men and women’s health: the cumulative advantages and ... · and sex (lanoé and...

Anne-Sophie COUSTEAUX CREST – Laboratoire de sociologie quantitative Timbre J 350 3 avenue Pierre Larousse 92245 Malakoff cedex France + 00.33.1.41.17.57.35 (phone)

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Summer RC28 meeting, MontrealPanel 3/1 “Work and health”

Men and Women’s Health: the Cumulative Advantages and Disadvantages of Social Position, Employment Status and Family Structure in Contemporary France

Please do not cite or quote without the author’s permission. Comments welcome.

ABSTRACT

Fitting in with gender comparative research developed since the 1990s, this paper intends to assess whether the

smaller social inequalities in health among women could be questioned by the varying occupational, work and

family positions of men and women. Using self-assessed health, longstanding illness and activity restrictions as

outcomes, social position is not only measured through occupational features but also integrates employment

status and family role. Does women’s disadvantaged position at home and on the labour market, which is

accentuated by the cumulative nature of disadvantages, increase social inequalities in health among women,

compared to men? The data come from the French Health Survey of 2002. What emerges from the results is that,

the smaller social gradient in self-perceived health among women is challenged by the two other health

measures. But considering full-time workers, social gradients are similar for both genders. Actually, gender

patterns are much more differentiated according to employment status and family structure because of gender-

specific situations such as part-time workers, housewives and single mothers. Besides, female part-time workers

form a heterogeneous population since women voluntarily working part time are as healthy as women working

full time, whereas women in imposed part-time work report significantly poorer health. Furthermore the smaller

social extent in social class inequalities among women comes particularly from the aggregation of working and

non-working women. The last occupation of women outside labour market does not affect the perception of their

health. These findings question the measure of social inequalities in health based on occupation only, and

advocate for taking into account the combination of social position, employment status and family structure for a

better appraisal of gender differences.

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INTRODUCTION

Questioning smaller social inequalities of health among women

In the 1990s, first descriptive studies of gender differences in social inequalities of morbidity

and of mortality highlighted the smaller gradient among women than among men (Arber,

1997; Koskinen and Martelin, 1994; Matthews, Manor and Matthews, 1999). French results

on mortality revealed the same pattern (Blondel and Reid, 1996; Desplanques, 1993; Mesrine,

1999; Monteil and Robert-Bobée, 2005; Robert-Bobée and Monteil, 2006; Leclerc, Chastang,

Menvielle and Luce, 2006). All these studies considered individual social class as an indicator

of men and women’s social position. But, as housewives remain a widespread situation and as

a half of active women belong to the “white collar workers”, it seems obvious that the

individual categorization is problematic to accurately appraise social disparities among

women. Actually, if social inequalities of health appear larger among men than among

women when using individual social class, this result is challenged by using other indicators.

Indeed this gender difference tend to be reduced when considering women’s level of

education (Desplanques, 1991; Arber, 1997; Cavelaars, Kunst, Geurts, et al., 1998; Lahelma

et al., 2004; Robert-Bobée and Monteil, 2006) or their husband’s social class (Arber, 1991;

Dahl, 1991; Mesrine, 1999; Robert-Bobée and Monteil, 2006). Fitting in with gender

comparative research developed since the 1990s, this paper intends to assess whether the

smaller social inequalities in health among women could be questioned by the varying

occupational, work and family positions of men and women.

In France, little research has concerned the gender differences in social inequalities of health

(Leclerc, Fassin, Grandjean et al., 2000; Khlat, Sermet and Le Pape, 2000). If separate

analyses by gender appear now essential in mortality studies because of the large gender gap

in life expectancy, French results on morbidity are still presented with an adjustment on age

and sex (Lanoé and Makdessi-Raynaud, 2005) which makes the implicit hypothesis that

social gradients are equivalent for both men and women. This standpoint may confirm that

researchers rarely wonder if socioeconomic differences in health vary by gender (Hunt and

Macintyre, 2000).

If the extent of the female social gradient varies according to the measure of their social

position, it could be an artefact due to the privileged way in studying social inequalities in

morbidity and mortality. Actually, different hypotheses could explain the female smaller

gradient obtained with individual social class. First, if the analyses of gender differences in

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social inequalities of health only focus on the socio-economic dimensions, it seems obvious

that this framework turns out to be more appropriate for men than for women. Consequently,

it is worth adopting a gender comparative approach. Second, the smaller gradient among

women could be the result of the well-known difficulty in measuring their social position. It

is all the more difficult since social classifications are used to describe more precisely male

jobs. Third, the global comparison of men and women corresponds in fact to a comparison of

different employment status and labour market attachments. That is why we have to take into

account female specificities on labour market and compare as far as possible “like with like.”

