Changes in working and health conditions in different sectors between 2010 and 2019 in a representative sample of French workers

Jean-Francois Gehanno; Ariane Leroyer; Manon Couvreur; Serge Volkoff; Laetitia Rollin

doi:10.1371/journal.pone.0324244

. 2025 Jun 4;20(6):e0324244. doi: 10.1371/journal.pone.0324244

Changes in working and health conditions in different sectors between 2010 and 2019 in a representative sample of French workers

Jean-Francois Gehanno ^1,^2,^*,^#, Ariane Leroyer ^3,^4,^#, Manon Couvreur ^5,^#, Serge Volkoff ⁶, Laetitia Rollin ^1,^2,^#

Editor: Swaantje Wiarda Casjens⁷

PMCID: PMC12136334 PMID: 40465657

Abstract

Background

Studies on evolution of working conditions and workers’ health in developed countries show conflicting results, and often fail to identify evolutions by occupational sector. This study aimed to describe recent evolutions of working conditions and health status of French workers over a decade across different activity sectors.

Methods and findings

Data from a large national French observatory of working conditions and health were used. This observatory collects, for a random sample of employees, data on their working conditions and health. Data on working conditions and health status of employees in the 13 main French activity sectors in 2010–2011 and 2018–2019 were used. A 2 steps weighting method was used to allow results to be extrapolated to the French employees.

Overall, 23,951 and 26,538 questionnaires were collected for the 2010–2011 and 2018–2019 periods, respectively. Job demand significantly decreased and job resources significantly increased between 2010–2011 and 2018–2019 while physical workload decreased. Neck, wrist, elbow and back pain disorders significantly decreased as well as anxiety, whereas shoulder disorders, fatigue and sleep disorders increased. However, there were large and significant disparities in evolutions between sectors, for exposures and health status. The most worrisome sector was the Human health and social work sector with no improvement in the working conditions and increasing health problems.

Conclusion

Overall, evolutions and prevalence of physical exposure or health problems do not bring the same information. It is important to understand the extent to which psychosocial, physical working conditions and health status differ among various industry categories, and to study the determinants of such disparities such that policy and practice interventions to reduce disparities can be appropriately directed. It is also important to continue monitoring health of workers, as the impact of changes in working conditions may not have an immediate effect, particularly for conditions with a long latency period.

Introduction

Globalization of market, job automation and digitalization, work extensity and physical hazards are some of the most important drivers of workers’ health changes [1]. However, it is difficult to get a reliable picture of the evolution of working conditions, if any, and there is uncertainty whether they are changing for the better or worse.

In Europe, estimates derived from the cross-national European Working Conditions Survey [2], suggested job insecurity, skill discretion and decision latitude had deteriorated over the 2005–2010 period while other work conditions, such as working hours and work-life imbalance, had improved. Comparing data from two surveys of employees in European Union member-states carried out in 1996 and 2001, Gallie found no evidence of a trend towards higher work pressure over this period [3], and a study exploring the development of working conditions within and between occupations in the Swedish labour market from 1997 to 2015 found that the global analysis of the work environment of occupations revealed few changes over time [4]. In the US, analyzing the NIOSH Quality of Work Life Surveys, Myers et al. observed statistically significant increases in job strain, low job control and work-family conflict [5] whereas, in Canada, Fan and Smith found improvements in some self-reported measures of the psychosocial work environment between 2002 and 2012 [6].

Studying global trends is important to identify new risk factors, assess if occupational health interventions on the national level are successful, and quantify the health impact of working conditions. However, it neglects possible differences between occupations [7]. The Swedish study pointed out that, although macro trends remained the same, the working conditions within different occupations were changing and most of the dimensions displayed occupational variation in trajectories over time [4].

Studying the global trends in workers’ health is subject to the same bias. Over the last decades, the nature of health problems has changed with emerging concerns around musculoskeletal disorders and mental health [8], but more precise data on the trends in different occupations are needed.

This study aimed to describe recent evolutions of working conditions (e.g., employee perceptions of psychosocial factors or physical exposures) and health status (musculoskeletal and psychological issues) of workers followed by occupational medicine services over a decade across different activity sectors using data from a large national French observatory of working conditions and health.

Method

Data from the National Evrest Observatory (EVolutions et Relations en Santé au Travail − Evolutions and Relationships in Health at Work) were used.

In France, all employees are required to attend an occupational health examination every two, three or five years, depending on the employee’s level of risk exposure (http://evrest.istnf.fr/page-0-0-0.html). Evrest is a national observatory, set up in France in 2007 by occupational health physicians and researchers aiming at collecting, for a random sample of employees, a database concerning their working conditions and their health. The scope of this observatory covers all employees in the public and private sectors working in mainland France, excluding agriculture and the state civil service, which includes ministries and national public administrative establishments. Since 2008, the Evrest database has included about 180,000 questionnaires, completed by about 80,000 employees and 1,700 occupational health teams.

Data are collected using a short, standardized questionnaire (one double-sided page), made up of closed-ended questions that have been used in large surveys on health in workplaces in France [9–12] (http://evrest.istnf.fr/page-0-0-0.html).

Working conditions are studied using data about psychosocial and biomechanical constraints.

The psychosocial constraints are explored according to 5 main axes as recommended by the College d’expertise sur le suivi statistique des risques psychosociaux au travail (College of experts on the statistical monitoring of psychosocial risks at work) [13], i.e., job demand (intensity and working time), margin of maneuver and autonomy, social support and reward, ethical dilemmas and job insecurity. The biomechanical constraints are explored according to 3 items: awkward postures, effort or carrying loads and repetitive movements.

Psychological distress is estimated based on the presence of one of the following symptoms: fatigue, sleeping disorders or anxiety-nervousness and on the presence of all these 3 symptoms during the last 7 days. Musculoskeletal complaints of the upper limbs are estimated based on the presence of shoulder, elbow or wrist/hand complaints. Musculoskeletal complaints of the spine are estimated based on the presence of dorsal/lumber vertebrae or cervical vertebrae complaints (Table 1).

Table 1. Dimensions description and scales used.

Domain and dimension	Dimension formulation	Response scale in present study	Question number
Job demands
Time pressure	Due to your workload, do you ever skip or shorten meal times, not take a break?	1 = never, 2 = rarely, 3 = quite often, 4 = very often	1
Time pressure	Due to your workload, do you ever complete too quickly an operation that should have required more attention?	1 = never, 2 = rarely, 3 = quite often, 4 = very often	2
Overtime	Due to your workload, do you ever work overtime?	1 = never, 2 = rarely, 3 = quite often, 4 = very often	3
Task interruptions	Are you frequently disturbed in your work by having to stop working on one task to complete another unforeseen one?	1 = yes, 2 = no	4
Ethical dilemma	Do you have the means to do your work to a high standard?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	5
Ethical dilemma	Do you have to do things you disapprove?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	6
Job insecurity	Do you work with the fear of losing your job?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	7
Job resources
Autonomy	Can you choose how you do things yourself?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	8
Social support	Do you have enough possibilities to obtain help and cooperation?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	9
Reward	Is your work recognized by your professional entourage?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	10
Learning opportunities	Does your work provide opportunities to learn new things?	1 = not at all, 2 = Mostly no, 3 = mostly yes, 4 = yes, absolutely	11
Physical workload
	Are you exposed to repetitive movements?	0 = no, never, 1 = yes, sometimes, 2 = yes, often	12
	Are you exposed to awkward postures?	0 = no, never, 1 = yes, sometimes, 2 = yes, often	13
	Are you exposed to carrying heavy loads?	0 = no, never, 1 = yes, sometimes, 2 = yes, often	14
Health status
Musculoskeletal	Neck pain or symptoms	1 = yes, 2 = no	15
disorders	Back pain or symptoms	1 = yes, 2 = no	16
	Wrist pain or symptoms	1 = yes, 2 = no	17
	Elbow pain or symptoms	1 = yes, 2 = no	18
	Shoulder pain or symptoms	1 = yes, 2 = no	19
Psychological	Sleep disorders during the last week?	1 = yes, 2 = no	20
	Fatigue during the last week?	1 = yes, 2 = no	21
	Anxiety during the last week?	1 = yes, 2 = no	22

Open in a new tab

In the questionnaire, sectors of activity and occupations are coded according to the national classifications of the National Institute of Statistics and Economic Studies, PCS-ESE-2003 and NAF-2008, respectively (https://www.insee.fr/en/metadonnees/nafr2/section/A).

The questionnaire is proposed by occupational health teams (physicians and nurses) participating in the survey to employees during their periodic occupational health examination. All other types of examination (resuming work after sick leave, spontaneous visit for health complaints, pre-employment visit) are excluded.

The part of the questionnaire concerning working conditions is completed by the employee in the waiting room and the second part, concerning state of health, is completed by the occupational health physician or the nurse during the visit.

To obtain a random sample of employees, only those born in October are asked to complete the questionnaire.

Population studied

Workers surveyed as part of the Evrest program in 2010–2011 and in 2018–2019 were included.

However, we included in the study only sectors of activity for which we had at least 500 questionnaires, which led us to include 13 main activity sectors.

C: Manufacturing
D: Electricity, gas, steam and air conditioning supply
F: Constructions and construction works
G: Wholesale and retail trade; repair of motor vehicles and motorcycles
H: Transportation and storage services
I: Accommodation and food service activities
J: Information and communication services
K: Financial and insurance services
M: Professional, scientific and technical services
N: Administrative and support service activities
O: Public administration and defense
Q: Human health and social work activities
S: Other services activities

Weighting methodology

A weighting methodology allowing results to be extrapolated to the French employees was used. The detailed weighted methodology is available in a previously published article [14]. Briefly, the weighting method includes two steps: 1) a first weighting based on the date of the last occupational health examination, to consider the probability of participation of each employee; and 2) a marginal calibration method to correct potential distortions of the sample in comparison with the scope of the survey, based on the distribution of French employees in 2015 (middle of the studied period) in terms of gender, age (5 groups), company size (6 groups) and sector of activity crossed with occupations (13x4 groups) (National Institute of Statistics and Economic Studies, https://www.insee.fr/fr/statistiques/3536754).

Statistical analysis

Data from workers surveyed as part of the Evrest program in 2010–2011 on the one hand, and in 2018–2019 on the other hand, were compared.

