Original research Occupational health, frontline workers and COVID-­19 lockdown: new gender-­related inequalities? Mireia Utzet ‍ ‍,1,2,3 Amaia Bacigalupe ‍ ‍,4,5 Albert Navarro ‍ ‍6,7 ► Additional supplemental ABSTRACT under-­ recognised and significantly invisibilised,4; material is published online Introduction The abrupt onset of COVID-­19, with its even categorised as ‘dirty work’.5 only. To view, please visit the journal online (http://​dx.​ rapid spread, has had brutal consequences in all areas of The implications of such a cessation of labour doi.​org/​10.​1136/​jech-​2021-​ varied greatly according to the type of sector. On the society, including the workplace. In this paper, we report 217692). the working conditions, health, and tranquilisers and one hand, people working on site in sectors defined 1 as essential (the frontline essential workers, from opioid analgesics use of workers during the first months Center for Research in now on, frontline workers) remained in employ- of the ensuing pandemic, according to whether they Occupational Health (CISAL), Universitat Pompeu Fabra, ment, generally in their usual place of work, but were frontline workers or not and also according to sex. Barcelona, Spain Methods Our analysis is based on cross-­sectional under extraordinary working and emotional condi- tions6; in many cases, they had to work without the 2 CIBER of Epidemiology and survey data (collected during April and May 2020) from Public Health (CIBERESP), the wage-­earning population in Spain (n=15 070). We necessary preventive measures, involving high levels Barcelona, Spain 3 IMIM, Parc Salut Mar, estimate prevalences, adjusted prevalence differences of risk for themselves and their families.7 On the Barcelona, Spain and adjusted prevalence ratios by sex and according to other hand, people working in non-­essential sectors 4 Department of Sociology and whether the worker is a frontline worker or not. and those working in essential sectors but were not Social Work, University of the Results Employment and working conditions, exposure in the frontline suffered radical changes in their Basque Country (UPV/EHU), employment and working conditions,8 such as the to psychosocial risks, as well as health status and the 48940 Leioa, Spain 5 Social Determinants of Health consumption of tranquilisers and opioid analgesics all imposition of teleworking, especially among non-­ and Demographic Change-­OPIK showed sex and sectoral (frontline vs non-­frontline) manual workers, the suspension of employment or Research Group, University of inequalities, which placed essential women workers reduction of working hours due to the application the Basque Country (UPV/EHU), in a particularly vulnerable position. Moreover, the of a temporary lay-­off procedure, the non-­renewal 48940 Leioa, Spain 6 Research Group on consumption of tranquilisers and opioid analgesics of temporary contracts or dismissal. Psychosocial Risks, Organization increased during the pandemic and health worsened From a gender perspective, the cessation of of Work and Health (POWAH), significantly among frontline women workers. activity had unequal consequences: many of the Universitat Autonoma de Conclusions The exceptional situation caused by the workers considered essential, because of their role Barcelona, Cerdanyola del COVID-­19 pandemic provides an opportunity to revalue in the reproduction of society and life, were women, Vallès, Spain 7 Unitat de Bioestadística, essential sectors and to dignify such employment and especially in sectors such as healthcare, cleaning, Facultat de Medicina, working conditions, especially among women. There is angeriatric care or food retail. Moreover, prior to the Universitat Autonoma de urgent need to improve working conditions and reduce pandemic, these sectors already showed precarious Barcelona, Cerdanyola del employment and working conditions and indicators occupational risk, particularly among frontline workers. Vallès, Spain In addition, this study highlights the public health of poor physical and mental health.9–11 Essential problem posed by tranquilisers and opioid analgesics and non-­essential women workers who teleworked Correspondence to Dr Mireia Utzet, Center for consumption, especially among frontline women. also had to take over most of the care and main- Research in Occupational Health tenance of household welfare,12 and this may be (CISAL), Universitat Pompeu associated with deterioration of their mental health Fabra, Barcelona 08003, Spain; during the lockdown,13 especially among the most ​mireia.​utzet@​upf.