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The Top U.S. States Where Work Stress Is Driving Early Aging, According to New Study

Jonathan H. Westover, PhD
2 hours ago
6 min read

A new study from Compare the Market shows where Americans are most at risk of accelerated aging due to their jobs highlighting the physical strain, long hours, and stress that are silently taking a toll on the workforce.

Nationally, the research finds that firefighters, truck drivers, chefs, lawyers, and journalists score highest on the Aging Impact Index, with firefighters leading at 73.32 out of 100 due to hazardous conditions and physically demanding tasks.

State-by-state data reveals where this impact is most concentrated. For example:

Arkansas: 3.6% of workers are employed in these high-aging jobs
North Dakota: 3.5% of workers
Tennessee: 3.4% of workers
Kentucky: 3.3% of workers

The state-level analysis uses U.S. Bureau of Labor Statistics data to calculate where the concentration of these high-impact jobs is greatest highlighting where workers may face increased long-term health strain.

Top 5 Professions with the Most Impact on Aging: 

Rank	Profession	Stress Load	Movement Imbalance	Hazard Exposure	Work Week Duration	Salary (USD)	Aging Impact Score
1	Firefighter	6.87	4.73	6.30	7.04	$57,078	73.32
2	Truck/Lorry Driver	5.61	5.64	4.19	9.20	$95,583	67.98
3	Chef	7.06	3.56	4.27	9.65	$64,064	66.32
4	Lawyer	8.08	5.55	1.00	7.24	$105,437	60.89
5	Journalist	5.85	5.09	1.73	7.29	$49,012	57.85

But which states are workers in these top 5 jobs?

Using data from the U.S. Bureau of Labor Statistics, the number of workers in each of the five professions was analysed by state and divided by the total working population to determine the percentage of workers in roles linked to accelerated aging.

State	Chefs	Firefighters	Journalist	Lawyers	Truck Driver Heavy & Light	Total workers in top 5 jobs	% of population in jobs that age them
Arkansas	950	2,280	210	3,500	41,460	48,400	3.6%
North Dakota	90	750	140	1,070	12,650	14,700	3.5%
Wyoming	330	680	70	940	8,090	10,110	3.5%
Rhode Island	700	1,590	140	1,910	15,460	19,800	3.5%
Tennessee	2,720	6,510	650	8,830	93,810	112,520	3.4%
Kentucky	1,860	5,320	520	6,380	51,350	65,430	3.3%
Iowa	1,500	2,050	560	3,550	46,370	54,030	3.3%
Nebraska	600	1,060	430	3,470	27,880	33,440	3.2%
Mississippi	950	2,630	280	3,200	32,010	39,070	3.2%
Ohio	4,040	18,750	1,310	19,690	126,600	170,390	3.0%
Indiana	1,140	8,550	720	8,510	80,200	99,120	3.0%
Wisconsin	2,130	8,010	750	8,820	72,000	91,710	3.0%
Maine	1,290	2,390	270	2,080	14,230	20,260	3.0%
Alabama	1,280	6,930	510	5,810	52,570	67,100	2.9%
Kansas	980	3,630	320	4,270	33,560	42,760	2.9%
Illinois	5,540	14,510	1,410	33,430	125,590	180,480	2.9%
Louisiana	1,860	4,690	410	8,610	41,020	56,590	2.8%
Delaware	490	450	40	2,970	9,850	13,800	2.8%
North Carolina	4,100	18,200	980	17,380	102,470	143,130	2.8%
Idaho	420	2,100	210	2,070	22,300	27,100	2.8%
Missouri	1,590	6,740	460	11,950	63,890	84,630	2.8%
Georgia	4,390	11,660	1,370	23,010	104,210	144,640	2.8%
Oklahoma	1,210	4,110	420	7,430	38,090	51,260	2.7%
Pennsylvania	7,060	0	1,240	26,340	132,520	167,160	2.6%
South Dakota	290	540	210	1,130	10,370	12,540	2.6%
Montana	500	960	310	2,460	10,410	14,640	2.6%
South Carolina	2,000	7,570	570	7,270	45,840	63,250	2.6%
New Jersey	6,060	6,590	660	23,360	84,740	121,410	2.6%
Texas	16,550	30,400	2,460	54,680	284,360	388,450	2.6%
California	26,500	27,580	4,530	92,580	328,990	480,180	2.6%
Florida	17,170	21,470	3,180	59,010	177,070	277,900	2.6%
Virginia	3,900	10,820	1,380	18,420	80,000	114,520	2.6%
Nevada	4,560	2,360	310	6,130	26,550	39,910	2.6%
New York	15,420	14,730	5,220	91,440	113,700	240,510	2.6%
West Virginia	310	1,040	230	2,460	15,250	19,290	2.6%
Minnesota	1,630	4,890	370	12,880	57,180	76,950	2.5%
Utah	1,880	2,650	220	5,850	34,150	44,750	2.5%
Oregon	3,640	3,660	420	7,690	36,810	52,220	2.5%
Michigan	5,310	7,390	790	16,060	89,020	118,570	2.5%
Massachusetts	5,330	11,910	1,180	22,020	51,530	91,970	2.5%
Arizona	3,260	6,870	570	12,130	60,370	83,200	2.3%
Washington	3,840	8,000	1,040	13,140	62,870	88,890	2.3%
Colorado	4,180	6,170	740	17,160	41,650	69,900	2.2%
New Mexico	400	2,200	160	3,130	14,990	20,880	2.2%
Vermont	530	470	110	1,150	5,390	7,650	2.2%
Maryland	3,310	5,250	730	16,420	43,260	68,970	2.2%
Connecticut	3,600	2,860	310	7,500	26,760	41,030	2.2%
Alaska	780	1,040	120	1,040	4,330	7,310	2.1%
New Hampshire	1,260	2,880	150	0	11,710	16,000	2.1%
Hawaii	830	N/A	170	2,430	6,900	10,330	1.6%

