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The Health of Young US Workers Manuel A. Ocasio, MSPH, Lora E. Fleming, MD, PhD, Julie Hollenbeck, MA, Cristina A. Fernandez, MSEd, William G. LeBlanc, PhD, Jenelle Lin, MSPH, Alberto J. Caban Martinez, DO, PhD, Diana Kachan, PhD, Sharon L. Christ, PhD, John P. Sestito, JD, and David J. Lee, PhD Objectives: To provide an overview of the health status of young US workers across four domains: functional health, physical and psychological health, health behavior, and health care utilization. Methods: Pooled data from the 2004 to 2010 National Health Interview Survey were analyzed for 11,279 US workers aged 18 to 24 years, representing an estimated 16.9 million workers annually. Thirty-nine health indicators were examined and compared across nine occupational groups. Results: Compared with other occupational groups, craft workers and laborers and helpers had the highest prevalence of risky health behaviors, including current smoking and risky drinking, as well as fewer reported visits to a primary care physician in the past year. Conclusions: Young workers engage in risky health behaviors, and may benefit from targeted workplace interventions to mitigate the potentially negative long-term effects on health and well-being.

Y

oung workers (≤24 years) are a large and relatively unstudied population in the United States.1 Yet, by the time they finish high school, 80% of US youth (approximately 8 million people) will have worked in some capacity, constituting the highest proportion of young workers in any developed nation.2 Over a third of US high school students report working during the school year, and an even greater proportion report working during the summer.3 Specifically, youth labor force participation peaks in July, in which there were From the Department of Public Health Sciences (Mr Ocasio, Ms Fernandez, Dr LeBlanc, Ms Lin, Dr Caban Martinez, Dr Kachan, and Dr Lee), University of Miami Miller School of Medicine, Fla; European Centre for Environment and Human Health (Dr Fleming and Ms Hollenbeck), University of Exeter Medical School, Truro, Cornwall, UK; Environmental and Occupational Medicine and Epidemiology Program (Dr Caban Martinez), Department of Environmental Health, Harvard University, School of Public Health, Boston, Mass; Department of Human Development and Family Studies (Dr Christ), Purdue University, West Lafayette, Ind; and National Institute for Occupational Safety and Health (Mr Sestito), Division of Surveillance, Health Evaluations and Field Studies, Cincinnati, Ohio. This study was funded in part through the NIOSH Grant number R01 0H003915. Funding was also provided to the European Centre for Environment and Human Health at the University of Exeter Medical School through the European Union Convergence Program (European Regional Development Fund and European Social Fund), National Institute on Aging grant #F30AG040886 (Trainee: Kachan), and from the National Institute of Arthritis and Musculoskeletal and Skin Diseases grant T32 AR055885 (PI: Katz) to the Clinical Orthopedic and Musculoskeletal Education and Training Program at Brigham and Women’s Hospital, Harvard Medical School and Harvard School of Public Health (Trainee: Caban-Martinez). The data for the NHIS were originally collected and prepared by the US Department of Health and Human Services and the National Center for Health Statistics. The collector of the original data bears no responsibility for the analyses or interpretations presented in this publication. Additional information on this study can be found at the Study Websites located at http://www.umiamiorg.com and www.flye.co. Authors Ocasio, Fleming, Hollenbeck, Fernandez, LeBlanc, Lin, Caban Martinez, Kachan, Christ, Sestito, and Lee have no relationships/conditions/ circumstances that present potential conflict of interest. The JOEM editorial board and planners have no financial interest related to this research. Address correspondence to: Manuel A. Ocasio, MSPH, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Clinical Research Building, Rm 1075, 1120 N.W. 14th St, 10th Floor (R-669), Miami, FL 33136 ([email protected]). C 2014 by American College of Occupational and Environmental Copyright  Medicine DOI: 10.1097/JOM.0000000000000256

Learning Objectives

r Become familiar with previous data on the “tangible and r r

intangible benefits,” as well as the risks, of employment for young adults. Summarize the findings of the overview of health status among young US workers across nine occupational categories, including the groups at higher risk in four health domains. Identify some possible approaches to mitigating the potentially negative long-term effects of occupational health risks for young workers.