​edu INTRODUCTION vulnerable women.14 Received 20 July 2021 Spain was one of the countries most affected by Since the beginning of the pandemic, occupa- Accepted 2 February 2022 the 2020 COVID-­19 pandemic, caused by SARS-­ tional health research has been very fruitful but has CoV-­2.1 During the first wave, Spain became one mainly focused on morbidity and mortality asso- of the European epicentres of the pandemic in ciated with COVID-­ 19 in healthcare workers.15 terms of diagnosed cases. As in most European There is less research on frontline non-­healthcare countries, the first wave was controlled through workers, but it appears that the lack of preventive 16 17 the imposition of a state of alarm and strict lock- measures, the risk of COVID-­19 infection and 6 down measures, which included the shutdown of the deterioration of the mental health of frontline © Author(s) (or their most social activities and employment, except for workers were very high. However, most studies employer(s)) 2022. No workers in the economic sectors classified as ‘essen- did not incorporate a gender perspective in their commercial re-­use. See rights tial’ in ad hoc regulations.2 Despite the lack of an analysis. and permissions. Published by BMJ. agreed definition of essential in this context, we can The potential impact of the pandemic on occu- assume that it includes all those activities that are pational health in Spain has to be understood in To cite: Utzet M, necessary for the continuation of life and society, the context of the Spanish national labour market, Bacigalupe A, Navarro A. J which some authors have called ‘life-­making activ- which is characterised by high chronic unemploy- Epidemiol Community Health 18 Epub ahead of print: [please ities’.3 This therefore clearly includes the health- ment, as well as precariousness and segmentation 19 include Day Month Year]. care sector, but also cleaning, food retail, transport by gender, age, class and country of origin. This doi:10.1136/jech-2021- and security sectors, which are characterised by a implies that people who occupy less advantaged 217692 high proportion of jobs that are usually socially social positions are relegated to the bottom rungs Utzet M, et al. J Epidemiol Community Health 2022;0:1–7. doi:10.1136/jech-2021-217692 1 Original research of the occupational structure and, more specifically, that women dose, or I have changed to a stronger one/yes, I do not usually systematically experience more unemployment and tempo- consume them but in this period, I have). Both questions were rary employment20 and precariousness,21 as well as being more split into two variables: tranquiliser or painkiller consumption exposed to certain psychosocial risks.22 The few studies that among those who were taking them before the state of alarm was have analysed the impact of the pandemic on working condi- declared (same dose/increased dose) and tranquiliser consump- tions generally note a significant deterioration in working condi- tion among those who were not taking them before the state tions and health indicators, especially among certain vulnerable of alarm was declared (still not consuming/started to consume). groups of workers.8 Finally, other sociodemographic variables included in the Health and economic crises often have differential impacts analysis were sex, age and occupational social class, which was according to gender, and existing gender inequalities can be obtained using the 2011 National Classification of Occupations reinforced.23 Therefore, in this paper, we analyse working (CNO11), which is based on the International Standard Clas- conditions, health, and tranquilisers and opioid analgesics sification of Occupations (ISCO88) and was divided into non-­ consumption among wage-­earner men and women during the manual and manual workers. first months of the COVID-­19 pandemic, according to whether they were frontline or non-­frontline workers. Statistical analysis The prevalence of the different items was estimated by sex and METHODS type of worker (frontline/non-­ frontline). Prevalence differ- This is an observational cross-­ sectional study based on data ences adjusted by age and occupational social class, with their from an online survey carried out between 29 April and 28 May respective 95% CIs, were calculated by sex and type of job. 2020, including 20 328 participants. The study population was The adjusted prevalence ratio (aPR) by age and occupational all wage-­earners in Spain who had a job on 14March 2020 (the social class and the corresponding 95% CI were estimated using day the state of alarm began). The sampling designs applied are Poisson regression with robust variance.30 reported elsewhere.8 In the present study, we excluded people All the analysis was carried out using data weighted according who were subsequently fired or affected by a temporary lay-­off to gender crossed with age and occupational social class distri- procedure, so the final sample size included 15 070 participants. butions from the last quarter of 2020, taken from the survey of Workers were initially classified as essential or non-­essential, the active population in Spain (EPA), to mitigate any possible based on the answer to a self-­report question. In addition, essen- selection bias due to the sociodemographic and occupational tial workers who had to go to work during the estate of alarm structure (the distribution of the participants by gender and were categorised as frontline workers, and those who, at the employment, using both non-­weighted and weighted data, is time of answering, had been fired, affected by a temporary lay-­ presented in online supplemental table S2). All the calculations off procedure or could stay at home teleworking were grouped were conducted with STATA V.14.2 (College 35 Station, Texas, with the non-­ essential workers (overall called non-­ frontline USA). workers). Online supplemental table S1 presents the distribu- tion of the main sectors of the frontline workers and the non-­ RESULTS frontline workers. As presented in table 1, frontline workers, who represented The employment and working conditions recorded included: 29.9% of our sample, were slightly older and employed in contract relationship (permanent/temporary) and salary that manual occupations in a proportion twice as large as non-­ covers basic needs (always and many times/sometimes, only frontline workers (69.2% vs 31.0%), specifically in catering, once, and never). Psychosocial risks were assessed with items personal and protection services, and salespersons (28.6% vs corresponding to the short version of the Copenhagen Psychoso- 11.3% and unskilled workers (18.0% vs 7.7%). In terms of cial Questionnaire (CoPsoQ)24 adapted to Spanish and validated gender differences, among both frontline and non-­ frontline in Spain (COPSOQ-­ Istas21).25 Four psychosocial dimensions occupations, the age distribution is similar, while the proportion were included: emotional demands, social support, work–family of men in manual occupations is higher than that of women. conflict and job insecurity. Meanwhile, the demand–control Among the frontline occupations, the high proportion of women model26 was measured with the partial scales for psychological in catering, personal and protection services, and salespersons demands and control, which are considered to provide a good (36.6%) and unskilled workers (22.9%) stands out. More than reflection of the original instrument.27 60% of frontline female workers were in the healthcare (31.3%), The health status of workers was assessed using general and social care (19.0%) or cleaning (14.2%) sectors, while approxi- mental health indicators. One item referring to general health mately 60% of frontline men were employed in the construction was included ‘How do you consider your current state of health, and industry (26.6%), transport (22.0%) or healthcare (12.6%) compared to before the state of alarm was declared?’ (better or sectors (see online supplemental table S1). unaltered/worse). Mental health was gauged using the Mental As shown in table 2, frontline and non-­frontline workers did Health domain of the Spanish version of the Short Form-­36 not differ in their contract relationship, but the proportion of health survey (SF -36)28: a generic instrument for assessing workers whose salary sometimes, only once, or never covered health-­related quality of life. Participants were classified as ‘at basic needs was higher among frontline workers (32.2% vs risk of poor mental health’ when their score was 56 or lower. 23.9%). There were clear differences by sex, with women expe- Drug consumption was assessed via questions from the survey riencing more temporary contracts (28.8% vs 15.3% among on alcohol and other drugs in Spain (EDADES) of the National frontline workers and 23.3% vs 17.0% among non-­frontline Drug Plan.29 Two questions were included: ‘In the past thirty workers) and worse wages (39.4% vs 26.0% among frontline days, have you used any tranquilisers/sedatives or sleeping pills?’ workers and 27.0 vs 20.5 among non-­ frontline workers). In and ‘In the past thirty days, have you used painkillers (opioids)?’ terms of exposure to psychosocial risks, frontline workers were (no/yes, I was taking them before and now I take the same dose/ less exposed to high levels of job insecurity (29.5% vs 38.2%) yes, I was taking them before but now I have increased my as well as to high work–family conflict (48.6% vs 55.1%) than 2 Utzet M, et al. J Epidemiol Community Health 2022;0:1–7. doi:10.1136/jech-2021-217692 Original research Table 1 Sociodemographic characteristics of frontline and non-­frontline workers and by sex (%) Frontline workers Non-­frontline workers Women Men Total Women Men Total Total 46.8 53.2 100.0 52.8 47.2 100.0 Age (years)  16–34 24.4 23.0 23.6 18.8 22.2 20.4  35–49 42.4 44.9 43.7 55.0 43.0 45.0  50 or over 33.2 32.0 32.7 34.4 34.8 34.6 Occupational social class (CNO11)  Directors and managers 1.0 2.4 1.7 3.1 5.2 4.1  Scientists, academics and similar professionals 19.8 8.6 13.8 35.7 29.5 32.8  Technicians; professional support staff 4.6 11.0 8.0 13.1 16.3 14.6  Accountants, administrative workers and other office employees 9.7 5.1 7.3 22.6 11.7 17.5  Workers in catering, personal and security services, and salespersons 36.6 21.4 28.6 13.4 9.0 11.3  Skilled agricultural, forestry and fishing