Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line (2020)

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24 4.1 Introduction This chapter aims to identify and estimate national healthcare costs and worker productivity as a function of transit worker illness and injury. The estimates provided are generally for the entire population of transit workers and are used to inform evaluations of transit agency health promotion programs. As Figure 3 shows, the costs of the harms related to worker illness and injury are paid by workers, employers, and society, which underscores the need to iden- tify ways to increase the effectiveness of transit agency wellness programs for preventing and reducing the burden of transit worker chronic illness and injuries (Asay, Roy, Lang Payne, and Howard 2016; MEPS 2014). Recognition is growing of the importance of adopting an approach to improving worker health that includes facets of both physical and mental health (CDC 2018c). This recognition is particularly true for transit workers, who face many work-related challenges that can have deleterious effects on their health (Tse, Flin, and Mearns 2006; Greiner, Krause, Ragland, and Fisher 1998). Figure 3 shows the relationships between the costs to society, employers, and workers related to worker illness and injury. The top box shows examples of costs of worker illness and injury paid by workers, which include lost wages from lost days of work, out-of-pocket medical costs, and the employees’ share (if any) of health and disability insurance premiums, as well as dimin- ished quality of life. The lower right-hand box shows examples of costs paid by employers, which include costs associated with worker absenteeism and turnover, as well as the (typically greater) share of costs for employer-based health insurance. Examples of costs shared between workers and employers include disability insurance and lost productivity in terms of worker and employer output of quality and effective services. The lower left-hand box shows examples of costs paid by society, which include costs to state resources (e.g., workers’ compensation, Medicaid) and costs to federal resources (e.g., disability, Medicare, Tricare). Examples of shared costs between society and employers include losses in the labor force and costs to workers’ compensation programs that are supported by employers and states. Examples of shared costs between workers and society are fewer public services, reduced public safety, and detrimental health and financial spillover to families of workers. Overlaps across categories also can make it difficult to establish precise divisions or counts; for example, if the employer covers all or most of the cost to provide health insurance, this benefit to workers often comes at a cost to employees in the form of lower wages. Using publicly available data and empirical findings on worker populations, the project team approximated some of the costs of transit worker health and injury paid by different stakeholders, as seen in Table 2. This chapter describes the data sources and metrics used to determine the national prevalence of worker illness and work-related injuries, as well as their associated costs. Where possible, C H A P T E R 4 Prevalence and Costs of Health Conditions

Prevalence and Costs of Health Conditions 25 Figure 3. Examples of costs of transit worker illness and injury paid by workers, employers, and society. Category of Cost/Stakeholder Expenditures and Losses Medical expenditures related to worker chronic illness or illness risk factors Transit workers Out-of-pocket spending (e.g., copays) Employee share of health care insurance spending (i.e., share of premiums, if any) Employers and unions Employer or union health care insurance spending Society (federal programs) Medicare spending Medicaid spending Disability spending Medical expenditures related to work-related injury Transit workers Out-of-pocket spending (e.g., copays) Employers Employer health care insurance spending (i.e., employer- or union-paid premiums) Workers’ compensation insurance spending Society (federal and state programs) State workers’ compensation payments Medicare spending Medicaid spending Disability spending Productivity losses from worker illness and/or injury Employers AbsenteeismTurnover Table 2. Cost categories, transit workers’ chronic illness and injury risks by type of stakeholder. comparisons of costs of transit worker illness and injury to costs of the general working popu- lation have been included to illustrate potential risk factors that may contribute to transit worker illness and injury. Levels of data describing the transit worker population vary, as do the definitions of conditions and injuries. Because the sources used to estimate costs draw from various data sources and peer-reviewed findings, the national estimates for medical and pro- ductivity costs associated with transit worker illness and injury are approximations. Medical