approximately 20 million employed youths in July 2013.4 Roughly 8% of young workers in the United States are employed in the agriculture industry, whereas the vast majority are employed in the retail (>50%) and service (25%) sectors.2,5 Research to date suggests that young adult employment comes with benefits and risks, both in the short and long terms. Employment can provide youth with a range of tangible and intangible benefits, particularly now that the majority of US youth do not work solely to provide income for the family.5,6 Even part-time work can teach youth valuable lessons (such as responsibility and independence), as well as provide real-work experience, life skills, and increased selfesteem.2,5 Furthermore, research has shown that young workers may attain higher employment rates and better wages as long as a decade after high school graduation.6,7 At the same time, young workers are at increased risk for injury, illness, and death compared with all other workers.2,5,6,8,9 As their working hours increase, young workers are more likely to engage in risky personal behaviors (such as smoking and drug use and decreased physical activity and sleep), be less likely to participate in extracurricular school activities, spend less time with their family (unless working in a family business), have difficulties at school, and engage in illegal activities.2,6 In addition, the likelihood of enrolling and graduating from college was significantly reduced the more hours an individual had worked while in high school. This inverse effect persisted even 10 years after completing high school.6 Using the 2004 to 2010 National Health Interview Survey (NHIS), a nationally representative surveillance tool, we explored various aspects of functional health, physical and psychological health, health behavior, and health care utilization of young workers aged 18 to 24 years, with a focus on the role of occupation type on the health and well-being of young workers.

METHODS Data Source The NHIS is a continuous, self-reported survey that utilizes a multistage area probability design to obtain a representative sample of the US civilian noninstitutionalized population living at addressed dwellings.10–13 The NHIS collects key health information from a single randomly selected adult household member. For the pooled 2004 to 2010 NHIS, there were 242,487 adult participants (aged ≥18 years) currently employed at the time of the NHIS interview,

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of which 11,279 were aged 18 to 24 years. Annual response rates to the 2004 to 2010 adult core ranged from 61% (in 2010) to 73% (in 2004).14

Key 2004 to 2010 NHIS Measures In Table 1, we list the 39 functional health, physical and psychological health, health behavior, and health care utilization measures assessed consistently by the NHIS from 2004 to 2010 and included in our analyses. These variables include demographic information, measures of morbidity and well-being in terms of functional health (including physical, mental, and social limitations) and physical health (including chronic health conditions), other measures of health (including self-rated health and use of health services), and health behaviors (including alcohol and smoking, physical activity, and use of preventive vaccinations). Many of these measures have also been included in other studies published by our research group (www.umiamiorg.com), allowing for comparisons between industry sectors, older age groups, and other pooled years of data.

Employment and Occupation Employment is defined in the NHIS as having worked during the week before the interview, and is assessed of all NHIS participants aged 18 years and more. This definition includes both paid and unpaid work. The NHIS employs US Census Occupational and Industrial Codes to classify workers.15 From 2004 forward, the NHIS used the 2000 US Census SOC Codes to create 93 occupational subgroups, which were collapsed to nine broad occupational categories (Table 2). A detailed listing of these occupations can be found at the US Census Web site (http://www.census.gov/ hhes/www/eeoindex/jobgroups.pdf ). We have created a “crosswalk” demonstrating how each of the 93 more detailed NHIS occupational codes was mapped onto the nine census occupational groupings (see http://umiamiorg.com/publications/monographs.html). Table 2 also provides examples of select NHIS detailed occupations that are classified under each of the broad occupational groups.

Statistical Methods Because of the complex sampling design of the NHIS, all analyses were performed with adjustment for design effects (including

sample-weighted estimates and standard error estimates) using the SUDAAN 10.0 and SAS 9.2 statistical packages.16,17 These analyses also took into account relatively minor sample design modifications implemented in 2006 because of smaller sample size recruitment targets.18 The sample weights used were those required for the analysis of data from combined survey years, and were calculated as originally specified by Botman and currently recommended by the National Center for Health Statistics.11,18 Sample weights were also used to estimate the number of young adult workers in the United States with various health conditions. In some cases, these values were underestimated because of either (1) the presence of missing data for the condition of interest (eg, respondents did not answer a health indicator question), or (2) in the case of stratified analyses, values were missing for the stratification variable (eg, educational attainment). Missing data were handled using list-wise deletion.

