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American Journal of Public Health logoLink to American Journal of Public Health
. 2005 Sep;95(9):1614–1622. doi: 10.2105/AJPH.2004.050112

Obesity in US Workers: The National Health Interview Survey, 1986 to 2002

Alberto J Caban 1, David J Lee 1, Lora E Fleming 1, Orlando Gómez-Marín 1, William LeBlanc 1, Terry Pitman 1
PMCID: PMC1449406  PMID: 16051934

Abstract

Objectives. Obesity has emerged as one of the most important public health issues in the United States. We assessed obesity prevalence rates and their trends among major US occupational groups.

Methods. Self-reported weight and height were collected annually on US workers, aged 18 years or older, from the 1986 to 1995 and the 1997 to 2002 National Health Interview Surveys. Overall, occupation-, race-, and gender-specific rates of obesity (defined as a body mass index>30.0 kg/m2) were calculated with data pooled from both study periods (n>600000). Annual occupation-specific prevalence rates were also calculated, and their time trends were assessed.

Results. Obesity rates increased significantly over time among employed workers, irrespective of race and gender. The average yearly change increased from 0.61% (±.04) during the period from 1986 to 1995 to 0.95% (±.11) during the period from 1997 to 2002. Average obesity prevalence rates and corresponding trends varied considerably across occupational groups; pooled obesity prevalence rates were highest in motor vehicle operators (31.7% in men; 31.0% in women).

Conclusions. Weight loss intervention programs targeting workers employed in occupational groups with high or increasing rates of obesity are urgently needed.

In the United States, obesity has risen at an unprecedented rate during the past 20 years,1 and current research indicates that the situation is worsening rather than improving. From 1960 to 1980, the prevalence of obesity among adults in the United States was relatively stable; however, recent findings from the National Health and Nutrition Examination Survey (NHANES) showed that 3 out of every 10 US adults are obese.2 In addition to increasing mortality from all causes, obesity is linked to an increased risk of developing hypertension, type 2 diabetes mellitus, dyslipidemia, gallbladder disease, osteoarthritis, coronary heart disease, stroke, asthma, and sleep apnea.3–7 Additionally, new evidence suggests that obesity is a risk factor for endometrial, breast, prostate, and colon cancers. 8–10

The relationship between obesity and occupation has not been fully investigated. Work-related factors, such as job and position, job stress, and extended work (including overtime night work and sedentary work) may promote weight gain and abdominal fat accumulation.11–14 One of the national Healthy People 2010 Objectives is to reduce the prevalence rate of obesity among adults to less than 15%,15 therefore, because treatment often fails, research efforts focused on prevention are required. Weight loss intervention and education programs targeting workers employed in various occupational groups are urgently needed, but, unfortunately, nationally representative data identifying occupational groups with the highest obesity rates are not presently available.16,17 It is also not known which occupational groups are experiencing large increases in obesity rates. Our research objective was to evaluate overall, gender- and race-specific obesity rates and their 17-year trends, including the past decade, within 41 occupational groups using nationally representative samples of the US worker population.

METHODS

The National Health Interview Survey (NHIS) is a continuous multipurpose and multistage probability area survey of the US civilian noninstitutionalized population living at addressed dwellings.18 Each week, a probability sample of households is interviewed by trained personnel to obtain information about the characteristics of each member of the household.19 In the majority of cases (63%) in the 1986 to 1996 NHIS surveys, the participants themselves answered all the questions; for the remaining participants, the responses were obtained from their relatives or other proxies. However, beginning with the 1997 NHIS survey, all survey responses were self-reported. For simplicity, in the present study, both self-reported or proxy-reported data are referred to as “reported.” In the period from 1986 to 1996, annual NHIS survey response rates ranged from 95% to 98%20; in the period from 1997 to 2002, these rates fell to 70%–80%, reflecting the trend of lower response rates in all national surveys.21,22

Body mass index (BMI) is commonly used to define obesity and has been found to closely correlate with the level of body fat.23 BMI was calculated by dividing weight in kilograms by height in meters squared. Respondents were classified as obese if their BMI was greater than 30.0 kg/m2.24 From 1986 to 1995, the NHIS reported weight and height values for all participants. Data from the 1996 survey year are not presented because, for that year, the National Center for Health Statistics (NCHS) reported data only for participants with a weight between 98 and 289 pounds and a height between 59 and 76 inches; BMI for the 1996 participants outside of these weight and height ranges were not made available by NCHS. Starting in 1997, the NHIS was redesigned and the NCHS made available the BMI values for all participants, even those with weight and height outside the above ranges.25 Because of these differences in the reporting, and because of the major redesign of the sampling and interview format, we analyzed data separately for NHIS survey periods 1986 to 1995 and 1997 to 2002.

In the 1986 to 1995 NHIS, employment information was collected on all subjects aged 18 years or older who reported working during the 2 weeks prior to the survey26,27; starting in 1997, NCHS collected employment information from adults who stated that they were working during the week before the NHIS survey. Both of these definitions included paid and unpaid work. Forty-one standardized occupational codes derived from more detailed US Census occupational codes were provided in the NHIS database from 1986 to 1995 and from 1997 to 2002.28,29 We grouped survey participants in the trend data analysis into White, Black, or “other race” category. “Other race” included other, Aleutian Eskimo/American Indian, Asian/Pacific Islander, and unknown/multiple races.

Because of the complex sample survey design, analyses were completed with the SUDAAN package to take into account sample weights and design effects.30 For pooled prevalence estimates, sample weights were adjusted to account for the aggregation of data over multiple survey years by dividing the original weight by 10 (the number of years combined in survey years 1986 through 1995) and by 6 (the number of years combined in survey years 1997 through 2002).18 To assess obesity trends within each survey period, a weighted linear regression model was fitted to the annual design-adjusted rates within occupational groups. The weight used for each annual rate was the inverse of its variance.

