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A 34-year overview of night work by occupation and industry in France based on census data and a sex-specific job-exposure matrix

Abstract

Background

Night work has been increasing in the last decades due to new working arrangements for good and services production. Numerous studies have shown that night shift work causes disruptions in circadian rhythms that may affect health. In 2019, night shift work was classified as probably carcinogenic to humans by the International Agency for Research on Cancer, and may contribute to other health disorders. In this context, we assessed the number and proportion of workers exposed to night work today and investigated time trends by occupation and industry in France since 1982 in terms of prevention.

Methods

Using the data on work time schedules collected in the French Labour Force Surveys, sex- and period-specific job-exposure matrices (JEMs) to night work (working between midnight and 5 AM) were developed. After linkage of the JEMs with data of the national censuses of 1982, 1990, 1999, 2007 and 2015, the numbers and proportions of workers usually or occasionally exposed to night work were estimated.

Results

The number of night workers (usual and occasional) increased from 3.67 million in 1982 to 4.37 million in 2015 (15.8% vs 16.4%). Night work was more common in men than in women (e.g. 22.4% vs 10.0% in 2015), and usual night work largely increased after 2000 (4.4% in 1999, 7.2% in 2007). In 2015, 1.29 million men worked usually at night, including 882,000 workers in the service sector (63%) and 360,000 in the manufacturing and extracting industries (28%). For the same period, 581,000 women were usual night workers, most of them being employed in the service sector (90%). Among women, a 97% increase of usual night work was observed between 1982 and 2015.

Conclusions

This study shows that night work involves a growing number of workers in France, particularly in women in the service sector. These results raise concern about the public health impact of night work and particularly about the numbers of outcomes attributable to this exposure such as breast or prostate cancers.

Peer Review reports

Introduction

Several occupations have traditionally been carried out both day and night, such as those that require 24 hours services for health care or security. The need for working-time arrangements that allow goods and services to be produced 24 hours a day, 7 days a week has increased over the last decades. Shift work typically involves working outside the standard daytime hours — such as at night, during evenings, or starting on early morning — and shifts can be permanent, switching from day to night, or without any particular pattern. Night shift work is a common occupational exposure, with approximately 19 to 25% of all workers in Europe and the United States working a variety of night shift schedules [1, 2].

Numerous studies have shown that shift work, in particular night shift, causes disruptions in circadian rhythms that may affect well-being and health [3]. Exposure to light at night (LAN) can lead to misalignement of the central biological clock with the day-night cycle, that contributes to sleep changes and circadian disruption [4]. Moreover, shift work affects multiple daily activities such as eating, sleeping, physical activity, tobacco smoking and alcohol consumption. These exposures can vary depending on the studied health outcome (sleeping disorders may be more important for fatal driving accident and co-exposures for cancer outcomes) [3]. Based on a literature review in 2019, the IARC monograph concluded that night shift work was probably carcinogenic to Humans (group 2A) [3].

In France, up to 2001, due to its legislation, women were not allowed to work at night except for some very specific activities such as industries processing perishable goods and in hygiene or well-being activities. Since then and to be in compliance with the European law based on the principle of gender equality in the workplace, the French labour code has been modified to allow night work to women and pointed out the derogatory nature of night work implying an enhanced medical surveillance of night workers [5, 6].

Exposure assessment in epidemiological studies may require the use of job-exposure matrices (JEMs) when studies involve large populations [7, 8]. For night shift work, the assessment is often derived from national labour surveys which provide sociodemographic data for the working population or from studies by interviews on a random of population [9,10,11,12], and similarly for existing JEMs [13, 14].

In order to provide information on exposure to night work useful for occupational exposure surveillance, our objective in this paper was to present estimates of the number and proportion of workers exposed to night work in France, overall and by occupation and industry, and study their evolution over 34 years using census data and sex-specific job-exposure matrices.

Methods

The numbers and proportion of workers exposed to night work were estimated between 1982 and 2015 by sex and period by linking job-exposure matrices (JEMs) with occupational census data for the French population.

Development of the JEMs

A series of JEMs, tables reporting proportion of exposed workers for each job (occupation in an industry), were elaborated from the data on work time schedules collected in the French national Labour Force Surveys (“Enquête Emplois”). These surveys have been conducted annually since 1993 and quarterly continuously over the year since 2003 by the National Institute of Statistics and Economic Studies (INSEE) to provide information on employment status in France [15,16,17,18]. The surveys conducted among individuals over 15 years of age living in randomly selected households, included 110,000 to 150,000 individuals per year.

