabolic rates. A MET-minute is computed by multiplying the METs used per minute for an activity by the number of minutes performed. Total MET-minutes used per week is the total of vigorous, moderate and walking MET-min/week. The activity data collected were reported as a continuous variable in MET-min/week [15].

The Statistical Package for the Social Sciences (SPSS, Inc) version 14.0 was used to analyse data. Analysis of variance (ANOVA) procedures tested differences between males and females in descriptive statistics for age, height, body weight, BMI (weight in kg/height in m2) and overall pounds gained for all groups in 8-month period and pounds gained in 8 months for those that reported weight gained. Prevalence of BMI was presented in percentages and standard error of estimates breaking BMI scores into five categories: underweight ≤18.5, normal 18.6–24.9, overweight 25.0–29.9, obese 30.0–39.9 and extreme obese 40.0+. BMI percentage comparisons with USA [17] used three categories: overweight or obese (BMI 25 or higher), obese (BMI 30 or higher) and extreme obese (BMI 40 or higher).

ANOVA procedures were used to compare variances as follows: (i) between non-obese (BMI ≤ 29.9) and obese (BMI ≥ 30) and (ii) non-weight gainers and gainers for age, bodyweight, body part discomfort, fatigue on job after 5 min and after 8 h, job adaptation, weight gain for all subjects and for only those reporting weight gains and MET-min/week for vigorous, moderate, walking and total exercise. The 18 body part discomfort variables were shoulder, elbow, wrist, leg, knee and foot (reported separately by left and right sides) and buttocks, head, eyes, neck, upper back and low back. A discomfort index was generated through a principal components analysis that combined all body part discomfort scores. MET-min/week of exercise scores were analysed using a Kruskal–Wallis distribution test comparing median values in addition to the ANOVA. IPAQ procedures suggested median comparisons because IPAQ data tend to be skewed [15]. ANOVA procedures were used to test independent variables of exercise club membership, previous position and previous musculoskeletal injury against dependent variables of BMI and amount of body weight gained.

Participant's BMI at the start of employment was unknown. Therefore, the BMI at the start of employment was calculated using the body weight derived from the following formula: body weight at start = body weight at 8 months minus reported weight gained. The data were analysed to determine if the start of employment BMI analyses gave different results from the 8-month BMI analyses.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Conflicts of interest
 References
 
From ~1100 employees of the call centre who received the questionnaire, 393 volunteers or 36% completed the survey. Seventy-one per cent of respondents were female. The average age for females and males was similar with a combined average of 33.6 ± 9.8 years ranging from 19 to 64 years. Body weight and height between males and females were significantly different (P = 0.001) with no statistical differences in BMI between females and males (Table 1).


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  		Table 1. Comparisons by gender of age, height, weight, BMI and kilograms gained after 8 months of employment in a call centre

 
Approximately 80% of participants had been employed since the call centre opened 8 months earlier. The overall average weight gain was the same for females and males at 5.1 kg (Table 1). Sixty-eight per cent reported gaining weight with an average weight gain of 7.5 kg.

A Pearson correlation analysis revealed that increasing BMI was positively correlated with increasing age (r = 0.252, P < 0.01). This is seen in more detail in Table 2. Relationships of the call centre BMI percentages to US percentages for 2003–2004 [17] were similar.


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  		Table 2. Prevalence of underweight, normal weight, overweight, obesity and extreme obesity in call centre employees by sex and age

 
Non-obese (BMI ≤ 29.9) individuals were compared to obese (BMI ≥ 30) individuals (Table 3). Non-obese employees were significantly (P ≤ 0.05) younger, gained less weight in 8 months of employment and tended to expend more MET-min/week for total (P = 0.08) and for vigorous (P = 0.06) exercise. The average weight gain was 3.7 kg for vigorous exercisers versus 8.0 kg for non-vigorous exercisers. Vigorous exercise median scores comparing non-obese to obese were 320 versus 0 MET-min/week (P < 0.05).


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  		Table 3. Comparisons of non-obese to obese after 8 months of employment in call centre

 
The average fatigue experienced at the beginning of a shift was significantly higher in non-obese individuals compared to obese individuals (P < 0.05). Differences disappeared after 8 h on the job. It took 33 days for both non-obese and obese individuals to adapt to the job (Table 3). Comparisons of non-obese with obese individuals indicated no differences in the overall discomfort index (Table 3). In both groups, the most prevalently reported body part discomfort (percent reporting a discomfort rating of 3 and higher) were low back (41%), neck (35%), upper back (30%), eyes (27%), right shoulder (24%), left shoulder (21%) and right wrist (20%).

Table 4 provides the BMI and weight gained in relation to club membership, previous position and injury. Exercise club members had significantly higher average BMIs than non-members (P < 0.01). No significant differences were found between males and females relating to club membership and average BMI. No differences were found related to BMI and previous similar job or previous injury.