RESULTS

A total of 603 139 persons aged 18 years and older reported working within the 2 weeks prior to their participation in the 1986 to 1995 NHIS surveys, and in the 1 week prior to their participation in the 1997 to 2002 NHIS surveys. Among the 488 612 workers in the 1986 to 1995 survey period, the mean age (±SD) was 38.9 ±12.8, with a total of 226 128 women (46.3%); the mean age of the 114 527 workers from the 1997 to 2002 period was 40.3 ±12.7, including 57198 women (49.9%).

The average yearly change (±SE) in obesity rates increased from 0.61% (±.04) in the 1986 to 1995 period to 0.95% (±.11) in the 1996 to 2002 period. Annual obesity rates increased significantly among all gender-race groups in the survey periods 1986 to 1995 and 1997 to 2002 (Figure 1 ▶). In all survey years, annual obesity rates were highest in Black workers (particularly women) and lowest among those in the “other race” category.

FIGURE 1—

FIGURE 1—

FIGURE 1—

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Trends in gender- and race-specific prevalence rates of obesity among working adults, (a) men and (b) women: the National Health Interview Survey, 1986 to 2002.

For each gender and each 1 of the 41 occupational groups, Tables 1 ▶ and 2 ▶ show: the sample size; the percentage of Black workers for each occupational group (given that Black workers had the highest rates of obesity); the pooled and annual prevalence rates of obesity; and the slope (i.e., yearly change in obesity rate) of the weighted linear regression of rate of obesity over time, its standard error, and the corresponding P value. Slopes were not calculated for a particular occupational group when the sample size for any given survey year was below 46. Pooled and annual obesity rates preceded by an asterisk have a relative standard error [defined as 100 × SE (rate)/rate] of greater than 30% and, following the practice of the NCHS, should be considered imprecise estimates.31

TABLE 1—

Pooled and Annual Prevalence Rates of Obesity in 41 Occupational Categories: the National Health Interview Survey, 1986–1995