If necessary, each working condition indicator was dichotomized, by grouping together: for time pressure and overtime, the responses “quite often” and “very often” in one hand and “never” and “rarely” on the other; for ethical dilemma, job insecurity, job resources, autonomy, social support, reward and learning opportunities, the responses “quite often” and “very often” in one hand and “not at all” and “mostly no” on the other; for physical workload, the response “yes, often” was opposed to the responses “no never” and “yes, sometimes”.

Decrease of exposure to job demand (i.e., from “quite often” or “very often” to “never” or “rarely”), decrease of exposure to physical workload (from “yes, often” to “yes, sometimes” or “no never”), decrease of frequency of musculoskeletal or psychological disorders (from “yes” to “no”) or increase of job resources (from “not at all” or “Mostly no” to “mostly yes” or “yes, absolutely”) was considered as an improvement, the opposite being considered as a deterioration.

For each working condition and health indicator studied, the proportion of workers who were concerned was calculated for each period, and a proportion difference test for weighted data (Rao-Scott) was performed to test the evolution of the situation between the two periods. The Rao‐Scott method introduced a correction into the classic chi-square test in order to took into account the weights as well as, if any, the clustering and stratification involved in the collection of the sample[15].

The significance threshold was set at 5%, and analyses were performed with R version 4.1.2.

Ethics statement

The recruitment period for this study started on January 1, 2010, ended December 31, 2011 for the first period and on January 1, 2018, and ended December 31, 2019 for the second period.

Before participation, employees were informed of their rights in writing and they had the choice to decline completing the questionnaire and participating to the study. No minor was included in the study.

All personal data are anonymized in the database. The observatory and the database obtained authorization from the French Data Protection Authority (Commission nationale de l’informatique et des libertés, CNIL, Authorization number 906290V1) and the National Advisory Committee on the Processing of Health Research Information (Authorization number 06.390) in 2006. The observatory and the database comply with the European General Data Protection Regulation (EU 2016/679).

Results

Description of the population.

Overall, 23,951 and 26,538 questionnaires were collected for the 2010–2011 and 2018–2019 periods, respectively (Table 2).

Table 2. Description of the population included (weighted percentages).

Sector of activity	Years	N	Gender (%)		Age (%)					Occupation (%)
			Female	Male	< 25	25-34	35-44	45-54	≥55	M	IP	E	MW
Manufacturing	2010-2011	4018	42.5	57.5	12.7	22.1	26.1	24.7	14.4	5.6	9.6	39.7	45.1
Manufacturing	2018-2019	3346	40.0	60.0	17.6	18.3	24.0	24.2	15.9	5.6	9.6	39.7	45.1
Electricity, gas, steam and air conditioning supply	2010-2011	2305	43.0	57.0	7.2	23.3	24.5	37.2	7.9	4.6	7.0	79.1	9.2
Electricity, gas, steam and air conditioning supply	2018-2019	3761	40.0	60.0	6.7	30.1	28.2	24.7	10.2	4.8	7.4	76.2	11.5
Constructions and construction works	2010-2011	1641	31.6	68.4	18.9	22.2	25.9	19.1	13.9	0.9	3.5	40.4	55.3
Constructions and construction works	2018-2019	2230	35.2	64.8	13.5	24.2	24.0	24.1	14.2	0.9	3.5	40.4	55.3
Wholesale and retail trade	2010-2011	3909	45.0	55.0	16.9	28.0	24.9	19.2	11.0	6.9	46.3	37.4	9.3
Wholesale and retail trade	2018-2019	3718	44.2	55.8	19.3	27.3	22.6	20.1	10.7	7.4	46.9	36.0	9.8
Transportation and storage services	2010-2011	1528	20.8	79.2	6.0	22.6	27.3	31.3	12.9	5.8	41.6	16.5	36.1
Transportation and storage services	2018-2019	1467	26.0	74.0	6.6	21.9	25.2	28.8	17.5	6.5	42.2	15.7	35.6
Accommodation and food service	2010-2011	875	48.0	52.0	30.4	24.7	18.6	17.1	9.2	5.2	26.1	59.9	8.7
Accommodation and food service	2018-2019	1017	45.7	54.3	34.3	21.9	18.5	17.7	7.6	3.3	27.1	60.7	8.8
Information and communication	2010-2011	664	28.4	71.6	12.0	32.6	27.8	19.9	7.7	53.6	36.4	8.4	1.5
Information and communication	2018-2019	903	27.7	72.3	15.3	28.4	22.3	20.9	13.1	43.9	42.9	12.5	0.6
Finance and insurance	2010-2011	988	55.3	44.7	9.6	24.6	21.8	24.2	19.8	23.8	42.5	33.5	0.2
Finance and insurance	2018-2019	696	53.8	46.2	10.8	28.3	27.3	19.5	14.2	21.3	49.1	28.7	1.0
Professional, scientific and technical	2010-2011	1317	43.3	56.7	10.1	31.8	26.2	18.9	13.0	34.3	41.9	20.8	2.9
Professional, scientific and technical	2018-2019	1481	44.3	55.7	13.8	31.1	25.0	20.1	10.0	36.6	36.8	23.9	2.7
Administrative and support service	2010-2011	1484	42.8	57.2	18.1	26.2	26.2	17.3	12.1	8.4	25.0	41.5	25.1
Administrative and support service	2018-2019	1848	41.4	58.6	19.8	25.3	22.2	21.3	11.3	12.4	25.7	40.9	20.9
Public administration and defense	2010-2011	1009	59.2	40.8	2.7	16.9	23.5	32.5	24.3	24.1	26.0	39.2	10.6
Public administration and defense	2018-2019	749	52.5	47.5	4.6	14.8	24.4	32.9	23.2	14.4	27.9	45.8	11.9
Human health and social work	2010-2011	2428	69.8	30.2	8.5	22.1	22.8	27.2	19.4	6.6	59.2	18.6	15.6
Human health and social work	2018-2019	3436	71.3	28.7	8.5	24.7	24.1	24.6	18.1	6.6	59.2	18.6	15.6
Other services activities	2010-2011	719	58.2	41.8	15.1	25.7	22.5	21.8	14.8	34.4	43.2	19.3	3.0
Other services activities	2018-2019	583	59.3	40.7	15.0	22.5	22.8	23.0	16.8	36.4	39.2	21.0	3.4
Global	2010-2011	23951	50.2	49.8	12.1	23.7	24.2	24.5	15.5	14.2	32.7	32.6	20.6
Global	2018-2019	26538	50.2	49.8	12.1	23.7	24.2	24.5	15.5	14.2	32.7	32.6	20.6

Open in a new tab

N: Number of individuals; M: Managers; IP: Intermediate professions; E: Employees; MW: Manual workers

Male to female ratio remained close between the two periods (from 1.42 to 1.46). The proportion of workers aged 25–34 increased by 1%, and the number of employees and manual workers decreased by 2.3%.

The global prevalence and trends of exposure to risk factors and health issues are presented in Fig 1.

Each radar displays the proportion of workers who were exposed to the dimension of job demand or of physical workload mentioned in Table 1, the proportion of workers who declared having one or several job resources mentioned in Table 1 and the proportion of workers who suffered of Musculoskeletal or psychological disorders

Overall, job demand and job resources significantly improved between 2010–2011 and 2018–2019 while physical workload decreased. Concerning health status, neck, wrist, elbow and back pain disorders significantly improved as well as anxiety, whereas shoulder disorders, fatigue and sleep disorders increased.

However, there were large disparities in trends between sectors for all domains and dimensions (exposure or health status) (Figs 2–14)

These differences were significantly different among all sectors (Table 3).

Table 3. Changes of the proportion of workers concerned by each item from 2010-2011 to 2018-2019 for each sector of activity.

Sector of activity*		C	D	F	G	H	I	J	K	M	N	O	Q	S	Global	Global p-value
Working conditions
Time pressure	1-Shorten meal times	+6	−21	−4	−2	+5	+3	−26	−2	−5	−15	−1	+6	−23	−6	0.06
Time pressure	2-Complete too quickly an operation	−23	−31	−4	−13	−3	−15	−16	−17	−10	+2	−3	+7	−26	−9	0.003
Overtime	3-Working overtime	+5	−16	+6	−10	−2	+3	−28	−14	−15	−17	−14	−0	−25	−6	0.007
Task interruptions	4-Need to stop his task	−10	−16	−12	−3	−1	−7	−16	−11	−8	−16	−9	+6	−8	−6	0.002
Ethical dilemmas	5-Insufficient means to perform his task	−24	−44	−44	−32	−3	−38	−45	−16	−6	−4	−4	+15	−43	−24	0.001
Ethical dilemmas	6-Doing think he disapprove	−15	−17	−19	−13	+12	−19	−16	−43	−24	−12	−4	+11	−45	−16	0.001
Job insecurity	7-Fear of losing his job	−23	+96	−20	−26	−23	−25	−49	+54	−42	−29	+93	−13	−22	−11	0.11
Autonomy	8-Not choosing how to do	−4	−20	−23	−11	−6	+19	+6	−15	−13	+0	−21	+6	−1	−9	0.011
Social support	9-Lack of cooperation	−21	−61	−22	−26	−21	−35	−46	−42	−37	−12	−8	−17	−16	−23	0.001
Reward	10-Work not recognized	−35	−38	−34	−26	−36	−44	−47	−38	−45	−35	−17	−23	−31	−32	0.001
Learning opportunities	11-No opportunity to learn	−20	−21	−22	−26	−1	−21	−34	−9	−25	−20	−20	−9	−12	−20	0.001
Physical workload	12-Repetitive movements	−9	+15	−6	−3	−10	−6	−11	+12	+6	−7	−4	−6	−6	−5	0.06
	13-Awkward postures	−6	−8	−9	+6	−10	−11	−6	+5	+5	−15	+11	+1	−14	−5	0.18
	14-Carrying heavy loads	−0	−32	−2	+5	−15	−10	−10	−51	−31	−31	+12	−7	+34	−5	0.16
Health status
Musculoskeletal disorders	15-Neck	−12	−23	−12	−7	−15	−23	+36	+6	−14	−3	−4	+25	−26	−10	0.08
	16-Back	−8	−26	−26	−7	−3	−8	+12	−29	−22	+4	−24	−10	−2	−15	0.001
	17-Wrist	−11	−29	+6	−15	+34	+32	+7	−28	−29	−18	−5	+8	−22	−6	0.43
	18-Elbow	−8	−51	−0	−8	−23	+30	+12	+25	−35	−39	+6	+26	−70	−12	0.21
	19-Shoulder	+6	−30	+15	+4	+24	+3	+75	+51	−13	−21	+7	+27	−17	+10	0.14
Psychological issues	20-Sleep disorders	+4	−8	−9	+5	−7	+25	+21	+10	−4	+14	−4	+19	+6	+4	0.34
	21-Fatigue	+3	−16	+15	+12	+6	+3	+23	+23	+1	+34	+1	+41	−6	+11	0.007
	22-Anxiety	−29	−31	−47	−15	−6	+2	−6	−10	−23	−17	−15	+3	−28	−20	0.001

Open in a new tab

The values in the boxes represent the percentage change between 2010–2011 and 2018–2019.

