Assessing the economic impact of obesity and overweight on employers: identifying opportunities to improve work force health and well-being

The nation’s obesity prevalence causes a significant economic burden on employers and employees, increasing the costs of goods and services while decreasing overall productivity and economic well-being. Excess body weight is associated with a heightened risk of heart disease, type 2 diabetes, and other diseases [1,2,3,4]. Furthermore, obesity increases susceptibility to severe influenza and COVID-19 [5,6,7]. These health issues lead to higher healthcare and disability expenses [8,9,10,11], more days of work missed due to illness or injury [10,11,12,13,14], and reduced workforce productivity [14, 15]. The health consequences of obesity contribute to lower levels of employment and premature mortality, leading to a diminished labor force [16,17,18]. In physically demanding occupations, the fitness challenges associated with obesity reduce the recruiting pool.

Of the estimated 169.3 million people employed in the U.S., 158 million were civilian employees on nonfarm payrolls, the focus of this study [19]. Approximately 46.9 million (30%) of these workers had a body mass index (BMI) that met the criteria for obesity (BMI ≥ 30), and 53.8 million (34%) met the criteria for overweight (25 ≤ BMI < 30) [20, 21]. The workforce exhibits substantial heterogeneity, resulting in geographic, industry-specific, and worker-characteristic variations in the economic implications of obesity and its solutions. While many studies have explored individual economic components of obesity, comprehensive assessments from the employer’s perspective on the economic costs of obesity and the value of prevention and treatment are limited.

The primary objective of this study is to quantitatively assess the workforce and economic impact of excess body weight from the employer’s perspective. This includes an assessment by economic sector, presenting data at the national level, per employee with obesity or overweight, and for a hypothetical nationally representative employer with 10 000 employees. Detailed estimates for seven major industries (Construction, Education & Health, Financial Activities, Government, Manufacturing, Professional & Business Services, and Transportation & Utilities) are provided.

The study also explores the estimated value of treating obesity. Evidence-based approaches to treat obesity include intensive lifestyle modification programs and medical interventions, such as obesity medications (OMs) and metabolic/bariatric surgery [17, 22,23,24,25,26,27,28,29]. We modeled the reduced incidence of obesity related diseases and estimated medical savings associated with achieving and maintaining weight loss ranging from 5% up to 25%. Information on the costs of obesity and potential cost offsets by treating obesity can help inform employer initiatives around obesity prevention and treatment.

A Microsoft Excel®-based model was developed to estimate the annual economic impact of obesity and overweight, encompassing both direct medical costs and indirect costs related to productivity loss across the non-farm civilian workforce. The analysis combined data from published reports and studies with original analysis of national databases.

Costs were presented at the national level, per employee with obesity and overweight, and for a hypothetical nationally representative employer with 10,000 employees across all industries as well as the seven major industries—Construction; Education & Health Services; Financial Activities; Government; Manufacturing; Professional & Business Services; and Transportation & Utilities—by combining different cost components associated with excess weight. All data were analyzed using R software version 4.3.2.

Study sample

Person-level analyses were conducted using pooled adult sample records from the National Health Interview Survey (NHIS) and the Medical Expenditure Panel Survey (MEPS). These analyses compared health and economic outcomes for employed adults with obesity or overweight relative to their peers with a healthy weight (18.5 ≤ BMI < 25) [20]. The NHIS is an annual survey of a nationally representative sample of the U.S. civilian noninstitutionalized population. Data collected include self-reported demographics, health risk factors, and work-related variables (e.g., employment status, industry, missed workdays due to illness or injury, and days with reduced productivity due to illness or injury). The MEPS, a subset of NHIS respondents, includes additional survey questions and medical record extraction to gather data on healthcare utilization and expenditures.

Prevalence of overweight and obesity

We estimated the prevalence of obesity and overweight among adults by employment status, industry, and occupation using self-reported height and weight from the 2015-2018 combined NHIS files (n = 268,527). Self-reported height and weight can lead to systematic misclassification of BMI categories, and the inherent skewness of BMI distributions may result in underestimation of obesity prevalence [30].