Annual Prevalence Rate of Obesity
Occupation Sample No. Estimated US Population Percentage Black Overall Prevalence 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 Slope ± SE P
Men
Officials and administrators (public administration) 1341 320 864 7.2 14.95 10.3 13.2 12.4 16.0 16.3 13.3 13.4 14.4 19.3 19.2 0.631 ± 0.245 .03
Managers and administrators (except public administration) 30 273 7 217 767 4.9 13.11 11.4 10.6 11.5 12.7 12.6 12.8 13.2 15.0 15.5 15.6 0.578 ±0.064 .00
Management-related occupations 7822 1 882 304 6.0 11.97 12.2 10.3 10.0 9.9 10.6 10.3 12.6 14.2 14.6 15.3 0.545 ± 0.170 .01
Engineers 7578 1 821 250 3.8 10.37 9.2 8.8 10.9 8.3 8.6 10.5 10.8 9.6 12.2 15.2 0.389 ±0.179 .06
Architects and surveyors 729 174 141 3.5 8.34 8.3a 14.5a 4.8a 8.7a 4.7a 12.6 8.1a 10.7a 6.0a 9.7a b b
Natural, mathematical/computer scientists 3835 939 904 5.3 10.43 5.8 9.7 9.8 10.0 7.8 9.2 10.1 11.1 15.1 12.3 0.641 ±0.192 .01
Health-diagnosing occupations 2813 664 264 3.4 6.15 2.8 4.1 10.2 4.8 5.9 5.0 4.8 10.1 6.5 7.0 0.335 ±0.224 .17
Health assessment/treating occupations 1349 323 775 8.0 11.03 6.9 4.7 7.8 14.5 10.7 15.9 9.9 16.7 13.1 9.5 0.791 ±0.344 .05
Teachers, librarians, counselors 6904 1 643 367 7.4 12.66 7.9 10.5 12.1 12.1 13.5 12.2 12.9 14.5 12.3 17.8 0.613 ±0.171 .01
Writers, artists, entertainers, athletes 4206 1 032 077 6.5 9.68 8.3 5.7 7.5 10.6 9.0 7.4 12.0 12.2 15.1 8.4 0.593 ±0.265 .06
Other professional specialty occupations 5612 1 332 807 7.9 11.86 8.8 9.9 9.6 10.6 10.4 12.8 12.9 13.9 15.4 13.7 0.719 ±0.094 .00
Health technologists/technicians 1046 257 832 12.6 12.37 9.3a 5.a4 11.7 9.1 6.3a 7.3 17.8 11.7 18.4 16.2 b b
Technologists, technicians (except health) 7621 1 854 827 6.7 11.72 10.1 9.5 9.4 9.9 11.8 11.0 12.1 13.9 13.0 15.3 0.586 ±0.088 .00
Supervisors and proprietors 9661 2 325 275 3.8 13.02 9.9 10.9 10.2 11.5 11.2 15.7 14.5 14.4 14.7 15.8 0.710 ±0.127 .00
Sales representatives, commodities and finance 9883 2 380 853 3.6 12.13 9.9 10.4 11.3 12.3 10.6 9.9 12.9 12.9 15.0 15.9 0.568 ±0.145 .00
Other sales personnel 8391 2 018 715 7.9 12.07 7.1 10.1 9.9 11.6 10.8 12.3 13.5 14.7 13.0 16.3 0.762 ±0.114 .00
Computer equipment operators 920 222 071 12.8 12.53 10.1 9.1 9.8 10.5 13.2 12.3 15.1 16.3 21.0 13.9a b b
Secretaries, stenographers, and typists 340 79 564 16.6 11.01 0.0 8.4a 12.1a 17.3a 7.0a 12.7a 15.7a 4.9a 10.0a 22.0a b b
Financial records processing occupations 889 215 674 8.4 9.81 4.4 7.4 8.8 9.5 10.1 9.4 12.7 11.9 12.7 14.8 0.984 ±0.129 .00
Mail and message distribution personnel 2482 570 995 17.4 11.88 6.6 7.2 12.1 12.4 13.2 12.5 15.0 10.5 13.4 18.2 0.918 ±0.243 .01
Other administrative support personnel 10 893 2 629 800 12.5 13.56 10.4 12.5 9.4 9.4 11.3 13.0 16.2 16.4 16.7 17.5 0.940 ±0.202 .00
Private household occupations 153 34 702 18.6 15.80 24.9a 26.7a 17.0a 1.2a 18.1a 10.2a 17.8a 26.4a 7.3a 16.3a b b
Police and firefighters 4258 1 023 980 12.5 17.70 15.2 13.8 15.6 18.0 13.9 19.3 18.2 18.6 18.7 24.2 0.871 ±0.229 .01
Other protective service occupations 2718 636 439 21.2 19.16 13.7 13.2 19.6 19.6 16.9 21.0 20.8 21.0 23.8 21.7 1.066 ±0.231 .00
Food service personnel 7182 1 719 150 16.1 9.94 7.1 9.1 9.1 9.2 9.4 10.1 10.1 12.4 10.1 12.0 0.384 ±0.093 .00
Health service personnel 896 207000 30.4 16.58 14.3a 18.0 10.3a 17.0a 17.1 16.6 15.8 17.1 20.9 16.8 b b
Cleaning and building service personnel 7421 1 666 428 21.3 14.52 11.9 14.2 11.6 15.0 14.4 14.0 16.1 17.2 14.2 16.3 0.414 ±0.152 .03
Personal service workers 1808 429 701 15.2 9.71 3.3a 9.6 6.3a 8.6 6.2a 5.8a 14.9 10.4 11.5 17.7 0.973 ±0.340 .02
Farm operators and managers 5041 1 110 014 2.0 15.37 11.9 14.2 14.1 14.5 16.1 14.6 15.3 20.9 14.8 20.6 0.620 ±0.214 .02
Farm workers and other agricultural workers 5714 1 288 324 10.5 12.36 10.4 9.0 12.1 11.2 13.8 13.3 12.2 10.4 15.9 14.4 0.490 ±0.192 .03
Forestry and fishing occupations 742 186 114 10.4 15.10 10.7a 12.3a 9.8a 12.0a 12.7a 24.0 16.9 17.6 24.2 13.2a 0.966 ±0.430 .06
Mechanics and repairers 16727 3 953 408 7.5 14.51 12.8 12.6 11.4 14.6 14.2 14.5 14.9 16.6 15.9 18.0 0.601 ±0.108 .00
Construction and extractive trades 20 296 4 815 157 6.9 12.19 10.8 11.5 9.8 10.5 11.3 11.7 14.1 15.8 13.4 13.4 0.517 ±0.142 .01
Precision production occupations 12 183 2 845 536 7.2 14.62 11.7 13.0 12.4 15.0 14.5 14.4 15.1 18.0 16.6 16.2 0.576 ±0.102 .00
Machine operators/tenders (except precision) 13 316 3 094 652 13.2 14.50 10.5 12.4 13.0 13.8 14.8 15.0 15.3 15.7 18.2 16.4 0.671 ±0.085 .00
Fabricators, assemblers, inspectors, samplers 6702 1 557 173 11.6 14.41 11.6 13.7 12.2 13.3 13.2 15.3 15.6 15.5 15.6 18.1 0.568 ±0.103 .00
Motor vehicle operators 13 567 3 136 798 15.3 19.83 17.7 16.2 18.4 18.0 19.6 20.7 19.7 19.5 23.7 24.1 0.713 ±0.140 .00
Other transportation (except motor vehicles) 698 168 742 7.5 18.20 10.8a 11.9a 20.4 18.6 16.0 17.6a 29.3 10.9a 24.7 18.6 b b
Material-moving equipment operators 4396 1 018 823 13.4 19.18 16.8 16.9 16.9 15.6 20.8 18.7 26.1 19.2 21.1 20.7 0.670 ±0.267 .04
Construction laborers 2890 676292 13.5 11.98 9.5 11.6 12.2 11.9 9.3 11.3 13.5 12.3 12.0 15.3 0.378 ±0.162 .05
Freight, stock, material handlers 11 188 2 618 398 16.5 12.46 8.9 10.3 10.5 12.9 12.4 12.5 12.2 13.4 15.4 15.6 0.645 ±0.095 .00