26 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line care costs include those paid by both transit workers and their employers. Because of data confidentiality restrictions and differences in cost measurement, it is not always possible to differentiate costs among transit workers, employers, and state/federal entities. Cost estimates from national data sources often combine multiple cost domains to provide a single estimate. Further, cost estimates based on claims data may be limited to only certain types of claims. For this project, the different sources of costs were used to arrive at approximations to further identify potential areas of focus for transit worker health promotion programs and their evaluations. First, the prevalence of illness and injury in transit workers was identified by reviewing existing peer-reviewed literature and national data sources, including survey and claims-based data. The information given in this report specifies whether the estimate for the transit worker population was based on the general transportation population or the narrower transit worker population. Next, costs (i.e., economic, productivity) associated with illness and injury in transit workers were identified by reviewing existing peer-reviewed literature and national data sources such as APTA, the MEPS from the Agency for Healthcare Research and Quality, and the Survey of Occupational Injuries and Illnesses (SOII) from the BLS. The research examined the prevalence and associated medical costs for smoking and obesity, which are known risk factors for cardiovascular disease, diabetes, cancer, respi- ratory disease, and arthritis (CDC 2019a; CDC 2018b). To allow for a broader range of cost approximations, data were included on both medical expenditures and productivity costs (e.g., absenteeism, turnover). Finally, medical expenditures were approximated for certain conditions using MEPS public use data selected for respondents who work in the transportation and utilities industry and who share similar work environments and demo- graphic composition with transit workers. It should be noted that the cost estimates obtained from the MEPS do not indicate which expenditures are covered by workers’ compensation. These cost estimates can help inform the design of health promotion, prevention, and safety programs. Targeting the conditions that are the most prevalent can help reduce medical and other costs and improve the health and safety conditions of transit workers. For example, cost estimates can reveal the costliest conditions, identifying what may be good targets for health intervention programs. Alternatively, they can reveal other areas of emphasis: For example, if costs associated with injuries or workers’ compensation programs are high, this may indicate the need for emphasis on safety or on the management of the workers’ compensa- tion system and rehabilitating workers. A limitation of this research, which is common to all work on prevalence, is that informa- tion could not be included about the prevalence and costs of workers who had to leave transit work as a result of deteriorating health caused by the nature of their work. Life-course and longi tudinal studies are an excellent approach to answering this type of question but were not feasible for the current study. The estimates of incremental costs over and above the “average” also could not adjust for demographic characteristics of the average worker (e.g., age and gender) relative to the transit worker because most of the data sources did not allow for this type of adjustment. Adjusting for demographic factors would add an important perspective to research on health outcomes because transportation workers are disproportionately male and older. If possible, these elements should be included in surveys that gather occupational data. 4.2 Key Characteristics of Transit Workforce This section summarizes some important characteristics of the transit workforce and estab- lishes baseline data describing the population of interest. As Table 3 shows, vehicle operations and vehicle maintenance personnel represent most of the transit industry workforce (72% and 17% respectively).

Prevalence and Costs of Health Conditions 27 In Table 3, vehicle operations refers to all activities associated with vehicle operations, including transportation administration and support, revenue vehicle movement control, scheduling of transportation operations, revenue vehicle operation, ticketing and fare collec- tion, and system security. Vehicle maintenance refers to all activities associated with revenue and non-revenue (service) vehicle maintenance, including administration, inspection and maintenance, and servicing (e.g., cleaning, fueling) vehicles. Non-vehicle maintenance refers to all activities associated with facility maintenance, including administration; the repair of buildings, grounds, and equipment as a result of accidents or vandalism; and the main- tenance of power facilities, roadways and tracks, and other facilities and systems. APTA also lists a fourth category, “general administration,” which was left out of the population totals for this project as it consists of administrative activities associated with the general or business management of the transit agency that generally involve fewer physical demands. As Table 3 illustrates, most transit workers are involved in vehicle operations and, of these, the majority are bus operators. Bus operator employment is