The main research questions are: How do theoretically defined aspects of social position,

employment status and family structure affect men and women’s health? Does women’s

disadvantaged position at home and on the labour market, which is accentuated by the

cumulative nature of disadvantages, increase social inequalities in health among women,

compared to men?

From male social framework and female role framework to gender comparative research

First studies of morbidity or mortality were based on male population. In the 1970s with the

development of female wage-earning work and feminist theories, it seemed no longer

acceptable to leave women aside. Because the men model focusing only on paid work

appeared inappropriate in order to analyse women’s health, researchers developed specific

models for women in the 1980s. Integrating paid work and domestic work, the main research

question focused on whether multiple role occupancy (as a worker, a spouse and a mother)

could have beneficial or detrimental effects on women’s health. This question led to two

competing models. According to the role enhancement model, women experiencing multiple

roles should be in better health than women occupying only one. Conversely, as multiple role

occupancy increases stress, demands and role conflicts, the role strain model stresses on the

harmful effects of these multiple roles on women’s health. Even if some evidence could also

have been found in support of the second hypothesis, it is now widely accepted that

combining paid work, marriage and motherhood has more beneficial effects on women’s

health than detrimental (for a research synthesis, see Klumb and Lampert 2004).

Since the 1990s, researchers have tended to highlight the necessity of going beyond separate

analyses with a social class framework for men and a role framework for women (Lahelma et

al. 2002). Studying gender inequalities in health requires gender comparative research, i.e. a

systematic study of similarities and differences between men and women (Annandale and

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Hunt 2000). Even if family role and domestic work are above all more important factors for

women’s health than for men’s one, a similar attention must be paid to employment and

family (and their combination) for both men and women (Arber 1991, Hunt and Annandale

1993). In other words, “it is essential to examine how socio-economic circumstances, together

with marital and parental roles, influence inequalities in health, and to assess whether the

nature of these inequalities in health are gendered” (Arber and Cooper 2000, p. 133). As

advocated by Arber (1991), researchers in the last decade of the 20th century analysed family

role within a structural framework in a similar way for men and women (Bartley et al., 1992;

Macran et al., 1994, 1996; Arber, 1997; Arber and Cooper, 2000; Sekine, Chandola, Marmot

et al., 2006). But gender comparative research raises the problems of measuring social

position and of defining similar circumstances in a gendered society.

Measuring men and women’s social position

The first problem to compare socioeconomic inequalities between men and women is how the

social position of women is best measured (Bartley 2004). By the way, the tradition of

separate analyses for men and women in health research can be partly explained by the

difficulty of classifying women (Vagero 2000). It refers particularly to the sociological debate

on “conventional” and “individual” approaches initiated by John Goldthorpe (for a review,

see Sorensen 1994)1. In the conventional approach, the social position of the family, which is

considered as the unit of social stratification, is defined by men’s occupation, i.e.

independently of women’s one. Because of their weaker attachment to labour market,

women’s life chances would be more dependent on the social position of their husband than

on their own. And in practice, the conventional approach has the advantage of ascribing a

social position to housewives. But in fact this hypothesis comes down to considering that a

housewife married to a senior manager occupy the same social position since the husband’s

position is the reference one. Conversely and by definition, individual is at the centre of the

individual approach, and his social position corresponds to his own current or last occupation.

In health studies, the two approaches have been used to define women’s social position.

However in a gender comparative perspective, it would be questionable to define social

position in different ways according to gender, i.e. to use the individual social position for

men and single women and the partner’s social position for married women (Arber 1997).

1 Robert Erikson proposed a third approach based on the dominance principle (Erikson 1984). This method shows greater social gradient in mortality for both men and women (Erikson 2006).

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That is why, in our study, we have adopted the individualistic approach in order to define

social position.

Concerning the measure of social position itself, it is important to understand what is really

measured by the chosen indicator. It is all the more important since results on gender

differences in social inequality of health depend on the choice of social position measure

(Manor, Matthews and Power, 1997; Sacker et al. 2000, Mustard and Etches 2003).

Theoretically based measures make it possible to distinguish different aspects of social

position and are useful in morbidity and mortality studies (Arber 1997, Krieger et al. 1997,

Chenu 2000). We considered different measures of social position: social class, highest level

of education and material resources. Class situation corresponds to individual chances to have

access to ownership and economic resources. In this paper, social class will be defined in

accordance to Erikson and Goldthorpe’s schema, relying on employment relation, type of

remuneration and job responsibilities. Firstly, this schema obviously distinguishes employers

from employees. Then, within employee categories, the nature of “employment relation”

between an employee and his employer, defined by the work contract, is considered to be

more important in class definition than tasks content or market situation. This relation defines

“job attributes” which are specific to occupational position and independent from the personal

characteristics of the incumbent. The “service relation” characterizes the “service class” who

experiences trust of the employer, a high level of responsibilities, autonomy and job security

and also possibilities of career advancement. Conversely, the “working class” is in a “wage-

labour relation” that is, largely supervised, paid by the hour, with a lower level of job security

and no career structure. Between these two types of employment relation, intermediate classes

combine at the same time “service relation” and “wage-labour relation” (Erikson Goldthorpe