Women
Officials and administrators (public administration) 1040 230 806 12.0 11.54 11.7a 9.3a 13.3 9.2a 5.5a 12.4 11.5 11.3 18.0 10.7 b b
Managers administrators (except public administration) 17 747 4 057 038 6.9 10.26 8.0 9.4 8.0 8.6 10.4 9.7 11.3 11.7 10.2 13.7 0.501 ±0.119 .00
Management-related occupations 9035 2 066 419 9.3 9.24 6.6 7.3 7.1 6.8 8.3 9.0 8.3 12.2 10.9 13.4 0.709 ±0.129 .00
Engineers 694 159 477 7.5 5.75 0.0 2.1a 6.2a 3.1a 8.4a 4.3a 4.0a 9.2a 9.8a 9.9a b b
Architects and surveyors 109 24 678 3.3 1.67a 0.0 6.3a 5.4a 0.0 0.0 0.0 0.0 0.0 0.0 2.6a b b
Natural, mathematical/computer scientists 1830 423 638 8.7 7.85 1.4a 5.5a 11.4 7.2 8.4 6.7 11.3 8.1 6.4 8.8 0.580 ±0.290 .08
Health-diagnosing occupations 735 167 635 6.6 4.27 3.0a 5.4a 4.2a 6.6a 2.8a 4.1a 4.6a 3.7a 4.7a 3.6a b b
Health assessment/treating occupations 9457 2 15 290 9.4 11.57 9.0 8.9 10.4 9.9 9.3 13.0 12.7 13.5 14.9 12.8 0.624 ±0.127 .00
Teachers, librarians, counselors 15 718 3 551 611 9.3 10.33 8.6 7.9 9.6 8.6 8.8 10.4 11.3 12.2 11.4 13.4 0.563 ±0.095 .00
Writers, artists, entertainers, athletes 3999 936 020 4.4 6.59 5.1 4.1 6.5 7.1 6.7 7.5 7.3 5.6 7.0 8.2 0.317 ±0.110 .02
Other professional specialty occupations 3956 882 293 13.6 11.22 9.9 7.8 7.4 10.4 11.0 12.4 11.4 13.5 14.2 11.7 0.674 ±0.159 .00
Health technologists/technicians 5033 1 109 678 14.9 15.10 14.7 13.4 14.5 14.6 12.7 15.7 14.4 14.2 17.3 18.5 0.395 ±0.158 .04
Technologists, technicians (except health) 3559 826 693 8.4 8.71 6.0 6.9 5.4 7.4 7.5 9.3 9.9 10.2 12.4 11.6 0.738 ±0.099 .00
Supervisors and proprietors 5598 1 278 544 6.2 11.78 10.6 8.6 9.9 11.5 12.5 11.5 12.6 12.0 13.3 14.0 0.497 ±0.093 .00
Sales representatives, commodities and finance 5167 1193 821 4.7 6.58 4.5a 3.8 5.9 4.8 5.7 6.5 8.3 8.2 8.6 9.2 0.635 ±0.085 .00
Other sales personnel 16 605 3 796 117 11.0 10.83 8.2 9.6 8.2 9.9 10.0 11.8 11.9 13.1 12.7 13.2 0.594 ±0.084 .00
Computer equipment operators 1810 400 929 14.5 9.99 7.1a 6.5 9.0 9.8 11.3 14.2 10.4 15.4 13.6 4.8a 0.329 ±0.364 .39
Secretaries, stenographers and typists 18 167 4 131 183 8.6 9.58 6.8 6.6 7.7 7.7 9.0 10.7 10.0 12.2 13.8 14.4 0.889 ±0.084 .00
Financial records processing occupations 8563 1 955 437 6.0 11.00 8.2 9.2 9.1 9.0 9.6 11.4 11.7 13.3 14.0 16.7 0.810 ±0.111 .00
Mail and message distribution personnel 1538 328 665 22.5 13.60 7.2a 8.7 15.1 8.7 13.0 16.0 15.1 15.1 23.1 15.9 1.155 ±0.341 .01
Other administrative support 29 669 6 687 733 12.8 11.94 7.5 10.6 9.3 11.6 10.2 11.5 13.0 13.5 15.1 15.1 0.767 ±0.107 .00
Private household occupations 3369 697 123 27.7 18.85 22.0 18.4 17.9 20.4 17.4 18.7 17.1 19.3 20.9 16.0 –0.232 ±0.194 .27
Police and firefighters 628 138 860 26.6 11.41 1.6a 13.3a 10.7a 2.2a 16.6 7.2a 14.2a 14.9a 10.0 16.6 b b
Other protective service occupations 721 159 289 22.3 15.42 6.2a 9.4a 18.4 17.1a 14.1 19.0 16.7 17.6 16.3 16.7 b b
Food service personnel 12 391 2 785 582 11.2 12.85 8.5 11.6 12.4 12.4 11.2 13.0 14.1 14.5 14.8 15.3 0.586 ±0.107 .00
Health service personnel 8292 1 756 092 26.5 20.95 19.7 20.6 17.8 18.8 18.1 21.6 23.4 19.3 25.3 24.4 0.613 ±0.244 .04
Cleaning and building service personnel 5523 1 149 738 26.4 19.70 17.6 18.9 17.8 21.6 15.7 22.3 22.3 18.2 19.8 22.4 0.374 ±0.290 .23
Personal service workers 8514 1 908 222 11.3 13.73 13.3 14.1 11.8 12.3 10.0 14.4 14.1 14.7 16.4 15.3 0.438 ±0.200 .06
Farm operators and managers 1033 221 061 0.9 11.69 5.4a 8.9 9.2 11.9 12.1 16.2 16.8 10.0a 14.5 14.3 0.965 ±0.271 .01
Farm workers and other agricultural workers 1275 283 096 4.7 12.79 8.2a 10.1 8.6 13.0 14.0 8.8 17.8 12.1 20.6 14.4 0.836 ±0.326 .03
Forestry and fishing occupations 31 7307 14.2 15.30a 100.0 0.0 0.0 17.3a 0.0 0.0 23.1a 0.0 48.1a 0.0 b b
Mechanics and repairers 715 159 931 14.1 12.44 8.1a 12.6a 9.4a 13.7a 2.1a 12.8 17.4 17.8 12.6 20.6 1.092 ±0.924 .27
Construction and extractive trades 473 104 398 8.3 10.62 6.4a 6.1a 11.4a 5.4a 10.8a 8.5a 8.1a 28.9a 15.1a 13.2 b b
Precision production occupations 3844 847 349 11.6 14.35 13.7 13.2 11.6 13.5 12.8 13.4 14.6 16.7 17.1 17.4 0.585 ±0.139 .00
Machine operators/tenders (except precision) 9280 2 008 473 17.9 16.39 14.0 14.7 15.2 14.8 15.4 18.0 18.2 18.2 19.7 17.4 0.553 ±0.108 .00
Fabricators, assemblers, inspectors, samplers 4409 964 580 16.0 15.79 11.3 13.0 14.2 15.3 16.2 15.3 16.3 21.4 17.5 18.1 0.784 ±0.163 .00
Motor vehicle operators 1728 376 126 15.4 22.61 21.4 18.3 14.8 20.7 22.1 25.5 24.9 25.2 26.2 25.9 1.196 ±0.287 .00
Other transportation, except motor vehicles 23 5277 17.5 19.91a 0.0 0.0 31.6a 0.0 0.0 0.0 100.0 0.0 0.0 40.7a b b
Material moving equipment operators 255 55 875 18.5 16.54 6.4a 16.3a 13.0a 32.4a 10.8 6.6a 36.5a 13.3a 21.4a 4.1a b b
Construction laborers 88 21 029 18.3 12.81a 11.8a 0.0 32.4a 7.8a 0.0 7.6a 13.0a 0.0 21.3a 31.7a b b
Freight, stock, material handlers 3507 765 254 15.2 14.20 12.8 10.9 15.6 15.1 13.3 14.2 16.0 15.3 14.8 13.9 0.311 ±0.179 .12
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aEstimates have a relative standard error > 30% and should be used with caution, as they do not meet NCHS standards of reliability or precision.31