sector workers 0.4 2.1 1.3 0.2 1.8 1.0  Crafts persons and skilled workers in manufacturing and construction (except installers and machine operators) 1.6 16.9 9.6 1.1 13.1 6.7  Installers, machine operators and assemblers 3.7 18.9 11.7 1.5 7.4 4.2  Unskilled workers 22.9 13.6 18.0 9.3 6.0 7.7 Occupational social class  Non-­manual 34.9 27.1 30.8 74.5 62.7 69.0  Manual 65.1 72.9 69.2 25.5 37.3 31.0 CNO11, 2011 National Classification of Occupations. non-­frontline workers. In addition, female frontline workers onset, frontline workers showed a slightly higher consumption were more exposed than male frontline workers to high levels of of tranquilisers and opioid analgesics (14,7% increased the dose emotional demands (71.8% vs 57.7%) and high strain (50.7% vs of tranquilisers, 12.0% of them started using opiates and 28.5% 38.5%). Workers in frontline sectors had a higher risk of suffering increased their dose, compared with 11,9%, 9.5% and 24.7%, poor mental health than those in non-­frontline sectors (56.8% vs respectively, among non-­frontline workers) and women more so 52.6%), and in both cases, women had poorer health. As for the than men. The only exception referred to those starting to use consumption of tranquilisers and opioid analgesics, we assume a tranquillisers, whose proportion is higher among non-­frontline prepandemic scenario in which approximately 12% of women users. and 7% of men, both frontline and non-­frontline workers, were Table 3 shows that women in frontline sectors had significantly taking them (online supplemental table S3). After the pandemic worse conditions than those in non-­frontline sectors: a higher Table 2 Prevalence of employment and working conditions, psychosocial exposure, health characteristics and drug consumption, by type of employment and sex (%) Frontline workers Non-­frontline workers Women Men Total Women Men Total Employment and working conditions  Temporary contract 28.8 15.3 21.9 23.3 17.0 20.3  Salary sometimes, only once or never covers basic needs 39.4 26.0 32.2 27.0 20.5 23.9 Psychosocial exposure  Exposed to high emotional demands 71.8 57.7 64.4 70.8 69.0 70.0  Exposed to low social support 44.1 42.1 43.0 41.8 38.1 40.1  Exposed to high job insecurity 27.4 31.7 29.5 37.0 39.5 38.2  Exposed to high work–family conflict 49.2 47.8 48.6 56.4 53.6 55.1  Exposed to high strain 50.7 38.5 44.3 40.8 36.9 39.0 Health characteristics and drug consumption  Worse general health than before the state of alarm 45.5 28.8 36.6 46.6 33.9 37.4  At high risk of suffering poor mental health: 68.7 46.9 56.8 60.3 44.1 52.6  Increased tranquiliser consumption among those who were taking them before the state of alarm* 39.3 26.4 34.2 41.5 29.3 37.4  Started to consume tranquilisers during the state of alarm† 20.5 9.7 14.7 14.9 8.7 11.9  Increased painkiller (opioid) consumption among those who were taking them before the state of alarm* 32.5 21.6 28.5 28.1 17.3 24.7  Started to consume painkillers (opioids) during the state of alarm† 15.3 9.2 12.0 10.3 8.5 9.5 *Category not shown: same dose. †Category not shown: still not consuming. Utzet M, et al. J Epidemiol Community Health 2022;0:1–7. doi:10.1136/jech-2021-217692 3 Original research Table 3 Adjusted prevalence difference and 95% CI,* and adjusted prevalence ratio (aPR and 95% CI),* for employment and working conditions, psychosocial exposure, health characteristics and drug consumption among frontline versus non-­frontline workers, according to sex Women Men Prevalence difference Prevalence difference (95% CI)† aPR (95% CI)‡ (95% CI)† aPR (95% CI)‡ Employment characteristics  Temporary contract 3.9 (12.8 to 6.5) 1.16 (1.05 to 1.28) −2.9 (−6.9 to 1.0) 0.83 (0.66 to 1.06)  Salary sometimes, only once or never covers basic needs 12.4 (9.7 to 15.0) 1.46 (1.35 to 1.58) 0.1 (−3.5 to 3.7) 1.00 (0.86 to 1.17) Psychosocial exposure (reference category: not exposed)  Exposed to high emotional demands 5.0 (2.1 to 7.9) 1.07 (1.03 to 1.12) −8.5 (−12.9 to −0.4) 0.87 (0.81 to 0.94)  Exposed to low social support −1.5 (−4.7 to 1.6) 0.96 (0.90 to 1.04) 1.3 (−3.3 to 6.0) 1.03 (0.92 to 1.16)  Exposed to high job insecurity −14.1 (−16.9 to −11.4) 0.64 (0.58 to 0.70) −12.3 (−16.4 to −8.2) 0.71 (0.63 to 0.80)  Exposed to high work–family conflict −5.6 (−8.9 to −2.3) 0.90 (0.84 to 0.96) −5.0 (−9.6 to −0.3) 0.91 (0.83 to 0.99)  Exposed to high strain 1.7 (−1.5 to 4.9) 1.04 (0.97 to 1.12) −1.3 (−5.9 to 3.4) 0.97 (0.86 to 1.09) Health characteristics and drug consumption  Worse general health than before the state of alarm 2.5 (−0.4 to 5.6) 1.06 (0.99 to 1.14) −4.2 (−8.2 to −0.5) 0.88 (0.77 to 1.00)  At high risk of suffering poor mental health: 3.6 (0.7 to 6.5) 1.06 (1.01 to 1.11) 0.4 (−4.1 to 4.9) 1.01 (0.91 to 1.11)  Increased tranquiliser consumption among those who were taking −3.3 (−10.7 to 4.1) 0.92 (0.76 to 1.11) −2.0 (−13.9 to 9.9) 0.93 (0.61 to 1.42) them before the state of alarm  Started to consume tranquilisers during the state of alarm 4.6 (1.9 to 7.3) 1.30 (1.11 to 1.52) 0.5 (−1.9 to 3.0) 1.06 (0.81 to 1.38)  Increased painkiller (opioid) consumption among those who were 2.5 (−4.6 to 9.7) 1.09 (0.85 to 1.39) 3.90 (−8.6 to 16.3) 1.23 (0.64 to 2.34) taking them before the state of alarm  Started to consume painkillers (opioids) during the state of alarm 2.1 (0.0 to 4.2) 1.19 (1.00 to 1.41) −0.6 (−3.0 to 1.8) 0.94 (0.71 to 1.23) *Adjusted by age and occupational social class. †(prevalence in frontline workers – prevalence in non-­frontline workers). ‡Reference category: non-­frontline workers. rate of temporary contracts (aPR: 1.16 (95% CI 1.05 to 1.28)), aPR=1.21 (95% CI 1.11 to 1.32)) and a greater risk of suffering worse pay (aPR: 1.08 (95% CI 1.01 to 1.17)), while no signifi- poor mental health (aPR=1.48 (95% CI 1.37 to 1.59) and cant difference was observed among men. Among women, those aPR=1.39 (95% CI 1.31 to 1.48)) than men. The same pattern in frontline sectors were exposed to higher emotional demands held for the initiation of tranquilliser consumption among non-­ than those in non-­frontline sectors (aPR=1.07 (95% CI 1.03 users (aPR=2.10 (95% CI 1.69 to 2.60) and aPR=1.78 (95% CI to 1.12)), had less job insecurity (aPR: 0.64 (95% CI 0.58 to 1.49 to 2.12)) and of opiates (aPR=1.67 (95% CI 1.35 to 2.08) 0.70)) and less work–family conflict (aPR=0.90 (95% CI 0.84 to and aPR=1.32 (95% CI 1.09 to 1.60)). These differences were 0.96)). Among men, those working in frontline sectors also had more pronounced among frontline workers. both less emotional demands (aPR=0.87 (95% CI 0.81 to 0.94)) and job insecurity (aPR=0.71 (95% CI 0.63 to 0.80)) together with lower levels of work–family conflict (aPR=0.91 (95% CI DISCUSSION 0.83 to 0.99)). Finally, women in frontline sectors showed worse The abrupt emergence of COVID-­19 and its rapid spread had health and more tranquilisers and opioid analgesics consump- brutal consequences in all areas of society, including, of course, tion than those in non-­ frontline sectors (poor mental health the workplace. The main results of this study suggest that (aPR: 1.06 (95% CI 1.01 to 1.11)) and initiation of tranquilliser employment and working conditions, exposure to psychoso- use (aPR: 1.30 (95% CI 1.11 to 1.52) and opiate use (aPR: 1.19 cial risks, as well as health status and the consumption of tran- (95% CI 1.00 to 1.41)). Among men, there were no significant quilisers and opioid analgesics, all show gender inequalities and differences by type of employment. inequalities according to whether they were frontline or non-­ The differences between women and men in employment and frontline workers. working conditions were significant among both frontline and With few exceptions, while an overall analysis shows no non-­frontline workers (see table 4). Women were more engaged remarkable differences between frontline and non-­ frontline in temporary contract arrangements than men (aPR=1.83 (95% workers, an analysis by sex reveals significant inequalities. 1.56 to 2.14) in frontline and aPR=1.44 (95% CI 1.25 to 1.65) Overall, frontline women workers endure worse employment for non-­frontline) and were paid less (aPR=1.59 (95% CI 1.42 conditions, are exposed to high levels of emotional demands to 1.79) and aPR=1.50 (95% CI 1.33 to 1.68). Whether they (but lower job insecurity), have poorer health and consume were frontline or non-­frontline workers, women were exposed more tranquilisers and opioid analgesics than non-­ frontline to significantly higher levels of work-­related strain (aPR=1.34 women. In contrast, men present almost no remarkable differ- (95% CI 1.21 to 1.47) and aPR=1.17 (95% CI 1.08 to 1.27)) ences according to whether they are frontline or non-­frontline than men. Only among frontline workers were women exposed (except that frontline workers are exposed to lower levels of to higher emotional demands (aPR=1.22 (95% CI 1.14 to 1.30)) work-­related strain, work–family conflict and job insecurity). and experienced less job insecurity (aPR=0.86 (95% CI 0.77 to The poorer employment and working conditions of frontline 0.97)). Among both frontline and non-­frontline workers, women women workers may reflect the undervaluation and increased had worse general health (aPR=1.56 (95% CI 1.40 to 1.74) and precariousness of most occupations highly feminised (many 4 Utzet M, et al. J Epidemiol Community Health 2022;0:1–7. doi:10.1136/jech-2021-217692 Original research Table 4 Adjusted prevalence difference and 95% confidence interval (95% CI),* and adjusted prevalence ratio (aPR and 95% CI),* of employment and working conditions, psychosocial exposure, health characteristics and drug consumption in women versus men, according to employment (frontline/non-­frontline) Frontline workers Non-­frontline workers Prevalence difference Prevalence difference (95% CI)† aPR (95% CI)‡ (95% CI)† aPR (95% CI)‡ Employment conditions  Temporary contract 12.9 (9.9 to 16.0) 1.83 (1.56 to 2.14) 7.3 (4.7 to 9.9) 1.44 (1.25 to 1.65)  Salary sometimes, only once or never