For example, the proportion of workers who declared being exposed to working overtime increased by 5% between 2010–2011 and 2018–2019 in the manufacturing sector but this change was not statistically significant, whereas the decrease of 28% in the Information and communication services sector was statistically significant. Statistically significant improvement Statistically significant deterioration

* C: Manufacturing; D: Electricity, gas, steam and air conditioning supply; F: Constructions and construction works; G: Wholesale and retail trade; repair of motor vehicles and motorcycles

H: Transportation and storage services; I: Accommodation and food service activities J: Information and communication services; K: Financial and insurance services; M: Professional, scientific and technical services; N: Administrative and support service activities; O: Public administration and defense; Q: Human health and social work activities; S: Other services activities

Evolutions of working conditions

Social support, Reward and Learning opportunities improved for all sectors within the decade, but at different levels. Improvement was also globally observed for all the other psychosocial dimensions but with exceptions for some sectors. For example, the percentage of employees who feared losing their job was divided by two in the Information and communication services sector (from 13.2% to 6.8%) but nearly doubled for the Electricity, gas, steam and air conditioning supply and Public administration and defense sectors (from 3.8% to 7.4%).

Working overtime and being exposed to task interruptions were the two most prevalent psychosocial risk factors across all sectors of activity.

Physical workload remained unchanged within the period except for the task of Carrying heavy loads which significantly decreased in three sectors (Financial and insurance services, Professional, scientific and technical services and Administrative and support service activities).

Two sectors were particularly exposed to repetitive movements: Manufacturing and Accommodation and food service activities

Evolutions of health status

For health status, the differences were even more pronounced, with some sectors showing improvement and others showing the opposite for the same dimension. The differences between sectors were significant for all dimensions.

Musculoskeletal disorders of the back, wrist and elbows decreased in many sectors whereas shoulder’s disorders significantly increased in several sectors (e.g., + 75% for the shoulder in the Information and communication services sector).

Concerning psychological issues, the present study examined the development of fatigue and anxiety in 13 sectors of activity. The results revealed that these two phenomena have evolved in opposite ways in 10 of the sectors studied. This contrasting trend was found to be statistically significant in seven of these ten sectors.

Relations between exposures and health problems

Trends in working conditions and health status were in general concordant within each sector.

For sectors C, F, H, M and S, working conditions and health status remained stable or improved over the period.

However, while working conditions remained stable or improved for the Human health and social work activities sector (Q), 7 out of 8 health disorders increased, significantly for 4 of them.

This was also the case, to a lesser extent, in the Wholesale and retail trade; repair of motor vehicles and motorcycles and the Information and communication services sector (G and J).

Looking beyond trends

An analysis of the changes that have occurred between the two periods under study in the various sectors of activity may provide a misleading picture of the level of exposure to occupational risk factors or of the state of health of employees in these sectors.

In certain sectors, a substantial decline in exposure or health impairment has been observed; however, residual levels persist at elevated levels in comparison to other sectors. For example, task interruptions significantly decreased in the Information and communication services, the Financial and insurance services and the Professional, scientific and technical services sectors. However, they still concerned more than 55% of employees in 2018–2019. On the other side, prevalence of task interruptions did not improve for the Transportation and storage services sector between the two periods but concerned “only” 45.7% of employees. While job insecurity significantly increased in the Financial and insurance services sector and significantly decreased in the Administrative and support service activities sector, it still concerned in 2018–2019 14.0% of employees in the Administrative and support service activities sector compared to 11.4% in the Financial and insurance services sector.

Discussion

The main results of this study are a global improvement of health status, job demand and job resources while physical workload remained at the same level, among French workers between 2010–2011 and 2018–2019, with marked differences across sectors of activity.

Limitations

A limitation of our study is that data were collected before COVID. The COVID-19 pandemic changed people’s working conditions worldwide, induced income losses, increased work stressors and impaired the mental health of workers [7,16,17]. However, most studies on trends in working conditions and health are in the same situation, due mainly to the delay in collecting and analysing data at a national level. Furthermore, knowing the trends before the pandemic will be important to analyze the changes it induced.

Another limitation is that this study is longitudinal, but does not follow the same individuals over time. Internationally, there are several major longitudinal cohort studies with a focus on work environment and health. Some of them, such as the Whitehall II study in England [18], the French GAZEL cohort [19] and the Finnish Public sector study [20] have multiple repeated measures on a range of factors concerning work, private life and health. All of these studies are, however, restricted to specific groups of employees: civil servants, employees at a gas or electricity company, or public sector employees, respectively. Our study, based on a representative sample, allowed us to compare trends between sectors of activity.

We studied 13 sectors of activity, among the 21 registered in the French National Institute of Statistics and Economic Studies database. We had not enough data for the 8 other sectors of activity, which employ a limited number of workers. We set the threshold at 500 questionnaires at least for one sector of activity and for both periods. For example, there were only 170, 47 and 20 workers included for “Arts, entertainment and recreation”, “Mining and quarrying” and “Activities of households as employers” sectors, respectively. The agricultural sector (sector A ‘Agriculture, forestry and fishing’) was also very poorly represented (only 77 workers included 2010), as it is subject to specific occupational health monitoring by a special social security system. It was therefore excluded from the survey.

It should be noted that all employees in an industry category were classified according to their main activity. This implies that different job tasks that might affect job demands, control and social support or physical exposure, such as administrators, service workers, managers, or workers performing the core production, are merged and that the impact of these different job tasks could not be assessed. However, it is noteworthy that despite this limitation, several significant differences between sectors were found. To get more precise estimates, information on occupation could be used for stratification of workers performing the core tasks from other functions in the production units, for example.

The measures of the demands, decision authority and support dimensions that were used in the present study are not directly comparable with the standard measures of the demand-control-support model of Karasek and Theorell. However, these measures allow for comparisons between industry categories and over time and have been used in previous studies [12].

The way to dichotomize the scales of response for some working conditions, considering the responses “yes” in one hand and “no” in the other hand, does not take into account that for some of these working conditions, there may have been changes in frequency inside categories, such an increase of responses “very often” and a decrease of response “quite often” for time pressure, leading to a stability of the “yes” response.

Finally, our sample was restricted to those who were employees at the time of the survey and therefore self-employed or unemployed people were not included.

Strenghts

The following strengths of our study should be underlined.

We measured both work environment and health extensively. Yet, our study was based on a large nationally representative sample of the French working population of employees. The number of employees included with more than 20,000 per period, as compared to the 9,000 initially included in the Swedish Longitudinal Occupational Survey of Health [21].

Randomization of employees included in the study, on the basis of attendance to a periodic medical examination, and the use of sample weights for all the statistical analyses ensureed that our results can be extrapolated to the population of salaried workers in France, at least for workers belonging to the 13 sectors of activity studied. The random selection of the workers included in the study provided a more realistic view of their actual state of health and occupational exposure than the analysis of people referred to an occupational health center for pathological assessment, as is the case for the French National Network for Occupational Disease Vigilance and Prevention or the Danish Occupational Medicine Cohort[22,23].

Concerning the reliability of health status assessment, self-rated health status may be influenced by perceived occupational exposures [24], but our study did not only rely on self-assessment for health status since this part of the variable was assessed by an occupational health professional.

Main evolutions

Globally, we observed improvement in workplace exposures and psychological and physical health status.

Job insecurity decreased in most sectors of activity over the period. This is consistent with the data of the French working conditions survey which observed no evolution of the prevalence of job insecurity between 2006 and 2013 [25,26]. Despite this global trend, job insecurity increased in two public sectors, i.e., Electricity, gas, steam and air conditioning supply and Public administration and defense categories. This may seem surprising given the job security enjoyed by civil servants in France, but it probably reflects the fact that these civil servants are not sure whether their health status will allow them to keep on working in the forthcoming years [11].

The prevalence of musculoskeletal disorders decreased over the period, which is consistent with the decrease in exposure to psychosocial risk factors and physical workload since both are linked [20,27–29]. Other national or international surveys have also described a decreasing trend in work-related musculoskeletal disorders in the last decades, either globally [27,30–32], for specific localizations such as carpal tunnel syndrome [33] or in specific activities such as in the US construction industry [34]. Nevertheless, they was an increase in the Italian agricultural sector between 2004 and 2017 [35]. The limit of some of these studies is that they relied on compensation claims, which are notably under-reported [36], whereas the method used in our study was not impacted by such bias.

Sleep disorders were widely represented, affecting between 20% and 30% of the subjects participating in the study, and this proportion remained relatively constant, despite the improvement of working conditions. Yet, a French cross-sectional study has previously identified an association between psychological demands, low social support, low recognition, emotional demands and sleep disorders[37]. We had no information on shift work of employees in our study, although it is a significant risk factor for sleep disorders. However, we observed an increase of sleep disorders in the Financial and insurances services sector, which is not exposed to shift-work.

The proportion of employees indicating that they had suffered from fatigue in the previous week increased in 85% of sectors between 2010–2011 and 2018–2019. Physical exposures are associated with increased bodily fatigue, the most marked associations being found when summing the number of different exposures [38]. However, the present study found no increase in exposure to physical factors which could provide a potential explanation for the observed increase in employees’ fatigue. It could be hypothesized that the occurrence of fatigue is partly attributable to compassion fatigue, given its increased prevalence among sectors of activity characterized by frequent contact with the public in our study.

It is imperative that particular attention be given to a specific area of activity, owing to the unfavorable evolution of several parameters, i.e.,. Human health and social work activities. In the period spanning from 2010–2011–2018–2019, it was observed that seven out of eight health disorders exhibited a marked progression, with four of these disorders showing a significant escalation in severity. Concurrently, it was noted that the prevailing working conditions remained relatively constant, but to a high level, especially for working overtime and task interruptions. In the Swedish Longitudinal Occupational Survey of Health, workplace violence and low decision authority was considered to mediate the association between employment in the health and social care industry and sickness absence[39].