For each subject, the Labour Force surveys provide information on age, sex and current occupation and industry coded according to the Professions and socio-professional classification (“Profession et Catégorie Socio-professionnelle”, PCS) and French industries classification codes (“Nomenclature des activités française”, NAF), respectively [19,20,21,22,23]. Each subject was classified as a usual night worker, an occasional night worker or a non-night worker, based on the answer to the question: “Do you work at night, i.e. between midnight and 5:00 AM?: (1) yes usually, (2) yes only some nights, (3) never” in a specific block on the main job in the surveys from 1993 to 2002, or “In your main job, how often do you work at night, i.e. between midnight and 5:00 AM?: (1) usually; (2) occasionally; (3) never” in the surveys from 2003 to 2012 (Additional file 1). Because of significant changes in the wording of the questions on work time schedules after 2012, the categorization into usual or occasional night workers could not be applied using the subsequent surveys which were not used in the present analysis (see Additional file 1).

We developed a series of JEMs for men and women separately combining the survey data by 5-year periods (1993–1997, 1998–2002, 2003–2007, 2008–2012). This chronological breakdown coincides with the different versions of the national PCS and NAF classification system, and takes into account changes in the wording of the questions on night work (Additional file 1). The JEMs (PCS x NAF JEMs) were elaborated in a flexible way by combining the PCS codes at a 4-digit level (PCS-4) and the NAF codes at a 2- or 3-digit level (NAF-2, NAF-3). The probabilities of being a usual or an occasional night worker in the PCS x NAF JEMs were calculated as the proportion of usual and occasional night workers in each job defined by the combination of PCS-4 and NAF-3 codes under the following two conditions: (i) the job included at least 30 individuals, and (ii) the precision of the proportion of usual night workers did not exceed 10%. If these conditions were not met, jobs were aggregated by combining PCS-4 with NAF-2 instead of NAF-3 codes. For the occupations poorly represented in the Labour Force Surveys that could not meet the conditions above, the probabilities of exposure to usual or occasional night work were calculated by PCS codes only regardless of the NAF codes using a “PCS-only” JEM. A complete description of the JEMs development is provided in Additional file 1.

Statistical analysis

The sex- and period-specific JEMs were linked with the Census occupational data for metropolitan France (defined as European territory of France) using the sex, PCS and NAF codes as the matching variables. The census data from 1982, 1990, 1999, 2007 and 2015 were used [24, 25]. The 1982 and 1990 censuses were merged with the 1993–1997 JEM, the 1999 census with the 1998–2002 JEM, and the 2007 and 2015 censuses with the 2008–2012 JEM.

For each of these censuses, as presented in Fig. 1, the exposure assessment to night work was undertaken in two consecutive steps. First, the assessment was based on the detailed JEMs (PCSxNAF JEM), and taking into account the exposure period and sex. Secondly, for the job that would not have been assessed by the PCSxNAF JEM (certain jobs are not assessed due to lack of power), the exposure probability was assigned using the sex-specific PCS JEM assessing night work based only on the PCS. As the JEMs were sex-specific, the different exposure probabilities for men and women were considered at the time of the linkage (Fig. 1).

Fig. 1
figure 1

Example of linkage between the 1999 Census and the night work JEMs for 1998–2002 period

The numbers of usual and occasional night workers in France were obtained by multiplying the exposure probability provided by the JEMs by the number of workers in the job in the census data. The proportions of usual and occasional night workers were obtained by dividing the total number of usual and occasional night workers by the total number of workers in the population. A sensitivity interval (SI) for the proportion of exposed workers was calculated using the lower and upper bound of the confidence interval of the exposure probabilities provided by the matrix. The number and proportion of night workers were estimated for 1982, 1990, 1999, 2007 and 2015 according to sex in all employed workers aged 15 years and over in metropolitan France. These exposure indicators for occupation or industry groups were also given by sex, usual or occasional night work. The occupation or industry choices were based according to whether the groups of industry or occupation were comparable over time because of the different classification versions used in the censuses (Additional file 2).

Results

The number of night workers (usual and occasional) increased from 3.67 million in 1982 to 4.37 million in 2015 (15.8% vs 16.4%). During this same period, the French total workforce has increased by 15% from 23 million workers to nearly 27 million (Table 1).