b Trends were not calculated when the sample size for any individual survey year fell below 45.

TABLE 2—

Pooled and Annual Prevalence Rates of Obesity in 41 Occupational Categories: the National Health Interview Survey, 1997–2002

Annual Prevalence Rate of Obesity
Occupation Sample No. Estimated US Population Percentage Black Overall Prevalence 1997 1998 1999 2000 2001 2002 Slope ±SE P
Men
Officials and administrators (public administration) 335 401 695 12.70 27.79 26.5 25.3 21.1a 18.4a 32.8 38.0 b b
Managers administrators (except public administration) 6005 7 316 851 5.40 22.34 17.4 22.4 25.0 20.3 24.1 24.6 1.152 ±0.556 .11
Management-related occupations 1767 2 114 629 7.20 19.12 16.3 20.3 14.5 22.8 20.9 20.1 0.820 ±0.718 .32
Engineers 1471 1 831 119 4.10 18.18 14.9 15.4 16.2 22.6 16.9 23.4 1.317 ±0.628 .10
Architects and surveyors 158 185 661 4.50 14.54 9.4a 21.1a 11.1a 12.6a 13.6a 14.1a b b
Natural, mathematical/computer scientists 1543 1 794 908 4.90 18.85 18.5 19.1 15.1 15.5 25.1 18.6 0.439 ±0.885 .65
Health-diagnosing occupations 579 745 432 2.20 11.19 7.2a 8.0a 17.1 17.1 8.6a 10.8a 0.642 ±0.851 .49
Health assessment/treating occupations 357 412 753 9.00 22.20 22.3 12.0a 25.6a 23.1 17.4a 31.2 1.360 ±1.668 .46
Teachers, librarians, counselors 1798 2 073 333 8.00 20.37 17.8 20.2 21.6 19.7 21.1 21.4 0.574 ±0.249 .08
Writers, artists, entertainers, athletes 1104 1 202 685 8.00 16.88 12.4 17.5 14.1 18.4 18.1 20.8 1.360 ±0.473 .05
Other professional specialty occupations 1231 1 426 256 9.00 20.72 16.8 23.1 13.5 27.3 18.5 25.8 1.141 ±1.278 .42
Health technologists/technicians 302 358 786 10.90 13.67 15.5a 9.2a 7.6a 23.0a 12.3a 13.0a b b
Technologists, technicians (except health) 1615 1 901 481 7.20 23.29 19.1 21.4 26.4 24.9 19.9 27.8 1.042 ±0.777 .25
Supervisors and proprietors 1871 2 274 531 5.30 21.79 22.2 15.8 24.6 17.5 26.5 23.9 0.912 ±1.039 .43
Sales representatives, commodities and finance 2097 2 570 730 4.50 19.02 18.9 16.7 20.5 22.3 17.7 18.3 0.049 ±0.514 .93
Other sales personnel 1891 2 320 817 9.50 18.67 14.9 18.3 20.6 18.8 17.5 22.1 0.892 ±0.487 .14
Computer equipment operators 155 180 586 13.10 24.94 20.0a 18.5a 28.9a 25.3a 29.9a 33.1a b b
Secretaries, stenographers, and typists 59 59 810 9.70 17.65a 5.6a 7.3a 43.7a 0.0 27.5a 0.0 b b
Financial records processing occupations 200 222 444 18.60 23.10 12.8a 33.1a 23.3a 27.0a 16.5a 24.3a b b
Mail and message distribution personnel 441 505 995 24.10 20.45 20.0 15.8 31.8 9.8 17.6 25.6 0.131 ±2.135 .95
Other administrative support personnel 2593 2 949 184 14.80 22.88 18.9 18.3 25.0 22.2 25.0 27.0 1.677 ±0.463 .02
Private household occupations 26 29 512 34.60 31.32a 0.0 42.8a 0.0 19.5a 47.1a 37.7a b b
Police and firefighters 987 1 186 698 12.80 29.79 22.5 25.7 33.5 31.1 35.4 30.7 2.053 ±0.796 .06
Other protective service occupations 646 696 744 22.50 27.58 21.2 31.0 19.2 27.1 38.5 28.3 1.681 ±1.456 .31
Food service personnel 1825 2 080 815 14.60 18.49 16.2 13.1 23.5 18.4 17.3 22.4 1.205 ±0.843 .23
Health service personnel 247 254 544 33.30 24.61 30.0 23.4a 33.5a 19.7a 24.8 16.7a b b
Cleaning and building service personnel 1507 1 612 197 19.60 22.99 18.0 21.4 22.2 22.6 25.6 27.8 1.751 ±0.218 .00
Personal service workers 418 436 927 17.30 17.14 17.5a 23.8 17.5 15.6a 11.8a 15.5a –1.362 ±0.775 .15
Farm operators and managers 627 764 784 1.00 21.62 14.9 19.9 23.8 26.9 23.1 22.6 1.692 ±0.741 .08
Farm workers and other agricultural workers 1556 1 535 568 6.70 18.72 19.5 17.3 23.6 17.0 19.2 15.2 –0.600 ±0.658 .41
Forestry and fishing occupations 117 134 640 6.00 19.81 16.0a 25.8a 0.0 17.4a 39.8a 20.5a b b
Mechanics and repairers 3626 4 333 134 7.90 22.94 21.1 23.2 21.8 21.5 24.3 25.5 0.701 ±0.275 .06
Construction and extractive trades 4686 5 398 196 7.40 18.45 16.5 16.6 17.9 15.2 21.9 21.9 1.071 ±0.553 .13
Precision production occupations 2223 2 641 979 7.20 25.00 18.7 23.4 25.6 31.0 26.3 25.2 1.628 ±0.773 .10
Machine operators/tenders (except precision) 2605 2 947 586 11.80 23.37 24.2 20.0 25.5 24.9 20.6 25.2 0.024 ±0.662 .97
Fabricators, assemblers, inspectors, samplers 1414 1 690 948 10.90 22.00 21.8 19.5 17.7 24.9 22.4 26.4 0.973 ±0.662 .22
Motor vehicle operators 2989 3 426 058 14.40 31.66 27.9 31.5 29.5 30.9 34.2 35.9 1.391 ±0.347 .02
Other transportation (except motor vehicles) 140 185 361 10.40 28.72 12.2a 30.6a 49.0a 27.0 21.9a 32.3a b b
Material-moving equipment operators 927 1 094 993 12.90 28.24 23.1 27.4 30.4 25.6 32.8 30.1 1.410 ±0.652 .10
Construction laborers 836 897 497 10.80 22.32 22.2 14.5 15.2 25.8 29.2 24.8 1.782 ±1.269 .23
