Occupational Disease in New York State: An Update

Abstract

An assessment of occupational disease in New York State was undertaken that partially replicated and expanded earlier work from 1987. Utilizing an expanded conception of occupational disease, the assessment used a variety of data sources and methods to provide estimates of mortality and morbidity of occupational disease; workers exposed to specific workplace hazards; disparities in occupational disease among racial/ethnic groups and gender; costs and distribution of costs of occupational disease; and accessible occupational medical resources. Examples of the pathways work may impact health in some of the major health issues of current import including stress-related health conditions; substance use; and overweight/obesity were included. The report contains recommendations for addressing the problem of occupational disease in New York State and advocates for the convening of a statewide group to develop an occupational disease prevention agenda.

Keywords

occupational disease occupational disease prevention occupational disease surveillance occupational epidemiology occupational health occupational medicine occupational health services work-related illness

Introduction

In the mid-1980s, labor leaders created a broad-based coalition with health and safety activists and academics to advocate for the establishment of a publicly funded Occupational Health Clinic Network (OHCN) in New York State (NYS). As envisioned, the OHCN would employ a multidisciplinary approach to diagnose and prevent occupational disease. To support the campaign, a study by Philip Landrigan and Steven Markowitz at Mount Sinai University was commissioned to provide an overview of occupational disease in the state.

More than 30 years later, with massive changes in the world of work and in health care systems, a re-assessment was necessary to guide further efforts to reduce the toll of occupational disease. This study finds that the conditions described in the original study persist. There are high levels of mortality and morbidity from occupational disease; very large numbers of workers employed in hazardous jobs; immense social and medical costs; and few specialized occupational medicine resources. In the intervening years, not only has a changed landscape of work reshaped the types of hazards workers face, but also a broader conception of what should be considered a work-related disease is required.

Documenting these changes, the new study proposes recommendations to address the problem of an occupational disease that may serve as a starting point for discussion and action. What follows is the executive summary and the first chapter.¹

Executive Summary

An occupational disease is an epidemic that is largely “hidden in plain sight.” At the same time, the work-related disease is preventable. Since these illnesses arise or are made worse by hazardous workplace conditions, elimination or reduction of those hazards eliminates or reduces disease.

More than 30 years ago, a report by Drs Landrigan and Markowitz found that more than 5000 NYS workers died from an occupational disease and at least 35,000 more developed a work-related illness each year. This new report shows that occupational disease remains a major public health problem in NYS, with little progress made since 1987.

Annually, over 7000 New Yorkers lose their lives due to preventable exposure to workplace hazards, and at any given time, over 2 million New Yorkers suffer from a non-fatal work-related disease. Protecting workers from these hazards requires a multi-faceted approach, addressing disease recognition, treatment, and prevention, and must involve both governmental agencies and non-governmental organizations and advocates.

Background

In 1987, Landrigan and Markowitz co-authored a report that showed:

At least 5000–7000 workers died from an occupational disease, and at least 35,000 workers developed a work-related illness each year.

Nearly 10% of New York workers were employed in the 50 most hazardous industries and the industrial use of toxic materials was extensive. Legally permissible levels of exposure were commonly exceeded.

The annual costs of occupational disease exceeded $600 million and much of the costs were borne by ill workers, their families, and taxpayers.

Very few clinical resources existed to diagnose and prevent occupational disease.

This new report builds on the framework created by Markowitz and Landrigan but includes diseases and hazards that have emerged since that report, and takes into consideration additional ways that work plays a role in many chronic diseases, including cardiovascular disease, diabetes, and obesity.

Occupational Disease Mortality and Morbidity—New Findings

− Using the same methods as the 1987 study, this new report finds an estimated 3085 to 4430 workers die of an occupational disease annually in NYS. Though this number is slightly lower than in 1987, occupational diseases account for 3.3% to 4.7% of total deaths each year which is a higher percentage than in 1987.

− When “emergent” diseases are taken into account, an estimated 7016 deaths annually were due to occupational disease, with 5243 among men and 1709 among women. Work-related cancer and circulatory diseases comprised the majority of deaths for both genders.

− We estimated the annual prevalence of non-fatal occupational disease at 13.2% of total disease prevalence in the state or over 2 million cases.

− Eighty-six percent of the fatal diseases were cancers and circulatory, and 70% of the non-fatal diseases were musculoskeletal and respiratory.

Estimating the Extent of Hazardous Work

A very high proportion of workers in NYS continue to work under hazardous conditions that put them at risk of occupational disease. These hazards include:

Chemical exposures	468,509 employees in 30,880 workplaces were exposed to at least one of roughly 250 hazardous chemicals.
Lead	Over 300,000 workers were employed in industries with a risk of high lead exposure. An unknown additional number is at risk of lower, yet still health-threatening levels.
Silica	About 100,000 workers are exposed to silica at levels posing a risk of silicosis and other diseases. Over 90% of these exposures are in the construction industry.
Asbestos	Though asbestos use has declined precipitously since the mid-1970s, workers in the construction trades continue to be at high risk due to handling “asbestos in place.”
Ergonomic hazards	Ergonomic hazards are associated with a range of musculoskeletal conditions.
	Between 1 and 4 million workers reported significant exposure to ergonomic hazards.
Stressors	Psychosocial stress on the job is widespread, with as many as 6 million workers reporting significant exposure to stressful conditions at work.
COVID-19	A very high proportion of workers in NYS are employed in health care and other jobs deemed “essential” and at high risk of acquiring COVID-19 infection, with a disproportionate burden of infection and mortality borne by Black and Latinx workers.

Occupational Health Inequities

Employer attitudes and practices, declining unionization, discrimination, and government policies all contribute to increasing numbers of “vulnerable workers” at increased risk of occupational disease. “Vulnerable workers” are concentrated in low-wage jobs that make up almost 40% of all jobs in the state. Workers in these jobs are disproportionately Black, Latinx, and women.

Estimating the Costs of Occupational Disease

The annual costs of occupational disease in NYS, an estimated $4.077 billion, are tremendous. Employers are able to pass off most of those costs to others with injured workers, their families, and taxpayers paying over 70%.

Clinical Occupational Health Resources

Despite the creation of the publicly funded OHCN, clinical occupational medicine resources remain scarce, particularly upstate. There are only 30 Board Certified Occupational Medicine specialists accepting patients with workers’ compensation insurance in the entire state, almost one-third of whom are employed by the OHCN. A large gap remains between the magnitude of the problem of occupational disease and the clinical resources devoted to the diagnosis, treatment, and prevention.

Recommendations

Recommendations to reduce the toll of occupational disease in NYS include:

Adequate funding

- Increase funding for governmental and non-governmental occupational health programs commensurate with the need for services.

- Develop mechanisms that make OHCN and Occupational Safety and Health Training and Education Program (OSHTEP) funding sustainable and keep pace with increases in the cost of living.

Building on the existing OSH infrastructure

- Systematically analyze existing data on occupational disease from the WCB, the OHCN, and state registries to target prevention efforts.

- Develop other data sources to provide more comprehensive information on occupational disease workplace hazards.

- Improve the workers’ compensation process to provide an incentive for clinicians to participate

- Eliminate barriers to care for occupational disease by workers’ compensation reforms that curb insurance carrier powers to deny and delay claims

Prevention of occupational disease

- Development of a statewide occupational disease prevention agenda that includes both governmental and non-governmental organizations in its crafting

- Incentivize employers to engage in occupational disease prevention efforts by reducing their ability to socialize the costs of occupational disease and by more assertive state intervention and regulation of workplace hazards.

Integration and collaboration

- Development of a statewide occupational disease prevention agenda that includes both governmental and non-governmental organizations in its crafting.

- Continue the collaboration between these groups in the implementation of the agenda.

Building worker capacity and expanding worker participation

- Build worker-based occupational health capacity.

- Include workers and worker advocacy organizations as central participants in collaborative occupational health efforts.

Occupational Disease in NYS (Chapter 1 of the Report)

In 1987, Landrigan and Markowitz co-authored a report on occupational disease in NYS.^1,2 This pioneering effort estimated that:

At least 5000–7000 workers die from an occupational disease, and at least 35,000 workers develop a work-related illness each year.

“(N)early 10% of New York workers were employed in the fifty most hazardous industries…Industrial use of toxic materials is extensive. Legally permissible levels of exposure are commonly exceeded.”

The annual costs of occupational disease exceeded $600 million and that much of the costs are borne by ill workers, their families, and taxpayers.

The report concluded that: occupational disease was common and often deadly; millions of workers labor under hazardous conditions that put them at risk of occupational disease; and the costs of occupational disease were enormous. Given the magnitude of the problem, the authors emphasized that resources to diagnose, treat, and prevent occupational disease were wholly inadequate.

The report served to bolster an organizing effort led by the labor union movement but included a broad range of occupational health professionals and activists, to establish a publicly funded network of occupational health clinical centers. The effort was successful in convincing state legislators and the governor to provide funding for the creation of a network.³ Funding has been maintained for more than 30 years since and the OHCN consists of eight clinics with a regional responsibility and one with a statewide mandate focused on agricultural safety and health.⁴ OHCN clinics were envisioned as community-based and advised centers that would employ multidisciplinary teams (including an Occupational Medicine physician, an Industrial Hygienist, and a Social Worker) to diagnose and prevent occupational disease.^5,6

Just prior to the Landrigan/Markowitz report, the OSHTEP was created to fund organizations to provide training and education to workers, heightening awareness about occupational health hazards and facilitating the development of the knowledge and skills necessary to reduce hazards by changing workplace conditions. OSHTEP funds were crucial to building both Committees on Safety and Health and union health and safety staff. ⁷

Both OSHTEP and the OHCN were funded through an assessment of workers’ compensation insurance premiums paid by employers. As a result of these pieces of legislation, public funding in New York has been crucial to building a relatively extensive, sustained, and unique occupational health infrastructure. That infrastructure includes state-based programs in the Department of Labor and the Department of Health (DOH) engaged in regulating, educating, data collection and analysis, and technical assistance on occupational health issues. In addition, it includes the State's Workers’ Compensation system that provides access to medical, wage replacement and vocational rehabilitation benefits to workers suffering from work-related diseases.