Table 1 Number and proportion of usual and occasional night workers by sex and large industry group

Men

The total number of workers in France remained relatively stable between 1982 and 2015 with a workforce estimated at 13.0 to 14.0 million men per year (Table 1). During this period, the number of usual night workers increased by 80% from 712,000 to 1.29 million, while the estimated number of occasional night workers decreased by 20% from 2.23 to 1.80 million. In 2015, the proportions of usual and occasional night workers among men represented 9.3% 95%SI[6.4–12.5] and 13.0% [8.3–18.0] of the workforce, respectively.

In 1982, the 712,000 usual night workers were primarily employed in the service sector (337,000, 47%) and in the manufacturing and extracting industries (303,000, 43%). In 2015, among the 1.29 million usual night workers the most part (882,000, 63%) was employed in the service sector and 0.36 million in the manufacturing and extracting industries (28%). During the study period, the number of occasional night workers also increased slightly in the service sector (1.14 to 1.27 million), while it decreased sharply in the manufacturing and extracting industries (5.55 to 2.58 million). Nevertheless, the latter was the industry where the proportion of usual night workers was the highest in 2015 with 15.1% (Table 1).

Women

The contribution of women to the workforce in France increased sharply from 9.38 to 12.88 million women between 1982 and 2015 (+ 37%). In the same time, the number of usual night workers among women increased from 173,000 to 581,000 (+ 236%) and the number of occasional night workers from 554,000 to 701,000 women (+ 25%) (Table 1). In 2015, the proportions of usual and occasional night workers among women represented 4.5% [2.9–6.3] and 5.4% [2.9–8.3] of the workforce, respectively (Table 1).

The vast majority of the usual night workers among women was employed in the service sector (83% in 1982 vs 90% in 2015). This was also true for occasional night workers in 2015. The highest proportions of usual night workers in 2015 were observed in the manufacturing and extracting industries (5.3%) and in the service sector (4.6%) (Table 1).

Occupation and industry

In the service sector, the number of workers has largely increased between 1982 and 2015 (13 million vs 21 million, + 44% in men and + 85% in women). The proportion of night workers among men was quite stable over the period (23% that represents 2 million night workers in 2015) but increased by 25% in women (1.14 million in 2015) (Table 1). However, usual night work increased from 5 to 9% in men and doubled in women over the same period. In 2015, 1.4 million workers were usually working at night and 1.9 million occasionally and 35% were women.

In the transport sector, which is a male dominated sector (78% men in 1982 and 62% in 2015), night work increased by 25% in men (32% in 1982 to 41% in 2015, around 25,000 night workers), and doubled in women (16 to 32%, 12,000 night workers) (Fig. 2). The proportion of usual night workers has tripled in men and almost quadrupled in women over the same period. The number of male road transport night workers stayed stable during all the studied period, but the proportion of usual night workers increased by 75% (29% in 2015) while occasional night workers decreased by 25% (Table 2). Female road transport workers are scarce compared to men (7000 women vs 300,000 men) but among them 39% worked usually at night and 9% occasionally in 2015.

Fig. 2
figure 2

Trend in the proportion of night workers by sex. Health and transport activities

The sensitivity intervals presented on the figure were calculated for the proportion of total night workers (usual + occasional night workers)

Table 2 Number and proportion of usual and occasional night workers by sex and occupation

Conversely, the health sector, which is a female dominated sector (79% women in 2015), has largely increased between 1982 and 2015 from 1.6 million workers to 3.9 million (+ 143%). On the contrary, the proportion of night workers in this sector decreased for both men and women over the same period (− 22%). However, after 1999, we observed a great increase in usual night work (+ 81% in men and + 31% in women) (Fig. 2). Self-employed nurses are mostly working occasionally at night, although we observe a decrease by 50% in men and by 45% in women over the period (Table 2). On the other hand, general care nurses (salaried nurses) are more working usually at night particularly since 2007 (32% in men, 26% in women, 103,000 workers) than by occasional night work (18% in men, 15% in women, 63,000 workers). The number of midwife night workers largely increased between 1982 and 2015 (+ 146%) even if the proportion stayed stable in women (around 75% night workers) with a high increase for usual night work after 2000 (+ 143%).