covers basic needs 15.0 (11.5 to 18.4) 1.59 (1.42 to 1.79) 9.5 (7.0 to 12.0) 1.50 (1.33 to 1.68) Psychosocial exposure  Exposed to high emotional demands 12.8 (8.8 to 16.8) 1.22 (1.14 to 1.30) 0.9 (-­1.9 to 3.8) 1.01 (0.97 to 1.06)  Exposed to low social support 2.8 (−1.2 to 6.8) 1.07 (0.97 to 1.17) 4.8 (1.4 to 8.2) 1.13 (1.03 to 1.23)  Exposed to high job insecurity −4.3 (−7.9 to −0.7) 0.86 (0.77 to 0.97) −0.7 (−3.7 to 2.3) 0.98 (0.91 to 1.06)  Exposed to high work–family conflict 4.8 (−3.6 to 4.6) 1.01 (0.93 to 1.10) 1.9 (−1.3 to 5.1) 1.04 (0.98 to 1.10)  Exposed to high strain 13.0 (9.0 to 17.0) 1.34 (1.21 to 1.47) 6.2 (3.0 to 9.3) 1.17 (1.08 to 1.27) Health characteristics and drug consumption  Worse general health than before the state of alarm 16.3 (12.7 to 19.9) 1.56 (1.40 to 1.74) 7.1 (4.0 to 10.1) 1.21 (1.11 to 1.32)  At high risk of suffering poor mental health: 22.1 (18.3 to 25.9) 1.48 (1.37 to 1.59) 17.3 (14.2 to 20.4) 1.39 (1.310 to 1.48)  Increased tranquiliser consumption among those who were taking 12.3 (1.7 to 22.9) 1.45 (1.02 to 2.05) 11.7 (3.3 to 20.1) 1.39 (1.07 to 1.82) them before state of alarm  Started to consume tranquilisers during the state of alarm 10.8 (8.1 to 13.5) 2.10 (1.69 to 2.60) 6.8 (4.9 to 8.7) 1.78 (1.49 to 2.12)  Increased painkiller (opioid) consumption among those who were 9.8 (−2.2 to21.8) 1.44 (0.86 to 2.40) 10.9 (2.7 to 19.1) 1.65 (1.07 to 2.57) taking them before the state of alarm  Started to consume painkillers (opioids) during the state of alarm 6.2 (3.8 to 8.5) 1.67 (1.35 to 2.08) 2.6 (0.9 to 4.3) 1.32 (1.09 to 1.60) *Adjusted by age and occupational social class. †(Prevalence among women – prevalence among men). ‡Reference category: men. of which are considered essential because they are life-­making could be due to a compensation effect: on the one hand, while jobs) demonstrated in studies prior to the pandemic.21 31 Front- men with essential jobs who had to work outside could have seen line women workers report greater exposure to high emotional their health protected by effect of maintaining a breadwinner demands than non-­frontline women, which could be explained role,35 men who stayed at home could have suffered worse by the emotional strain of working on the frontline during the health indicators, for this same question. Although staying at first weeks of the pandemic,32 in many cases without the neces- home was not necessarily associated with a higher risk of losing a sary protection.33 In the case of men, there is no such greater job, it could destabilise the traditional male breadwinner identity exposure to emotional demands among frontline workers. This (assuming even traditionally female roles), with negative reper- difference could be explained by the composition of essential cussions on their health.36 sectors for women and men. Among frontline women workers, a If we focus on gender inequalities within the frontline and high proportion work in sectors involving interaction with other non-­frontline workers, we find that, in both sectors, women people (whether they are sick or not), such as health and social have worse employment and are more exposed to high levels of care or retailing, whereas among frontline men workers, a higher work-­related strain than men. Moreover, among the frontline proportion work in sectors such as construction or industry, workers, women are more exposed to higher levels of emotional where the emotional demand is lower and there is almost no demands but less exposed to job insecurity. Despite the prolif- social interaction. eration of research aimed at providing an understanding of the Concerning health dimensions, the emotional demands to effects of the pandemic, there is almost no work that addresses which frontline women workers are exposed could have condi- inequalities in working conditions and health between frontline tioned the worsening of general and mental health that we and non-­frontline workers from a gender perspective. Histori- found, a hypothesis put forward in similar research.34 In addi- cally, the gender perspective in occupational health research has tion, this worsening could also be related to the fear of contagion been limited, as several reviews have revealed.35 Even so, these from themselves and their families through them.8 Finally, and findings are consistent with prepandemic studies that describe perhaps because of these working conditions and the deteriora- marked gender inequalities in relation to job insecurity and tion of mental health, a higher proportion of frontline women wages21 31 but few inequalities in exposure to psychosocial risks started to consume tranquilisers and opioid analgesics. Despite between men and women.22 Differences in the exposure to job the public health implications of this last finding, to the best of insecurity will need to be thoroughly explored in future articles. our knowledge, no similar research has been published. Among Regarding the health indicators, the pandemic has resulted men, there are no differences in health or consumption between in a clear deterioration of both general and mental health, in those in frontline and non-­frontline sectors. This result could both men and women. If we compare our current findings with be explained by the aforementioned lower emotional demand similar studies from before the pandemic, the prevalence of poor associated with the majority of sectors among frontline men mental health has doubled22 while sustaining gender inequali- workers—compared with frontline women. However, it also ties. Furthermore, the results presented here demonstrate how Utzet M, et al. J Epidemiol Community Health 2022;0:1–7. doi:10.1136/jech-2021-217692 5 Original research the health crisis has triggered an increase in the consumption of frontline women workers in a particularly vulnerable position. tranquilisers and opioid analgesics among women, who already There is an urgent need to improve working conditions and consumed more than men, and especially among the frontline reduce occupational risks, particularly among frontline workers. workers. These results are consistent with other research in the On the other hand, this study highlights the public health general population, which shows that gender inequalities in problem of tranquilisers and opioid analgesics consumption, mental health and drug use are generally very pronounced.37 38 especially among women in key sectors. This reinforces the need Although there are almost no studies on this reality according for further research on the relationship between employment to sector of activity (frontline or non-­ frontline) during the and working conditions and such consumption, to enable us to pandemic, studies in the Spanish context have suggested that propose appropriate preventive measures to reduce the alarming the situation resulting from lockdown had a greater effect on consumption of tranquilisers and opioid analgesics. mental health and increased tranquilisers and opioid analge- sics consumption among women.34 Prior to the pandemic, such What is already known on this subject? consumption had already been reported to be very high among women.38 This study has several limitations. The main one is the data ► Health and economic crises often have differential impacts collection method: an online survey. This method implies, according to gender, and existing gender inequalities can be among other aspects, that we cannot ensure the representative- reinforced. ness of our sample, so selection bias may occur. In a previous ► The few studies that have analysed the impact of the study,8 sensitivity analysis was carried out and showed that, pandemic on working conditions generally note a significant even if present, this bias would not have a relevant effect on the deterioration in working conditions and health indicators, estimates. Another limitation is that, as this is a cross-­sectional especially among certain vulnerable groups of workers. design, we cannot directly compare the results obtained with ► Studies in the Spanish context have suggested that the prepandemic situation among the same workers. However, we situation resulting from lockdown had a greater effect have made comparisons with results from articles analysing on mental health and increased tranquilisers and opioid similar samples of workers before the pandemic. Also, it is a self-­ analgesics consumption among women. reported survey, which may imply some bias. Finally, the concept of ‘essential’ itself, which is used to define the frontline workers. What this study adds? Before the start of the pandemic, the concept of an essential sector or activity was not very common in the specialised scien- ► Employment and working conditions, exposure to tific literature, nor was it understood as a means of categorisa- tion.39 Today, there is also no clear or agreed definition of what psychosocial risks, as well as health status and the an essential job or activity is. This implies that very heteroge- consumption of tranquilisers and opioid analgesics, show neous occupations are grouped under the umbrella of essenti- gender inequalities and inequalities according to whether the ality, which can make interpretation of findings rather difficult. workers were frontline or not). Nevertheless, ‘essential’ refers to those sectors that are neces- ► Overall, frontline women workers endure worse employment sary for the functioning and reproduction of society: sectors that and working conditions, have poorer health and consume are usually undervalued and devalued in the capitalist system.39 more tranquilisers and opioid analgesics than non-­frontline It would be very interesting, in future research, to analyse the women. In contrast, men show the opposite pattern. differences between essential workers according to occupation. ► If we focus on gender inequalities between frontline workers One of the main strengths of the study is the analysis of up-­to-­ and non-­frontline workers, we find that, in both cases, date and highly relevant information on the working conditions women have worse employment and working conditions and health of the working population in Spain at the beginning and are more exposed to high levels of work-­related strain of the pandemic. Moreover, it is based on a large sample, which than men. Moreover, these inequalities are more pronounced allows worker profiles to be representative according to sex, age, among frontline workers. occupational group and territory. Finally, the gender perspec- ► There is an urgent need to improve working conditions tive, both in our analysis and discussion of the results, is one and reduce occupational risk, particularly among frontline of the great strengths of this work, especially when considering workers. the limited inclusion of the gender perspective in occupational ► There is a public health problem posed by tranquilisers and health research. opioid analgesics consumption, especially among frontline Despite the United Nations’ request to consider all workers as women. essential for the existence and functioning of society,40 only those in formal employment whose economic sector was considered Contributors MU and AB conceived the idea of the paper. AN verified and essential, that is, life-­making activities, were classified as such in provided the data. AN and MU were responsible for the analysis of data. AB and Spain at the start of the COVID-­19 pandemic. The exceptional MU were responsible for a first interpretation of data. All authors wrote a first draft situation caused by the pandemic could have offered an opportu- of the paper. All authors read and approved the final manuscript. All authors are guarantors. nity to revalorise all the essential sectors, by means of dignifying their employment and working conditions, especially among Funding The authors have not declared a specific grant for this research from any women. In the face of probable future pandemics, it would be funding agency in the public, commercial or not-­for-­profit sectors. good if this would be really undertaken, so that gender inequali- Competing interests None declared. ties will not be reinforced, and the invisibility and precariousness Patient consent for publication Not applicable. of certain occupations will neither deepen. Ethics approval The study was carried out following current laws and was On the one hand, this study has shown the joint influence that approved by the Ethics Committee of the Universidad Autónoma de Barcelona the sector of activity and gender have on working and employ- (CEEAH-­5158). Participants gave informed consent to participate in the study before ment conditions, as well as on women’s health, which places taking part. 6 Utzet M, et al. J Epidemiol Community Health 2022;0:1–7. doi:10.1136/jech-2021-217692 Original research Provenance and peer review Not commissioned; externally peer reviewed. 17 Mutambudzi M, Niedwiedz C, Macdonald EB, et al. Occupation and risk of severe COVID-­19: prospective cohort study of 120 075 UK Biobank participants. Occup Data availability statement Data are available on reasonable request. Data are Environ Med 2020;78:307–14. available on resonable request. 18 Julià M, Vives A, Tarafa G, et al. Changing the way we understand precarious Supplemental material This content has been supplied by the author(s). It employment and health: Precarisation affects the entire salaried population. Saf Sci has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have 2017;100:66–73. been peer-­reviewed. Any opinions or recommendations discussed are solely those 19 Banyuls J, Recio A. Labour segmentation and precariousness in Spain: theories and of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and evidence. In: Making work more equal, 2017: 129–49. responsibility arising from any reliance placed on the content. Where the content 20 Eurofound. The gender employment gap: challenges and solutions. Luxembourg, includes any translated material, BMJ does not warrant the accuracy and reliability 2016. of the translations (including but not limited to local regulations, clinical guidelines, 21 Menéndez M, Benach J, Muntaner C, et al. Is precarious employment more damaging terminology, drug names and drug dosages), and is not responsible for any error to women’s health than men’s? Soc Sci Med 2007;64:776–81. and/or omissions arising from translation and adaptation or otherwise. 22 Utzet M, Llorens C, Moriña D, et al. Persistent inequality: evolution of psychosocial This article is made freely available for personal use in accordance with BMJ’s exposures at work among the salaried population in Spain between 2005 and 2016. website terms and conditions for the duration of the covid-­19 pandemic or until Int Arch Occup Environ Health 2021;94:621-­629. otherwise determined by BMJ. You may download and print the article for any lawful, 23 Seck PA, Encarnacion JO, Tinonin C, et al. 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