Thirty years later, it is time to re-assess the state of occupational disease in NYS. Over that period, aside from the development of the OHCN and OSHTEP, there have been significant economic, political, and scientific changes that have had important implications for occupational disease. Key issues include:

A dramatic shift in the economic base of the state away from manufacturing and toward service industries.

A large growth of low-wage jobs that offer little in the way of security or benefits.

A major increase in the participation of women and immigrants in the state's workforce.

A significant decline in the size and power of the labor union movement.

A sustained shift away from a liberal “welfare state” to a neoliberal state emphasizing deregulation, governmental downsizing, and shrinking both taxation (particularly business taxes) and government spending.

Reform to the Workers’ Compensation system induced large numbers of physicians to exclude patients with work-related injuries or illnesses from their practices.

A global viral pandemic (COVID-19) that dramatically reshaped virtually all aspects of life beginning in 2020. Work-related infections and deaths brought the issue of occupational disease to widespread attention.

Recognition of a high incidence of musculoskeletal injuries due to long-term work in ergonomically poorly designed jobs.

An evolution in the way occupational disease is defined and conceptualized.

As a whole, these changes are likely to substantially impact the results of an inquiry into all the areas covered in the original 1987 Landrigan/Markowitz report. The changing landscape of work alters the profile of hazards workers face on the job. Other political and economic changes combine to make it less likely that occupational disease will be recognized. Conversely, a redefinition of an occupational disease that enlarges the concept and will improve the accuracy of what is recognized. The COVID-19 pandemic may generally raise awareness and sensitivity to other work-related diseases. Consequently, the approach to identifying, treating, and preventing occupational disease will require modification to be effective under these changed circumstances.

This paper uses the Landrigan/Markowitz report as a model to re-assess occupational disease incidence, the extent of hazardous work that puts workers at risk of occupational disease, the costs of occupational disease, and occupational health resources available to identify and prevent occupational disease in NYS. Though the paper explores the same themes as Landrigan/Markowitz, it does so with a modified definition of occupational disease and the use of some different sources of data and methodology.

This report intends to provide data that can both frame and inform efforts to reduce the toll of occupational disease in NYS.

What is an Occupational Disease?

The traditional definition of an occupational disease^8,9 has two key components that distinguish it from an occupational injury:

An exposure to a hazard that occurs over a period of time.

An ill-defined onset that becomes evident over a period of time.

In contrast, an injury is conceived as a condition that:

Results from exposure to a hazard that produces immediate effects.

Results in symptoms with a well-defined, often abrupt onset.

There is a need to critically evaluate the definition of occupational disease in order to better determine what gets counted when assessing incidence, risk, and costs, and consequently, the type and amount of resources that need to be devoted to the prevention, treatment, and compensation of these conditions.

Classic examples of occupational diseases include asbestosis from years of asbestos exposure, lead poisoning from radiator repair work, and solvent-related encephalopathy. “Emergent” occupational diseases that have become evident over the past several decades fall into several categories:

Musculoskeletal conditions are caused by prolonged exposure to work-related risk factors.

Airborne infectious disease (e.g. COVID-19).

Conditions that are multifactorial and may include non-work-related causes (e.g. heart disease, chronic lung disease).

Conditions that are caused by workplace psychosocial factors (e.g. work-related stress, bullying, violence).

Conditions that are caused by organizational factors (e.g. shiftwork, short-staffing, long hours).

Mental health conditions that occur as a direct result of workplace conditions or as sequelae of a work-related physical condition.

Work-related substance abuse.

Less well-defined health conditions (e.g. loss of well-being) related to work.

Non-musculoskeletal conditions that do not meet the prolonged exposure time and/or chronic onset aspects of the classic occupational disease definition.

The possible pathways along which workplace exposures may interact with each other, and workplace exposures may interact with non-workplace exposures, to impact the expression of disease are many and potentially complex. The classic example is the interaction between cigarette smoking and asbestos exposure which greatly increases the risk of lung cancer beyond that of either exposure alone.^10–12 ‘Work aggravated’ asthma is another example of this interaction.^13–15 The COVID-19 pandemic has also dramatically illustrated this interaction. Recognizing that the non-work and work worlds interact greatly complicates the concept of occupational disease. In addition, it may be quite difficult to parse out the contribution of the various exposures, and the occupational component may vary from minimal to predominant.¹⁶

One of the insights of this more complex model is that exposure to workplace hazards can interact with non-work exposures to contribute to the production of diseases typically not thought of as “occupational” in origin. Characteristics of workplace stress that put workers at increased risk of cardiovascular disease including hypertension, myocardial infarction, and stroke have been elucidated over the past several decades.^17–21 Workplace hazards can play a role in aggravating, or perhaps in causing diabetes through a variety of mechanisms including direct exposure to endocrine disrupting chemicals; limiting breaks necessary to access insulin and/or food; limited access to healthy food; or high-stress levels.^22–30 Obesity can be encouraged through some of these same pathways, as well as by sedentary jobs that restrict movement throughout the work shift.^31–43

At the time of the Landrigan/Markowitz report, musculoskeletal conditions due to workplace conditions such as repetitive motion, forceful movements, and static posture were beginning to be recognized as an important part of the occupational disease landscape, but they were not included in the Landrigan/Markowitz assessment. In the ensuing decades, they have been established as a major source of work-related morbidity and disability and require inclusion in the discussion of occupational disease.^44–46

The psychosocial and organizational characteristics of work have received considerable attention and recognition as contributors to illness. The characteristics of modern work have been explored including attributes of the work itself (e.g. high job demands with low control over work, machine-paced work, shiftwork), social characteristics of the workplace (e.g. presence or absence of social support, lack of respect, bullying supervisor), and more macro-level factors (e.g. lack of job security, unemployment).^17,47–55 Cardiovascular and mental health were the main health impacts studied early on, but it has become evident that the potential health impacts of poor psychosocial work conditions are much broader.⁵⁶ For example, the epidemic of violence in health care workplaces exemplifies how systemic factors such as understaffing and underfunding lead to extreme stressors with complex multifactorial sources of job strain.^57,58 As already suggested above, work plays some role as a contributor to most, if not all, contemporary major health challenges including the obesity epidemic, diabetes, and substance abuse (not only opiates, but alcohol, tobacco, and other substances as well).^{30,34,59–62} Undoubtedly, other health issues will continue to emerge. For example, the importance of sleep is increasingly recognized, and the way work is organized can have a major impact on sleep or lack of it.^63–68 Psychosocial and organizational characteristics of work play a major role in the production of these issues.

Mental health and its relationship to work is a specific area requiring attention. As already discussed, aspects of work generically grouped as “stressful” have mental health consequences, commonly including depression and anxiety. The mental health impact is also manifest as a consequence of suffering from an occupational disease and the resulting trauma of job loss, decline in physical capabilities, loss of friendships and social networks, financial stress, and the indignities of the workers’ compensation process.^69,70

Substance abuse is another contemporary public health challenge. While opiates have received most of the attention, tobacco and alcohol are the most commonly abused substances. Work may play a role in these addictions with their use as a way of coping with the various stresses of work. Tobacco may augment workers’ ability to stay alert for long hours, and function as a substitute for food. Alcohol is used to unwind after a shift. And opiates help workers who are in pain to keep working, or to come back to work sooner after an injury.

Even an expanded definition of occupational disease does not adequately capture all aspects of health. Well-being can be stimulated or enhanced by work, but also the lack of well-being can be caused by or contributed to by work. The concept, as advanced by Schulte and colleagues, describes well-being as

flourishing and aspiring to… a good life that is characterized by happiness, life satisfaction, positive emotion and self-determination. It includes health, but goes beyond that … and has been linked to individual enterprise, national health care costs, reduced injury and illness and lower rates of absenteeism and presenteeism.⁷¹

The loss of a sense of “well-being” is important to the individual worker as it can negatively color all aspects of their lives, reducing their ability to engage and be present. Prolonged loss of “well-being” can have an impact on mental health and possibly on physical health as well.^71,72

Finally, there are a number of conditions that intuitively seem like diseases that do not meet one or both criteria of prolonged exposure and ill-defined progressive onset. For example, asthma can occur, and become persistent, immediately following initial heavy exposure to chlorine gas. In fact, asthma is an example of a disease that occurs along a full spectrum of both acute and chronic exposure and acute and chronic onset and progression. Contact dermatitis typically appears rapidly upon re-exposure to a substance to which an individual has been sensitized. It then recurs whenever the person is re-exposed to the allergen and can become nonspecific, occurring with exposure to other substances as well. An argument that these conditions should be included among diseases and not injuries is based upon the cause: an exposure to an airborne, dermal, or, occasionally, ingested hazard.

An overall assessment of occupational disease requires investigation of both “classic” and “emergent” conditions.

Assessing the Incidence and Prevalence of Occupational Disease

Obtaining accurate and comprehensive data on occupational disease is notoriously difficult, as the United States and NYS have no systematic reporting systems in place that capture deaths and morbidity due to a workplace cause.⁷³ The NYS Workers’ Compensation Board and Bureau of Labor Statistics are the most obvious potential sources of data, but they suffer from a narrow definition of occupational disease and multiple barriers to reporting and recognition. ^54,74–83 Additionally, the NYS Workers’ Compensation Board to date has offered only a superficial analysis of its data and has not made its occupational disease data available in a meaningful way to allow further analysis. ⁸⁴

The NYS DOH maintains several registries (i.e. Heavy Metals Registry, Occupational Lung Disease Registry, and Pesticide Registry). All suffer from limitations including difficulty accessing the data, and (except for the Heavy Metals Registry) non-comprehensive reporting which makes them of little use in estimating incidence or prevalence. The OHCN has amassed considerable data on patients with suspected work-related conditions evaluated over the last 32 years. This is a rich source of information that adds to the picture of occupational disease in the state, but is not comprehensive and also cannot be utilized to estimate incidence/prevalence.