Differences between sectors of activity

Beyond the overall trends, we observed major disparities between the different sectors of activity, both in terms of occupational exposure and the state of health of their employees.

Previous studies have shown that exposures to job stressors vary between working population groups in industrialized countries, which contributes to occupational health disparities [40,41]. Comparing trends in job demands, decision authority, and social support in 7 different categories of industry, Cerdas et al. observed different directions developments between 1991–2013 with high differences between industry categories [42].

What could explain the different trends among sectors of activity observed in our study?

First of all, we could think that occupational health policies or interventions specific to some activity sectors could explain why some sectors showed improvement while others did not. However, we are not aware of such specific interventions in the period studied. Moreover, regulations concerning occupational health in France are very detailed and strict and they apply to all employees. It is therefore unlikely that actions at a national level could have been implemented, without us knowing it. Local actions may have occurred, but they cannot explain changes at a national level. We believe that the changes we observed are probably linked to economic changes.

Differences between sectors of activity may be linked to different compositions in terms of gender, age, employment arrangement, socioeconomic and social class positions or occupational skill level [4,5,40–42]. For example, in the Swedish work force, a negative trend of job demands and decision authority was observed in the female-dominated industries between 1991 and 2013, and, in 2020, the highest prevalence of problem drinking was in male-dominated Goods and Energy Production (7.7%), and the lowest was in female-dominated Health and Social Care (4.7%) [42,43]. However, some disparities between industry categories are independent of these factors. In France, the prevalence ratio of job insecurity is 1.4 for the private sector compared to the public one and blue-collar workers, particularly unskilled blue-collar and industrial workers, have a higher prevalence of job insecurity among both genders [26]. In our study, the apparent reduction in job insecurity could therefore be the result of a reduction in the proportion of employees and manual workers in the 2018–2019 cohort compared with the 2010–2011 cohort.

Another possible determinant of such differences is an unequal distribution of company characteristics, such as the economic activity of the company and its implications for the volatility of the market for its products or services, differences in employment norms associated with different types of ownership, and differences in human resource policies related to organizational size [26,44].

Conclusion

In general, the evolution and prevalence of occupational exposures or health problems do not provide equivalent information. It is possible to observe an improvement in an industry category over time, even if the prevalence of exposure or health complaint remains higher than in other categories where the prevalence has increased or remained stable.

It is imperative to comprehend the extent to which psychosocial and physical working conditions and health status vary across diverse industry categories, and to investigate the determinants of such disparities, in order to ensure that policy and practice interventions to reduce disparities can be appropriately directed.

From an interventionist perspective, the understanding of how work requirements and resources vary between sectors of activity, independent of the types of occupations, could facilitate the identification of sectoral factors in addition to general differences between occupations. Consequently, intervention policies in the domain of health and safety could be more effectively targeted towards specific sectors of activity. The health sector, for instance, appears to be experiencing an unfavorable trend, a situation that has likely been exacerbated by the pandemic.

Furthermore, the study of trends is of paramount importance for the identification of new risk factors, the determination of the success of occupational health interventions on a national level, and for the quantification of the health impact of various hazards [45].

Finally, it is imperative to maintain ongoing monitoring of the health of workers, as the impact of changes in working conditions may not be immediately apparent, particularly for conditions with a long latency period. Observatories such as EVREST, which rely on randomization of participants, should be promoted since they can provide relevant answers to those questions.

Acknowledgments

The authors thank all EVREST national project team members.

Data Availability

Data cannot be shared publicly due to legal reasons related to data protection and confidentiality. The data of the EVREST French observatory can be accessed on the basis of a research project submitted to the executive committee. The contact point for accessing the data is the Data Protection Officer of the University of Rouen: dpo@univ-rouen.fr More information can be found on the following website: https://evrest.istnf.fr/_docs/Fichier/2017/4-170512013717.pdf

Funding Statement

The author(s) received no specific funding for this work.