projected to grow by 6% from 2016 to 2026; by contrast, rail operator employment is projected to decrease by 3% (BLS 2018i; BLS 2018j). Table 4 shows the mean hourly wages for workers using NAICS codes from the 2010 Stan- dard Occupational Classification (SOC) Manual. The NAICS codes were used throughout this project for cost estimates. The 48-49 NAICS codes are related to those in the 2010 SOC Manual, including the codes for transportation and material moving occupations (53-0000) and the occupation bus drivers, transit and intercity (53-3021). When designations for transit workers were Statistical Category Bus Demand-Response Commuter Rail Heavy Rail Light Rail Total Percent Employees, vehicle operations 132,076 91,983 10,953 20,387 5,242 260,641 72% Employees, vehicle maintenance 32,989 8,729 8,751 9,570 2,339 62,378 17% Employees, non-vehicle maintenance 7,064 2,484 7,059 17,559 2,484 36,650 10% Total employees 172,129 103,196 26,763 47,516 10,065 359,669 100% Source: APTA (2018) Table 3. Total and percentage of total employees by transit mode and function, 2015: bus, heavy rail, and light rail. Code Occupation Source Total Employment Mean Hourly Wage Mean Annual Wage NAICS 48-49 a Transportation and warehousing BLS (2017) b 5,792,400 $22.94 $47,200 NAICS 485 Transit and ground passenger transportation BLS (2017) c 494,700 (Mar. 2018) $18.90 (Feb. 2018) $39,305 NAICS 4851 Urban transit systems BLS (2017) d 47,000 (May 2017) $20.51 (May 2017) $42,660 NAICS 4852 Interurban and rural bus transportation BLS (2017) e 17,690 $18.56 $38,600 SOC 53-3021 Bus drivers, transit and intercity BLS (2017) f 176,140 $20.81 $43,290 SOC 53-4099 Rail transportation workers, all other BLS (2017) g 2,780 $28.82 $59,950 Sources: a NAICS codes 48 and 49, grouped as 48-49 for transportation and warehousing; b BLS (2018f); c BLS (2018c); d BLS (2018d); e BLS (2018e); f BLS (2018g); g BLS (2018h) Table 4. Mean hourly wages for cost estimates.

28 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line available by occupation codes instead of by four-digit NAICS codes, the project team used the relevant occupation codes. For calculating industry-wide costs for transit workers, APTA’s base figure of 359,669 transit workers was used. It should be noted, however, that costs have not been reported specifically for this population. Costs typically are reported for the transportation and warehousing sector (NAICS 48-49), which has a count of 5,279,300 people. When categories more specific to transit workers were used, costs were calculated for codes 4851 and 4852, which had counts of 47,000 and 17,690 people, respectively (a total of 64,690 people). The 4851 and 4852 codes were preferred, but data were not always available at this level. The project team felt most confident in attributing data to transit workers when the avail- able data covered transit-specific work categories. In accordance with the classification system, however, the project team also was confident that—in comparison with data for workers in general—data from the “transportation workers” category likely reflected the conditions and experiences of workers who have traits and experiences in common with transit workers. Accordingly, when it was the only category available, the general category “transportation workers” was used. When presenting data from studies and government sources that reflect cost estimates for health conditions and risks associated with transit workers, this report indi- cates whether the reference applies to a general category (e.g., “transportation workers”) or specifically to transit workers. Other key data characterizing the transit worker population relate to demographics. Table 5 displays demographic characteristics of workers in the bus service and urban transit industry (NAICS codes 4851, 4852, 4854, 4855, and 4859). As Table 5 displays, compared to the general worker population the transit worker population is disproportionately Black/African-American, older (over the age of 45), and male. Each demo- graphic characteristic has asso ciations with health risks and health costs that must be factored into economic modeling of cost savings from health promotion programs (Choi et al. 2017). 4.3 Identify Common Health Conditions Associated With Transit Workers The project team used PubMed, Google Scholar, and the U.S. DOT Library to review the available literature on health conditions associated with transit workers to better understand which types of conditions are prevalent. National data and findings from the MEPS, the National Health Interview Survey (NHIS), and the SOII also were used. Demographic Characteristic Employed Persons, Ages 16 Years and Older General Population Bus Service and Urban Transit Industry * Full-time 82.2% N/A Male 53.1% 62.9% Aged 40+ 54.3% 66.2% ( 45+) White 78.4% 62.6% Black/African-American 12.1% 29.3% Asian 6.2% 6.0% Other race 3.3% 2.1% Hispanic or Latino ethnicity 16.9% 15.9% * The bus service and urban transit industry classification represents NAICS codes 4851, 4852, 4854, 4855, and 4859. Source: BLS (2019a) and 2002 Census Table 5. Demographic characteristics, general employed population and population employed in the bus service and urban transit industry.