1992). Because of the female career patterns, educational qualifications could be seen as more

stable than occupation for women and are indeed good predictors of women’s self-assessed

health (Arber 1997, Arber and Cooper 2000) and mortality (Erikson 2001). A third aspect of

social position is material living standards measured at the household level and including

income, ownership of home and car. From studies on women’s health, other dimensions

appeared essential. Marriage seems to have a beneficial effect for men, but for women it has a

cost in terms of their occupational career. Additionally, domestic work and children education

require less commitment to occupational role and limit women’s participation in the labour

force (De Singly 2004). Many married women drop out from the labour force after childbirth

and then return to work, often at a lower level (Joshi et al. 1996). Consequently, employment

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status and family structure must also be taken into account. Thus, gender comparative

research has to assess whether these aspects, i.e. socioeconomic position, employment status

and family structure, are relevant for both men and women (Arber and Khlat 2002).

Defining similar circumstances in gendered society

The difficulty of gender comparative research is to “compare like with like” since we live in

gendered societies. In most studies focusing on health and gender, men and women are

globally compared whereas they occupy different positions on labour market and domestic

roles (Hunt and Macintyre 2000). On labour market, “horizontal segregation” refers to the

concentration of women in certain occupations, mainly in white-collar occupations. There is

also a form of “vertical segregation” since women are less likely to get jobs in top

management because of the “glass ceiling.” Moreover part-time work and non-employment

are female specific situations. So gender-segregation in employment constrains gender

comparative research (Annandale and Hunt 2000). Gender specificities exist also on marriage

market. The pattern of desirability is not gender-neutral since, contrary to men, women in

higher categories are more likely to live alone than women in lower categories or housewives.

Furthermore, marriage and family favour male career but limit female participation in the

labour force. Lastly the increase in the number of divorces has created a new disadvantaged

group: single-parents, which are women in most cases (Table 1).

Despite the consistent evidence of smaller inequalities among women and of female excess in

reporting morbidity, the results obtained when men and women are in similar circumstances

could challenge such results. Comparing men and women working full time in a large British

bank, Emslie et al. (1999a, 1999b) conclude that the relationship between working conditions

and morbidity and between occupational grade and morbidity are similar for men and women

and that “these results lend support to a differential exposure, rather than a differential

vulnerability, model of gender differences in health” (Emslie et al. 1999a, p.465) It suggests

that if men and women were in the same social circumstances, the gender differences would

be weaker or even disappear. And so, working and living in gendered societies, the female

excess in morbidity would come from the greater social disadvantage women experience.

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DATA AND METHODS The sample

The data come from the French Health survey of 2002-2003. Every ten years, the French

National Institute for Statistics and Economic Studies (INSEE) conducts this survey, which

describes health status and health care consumption of the French population. The Health

survey offers in particular great possibilities to study health status according to socioeconomic

characteristics of households and individuals. More than 16 000 households (corresponding to

40,000 individuals) were interviewed. To take into consideration only individuals of working

age and who are likely to have a relatively stable situation, the analysis covers men and

women between 25 and 59 years of age who worked at some point in their lives2.

When we ask how social determinants affect men and women’s health, we make an

assumption on the sense of the causality. Health selection is an important limitation of the

research on social inequalities in health (Dahl, 1993). For instance, economically inactive

men of working age are strongly selected on their health status. Working part time could be

due to health problems. To take into account of health selection in the French cross-sectional

survey, three questions could be used: “You are not currently in work, is it for health

reasons?”, “You work part time, is it for health reasons?” and “During your working life

(since your first job), have you moved to a different job for health reasons?” 7% of men and

women answer yes to at least one of these questions. Following a clear social gradient, men in

all classes are more likely to report that their work situation is the result of health problems.

Actually, social inequalities in health selection on labour market are larger among men than

among women. Male unskilled manual workers have 8.4 higher risks to have been selected on

their health status than the higher service class, respectively compared to 4.9 for women

(Figure 1). This gender difference is partly explained by the more pronounced concentration

among men than among women of unhealthy categories such as unemployed, long-term

disabled and early retired in the bottom of social hierarchy (Stronks, van de Mheen, van den

Bos, Mackenbach, 1995).

Finally, we have excluded all respondents for which we can suppose they have been selected

on their health status. It is worth bearing in mind that we work on a relatively healthy sub-

sample of men and women. In this way, the sample contains 16, 151 individuals. 2 In the initial sample, 72 men and 454 women between 25 and 59 do not report information on their current or last occupation.

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Health outcome variables

According to the World Health Organization definition, health correspond to a state of

physical, mental and social well-being, and not simply to an absence of disease or infirmity.