References

1.European Foundation for the Improvement of Living and Working Conditions. Working conditions and workers’ health. LU: Publications Office; 2019. Available: https://data.europa.eu/doi/10.2806/41725 [Google Scholar]
2.Malard L, Chastang J-F, Schütte S, Parent-Thirion A, Vermeylen G, Niedhammer I. Changes in Psychosocial Work Exposures Among Employees Between 2005 and 2010 in 30 Countries in Europe. Journal of Occupational & Environmental Medicine. 2013;55: 1135–41. doi: 10.1097/JOM.0b013e3182a3eb90 [DOI] [PubMed] [Google Scholar]
3.Gallie D. Work Pressure in Europe 1996–2001: Trends and Determinants. British Journal of Industrial Relations. 2005;43: 351–75. doi: 10.1111/j.1467-8543.2005.00360.x [DOI] [Google Scholar]
4.Corin L, Pousette A, Berglund T, Dellve L, Hensing G, Björk L. Occupational trajectories of working conditions in Sweden: Development trends in the workforce, 1997–2015. Scand J Work Environ Health. 2021;47: 335–48. doi: 10.5271/sjweh.3955 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Myers S, Govindarajulu U, Joseph M, Landsbergis P. Changes in work characteristics over 12 years: Findings from the 2002-2014 US National NIOSH Quality of Work Life Surveys. Am J Ind Med. 2019;62: 511–22. doi: 10.1002/ajim.22971 [DOI] [PubMed] [Google Scholar]
6.Fan JK, Smith PM. Self-reported work conditions in Canada: examining changes between 2002 and 2012. Can J Public Health. 2018;109: 882–90. doi: 10.17269/s41997-018-0096-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Backhaus I, Hoven H, Bambra C, Oksanen T, Rigó M, di Tecco C, et al. Changes in work-related stressors before and during the COVID-19 pandemic: differences by gender and parental status. Int Arch Occup Environ Health. 2023;96: 421–31. doi: 10.1007/s00420-022-01933-w [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Schütte S, Chastang J-F, Malard L, Parent-Thirion A, Vermeylen G, Niedhammer I. Psychosocial working conditions and psychological well-being among employees in 34 European countries. Int Arch Occup Environ Health. 2014;87: 897–907. doi: 10.1007/s00420-014-0930-0 [DOI] [PubMed] [Google Scholar]
9.Leroyer A, Molinié A-F, Buisset C, Archambault C, Volkoff S. Mise en place d’un observatoire par questionnaire en santé au travail: le dispositif EVREST. Santé Publique. 2008;20: 49–56. doi: 10.3917/spub.080.0049 [DOI] [PubMed] [Google Scholar]
10.Molinié A-F, Leroyer A. Suivre les évolutions du travail et de la santé: EVREST, un dispositif commun pour des usages diversifiés. Perspectives interdisciplinaires sur le travail et la santé. 2011. [cited 20 May 2023]. doi: 10.4000/pistes.1852 [DOI] [Google Scholar]
11.Rollin L, Gehanno J-F, Leroyer A. Occupational stressors in healthcare workers in France. Revue d’Épidémiologie et de Santé Publique. 2022;70: 59–65. doi: 10.1016/j.respe.2022.02.002 [DOI] [PubMed] [Google Scholar]
12.Leroyer A, Mardon C, Rollin L, Volkoff S. Individual changes in working and health conditions: A longitudinal study of 8,000 employees between 2010 and 2017 in France. WOR. 2022;73: 1023–35. doi: 10.3233/WOR-210992 [DOI] [PubMed] [Google Scholar]
13.Askenazy P, Baudelot C, Brochard P, Brun J-P, Davezies P, Falissard B, et al. Mesurer les facteurs psychosociaux de risque au travail pour les maîtriser. Paris: DARES, Ministère du travail et de l’emploi; 2011. pp. 1–223. Available: https://travail-emploi.gouv.fr/IMG/pdf/rapport_SRPST_definitif_rectifie_11_05_10.pdf [Google Scholar]
14.Leroyer A, Murcia M, Chastang J-F, Rollin L, Volkoff S, Molinié A-F, et al. Méthodologie de redressement des données nationales de l’enquête Évrest: Santé Publique. 2020;Vol. 31: 645–55. doi: 10.3917/spub.195.0645 [DOI] [PubMed] [Google Scholar]
15.Rao JN, Scott AJ. A simple method for the analysis of clustered binary data. Biometrics. 1992;48: 577–85. [PubMed] [Google Scholar]
16.de Miquel C, Domènech-Abella J, Felez-Nobrega M, Cristóbal-Narváez P, Mortier P, Vilagut G, et al. The Mental Health of Employees with Job Loss and Income Loss during the COVID-19 Pandemic: The Mediating Role of Perceived Financial Stress. Int J Environ Res Public Health. 2022;19: 3158. doi: 10.3390/ijerph19063158 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Trógolo MA, Moretti LS, Medrano LA. A nationwide cross-sectional study of workers’ mental health during the COVID-19 pandemic: Impact of changes in working conditions, financial hardships, psychological detachment from work and work-family interface. BMC Psychol. 2022;10: 73. doi: 10.1186/s40359-022-00783-y [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Marmot M, Brunner E. Cohort Profile: the Whitehall II study. Int J Epidemiol. 2005;34: 251–6. doi: 10.1093/ije/dyh372 [DOI] [PubMed] [Google Scholar]
19.Goldberg M, Leclerc A, Bonenfant S, Chastang JF, Schmaus A, Kaniewski N, et al. Cohort profile: the GAZEL Cohort Study. Int J Epidemiol. 2007;36: 32–9. doi: 10.1093/ije/dyl247 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Vahtera J, Laine S, Virtanen M, Oksanen T, Koskinen A, Pentti J, et al. Employee control over working times and risk of cause-specific disability pension: the Finnish Public Sector Study. Occup Environ Med. 2010;67: 479–85. doi: 10.1136/oem.2008.045096 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Magnusson Hanson LL, Leineweber C, Persson V, Hyde M, Theorell T, Westerlund H. Cohort Profile: The Swedish Longitudinal Occupational Survey of Health (SLOSH ). Int J Epidemiol. 2018;47: 691–2i. doi: 10.1093/ije/dyx260 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Dalgaard VL, Willert MV, Kyndi M, Vestergaard JM, Andersen JH, Christiansen DH. Cohort Profile: The Danish Occupational Medicine Cohort—a nationwide cohort of patients with work-related disease. International Journal of Epidemiology. 2023;52: e201–e210. doi: 10.1093/ije/dyad013 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Lucas D, Robin C, Vongmany N, Dewitte JD, Loddé B, Pougnet R, et al. Main Causal Agents of Occupational Asthma in France, Reported to the National Network for Occupational Disease Vigilance and Prevention (RNV3P) 2001-2018. Ann Work Expo Health. 2023;67: 297–302. doi: 10.1093/annweh/wxac079 [DOI] [PubMed] [Google Scholar]
24.Ijmker S, Huysmans MA, van der Beek AJ, Knol DL, van Mechelen W, Bongers PM, et al. Software-recorded and self-reported duration of computer use in relation to the onset of severe arm-wrist-hand pain and neck-shoulder pain. Occup Environ Med. 2011;68: 502–9. doi: 10.1136/oem.2010.056267 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Murcia M, Chastang J-F, Niedhammer I. Psychosocial work factors, major depressive and generalised anxiety disorders: Results from the French national SIP study. Journal of Affective Disorders. 2013;146: 319–27. doi: 10.1016/j.jad.2012.09.014 [DOI] [PubMed] [Google Scholar]
26.Niedhammer I, Pineau E, Bertrais S, Gallie D. Exploring the employment determinants of job insecurity in the French working population: Evidence from national survey data. PLoS One. 2023;18: e0287229. doi: 10.1371/journal.pone.0287229 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Surís X, Ortiz-Santamaria V, Pueyo-Sánchez MJ, Mompart-Penina A, Larrosa M, Ricart A. Decreasing prevalence of chronic back pain in Catalonia. Analysis of the Catalan Health Survey. Public Health. 2022;206: 38–45. doi: 10.1016/j.puhe.2022.02.019 [DOI] [PubMed] [Google Scholar]
28.Yang H, Hitchcock E, Haldeman S, Swanson N, Lu M-L, Choi B, et al. Workplace psychosocial and organizational factors for neck pain in workers in the United States. Am J Ind Med. 2016;59: 549–60. doi: 10.1002/ajim.22602 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Yang H, Lu M-L, Haldeman S, Swanson N. Psychosocial risk factors for low back pain in US workers: Data from the 2002-2018 quality of work life survey. Am J Ind Med. 2023;66: 41–53. doi: 10.1002/ajim.23444 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Dick RB, Lowe BD, Lu M-L, Krieg EF. Trends in Work-Related Musculoskeletal Disorders From the 2002 to 2014 General Social Survey, Quality of Work Life Supplement. J Occup Environ Med. 2020;62: 595–610. doi: 10.1097/JOM.0000000000001895 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Macpherson RA, Lane TJ, Collie A, McLeod CB. Age, sex, and the changing disability burden of compensated work-related musculoskeletal disorders in Canada and Australia. BMC Public Health. 2018;18: 758. doi: 10.1186/s12889-018-5590-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Marcum J, Adams D. Work-related musculoskeletal disorder surveillance using the Washington state workers’ compensation system: Recent declines and patterns by industry, 1999-2013. Am J Ind Med. 2017;60: 457–71. doi: 10.1002/ajim.22708 [DOI] [PubMed] [Google Scholar]
33.Roquelaure Y, Chazelle E, Gautier L, Plaine J, Descatha A, Evanoff B, et al. Time trends in incidence and prevalence of carpal tunnel syndrome over eight years according to multiple data sources: Pays de la Loire study. Scand J Work Environ Health. 2017;43: 75–85. doi: 10.5271/sjweh.3594 [DOI] [PubMed] [Google Scholar]
34.Wang X, Dong XS, Choi SD, Dement J. Work-related musculoskeletal disorders among construction workers in the United States from 1992 to 2014. Occup Environ Med. 2017;74: 374–80. doi: 10.1136/oemed-2016-103943 [DOI] [PubMed] [Google Scholar]
35.van der Molen HF, Marsili C, Vitali A, Colosio C. Trends in occupational diseases in the Italian agricultural sector, 2004-2017. Occup Environ Med. 2020;77: 340–3. doi: 10.1136/oemed-2019-106168 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Riviere S, Martinaud C, Roquelaure Y, Chatelot J. Estimation de la sous-déclaration des troubles musculo-squelettiques dans onze régions françaises en 2011. Archives des Maladies Professionnelles et de l’Environnement. 2018;79: 405–6. doi: 10.1016/j.admp.2018.03.439 [DOI] [Google Scholar]
37.Chazelle E, Chastang J-F, Niedhammer I. Psychosocial work factors and sleep problems: findings from the French national SIP survey. Int Arch Occup Environ Health. 2016;89: 485–95. doi: 10.1007/s00420-015-1087-1 [DOI] [PubMed] [Google Scholar]
38.Bláfoss R, Sundstrup E, Jakobsen MD, Brandt M, Bay H, Andersen LL. Physical workload and bodily fatigue after work: cross-sectional study among 5000 workers. Eur J Public Health. 2019;29: 837–42. doi: 10.1093/eurpub/ckz055 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Nyberg A, Peristera P, Toivanen S, Johansson G. Does Exposure to High Job Demands, Low Decision Authority, or Workplace Violence Mediate the Association between Employment in the Health and Social Care Industry and Register-Based Sickness Absence? A Longitudinal Study of a Swedish Cohort. International Journal of Environmental Research and Public Health. 2022;19: 53. doi: 10.3390/ijerph19010053 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.LaMontagne AD, Krnjacki L, Kavanagh AM, Bentley R. Psychosocial working conditions in a representative sample of working Australians 2001–2008: an analysis of changes in inequalities over time. Occup Environ Med. 2013;70: 639–47. doi: 10.1136/oemed-2012-101171 [DOI] [PubMed] [Google Scholar]
41.Landsbergis PA, Grzywacz JG, LaMontagne AD. Work organization, job insecurity, and occupational health disparities. American Journal of Industrial Medicine. 2014;57: 495–515. doi: 10.1002/ajim.22126 [DOI] [PubMed] [Google Scholar]
42.Cerdas S, Härenstam A, Johansson G, Nyberg A. Development of job demands, decision authority and social support in industries with different gender composition – Sweden, 1991–2013. BMC Public Health. 2019;19: 758. doi: 10.1186/s12889-019-6917-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Tareq H, Nyberg A, Wennberg P, Redmalm D, Toivanen S, Mensah A. Prevalence of problem drinking in the Swedish workforce: differences between labour market industries based on gender composition and main job activity. BMC Public Health. 2024;24: 2683. doi: 10.1186/s12889-024-20163-y [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Böckerman P. Perception of Job Instability in Europe. Social Indicators Research. 2004;67: 283–314. [Google Scholar]
45.Burr H. Monitoring trends in psychosocial and physical working conditions: Challenges and suggestions for the 21st century. Scand J Work Environ Health. 2021;47: 329–33. doi: 10.5271/sjweh.3973 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. 2025 Jun 4;20(6):e0324244. doi: 10.1371/journal.pone.0324244.r001

Author response to Decision Letter 0

30 Jun 2024

PLoS One. doi: 10.1371/journal.pone.0324244.r002

Decision Letter 0

Swaantje Wiarda Casjens

5 Feb 2025

Dear Dr. Gehanno,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Mar 22 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Swaantje Wiarda Casjens

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In the online submission form you indicate that your data is not available for proprietary reasons and have provided a contact point for accessing this data. Please note that your current contact point is a co-author on this manuscript. According to our Data Policy, the contact point must not be an author on the manuscript and must be an institutional contact, ideally not an individual. Please revise your data statement to a non-author institutional point of contact, such as a data access or ethics committee, and send this to us via return email. Please also include contact information for the third party organization, and please include the full citation of where the data can be found.

Additional Editor Comments:

Two reviewers have provided insightful feedback aimed at enhancing your manuscript. Both have raised concerns about the selection of sectors to be addressed, a point which I also found to be a critical issue. Furthermore, the terminology should be made more precise, as highlighted by the second reviewer, particularly in relation to terms like “sectors” and “professional categories.” In this context, I would also like to request that the terminology be reviewed and refined in the tables, with abbreviations consistently clarified in footnotes (e.g., sector abbreviations in Table 3). Additionally, please specify in Table 3 the nature of the “significant” improvement or deterioration—was this clinically/medically or statistically significant?

Other comments pertain to the data selection, particularly the time intervals and the focus on individuals born in October. Additionally, the presentation of statistical methods and the representation of results require further attention. Both reviewers also provided feedback on the discussion and conclusion sections. The inclusion of older references should be reconsidered, as I agree with Reviewer 2 that your results would benefit from comparison with more recent data.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1: Did any broader economic changes or trends in France during this period potentially influence the working conditions and health outcomes observed? How might these external factors have played a role?

Why were these 13 activity sectors chosen for analysis over the others defined by the National Institute of Statistics and Economic Studies? Was there a specific rationale for excluding the other sectors?

Given that only employees born in October were surveyed, how representative is the sample of the broader French workforce? Are there any potential biases introduced by this method?

Are there existing occupational health policies or interventions that could explain why some sectors showed improvement while others did not? Could you identify any sector-specific challenges that require policy changes or interventions?

Given that the data collection ended before the COVID-19 pandemic, it would be beneficial to include a brief discussion on how the pandemic might have influenced the observed trends, considering its significant impact on working conditions and health.

Some health outcomes, such as the increase in sleep disorders and fatigue, were highlighted but not deeply analyzed. Discuss potential reasons for these trends, such as changes in work environment, lifestyle factors, or stressors.

The conclusion could be enhanced by offering more concrete recommendations for policymakers or occupational health professionals on how to address the identified disparities across sectors.

Reviewer #2: This research article studies changes in physical exposure, psychosocial factors, psychological distress and musculoskeletal problems between the periods 2010-2011 and 2018-2019 across several sectors of activity. Based on the French Evrest database, it highlights an improvement in several physical and psychosocial constraints between the two periods, as well as a reduction in the percentage of musculoskeletal disorders and anxiety distributed across the different sectors. It also highlights the factors and diseases that have increased, as well as the differences between sectors.

The work carried out is of interest in occupational health by highlighting the factors requiring in-depth monitoring, as well as the sectors requiring the implementation of appropriate preventive measures. The choices made in the methodology should be clarified in order to provide a better understanding of the objective of this study and the work carried out.