Medical costs

A representative sample of employees from the US nonfarm civilian workforce, derived from the 2018-2021 combined MEPS files (n = 53,577), was used for this analysis. Due to the skewed nature of annual medical expenditures, with many individuals having zero expenditures and some having very large expenditures, we used a two-step process to estimate direct medical costs associated with overweight and obesity. This involved logistic regression and a generalized linear model with a log link applied to the combined dataset [3, 31]. The dependent variable was annual medical expenditures scaled to 2023 dollars using the medical component of the Consumer Price Index. Explanatory variables included body weight category (healthy, overweight, obesity), age group, gender, race, Hispanic ethnicity, marital status, industry, and year. The analysis excluded women who had pregnancy or childbirth during the year. Data limitations prevented identifying covered adult dependents of a person employed in a particular economic sector. Therefore, for modeling, we assume that excess medical costs associated with obesity and overweight among covered dependents is the same as the impact for the employed adult members. Research finds that married couples and domestic partners share many of the same disease risk factors and behaviors (e.g., smoking, diet, and physical activity level) [32, 33]. Furthermore, they generally have similar socioeconomic characteristics and share the same healthcare plan.

Non-medical direct and indirect costs

Obesity is linked to increased rates of work absenteeism (missed workdays) and presenteeism (reduced productivity while at work), as well as higher payments for disability and Workers’ Compensation programs [11, 13, 14, 34]. Employers may incur direct costs for absenteeism, such as wages paid to absent employees, worker replacement expenses (e.g., overtime pay or temporary worker hiring), and administrative costs. Indirect costs include diminished team productivity, safety concerns, lower service or product quality due to understaffing, and potential burnout or poor morale among employees covering for an absent or less productive coworker [35,36,37]. Overweight is weakly associated with increased absenteeism and was excluded from our cost calculations.

A 2023 study, examining MarketScan data on 719 482 employees with and without obesity between January 2015 and December 2019, estimates that obesity raises annual absenteeism costs by $891 (reaching $1036 for employees with class 3 obesity) relative to employees with healthy weight [11, 34]. Notably, these estimates consider only employee wages when calculating the productivity cost of missed workdays. Previous studies have suggested using wage multipliers to estimate the total economic cost of absenteeism from the employer’s perspective [13, 38,39,40]. This wage multiplier accounts not only for the immediate financial loss associated with absenteeism but also extends its scope to encompass broader repercussions. Our model employs a wage multiplier of 1.97 times the average wage to estimate productivity loss due to absenteeism [13]. Therefore, the $891 average annual cost of obesity-associated absenteeism based on employee wages translates to an average annual cost of $1755 per person with obesity for employers.

To estimate how costs associated with absenteeism vary by industry, we used Poisson regression analysis of pooled 2013–2018 NHIS data (n = 33,216), modeling annual workdays missed due to illness or injury while controlling for age group, race/ethnicity, gender, industry, and year. We then adjusted the national average to account for variation across industries in the number of obesity-related missed workdays and average earnings.

To estimate costs related to presenteeism, we used logistic regression analysis of pooled 2013-2018 NHIS data (n = 53 693), translating limited work capacity into a presenteeism measure. Among employed adults, 7.7% of NHIS respondents with obesity reported being “somewhat limited” in the kind and amount of work they could do due to physical, mental, or emotional problems. In comparison, 5.2% of employees with overweight and 5.0% with healthy weight reported similar limitations. After adjusting for demographics using logistic regression, obesity and overweight are associated with a 2.6 percentage point and 0.9 percentage point increase, respectively, in employees reporting limited work productivity. We use these percentages as a proxy for presenteeism (with results varying by industry).

For comparison, one study estimates diabetes-attributable presenteeism equates to a 6.6% decline in productivity [41]. A 2017 review of nine studies found that presenteeism costs per worker per year ranged from negative $776 to $2020 for overweight (midpoint = $622) and from $14 to $5304 for obesity (midpoint = $2659), relative to a healthy weight population and adjusted to 2023 dollars [14]. These studies used earnings as a proxy for the value of productivity, and when comparing these midpoint estimates to average earnings among the nonfarm civilian workforce, this equates to about a 4.4% decline in productivity associated with obesity and a 1.0% decline associated with overweight. A 2008 study among manufacturing employees (n = 341) reported a 4.2% health-related reduction in productivity among workers with BMI ≥ 35 (class 2 or class 3 obesity), with this loss being 1.2% higher than for other workers (BMI < 35) [42].