RESULTS Weighted prevalence estimates for functional health, physical and psychological health, health behavior, and health care utilization measures during the study period 2004 to 2010 for all US workers aged 18 to 24 years are summarized below. The data for the 39 functional health, physical and psychological health, health behavior, and health care utilization measures are presented in tabular format for all US workers, and then for each of the nine occupational groups can be accessed at URL: http://umiamiorg.com/publications/ monographs.html. A complete description, including detailed operational definitions, for each of the indicators can be found in Appendix 2 (page 78) of the Young Worker Monograph located at that URL. Within each table, these data are shown for all workers of the particular subpopulation, and then by sex, race, ethnicity, education, and health insurance status within that subpopulation; each table also gives the NHIS sample size and the estimated annual US worker population by each of these subcategories. Table 3 provides prevalence estimates for sociodemographic characteristics for all workers and each of the nine occupational groups. From 2004 to 2010, 11,279 US workers aged 18 to 24 years (representing an estimated 16,909,733 US young workers annually) completed the NHIS survey and were included in the probability sampling of the entire noninstitutionalized US population (see

TABLE 1. List of Health Indicators From the National Health Interview Survey Asked Consistently Across Survey Years 2004 to 2010* Functional Health

Medical and Physical Health

• Use of special equipment • Any functional limitations • Hearing impairment • Visual impairment • Use of special equipment

• Body mass index • Cancer • Hypertension • Heart disease • Asthma • Severe psychological distress • Diabetes • Chronic bronchitis • Sinusitis • Hay fever • Non-HIV STD • Hepatitis

Health Behavior • Smoking • Risky drinking • Leisure-time physical activity • Average hours sleep • Influenza vaccine • HIV/AIDS test • AIDS risk • Perceived HIV risk • Hepatitis B vaccination

Health Care Utilization • Health compared to last year • Self-rated health • Seen primary care provider • Seen dentist • Seen mental health provider • Seen chiropractor • Surgery • Seen eye doctor • Place for routine care • Needing but not affording care • Delaying care because of cost • Emergency department visit • Bed days • Lost workdays

*A detailed description of all indicators can be found at URL: http://umiamiorg.com/publications/monographs.html. STD, sexually transmitted disease.

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TABLE 2. 2000 US Census Standard Occupational Classification System Codes* and Examples of National Health Interview Survey Occupations Categorized Within Each Group EEO-1 Job Codes

EEO-1 Job Categories and Titles for the Census 2000 Special EEO File

01

Officials and managers

02 03 04 05 06

Professionals Technicians Sales workers Administrative support workers Craft workers

07

Operatives

08

Laborers and helpers

09

Service workers

Select NHIS Detailed Occupations Advertising, marketing, promotions, public relations, and sales managers Engineers, and postsecondary teachers Life, physical, and social science technicians Retail sales workers and sales representatives Legal support workers and financial clerks Extraction workers, vehicle and mobile equipment mechanics, installers, and repairers Food processing workers and motor vehicle operators Agricultural workers and construction trades workers Grounds maintenance workers, building cleaning, and pest control workers

*Crosswalk for the detailed NHIS occupations mapped to the EEO-1 job categories can be found at URL: http://umiamiorg.com/publications/monographs.html. NHIS, National Health Interview Survey.