In addition, the cumulative effect of the changes in the landscape of work that occurred since the Landrigan/Markowitz report has been to reduce the visibility of occupational disease.

As a consequence of the dearth of data, alternative and less direct methods must be utilized to estimate occupational disease mortality and morbidity. The specific methodologies used will be discussed in the sections that follow.

Occupational Disease: Estimating Mortality and Morbidity

Methods for Estimating Occupational Disease Mortality and Morbidity

Mortality. The Landrigan/Markowitz report used the idea of “attributable fraction” to estimate mortality in NYS. “Attributable fraction” is defined as the portion of overall deaths that can be attributed to occupational causes. For example, cancer can be caused by exposure to inhaled hazards at work or at home/in the community. The work-related attributable fraction or the percentage caused by work exposures is estimated to be 8.4%. The attributable fractions are derived from a review of the relevant epidemiologic literature. The totals for specific causes of death in NYS are obtained from death certificates. In Table 1, we replicated the Landrigan/Markowitz mortality assessment using average annual mortality rates for 2010 to 2016 in NYS, and applying the same attributable fractions used by Landrigan/Markowitz.¹

Table 1.

Occupational Disease Mortality Estimates in New York State, 2010–2017.

		Annual mortality, New York State^c									Occupational fraction^d		Occupational disease mortality
Cause of death^a,b	ICD-10 code(s)	2010	2011	2012	2013	2014	2015	2016	2017	Average 2010–2017	Lower range	Upper range	Lower range	Upper range
Cancer (malignant neoplasms)	C00–C97	28,817	28,750	29,110	28,921	28,455	28,061	28,428	28,042	28,573	8	10	2286	2857
Pneumoconioses^e	J60–J70	379	416	398	395	454	545	502	512	450	100	100	450	450
Chronic lower respiratory disease	J40–J47	4642	4665	4699	4709	4488	4666	4582	4702	4644	1	3	46	139
Cardiovascular disease, renal disease, and neurologic disorders
Circulatory system	I00–I99	30,048	29,582	28,716	29,168	28,701	29,339	29,673	29,571	29,350	1	3	293	880
Renal^e	N00–N98	1931	1842	1916	1846	1844	1866	2043	1977	1908	1	3	19	57
Neurological	G00–G98	2833	2791	2823	2881	2926	3267	3344	3509	3047	1	3	30	91
Other conditions		25,648	27,089	26,889	27,471	27,989	28,477	29,626	29,630	27,852	0	0	0	0
Total occupational disease													3125	4476
Total all-cause mortality		94,298	95,135	94,551	95,391	94,857	96,221	98,198	97,943	95,824
Percent of all deaths attributed to occupational disease													3.26%	4.67%

Cause of death computed from death certificates as recorded by New York State Vital Statistics.

Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Cause of Death 1999–2015 on CDC WONDER Online Database, released December 2016. Data are from the Multiple Cause of Death Files, 1999–2015, as compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program, http://wonder.cdc.gov/mcd-icd10.html (accessed 22 April 2019)

Age 15–84 economically active population, older ages accommodate disease latency.

Method derived from Landrigan & Markowitz, Occupational Disease in New York State, Proposal for a Statewide Network of Occupational Disease Diagnosis and Prevention Centers: Report to the New York State Legislature, February 1987.

Data suppressed for ages under 44 for some years due to confidentiality restraints (low numbers).

In addition, we estimated mortality using a different set of attributable fractions (Tables 2 and 3). Since the original Mount Sinai Report significant bodies of literature have accumulated that allow for an updating of the attributable fraction of occupational disease for many health conditions. In 2001, Nurminen and Karjalainen⁸⁵ estimated the global burden of occupational disease based on significant improvements in the calculation of the attributable fractions. Following their methods, we have reformulated occupational disease mortality estimates for NYS. Nurminen and Karjalainen's work also allows for the inclusion of health conditions that may be work-related but were not included in the Mount Sinai calculation. This is consistent with the idea of a broadened conception of occupational disease.^86–90 Their work also allowed us to demonstrate how occupational disease fatalities vary by gender (Table 4). In addition, to accommodate known latency in chronic disease and the fact that workers are working longer, we specified age ranges to include additional years beyond the conventional time of workforce participation.

Table 2.

Attributable Fraction^a (%).

Cause of death	Total	Women	Men
All causes (all codes)	6.7	2.1	10.2
Infectious diseases (all A and B)	8.8	32.5	4.8
Malignant neoplasms (all C)	8.4	2.2	13.8
Mental disorders (all F)	3.5	1.8	7.3
Diseases of the nervous system (all G and H)	3.1	1.7	5.1
Diseases of the circulatory system (all I)	12.4	6.7	14.4
Diseases of the respiratory system (all J)	4.1	1.1	6.8
Diseases of the digestive system (all K)	2.1	1.5	2.3
Diseases of the genitourinary system (all N)	1.3	0.4	3
Intentional self-harm and sequelae (X60–X84, Y87.0)	0.4	0.3	0.4

Nurminen and Karjalainen.⁸⁵

Table 3.

Estimated Work-Related Mortality in the United States and in New York State in 2016, by Causes of Death, Age 15–84.^a

Cause of death^b	Attributable fraction^c (%)	Numbers of deaths, US	Work-related mortality, US	% Work-related deaths, US	Numbers of deaths, NYS	Work-related mortality, NYS	% Work-related deaths, NYS
Infectious diseases (all A and B)	8.8	52,962	4661	3.8	3199	282	4.0
Malignant neoplasms (all C)	8.4	493,324	41,439	33.5	28,428	2388	34.0
Mental disorders (all F)	3.5	50,741	1776	1.4	2606	91	1.3
Diseases of the nervous system (all G and H)	3.1	96,951	3005	2.4	3350	104	1.5
Diseases of the circulatory system (all I)	12.4	506,027	62,747	50.8	29,673	3679	52.4
Diseases of the respiratory system (all J)	4.1	178,742	7328	5.9	8758	359	5.1
Diseases of the digestive system (all K)	2.1	87,119	1829	1.5	3815	80	1.1
Diseases of the genitourinary system (all N)d	1.3	44,202	575	0.5	2043	27	0.4
Intentional self-harm and sequelae (X60–X84, Y87.0)	0.4	43,308	173	0.1	1620	6	0.1
Other causes		303,564			14,706
Total occupational disease			123,534			7016
Total all-cause mortality		1,856,940			98,198
Percent of deaths attributable to occupational disease			6.65%			7.14%

Age 15–84, economically active population, older ages accommodate latency.

As recorded by New York State Vital Statistics, accessed via. CDC Wonder Detailed Mortality, Underlying Cause of Death (https://wonder.cdc.gov/ucd-icd10.html—abstracted April 2019).

Nurminen and Karjalainen.⁸⁵

Some figures suppressed for 15–24-year-old.

Table 4.

Occupational Disease Mortality in New York State in 2016 by Gender, Age,^a and Cause^b Estimated by Attributable Fraction.^c

Causes^b		Infectious diseases (all A and B)	Malignant neoplasms (all C)	Mental disorders (all F)	Diseases of the nervous system (all G and H)	Diseases of the circulatory system (all I)	Diseases of the respiratory system (all J)	Diseases of the digestive system (all K)	Diseases of the genitourinary system (all N)	Self-harm and sequelae (X60–X84, Y87.0)	Other causes	Total occupational disease	Total all-cause mortality	Percent of deaths attributable to occupational disease
Deaths women by age
	15–24	11	24	Suppressed	20	24	23	Suppressed	Suppressed	52	234		388
	25–34	25	124	27	30	74	26	26	Suppressed	62	484		878
	35–44	60	384	28	30	184	39	48	18	63	466		1320
	45–54	153	1322	39	80	677	180	189	40	91	714		3485
	55–64	286	3118	75	184	1662	605	323	127	69	886		7335
	65–74	390	4541	188	379	3234	1288	441	261	38	1071		11,831
	75–84	490	4661	861	953	6261	2039	580	507	25	1438		17,815
	Total	1,415	14,174	1218	1676	12,116	4.200	1,607	953	400	5,293		43,052
Attributable fraction women^c		32.5	2.2	1.8	1.7	6.7	1.1	1.5	0.4	0.3	0
Deaths from occupational disease women		460	312	22	28	812	46	24	4	1	0	1709	43,052	4.00%
Deaths men by age
	15–24	13	58	10	28	24	29	Suppressed	Suppressed	151	743		1056
	25–34	43	105	44	37	166	36	43	10	184	1337		2005
	35–44	77	295	87	42	447	66	114	15	204	1033		2380
	45–54	201	1163	166	106	1582	193	327	63	240	1384		5425
	55–64	481	3456	221	216	3614	737	585	172	241	1649		11,372
	65–74	486	5030	253	430	5112	1500	595	315	122	1379		15,222
	75–84	483	4711	603	810	6612	1997	531	509	78	1352		17,686
	Total	1,784	14,818	1,384	1,669	17,557	4558	2195	1084	1220	8877		55,146
Attributable fraction men^c		4.8	13.8	7.3	5.1	13.8	7.3	5.1	13.8	7.3	5.1
Deaths from occupational disease men		86	2045	101	85	2045	101	85	2045	101	85	5243	55,146	9.50%
Total work-related deaths		546	2357	123	114	2357	123	114	2357	123	114	6952	98,198	7.10%

Economically active population (age 15–64) also accommodates latency (age 65–84).