Freight, stock, material handlers 2355 2 815 269 18.00 22.09 19.4 21.6 23.1 15.1 27.0 26.4 1.050 ±1.207 .43
Women
Officials and administrators (public administration) 376 346 463 19.70 21.12 18.0 22.2 21.7 20.1a 25.2 19.5 0.621 ±0.601 .36
Managers administrators (except public administration) 4934 4 797 582 8.50 18.11 17.0 14.9 20.3 17.9 18.4 19.9 0.660 ±0.437 .21
Management-related occupations 2936 2 897 763 11.70 17.78 12.6 15.4 21.7 14.7 18.1 24.1 1.671 ±0.746 .09
Engineers 210 207 259 5.60 12.84 8.5a 12.1a 10.8a 15.6a 17.4a 11.7a b b
Architects and surveyors 39 40 444 2.60 7.29a 0.0 4.0a 0.0 15.6a 27.7a 0.0 b b
Natural, mathematical/computer scientists 799 768 699 9.50 13.30 12.6 10.3 16.5 14.5 12.3 13.8 0.374 ±0.515 .51
Health-diagnosing occupations 283 288 217 6.60 10.25 0.0 10.5a 16.9a 8.2a 10.2a 14.7a b b
Health assessment/treating occupations 2610 2 758 450 9.20 19.83 18.6 20.5 18.8 20.8 21.7 18.6 0.243 ±0.345 .52
Teachers, librarians, counselors 4400 4 477 066 9.40 16.84 15.7 14.4 16.6 16.6 18.9 18.6 0.818 ±0.234 .03
Writers, artists, entertainers, athletes 1117 1 092 478 5.30 13.48 13.2 10.4 17.8 11.2 12.0 16.8 0.451 ±0.683 .55
Other professional specialty occupations 1463 1 362 526 15.60 19.14 15.2 14.1 19.1 16.2 24.9 25.1 2.104 ±0.694 .04
Health technologists/technicians 1391 1 416 593 13.70 23.48 21.4 21.9 23.5 23.3 27.3 22.9 0.638 ±0.427 .21
Technologists, technicians (except health) 838 810 554 9.70 18.04 17.2 20.9 8.7 20.8 19.7 20.8 1.147 ±1.686 .53
Supervisors and proprietors 1421 1 449 510 7.50 19.96 16.4 20.5 17.0 18.2 21.4 25.1 1.390 ±0.546 .06
Sales representatives, commodities and finance 1503 1 483 280 6.00 13.68 9.0 15.9 13.3 15.0 12.8 16.6 1.159 ±0.534 .10
Other sales personnel 3585 3 684 792 12.60 18.24 14.7 19.2 21.0 18.5 19.1 16.7 0.370 ±0.583 .56
Computer equipment operators 236 224 232 15.40 23.76 20.3 19.2a 27.7 49.3 17.3 32.1a b b
Secretaries, stenographers, and typists 2532 2 572 819 8.70 19.63 21.2 17.1 21.6 19.1 17.9 21.3 –0.047 ±0.534 .93
Financial records processing occupations 1768 1 786 692 7.90 20.42 15.0 25.4 18.5 19.8 19.4 24.1 0.963 ±0.857 .32
Mail and message distribution personnel 379 361 468 20.90 17.39 26.3 11.1a 13.9a 17.7 15.4a 20.4 0.480 ±1.407 .75
Other administrative support personnel 7941 7 864 575 14.40 22.46 18.7 23.6 19.8 23.2 23.9 24.9 0.970 ±0.449 .10
Private household occupations 701 578 535 13.20 18.76 0.0 15.6 18.8 23.0 16.9 20.2 b b
Police and firefighters 232 189 198 29.00 15.89 26.0a 4.2a 13.3a 10.1a 26.1a 18.9a b b
Other protective service occupations 256 232 682 27.20 30.45 22.4a 27.3 24.0 33.8 27.1a 47.2 b b
Food service personnel 3030 3 032 388 11.10 20.10 18.5 19.3 22.0 17.8 22.2 20.5 0.437 ±0.407 .34
Health service personnel 2423 2 156 950 27.90 32.43 26.9 26.9 30.4 36.7 35.4 36.6 2.354 ±0.486 .01
Cleaning and building service personnel 1545 1 325 389 21.50 25.25 23.2 26.3 23.2 24.9 26.5 27.6 0.668 ±0.345 .13
Personal service workers 2261 2 167 360 13.90 22.01 18.0 22.4 21.7 24.0 22.8 23.2 0.968 ±0.358 .05
Farm operators and managers 130 147 997 0.00 18.35 11.4a 29.7a 15.5a 25.2a 15.6a 13.1a b b
Farm workers and other agricultural workers 358 344 144 4.40 22.76 14.2a 23.5 24.9a 30.8 22.1 21.7 1.372 ±1.138 .29
Forestry and fishing occupations 7 5 587 43.50 9.32a 0.0 0.0 0.0 32.2a 0.0 0.0 b b
Mechanics and repairers 218 203 532 11.80 20.65 8.9a 6.6a 21.5a 26.4a 25.3a 26.9a b b
Construction and extractive trades 144 152 008 4.50 6.93a 2.1a 3.6a 0.9a 10.7a 10.1a 16.4a b b
Precision production occupations 848 802 569 12.40 23.20 28.2 21.6 22.9 24.5 18.4 24.0 –0.978 ±0.792 .28
Machine operators/tenders (except precision) 1678 1 498 063 17.60 25.14 24.8 23.5 24.2 24.7 25.4 29.1 0.669 ±0.335 .12
Fabricators, assemblers, inspectors, samplers 1045 970 146 16.80 25.30 23.1 21.6 21.0 23.2 32.5 30.7 2.075 ±0.854 .07
Motor vehicle operators 499 472 407 18.20 31.02 15.2 18.1 37.0 33.5 37.3 42.6 5.722 ±1.080 .01
Other transportation (except motor vehicles) 5 2608 76.80 64.08a 0.0 0.0 0.0 100.0 100.0 0.0 b b
Material-moving equipment operators 86 76 818 15.90 29.53 10.4a 22.4a 27.4a 22.8a 41.6a 52.6a b b
Construction laborers 23 19 105 9.10 21.09a 15.1a 14.8a 47.5a 0.0 0.0 20.0a b b
Freight, stock, material handlers 948 905 494 14.10 19.12 15.4 19.5 15.3 22.1 21.7 19.9 1.061 ±0.595 .15
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aEstimates have a relative standard error > 30% and should be used with caution, as they do not meet NCHS standards of reliability or precision.31