overall demographics, Table 3). There were approximately equal numbers of young men (49.0%) and women (50.1%) working during this period. The majority of the young workers self-identified as white (78.3%), 15.8% identified as black, and 6.0% identified as “other” race. Approximately one quarter of the sample (24.6%) were Hispanic. The majority (56.7%) of young workers had more than a high school education, with 14.7% having less than a high school education and 28.3% who had completed high school only. Finally, 32.5% reported not having health insurance at the time of interview. The sociodemographic composition of young workers across occupational groups varied considerably. For example, there was a 23-fold variation among the occupations in the prevalence of female workers, administrative support occupations (67.2%) having the highest proportion of female workers. This means that there were 23 times more female workers in administrative support occupations compared with those in craft worker occupations (2.9%), which had the lowest proportion of females among all occupational groups. There was a 27-fold variation in the prevalence of having less than a high school education, with the highest prevalence found in laborer and helper occupations (41.2%). There was over a fourfold variation among the occupations in the prevalence of Hispanic workers, with the highest prevalence found in laborer and helper occupations (47.9%); in addition, an almost fivefold variation in the prevalence of black workers, with the largest prevalence in administrative support occupations (21.2%). An almost twofold variation among the occupations existed in the prevalence of insured workers across occupations, with the lowest prevalence in laborers and helpers (57.3%) and craft workers (52.6%).

Functional Health More than 6% (prevalence, 6.1%; 95% confidence interval, 5.5 to 6.7) of all young workers aged 18 to 24 years reported any functional limitations. Laborers and helpers experienced the highest prevalence of any functional limitation (6.9%; 4.1 to 11.3), whereas craft workers experienced the lowest (4.6%; 3.3 to 6.4). “Any functional limitation” was defined as having responded “yes” to any of the 12 NHIS activity limitation items, which includes having difficulty walking 1/4 mile without special equipment, reaching up over head without special equipment, and attending events without special equipment. Although special equipment utilization was uncommon

among young workers as a whole (0.5%; 0.4 to 0.7), technicians (0.9%; 0.1 to 6.3) and operatives (0.9%; 0.4 to 1.8) reported the highest overall prevalence of needing special equipment, whereas no workers in laborers and helpers occupations reported need for special equipment. Among all young workers, less than 6% (5.5%; 5.0 to 6.0) reported any hearing impairment (defined as a little trouble, a lot of trouble, or deaf). There was almost a threefold difference in prevalence of any reported hearing impairment across the occupational groups; craft workers (6.7%; 4.9 to 9.1) and operatives (6.6%; 5.1 to 8.4) workers reported markedly higher prevalence of hearing loss compared with technicians (2.9%; 1.3 to 6.2). There was an overall reported visual impairment prevalence of 5.5% (5.0 to 6.1) among all young workers; sales workers experienced the highest overall prevalence of self-reported current visual impairment (6.8%; 5.4 to 8.4), and laborers and helpers reported the lowest (3.2%; 1.8 to 5.5).

Physical and Psychological Health Among young workers, laborers and helpers reported the highest overall prevalence of fair/poor health (4.6%; 2.6 to 7.9), and professionals reported the lowest (1.0%; 0.6 to 1.7). Service workers experienced the highest prevalence of worse health in the previous year compared with their present health (4.8%; 3.9 to 5.9), whereas laborers and helpers experienced the lowest prevalence of this change (2.5%; 1.4 to 4.5). Officials and managers experienced the highest overall prevalence of ever having a diagnosis of asthma (16.3%; 12.9 to 20.3), and laborers and helpers had the lowest (9.7%; 6.4 to 14.5). Professionals reported the highest prevalence of chronic bronchitis (3.4%; 2.3 to 5.1). Technicians reported the lowest prevalence (0.5%; 0.1 to 2.6) of chronic bronchitis and the highest prevalence of both sinusitis (12.7%; 7.5 to 20.7) and hay fever (7.0%; 3.0 to 15.4). Craft workers experienced the lowest prevalence of sinusitis (3.4%; 2.0 to 5.6) and hay fever (2.9%; 1.7 to 4.9). Operatives had the highest overall prevalence of being obese, defined as having a body mass index greater than or equal to 30 (21.0%; 18.0 to 24.3), ever having a diagnosis of diabetes (1.7%; 0.9 to 3.2) and hypertension (6.8%; 5.3 to 8.8). Officials and managers had the lowest prevalence of obesity (10.6%; 8.1 to 13.8), and craft workers experienced the lowest prevalence of diabetes