In 2015, more than 90% of male army police officers and firefighters worked at night, representing 52,000 officers and 40,000 firefighters. The proportion of these night workers stayed quite stable during the studied period. In 2015, 60% of women army police officers (11,000 working nights) and 36% of women firefighters (1000) were usually working at night.

Discussion

This study describes the prevalence and proportion of night work among workers in France over more than 30 years, regardless of their status (salaried or self-employed), based on job-exposure matrices and census data.

Our study clearly shows an increase of usual night work in France from the 2000s (4.5% in 1999 to 7.0% in 2015). Conversely occasional night work has been less frequent (12.1% in 1999 to 9.4% in 2015) with overall night work being relatively stable over this period. The most important change concerns night work among women, who are increasingly working at night (7.7% in 1982 to 9.9% in 2015). This is explained by the French legislation concerning night work, which was until 2001 different according to sex. Before 2001, women were not allowed to work at night excepted in specific activities. According to Eurostat, nearly 2% of working French women were usual night workers in 1992 compared to nearly 5% in 2012 with an increase from 2.4 to 3.8% when considering the years framing the changes in the legislation [26].

The very large increase in the number of women working at night can also be explained by the growth in working women over this period (+ 37%) and particularly in job where women work usually at night (+ 150%). In comparison, the number of workers among men is relatively stable over the period (+ 0.2%) and usual night work increase moderately than among women (+ 79% in men). In 2015, the usual night workers are mainly in the service sector (1.4 million men and women) and in manufacturing and extracting industries (410,000 workers), the same observation applies to occasional night workers (1.9 million and 300,000 workers respectively). Night work was particularly frequent in public health activities, e.g. nurses, public administration, e.g. army officers, road transport activities, e.g. drivers, or among blue collar workers in the food-processing industries. It should be noted that the decrease in the number of night workers in the manufacturing and extracting industries could be explained by the sharp reduction of the workforce in this sector.

The Sumer surveys document the exposure of salaried workers in France to a wide range of occupational hazards. These national cross-sectional surveys were conducted in 1994, 2003, 2010 and 2017 by the French Directorate for Research, Studies and Statistics (DARES) and the French Ministry of Labour to assess occupational hazards among 25,000 to 50,000 French salaried workers based on questionnaire completed during the occupational health visits. The 2010 and 2017 surveys show that 14% of employees used to work at night between midnight and 5 AM even occasionally (20% among men and 8% among women, 3,521,100 employees working at night in 2017) [27,28,29]. Our own estimates for close years (2007 and 2015) were similar with 16% 95%SI [11–20] of night workers (22% [17–28] in men and 9% [6–13] in women, 3,307,100 employees working at night in 2015), despite the different exposure assessment method between the two studies. The occupations and industries with the highest number of night workers were also similar in the two studies.

At the European level, Eurostat compiles data on the active population of the Member States [26]. France is comparable in terms of percentage of night workers (usual and occasional) to the Netherlands, Finland and Greece (14.9%, 15.0 and 15.6% respectively vs 16% in France), but different from Portugal which has the lowest proportion (10%) or from Slovakia with the highest (23%). Our results are also similar to those in the United States with 9.1% [8.3–10.0] of men, and 5.6% [5.0–6.2] of women usually working at night compared to 9.3 and 4.5% respectively in our study [30]. The proportion of night work in sectors such as Healthcare and Manufacture are also comparable with 11.8%[9.6–14.6] and 10.8%[8.9–13.1] (10.3 and 12.2% respectively in our study). In 2011, in Canada, the proportion of usual night workers is higher than in France (12% vs 7% in 2015) but it includes rotating shifts [12]. However, comparisons of data at the international level must be made with caution due to variations in data collection methodology and definition of night work.

The PCS and NAF classifications used in both the Labour Force Surveys and in the Population Censuses have changed over time. The linkage between JEMs and population data could therefore be carried out based on the versions of classifications defined by period. Thus, we chose to develop several JEMs corresponding to periods with same versions of classifications, rather than developing only one JEM integrating a single version of classifications and several exposure periods. Only jobs from the 1982 and 1990 censuses coded in earlier versions of job classifications had to be cross-walked in order to be linked with the JEMs, using tables provided by the National Institute of Statistics (INSEE). This methodology reduced errors in matching the JEMs with the census data, but presents limitations for the study of temporal trends. Due to the modifications of the coding rules for certain jobs, we were unable to study the trends in night work exposure prevalence over the 30-year period in for example “Manufacture of leather and related products” (Additional file 2).