Prevalence and Costs of Health Conditions 29 In a 2012 Gallup Poll, transportation workers reported the highest rates of chronic health problems and the lowest well-being among different occupation types (Witters 2013). Based on these and other findings from a review of health conditions of urban bus drivers, a report of morbidity and disability in the transportation, warehousing, and utilities sector, and findings for local and interurban passenger transit workers from employer insurance claims data, the following were identified as important targets for transit worker health promotion efforts (Lee et al. 2012; Bushnell, Li, and Landen 2011; Tse, Flin, and Mearns 2006): • Cardiovascular disease, • Hypertension, • Diabetes, • Musculoskeletal disorders, • Mental health, and • Respiratory conditions (e.g., asthma). Findings from employer insurance claims indicate that local and interurban passenger transit workers have hypertension, depression, cardiovascular disease, and diabetes at rates that are more than 120% of the general population rate (CDC 2014). Findings also indi- cate that more than one-quarter of workers in the transportation, warehousing, and utilities sector report smoking and obesity (U.S. DOT 2010). 4.3.1 Locating Prevalence Estimates of Chronic Conditions and Risk Factors in Transit Workers Given the scarcity of data specific to transit and ground transportation workers, it was decided to include findings from research or datasets that provide prevalence findings for more general industry codes corresponding to the greater transportation workforce (e.g., persons working in the transportation, warehousing, and utilities sector). Health data were based on self-reports from interviews and surveys of adults ages 18 and older (e.g., from the NHIS), worker and employer self-reports (e.g., from the SOII), or employer insurance claims data (e.g., from regional health insurance providers) (CDC 2019d; Aizcorbe et al. 2012; Bushnell, Li, and Landen 2011). Society defines and measures illness according to concepts and conventions that can be referred to as illness constructs. The project team found that illness constructs are defined and queried in varying ways across data sources. For example, the MEPS (2018) asks respon- dents whether they have been diagnosed with certain conditions and includes questions about the following conditions: • Arthritis, • Asthma, • Attention deficit hyperactivity disorder/attention deficit disorder, • Cancer, • Chronic bronchitis, • Diabetes, • Emphysema, • Heart disease (including coronary heart disease, angina, myocardial infarction, and “other unspecified heart disease”), • High blood pressure, • High cholesterol, • Joint pain, and • Stroke. These conditions are included in the MEPS because of their known prevalence and because generally accepted clinical treatments are available for these conditions. The SOII asks Transit worker health promotion efforts often focus on: Cardiovascular disease Hypertension Diabetes Musculoskeletal conditions Mental health conditions Respiratory conditions (e.g., asthma).