The impact of presenteeism measured using lost employee wages will underestimate the cost to employers, as employees’ diminished productivity can result in suboptimal work quality and output. As with modeling absenteeism, a wage multiplier accounts for the immediate financial loss associated with presenteeism and extends to the indirect costs to employers, including factors such as team cohesion, knowledge transfer, and project continuity [13, 43]. Our model employs a published wage multiplier of 1.54 times the average wage to calculate productivity costs due to presenteeism [13].

In the aforementioned study utilizing MarketScan data, obesity is associated with higher annual employer costs of $623 for short-term disability, $41 for long-term disability, and $112 for Workers’ Compensation Program payments per employee with obesity, relative to employees with a healthy weight with costs increasing with each higher BMI category [11, 34]. These findings serve as the foundation for our national estimates regarding the financial burden of disability and workers’ compensation attributable to obesity. Injury risk and associated costs vary across industries due to specific risk factors, demographic disparities, and economic influences. To model variation across industries in disability and workers’ compensation costs, we analyzed NHIS data from 2013 to 2018 using logistic regression to estimate the likelihood of injury claims among employees categorized by weight and industry while controlling for demographics and year of data collection. Further analysis of MEPS data, linked to NHIS, assessed variation in workers’ compensation payments per incident across industries. By combining industry-specific variations in injury risk and compensation costs per incident and applying them to average industry costs for disability and workers’ compensation payments, obesity-related expenses per worker were estimated by industry.

To model the impact of obesity and overweight across industry sectors, we incorporated industry-specific costs, accounting for variations in workforce demographics, earnings, employer insurance coverage, and occupational risks. Key national parameters and model assumptions are summarized in Supplementary Table A1.

Potential savings

To demonstrate the value of treating obesity, we utilized a published computer simulation model, the Disease Prevention & Treatment Microsimulation Model (DPTMM) [44,45,46,47,48,49,50]. Drawing on a combination of public datasets, published studies, and clinical trials, the model allows for detailed predictions of how changes in key biometric markers, such as body weight, blood pressure, cholesterol, and HbA1c, affect the future risk of obesity-related diseases, including type 2 diabetes, hypertension, coronary heart disease, heart attack, and stroke. This allows for the projection of treatment impacts on the reduction of disease incidence and severity and associated direct and indirect costs. The simulation used a constructed population file that is representative of the workforce and adult dependents by industry sector, with adults with obesity in NHIS 1:1 matched to adults with obesity in NHANES based on propensity scores calculated from factors including BMI, age, gender, race/ethnicity, and marital status [51]. NHIS contains data on industry and the presence of select diseases, while NHANES contains data on metabolic markers. The constructed population file is representative of the workforce and adult dependents, by industry sector. The simulation estimated annual clinical improvements and healthcare costs associated with achieving body weight loss of up to 5%, 10%, 15%, 20%, and 25% in the first year and maintaining the effect over the next four years. More information about the DPTMM can be found in the Supplementary.

Prevalence of overweight and obesity

Among the 169.3 million people employed in October 2023, an estimated 30% (50.4 million) had obesity, while 34% (59.7 million) had overweight (Table 1). The prevalence of obesity varies significantly across industries, with the Transportation & Warehousing industry having the highest prevalence at 37% and the Professional & Business Services industry the lowest at 22%. These differences reflect variations in demographics, socioeconomic characteristics, and job-related factors. Specifically, within the 158 million civilian employees on nonfarm payrolls, 46.9 million were obesity, and 53.8 million were overweight.

Higher medical costs

Obesity and overweight are associated with increased annual medical expenditures of $1514 and $380, respectively, compared to employees with healthy weight (Table 2). The impact of obesity on medical costs varies by industry, ranging from $1787 in the Manufacturing industry to $1405 in the Financial Activities industry.

Absenteeism & Presenteeism

Employees with obesity miss an average of 3.2 extra workdays annually due to illness or injury compared to their healthy-weight peers, with the Professional & Business Services sector averaging 2.2 extra days and the Government sector 4.3 extra days (Table 3). Obesity-related absenteeism costs employers an average of $1755 per year. Weight-associated presenteeism costs employers $2427 annually per employee with obesity and $864 per employee with overweight. The absenteeism and presenteeism estimates vary by industry.