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All occupations US estimated 16,909,733 population NHIS, N 11,279 Prevalence (row %) 100.00 Officials and managers US estimated 863,934 population NHIS, N 625 Prevalence (row %) 5.54 Professionals US estimated 1,685,081 population NHIS, N 1,239 Prevalence (row %) 10.99 Technicians US estimated 410,713 population NHIS, N 263 Prevalence (row %) 2.33 Sales workers US estimated 2,771,115 population NHIS, N 1,793 Prevalence (row %) 15.90 Administrative support workers US estimated 2,705,992 population NHIS, N 1,846 Prevalence (row %) 16.37

Overall Total

8,118,152 5,751 50.99 444,808 326 52.16 1,002,850 751 60.61 232,318 151 57.41 1,605,879 1,124 62.69 1,706,788 1,241 67.23

5,528 49.01

419,126

299 47.84

682,231

488 39.39

178,395

112 42.59

1,165,237

669 37.31

999,204

605 32.77

Female

8,791,581

Male

Sex

1,349 73.08

2,064,910

1,334 74.40

2,189,148

212 80.61

356,933

938 75.71

1,367,074

478 76.60

694,176

8,826 78.25

13,858,509

White

392 21.24

483,637

352 19.63

425,133

36 13.69

38,318

148 11.95

175,819

92 14.74

106,446

1,779 15.77

2,201,915

Black

Race

105 5.69

157,446

107 5.97

156,834

15 5.70

15,462

153 12.35

142,188

54 8.65

63,312

674 5.98

849,308

Other

1,446 78.33

2,297,752

1,397 77.91

2,356,586

232 88.21

372,933

1,077 86.92

1,538,463

545 87.20

784,371

8,506 75.41

13,989,604

NonHispanic

400 21.67

408,240

396 22.09

414,529

31 11.79

37,780

162 13.08

146,619

80 12.80

79,563

2,773 24.59

2,920,128

Hispanic

Ethnicity

125 6.78

182,435

224 12.50

341,268

4 1.53

13,411

28 2.27

40,288

33 5.28

43,617

1,654 14.71

2,343,370

Less Than High School

505 27.39

752,041

543 30.30

848,555

45 17.18

70,868

102 8.25

140,840

107 17.12

157,699

3,197 28.44

5,062,500

High School

Education

1,214 65.84

1,769,940

1,025 57.20

1,579,246

213 81.30

324,072

1,106 89.48

1,501,204

485 77.60

662,617

6,392 56.85

9,453,140

More Than High School

1,415 77.15

2,114,937

1,208 68.06

1,942,277

216 83.40

339,699

1,032 83.50

1,411,371

505 81.19

695,040

7,550 67.35

11,621,682

Insured

419 22.85 (Continues)

566,501

567 31.94

799,912

43 16.60

64,635

204 16.50

269,985

117 18.81

161,781

3,660 32.65

5,161,152

Not Insured

Insurance

TABLE 3. Weighted Prevalence Estimates of Sociodemographic Characteristics for Young US Workers Aged 18 to 24 Years, 2004 to 2010 National Health Interview Survey

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1,497,681

950 97.14

1,514,052

954 75.96

461,504

288 81.59

978 8.67

1,956,453

1,256 11.14

559,068

353 3.13

Male

Sex

1,525,175

NHIS, National Health Interview Survey.

Craft workers US estimated population NHIS, N Prevalence (row %) Operatives US estimated population NHIS, N Prevalence (row %) Laborers and helpers US estimated population NHIS, N Prevalence (row %)

Overall Total

TABLE 3. (Continued)