30 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line employers for information about worker injury and illness, which is processed and reported by state agencies via the BLS (e.g., BLS 2017b). Illnesses included in the SOII refer to abnormal conditions or disorders that can be attributed to exposure to work-related conditions (Tse, Flin, and Mearns 2006). Examples of these illnesses include disorders of major organ systems such as the nervous system and sense organs, and skin, musculoskeletal, respiratory, and/or cardio- vascular conditions (BLS 2012). Illness constructs in claims data are based on the International Classification of Diseases associated with patient diagnoses. One advantage of claims-based illness prevalence data is that it is not subject to recall biases and underreporting, which often affects self-reporting measures. However, claims-based illness prevalence data are often limited to employer insurance providers within certain regions or to larger, self-selected employers who agree to share health insurance data (Mariotto, Yabroff, Shao, Feuer, and Brown 2011). Thus, although claims-based data provide more clinically exact information about illness diagnoses, preva- lence estimates may not be nationally representative. Further, confidentiality concerns limit the sociodemographic information available for analyses using claims data. The project team prioritized prevalence estimates for transit workers, then reported the prevalence rates based on broader illness categories (e.g., cardiovascular disease was favored over coronary artery disease, which can be thought of as a subset of cardiovascular disease). The prevalence rates reported were based on both survey and claims data. 4.3.2 Findings for Prevalence Estimates of Chronic Conditions and Risk Factors in Transit Workers from Literature and Data Sources Table 6 displays the most recent data for prevalence estimates of documented conditions in transit workers, identified as “Standard Industrial Classification Group 41—Local and Interurban Passenger Transit.” The data available under this category is more specific than the data available for the transportation and utilities sector. The data in Table 6 are based on Tim Bushnell’s 2018 study of more than 700,000 claims from 2006 to 2008 for Highmark, Inc., an independent insurance carrier, across 66 2-digit industry categories (Bushnell 2018). The table shows the percentages by which the prevalence rates for transit workers exceeded the prevalence rates for the general population in the database pool. As Table 6 indicates, estimates for the difference in prevalence of chronic conditions in transit workers compared to the general population range from 18% for cardiovascular disease to 57% for diabetes, with a heightened elevation of prevalence over the general population of 51% for chronic obstructive pulmonary disease (COPD). Publicly available data from the MEPS are available at the transportation and utilities industry level, but not at the transit worker occupational level. Condition Difference in Transit Worker Rate Over General Population Rate Cardiovascular disease 18% Diabetes 57% Hypertension 23% Musculoskeletal 20% Mental health (e.g., depression) 22% Respiratory (i.e., chronic obstructive pulmonary disease [COPD]) 51% Source: Adapted from Bushnell (2018) Table 6. Prevalence of chronic conditions affecting transit workers.

Prevalence and Costs of Health Conditions 31 Bushnell’s findings can be compared to a study by Gillespie, Watt, and Landsbergis et al. (2009) that compared the prevalence rates of disease among retired male New York City transit workers to those of male retirees throughout the United States. Using NHIS data from 2006, the earlier study had found that transit workers had an elevated rate of disease, but the mag- nitudes were quite different from what Bushnell found in 2018. For example, the 2009 study found that, compared to all male retirees in the United States, bus operators had a 30.9% higher rate of cardiovascular disease, a 27.3% higher rate of diabetes, and a 65.5% higher rate of hyper tension (Gillespie, Watt, and Landsbergis et al. 2009). Table 7 displays prevalence estimates for current smoking and obesity for workers in the transportation, warehousing, and utilities sector (NAICS 48-49, 22). Compared to the general worker population, workers across these industries are prone to higher levels of psycho- social stressors such as work-family imbalance, lack of control over shift scheduling, and hostile work environments (e.g., aggressive customers) (CDC 2013b). As Table 7 shows, more than one-quarter of transportation workers reported currently smoking and having a BMI that meets the classification for obesity (BMI ≥ 30). The preva- lence rates for health risks for chronic conditions among workers in the transportation, warehousing, and utilities industry sector also are higher than the prevalence rates in the general worker population. Such differences in illness risk factors between transportation workers and the general worker population could help explain the disparities in health conditions between transit workers and the general worker population seen in Table 6. Disparities in the prevalence of current smoking and obesity between transit workers and the general worker population can further compound the detrimental effects of the work environment on transit worker health. At the same time, challenges in the work environment may also exacerbate illness risk factors such as current smoking and obesity. In combination with the findings from Table 6 regarding the estimated prevalence of health conditions in transit workers, findings from Table 7 underscore the need for con- tinued research on transit worker populations to better identify targets for tailored health promotion efforts. Studies have further shown that mental and physical health burdens disproportionately affect women and Black or Hispanic/Latino workers in terms of obesity, job-related stressors, and smoking (Gu, Charles, and Bang et al. 2014; Cunradi, Lipton, and Banerjee 2007). Similar morbidity and mortality disparities are present in the general population for arthritis, cardio- vascular disease,depression, and diabetes (CDC 2013a; CDC 2015; CDC 2019b; CDC 2019c). Workers with lower education and income levels (i.e., lower socioeconomic status) have been found to experience poorer health than their more educated and more financially well- off counterparts (Braveman, Cubbin, and Egerter et al. 2010). African Americans, men, and Top three conditions by prevalence: Transit workers may experience these chronic conditions at rates 1.5 to 4 times higher than the general working population. More than 25% of trans- portation workers currently smoke and/or are obese. Risk Transportation Workers * Workers in General Current smoking a 27.8% 18.8% Obesity b 33.1% 27.6% * Transportation workers = workers in the transportation, warehousing, and utilities sector. Sources: a Syamlal, Mazurek, Hendricks, and Jamal (2014); b Luckhaupt, Cohen, Li, and Calvert (2014) Table 7. Comparing the prevalence of two health risks between transportation workers and workers in general.

