About the National Data


Baseline: 89.4 nonfatal work-related injuries resulting in 1 or more days away from work per 10,000 full-time private industry workers occurred in 2017

Target: 63.8 per 10,000

Number of reported work-related nonfatal injuries from employer's Occupational Safety and Health Administration (OSHA) injury and illness log resulting in 1 or more days away from work.
Number of hours worked by workers.
Target-setting method


Target-setting method details
Linear trend fitted using weighted least squares and a projection at the 50 percent prediction interval.
Target-setting method justification
Trend data were evaluated for this objective. Using historical data points, a trend line was fitted using weighted least squares, and the trend was projected into the next decade. This method was used because three or more comparable data points were available, the projected value was within the range of possible values, and a projection at the 50 percent prediction interval was selected because no additional information could be used to assess the trend line, so the target was based on the projection.


Methodology notes

Nonfatal occupational injuries are defined as any injury such as a cut, fracture, sprain, amputation etc., which results from a work-related event or from a single instantaneous exposure in the work environment. The SOII collects data on injuries that the Occupational Safety and Health Administration (OSHA) defines as recordable. SOII is a cooperative Federal–State program in which employer reports of occupational injuries and illnesses based on OSHA recordkeeping rules are collected from a nationally representative sample of private and public sector establishments. This includes work-related injuries involving loss of consciousness, days away from work, restricted work activity or job transfer, or medical treatment other than first aid. For this objective nonfatal occupational injuries include those to workers, regardless of age, that involve days away from work as well as those without lost workdays. For the first time in 2008, the SOII provided national public sector estimates covering nearly 19 million state and local government workers. The survey excludes the self-employed, farms with fewer than 11 employees, private household workers, and employees in Federal government agencies. The rate per 10000 full-time equivalent workers is computed by (1) dividing the number of occupational injuries reported by the total number of hours worked by all employees during the calendar year, and (2) multiplying the result by 20,000,000. The factor 20,000,000 represents the hours worked in a year by 10000 full-time equivalent workers (working 40 hours work per week, 50 weeks a year). Nonfatal work-related injuries continue to take a toll on the U.S. workforce with an estimated 3.5 million injuries resulting in medical treatment, lost time from work, or restricted work activity as reported by employers in 2016, and an estimated 2.8 million occupational injuries treated in emergency departments that same year. While the data from employer-reports have suggested considerable reductions in work-related injury incidence rates over time, the data from emergency departments have suggested stable rates in recent years. Work-related injuries are preventable.


Comparable HP2020 objective
Modified, which includes core objectives that are continuing from Healthy People 2020 but underwent a change in measurement.
Changes between HP2020 and HP2030
This objective differs from Healthy People 2020 objective OSH-2.1 in that objective OSH-2.1 tracked employer-reported nonfatal work-related injuries that resulted in medical treatment, lost time from work, or restricted work activity, while this objective tracks employer-reported nonfatal work-related injuries that resulted in 1 or more days away from work.

1. Because Healthy People 2030 objectives have a desired direction (e.g., increase or decrease), the confidence level of a one-sided prediction interval can be used as an indication of how likely a target will be to achieve based on the historical data and fitted trend.