b Trends were not calculated when the sample size for any individual survey year fell below 45.

During the period from 1986 to 1995, the highest pooled obesity rates were observed for male workers employed as motor vehicle operators (19.8%), material-moving equipment operators (19.2%), and other protective services employees (19.2%); for female workers, the highest pooled obesity rates were among motor vehicle operators (22.6%), health services workers (21.0%), and cleaning and building services workers (20.0%). Among men, the only occupational group with a pooled obesity prevalence rate below 7% was that of individuals employed in the health-diagnosing occupations (6.2%); female occupations with obesity prevalence rates below 7% included architects and surveyors (1.7%); health-diagnosing occupation employees (4.3%); engineers (5.8%); sales representatives and commodities and finance workers (6.6%); and writers, artists, entertainers, and athletes (6.6%). Irrespective of gender, there were no employed groups that experienced a reduction in obesity rates during this time period. Occupational groups with a significant increase of 1% or greater per year included male workers employed in the other protective service occupations (1.07 ±.23%, P < .001), female motor vehicle operators (1.20 ±.29%, P < .001), and female mail and message distributors (1.16 ±.34%, P < .01).

In the period from 1997 to 2002 (Table 2 ▶), the highest pooled obesity rates were observed for male workers employed as motor vehicle operators (31.7%), police and firefighters (29.8%), other transportation except motor vehicle moving operators (28.7%), and material-moving equipment operators (28.2%); and, for female workers, those employed as motor vehicle operators (31.0%), other protective service workers (30.5%), material-moving equipment operators (29.5%), and cleaning and building service workers (25.3%). In contrast to the earlier survey period, there were no occupational groups among the men with an obesity rate below 11%. Among women, only those employed in the health-diagnosing occupations (10.3%), as architects and surveyors (7.3%), and in the construction and extractive trades (6.9%) had obesity rates below 11%. There were no significant downward trends in obesity rates for any occupational group during the survey period from 1997 to 2002. Obesity rates among male workers employed as police or firefighters had an annual increase of 2.1% (±.8); female workers with annual increases above 2% included motor vehicle operators (5.7 ±1.1); health service workers (2.4 ±.5); other professional specialty occupation employees (2.1 ±.7); and fabricators, assemblers, inspectors, and samplers (2.1 ±.9).

DISCUSSION

Using data from a large, nationally representative sample of US workers, we found that obesity rates were higher for female workers than for male workers within most of the 41 occupational groups. Black female workers were found to have the highest prevalence of obesity relative to “other race” and White workers of both genders. However, it is important to note that over the past decade, obesity rates were rising in all worker groups, irrespective of race and gender. Among the various US working groups, the prevalence of obesity increased almost 10% between the survey years 1986 and 2002. This increasing obesity epidemic poses substantial challenges to the US workforce.