32 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line people over age 45 are represented in higher numbers within the transit worker population than the general worker population. As such, the prevalence of health conditions and risk factors among transit and transportation workers as listed in Table 6 and Table 7 likely also varies by sociodemographic variables, with some groups experiencing higher rates of health conditions and risk factors than others. Developing a better understanding of such health disparities may help identify worker populations and their potential interactions with work environmental factors as targets for health promotion efforts. Prevalence rates for various conditions were obtained from interviews and through data collected from insurance provider annual reports for transit agencies in Louisville, Kentucky; Rochester, New York; and Los Angeles, California (see Figure 4). The prevalence rates for the top illnesses or conditions identified by transit agencies often exceeded those of the general population of claimants covered by the insurance company. According to the Transit Authority of River City (TARC) in Louisville, from February 2017 through January 2018 the top five diseases among transit workers were hypertension (37.8%), hyperlipidemia (26.5%), back pain (22.7%), osteoarthritis (15.6%), and diabetes (15.3%). Specific comparison data were not available for the general population in this area, but the rates of disease prevalence were similar to those observed for transit workers in other areas. Per the Rochester Regional Transit Service (RTS), between April 1, 2017, and March 31, 2018, the top five categories of claims were for hypertension, cholesterol disorders, back and neck problems, diabetes, and depression and anxiety. These claims data were mea- sured by the insurer Excellus BlueCross BlueShield (Excellus) for 729 subscribers, inclusive of maintenance, operations, and administrative workers, who participated in the agency’s workplace wellness program and made up approximately 25% of the transit agency’s insur- ance subscribers (Excellus 2018). In the category of cholesterol disorders, RTS subscribers had a prevalence rate of 29%, compared to 18.9% in the general Excellus population; for hypertension, the subscribers had a rate of 41.9%, compared to 23.2%. For diabetes, sub- scribers had a prevalence rate of 16.7%, compared to 8.1% in the general population. In the case of back or neck problems and depression and anxiety, the reported prevalence rates for RTS employees were lower than those for the general claimant population: 12.9% compared to 14.9%, respectively, for back and neck problems, and 5.9% compared to 9.6%, respec- tively, for depression and anxiety. Figure 4. Example of prevalence data, conditions affecting transit workers in Louisville, Kentucky, in 2017.