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  		Table 4. BMI and weight gained after 8 months of employment in call centre in relation to club membership, previous position and previous injury

 
Comparisons between non-weight gainers and gainers as seen in Table 5 indicated little difference related to age, body weight, total discomfort index, shift fatigue, job adaptation and total MET-min/week. However, non-weight gainers had significantly higher vigorous exercise expenditure per week (P < 0.05) with no significant differences (P > 0.05) in moderate and walking exercise (Table 5).


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  		Table 5. Comparisons of non-weight gainers and gainers after 8 months of employment in call centre

 
The amount of weight gained was compared to club membership, similar previous position and previous injuries (Table 4). Exercise club members averaged significantly more weight gain than non-members, 6.3 versus 4.3 kg (P < 0.01). Weight gainers with no previous injury gained on average significantly less weight than those reporting previous injuries, 4.2 versus 6.4 kg (P < 0.01).


   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Conflicts of interest
 References
 
The principal findings of our survey revealed that call centre employees reported a substantial weight gain during the first 8 months of employment. Vigorous exercise was significantly associated with non-weight gain. Three risks factors were identified for weight gain: obese when hired, history of previous injury and lack of vigorous exercise.

The primary strength of this study was that it provided a unique picture of the employee health status in a major call centre during the 8 months of operation. While there are distinct advantages when assessing a worksite with commonly used surveys, there are also inherent weaknesses. Reporting of BMI [18], discomfort profiles [19] and exercise assessments [20,21] suffers from errors common to self-reported recall instruments. Self-reported weight and height questionnaires have limitations due to the tendency for women to underreport their weight, particularly the obese [8]. Body weight and BMI have limitations as indicators of health status because both are unable to distinguish between fat mass and lean mass. The weight gain reported by those with fitness club memberships could have been the result of lean mass increases.

Another criticism of our study was the low response rate (36%). This low response rate to the questionnaire can be attributed to it being administered by employee wellness centre staff as opposed to supervisory personnel. In addition, employees had to find time during the work shift to complete the questionnaire. The low response rate could have biased our results.

In our study, the 68% of the employees that gained weight reported an average gain of 7.3 kg in only 8 months. Increased coronary heart disease risk [6] and a 2-fold risk increase of diabetes have been shown with a weight gain of 5.0–7.8 kg >14 years in women [5]. Weight gain of as little as 2.3 kg has been shown to contribute to worsening health status [9], and to increase risk of diabetes, regardless of BMI [22]. The conclusion follows that overweight and obesity should be taken seriously even if disease factors are not obvious [6]. One of the findings of our study was that obese employees gained more weight than non-obese employees. This is supported in the study by St Jeor et al. [23] which determined that weight gainers tended to be younger obese subjects.

Studies have not consistently demonstrated an inverse association between physical activity and BMI or physical activity and weight gain [24–26]. Our participants gained weight despite moderate and walking activity. A key finding in our study is that obese individuals and weight gainers reported significantly less vigorous exercise per week. Our report was consistent with Salmon et al. [27] in finding female respondents with a BMI ≥25 were significantly less likely to engage in vigorous physical activity sessions than their counterparts with a BMI ≤25. Also in support of this, Mummery et al. [3] reported that those with long sitting hours at work may find the minimum dose of prescribed moderate intensity activity (30 min/day) insufficient to prevent obesity. These findings have major implications for exercise dose recommendations for employees in sedentary occupations such as call centre operators.

Our study found significant associations between previous injury and weight gain. However, BMI was similar for both injured and non-injured. Little research has been done on the relationship of previous musculoskeletal injury and its affect on BMI and or weight gain. However, a study of back pain indicated female subjects who experienced chronic back pain gained significantly more weight than those reporting no pain [28]. The conclusion follows from our work that the tracking of previous injury data could assist in identifying employees at risk of weight gain.

Our study has identified potential risk factors for weight gain (i.e. obese when hired, does not engage in vigorous exercise or has a history of prior injury). Specific interventions could be introduced relating to these risk factors. St Jeor et al. [23] have suggested a classification system to evaluate weight maintainers, gainers and losers. This system could prove useful in further research regarding impact of weight changes in this industry.

Suggestions for further study include documenting objective physiological measures such as recording weight upon employment and periodically thereafter. In addition, utilizing anthropometric measures including circumferences and skin-folds would provide a more complete picture of body composition. Other suggestions include reviewing the association of weight gain with productivity and insurance costs, and more specifically, association of weight gain with body discomfort, employee retention and job satisfaction. Research is needed to address the intensity, type and frequency of exercise and the caloric intake required to maintain weight while performing call centre work. In addition, it would be useful to determine if weight gain or BMI has an impact on organizational effectiveness.


Key points
  • Call centre employees reported a substantial weight gain during the first 8 months of employment.
  • Vigorous exercise was significantly associated with non-weight gain.
  • Three risk primary factors were identified in association with weight gainers: obese when hired, history of previous injury and lack of vigorous exercise.

 


   Conflicts of interest
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
References
 
None declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conflicts of interest
 References
 

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