As recorded by New York State Vital Statistics, accessed via CDC Wonder, Detailed Mortality, Underlying Cause of Death (https://wonder.cdc.gov/ucd-icd10.html—abstracted April 2019).

Nurminen and Karjalainen.⁸⁵

Morbidity. The Landrigan/Markowitz report used three data sources to estimate occupational disease morbidity:

NYS Workers’ Compensation data.

Bureau of Labor Statistics reports.

Physicians’ reports of occupational disease in California. They acknowledged the severe limitations of each of these sources.

Numerous studies have emphasized the small proportion of individuals with an occupational disease whoever actually apply for and receive Workers’ Compensation benefits.^75–83 These studies have examined well-established work-related conditions such as silicosis and asbestosis. Given the low recognition of even these diseases in Workers’ Compensation, recognition of many of the conditions in the expanded definition of occupational disease would likely not be represented in this data. A further difficulty is that the NYS Workers’ Compensation Board is not currently organizing its case data to even make an analysis of occupational disease possible.⁸⁴

Bureau of Labor Statistics data are based on employer reports of occupational disease. These reports are mandated by the Occupational Safety and Health Administration (OSHA). A major limitation of this data is that it is restricted to a relatively few conditions which are almost entirely easily recognizable and acute.

In California, physicians are required to submit reports of occupational disease to the State Department of Labor. Similar to the BLS data, the California Doctors’ reports suffer from restriction to a limited set of primarily acute conditions. Physician and employer recognition and reporting of occupational disease suffer from significant limitations which also contribute to the lack of comprehensiveness of the BLS and California physicians’ data.

Given the limitations of available data, we chose to estimate occupational disease morbidity in two ways. The first estimate uses BLS data. The second estimate attributable fractions using Nurminen and Karjalainen's 2001 work as a starting point and modifying their estimates based on newer data. Consequently, our estimates rest on the assumption that attributable fractions for mortality are also valid for estimating morbidity. Since occupationally related cases for any given diagnosis are likely to have a similar probability of death as non-occupational cases, this assumption seems reasonable. Because most available data estimate prevalence rather than incidence, we chose to use prevalence rather than incidence rates. This was largely based on the practicalities of available data. In order to estimate the attributable fraction, the total number of people with the disease must be ascertained. Consequently, the morbidity estimates provide a useful picture of the overall occupational disease burden, but do not reveal how many cases occur each year, and are not directly comparable with the Landrigan/ Markowitz morbidity estimates.

Results: Mortality and Morbidity

Mortality

The Mount Sinai study estimated between 4686 and 6592 New Yorkers died each year from an occupational disease. Table 1 provides our estimate of occupational disease mortality. Using an average annual mortality for 2010 to 2016 in New York, and applying the same attributable fractions used by Landrigan/Markowitz, current estimates of occupational disease fatalities range from 3085 to 4430. The overall number of deaths has decreased from 2010 to 2016 compared to the 1979 to 1982 period described in the Mount Sinai report, with 95,824 and 132,139 annually in the respective time periods.^88,89 Consequently despite the decline in the number of deaths, the occupational disease accounts for an increased proportion of deaths in 2016 compared with 1987, with the estimate ranging from 3.3% to 4.7% in 2016 and from 2.8% to 3.7% in 1987.

Using Nurminen and Karjalainen's attributable fractions (Tables 2 and 3), a total of 7016 deaths (7.14%) were due to occupational disease in NYS. Table 4 stratifies mortality by gender and age and relies on gender-based attributable fractions. Deaths attributable to occupational disease in men numbered 5243 or 9.5% of deaths from all causes among men. Deaths attributable to occupational disease in women numbered 1709 or 4.0% of deaths from all causes among women. Among men, cancer and circulatory causes made up 87% of occupationally related deaths, and among women, 93% were comprised of cancer, circulatory conditions, and infectious diseases.

Morbidity: Non-Fatal Occupational Illnesses

According to BLS data abstracted for NYS, there are an estimated 9300 people diagnosed with a non-fatal occupational illness in NYS each year. In 2016, the incidence rate was 13 per 10,000 full-time workers (Table 5). It should be noted that these are mostly acute or subacute conditions, with chronic conditions largely unrecognized. Two-thirds of the illness are occurring in the private sector with the remaining one-third in state and local government. In the private sector, utilities, manufacturing, health care, social assistance, and transportation and warehousing have higher-than-average incidence rates. Hearing loss drives the figures for utilities and manufacturing while the category named “all other illnesses” drives the figures for health care and social assistance significantly. Among public sector workers, the “all other illnesses” category also drives the reported rates. Examples of all other illnesses include heatstroke, heat exhaustion, and heat stress; freezing and frostbite; decompression sickness; effects of ionizing radiation (isotopes, x-rays, radium); effects of nonionizing radiation (welding flash, ultra-violet rays, lasers); anthrax; bloodborne pathogenic diseases such as AIDS, HIV, hepatitis B or hepatitis C; brucellosis; malignant or benign tumors; histoplasmosis; coccidioidomycosis.

Table 5.

Incidence Rates^a and Numbers of Non-Fatal Occupational Illnesses by Industry Sector and Category of Illness, New York, 2016.

	Total cases	Skin disorders	Respiratory conditions	Poisonings	Hearing loss	All other illnesses	Total cases	Skin disorders	Respiratory conditions	Poisonings	Hearing loss	All other illnesses^f
Industry sector^b	Incidence rates per 10,000 full-time workers^a						Numbers of illnesses in thousands
All industries including state and local government^c	13.0	1.3	1.1	0.2	2.0	8.4	9.3	0.9	0.8	0.1	1.5	6.0
Private industry^c	9.9	0.8	0.6	0.1	2.1	6.2	6.1	0.5	0.4	0.1	1.3	3.8
Goods-producing^c	19.7	1.3	0.6	—	8.9	9.0	1.6	0.1	*	*	0.7	0.7
Natural resources and mining^c,d	—	—	—	—	—	—	—	—	*	*	*	—
Agriculture, forestry, fishing, and hunting^c	—	—	—	—	—	—	—	—	*	*	*	—
Mining, quarrying, and oil and gas extraction^d	—	—	—	—	—	—	*	*	*	*	*	*
Construction	2.5	—	0.5	—	—	1.7	0.1	*	*	*	—	0.1
Manufacturing	26.0	1.4	0.7	—	15.7	8.2	1.1	0.1	*	*	0.7	0.4
Service-providing	8.4	0.8	0.6	0.1	1.1	5.8	4.5	0.4	0.3	0.1	0.6	3.1
Trade, transportation, and utilities^e	8.1	0.4	0.6	—	1.7	5.2	1.0	*	0.1	—	0.2	0.7
Wholesale trade	1.6	—	—	—	—	1.3	0.1	*	*	*	*	*
Retail trade	7.5	0.5	0.6	—	—	5.6	0.5	*	*	—	—	0.4
Transportation and warehousing^e	15.1	—	1.2	—	3.4	10.1	0.3	*	*	*	0.1	0.2
Utilities	34.7	—	—	—	32.0	—	0.1	*	*	*	0.1	*
Information	5.2	0.9	—	—	—	3.5	0.1	*	—	*	*	0.1
Finance, insurance, and real estate	—	—	—	—	—	1.2	—	—	—	*	—	0.1
Finance and insurance	0.7	—	—	—	—	0.6	*	*	*	*	*	*
Real estate and rental and leasing	—	—	—	—	—	—	—	—	—	*	—	—
Professional and business services	3.3	—	0.3	—	—	2.2	0.4	—	*	*	*	0.2
Professional, scientific, and technical services	1.9	—	—	—	—	—	0.1	*	*	*	—	—
Management of companies and enterprises	—	—	—	—	—	—	*	*	*	*	*	*
Administrative and support and waste management and remediation services	6.3	—	0.4	—	—	3.9	0.2	—	*	*	—	0.1
Educational and health services	15.6	1.1	0.9	0.1	—	13.3	2.0	0.1	0.1	*	*	1.7
Educational services	9.4	—	0.9	—	—	8.0	0.2	*	*	*	*	0.2
Health care and social assistance	16.9	1.3	1.0	0.2	—	14.5	1.8	0.1	0.1	*	*	1.6
Leisure, entertainment, and hospitality	5.8	0.9	0.6	—	—	4.0	0.3	0.1	*	*	—	0.2
Arts, entertainment, and recreation	9.0	—	—	—	—	7.0	0.1	—	*	*	—	0.1
Accommodation and food services	5.3	0.9	0.7	—	—	3.5	0.3	*	*	*	*	0.2
Other services (except public administration)	6.1	1.1	—	—	—	3.1	0.2	*	—	*	*	0.1
Other services (except public administration)	6.1	1.1	—	—	—	3.1	0.2	*	—	*	*	0.1
State and local government^c	33.3	4.0	4.4	0.5	1.7	22.8	3.2	0.4	0.4	*	0.2	2.2
State government^c	25.8	2.2	3.3	1.0	1.2	18.1	0.5	*	0.1	*	*	0.4
Local government^c	35.4	4.5	4.7	0.3	1.9	24.1	2.7	0.3	0.4	*	0.1	1.8

Incidence rates represent the number of illnesses per 10,000 full-time workers and were calculated as (N/EH)×20,000,000, where: N=number of illnesses; EH=total hours worked by all employees during the calendar year; 20,000,000=base for 10,000 equivalent full-time workers (working 40 h per week, 50 weeks per year).

North American Industry Classification System—United States, 2012.

Excludes farms with fewer than 11 employees.

Data for mining (Sector 21 in the North American Industry Classification System Manual, 2012 edition) include establishments not governed by the Mine Safety and Health Administration (MSHA) rules and reporting, such as those in oil and gas extraction and related support activities. Data for mining operators in coal, metal, and nonmetal mining are provided to BLS by the MSHA, U.S. Department of Labor. Independent mining contractors are excluded from the coal, metal, and nonmetal mining industries. These data do not reflect the changes Occupational Safety and Health Administration (OSHA) made to its recordkeeping requirements effective 1 January 2002; therefore, estimates for these industries are not comparable to estimates in other industries.