65 18.41

97,563

302 24.04

442,401

28 2.86

27,494

Female

327 92.63

524,596

1,022 81.37

1,633,204

897 91.72

1,405,595

White

16 4.53

22,974

181 14.41

247,625

56 5.73

85,979

Black

Race

10 2.83

11,498

53 4.22

75,623

25 2.56

33,601

Other

184 52.12

376,714

870 69.27

1,543,981

553 56.54

1,060,879

NonHispanic

169 47.88

182,353

386 30.73

412,472

425 43.46

464,296

Hispanic

Ethnicity

143 41.21

164,179

282 22.51

377,972

310 32.02

430,774

Less Than High School

105 30.26

207,574

518 41.34

842,364

410 42.36

664,604

High School

Education

99 28.53

176,885

453 36.15

731,998

248 25.62

413,853

More Than High School

150 42.74

280,334

772 61.81

1,276,634

463 47.44

799,702

Insured

201 57.26

276,486

477 38.19

669,544

513 52.56

724,471

Not Insured

Insurance

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(0.3%; 0.1 to 0.8) and hypertension (3.0%; 2.0 to 4.4). There was an overall prevalence of 3.3% (2.8 to 3.7) of ever having a diagnosis of any kind of heart disease among all young workers; service workers experienced the highest prevalence of heart disease (4.1%; 3.3 to 5.3), and laborers and helpers the lowest (1.9%; 0.9 to 4.2). Among all occupational groups, there was a low prevalence of ever having cancer (0.8%; 0.7 to 1.0), with craft workers reporting the lowest prevalence (0.2%; 0.1 to 1.1) and technicians the highest (1.5%; 0.6 to 3.8). Laborers and helpers reported the highest prevalence of hepatitis (1.4%; 0.5 to 4.0), and officials and managers the lowest (0.4%; 0.1 to 1.0). Officials and managers reported the highest prevalence of having a non-HIV sexually transmitted disease (5.8%; 3.3 to 10.1), and laborers and helpers the lowest prevalence (2.4%; 1.0 to 5.7). The prevalence of severe psychological distress (on the basis of scores from the K6 scale) in the previous 30 days was very low among young workers (0.4%; 0.3 to 0.6). Craft workers reported the highest overall prevalence of severe psychological distress (0.7%; 0.2 to 2.1), whereas workers in laborer and helper and technician occupations did not report any psychological distress.

Health Behavior Among young workers, craft workers reported the highest overall smoking prevalence (36.4%; 32.2 to 40.7), and professionals reported the lowest (12.3%; 10.3 to 14.5). Officials and managers had the highest overall prevalence of risky (defined as either a binge and/or heavy drinking) alcohol drinking (44.9%; 39.6 to 50.3), whereas administrative support workers had the lowest (30.7%; 28.2 to 33.4). Professionals reported the highest overall prevalence of having met the Centers for Disease Control and Preventionrecommended definition of healthy leisure-time physical activity (50.7%; 47.0 to 54.4),19 and young adult workers employed as operatives had the lowest (32.3%; 29.0 to 35.7). Laborers and helpers experienced the highest overall mean hours of sleep within a 24-hour period (7.4 hours; 7.3 to 7.6), whereas technicians had the lowest (7.0 hours; 6.9 to 7.2). Technicians reported the highest overall prevalence of having received a flu shot in the past 12 months (30.6%; 23.0 to 39.5) and having ever received a hepatitis B vaccine (71.5%; 64.1 to 78.0), whereas laborers and helpers had the lowest prevalence of flu vaccination in the previous year (5.8%; 3.5 to 9.4), and craft workers had the lowest prevalence of hepatitis B vaccination (35.6%; 31.2 to 40.3). Officials and managers had the highest overall prevalence of having ever been tested for HIV (36.6%; 31.8 to 41.6). Laborers and helpers had the lowest reported prevalence of lifetime HIV testing (22.4%; 17.3 to 28.4) and of having at least one risk factor for AIDS (1.1%; 0.3 to 4.1), such as having traded sex for money or drugs. Sales workers (4.6%; 3.4 to 6.2) and craft workers (4.6%; 2.9 to 7.1) reported the highest overall prevalence of having at least one risk factor for AIDS. Administrative support workers had the highest overall prevalence of reporting no self-perceived chances (compared with high, medium, or low) of getting HIV (71.1%; 68.5 to 73.7), and technicians had the lowest (62.1%; 53.6 to 69.8).