Based on our research the least impactful professions on aging include roles like software developers and data scientists. These jobs have more manageable workweeks and lower stress, reducing the overall physical and mental strain that contributes to faster aging. However, even in these fields, prolonged periods of sedentary activity can still contribute to certain aspects of aging, though not to the same extent as more physically demanding roles.

"These findings highlight the significant toll certain professions take on long-term health, with high stress, physical strain, and exposure to hazards accelerating aging," says Steven Spicer, Executive General Manager of Health, Life and Energy at Compare the Market AU.

"Understanding the health risks associated with your profession is crucial when considering health insurance options. Professions with higher aging impacts may require more frequent medical care, better preventive measures, and higher levels of coverage. It's important to assess not only your lifestyle and job demands but also how your health insurance can support you as you navigate these challenges and safeguard your well-being in the long run.”

To find out more about the aging jobs study, please visit: https://www.comparethemarket.com.au/health-insurance/features/jobs-that-age-you-the-fastest/

Methodology: This dataset ranks 20 professions based on their impact on aging using 5 key factors. Each factor’s data was collected and normalised for the ranking. The scores were then combined to give each profession a total score out of 100, and professions were ranked from highest to lowest. ONET - the U.S. Department of Labor’s occupational database - evaluates jobs across hundreds of “element types” (e.g., Work Context and Work Activities) covering schedule demands, physical load, environmental hazards, interpersonal pressures, and more. For category construction, the underlying O*NET elements (originally on mixed scales) were first rescaled to 0-10, then averaged to form each factor before normalising to 0-1.

Aging Impact Index 2025: CTM

This dataset ranks 20 professions based on their impact on aging using 5 key factors. Each factor’s data was collected and normalised for the ranking. The scores were then combined to give each profession a total score out of 100, and professions were ranked from highest to lowest. ONET - the U.S. Department of Labor’s occupational database - evaluates jobs across hundreds of “element types” (e.g., Work Context and Work Activities) covering schedule demands, physical load, environmental hazards, interpersonal pressures, and more. For category construction, the underlying O*NET elements (originally on mixed scales) were first rescaled to 0–10, then averaged to form each factor before normalising to 0–1.

The factors used were:

•  Length of Work Week: Typical weekly hours from ONET. Longer weeks reduce recovery and sleep, increase allostatic load, and are associated with faster biological aging.

•  Stress and Cognitive Pressure: Composite of ONET elements that capture psychosocial strain, for example Time Pressure, Frequency of Decision Making, Responsibility for Outcomes and Results, Deal with Unpleasant or Angry People, and Frequency of Conflict Situations. Higher scores indicate sustained stress, which is linked to accelerated aging.

•  Hazard Exposure: Composite of ONET elements indicating unsafe or unhealthy environments, for example Exposed to Contaminants, Hazardous Equipment, Risk of Injury, and Exposure to Disease. Greater exposure raises long term health risk.

•   Movement Imbalance: Composite that penalises both extremes of physical activity. Sedentary patterns such as Spend Time Sitting and Standing Still increase risk, and so do high strain patterns such as Heavy Lifting, Repeating Same Motions, and Spend Time Bending or Twisting. Roles with balanced movement score better on this factor.

•  Average Salary (USD): Desk researched from multiple sources and anchored to U.S. salaries to match ONET coverage. Lower pay is associated with higher chronic stress and fewer resources for rest and healthcare, so this factor is reverse scored.

Job title matching: The job titles from ONET were matched to a predefined set of professions identified for analysis in this study. Where multiple ONET roles represented variations of the same occupation, they were grouped under a single representative title. For example, different types of nurse were grouped under “Nurse.” Matching was based on recognised job titles and their suitability for the study. The final category scores represent the average of the relevant grouped job roles.

All data is accurate as of 15/8/2025. Rankings reflect the data sources used but may not capture every real-life detail. Salary figures use U.S. data and were converted for presentation. They do not represent local pay levels. The rationale is that relative differences between roles are more informative for this analysis than country by country levels.

Currencies were converted from USD to GBP, AUD, and EUR using Google rates on 12/08/2025 at: 1 USD = 0.74 GBP; 1 USD = 1.53 AUD; 1 USD = 0.86 EUR.