Data for employers in railroad transportation are provided to BLS by the Federal Railroad Administration, U.S. Department of Transportation.

Examples: heatstroke, sunstroke, heat exhaustion, heat stress and other effects of environmental heat; freezing, frostbite, and other effects of exposure to low temperatures; decompression sickness; effects of ionizing radiation (isotopes, x-rays, radium); effects of nonionizing radiation (welding flash, ultra-violet rays, lasers); anthrax; bloodborne pathogenic diseases such as AIDS, HIV, hepatitis B or hepatitis C; brucellosis; malignant or benign tumors; histoplasmosis; coccidioidomycosis.

Note: Because of rounding, components may not add to totals. Dash indicates data do not meet publication guidelines. Asterisk indicates data too small to be displayed.

Source: U.S. Bureau of Labor Statistics, U.S. Department of Labor, Survey of Occupational Injuries and Illnesses in Cooperation with Participating State Agencies, 9 November 2017.

Nurminen and Karjalainen's attributable fraction approach estimates that occupational disease comprises 13.2% of total disease prevalence in the state. In contrast to mortality, musculoskeletal, respiratory, and nervous disorders make up nearly 80% of the total occupational disease burden. Diseases of the skin, circulatory system, and cancer account for an additional 17% of the total. Occupationally related mental illness is an estimated 4.5%. These results, applying Nurminen and Karjalainen's attributable fraction values, are shown in Table 6. In total, there were an estimated 2,218,426 cases of occupational disease prevalent in 2016.

Table 6.

Excess Occupational Disease Burden^a in the United States and in New York State in 2016.^b

Illnesses^c	Population attributable fraction^a (%)	Prevalence rates, US^d	U.S. population age 18–84^e	Numbers of illnesses, US^e	Excess occupational disease burden, US	% Work-related illnesses, US	Prevalence rates,^d NYS	NYS population adults 18–84^f	Numbers of illnesses, NYS	Excess occupational disease burden, NYS	% Work-related illnesses, NYS
Infectious diseases (A and B)^g	8.8	0.1	238,918,622	328,119	28,874	0.08	0.01	15,029,160	20,233	1,781	0.08
Cancer (C and D, 0–99)^h	8.4	4.24	238,918,622	10,130,150	850,933	2.38	7	15,029,160	981,084	82,411	3.71
Mental disorders (F, X60–84, Y87)ⁱ	3.5, 0.4	18.9	238,918,622	45,466,214	1,581,689	4.42	18.9	15,029,160	2,860,049	99,496	4.48
Diseases of the nervous system (G and H)^j	6.7	0.57, 2.3, 16	238,918,622	45,988,041	3,081,199	8.61	2.5, 2.6, 12.9	15,029,160	2,436,637	163,255	7.36
Diseases of the circulatory system (I)^k	12.4	9	238,918,622	24,300,000	3,013,200	8.42	7.4	15,029,160	1,112,158	137,908	6.22
Diseases of the respiratory system (J)^l	11.7, 18.2, 100, 15.4	6.2, 8.3, .06	238,918,622	168,138,002	5,399,156	15.08	4.0, 9.5, .0006	15,029,160	2,038,614	335,359	15.12
Diseases of the digestive system (K)^m	2.1	5.7 1.9	238,918,622	18,157,815	381,314	1.07	5.7 1.9	15,029,160	1,142,216	23,987	1.08
Diseases of the genitourinary system (N)ⁿ	1.3	2.7	238,918,622	6,450,803	83,860	0.23	2	15,029,160	330,642	4,298	0.19
Diseases of the skin (L)^o	10.2	10.1	238,918,622	24,130,731	2,461,340	6.88	10.1	15,029,160	1,517,945	154,830	6.98
Diseases of the musculoskeletal system (M)^p	3.68	5.68,1.68,15.1	238,918,622	70,003,156	18,912,034	52.84	5.68 /1.68 /19.7	15,029,160	4,403,544	1,215,102	54.77
Total disease and occupational disease				413,093,080	35,793,599				16,843,121	2,218,426
Percent of illnesses attributable to occupational disease					8.66%		100			13.17%	100

Prevalence estimates for several selected diseases and conditions representing current major health and public health challenges are demonstrated in Table 7. The prevalence of all of these conditions (except opioid misuse) is quite high in the general population, and the health consequences of all are serious and potentially lethal. Through different mechanisms, work can contribute to all of these conditions. Attributable fractions demonstrating the occupational contribution to these specific conditions have not been developed. However, even a relatively small attributable fraction would represent thousands of cases and a significant burden of disease contributed to by workplace conditions.

Definitions for Analysis of Occupational Disease Burden^a for Table 6.

Illnesses^c	Definition and individual population attributable fraction (when applicable)	Population attributable fraction^a (%)
Infectious diseases (A and B)^g	All reportable (except STDs and congenital)	8.8
Cancer (C and D 0-99)^h	All sites	8.4
Mental disorders (F, X60–84, Y87)ⁱ	AMI 3.5; intentional self-harm and sequelae 0.4	3.5, 0.4
Diseases of the nervous system (G and H)^j	Parkinson's 9.2; Alzheimer's 2.3; hearing loss 7.2	6.7
Diseases of the circulatory system (I)^k	Cardiovascular diseases (CHD, HF, stroke)	12.4
Diseases of the respiratory system (J)^l	COPD 11.7; asthma 18.2; pneumoconiosis 100; idiopathic pulmonary fibrosis 15.4	11.7, 18.2, 100, 15.4
Diseases of the digestive system (K)^m	Gastric and duodenal ulcers 5.7; liver disease 1.9	2.1
Diseases of the genitourinary system (N)ⁿ	Chronic kidney disease	1.3
Diseases of the skin (L)^o	NHIS definition, ICD-10 L except for infection and cancer	10.2
Diseases of the musculoskeletal system(M)^p	Low back pain, carpal tunnel syndrome, arthritis	3.68

STD: sexually transmitted disease; AMI: any mental illness; CHD: congenital heart disease; HF: heart failure; COPD: chronic obstructive lung disease.

Nurminen and Karjalainen,⁸⁵ except for MSDs and skin disease, across all occupational diseases 6.7%.

Age 18–84, economically active population, older ages accommodate latency, analysis focused on 2016 with some exceptions due to availability of data.

Selected illnesses organized by ICD-10 code scheme.

Prevalence (period rates expressed as % of population).

Based on the 2016 U.S. population age 18–84, U.S. Census.

Based on the 2016 NYS population age 18–84, U.S. Census.

Karjalianen et al. (1998), National Public Health Institute Finland (1998), and Nuorti et al. (2000).

CDC, SEER, 24-year limited-duration prevalence counts for 2016 divided by the population for the US in 2016=13,725,579/323,400,000.

ⁱ

AMI as recognized by NIMH.

Sawitz et al.,⁹¹ Gorell et al.,⁹² Checkoway and Nelson,⁹³ and Sobel et al.⁹⁴

Tenkanen et al.,⁹⁵ Kawachi et al.,^96,97 Olsen and Kristensen,⁹⁸ Stern et al.,⁹⁹ Virtanen and Notkola,¹⁰⁰ and Bonita et al.¹⁰¹

^lSources: Coggon et al.,¹⁰² Isoaho et al.,^103,104 Hunting and Welch,¹⁰⁵ Euler et al.,¹⁰⁶ Karjalainen et al.,^107,108 Kogevinas et al.,¹⁰⁹ Torén et al.,¹¹⁰ Leino et al.,¹¹¹ Flodin et al.,¹¹² and Hubbard et al.¹¹³

Tüchsen et al.¹¹⁴ and Numunen and Karjalianen.¹¹⁵

ⁿ

U.S. Renal Data System chronic kidney disease in the US. NHANES participants equal to or over 20 14.8% in 2011 to 2014.

NHIS 1988 figure of 1.7% prevalence self-reported occupational dermatitis was used, contact dermatitis, photoreactive dermatitis, folliculitis and acne, contact urticaria, nail discoloration and dystrophy, and acro-osteolysis.

NHIS unadjusted prevalence among all employed adults 2013–2015, not including upper extremity MSDs (complaints of arm, neck, and/or shoulder), knees, cumulative trauma disorders, https://wwwn.cdc.gov/Niosh-whc/chart/nhis-sd/illness?OU=ARTH1&T=GE&V=R.

Table 7.

Adults with Health Conditions Expected to Contribute to Future Occupational Disease Diagnosis.^a

Illnesses	Prevalence rate, US^b	U.S. population age 18–84^c	Numbers of illnesses, US^d	Prevalence rate, NYS^b	NYS population^e	Numbers of illnesses, NYS
Diabetes	10.5	238,918,622	25,086,455	10.5	15,029,160	1,578,062
Hypertension	31.4	238,918,622	75,020,447	31.7	15,029,160	4,764,244
Obesity	30.1	238,918,622	71,914,505	25.5	15,029,160	3,832,436
Binge drinking in the past month	16.9	238,918,622	40,377,247	17.5	15,029,160	2,630,103
Currently smoking	17	238,918,622	40,616,166	14.2	15,029,160	2,134,141
Opioid misuse^e	4.6	238,918,622	10,933,000	3.7	15,029,160	553,073

US: United States; NYS: New York State.

BRFSS, prevalence rates, 2016 CDC division of population health: chronic disease indicators: explore by location: crude prevalence (%), adults ≥18.

Prevalence (period rates expressed as % of population).

Based on the 2016 U.S. population age 18–84, U.S. Census.

Based on the 2016 NYS population age 18–84, U.S. Census.

Substance Abuse and Mental Health Services Administration, misuse opioids (heroin or prescription pain relievers) in the past year age 18 and over, 2016.