The French Labour Force survey concerns a very large sample of the population at work; however, some jobs (PCSxNAF defined at the finest level) present in the general census may not be represented in the survey and therefore not evaluated in the PCSxNAF JEMs. To limit this problem, a matrix developed on the PCS regardless of NAF (PCS JEM) was used for the jobs not assessed rather than consider them not exposed to night work (20% of the overall population was assessed by the PCS JEM in 1999). Eventually, few jobs were not evaluated (1016 individuals for the 1999 census out of more than 23 million individuals) but they are little concerned by night work (in 2007 and 2015 the unassessed PCS concern only women for field jobs in the construction sector). The changes in the frequency modality of night work rise a question about the increase observed in our results after 2000. For the entire population, we do indeed observe an increase in the percentage of usual night workers after 2000 (4.5% in 1999 vs 7% in 2015) and conversely a decrease in the percentage of occasional night workers (12.1% vs 9.4%), but this trend is also visible between 1990 and 1999. Moreover, the analysis carried out by occupational groups usually working at night before the 2003 legislation (nurses, army police officers) shows rather the opposite trend, with an increase in usual night work over time. The change in the definition of this frequency modality therefore does not seem to have had an impact on the results after 2003. The surveys after 2012 were not used in this analysis because of a new change in the question where the exposure to night work was assessed only in the last four weeks of work prior the interview and with important changes in the frequency modalities based on the percentage of work time (Additional file 1).

The JEMs for night work presented in this paper were developed using data collected in France from large samples of workers during cross-sectional surveys repeated over several decades. These data provided a solid basis for developing our job-exposure matrices using an a posteriori method [31, 32]. The large amount of data retrieved in census with detailed occupation data permits to analyse exposure to night work at a detailed level. The JEMs are easy tool that help assess exposure especially when information is not available such as night work. JEMs present some limitations such as the use of occupation and industry classifications that may group jobs with different exposures. Therefore, the JEMs exposure indices are averaged by job code and take into account the variation of exposure between different jobs or different seasons or different activities characteristics. When exposure to night work is studied as a risk factor for an outcome, it should be considered as a proxy as it does not take into account all the complex combination leading to circadian disruption [33]. Although this night work JEM is specific to the French working organization, our method is reproducible to obtain JEM specific to every working organization as similar data (census and labour force surveys) are available in many countries. This study is also easily reproducible on future data census and assess exposure to all workers in France regardless of sex and worker status (salaried and self-employed).

Although only results on night work are presented in this article, “evening” and “shiftwork” matrices has been developed using the same methodology and are available. It is also planned to develop a matrix combining night and shiftwork in order to take into account every type of shift rotation. This JEM could be used to estimate health impact in epidemiological studies (e.g. estimation of population-attributable fractions to night shift work for several cancers such as breast and prostate cancer), if additional data are available on exposures to other factors involving circadian disruptions, such as light at night, sleep disturbances, poor diet, lack of physical activity, lack of vitamin D [33,34,35].

Conclusion

This study presents the trends in workers working at night usually and occasionally according to industries and occupations over 34 years in order to monitor the trend of this exposure on the entire population at work and help target the occupational groups with the highest proportion of night workers. The development of matrices has also been extended beyond 2013 and makes it possible to construct new JEMs from the future French Labour Force surveys data.

Availability of data and materials

The night shift work JEMs will be available for consultation on the Exp-Pro website (http://www.exppro.fr) and the exposure indicators will be available by sex and region on the Santé publique France’ Géodes portal (http://www.geodes.santepubliquefrance.fr). The JEMs file are available upon reasonable request from Marie-Tülin Houot (marie.houot@santepubliquefrance.fr). The census data and French Labour Force surveys produced by the French National Institute for Statistics and Economic Studies (Insee) are publicly available on their website (http://www.insee.fr). The detailed files used for this study which include occupation and industry codes using French classification, sex, age, residency department, questions on night work (only for the Labour Force Survey) and number of workers are available upon request through the Insee website.

References

  1. Eurofound. Sixth European Working Conditions Survey – Overview report (2017 update). Luxembourg: Publications Office of the European Union; 2017.