I'm not qualified to assess the quality of English writing

General comments :

- Vocabulary: Starting from the abstract and in the rest of the paper, the vocabulary is very confusing. Lines 33 and 34 it is said “Job demand and job resources significantly improved […] physical workload decreased. Neck, elbow and back pain disorders significantly improved…”. The meaning of “decreased” and “improved” in this context is unclear. I suggest to remain more factual to enhance readability: something like “the proportion of workers reporting high job demand decreased”. At least define clearly what does “decrease” and “increase” mean in terms of proportions of exposures and diseases.

- Statistical unit of the study: The sector of activity is presented as the statistical unit. However, it is mentioned that it is also cross-referenced with professional categories (line 123). This leads to confusion as to what is being used. In addition, the nomenclatures used to code the NAF-2008 sector of activity and the PCS-ESE-2003 are also confusing, as the PCS-ESE-2003 is used to code occupations. Then in the tables and figures, the “professional category” is mentioned, but the labels seem to be activity sectors (NAF-2008 probably?). The statistical unit used should be clarified and standardised throughout the article.

- The choice of sectors of activity: Only 13 of the 21 sectors were studied, so it would be interesting to understand why this selection was made and what criteria were used.

- Presentation of Evrest database : the sections “the Evrest observatory” and “databases used” in the “Method” sections are not clearly defined, what is their respective purpose? The general information about the observatory are somewhat mixed with the subparts of data extracted and used in the study. I suggest to clarify, either with two clear sections or only one that gathers (1) all the information about Evrest and (2) the data management performed and its resulting sub-data. For example, I would expect the Table 1 in the “general description” of Evrest, whereas the list of main activity sectors explored should be in the description of the specific data extraction of this study.

- The choice of time periods: It would be interesting to know why these two periods were chosen and why the evolution of constraints was not studied over a continuous period. As far as I know, the Everest data is available for each year (since 2007?).

- The method for assessing the statistical significance of the evolution of results from 2010-2011 to 2018-2019 should be further explained. Even if the Rao-Scott test seem to be quite a classic, I’m not familiar with it. I understood it is more or less a Chi square test, but adjusted with the weights of observations. I’m not sure to really understand the relationship between the stratification variables of data used for the design of the weights, the objectives of the analysis (global statistics and sectoral statistics) and the adequacy of the test. In other words, I suggest to add one or two sentences about the choice of this test: why is this test really appropriate for this data? What are the assumptions (normality of data?) Maybe a literal description of the computation with an example should help. Note that this question is linked with the previous about the choice of the periods because the statistical significance of a trend over a continuous (or semi-continuous) period would be assessed with other methods.

- Base results : the provided data are focused on the differences between 2010-2011 and 2018-2019, but it would be interesting to discuss the level of exposures and the health status in 2010-2011. Indeed, the initial percentages of exposures and the percentages of workers suffering diseases are not clearly presented. As far as I understand, these values could be read on the figures and the levels of exposure are very different (around 50% for question 4 “task interruption” and almost zero for question 18 “elbow pain”). Please add a table or a figure at the beginning of the results.

- Improving the figures: The figures require further explanation to make them easier for readers to understand. I’m still unsure of what is presented (is it really the percentages of workers who answered “yes” to the 22 questions?). At least, a sentence reminding us of the link between the numbers in the figures and Table 1 would be useful. Better would be to use the labels instead of the numbering of questions. The legend mentions “significant improvement/degradation” when a cross is reported, but I can’t see any cross on the graph. It is difficult to read the set of graphs depicting the evolution for each activity sector. There are too much information. It is unclear whether the maximum is always 80%. The legends of these figures are missing.

- Structuring the results: The results may benefit from more structuration because the working conditions are presented first, then diseases and finally sectors of activity, but some of the information tends to overlap. A different presentation or the creation of sub-sections would perhaps make the reading easier.

- Improving the discussion 1: there is a lot of relevant information in the discussion but it is not really structured. It seem that the ideas are just presented as a list, adding transitions and linkage between ideas would help the reader.

- Improving the discussion 2: Lines 291 and following, two studies are largely used as comparison basis (Cerdas et al. and Swedish Work Environments Surveys), but these studies are old, and the world changed a lot since 1991. I’m not sure it is relevant to make any comparison between the period 1991-2013 of these studies and the period 2010-2019 explored in this paper. At least, reduce the part of the discussion dedicated to this comparisons or provide a better explanation of why you believe that your results are worth to be compared with such old data.

Specific comments

Authors : The symbol “&” is reported for authors who equally contributed to the work, but only Dr. Serge Volkoff has this sign associated with his name

Asbtract - Keywords: Add ‘physical’ to the term ‘occupational exposures’.

Introduction, Line 58 : define “macro analysis”

Introduction, Line 73: Explain what is meant by working conditions in this study (e.g. employee perceptions of psychosocial factors or physical exposures).

Introduction, Line 73: Specify the health problems studied in this article.

Method, lines 114-115 : a difference is mentioned about “public and private sectors” and “state public service”. The difference is unclear, in particular for non-French readers.

Method - The Evrest observatory, Line 123: Wouldn't it be (13*4) because 13 sectors of activity were selected? If not, then an explanation is missing.

Method - Databases used, Line 131 : 5 main axes concerning psychosocial constraints have been defined but are not subsequently used. Why not use them in the results?

Method, line 132 : Provide an English translation of “College d’expertise sur le suivi statistique des risques psychosociaux au travail »

Method - Ethics statement, Line 146 : Put a capital letter at the beginning of the sentence ‘Start and end ...’.

Result, Table 2: Why use the term “Professional categories”? Doesn't it correspond to the socio-professional categories shown in the last column of the table? Shouldn’t the term be changed into “Sector of activity”?

Result, Table 2: the numbers in the last two lines (global, at the very end of the table) are rigorously identical, which look like a copy/paste mistake.

Result, Line 203 and Line 207: Write the names of the sectors concerned.

Discussion, Line 287: Several sectors are mentioned, but only one is cited.

Discussion, line 320: You mention other studies about the decreasing trend in work related musculoskeletal disorders, but what about the trends in France? Why didn’t you mentioned the French health insurance data? As far as I know, the number of MSD compensated has greatly increased during the last decades (TMP n°57 RG at least)?

**********

what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

PLoS One. 2025 Jun 4;20(6):e0324244. doi: 10.1371/journal.pone.0324244.r003

Author response to Decision Letter 1

10 Apr 2025

Response to reviewers

PONE-D-24-25814

Changes in working and health conditions in different sectors between 2010 and 2019 in a representative sample of French Workers

PLOS ONE

Dear Dr. Gehanno,

Please submit your revised manuscript by Mar 22 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Swaantje Wiarda Casjens

Academic Editor

PLOS ONE

Journal requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

The contact point for accessing the data is the Data Protection Officer of the University of Rouen: dpo@univ-rouen.fr

We used a Data Availability Statement formulation inspired from the one of another study published in PLOS ONE (https://doi.org/10.1371/journal. pone.0287229):

Data Availability Statement:

The EVREST observatory was authorized by the Commission Nationale de l'Informatique et des Libertés (CNIL) on 4 March 2008. Following the General Data Protection Regulation (Regulation (EU) 2016/679), which came into force on 25 May 2018, this observatory was validated by the University of Rouen's Data Protection Officer and entered in the institution's data processing register under number 202009_008 and registered in the national HealthDataHub register (N° F20221129113417, https://www.health-data-hub.fr/projets/evolutions-et-relations-en-sante-au-travail-evrest). Data underlying the results are not publicly available due to legal reasons related to data protection and confidentiality. The data of the EVREST French observatory can be accessed on the basis of a research project submitted to the executive commitee. More information can be found on the following website: https://evrest.istnf.fr/_docs/Fichier/2017/4-170512013717.pdf

Additional Editor Comments:

We agree and thank the Editor for this comment. Occupations and socio-professional categories (acronym, PCS) is a French statistical nomenclature used to classify occupations according to multiple factors, such as employment status (employee versus self-employed), the nature of the employer, the professional classification for employees, and the size of their company for the self-employed. Its name can be misleading and we were wrong using the term “professional categories” as a synonym of “Sector of activity”. We clarified and standardized this throughout the article

In Table 3, significant means statistically significant. It has been added in the text. Footnotes have been added.

Response to reviewers

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

France has experienced four recessions since 1945: in 1975 (-0.9%), 1993 (-0.6%), 2009 (-2.9%) and 2020 (-7.5%). In 2008, the financial crisis of 2007 turned into an economic crisis and a global recession. In the United States, this began in early 2008. In European countries, and France in particular, it began at the end of 2008, following the worsening of the global financial crisis (bankruptcy of Lehman Brothers). Indeed, the 2009 recession in France was a direct consequence of the 2007-2008 financial crisis.

There was no crisis between 2009 (subprimes) and 2020 (COVID), although France came close to recession again in the first quarter of 2013, against the backdrop of the eurozone crisis. According to INSEE, all the engines of the French economy worked in slow motion: household consumption, although revised upwards, remained at half-mast, as did business investment, weighed down by weak margins. Foreign trade also suffered from an unexpected fall in German and British imports.

We had not enough data for the 8 other sectors of activity, which employ a limited number of workers. We set the threshold at 500 questionnaires at least for one sector of activity and for both periods. For example, there were only 170, 47 and 20 workers included for “Arts, entertainment and recreation”, “Mining and quarrying” and “Activities of households as employers” sectors, respectively. The agricultural sector was also very poorly represented (only 77 workers included 2010), as it is subject to specific occupational health monitoring by a special social security system. It was therefore excluded from the survey (sector A ‘Agriculture, forestry and fishing’)

Given that only employees born in October were surveyed, how representative is the sample of the broader French workforce? Are there any potential biases introduced by this method?

We used the same methodology that the permanent demographic sample (échantillon démographique permanent – EDP) which was created in 1968 at INSEE (French National Institute for Statistics and Economic Studies) from the compilation of data from the population censuses and civil register. The aim was to set up a new tool for the analysis of geographical mobility and social trajectories, such as social differentials in mortality, professional trajectories over a long period or the trajectory of immigrants (professional mobility and acquisition of French nationality, for example). This EDP includes people born in October as randomization method.