Conclusions

Mortality and Morbidity

The occupational disease remains a significant cause of death and illness in NYS. Our estimates demonstrate that the percentage of all death in NYS attributable to occupational illness ranges from 3.3% to 4.7%, with men experiencing more than twice the deaths as women. Also, over 2 million working people are experiencing work-related illness (13.2% of the total disease prevalence). Finally, an expanded definition of occupational disease should include highly prevalent conditions that contribute to workers’ lack of health, especially because the connections between work and health for these conditions are well-documented.

Using the Landrigan/Markowitz methodology, the proportion of annual deaths attributable to occupational causes is actually higher than the proportion they found in the 1980s. Not surprisingly, using an expanded definition of occupational disease based on Nurminen and Karjalainen's work yields an estimate of occupational disease-related deaths 57% higher than the estimate using the Landrigan/Markowitz methods.

Non-fatal occupational diseases are also quite prevalent in NYS. Roughly half of the cases are musculoskeletal conditions due to chronic exposure to work characterized by some combination of repetition, forceful movements, awkward postures, and vibration. Only a relatively few of the total types of musculoskeletal diagnoses were included due to limitations in available data. Consequently, despite the high prevalence, the estimate is likely to be a substantial underestimate. This underscores the importance of these types of conditions in the current landscape of work.

More than three-quarters of illnesses originate in the musculoskeletal, respiratory, and nervous systems. Respiratory conditions included asthma, pneumoconiosis, chronic obstructive lung disease (COPD), and interstitial lung disease, all of which have well-known connections to various workplace exposures. The prominence of nervous system conditions is driven by the high prevalence of hearing loss.

The actual prevalence of work-related mental health conditions is likely severely underestimated by this data. Clinical experience evaluating individuals with work-related illnesses over a period of many years demonstrates the widespread occurrence of mental health issues.¹¹⁶ These can occur as a direct result of the nature of the work itself or as a consequence of being diagnosed with another occupational disease and all of the implications (social, financial, job, and career) that entails.⁶⁷ These effects are important in terms of their impact on the individual, but may not conform to the diagnostic criteria of a “mental illness,” or may not be formally recognized and diagnosed by the treating clinician.^117–140

A broadened definition of occupational disease allows for an exploration of how work may contribute to the major health challenges faced by modern society. For example, hypertension is a major risk factor for heart attack and stroke and is highly prevalent, especially among men, Black men in particular, with age-adjusted rates for white and black men reaching 26.5% and 30.3%, respectively.¹³⁸ Stressful psychosocial conditions of work have been identified as important contributors to the development of high blood pressure.^139,140 Many causes have been hypothesized for the rapidly increasing prevalence of obesity and diabetes.^22–30 Working conditions have appeared in the mix of factors considered, operating through several different potential mechanisms. Likewise, multiple mechanisms originating at work contribute to the epidemic of substance abuse, including alcohol, tobacco, and opiates.^55–62

The extent of the role work plays in these conditions is debated and only relatively recently received research attention. Further exploration may reveal a significantly more important role for work in some, or all of these conditions. Tables 6 and 7 illustrate the large numbers of people potentially affected. From a public health perspective, an important conclusion of this report is that the contribution of work should be considered and investigated for all of the major modern health issues.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Jeanette M. Zoeckler

Notes

Author Biographies

Michael Lax, MD, MPH, has been the Medical Director of the Occupational Health Clinical Center in Syracuse New York since 1988. He has been engaged in clinical care, teaching, and research in that role. The Center is a program of the Department of Family Medicine at the State University of New York, Upstate Medical University and Michael is a Professor in the Department.

Jeanette Zoeckler, PhD, MPH, is the Director of the Occupational Health Clinical Center, SUNY Upstate Medical University, Syracuse, NY. In addition to oversight of clinical and preventive programming, she designs and implements collaborative public health initiatives that focus on occupational health inequities. She has published on return-to-work, low-wage work conditions, work-related stressors, home care work policy, work and aging, and occupational epidemiology. She completed her MPH from SUNY Upstate Medical University (2011) and her PhD in Social Science at Syracuse University (2017).

References

Landrigan

Markowitz

. Proposal for a statewide network of occupational disease diagnosis and prevention centers. Report to the New York State Legislature. New York, NY: Environmental and Occupational Medicine, Department of Community Medicine. Mount Sinai School of Medicine of the City University of New York, 1987.

Tuminaro

. Organizing for a statewide network of occupational disease diagnostic centers. New Solut 1991; 1: 18–19.

New York State workers’ compensation law. Section 151, https://www.nysenate.gov/legislation/laws/ WKC/151 (accessed 19 January 2020).

New York State Department of Health. Occupational health clinic network—prevention and protection for the NYS workforce, https://www.health.ny.gov/environmental/workplace/clinic.htm (2018, accessed 19 January 2021).

Lax

. The occupational health clinical center in New York state: Achievements, prospects, and constraints. In: Levenstein

Wooding

(eds) Work, health and environment. New York: Guilford Press, 1997, pp.363–384.

Lax

. Occupational health in central New York: A publicly funded occupational health clinical center after 25 years. Rev Bras Saúde Ocup 2013; 38: 149–161.

Lax

. New York State’s COSH movement: A brief history. New Solut 2018; 28: 202–226.

Guidotti

. Chapter 18. Occupational diseases. In: Handbook of occupational and environmental medicine: Principles, practice, populations, and problem-solving. 2nd ed. Santa Barbara, CA: Praeger, 2020, pp.745–746.

Oppliger

Seixas

. What makes a disease ‘occupational’? Ann Work Expo Health 2017; 61: 135–136.

10.

Liddell

. The interaction of asbestos and smoking in lung cancer. Ann Occup Hyg 2001; 45: 341–356.

11.

Berry

Liddell

. The interaction of asbestos and smoking in lung cancer: A modified measure of effect. Ann Occup Hyg 2004; 48: 459–462.

12.

Boffetta

. Epidemiology of environmental and occupational cancer. Oncogene 2004; 23: 6392–6403.

13.

Vlanovich

Sood

. Update on occupational lung diseases: A narrative review. Pulm Ther 2019; 7: 75–87.

14.

Vandenplas

Godet

Hurdubaea

, et al. Severe occupational asthma: Insights from a multicenter European cohort. J Allergy Clin Immunol Pract 2019; 7: 2309–2318.

15.

Logar-Henderson

MacLeod

Arrandale

, et al. Adult asthma among workers in Ontario. Results from the occupational disease surveillance system. Ann Am Thorac Soc 2019; 16: 563–571.

16.

Beach

Chen

Cherry

. How physicians allocate causation: A scenario study with factorial design. Occup Med 2012; 62: 07–412.

17.

Karasek

Theorell

. Healthy work: Stress, productivity, and the reconstruction of working life. New York: Basic Books, 1990.

18.

Siegrist

. Adverse health effects of high-effort/low-reward conditions. J Occup Health Psychol 1996; 1: 27–41.

19.

Schnall

Pieper

Schwartz

, et al. The relationship between ‘job strain,’ workplace diastolic blood pressure, and left ventricular mass index: Results of a case-control study. JAMA 1990; 263: 1929–1935.

20.

Landsbergis

Schnall

Warren

, et al. Association between ambulatory blood pressure and alternative formulations of job strain. Scand J Work Environ Health 1994; 20: 349–363.

21.

Kivimäki

Nyberg

Batty

, et al. Job strain as a risk factor for coronary heart disease: A collaborative meta-analysis of individual participant data. Lancet 2012; 380: 1491–1497.

22.

Jarczok

Loerbroks

, et al. Work stress is associated with diabetes and prediabetes: Cross-sectional results from the MIPH industrial cohort studies. Int J Behav Med 2013; 20: 495–503.

23.

Nowrouzi-Kia

. Impact of diabetes mellitus on occupational health outcomes in Canada. Int J Occup Environ Med 2017; 8: 96–108.

24.

Kivimaki

Virtanen

Kawachi

, et al. Long working hours, socioeconomic status, and the risk of incident type 2 diabetes: A meta-analysis of published and unpublished data from 222 120 individuals. Lancet Diabetes Endocrinol 2015; 3: 27–34.

25.

Poulsen

Cleal

Clausen

, et al. Work, diabetes and obesity: A seven-year follow-up study among Danish health care workers. PLoS One 2014; 9: e103425.

26.

Vanni

Bussuan

Rombaldi

, et al. Endocrine disruptors and the induction of insulin resistance. Curr Diabetes Rev 2020; 17(7): e102220187107. doi:10.2174/157339981666620

27.

Lian

Sun

Guan

, et al. Effect of changing work stressors and coping resources on the risk of type 2 diabetes: The OHSPIW cohort study. Diabetes Care 2018; 41: 453–460.

28.

Mutambudzi

Javed

. Job strain as a risk factor for incident diabetes mellitus in middle and older age U. S. Workers. J Gerontol B Psychol Sci Soc Sci 2016; 71: 1089–1096.

29.

Mutambudzi

Siegrist

Meyer

, et al. Association between effort-reward imbalance and self-reported diabetes mellitus in older U.S. workers. J Psychosom Res 2018; 104: 61–64.

30.

Nyberg

Fransson

Heikkil

, et al. Job strain as a risk factor for type 2 diabetes: A pooled analysis of 124,808 men and women. Diabetes Care 2014; 37: 2268–2275.

31.

Schulte

Wagner

Ostry

, et al. Work, obesity, and occupational safety and health. Am J Public Health 2007; 97: 428–436.

32.

Roos

Lallukka

Rahkonen

, et al. Working conditions and major weight gain: A prospective cohort study. Arch Environ Occup Health 2013; 68: 166–172.

33.

Pandalai

Schulte

Miller

. Conceptual heuristic models of the interrelationships between obesity and the occupational environment. Scand J Work Environ Health 2013; 39: 221–232.

34.