Prevalence and Costs of Health Conditions 33 During the fourth quarter of 2017, 76.8% of 3,780 rail and bus operators, mechanics, and clerks who belonged to the Los Angeles County Metropolitan Transportation Authority (MTA) and subscribed to the union’s health coverage made clinical visits at which the recorded BMI for 62.2% of the workers classified them as obese (Calvin, personal communication, 2019). Examining prevalence rates across several illness categories, the prevalence rates among workers at the LACMTA exceeded the average prevalence rates among general insurance subscribers (Wormley, personal communication, 2019): • Obesity (62.2% in the transportation group, compared to 49.6% for general subscribers); • Depression or anxiety (4.5%, compared to 3.1%); • One major chronic condition (22.0%, compared to 17.3%); and • Two or more major chronic conditions (5.4%, as compared to 4.0%). 4.4 Identify Estimates of Costs for Health Conditions Chronic conditions carry substantial medical and economic costs. For example, people with diabetes incur an estimated average of $7,900 per year in diabetes-related medical expen- ditures (American Diabetes Association, 2013). Obesity is associated with multiple chronic conditions, and the estimated annual medical cost of obesity was calculated at $147 billion in 2008, or $1,429 more per individual than the comparable costs for persons categorized as having a normal weight (CDC 2018a). 4.4.1 Locating Medical Expenditure Estimates for Chronic Conditions and Risk Factors in Transit Workers Data on medical expenditures from chronic conditions and risk factors specific to tran- sit workers are limited. Findings from claims data provide information on the prevalence of chronic conditions in U.S. workers, but they do not provide information about payments for healthcare services (Gu, Charles, and Bang et al. 2014; Cunradi, Lipton, and Banerjee 2007). To provide approximations of individual costs associated with conditions prevalent in transit workers, the project team referred to U.S. population-level estimates from the MEPS for average medical expenditures from the treatment of chronic conditions per person. The MEPS files that are available for public use have high-level condensed industry code categories that prohibit investigation of estimated illness prevalence and health costs specific to transit workers. Access to MEPS data that use U.S. Census industry codes at the four-digit level (i.e., 6180 for bus service and urban transit) is restricted and requires an application, application fee, and data use agree- ment with the Agency for Healthcare Research and Quality. Communication with the MEPS data team did reveal that sample sizes for respondents with the bus service or urban transit U.S. Census industry code ranged from 59 to 76 between 2005 and 2015 (Carroll, personal commu- nication, 2018). In this report, medical expenditures from the MEPS are based on national medical expen- diture data for the mean expenses per person for any medical service in the United States in 2015 (e.g., office-based provider visits, inpatient hospital stays, prescription medications) (MEPS 2019). Medical expenditures in the MEPS are the sum of direct payments for care pro- vided during the year, including individuals’ out-of-pocket payments and payments made by private insurance companies, Medicaid, Medicare, and other sources. Payments for over- the-counter drugs are not included in the MEPS. Indirect payments not related to specific medical events such as Medicaid Disproportionate Share and Medicare Direct Medical Education subsidies also are not included (MEPS 2017). Expenditures information is based on respondent self-reporting as well as on reports from medical providers. Thus, expenditures from the MEPS reflect costs to the individual and employers, and costs to the greater society through the benefit programs of Medicaid and Medicare. Of the 3,780 LACMTA employees insured through the SMART-MTA-UTU Trust Fund, 62.2% had a BMI that qualified them as obese, compared to 49.6% of the general population insured by Kaiser Permanente.

34 Improving the Health and Safety of Transit Workers with Corresponding Impacts on the Bottom Line 4.4.2 Findings for Medical Expenditure Estimates of Chronic Conditions and Risk Factors in Transit Workers From the Literature and Data Sources Differences in the prevalence rates of certain conditions among transit workers beyond those of the general population were presented in Table 6. Table 8 displays average annual medical expenditures per person by condition based on the 2015 MEPS data. The expenditures have been inflated to 2018 dollars using the Medical Care Index of the Consumer Price Index. Assuming a transit worker population base of 359,669 workers, the excess prevalence rates for transit workers were multiplied by the average annual cost per person in the United States to calculate the estimated annual excess expenditures for the transit worker population in 2018 dollars. As Table 8 shows, based on higher prevalence rates, the difference in approximated medical expenditures for the transit worker population over that of the general population ranges from about $44 million to about $757 million. The top three excess medical expenditures are asso- ciated with diabetes, cardiovascular disease, and mental health. From a financial perspective, preventing the development of diabetes and cardiovascular