The methods used to ensure representability of the sample have been described in another article (Ref 13): Weighting methodology for the national EVREST survey data

Objectives: The main objective was to describe the weighting methodology used for the national EVREST (Evolution and Relations in Health at Work) survey data. The secondary objectives were on the one hand to assess the extent of the differences between crude and weighted estimates, on the other hand to verify that the two-year gap in the availability of the reference data used does substantially not impact the estimates.

Methods: The study was based on data collected in 2013 and 2014 (N = 26,227). The weighting included 2 steps: 1) a first weighing to take into account the probability of participation of each employee; and 2) a calibration on margins to correct the potential distortions of the sample in comparison with the scope of the survey, the reference data used coming from the annual declarations of social data (DADS) of the years 2014 and 2012. The impact of the weighting method was studied using the differences between crude and weighted percentages for the 60 variables of the questionnaire.

Results: 90% of the differences between crude and weighted estimates were between – 2.0% and + 2.0% using the 2014 DADS, and 83% using the 2012 DADS. The most overestimated crude estimate concerned full-time work and the most underestimated was contact with the public. The impact of the two-year gap in the availability of the reference data used was weak.

Conclusion: A weighting methodology for EVREST survey was define and implement, allowing results to be extrapolated to the scope of the survey

We are not aware of such specific interventions in the period studied. However, regulations concerning occupational health in France are very strict and detailed and they apply to all employees. It is therefore unlikely that actions at a national level could have been implemented, without us knowing it. Local actions may have occurred, but they cannot explain changes at a national level. We believe that the changes we observed are probably linked to economic changes.

This was added in the manuscript.

We probably did not understand well this comment but the COVID-19 pandemic cannot not have influenced the results for 2018-2019. However, we fully agree with the impact of this pandemic and we plan to compare 2018-2019 to 2023-2024 when the data will be consolidated.

We already mentioned in the manuscript that “A limitation of our study is that data were collected before COVID. The COVID-19 pandemic changed people's working conditions worldwide, induced income losses, increased work stressors and impaired the mental health of workers [7,15,16]. However, most studies on trends in working conditions and health are in the same situation, due mainly to the delay in collecting and analysing data at a national level. Furthermore, knowing the trends before the pandemic will be important to analyze the changes it induced.”

We agree and we developed these points in the discussion.

The conclusion could be enhanced by offering more concrete recommendations for policymakers or occupational health professionals on how to address the identified disparities across sectors.

We agree and we developed these points in the conclusion.

Attachment

Submitted filename: Response to reviewers.docx

pone.0324244.s002.docx^{(39.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0324244.r004

Decision Letter 1

Swaantje Wiarda Casjens

15 Apr 2025

Dear Dr. Gehanno,

Please submit your revised manuscript by May 30 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Swaantje Wiarda Casjens

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

Thank you for the revised manuscript. You have addressed the reviewer comments, and I believe these changes have significantly improved the manuscript. Nevertheless, I have a few minor comments that should still be addressed:

The explanation of Figure 1 is very well done. Please also specify what type of significance is being referred to here. Additionally, there is a typo: “2018-2018”. In general, statistically significant results should be represented differently than with the colors "red" and "green" in all figures due to the prevalence of congenital red-green color blindness.

How do Figure 1 and Figure 2 differ? If they are based on the same data, Figure 1, including the explanations, should be sufficient.

Further minor comments:

• Method, line 96: Provide an English translation of “College d’expertise sur le suivi statistique des risques psychosociaux au travail.

• Discussion, line 285: The term “limitation” should be used instead of “weaknesses.”

[Note: HTML markup is below. Please do not edit.]

PLoS One. 2025 Jun 4;20(6):e0324244. doi: 10.1371/journal.pone.0324244.r005

Author response to Decision Letter 2

17 Apr 2025

Additional Editor Comments:

Thank you for the revised manuscript. You have addressed the reviewer comments, and I believe these changes have significantly improved the manuscript.

We agree and we thank the reviewers for their valuable comments

Nevertheless, I have a few minor comments that should still be addressed:

The explanation of Figure 1 is very well done. Please also specify what type of significance is being referred to here.

We added “Statistically significant” in figure 1

In general, statistically significant results should be represented differently than with the colors "red" and "green" in all figures due to the prevalence of congenital red-green color blindness.

We have kept the colour in the figures but added a specific symbol for statistically significant deteriorations or improvements, to make them easier to read for people who cannot distinguish red from green.

Additionally, there is a typo: “2018-2018”.

This has been corrected

How do Figure 1 and Figure 2 differ? If they are based on the same data, Figure 1, including the explanations, should be sufficient.

We agree. We had displayed two figures since the first one was just to explain how to read the figures overall. We have removed Figure 2 and renumbered Figures 3 to Figures 2

Further minor comments:

• Method, line 96: Provide an English translation of “College d’expertise sur le suivi statistique des risques psychosociaux au travail.

We added the translation: “College of experts on the statistical monitoring of psychosocial risks at work”

• Discussion, line 285: The term “limitation” should be used instead of “weaknesses.”

It has been changed

PLoS One. doi: 10.1371/journal.pone.0324244.r006

Decision Letter 2

Swaantje Wiarda Casjens

23 Apr 2025

Changes in working and health conditions in different sectors between 2010 and 2019 in a representative sample of French Workers

PONE-D-24-25814R2

Dear Dr. Gehanno,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Swaantje Wiarda Casjens

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0324244.r007

Acceptance letter

Swaantje Wiarda Casjens

PONE-D-24-25814R2

PLOS ONE

Dear Dr. Gehanno,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Swaantje Wiarda Casjens

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

Submitted filename: Response to reviewers.docx

pone.0324244.s002.docx^{(39.8KB, docx)}

Data Availability Statement

[pone.0324244.ref001] 1.European Foundation for the Improvement of Living and Working Conditions. Working conditions and workers’ health. LU: Publications Office; 2019. Available: https://data.europa.eu/doi/10.2806/41725 [Google Scholar]

[pone.0324244.ref002] 2.Malard L, Chastang J-F, Schütte S, Parent-Thirion A, Vermeylen G, Niedhammer I. Changes in Psychosocial Work Exposures Among Employees Between 2005 and 2010 in 30 Countries in Europe. Journal of Occupational & Environmental Medicine. 2013;55: 1135–41. doi: 10.1097/JOM.0b013e3182a3eb90 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref003] 3.Gallie D. Work Pressure in Europe 1996–2001: Trends and Determinants. British Journal of Industrial Relations. 2005;43: 351–75. doi: 10.1111/j.1467-8543.2005.00360.x [DOI] [Google Scholar]

[pone.0324244.ref004] 4.Corin L, Pousette A, Berglund T, Dellve L, Hensing G, Björk L. Occupational trajectories of working conditions in Sweden: Development trends in the workforce, 1997–2015. Scand J Work Environ Health. 2021;47: 335–48. doi: 10.5271/sjweh.3955 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref005] 5.Myers S, Govindarajulu U, Joseph M, Landsbergis P. Changes in work characteristics over 12 years: Findings from the 2002-2014 US National NIOSH Quality of Work Life Surveys. Am J Ind Med. 2019;62: 511–22. doi: 10.1002/ajim.22971 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref006] 6.Fan JK, Smith PM. Self-reported work conditions in Canada: examining changes between 2002 and 2012. Can J Public Health. 2018;109: 882–90. doi: 10.17269/s41997-018-0096-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref007] 7.Backhaus I, Hoven H, Bambra C, Oksanen T, Rigó M, di Tecco C, et al. Changes in work-related stressors before and during the COVID-19 pandemic: differences by gender and parental status. Int Arch Occup Environ Health. 2023;96: 421–31. doi: 10.1007/s00420-022-01933-w [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref008] 8.Schütte S, Chastang J-F, Malard L, Parent-Thirion A, Vermeylen G, Niedhammer I. Psychosocial working conditions and psychological well-being among employees in 34 European countries. Int Arch Occup Environ Health. 2014;87: 897–907. doi: 10.1007/s00420-014-0930-0 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref009] 9.Leroyer A, Molinié A-F, Buisset C, Archambault C, Volkoff S. Mise en place d’un observatoire par questionnaire en santé au travail: le dispositif EVREST. Santé Publique. 2008;20: 49–56. doi: 10.3917/spub.080.0049 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref010] 10.Molinié A-F, Leroyer A. Suivre les évolutions du travail et de la santé: EVREST, un dispositif commun pour des usages diversifiés. Perspectives interdisciplinaires sur le travail et la santé. 2011. [cited 20 May 2023]. doi: 10.4000/pistes.1852 [DOI] [Google Scholar]

[pone.0324244.ref011] 11.Rollin L, Gehanno J-F, Leroyer A. Occupational stressors in healthcare workers in France. Revue d’Épidémiologie et de Santé Publique. 2022;70: 59–65. doi: 10.1016/j.respe.2022.02.002 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref012] 12.Leroyer A, Mardon C, Rollin L, Volkoff S. Individual changes in working and health conditions: A longitudinal study of 8,000 employees between 2010 and 2017 in France. WOR. 2022;73: 1023–35. doi: 10.3233/WOR-210992 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref013] 13.Askenazy P, Baudelot C, Brochard P, Brun J-P, Davezies P, Falissard B, et al. Mesurer les facteurs psychosociaux de risque au travail pour les maîtriser. Paris: DARES, Ministère du travail et de l’emploi; 2011. pp. 1–223. Available: https://travail-emploi.gouv.fr/IMG/pdf/rapport_SRPST_definitif_rectifie_11_05_10.pdf [Google Scholar]

[pone.0324244.ref014] 14.Leroyer A, Murcia M, Chastang J-F, Rollin L, Volkoff S, Molinié A-F, et al. Méthodologie de redressement des données nationales de l’enquête Évrest: Santé Publique. 2020;Vol. 31: 645–55. doi: 10.3917/spub.195.0645 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref015] 15.Rao JN, Scott AJ. A simple method for the analysis of clustered binary data. Biometrics. 1992;48: 577–85. [PubMed] [Google Scholar]