    Google Scholar 

  2. NHIS Occupational Health Supplement (NHIS-OHS). 2015. Available from: https://wwwn.cdc.gov/NIOSH-WHC/chart/ohs-workorg/work?OU=*&T=OU&V=R.

  3. IARC. Night shift work. IARC Monogr Identif Carcinog Hazards Hum. 2020;124:1–371.

    Google Scholar 

  4. Vetter C. Circadian disruption: what do we actually mean? Eur J Neurosci. 2020;51(1):531–50.

    Article  Google Scholar 

  5. LAW n° 2001–397 of May 9, 2001 relating to professional equality between women and men [LOI n° 2001–397 du 9 mai 2001 relative à l'égalité professionnelle entre les femmes et les hommes], 2001–397 (2001).

  6. Agreement of May 2, 2002 on night work [Accord du 2 mai 2002 portant sur le travail de nuit], (2002).

  7. Kauppinen T, Toikkanen J, Pukkala E. From cross-tabulations to multipurpose exposure information systems: a new job-exposure matrix. Am J Ind Med. 1998;33(4):409–17.

    Article  CAS  Google Scholar 

  8. Févotte J, Dananché B, Delabre L, Ducamp S, Garras L, Houot M, et al. Matgéné: a program to develop job-exposure matrices in the general population in France. Ann Occup Hyg. 2011;55(8):865–78.

    PubMed  Google Scholar 

  9. Peters CE, Ge CB, Hall AL, Davies HW, Demers PA. CAREX Canada: an enhanced model for assessing occupational carcinogen exposure. Occup Environ Med. 2015;72(1):64–71.

    Article  Google Scholar 

  10. Eng A, T Mannetje A, Cheng S, Douwes J, Ellison-Loschmann L, McLean D, et al. The New Zealand workforce survey I: self-reported occupational exposures. Ann Occup Hyg. 2010;54(2):144–53.

    CAS  PubMed  Google Scholar 

  11. Carey RN, Driscoll TR, Peters S, Glass DC, Reid A, Benke G, et al. Estimated prevalence of exposure to occupational carcinogens in Australia (2011–2012). Occup Environ Med. 2014;71(1):55–62.

    Article  Google Scholar 

  12. Rydz E, Hall AL, Peters CE. Prevalence and recent trends in exposure to night shiftwork in Canada. Ann Work Expo Health. 2020;64(3):270–81.

    Article  Google Scholar 

  13. Harris MA, MacLeod J, Kim J, Pahwa M, Tjepkema M, Peters P, et al. Use of a Canadian population-based surveillance cohort to test relationships between shift work and breast, ovarian, and prostate cancer. Ann Work Expo Health. 2020;64(4):387–401.

    Article  Google Scholar 

  14. García AM, González-Galarzo MC, Kauppinen T, Delclos GL, Benavides FG. A job-exposure matrix for research and surveillance of occupational health and safety in Spanish workers: MatEmESp. Am J Ind Med. 2013;56(10):1226–38.

    Article  Google Scholar 

  15. Insee. Labour Force Surveys up to 2002 [Enquêtes sur l'emploi jusqu’en 2002]. Sources et méthodes. 2003:1–26. Available from: www.insee.fr/fr/metadonnees/source/fichier/emploi_jus2002.pdf.

  16. Givord P. A new Labour Force Survey [Une nouvelle Enquête Emploi]. ÉCONOMIE ET STATISTIQUE. 2003;362:59–66.

    Article  Google Scholar 

  17. Goux D. Labour Force Survey's history [Une histoire de l’Enquête Emploi]. ÉCONOMIE ET STATISTIQUE. 2003(N° 362):41–57.

  18. Insee. Continuous Labour Force Surveys [Enquête Emploi en continu]. Sources et méthodes; 2011. p. 1–31. Available from: www.insee.fr/fr/metadonnees/source/fichier/methodologie_emploi_continu.pdf

    Google Scholar 

  19. Insee. Professions and socio-professional classification (PCS) [Nomenclature des professions et catégories socio-professionnelles PCS]. 1st ed1982.

  20. Insee. Professions and socio-professional classification (PCS) [Nomenclature des professions et catégories socio-professionnelles PCS] 2003. Available from: www.insee.fr/fr/statistiques/fichier/2401328/Brochure_PCS_ESE_2003.pdf.