disease or helping transit workers better manage these conditions could yield meaningful cost savings. The expenditure approximations in Table 8 do not include the costs of lost productivity. Further, even the direct estimated expenditures for each condition can vary by level of ill- ness severity: Asthma and COPD are both chronic conditions requiring regular management, but for workers who develop pneumonia, which is a more acute respiratory condition, the costs are higher. U.S. population estimates suggest that the average annual expenditures on acute respiratory conditions could have been as high as $7,248 per person in 2015 (Suls, Green, and Davidson 2016). Medical expenditures incurred by transit workers with more than one chronic condition are not necessarily independent of each other. Treatments for one con- dition may affect treatments and costs for other conditions, or may affect the risk of developing other conditions. Lifestyle factors (e.g., diet, exercise) also affect the cumulative risks and expenditures for the conditions listed in Table 6 (Suls, Green, and Davidson, 2016). Condition U.S. Average Medical Expenditures per Person ($2018) (A) Percentage Difference Transit Worker Prevalence Over Population Prevalence (B) a Approximated Excess Expenditures Transit Workers Over General Population ($2018) (A × B × 359,669) b Cardiovascular $4,943 18% $320,011,896 Diabetes $3,691 57% $756,696,819 Hypertension $893 14% $44,965,818 Musculoskeletal $2,170 c 18% $140,486,711 Mental health $2,161 d 22% $170,993,836 Respiratory $1,772 e 20% $127,466,694 a Prevalence rates for all conditions except hypertension are based on claims data from 2014 (presented in Table 6); prevalence rates for hypertension are based on employer claims data from 2002–2005. b Population-weighted estimates for medical expenditures are calculations based on a transit worker population base of 359,669. c Estimated for “Osteoarthritis and other non-traumatic joint disorders.” d Estimated for “Mental disorders.” e Estimated for “COPD, Asthma.” Sources: a Bushnell, Li, and Landen et al. (2011); b the MEPS (2015); APTA (2018) Table 8. Medical expenditure excess approximations for transit worker population over general population.

Prevalence and Costs of Health Conditions 35 Tobacco use and obesity have wide-ranging public health impacts through the exacerbation of illness symptoms and illness risks. These illness risk factors have been associated with higher medical spending. The estimated annual medical cost of obesity in 2008 was $147 billion, with estimated medical costs per obese individual averaging $1,429 more than the comparable costs per normal-weight individual (CDC 2018a). Further, from 2006 to 2010, smoking accounted for an estimated 3.2% of total healthcare spending, 5.4% of private insurance, 9.6% of Medicare spending, 15.2% of Medicaid spending, and 32.8% of spending by other federal programs (e.g., Tricare, Indian Health Service) (Xu, Bishop, Kennedy, Simpson, and Pechacek 2015). Given the higher prevalence rates of obesity and smoking in transportation workers (as shown in Table 7), the associated costs are expected to be proportionately higher for this population than for the general population. 4.5 Conclusions This chapter discussed the prevalence rates for the most common health conditions affecting transit workers, followed by the costs for those conditions and additional medical expen- ditures. It also provided a summary of the key characteristics of the transit worker population. Most transit workers are involved in vehicle operations (72%) and of these, just over 50% are bus operators. Most are male (63%), over 45 years of age (66%), and White (63%). Even though the majority of transit workers are White, Black workers make up a higher percentage of the transit worker population (29%) than the general workforce (12.1%). Women, however, are underrepresented at 37% of the transit industry, compared to 47% of the overall workforce. The most common health conditions associated with transit workers were identified, together with the magnitude and prevalence of those conditions. The conditions identified were cardiovascular disease, hypertension, diabetes, musculoskeletal disorders, mental health, and respiratory conditions (e.g., COPD, asthma). Another finding was that rates of smoking and obesity are higher in the transit worker population than in the general population. Next, appropriate estimates were determined for the costs of each of these conditions, based on information available from journal articles and other sources. An important observation was that the costs associated with each condition are not necessarily additive, due to comor- bidities. After establishing prevalence rates and the associated costs for the most common health conditions, the costs and rates associated with transit workers were compared with those associated with the general population. Using the general population as a baseline, esti- mates of the health condition costs to transit workers over and above the same costs to the general population were determined. The costs for transit workers were found to be consis- tently in excess of those for the general worker population, by amounts ranging from tens of millions to hundreds of millions of dollars. The findings suggest where resources might be most effectively allocated to lessen the costs of transit worker health problems.