Nyberg

Heikkila

Fransson

, et al. Job strain in relation to body mass index: Pooled analysis of 160,000 adults from 13 cohort studies. J Intern Med 2012; 272: 65–73.

35.

Choi

Schnall

Yang

, et al. Sedentary work, low physical job demand, and obesity in US workers. Am J Ind Med 2010; 53: 1088–1101.

36.

Nobrega

Champagne

Abreu

, et al. Obesity/ overweight and the role of working conditions: A qualitative, participatory investigation. Health Promot Pract 2016 ; 17: 127–136.

37.

Magee

Caputi

Stefanic

, et al. Occupational factors associated with 4-year weight gain in Australian adults. J Occup Environ Med 2010; 52: 977–981.

38.

Iversen

Strandberg-Larsen

Prescott

, et al. Psychosocial risk factors, weight changes and risk of obesity: The Copenhagen city heart study. Eur J Epidemiol 2012; 27: 119–130.

39.

Marchand

Beauregard

Blanc

M-E

. Work and non-work stressors, psychological distress and obesity: Evidence from a 14-year study on Canadian workers. BMJ Open 2015; 5: e006285.

40.

Solovieva

Lallukka

Virtanen

, et al. Psychosocial factors at work, long work hours, and obesity: A systematic review. Scand J Work Environ Health 2013; 39: 241–258.

41.

Brunner

Chandola

Marmot

. Prospective effect of job strain on general and central obesity in the Whitehall II study. Am J Epidemiol 2007; 165: 828–837.

42.

Shrestha

Pedisic

Neil-Sztramko

, et al. The impact of obesity in the workplace: A review of contributing factors, consequences and potential solutions. Curr Obes Rep 2016; 5: 344–360.

43.

Shulte

Wagner

Downes

, et al. A framework for the concurrent consideration of occupational hazards and obesity. Ann Occup Hyg 2008; 52: 555–566.

44.

National Research Council (US) and Institute of Medicine (US) Panel on Musculoskeletal Disorders and the Workplace. Musculoskeletal disorders and the workplace: Low back and upper extremities. Washington (DC): National Academies Press (US), 2001.

45.

Hulshof

CTJ

Pega

Neupane

, et al. The prevalence of occupational exposure to ergonomic risk factors: A systematic review and meta-analysis from the WHO/ILO joint estimates of the work-related burden of disease and injury. Environ Int 2021; 146: 106157.

46.

Foley

Silverstein

. The long-term burden of work-related carpal tunnel syndrome relative to upper-extremity fractures and dermatitis in Washington state. Am J Ind Med 2015; 58: 1255–1269.

47.

Siegrist

. Effort-reward imbalance at work and cardiovascular diseases. Int J Occup Med Environ Health 2010; 8: 1–7.

48.

Tsutsumi

Kayaba

Ishikawa

. Impact of occupational stress on stroke across occupational classes and genders. Soc Sci Med 2011; 72: 1652–1658.

49.

Szerencsi

van Amelsvoort

Viechtbauer

, et al. The association between study characteristics and outcome in the relation between job stress and cardiovascular disease—a multilevel meta-regression analysis. Scand J Work Environ Health 2012; 38: 489–502.

50.

Kalleberg

. Precarious work, insecure workers: Employment relations in transition. Am Sociol Rev 2009; 74: 1–22.

51.

Lewchuk

WMC

Wolff

. Working without commitments: The health effects of precarious employment. Montreal: McGill-Queen’s University Press, 2011.

52.

Doussard

. Degraded work: The struggle at the bottom of the market. Minneapolis: University of Minnesota Press, 2013.

53.

Weil

. The fissured workplace: Why work became so bad for so many and what can be done to improve it. Cambridge, MA: Harvard University Press, 2014.

54.

Bernhardt

Milkman

Theodore

, et al. Broken laws, unprotected workers: violations of employment and laws in America’s cities, https://www.nelp.org/publication/broken-laws-unprotected-workers-violations-of-employment-and-labor-laws-in-Americas-cities/ (2009, accessed 20 January 2021).

55.

Muntaner

Solar

Vanroelen

, et al. Unemployment, informal work, precarious employment, child labor, slavery, and health inequalities: Pathways and mechanisms. Int J Health Serv 2010; 40: 281–295.

56.

Brophy

Keith

Hurley

. Breaking point: Violence against long-term care staff. New Solut 2019; 29: 10–35.

57.

Brophy

Keith

Hurley

. Assaulted and unheard: Violence against healthcare staff. New Solut 2018; 27: 581–606.

58.

Tausig

Fenwick

. Work and mental health in social context. New York: Springer, 2011.

59.

Marchand

Blanc

. Occupation, work organization conditions and alcohol misuse in Canada: An 8-year longitudinal study. Subst Use Misuse 2011; 46: 1003–1014.

60.

Kowalski-McGraw

Green-McKenzie

Pandalai

, et al. Characterizing the interrelationships of prescription opioid and benzodiazepine drugs with worker health and workplace hazards. J Occup Environ Med 2017; 59: 1114–1126.

61.

Choi

. Opioid use disorder, job strain, and high physical job demands in US workers. Int Arch Occup Environ Health 93(5): 577–588.

62.

Shaw

Roelofs

Punnett

. Work environment factors and prevention of opioid-related deaths. Am J Public Health 2020; 110: 1235–1241.

63.

de Lange

Kompier

Taris

, et al. A hard day’s night: A longitudinal study on the relationships among job demands and job control, sleep quality and fatigue. J Sleep Res 2009; 18: 374–383.

64.

Wang

Armstrong

Cairns

, et al. Shift work and chronic disease: The epidemiological evidence. Occup Med 2011; 61: 78–89.

65.

Gumenyuk

Roth

Drake

. Circadian phase, sleepiness, and light exposure assessment in night workers with and without shift work disorder. Chronobiol Int 2012; 29: 928–936.

66.

Zhao

Bogossian

Turner

. The effects of shift work and interaction between shift work and overweight/obesity on low back pain in nurses: Results from a longitudinal study. J Occup Environ Med 2012; 54: 820–825.

67.

Burgard

Ailshire

. Putting work to bed: Stressful experiences on the job and sleep quality. J Health Soc Behav 2009; 50: 476–492.

68.

Knudsen

Ducharme

Roman

. Job stress and poor sleep quality: Data from an American sample of full-time workers. Soc Sci Med 2007; 64: 1997–2007.

69.

Lax

Klein

. More than meets the eye: Social, economic and emotional impacts of work-related injury and illness. New Solut 2008; 18: 343–360.

70.

LaMontagne

Keegel

Louie

, et al. Job stress as a preventable upstream determinant of common mental disorders: A review for practitioners and policy-makers. Adv Ment Health 2010; 9: 17–35.

71.

Schulte

Pana-Cryan

Schnorr

, et al. An approach to assess the burden of work-related injury, disease, and distress. Am J Public Health 2017; 107: 1051–1057.

72.

Schulte

Guerin

Schill

, et al. Considerations for incorporating “well-being” in public policy for workers and workplaces. Am J Public Health 2015; 105: e31–e44.

73.

National Academies of Sciences, Engineering, and Medicine. A smarter national surveillance system for occupational safety and health in the 21st century. Washington, DC: The National Academies Press, 2018.

74.

Rosenman

Kalush

Reilly

, et al.

How much work-related injury and illness is missed by the current national surveillance system?

J Occup Environ Med 2006; 48: 357–365.

75.

Galizzi

Miesmaa

Punnett

, et al. Injured workers’ underreporting in the health care industry: An analysis using quantitative, qualitative, and observational data. Ind Relat 2010; 49: 22–43.

76.

Grey

. Workers’ Compensation in New York State: State of the system. NY, USA: Grey & Grey, 2016.

77.

Dworsky

Broten

. How can workers’ compensation systems promote occupational safety and health? Stakeholders views on policy and research priorities. Santa Monica, CA: Rand Corporation, https://www.rand.org/t/RR2566 (2018, accessed May 25, 2021).

78.

Morantz

. Workers’ compensation at a crossroads: back to the future or back to the drawing board? In: Pound Institute/Rutgers/Northeastern symposium, the demise of the grand bargain: compensation for injured workers in the 21st century, 2016. http://poundinstitute.org/content/2016- symposium-papers (accessed 25 May 2021).

79.

Morantz

Bodson

Levine

, et al. Economic incentives in workers’ compensation: A holistic, international perspective. Rutgers Univ Law Review 2016; 69: 1015–1080.

80.

McLaren

Baldwin

. Workers’ compensation: Benefits, coverage, and costs (2015 data). Washington, DC: National Academy of Social Insurance, 2017.

81.

Spieler

Wagner

. Counting matters: Implications of undercounting in the BLS survey of occupational injuries and illnesses. Am J Ind Med 2014; 57: 1077–1084.

82.

Leigh

Marcin

. Workers’ compensation benefits and shifting costs for occupational injury and illness. J Occup Environ Med 2012; 54: 445–450.

83.

Leigh

Robbins

. Occupational disease and workers’ compensation: Coverage, costs, and consequences. Milbank Q 2004; 82: 689–721.

84.

Executive correspondence with NYS Workers’ Compensation Board, Schenectady, NY 12305, 28 September 2018.

85.

Numinen

Karjalainen

. Epidemiologic estimate of the proportion of fatalities related to occupational factors in Finland. Scand J Work Environ Health 2001; 27: 161–213.

86.

Steenland

Armstrong

. An overview of methods for calculating the burden of disease due to specific risk factors. Epidemiology 2006; 17: 512–519.

87.

Steenland

Burnett

Lalich

, et al. Dying for work: The magnitude of US mortality from selected causes of death associated with occupation. Am J Ind Med 2003; 4: 461–482.

88.

Driscoll

Takala

Steenland

, et al. Review of estimates of the global burden of injury and illness due to occupational exposures. Am J Ind Med 2005; 48: 491–502.

89.