Health Care Utilization Among young workers, those employed as professional workers reported the highest overall prevalence of seeing or talking to a primary care provider in the past year (69.7%; 66.2 to 72.9) and craft workers reported the lowest (36.0%; 32.0 to 40.2). Craft workers also reported the lowest prevalence of seeking routine or preventive care at a health center, doctor’s office, Health Maintenance Organization (HMO), or hospital outpatient facility (50.8%; 46.44 to 55.15), whereas administrative support workers experienced the 1016

highest prevalence of seeking care at these sites (71.6%; 68.98 to 74.11). Officials and managers reported the highest prevalence of seeing or talking to a mental health care provider in the past 12 months (8.5%; 5.5 to 13.0), and craft workers reported the lowest (2.0%; 1.2 to 3.2). Craft workers reported the lowest prevalence of having visited a dentist within the past year (41.7%; 37.8 to 45.8); likewise, the same group of young adults had not visited an eye doctor in the past 12 months (13.9%; 11.3 to 17.1). Professionals reported the highest prevalence of having seen a dentist within the past year (66.8%; 63.3 to 70.2), and officials and managers had the highest prevalence of having seen an eye doctor within the past year (36.1%; 31.4 to 41.1). Technicians reported the highest prevalence of seeing or talking to a chiropractor in the past 12 months (9.3%; 5.4 to 15.6), and officials and managers had the lowest (5.1%; 3.3 to 7.7). Officials and managers reported the highest overall prevalence of having had surgery in the past year (9.9%; 7.3 to 13.2), and craft workers reported the lowest (6.9%; 5.1 to 9.2). Service workers experienced the highest overall prevalence of having had at least one emergency department visit (27.4%; 25.4 to 29.5) in the past 12 months, and professionals had the lowest (17.5%; 15.1 to 20.2). Professionals experienced the highest prevalence of two or more bed disability days because of injury or illness in the past 12 months (ie, days in bed for half a day or longer because of illness or injury; 29.2%; 26.3 to 32.3), and craft workers had the lowest (19.6%; 16.4 to 23.3). Craft workers experienced the highest prevalence of six or more workdays lost because of injury or illness in the past 12 months (10.4%; 8.1 to 13.3), whereas laborers and helpers experienced the lowest (7.4%; 4.9 to 11.1). Service workers reported the highest prevalence of not getting medical care because of the cost in the past 12 months (23.8%; 21.9 to 25.8), and professionals reported the lowest (16.0%; 13.7 to 18.4). Service workers experienced the highest prevalence of delaying medical care because of the cost in the past 12 months (11.1%; 9.8 to 12.7), and laborers and helpers had the lowest (6.0%; 3.7 to 9.4).

DISCUSSION Overall, young US workers are healthy and report relatively low burdens of acute and chronic diseases (eg, cancer and heart diseases) and current functional disability compared with other age groups and the general US population.20–25 Nevertheless, they also have a high prevalence of risky behaviors (eg, risky drinking and smoking) and receive relatively little preventive health (eg, influenza vaccination, HIV testing, and regular doctor/dentist visits). Furthermore, these indicators are not evenly distributed in the young worker population, varying substantially by occupation, sex, race, ethnicity, and education. For example, the prevalence of current smoking in this study is similar to that seen in US adults aged 25 to 44 years (24% vs 22%)26 ; however, when examining occupational groups, young craft workers (36%) and operatives (32%) have a substantially higher prevalence than other young workers. In addition, influenza vaccination coverage in the previous 12 months in the general US adult population ranges from 33% to 38%27 compared with a considerably lower prevalence among young workers (14%), and more specifically, among craft workers (9%) and laborers and helpers (6%). Many of these behaviors may be risk factors for future chronic disease and disability, leading to decreased quality of life and increased health care utilization. Intervention programs delivered in the workplace can potentially provide education and resources for addressing these risky behaviors and health conditions, as well as better access to preventive health (eg, influenza vaccines); these programs can be targeted at the higher risk subpopulations identified among the larger population of young workers (eg, smoking cessation for craft workers). In addition, the Affordable Care Act should result in