Obesity and its related health conditions directly damage the health and well-being of the current workforce and significantly contribute to long-term chronic disability.32–36 Additionally, the significant increase in the prevalence of obesity among children and adolescents indicates an even greater problem that employers will likely confront within the future workforce.37 Short-term disability claims attributed to obesity have increased 10-fold over the past decade, according to an UnumProvident study that analyzed its extensive disability database.38 Obesity-related disabilities cost employers an average of $8720 per employee every year.38 Designing and implementing worksite weight-loss programs that educate and help employees to achieve and maintain weight loss could substantially reduce the costly health burden on both employers and workers. This effort will not only prevent work-related illness, injury, and disability but also promote healthy lifestyles, which, in turn, will prevent and reduce chronic disease in working-age Americans, many of whom spend 8 to 12 hours per day at work.

Limitations

The NHIS data are cross-sectional data that permit only inferences of association of obesity in the 41 occupations analyzed. However, findings from this study are similar to those of others,33,34 in which the prevalence of obesity has been found to vary according to occupation. Consistent with the present findings, previous research has shown that race/ethnicity, social class, age, and/or sedentary jobs can contribute to an increase in obesity.32,33,37 Furthermore, it is possible that among obese people there exists bias by self-selection of occupation.

Although BMI has been shown, traditionally, to correlate with fat distribution, it must be noted that it does not take into account individuals who may have a large muscular habitus, nor does it directly measure percent body fat. However, most health organizations and scientists support the use of BMI to define overweight and obesity, particularly when direct measures of fat distribution are not available.39–41 Using a 2 or 1 week reference period prior to the NHIS interview to characterize occupational status might lead to misclassification of individuals with respect to their usual occupation. However, ongoing analyses of the NHIS data by the present team of investigators indicate a substantial concordance between self-reported current occupation and longest-held job.42

The present analysis suffers from many of the limitations seen in large population-based studies. Weight and height were collected in a self-reported or proxy fashion, which could have led to less precision in the calculation of the BMI.43,44 For example, previous research has suggested that people tend to underreport their weight and overreport their height, leading to the underestimation of BMI; additionally, the degree of under- and overreporting varies as a function of age, gender, race, ethnicity, and social class.45–47

The 1986 to 1995 NHIS employed proxy information when adults were not available for household interview. Proxy reports of weight and height may also be subject to bias. To reduce this potential bias, we reanalyzed our 1986 to 1995 data in the 61% of NHIS participants who directly reported weight and height during the interview. Results indicate that, for most occupations, the self-reported BMIs would be even higher than the combined proxy and self-reported BMIs. Examining the BMIs for all workers from 1986 to 1995, we found the average annual difference in the percentage of obesity between the nonproxy (self-reported) BMIs and the combined proxy and self-reported BMIs was 0.73%.

Finally, the change in the survey design methodology in 1996 prevented trend comparisons over the total 17-year time period. Moreover, small sample sizes could lead to less reliable estimates of obesity rates and trends in some worker subpopulations (e.g., private household occupations among men, and architects and surveyors among women).

Strengths

Despite the limitations presented, the use of large sample sizes, the nationally representative nature of the sample, oversampling of select subgroups (e.g., Blacks), and the annual assessment useful for assessing trends in prevalence of obesity within occupations allows this study to be favorably compared to other evaluations of the US obesity epidemic.

Irrespective of gender, individuals employed as motor vehicle operators were found to have the highest prevalence of obesity in both time periods. Among men, these pooled prevalence rates increased from 19.8% in the 1986 to 1995 survey period to 31.7% in the 1997 to 2002 survey period; corresponding rates for women were 22.6% and 31.0%, respectively. Developing weight-loss programs designed to take into account the job demands, physical demands, and even the socioeconomic and cultural backgrounds of motor vehicle operators could potentially help reduce this detrimental increase in obesity within this occupational group. Furthermore, examining occupations with a lower prevalence of obesity (such as female architects and surveyors or men employed in the health-diagnosing professions) could help researchers elucidate the relationship between occupation and optimal body weight.

Conclusions

The behavioral effects of physical activity on health are well established.48–51 Although the most promising weight-loss interventions focus on increasing physical activity in addition to implementing dietary changes, the increasing trend towards automation and other labor-saving strategies found at many work-sites will not foster physical activity conducive to weight loss. Primary and secondary prevention of obesity in occupational settings must therefore take into account the many societal and occupational factors that influence energy imbalance via multifaceted interventions (e.g., accountability of healthy food choices and food quantity, exercise programs). Such comprehensive, worksite-based interventions are urgently needed in order to slow the growing epidemic of obesity in the United States.

Acknowledgments

This study was funded in part through the National Institute of Occupational Safety and Health (NIOSH) (grant R01 OH003915).

Findings from this study were presented at the Annual Education Conference in 2004 of the Florida Public Health Association, Orlando, Florida, July 28, 2004; the Centers for Disease Control (CDC)/NIOSH conference “Steps to a Healthier US Workforce,” October 26–28, 2004; Washington, DC, Cafritz Conference Center; and at the 132nd Annual Meeting of the American Public Health Association in Washington, DC, November 8, 2004.

The data used in this article were made available in part by the Inter-University Consortium for Political and Social Research. The data for the National Health Interview Survey (NHIS) were originally collected and prepared by the US Department of Health and Human Services and the National Center for Health Statistics.

Note. Neither the collector of the original data nor the Inter-University Consortium for Political and Social Research bears any responsibility for the analyses or interpretations presented in this article.

Human Participant Protection…Because this study utilized anonymous data from a publicly available database, the protocol was reviewed and approved for exemption by the institutional review board of the University of Miami School of Medicine.

Peer Reviewed

Contributors…A. J. Caban, L. E. Fleming, and D. J. Lee originated the study and led the writing of this article. W. LeBlanc and O. Gómez-Marín managed the data and performed statistical analyses. T. Pitman provided study support and data management. All authors helped conceptualize ideas, interpret findings, and provide critical review of the article.

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