Takala

Hämäläinen

Saarela

, et al. Global estimates of the burden of injury and illness at work in 2012. J Occup Environ Hyg 2014; 11: 326–337.

90.

Hämäläinen

Takala

Saarele

. Global estimates of fatal work-related diseases. Am J Ind Med 2007; 50: 28–41.

91.

Sawitz

Checkoway

Loomis

. Magnetic field exposure and neurodegenerative disease mortality among electric utility workers. Epidemiology 1998; 9: 398–404

92.

Gorell

Johnson

Rybicki

Peterson

Richardson

. The risk of Parkinson’s disease with exposure to pesticides, farming, well water, and rural living. Neurology 1998; 50: 1346–1350.

93.

Checkoway

Nelson

. Epidemiologic approaches to the study of Parkinson’s disease etiology. Epidemiology 1999; 10; 327–336

94.

Sobel

Danipour

Sulkava

, et al. Occupations with exposure to electromagnetic fields: A possible risk factor for Atzheimer’s disease. Am J Epidemiol 1995; 142: 515–524.

95.

Tenkanen

Sjöblom

Kalimo

Alikoski

Härmä

. Shift work, occupation and coronary heart disease over 6 years of follow-up in the Helsinki Heart Study. Scand J Work Environ Health 1997; 23: 257–265

96.

Kawachi

Colditz

Stampher

, et al. Prospective study of shift work and risk of coronary heart disease in women. Circulation 1995; 92: 3178–3182

97.

Kawachi

Colditz

Speizer

, et al. A prospective study of passive smoking and coronary heart disease. Circulation 1997; 95: 2374–2379.

98.

Olsen

Kristensen

. Impact of work environment on cardiovascular diseases in Denmark. J Epidemiol Community Health 1991; 45: 4–10.

99.

Stern

Halperin

Hornung

Ringenburg

McCammon

. Heart disease mortality among bridge and tunnel officers exposed to carbon monoxide. Am J Epidemiol 1988; 128: 1276–1288.

100.

Virtanen

Notkola

. Socioeconomic inequalities in cardiovascular mortality and the role of work: a register study of Finnish men. Int J Epidemiol 2002 Jun; 31: 614–621. doi:10.1093/ije/31.3.614. PMID: 12055163.

101.

Bonita

Duncan

Truelsen

Jackson

Beagelhole

. Passive smoking as well as active smoking increases the risk of acute stroke. Tob Control 1999; 8: 156–160.

102.

Coggon

Inskip

Winter

Pannett

. Lobar pneumonia: An occupational disease in welders. Lancet 1994; 344: 41–43.

103.

Isoaho

Puolijoki

Huhti

Kivel

S-L

Tala

. Prevalence of asthma in elderly Finns. J Clin Epidemiol 1994; 47: 1109–1118

104.

Isoaho

Puolijoki

Huhti

Kivelä

S-L

Laippala

Tala

. Prevalence of chronic obstructive pulmonary disease in elderly Finns. Respir Med 1994; 88: 571–580.

105.

Hunting

Welch

. Occupational exposure to dust and lung disease among sheet metal workers. Br J Ind Med 1993; 50: 432–442.

106.

Euler

Abbey

Magie

Hodgkin

. Chronic obstructive pulmonary disease symptom effects of long-term cumulative exposure to ambient levels of total suspended particulates and sulfur dioxide in California Seventh-Day Adventist residents. Arch Environ Med 1987; 42: 213—22.

107.

Karjalainen

Aalto

Jolanki

Keskinen

Savela

. Occupational diseases in Finland in 1996: new cases of occupational diseases reported to the Finnish Register of Occupational Diseases. Helsinki: Finnish Institute of Occupational Health, 1998.

108.

Karjalainen

Kurppa

Virtanen

Keskinen

Nordman

. Incidence of occupational asthma by occupation and industry in Finland. Am J Ind Med 2000; 37: 451–458

109.

Kogevinas

Antó

Sunyer

, et al. Occupational asthma in Europe and other industrialised areas: a population-based study. Lancet 1999; 353: 1750–1754.

110.

Torén

Balder

Brisman

, et al. The risk of athma in relation to occupational exposures: a case-control study from a Swedish city. Eur Respir J 1999; 13: 469–501.

111.

Leino

Tammilehto

Paakkulainen

Orjala

Nordman

. Occurrence of asthma and chronic bronchitis among female hairdressers. J Occup Environ Med 1997; 39: 534–539.

112.

Flodin

Jönsson

Ziegler

Axelson

. An epidemiologic study of bronchial asthma and smoking. Epidemiology 1995; 6: 503–505.

113.

Hubbard

Lewis

Richards

Johnston

Britton

. Occupational exposure to metal or wood dust and aetiology of cryptogenic fibrosing alveolitis. Lancet 1996; 347: 284–289.

114.

Tüchsen

Jeppesen

Bach

. Employment status, nondaytime work and gastric ulcer in men. Int J Epidemiol 1994; 23: 365–370.

115.

Nurminen

Karjalainen

. Epidemiologic estimate of the proportion of fatalities related to occupational factors in Finland. Scand J Work Environ Health 2001;27(3):161–213. doi:10.5271/sjweh.

116.

United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC), and National Center for Health Statistics (NCHS). Compressed mortality file. https://wonder.cdc.gov/wonder/help/cmf.html (accessed 9 May 2021).

117.

Belkic

Savic

. Job stressors and mental health: A proactive clinical perspective. Hackensack, NJ: World Scientific Publishing Co. Pte. Ltd, 2013.

118.

Marchand

Durand

. Psychological distress, depression, and burnout: Similar contribution of the job demand-control and job demand-control-support models. JOEM 2011; 53: 185–189.

119.

Asfaw

Boden

. Impact of workplace injury on opioid dependence, abuse, illicit use and overdose: A 36-month retrospective study of insurance claims. Occup Environ Med 2020; 77: 648–653.

120.

López Gómez

Williams

JAR

Boden

, et al. The relationship of occupational injury and use of mental health care. J Safety Res 2020; 9: 227–232.

121.

López Gómez

Sabbath

Boden

, et al. Organizational and psychosocial working conditions and their relationship with mental health outcomes in patient-care workers. J Occup Environ Med 2019; 61: e480–e485.

122.

Sabbath

Williams

JAR

Boden

, et al. Mental health expenditures: Association with workplace incivility and bullying among hospital patient care workers. J Occup Environ Med 2018; 60: 737–742.

123.

Bültmann

Kant

Van den Brandt

, et al. Psychosocial work characteristics as risk factors for the onset of fatigue and psychological distress: Prospective results from the Maastricht cohort study. Psychol Med 2002; 32: 333–345.

124.

Nieuwenhuijsen

Bruinvels

Frings-Dresen

. Psychosocial work environment and stress-related disorders, a systematic review. Occup Med 2010; 60: 277–286.

125.

Harvey

Modini

Joyce

, et al. Can work make you mentally ill? A systematic meta-review of work-related risk factors for common mental health problems. Occup Environ Med 2017; 74: 301–310.

126.

Milner

Witt

LaMontagne

, et al. Psychosocial job stressors and suicidality: A meta-analysis and systematic review. Occup Environ Med 2018; 75: 245–253.

127.

Watanabe

Imamura

Kawakami

. Working hours and the onset of depressive disorder: A systematic review and meta-analysis. Occup Environ Med 2016; 73: 877–884.

128.

Laine

Saastamoinen

Lahti

, et al. The associations between psychosocial working conditions and changes in common mental disorders: A follow-up study. BMC Public Health 2014; 11: 588.

129.

Taniguchi

Takaki

Hirokawa

, et al. Associations of workplace bullying and harassment with stress reactions: A two-year follow-up study. Ind Health 2016; 54: 131–138.

130.

Rugulies

Aust

Madsen

. Effort-reward imbalance at work and risk of depressive disorders. A systematic review and meta-analysis of prospective cohort studies. Scand J Work Environ Health 2017; 43: 294–306.

131.

Theorell

Hammarström

Aronsson

, et al. A systematic review including meta-analysis of work environment and depressive symptoms. BMC Public Health 2015; 15: 738.

132.

Fan

Mustard

Smith

. Psychosocial work conditions and mental health: Examining differences across mental illness and well-being outcomes. Ann Work Expo Health 2019; 63: 546–559.

133.

Duchaine

Aubé

Gilbert-Ouimet

, et al. Effect of psychosocial work factors on the risk of depression: A protocol of a systematic review and meta-analysis of prospective studies. BMJ Open 2019; 9: e033093.

134.

Duchaine

Aubé

Gilbert-Ouimet

, et al. Psychosocial stressors at work and the risk of sickness absence due to a diagnosed mental disorder: A systematic review and meta-analysis. JAMA Psychiatry 2020; 77: 842–851.

135.

Sirviö

Jokelainen

, et al. Precariousness and discontinuous work history in association with health. Scand J Public Health 2012; 40: 360–367.

136.

Ervasti

Vahtera

Virtanen

, et al. Is temporary employment a risk factor for work disability due to depressive disorders and delayed return to work? The Finnish public sector study. Scand J Work Environ Health 2014; 40: 343–352.

137.

László

Pikhart

Kopp

, et al. Job insecurity and health: A study of 16 European countries. Soc Sci Med 2010; 70: 867–874.

138.

Villarroel

Blackwell

Jen

. National Center for Health Statistics, National Health Interview Survey. Tables of summary health statistics for U.S. adults: 2018, http://www.cdc.gov/nchs/ nhis/SHS/tables.htm (2019, accessed 21 May 2021).

139.

Karasek

Baker

Marxer

, et al. Job decision latitude, job demands, and cardiovascular disease: A prospective study of Swedish men. Am J Public Health 1981; 71: 694–705.

140.

Siegrist

. Adverse health effects of high effort—low reward conditions at work. J Occup Health Psych 1996; 1: 27–41.