    Google Scholar 

  21. Insee. French industries classification (NAF) [Nomenclature d'activités française, NAF]. 1st ed; 1993.

    Google Scholar 

  22. Insee. French industries classification (NAF) [Nomenclature d'activités française, NAF]2003.

    Google Scholar 

  23. Insee. French industries and products classification (NAF rev. 2 -CPF Rev 2.1) [Nomenclatures d’activités et de produits françaises NAF rev. 2 -CPF Rev 2.1] 2008. Available from: https://www.insee.fr/fr/statistiques/fichier/2120875/Nomenclatures_NAF_et_CPF_Edition_2019.pdf.

    Google Scholar 

  24. Insee. Census population description [Présentation du recensement de la population]. Available from: https://www.insee.fr/fr/information/2383265.

  25. Insee. Population Census. Evolutions: why favor five-year evolutions compared to thos from 1999 [Recensement de la population. Évolutions: pourquoi privilégier les évolutions quinquennales par rapport à 1999]. 2014.

  26. Employed persons working at nights as a percentage of the total employment, by sex, age and professional status (%). EUROSTAT. 2020. Available from: https://ec.europa.eu/eurostat/web/labour-market/quality-of-employment/database. Cited 2020 24 Nov

  27. Arnaudo B, Léonard M, Sandret N, Cavet M, Coutrot T, Rivalin R, et al. Occupational risks in 2010: strong differences in exposure according to sectors. [Les risques professionnels en 2010: de fortes différences d’exposition selon les secteurs.]. DARES ANALYSES. 2013(10).

  28. Matinet B, Rosankis E. Exposure to occupational risks: organizational and relationship constraints. [Les expositions aux risques professionnels: Les contraintes organisationnelles et relationnelles.]. Synthèsestat’. 2019;30.

  29. Matinet B, Rosankis E, Léonard M. Exposure to occupational risks by occupational group. [Les expositions aux risques professionnels par famille professionnelle.]. Synthèsestat’. 2020;34.

  30. Work Organization Characteristics (NHIS 2015) Charts. National Health Interview Survey (NHIS 2015). 2015. Available from: https://wwwn.cdc.gov/NIOSH-WHC/chart/ohs-workorg?OU=*&T=OU&V=R. Cited 28 April 2020

  31. Kauppinen T. Exposure assessment - a challenge for occupational epidemiology. Scand J Work Environ Health. 1996;1996:401–3.

    Article  Google Scholar 

  32. Benke G, Sim M, Fritschi L, Aldred G, Forbes A, Kauppinen T. Comparison of occupational exposure using three different methods: hygiene panel, job exposure matrix (JEM) and self reports. Appl Occup Environ Hyg. 2001;2001:84–91.

    Article  Google Scholar 

  33. Peters S, Hall AL. Is a JEM an informative exposure assessment tool for night shift work? Occup Environ Med. 2021;78(11):780–1.

    Article  Google Scholar 

  34. Fernandez RC, Peters S, Carey RN, Davies MJ, Fritschi L. Assessment of exposure to shiftwork mechanisms in the general population: the development of a new job-exposure matrix. Occup Environ Med. 2014;71(10):723–9.

    Article  Google Scholar 

  35. Fernandez RC, Moore VM, Willson KJ, Davies M. Night shift work undertaken by women and fertility treatment interact to increase prevalence of urogenital anomalies in children. Occup Environ Med. 2021;78(11):782–8.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank, the French Ministry of Labour and the French National Institute for Statistics and Economic Studies for sharing French Labour Force survey and Census data, respectively.

Funding

None.

Author information

Authors and Affiliations

Authors

Contributions

PG and CP designed the study. All authors participated in the development methodology of the JEM. NT and ECD participated in the conception of the JEM based on existing data. MTH analysed the data and interpreted the data in collaboration with ECD. MTH, ECD, PG and CP drafted and revised the manuscript. All authors approved the final version.

Corresponding author

Correspondence to Marie-Tülin Houot.

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Supplementary Information

Additional file 1.

Detailed JEM development methodology.

Additional file 2.

Groups of occupation and industries comparable over time throughout the different job classifications used in the Censuses.

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Houot, MT., Tvardik, N., Cordina-Duverger, E. et al. A 34-year overview of night work by occupation and industry in France based on census data and a sex-specific job-exposure matrix. BMC Public Health 22, 1441 (2022). https://doi.org/10.1186/s12889-022-13830-5

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