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the addition of large numbers of newly insured young adult workers by 2016.28 Therefore, campaigns targeting these young workers may be particularly effective in introducing them to the benefits of routine preventive care. Comparing the nine occupational categories among workers 18 to 24 years of age, there are clear and significant differences in functional health, physical and psychological health, health behavior, and health care utilization among the different occupations. In particular, as well as risky health behaviors, the laborers and helpers and craft workers reported the highest prevalence of physical and psychological issues. Furthermore, these same workers were less likely to report the use of preventive medical care such as seeing a physician, dentist, or mental health worker. This was most likely associated in part with their significant lack of health insurance. Although these health indicators are not classic occupationassociated conditions (eg, specific toxic exposures in the workplace leading to particular associated health effects), this combination of high physical and psychological morbidity with poor health behaviors and health care access could be characterized as a “work-related condition.” This situation arises at least in part from the clustering of sociodemographic and health factors associated with certain occupations. For example, blue-collar occupations with low wages and lack of health insurance are strongly associated with socioeconomically and educationally deprived individuals and communities.21,29 Thus, the workplace becomes part of the “milieu” or the larger environment and life course of the worker, as noted by the National Institute for Occupational Safety and Health (NIOSH) Total Worker HealthTM initiative.30 This, in turn, has important implications for identifying at-risk individuals and communities where prevention and treatment programs can potentially be targeted through the workplace.

Strengths and Limitations The cross-sectional survey design of the NHIS does not allow for causal inference. Because of the self-reporting nature of the NHIS, there is considerable potential for both under- and overreporting. For example, weight and height were collected in a selfreported or proxy fashion, which could have led to less precision in the calculation of body mass index. Previous research has suggested that people tend to underreport their weight and overreport their height; this would lead to an underestimation. It is also important to note that the degree to which these values are underand overreported can vary considerably by a number of sociodemographic characteristics, such as age, sex, race, ethnicity, and social class.29,31–33 We have used the NHIS data to provide a broad descriptive overview of a range of health and well-being characteristics of US young adult workers; there are potential interactions between these variables, which we have not explored. However, these data are available for use by researchers for further exploration and analysis (www.umiamiorg.com). Small sample sizes are also of concern in certain cases. There are a total of 93 occupational categories available in the NHIS, which were further condensed to nine broad occupational groups. Whereas occupations that are grouped within the larger census groupings share many characteristics, there may be within-group differences that we were unable to capture in our analyses. The NHIS defines employment status within the last week of the survey interview. This may lead to exclusion of youth who engage in seasonal work, such as those who work only during the summer vacation from school but were interviewed during another time of year. We were also unable to capture occupation information on youths below the age of 18 years or on jobs that are informal and not part of the standard occupational classification (eg, babysitting). Some of the occupational groups, particularly technicians and laborers and helpers, have relatively few workers (n = 263 and n = 353, respectively); therefore, it may be

The Health of Young US Workers

inappropriate to draw strong conclusions on these groups, particularly when stratified by the different sociodemographic subgroups. In addition, young individuals tend to be healthy overall and certain health conditions are rare in this age group (ie, cancer), thus likely to produce unreliable estimates. Despite these limitations, this study was based on a representative sample of the US civilian population. We were also able to observe a range of health-related factors that can be used as a baseline to evaluate future trends in young worker health in the United States.

CONCLUSIONS This study employed recent nationally representative data and demonstrated varying degrees of disability and morbidity across nine occupational groups for workers aged 18 to 24 years. The NHIS data are unique in providing reported functional health, physical and psychological health, health behavior, and health care utilization among certain demographic subpopulations and occupational groups for the entire US civilian non-institutionalized population. Although these data do not directly reflect traditional occupational exposures, these conditions and behaviors form the backdrop to the health of US workers and their families, as well as providing important information on evolving health trends. As the NIOSH Total Worker HealthTM initiative aims to improve worker health via the integration of health promotion and improvements in workplace safety,34 results from this study may provide additional insight and baseline for targeting and evaluating efforts among the US young worker population. Traditionally, young workers are a high-risk group, often neglected in occupational health surveillance, as noted by a series of symposia recently held to address issues relating to the health and safety of young workers.35 With regard to particular at-risk occupational groups, these NHIS data indicate that craft workers and laborers and helpers may be particularly at increased risk for illness and disability in the future, potentially because of the lack of access to health care and current high-risk behaviors such as smoking. The introduction of health prevention programs in the workplace targeted at particular worker and industry subpopulations might be an efficacious approach to preventing future morbidity and improving worker health and well-being.

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The health of young US workers.

To provide an overview of the health status of young US workers across four domains: functional health, physical and psychological health, health beha...
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