Injury risk, disability payments, and workers’ compensation payments

Injury claims among employees vary significantly by weight status and industry, controlling for demographics and year of data collection. The Construction sector has the highest on-the-job injury rates, with probabilities of 37%, 45%, and 51% for employees with healthy weight, overweight, and obesity, respectively. Approximately 27% of injuries in the Construction sector for employees with obesity can be attributed to their weight (Supplementary Table A-2).

Conversely, the Financial Activities sector exhibits lower injury rates, with probabilities of 5%, 7%, and 8% for employees with healthy weight, overweight, and obesity, respectively. In this sector, 38% of injuries among workers with obesity are attributed to their weight.

Analysis of MEPS data linked to NHIS revealed variations in workers’ compensation payments per incident across industries, ranging from $122 in the Professional & Business Services sector to $592 in Manufacturing. Considering industry variation in incidents and costs, combined annual obesity-related expenses for disability and injury worker compensation per worker range from $118 in the Financial Activities sector to $1857 in the Construction sector.

Summary of the cost of excess weight to employers and employees

Combining the medical and productivity costs, the annual additional cost per employee with obesity is calculated to be $6472, while the cost per employee with overweight is $1244 (Table 2). These calculations do not include additional healthcare costs associated with adult dependents with obesity or overweight. At the national level across nonfarm industries, excess body weight costs employers and workers an estimated $425.5 billion, with industry-specific estimates detailed in Table 4. Approximately $347.5 billion of this amount is associated with obesity, while $78.0 billion is associated with overweight.

For a hypothetical employer with 10,000 employees, approximately 2970 employees would have obesity and 3410 would have overweight, along with adult dependents covered by the employee’s plan. The annual cost associated with excess weight for this employer is approximately $26.9 million, with about $22 million attributed to obesity and $4.9 million to overweight. An estimated $3.6 million of higher medical costs is paid by employees through medical insurance premiums and out-of-pocket expenses, $4 million is covered by the employer, and $1.6 million is covered by another insurer (e.g., a spouse’s insurer). Industry-specific estimates for a hypothetical employer across the seven major industries are summarized in Table 5.

Potential savings with different weight loss scenarios

Substantial health benefits can be achieved for adults with obesity by maintaining just a 5% loss of body weight. Over five years, this 5% weight loss could result in a 6% reduction in the incidence of type 2 diabetes, 11% fewer strokes, 6% fewer heart attacks, and a 2% reduction in overall mortality among the population with obesity (Supplementary Fig. A-1). The benefits become even more substantial for those who can sustain greater weight loss. For this modeled cohort, sustaining a 25% weight loss could potentially reduce the onset of type 2 diabetes by 38%, the incidence of stroke by 26%, the incidence of heart attack by 25%, the incidence of heart disease by 20%, and overall mortality by 8%.

Among those who successfully achieve a 5% weight loss, an average savings of $430 can be expected in the first year. If this weight loss is maintained over five years, cumulative medical cost savings per person could reach $2270 (Supplementary Table A-3). Simulated medical savings tend to compound, and over ten years, this 5% reduction in body weight could result in $5310 in medical savings. Under the 25% weight loss scenario, simulated savings are $810 in the first year, $4830 over five years, and $13 510 over ten years. Particularly for individuals with a BMI greater than 40 kg/m2, sustaining higher weight loss can lead to medical savings of $1270 in the first year, $7950 over five years, and $21 980 over ten years. In addition to medical savings, there would be increased productivity and improved quality of life.

Among the estimated 158 million workers on nonfarm payrolls in 2023, approximately 46.9 million had obesity with an estimated 20.6 million additional adult dependents with obesity. For this population with obesity, achieving a sustainable 5% weight loss could result in substantial savings in medical costs over five years (excluding treatment costs). Specifically, this could lead to $153.3 billion in medical savings, with $106.4 billion in savings for employees and $46.9 billion in savings for their adult dependents (Table 6). In the highest (25%) weight loss scenario, medical savings over five years could amount to $326.1 billion, with $226.5 billion in savings for employees and $99.7 billion in savings for adult dependents. In the highest weight loss scenario, many individuals with obesity will not require the full 25% weight loss to move out of the obesity range.

