Obesity and Worker Productivity by Occupational Class in the U.S.

A new study focuses on the negative impacts of obesity across different occupational classifications

Obesity and its adverse effects on health and employment continue to be the subject of much-needed research and attention. In the recent past, I have taken a look at studies that examined the causes and effects of obesity as reflected in data from the Nurses’ Health Studies biannual research surveys, as well as a 50-state study that looked at the effect of employment absenteeism caused by obesity. Now the Journal of Occupational and Environmental Medicine has published a new study, “Impact of Obesity on Work Productivity in Different US Occupations: Analysis of the National Health and Wellness Survey 2014 to 2015,” which examines the impacts of obesity by different occupational classes.

METHODOLOGY

For this new study, the authors extracted their data from the 2014 and 2015 US National Health and Wellness Survey, an Internet survey with approximately 30,000 useable respondents of age 18 or older who provided demographic, occupational, and weight data, as well as information on health variables and history. The final group was about 19,000 male and 11,000 female. The average age was about 42, with a standard deviation of plus or minus 13. As with any study based on self-reported data, there was no way for the authors to objectively verify the accuracy of the responses and selection bias could have skewed the representativeness of the sample data.

However, taking the data as given, respondents were classified by their Body Mass Index (BMI=weight in kilograms divided by the square of height in meters), with BMIs between 18.5 and 25 classified as normal, between 25 and 30 classified as overweight, and greater than 30 classified as obese. The obese category was further subdivided into three classes, with demarcations coming every 5 BMI points. Respondents who would be considered underweight, i.e., whose BMI was lower than 18.5, were excluded from the study. Respondents were also placed along a comorbidity index based on their discrete health conditions, such as diabetes and chronic pulmonary disease, and as expected, comorbidity index scores tended to increase as BMI increased.

Occupational data provided by the respondents was fit into major occupational groups based on standard classifications developed by the Bureau of Labor Statistics (BLS). Some groups with a smaller number of participants, such as Installation, Maintenance, and Repair, Building and Grounds Cleaning, Farming, Fishing, and Forestry, and Construction and Extraction were consolidated into a single “Construction” group. The 12 occupational groups, in order of the number of respondents for each group, were Finance, Education, Healthcare, Computer, Manufacturing, Construction, Science, Hospitality, Arts, Protective Services, Transportation, and Legal.

FINDINGS

For the total group of survey respondents, 35% had normal BMIs, 32% were classified as overweight, and 32% were classified as obese. Slightly more than half of the obese were in the lowest subcategory with BMIs ranging from 30 to 35. Among the individual occupational groups, BMI results were as follows:

• Finance: 36% were overweight, 25% were obese.
• Education: 31% were overweight, 30% were obese.
• Healthcare: 31% were overweight, 30% were obese.
• Computer: 36% were overweight, 25% were obese.
• Manufacturing: 35% were overweight, 30% were obese.
• Construction: 38% were overweight, 29% were obese.
• Science: 37% were overweight, 21% were obese.
• Hospitality: 32% were overweight, 27% were obese.
• Arts: 34% were overweight, 26% were obese.
• Protective Services: 38% were overweight, 39% were obese.
• Transportation: 38% were overweight, 36% were obese.
• Legal: 38% were overweight, 24% were obese.

Thus, according to these numbers, Protective Services and Transportation were the occupational groups with the greatest percentage of overweight or obese members, with Construction coming in third but with a lower ratio of obese members compared to those who were merely overweight.

“Work impairment” was calculated for each respondent by combining (a) the reported number of hours missed in the past week for health reasons divided by the number of hours that could have been worked (absenteeism) with (b) “the self-reported level of impairment experienced while at work in the past seven days” (presenteeism). The authors found overall a positive association between work productivity impairment and increases in BMI class. For example, members within the Construction occupational group had a calculated mean percentage of overall work productivity impairment of about 18% for members with normal BMIs, about the same 18% for overweight BMIs, almost 20% for obese class 1, about 22% for obese class 2, and about 37% for obese class III (BMIs greater than 40). That 19 point difference from normal BMI to obese class III was the greatest range among the occupational groups, with the Arts group having the next greatest range at about 14.5 points, followed by the Healthcare group with a range of about 12 points. The groups whose work impairment calculations appeared to be the least impacted by increases in BMI included Finance, Protective Services, Computers, Science, and Legal, with ranges between about 5 and 8 points from normal to Obese class III.

The authors also calculated indirect costs for each respondent by multiplying absenteeism and presenteeism by hourly wage rates derived from median weekly income figures obtained from the BLS and found a similar positive association between these costs and BMI class. The mean indirect costs calculated as an annual amount was the highest, again, for the Construction group, increasing from about $7,000 annually for those with normal BMIs to about $12,000 annually for those in the obese class III category. Transportation was the next highest group, increasing from about $5,700 for the normal group to almost $12,000. The Arts group saw an increase from about $5,000 to almost $11,000, with the Computer group right behind with a range of about $5,700 to about $10,500. Manufacturing showed by far the lowest indirect costs, with a mean range from only $237 to about $1,100. However, the much lower amounts for members of this group might be attributable at least in part to lower wage rates, and the indirect costs still show to be almost five times greater for the highest obesity class than for the normal BMI class.

CONCLUSION

This newest study adds even more data to the growing mountain of evidence showing the deleterious effects of the obesity epidemic on the American population and workforce. While the problem is widespread and cuts across all occupational groups, further examination of the differential impacts among these groups might be beneficial for targeting appropriate responses for fighting the problem.

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