[pone.0324244.ref016] 16.de Miquel C, Domènech-Abella J, Felez-Nobrega M, Cristóbal-Narváez P, Mortier P, Vilagut G, et al. The Mental Health of Employees with Job Loss and Income Loss during the COVID-19 Pandemic: The Mediating Role of Perceived Financial Stress. Int J Environ Res Public Health. 2022;19: 3158. doi: 10.3390/ijerph19063158 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref017] 17.Trógolo MA, Moretti LS, Medrano LA. A nationwide cross-sectional study of workers’ mental health during the COVID-19 pandemic: Impact of changes in working conditions, financial hardships, psychological detachment from work and work-family interface. BMC Psychol. 2022;10: 73. doi: 10.1186/s40359-022-00783-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref018] 18.Marmot M, Brunner E. Cohort Profile: the Whitehall II study. Int J Epidemiol. 2005;34: 251–6. doi: 10.1093/ije/dyh372 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref019] 19.Goldberg M, Leclerc A, Bonenfant S, Chastang JF, Schmaus A, Kaniewski N, et al. Cohort profile: the GAZEL Cohort Study. Int J Epidemiol. 2007;36: 32–9. doi: 10.1093/ije/dyl247 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref020] 20.Vahtera J, Laine S, Virtanen M, Oksanen T, Koskinen A, Pentti J, et al. Employee control over working times and risk of cause-specific disability pension: the Finnish Public Sector Study. Occup Environ Med. 2010;67: 479–85. doi: 10.1136/oem.2008.045096 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref021] 21.Magnusson Hanson LL, Leineweber C, Persson V, Hyde M, Theorell T, Westerlund H. Cohort Profile: The Swedish Longitudinal Occupational Survey of Health (SLOSH ). Int J Epidemiol. 2018;47: 691–2i. doi: 10.1093/ije/dyx260 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref022] 22.Dalgaard VL, Willert MV, Kyndi M, Vestergaard JM, Andersen JH, Christiansen DH. Cohort Profile: The Danish Occupational Medicine Cohort—a nationwide cohort of patients with work-related disease. International Journal of Epidemiology. 2023;52: e201–e210. doi: 10.1093/ije/dyad013 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref023] 23.Lucas D, Robin C, Vongmany N, Dewitte JD, Loddé B, Pougnet R, et al. Main Causal Agents of Occupational Asthma in France, Reported to the National Network for Occupational Disease Vigilance and Prevention (RNV3P) 2001-2018. Ann Work Expo Health. 2023;67: 297–302. doi: 10.1093/annweh/wxac079 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref024] 24.Ijmker S, Huysmans MA, van der Beek AJ, Knol DL, van Mechelen W, Bongers PM, et al. Software-recorded and self-reported duration of computer use in relation to the onset of severe arm-wrist-hand pain and neck-shoulder pain. Occup Environ Med. 2011;68: 502–9. doi: 10.1136/oem.2010.056267 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref025] 25.Murcia M, Chastang J-F, Niedhammer I. Psychosocial work factors, major depressive and generalised anxiety disorders: Results from the French national SIP study. Journal of Affective Disorders. 2013;146: 319–27. doi: 10.1016/j.jad.2012.09.014 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref026] 26.Niedhammer I, Pineau E, Bertrais S, Gallie D. Exploring the employment determinants of job insecurity in the French working population: Evidence from national survey data. PLoS One. 2023;18: e0287229. doi: 10.1371/journal.pone.0287229 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref027] 27.Surís X, Ortiz-Santamaria V, Pueyo-Sánchez MJ, Mompart-Penina A, Larrosa M, Ricart A. Decreasing prevalence of chronic back pain in Catalonia. Analysis of the Catalan Health Survey. Public Health. 2022;206: 38–45. doi: 10.1016/j.puhe.2022.02.019 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref028] 28.Yang H, Hitchcock E, Haldeman S, Swanson N, Lu M-L, Choi B, et al. Workplace psychosocial and organizational factors for neck pain in workers in the United States. Am J Ind Med. 2016;59: 549–60. doi: 10.1002/ajim.22602 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref029] 29.Yang H, Lu M-L, Haldeman S, Swanson N. Psychosocial risk factors for low back pain in US workers: Data from the 2002-2018 quality of work life survey. Am J Ind Med. 2023;66: 41–53. doi: 10.1002/ajim.23444 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref030] 30.Dick RB, Lowe BD, Lu M-L, Krieg EF. Trends in Work-Related Musculoskeletal Disorders From the 2002 to 2014 General Social Survey, Quality of Work Life Supplement. J Occup Environ Med. 2020;62: 595–610. doi: 10.1097/JOM.0000000000001895 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref031] 31.Macpherson RA, Lane TJ, Collie A, McLeod CB. Age, sex, and the changing disability burden of compensated work-related musculoskeletal disorders in Canada and Australia. BMC Public Health. 2018;18: 758. doi: 10.1186/s12889-018-5590-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref032] 32.Marcum J, Adams D. Work-related musculoskeletal disorder surveillance using the Washington state workers’ compensation system: Recent declines and patterns by industry, 1999-2013. Am J Ind Med. 2017;60: 457–71. doi: 10.1002/ajim.22708 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref033] 33.Roquelaure Y, Chazelle E, Gautier L, Plaine J, Descatha A, Evanoff B, et al. Time trends in incidence and prevalence of carpal tunnel syndrome over eight years according to multiple data sources: Pays de la Loire study. Scand J Work Environ Health. 2017;43: 75–85. doi: 10.5271/sjweh.3594 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref034] 34.Wang X, Dong XS, Choi SD, Dement J. Work-related musculoskeletal disorders among construction workers in the United States from 1992 to 2014. Occup Environ Med. 2017;74: 374–80. doi: 10.1136/oemed-2016-103943 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref035] 35.van der Molen HF, Marsili C, Vitali A, Colosio C. Trends in occupational diseases in the Italian agricultural sector, 2004-2017. Occup Environ Med. 2020;77: 340–3. doi: 10.1136/oemed-2019-106168 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref036] 36.Riviere S, Martinaud C, Roquelaure Y, Chatelot J. Estimation de la sous-déclaration des troubles musculo-squelettiques dans onze régions françaises en 2011. Archives des Maladies Professionnelles et de l’Environnement. 2018;79: 405–6. doi: 10.1016/j.admp.2018.03.439 [DOI] [Google Scholar]

[pone.0324244.ref037] 37.Chazelle E, Chastang J-F, Niedhammer I. Psychosocial work factors and sleep problems: findings from the French national SIP survey. Int Arch Occup Environ Health. 2016;89: 485–95. doi: 10.1007/s00420-015-1087-1 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref038] 38.Bláfoss R, Sundstrup E, Jakobsen MD, Brandt M, Bay H, Andersen LL. Physical workload and bodily fatigue after work: cross-sectional study among 5000 workers. Eur J Public Health. 2019;29: 837–42. doi: 10.1093/eurpub/ckz055 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref039] 39.Nyberg A, Peristera P, Toivanen S, Johansson G. Does Exposure to High Job Demands, Low Decision Authority, or Workplace Violence Mediate the Association between Employment in the Health and Social Care Industry and Register-Based Sickness Absence? A Longitudinal Study of a Swedish Cohort. International Journal of Environmental Research and Public Health. 2022;19: 53. doi: 10.3390/ijerph19010053 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref040] 40.LaMontagne AD, Krnjacki L, Kavanagh AM, Bentley R. Psychosocial working conditions in a representative sample of working Australians 2001–2008: an analysis of changes in inequalities over time. Occup Environ Med. 2013;70: 639–47. doi: 10.1136/oemed-2012-101171 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref041] 41.Landsbergis PA, Grzywacz JG, LaMontagne AD. Work organization, job insecurity, and occupational health disparities. American Journal of Industrial Medicine. 2014;57: 495–515. doi: 10.1002/ajim.22126 [DOI] [PubMed] [Google Scholar]

[pone.0324244.ref042] 42.Cerdas S, Härenstam A, Johansson G, Nyberg A. Development of job demands, decision authority and social support in industries with different gender composition – Sweden, 1991–2013. BMC Public Health. 2019;19: 758. doi: 10.1186/s12889-019-6917-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref043] 43.Tareq H, Nyberg A, Wennberg P, Redmalm D, Toivanen S, Mensah A. Prevalence of problem drinking in the Swedish workforce: differences between labour market industries based on gender composition and main job activity. BMC Public Health. 2024;24: 2683. doi: 10.1186/s12889-024-20163-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0324244.ref044] 44.Böckerman P. Perception of Job Instability in Europe. Social Indicators Research. 2004;67: 283–314. [Google Scholar]

[pone.0324244.ref045] 45.Burr H. Monitoring trends in psychosocial and physical working conditions: Challenges and suggestions for the 21st century. Scand J Work Environ Health. 2021;47: 329–33. doi: 10.5271/sjweh.3973 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Changes in working and health conditions in different sectors between 2010 and 2019 in a representative sample of French workers

Jean-Francois Gehanno

Ariane Leroyer

Manon Couvreur

Serge Volkoff

Laetitia Rollin

Roles

Abstract

Background

Methods and findings

Conclusion

Introduction

Method

Table 1. Dimensions description and scales used.

Population studied

Weighting methodology

Statistical analysis

Ethics statement

Results

Table 2. Description of the population included (weighted percentages).

Fig 1. Figure interpretation guide and global results.

Fig 2. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the manufacturing sector.

Fig 14. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the other services activities sectors.

Fig 3. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the electricity, gas, steam and air conditioning supply sector.

Fig 4. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the construction sector.

Fig 5. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the wholesale and retail trade sector.

Fig 6. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the transportation and storage services sector.

Fig 7. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the accommodation and food service activities sector.

Fig 8. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the information and communication services sector.

Fig 9. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the financial and insurance services sector.

Fig 10. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the professional, scientific and technical services sector.

Fig 11. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the administrative and support service activities sector.

Fig 12. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the public administration and defense sector.

Fig 13. Evolution of the percentage of workers exposed to psychosocial or physical risk factors and their health status in the human health and social work activities sector.

Table 3. Changes of the proportion of workers concerned by each item from 2010-2011 to 2018-2019 for each sector of activity.

Evolutions of working conditions

Evolutions of health status

Relations between exposures and health problems

Looking beyond trends

Discussion

Limitations

Strenghts

Main evolutions

Differences between sectors of activity

Conclusion

Acknowledgments

Data Availability

Funding Statement

References

Author response to Decision Letter 0

Decision Letter 0

Swaantje Wiarda Casjens

Roles

Author response to Decision Letter 1

Decision Letter 1

Swaantje Wiarda Casjens

Roles

Author response to Decision Letter 2

Decision Letter 2

Swaantje Wiarda Casjens

Roles

Acceptance letter

Swaantje Wiarda Casjens

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases