The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: Results from a national survey of Chilean workers.

BACKGROUND: Social epidemiologic research in relation to the health impacts of precarious employment has grown markedly during the past decade. While the multidimensional nature of precarious employment has long been acknowledged theoretically, empirical studies have mostly focused on one-dimensional approach only (based either on employment temporariness or perceived job insecurity). This study compares the use of a multidimensional employment precariousness scale (EPRES) with traditional one-dimensional approaches in relation to distinct health outcomes and across various socio-demographic characteristics.
METHODS: We used a subsample of formal salaried workers (n = 3521) from the first Chilean employment and working conditions survey (2009-2010). Multilevel modified Poisson regressions with fixed effects (individuals nested within regions) and survey weights were conducted to estimate the association between general health, mental health and occupational injuries and distinct precarious employment exposures (temporary employment, perceived job insecurity, and the multidimensional EPRES scale). We assessed the presence of effect measure modification according to sex, age, educational level, and occupational class (manual/non-manual).
RESULTS: Compared to one-dimensional approaches to precarious employment, the multidimensional EPRES scale captured a larger picture of potential health effects and differences across subgroups of workers. Patterns of effect measure that modification were consistent with the expectations that groups in greater disadvantage (women, older individuals, less educated and manual workers) were more vulnerable to poor employment conditions.
CONCLUSIONS: Multidimensional measures of precarious employment better capture its association with a breath of health outcomes, being necessary tools for research in order to strengthen the evidence base for policy making in the protection of workers' health.

Introduction

The flexibilization of employment relationships of the past decades has led to the growth of precarious employment [1]. Important numbers of workers are affected by this precarisation of employment, motivating the study of its potential effects on the health and wellbeing of workers and their families. Such research has grown markedly during the past decades, but while scholars from different disciplines have long acknowledged that there are several dimensions to precarious employment, the main approaches to produce epidemiologic evidence have been largely one-dimensional, focusing primarily on job instability. In this context, the development of clearer, more comprehensive definitions of the concept of precarious employment and its operationalization are among the main research gaps that have been identified in the advancement of the precarious employment and health research agenda [2]. This paper aims at highlighting the importance of using a multidimensional theory-based employment precariousness scale in comparison with traditional one-dimensional empirical approaches, not only to improve or understanding of the problem but also to enhance the contribution that epidemiologic evidence can make to inform policy making towards the improvement and protection of workers’ health.

The two main one-dimensional approaches, which have contributed significantly to the available epidemiological evidence in the last decades, can be grouped into perceived job insecurity studies and temporary employment studies. Perceived job insecurity is the subjectively perceived likelihood of involuntary job loss [3], generally measured as the overall concern regarding the continuity of the job in the future [4]. Research on job insecurity shows there to be effects upon several health outcomes, the most studied of which are its effects on mental health [5]. However, perceptions of job insecurity may be elicited by different contextual determinants, including events in the private life of individuals, such as the appearance of health problems. Also, the magnitude of job insecurity in the face of external threats to the continuity of the job may vary considerably between individuals due to personal attributes. It is thus a largely “private” experience, more closely linked to individual psychology than to the actual employment relationship [6], but provides only a partial picture of precarious employment and how it may affect health [7]. The second one-dimensional approach, developed partly in response to the limitations of job insecurity studies, addresses the health effects of different types of ‘temporary employment’ jobs by comparing them to permanent jobs, which often are considered the “ideal” standard of employment, secure and non-precarious [8]. Temporary workers have been found to be exposed to worse working conditions and harmful exposures, and to be consistently associated with worse mental health and more workplace injuries [9]. Despite this, studies have produced contradictory findings, whereby some have found an inverse association between type of contract and health, or no association at all [10]. This may be partly explained because not all temporary jobs are necessarily precarious, but mainly because the increased utilization of temporary employment has expanded this precarisation to all contract types, such that many permanent jobs are also, to some extent, precarious. This implies that the one-dimensional temporary employment approach may produce exposure misclassification and ultimately underestimate the impact of precarious employment on health.

The limitations of one dimensional approaches to precarious employment have motivated the advancement of instruments that can account for its multidimensional nature. Several proposals for a multidimensional conceptualization of employment precariousness have emerged, but they have seldom been operationalized to use in epidemiologic research. One exception is the Employment Precariousness Scale (EPRES) developed by the GREDS-EMCONET research group drawing on Rodger’s multidimensional definition [11]. The EPRES encompasses not only the uncertainty of continuing employment; but also other key aspects of employment relationships, organized into six dimensions: ‘temporariness’ or employment instability; ‘disempowerment’ (individualized vs collective bargaining); ‘vulnerability’ (worker defenselessness to unacceptable workplace practices); ‘wages’ (low or insufficient; possible material deprivation); ‘rights’ (entitlement to social security benefits); and ‘exercise rights’ (powerlessness, in practice, to exercise workplace rights) [11, 12]. Recent research has described associations between the EPRES score and mental and general health [13, 14], as have studies using proxy multidimensional measures with European data from the European Working Conditions Surveys.

Nonetheless, to our knowledge no epidemiological effort has compared yet the health impacts of multidimensional and one-dimensional approaches to precarious employment in order to assess to which extent they differ in their association with health. It is also important to conduct such comparison across different outcomes that include mental health, physical health and occupational health to detect the potential different mechanisms involved.

In parallel, while most studies describing employment conditions tend to coincide in finding that groups in labour market disadvantage are more frequently in precarious employment, few studies have compared its health effects across sub-groups of workers, except for some studies stratifying by gender and, in few cases, occupation [15]. Assessing heterogeneity in the impact of one-and multi-dimensional measures is particularly important to identify vulnerable subgroups, so as to shape targeted interventions.

In Latin America epidemiological research on formal precarious employment and health is scant, in part due to the greater attention informal employment convenes given its pervasive presence in the region´s labour markets. In Chile, while informal employment still occupies a significant portion of the labour force, the majority of jobs are formal salaried jobs, but affected by significant instability [16]. The full version of the EPRES was included in the first Chilean employment and working conditions survey (ENETS), together with the main one-dimensional measures of precarious employment [17]. This provides a unique opportunity for comparing measures of precarious employment across different health outcomes. Initial descriptive analyses showed a high proportion of workers perceiving their jobs as insecure and suggest there to be a higher prevalence of poor health among workers in more insecure or precarious jobs [18].

Hence, using data from the first Chilean employment and working conditions survey (ENETS), which offers high quality data on employment and worker health, this study compares the association of one-dimensional measures (temporary employment, perceived job insecurity) and the multidimensional EPRES scale with general self-perceived health and mental health, the most studied outcomes of precarious employment, as well as self-reported occupational injuries, an objective occupational health outcome.

As a secondary objective, this study aims to identify heterogeneity across sub-groups to identify those especially vulnerable to poor employment conditions in one or another measure, by examining whether the observed associations are modified by four of the main axes of labour market inequality: gender, age, educational attainment and occupation (manual or non-manual).

Materials and methods

This study has been approved by Pontificia Universidad Católica´s School of Medicine Institutional Review Board (IRB), approval number 12–128. Consent was not required since secondary data were used and analyzed anonymously.

Data

The study sample comes from the first Chilean survey on Employment conditions, Work, Health and Quality of life (ENETS) conducted in 2009–2010, and is representative of the national workforce at national, regional and urban and rural levels [17]. Sample selection followed a multistage, stratified random sampling procedure, with an overall response rate was 73.9%. Interviews were conducted in the participant’s household by trained interviewers; participation was voluntary and confidential. Completely anonymized data sets are directly available from the Ministry of health’s webpage.

Because the EPRES is specifically devised for formally employed workers, the study sample will be restricted to workers in salaried employment with a formal work contract (n = 3521), thus making proper use of the scale and results comparable internationally.

Study variables

Health outcomes

Self-reported general health was assessed by the single item “In general would you say your health is…” with a dichotomous outcome variable (1: fair, less than fair, bad, very bad; 0: more than fair, good, very good).

Mental health was measured with the 12-item version of the General Health Questionnaire (GHQ-12) for non-specific psychiatric morbidity. The GHQ Likert scoring method was used to assess the magnitude of psychological distress [19], classifying subjects into poor mental health if they belong to the 4th quartile of the distribution.

Occupational injuries (yes/no) were all self-reported non-fatal workplace injuries in the 12 months prior to interview [20].

Precarious employment variables

Exposure was measured with two one-dimensional and one multidimensional approach: i) perceived job insecurity, measured as the concern about being fired or not having the contract renewed (Never and rarely = not insecure; almost always and always = insecure), ii) temporary employment, including both fixed-term and non-fixed term temporary contracts, compared to permanent jobs, and iii) the Employment precariousness scale (EPRES-Ch) for the multidimensional assessment, which encompasses 6 dimensions: ‘temporariness’ (3 items), ‘disempowerment’ (3 items), ‘vulnerability’ (5 items), ‘wages’ (3 items), ‘rights’ (3 items), and ‘capacity to exercise rights’ (5 items). EPRES subscale scores are computed as a simple average transformed into a 0–4 scale and then averaged into a global EPRES score which ranges from 0 (not precarious) to 4 (most precarious), and which we divided into tertiles.

Sociodemographic and occupational variables

The variables used were sex, age (as a continuous variable), educational attainment (primary or less, secondary, trade school, and university), urban or rural residency, occupational class based on the International Standard Classification of Occupations (ISCO-88) and grouped into manual and non-manual, economic activity (International Standard Industrial Classification of all Economic Activities (ISIC-Rev.2, 1968). Region of residency (15 Chilean regions) was included in the multilevel models.

Statistical analyses

Multilevel Poisson (modified with robust variance for binary outcomes) regressions with fixed effects, where each individual was nested in his region, were conducted to estimate adjusted prevalence ratios (PR) [21] representing the association between the health outcomes (n = 3) of interest and the exposure to each employment conditions (n = 4). A likelihood ratio test was used to consider the presence of within-region variability for each model. Covariates and causal pathways were defined a priori based on the literature. Analyses were thus adjusted for gender, age, and occupational class. We created tertiles for employment precariousness as an exposure of interest to investigate potential non-linear patterns. We considered the complex survey design by including the survey weights provided by ENETS in our analysis [17]. We performed complete case analysis for all our analyses.

We conducted sensitivity analyses by excluding from the models i) individuals aged more than 65 years; ii) individuals with limiting illness in the 12 months preceding the survey and ii) individuals working in the public sector.

As a secondary analysis, we assessed if the association between each of the health outcomes of interest (n = 3) and each of the precarious employment exposures (n = 3) was heterogeneous according the following variables: sex (men vs. women); age (considered as continuous variable, 1-year units); level of education (lowest vs. highest); occupational class (non-manual vs. manual). We assessed the presence of heterogeneity through the inclusion of an interaction product term in the Poisson models described above. We therefore obtained, for each model, the interaction term coefficient and its 95% confidence Interval (95% CI) to assess potential heterogeneity. When level of education was considered in the interaction term, occupational class was excluded from the models. All analyses were performed with Stata 14 SE.

Results

The majority of the sample are men (66%), aged 25 to 44 years (51.9%), has secondary education (58.7%), urban residence (86.1%), are non-qualified workers (62.7%; 31.5% non-manual and 31.2% manual); 32.6% work in communal services and 19% in commerce (wholesale). Up to 16.5% has temporary employment and 30.5% reports job insecurity. Employment precariousness scores ranged from 0 to 3.51, (median = 1.28). The prevalence of poor general health was 21.3%, poor mental health (third tertile) concentrated 361%, and 6.3% of workers reported having suffered at least one occupational injury in the preceding 12 months. (Table 1)

Table 1

Sample characteristics.

Variable		%
Sex	Men	64.1
	Women	35.9
Age groups (years)	15–24	12.9
	25–44	49.1
	45–64	35.7
	65+	2.3
Educational attainment	Basic	18.3
	Secondary	61.6
	Trade school	10.3
	University	9.8
Zone	Urban	89.1
Occupation	Qualified non-manual	20.9
	Non-qualified non-manual	31.5
	Qualified manual	16.3
	Non-qualified manual	31.2
Economic activity	Agriculture, hunting and forestry	12.0
(ISIC Rev.4)	Mining and quarrying	3.8
	Manufacturing	13.0
	Electricity, gas and water supply	1.3
	Construction	8.9
	Wholesale, hotels & restaurants	19.0
	Transport, storage and communication	6.4
	Real estate, renting and business activities	2.2
	Other social community services	32.6
Type of contract	Temporary	16.5
Job insecurity	Yes	30.5
Employment Precariousness (EPRES)	T1	34.0
	T2	29.9
	T3	36.1
Poor mental health	Yes	16.6
Poor self-reported health	Yes	21.3
Occupational injuries	Yes	6.3

Salaried formal workers, Chile 2009–10. (n = 3.521).

We found that poor general health was associated with employment precariousness in the form of a gradient, and with job insecurity, but not with temporary employment. Poor mental health was associated with the third tertile of employment precariousness and with job insecurity, but not with temporary employment. (Table 2)

Table 2

Prevalence rate ratios for the associations between study exposures and outcomes.

		Poor General Health			Poor Mental Health			Occupational Injuries
		PRR	LCI	UCI	PRR	LCI	UCI	PRR	LCI	UCI
Employment precariousness	T1*
	T2	1.59	1.14	2.22	1.23	0.72	2.11	2.21	1.17	4.17
	T3	3.07	2.20	4.29	2.38	1.43	3.96	2.48	1.42	4.33
Job Insecurity	Not insecure*
	Insecure	1.49	1.14	1.94	1.92	1.42	2.60	1.52	0.88	2.62
Type of Contract	Permanent*
	Temporary	0.99	0.74	1.33	1.23	0.86	1.76	0.99	0.56	1.76

Chile, salaried workers 2009–10.

PR: Prevalence ratios; LCI: Lower confidence interval; UCI: upper confidence interval.

* Reference group.

Occupational injuries were not associated with neither job insecurity nor temporary employment. Instead, a gradient association was observed with employment precariousness, reaching 2.48 (95%C.I.: 1.42–4.33) among workers in the third tertile.

Results for the heterogeneity assessments showed that women were more vulnerable than men in the association between employment precariousness and general and mental health, while men were more vulnerable than women in the association between job insecurity and type of contract with mental health.

For age, we found effect modification for all associations with general and mental health indicating that the eldest were more vulnerable. For education results only indicated a lower risk for those in higher education in the association with occupational injuries and type of contract. Finally, we found non-manual workers to be less vulnerable than manual workers in most associations (see S1 Table)

After conducting sensitivity analysis, our conclusions were not affected.

Discussion

To our knowledge, this is the first study to analyze and compare the health-related associations of the two main one-dimensional measures of precarious employment to a multidimensional measure of precarious employment. We show that different precarious employment exposures may lead to different conclusions in terms of health associations. Our main findings are that while employment precariousness and job insecurity were associated with all three health outcomes considered in this study, while temporary employment was associated with none, and that the multidimensional approach was the most sensible to both the association with health and to subgroup heterogeneity.

Against expectations, we found no associations between temporary employment and the three health outcomes studied. This finding adds to the body of contradictory or heterogeneous research findings. However, contrary to the hypothesis that this may be due to the heterogeneity of temporary employment jobs, in Chile it is more likely that the explanation lies in the fact that many permanent jobs are precarious. Based on data from this same survey, we have shown that the sensibility of temporary employment as indicator of precarious employment is low [22]. The implication is that temporary employment, as indicator of precarious employment, introduces non-differential exposure misclassification, producing an underestimation of the associations between precarious employment and health. This should be especially so in countries and contexts where most forms of employment tend to be precarious to some extent, as is the case of Chile. This does not preclude, however, the existence of associations between temporary employment and other health outcomes not included in this study, or for these same health outcomes in other contexts where the gap between temporary and permanent employment is greater [9].

Consistent with the literature, job insecurity exhibited a strong association with poor mental health, and, somewhat weaker, with poor general health. It did not, however, appear associated with occupational injuries, despite the expectations are that job insecurity affects the occupational health and safety of workers through different mechanisms such as over-exertion and performance pressures in order to preserve the job when it is perceived as insecure [23].

The strongest and most consistent pattern of associations with all three outcome variables were observed for multidimensional employment precariousness. This is consistent with our hypothesis that this is a more sensible measure and with greater explicative power than either job insecurity or temporary employment. Particularly interesting is the result of a strong, graded association between the EPRES and occupational injuries, association that was not observed for any of the other exposure variables. This is the first evidence of an association between the EPRES and occupational injuries, comparable to previous research on temporary employment [24-26], and consistent with the GREDS-EMCONET conceptual model on employment conditions and health, providing evidence to the proposal that precarious workers face worse working conditions and poorer occupational health and safety protection [27]. Also, given these results, self-self bias seems less likely given the higher objectivity of reporting occupational injuries as compared to general and mental health.

Results were also generally consistent with the expectation that groups in greater disadvantage are more vulnerable to poor employment conditions, possibly given cumulative vulnerability or the combination of several adverse exposures simultaneously or along the life course. We identified patterns of effect measure modification by sex, where employment precariousness appears to affect women’s mental and general health more, which is consistent with previous studies [13, 14], and where job insecurity and temporary employment appear to affect men’s mental health more than women’s, suggesting that job instability is especially crucial for them and that other dimensions of employment precariousness may be more relevant to women (e.g., vulnerability or defencelessness, incapacity to exercise rights).

With one exception, all observed associations were modified by age, indicating a greater risk as workers’ age increases, consistent with studies showing older workers are more likely to experience adverse effects in the face of insecure or precarious employment [24]. Heterogeneity by occupational class showed a clear pattern of lower vulnerability for those in non-manual occupations, especially concerning general health, the latter possibly due to a greater physical workload and a lower investment in manual workers’ occupational health and safety, resulting in a greater wearing-off of their health. It is noteworthy that the employment precariousness scale better captured these group differences, with a larger number of associations exhibiting heterogeneity for this exposure than for the others.

This study is not without limitations. To begin with, it is cross-sectional in nature, and thus, exposed to possible issues of reverse causality or selection bias. Yet our results remained unchanged after excluding individuals reporting a limiting illness in the 12 months preceding the survey.

Another limitation is the exclusion of the most vulnerable workers in the Chilean labour force, given its focus on salaried workers with a formal job contract. If currently unemployed workers, own-account workers, or informal workers were included in such a study, we might expect even larger associations. However, including them requires adapted versions of the EPRES questionnaire that need yet to be developed. Future research should consider these knowledge gaps, as well as expanding the study to other health outcomes, e.g. occupational illnesses, and in other time periods, to explore what the effects of economic crises may be on the observed associations.

Conclusions

In summary, our study shows that precarious employment conditions are harmful for health, but that different approaches to the measurement of precarious employment produce different results. According to the results presented here, the multidimensional employment precariousness scale is more sensible to the potential health effects of precarious employment than one-dimensional methods that only address employment instability, and is also more sensible to differences across groups of workers in their vulnerability to precariousness of employment. Another advantage of using a theory-based multidimensional measure is that it allows for the study of the health related effects along a gradient of precariousness irrespective of contract type. These results highlight the value of a multidimensional tool, for research as well as monitoring, in order to strengthen the evidence base for policy making to the benefit of workers’ health.

Interaction terms (95% C.I.) for the associations between study exposures and outcomes by sex, age, education and occupation.

(DOCX)

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15 Jun 2020

PONE-D-20-09255

The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: Results from a national survey of Chilean workers

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Reviewer #1: Dear authors,

The manuscript develops and important, and still neglected, determinant of health. In the case of Chile and other similar countries, relationship among work and health is still full of stigma and a lack of comprehensive polices to undermine the negative effects of (Precarious) work in population health.

My suggestions are focused in the introduction, methods, and discussions. In the case of introduction section, there are no references supporting Chile´s relationship between precarious work and health. In the same way, current (/Or not) policies related to the problem. Thus, in methods is necessary to support why Chile -and not another country with similar problems- was selected for using a multi-dimensional scale for precarious work and health. If the main reason for choosing Chile was data, it must by explicitly declared in this section. Finally, discussion needs to avoid repeating results and discuss with findings. I am aware multi-dimensional scale for measure precarious work and health cannot be available in similar context.

Reviewer #2: The paper titled “The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: Results from a national survey of Chilean worker” measures precarious employment by using one- and multi-dimensional indicators and assessing their relationship with several health outcomes. The paper seeks to contribute to the literature on precarious employment which, as they argue, has not really developed a clear and comprehensive operationalization of the concept.

The paper presents original research with results that, to my knowledge, have not been published elsewhere. However, there are certain issues with the paper that I think could be improved to make this paper a stronger contribution.

First of all, it is not fully clear the method the authors use. They state they use “multilevel modified poisson” models, where individuals are nested within regions. However, to my understanding, the data the authors are using is not representative at the regional level, therefore, the variances estimated at the regional level by a hierarchical model would not be valid. In that sense, I think it would be better to use a standard poisson model using clustered standard errors to adjust for the autocorrelation that might exist.

Regarding the measurement of their variables, it should be made clear that classifying individuals in the 4th quartile of the GHQ distribution as individuals with poor mental health is the standard in the literature. To what extent is that correlated with, for example, clinical depression. I imagine that adding sources that justify the way this is measure will not be hard and it will give the reader a higher sense of robustness in terms of measurement.

When it comes to the presentation of results, the use of tertiles for the employment precariousness variable is confusing. It is not mentioned before, until one reaches the table, that the variables is going to be used in tertiles rather than as a continuous variable. Why is the variable categorized? Is there a theoretical or methodoligcal justification? That should be made clear. Also, the analysis of “heterogeneity across sub groups” of the associations between precarious employment and health seems undone. At the very end of the results section that extra paragraph seems a little like added last minute and it is very briefly really discussed afterwards. In other words, it looks like a secondary objective that is not really adding to the paper. For me, the primary results are more than enough to make this a valuable contribution.

Finally, I cannot finish without commenting the results on temporary employment. Chile has two particular features that I think are very important to be discussed in the paper so that the results are actually valid. First, a very significant proportion of the labor force, as in the rest of Latin America, is in the informal sector. Because they have been left out of the analysis, these analyses are not really showing the whole pctire of precariousness. And don’t get me wrong, I think the analyses are not less valid because of this, but this should be made clear given the context in which the workers being analyzed live. It is very different to be a precarious worker in your sample---who is relatively more stable than a significant proportion of the labor force in their country---than a precarious worker in a country where most of the labor force are formally employed. And second, regarding the little effect of temporary jobs, it is important to mention that the Chilean law regulates temporarily employment, and in many cases, workers who are under a temporary contract are expected to move to long-term contracts in a relatively short period of time. Of course, this is not all workers, but it’s a significant part of them (maybe you can explore this with your data). But it could be that this fact is in part explaining part of that null finding.

Overall, I think this is a good paper, that makes a valuable contribution, and that needs to adjust some things in its methodology and presentation of results to make it an even stronger one. The article is presented in an intelligible fashion and is written in standard English, and there are no ethical concerns about the data being used. The article adheres to appropriate reporting guidelines and community standards for data availability.

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13 Aug 2020

Dear editor,

Please find below the reviewer comments, followed by our responses.

Editor

We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing requirements. PLOS does not permit references to inaccessible data. We require that authors provide all relevant data within the paper, Supporting Information files, or in an acceptable, public repository. Please add a citation to support this phrase or upload the data that corresponds with these findings to a stable repository (such as Figshare or Dryad) and provide and URLs, DOIs, or accession numbers that may be used to access these data. Or, if the data are not a core part of the research being presented in your study, we ask that you remove the phrase that refers to these data.

We have excluded the phrase in line 265 and added the corresponding reference instead. It is a recently accepted manuscript in Annals of Work Exposures and Health. We have entirely excluded the second phrase relative to this ( lines 296-300 of the manuscript with track changes) since those dara were not a core part of the research being presented here.

Reviewer #1

The manuscript develops and important, and still neglected, determinant of health. In the case of Chile and other similar countries, relationship among work and health is still full of stigma and a lack of comprehensive polices to undermine the negative effects of (Precarious) work in population health.

We thank reviewer 1 for his positive appreciation of our manuscript.

My suggestions are focused in the introduction, methods, and discussions.

1. In the case of introduction section, there are no references supporting Chile´s relationship between precarious work and health. In the same way, current (/Or not) policies related to the problem.

We thank the reviewer for this observation. There is scant epidemiological literature supporting this association in Latin America in general, and in Chile in particular. We have made reference to this in the introduction section and provided reference to descriptions of both the labor market and policy at the time the data were collected. Also, to the preliminary descriptive results of the survey. Because the primary focus of this study is the comparison between indicators of employment precariousness, we do not extend ourselves more in that regard.

2. Thus, in methods is necessary to support why Chile -and not another country with similar problems- was selected for using a multi-dimensional scale for precarious work and health. If the main reason for choosing Chile was data, it must by explicitly declared in this section.

We agree with the reviewer and have added a statement in the introduction regarding both the pertinence of the analyses in the Chilean context, and the availability of data that justify the employment of the ENETS survey.

3. Finally, discussion needs to avoid repeating results and discuss with findings. I am aware multi-dimensional scale for measure precarious work and health cannot be available in similar context.

We truly thank the reviewer for this observation. In fact, there are scant experiences with multi-dimensional scales for measuring precarious employment in the literature and more so regarding epidemiological research. To our knowledge, there is currently some research going on in central America, using an incomplete version of the EPRES questionnaire, but results have not been published. We have gone through the discussion to make it less repetitive and more synthetic and truly believe it has improved.

Reviewer #2

The paper titled “The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: Results from a national survey of Chilean worker” measures precarious employment by using one- and multi-dimensional indicators and assessing their relationship with several health outcomes. The paper seeks to contribute to the literature on precarious employment which, as they argue, has not really developed a clear and comprehensive operationalization of the concept. The paper presents original research with results that, to my knowledge, have not been published elsewhere.

However, there are certain issues with the paper that I think could be improved to make this paper a stronger contribution.

1. First of all, it is not fully clear the method the authors use. They state they use “multilevel modified poisson” models, where individuals are nested within regions. However, to my understanding, the data the authors are using is not representative at the regional level, therefore, the variances estimated at the regional level by a hierarchical model would not be valid. In that sense, I think it would be better to use a standard poisson model using clustered standard errors to adjust for the autocorrelation that might exist.

Thanks for this comment. We would like to clarify that the data are representative at the regional level. We clarified this in the methods section We actually considered both the hierarchical structure of the data (by using fixed effects at the regional level with clustered standard errors) and also included the survey weights. We used modified Poisson models as our outcomes are binary following the approach proposed by Barros et al. [See ref 18: https://doi.org/10.1186/1471-2288-3-21]. Therefore, our data consider any time-fixed confounding at the regional level and potential autocorrelation within regions and our estimates are representative of the target working Chilean population. We clarified this in the abstract and the methods section.

2. Regarding the measurement of their variables, it should be made clear that classifying individuals in the 4th quartile of the GHQ distribution as individuals with poor mental health is the standard in the literature. To what extent is that correlated with, for example, clinical depression. I imagine that adding sources that justify the way this is measure will not be hard and it will give the reader a higher sense of robustness in terms of measurement.

We thank the reviewer for this suggestion. In fact, the GHQ can be scored in different manners, this being the dimensional approach, which uses a Likert scoring method, and is frequently used in epidemiological research to assess intensity of psychological distress at the population level. It does not aim at a clinical diagnosis of depression nor as a clinical screening tool, for which the GHQ scoring approach is best recommended. With this method, a score is obtained which is a continuous variable, where higher scores indicate higher psychological distress. We have included a reference to support this utilization. Further, we changed “dimensional” for “Likert” in the manuscript to be in consistence with the reference. Here we dichotomize the GHQ score. This is a frequently used strategy, and the choice here, in order to produce a dichotomous variable for the proposed analytical strategy.

3. When it comes to the presentation of results, the use of tertiles for the employment precariousness variable is confusing. It is not mentioned before, until one reaches the table, that the variables is going to be used in tertiles rather than as a continuous variable. Why is the variable categorized? Is there a theoretical or methodoligcal justification? That should be made clear.

We thank the reviewer for this observation. The employment precariousness scale is scored as a continuous variable and has been most frequently been used in quantiles in order to show non-linear associations with the outcome. In this study, we a priori used tertiles for employment precariousness to investigate potential non-linear patterns while keeping enough observations in each group. We agree this information should be clarified further in the text, so included a statement about this in the methods section (lines 197-199).

4. Also, the analysis of “heterogeneity across sub groups” of the associations between precarious employment and health seems undone. At the very end of the results section that extra paragraph seems a little like added last minute and it is very briefly really discussed afterwards. In other words, it looks like a secondary objective that is not really adding to the paper. For me, the primary results are more than enough to make this a valuable contribution.

We totally agree with the reviewer. Indeed, this effect measure analyses do not constitute a primary aim but rather an exploratory/secondary aim and we should have clarified this. In the revised version, we clarified that such analysis constitutes a secondary aim and we moved the results table to the appendix section. Consistent with this, we also reduced the length of the corresponding paragraph in the results and discussion sections.

5. Finally, I cannot finish without commenting the results on temporary employment. Chile has two particular features that I think are very important to be discussed in the paper so that the results are actually valid. First, a very significant proportion of the labor force, as in the rest of Latin America, is in the informal sector. Because they have been left out of the analysis, these analyses are not really showing the whole picture of precariousness. And don’t get me wrong, I think the analyses are not less valid because of this, but this should be made clear given the context in which the workers being analyzed live. It is very different to be a precarious worker in your sample---who is relatively more stable than a significant proportion of the labor force in their country---than a precarious worker in a country where most of the labor force are formally employed.

We entirely agree with the reviewer. In the limitations section of the discussion we refer to this exclusion of the most vulnerable workers, that is, informal workers. As we indicate there, their inclusion requires an adaptation of the employment precariousness scale, and also a different conceptualization if we were to include self-employed workers, an important part of our informal labor force. We aim here to reinforce the notion that multidimensional measures of employment precariousness are needed to adequately assess its impact on health, and to discuss with the literature concerning the limitations of other approaches. However, we do agree with the reviewer that this is a critically important topic, and which requires careful formulation of concepts and measurement instruments to address these groups. We hope the reviewer will find our discussion of these limitations in the paper satisfactory.

6. And second, regarding the little effect of temporary jobs, it is important to mention that the Chilean law regulates temporarily employment, and in many cases, workers who are under a temporary contract are expected to move to long-term contracts in a relatively short period of time. Of course, this is not all workers, but it’s a significant part of them (maybe you can explore this with your data). But it could be that this fact is in part explaining part of that null finding.

We thank the reviewer for this observation. This is an interesting hypothesis, although we cannot directly explore in the data. We have, however, analyzed the extent of precariousness of temporary workers in another paper (now cited in the manuscript) and have found that they are indeed almost all in precarious job situations and are more intensely precarious than jobs with permanent contracts. The issue is, however, that many precarious jobs are permanent jobs, so the use of this indicator relying on type of contract produces misclassification error and thus underestimates the associations. We have indicated this more clearly in lines 263-268.

Overall, I think this is a good paper, that makes a valuable contribution, and that needs to adjust some things in its methodology and presentation of results to make it an even stronger one. The article is presented in an intelligible fashion and is written in standard English, and there are no ethical concerns about the data being used. The article adheres to appropriate reporting guidelines and community standards for data availability.

We thank the reviewer for this positive evaluation of our manuscript.

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17 Aug 2020

The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: Results from a national survey of Chilean workers

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15 Sep 2020

PONE-D-20-09255R1

The importance of using a multi-dimensional scale to capture the various impacts of precarious employment on health: Results from a national survey of Chilean workers

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