This study addresses a significant gap in the existing literature by examining the economic ramifications of obesity from the employer’s perspective, highlighting the broader implications of obesity on workforce dynamics and employee well-being. While previous research has provided valuable insights into the additional medical costs associated with obesity and overweight, our study takes a unique approach by focusing on the repercussions for employers, their employees, and the adult dependents of these employees. Although many of these effects are challenging to quantify in monetary terms, they are anticipated to impact employee morale and influence employers’ corporate social responsibility and sustainability initiatives.

A notable strength of our study is the provision of estimates for potential medical savings (excluding treatment costs) from various weight loss scenarios across major industries, both nationally and for a hypothetical employer with 10,000 employees. By offering insights into the potential economic benefits of obesity management strategies, our study contributes to the ongoing discourse on combating obesity as a public health concern while emphasizing the significance of prioritizing interventions that foster a healthier, more productive workforce.

For contextual comparison, studies have reported annual additional medical costs attributed to obesity ($1612 [4], $2438 [8], and $4231 [9]) and overweight ($224 [4]) in 2023 dollars among adults with private insurance. Other studies have reported additional costs of obesity ($2055 [3], $2593 [52]) and overweight ($400 [52]) among all adults when scaled to 2023 dollars. Our estimate of the additional medical costs of obesity ($1514) is on the lower end of published studies, which is unsurprising, as people with obesity who are in the workforce are likely to have fewer obesity-related comorbid conditions compared to those not in the workforce.

However, there are limitations to our analysis. One, the study relies on self-reported data from surveys such as NHIS and MEPS, which may be subject to recall bias and inaccuracies in reporting height and weight, leading to misclassification of BMI status. Two, due to insufficient information on the dependents of employees, we used the cost of obesity and overweight for employed adults as a proxy for costs among adult dependents, which might result in underestimation. Three, the analysis focused primarily on direct medical costs and indirect costs related to productivity loss, neglecting other potential economic impacts such as reduced quality of life, caregiver burden, the financial impact on employers of lower labor force participation, employee turnover, and hiring discrimination due to data limitations. Four, this study focuses on the adult population with obesity, although prevalence of obesity among children and adolescents raises medical and indirect costs. Consequently, the total economic and societal burden of obesity and overweight may be underestimated. Five, due to limitations in data sources and lack of relevant studies, the simulation model does not fully consider the longitudinal impact that patients’ prior history of obesity or overweight may have on the risk of related disease conditions. Hence, savings associated with weight loss might be smaller than our estimates. Six, for productivity loss components (i.e., absenteeism and presenteeism), it remains unclear to what extent this burden is borne by employers in the form of lost revenues or by employees as lost earnings.

In estimating potential savings through obesity treatment, the study assumed certain weight loss goals achievable through treatment interventions. However, the actual effectiveness of such interventions may vary depending on individual characteristics, adherence to treatment, and availability of healthcare resources, which could affect the estimated economic benefits. Furthermore, potential savings estimates do not account for the cost of different interventions such as lifestyle modification, anti-obesity medications, or bariatric surgery, as the ideal recommended treatment is unique to each individual.

Nevertheless, this study underscores the imperative for concerted efforts to combat obesity, offering valuable insights into its multifaceted impact on the economy and highlighting the importance of proactive interventions to foster a healthier and more productive workforce.

In conclusion, the economic burden of obesity and overweight on employers and employees is staggering, amounting to $425.5 billion in 2023 alone. These costs encompass higher medical expenses, increased absenteeism, reduced productivity (presenteeism), elevated disability costs, and augmented Workers’ Compensation Program expenses. Importantly, these impacts vary across industries, with costs ranging from $19.4 million in the Professional & Business Services sector to $36.7 million in the Government sector for a typical employer with 10,000 employees.

On a per-employee basis, the annual additional cost per employee with obesity is calculated to be $6472, while the cost per employee with overweight is $1244. These are costs that will continue to be incurred in the absence of obesity treatment.

Such substantial financial implications underscore the critical need for employers to address the challenges posed by obesity within their workforce. Supporting employees and their dependents in managing obesity represents a strategic investment for employers, yielding significant economic benefits and fostering a more resilient, productive workforce. By implementing initiatives aimed at obesity prevention and treatment, employers can enhance employee well-being, boost productivity levels, and contribute to the creation of a healthier, more prosperous society.