As outcomes, we have used self-perceived health, long-standing illness and activity

restrictions which respectively refer to the subjective, medical and functional dimensions of

health status (Figure 2). Besides, Eurostat recommend to use these three questions in

European Health Surveys. First, self-perceived health is a common measure of health in

empirical research which is known as a good predictor of morbidity (Ferraro, Farmer, 1999)

and mortality (Idler, Benyamini, 1997). In the French Health survey, the following question

gives the measure of general self-assessed health: “How is your health in general…Very

good? Good? Fair? Poor? Very poor? ” For the analyses, we distinguish individuals who

report their health “less than good.” Second, we measure overall prevalence of chronic

conditions by the following question: “Do you have any long-standing illness?” for which

interviewers had to precise the definition of long-standing illness. Third, we assess the

limitation because of a health problem in usual activities by “For the past six months or more,

have you been limited in activities people usually do because of a health problem?” There is

not necessarily congruence between reporting a medical or a functional problem and reporting

poor health. 2/3 of men and women feeling restriction activity assess their health status less

than good, compared to only 1/3 of individuals with long-standing illness. As all these three

measures of health status belong to reported morbidity, our results could be questioned by

possible biases, especially a gender bias. But, contrary to the common representation, some

evidence highlight that women do not tend to “over-report” morbidity (Macintyre 1993,

Macintyre et al. 1996, Macintyre et al. 1999).

Statistical models

Logistic regression models estimate the probabilities to report poor health, to have long-

standing illness and to feel activity restrictions. For each health outcome, models are fitted

simultaneously for men and women crossing independent variables with sex in order to reveal

possible contradictory effects. In this way, it is possible to assess significant differences

between male and female parameters.

Controlling for age in five year age groups, the first model introduce only EGP social class.

Considering individual current occupation for the working population and the last occupation

for the unemployed or the non-employed who did work at some point, social class is

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measured according to the Erikson-Goldthorpe class schema. In this paper, we have used a

collapsed version in eight classes: I- Service class (higher grade), II- Service class (lower

grade), IIIa- Routine non-manual employees (administration and commerce), IIIb-Routine

non-manual employees (sales and service), IV- Small proprietors, V- Lower grade technicians

and supervisors, VI- Skilled manual workers, VII- Semi- and unskilled manual workers. Like

for manual workers, we have retained the distinction between skilled and unskilled employees

in class III, which is particularly relevant for women (Burnod and Chenu, 2001). The second

model intends to verify if the relationship between social class and health resists for both men

and women when introducing the highest level of education and household income per

consumption units3 ranked into quartiles from 1 (lowest) to 4 (highest). In the third model, we

have added employment status and family structure. Our work categories are inspired by the

Crompton schema (presented in Annandale, Hunt, 2000). For men and women, we have

distinguished secure full-time work, insecure full-time work, part-time work, dividing

between part-time work chosen by the employee and imposed by the employer4,

unemployment and non-working. We have combined marital status and parental status as “the

health effects of each one of those roles depends on the status of the woman in terms of the

other one” (Khlat et al. 2000, p.1818). So, to approach domestic roles and social support, we

have taken into account family structure, i.e. couple with children5, couple with no children,

single with children, single with no children and other households.

RESULTS Similarities and differences in male and female social gradient of health

What emerges first is that, if all other characteristics are fixed, women report poorer health

than men (Table 2) but this gender effect is not significant for long-standing illness (Table 3)

and activity restrictions (Table 4). It suggests that women do not tend to ‘over-report’ health

problems but perceive their health in a more pessimistic way.

Looking at self-perceived health, male and female social gradients present a relatively similar

extent when model introduces only age and EGP social class (Model 1). We just observe that 3 To compare standards of living when households do not have the same size or the same structure, we use a measure of income corrected by consumption units (CU). The following scale has been established by the OECD (Organization for Economic Cooperation and Development): 1 CU for the first adult in the household, 0.5 CU for all other individuals older than 14 years of age and 0.3 CU for all children under 14. 4 Part-time work is described as chosen if the respondent has answered that he has chosen to work part time or if he has not, he would not like to work more. This does not mean that the choice is totally independent of other constraints, particularly family responsibilities. 5 We have used the number of children in the household.

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compared to the highest social class, male skilled manual workers (OR = 3.7) tend to report

poorer health than their female counterparts (OR = 2.5). But, when we add education and

household income (Model 2) then employment status and family structure (Model 3), female

social gradient is more reduced than male one. Like skilled manual workers, the difference

between male and female routine non-manual employees working in sales and service is now

statistically significant (OR = 1.6 for men and 1.3 for women). Our result is strengthened by

the fact that other social class measures, such as ONS new classification (Sacker et al. 2000)

or the Wright’s schema (Wolfarth, 1997; Borrell, Muntaner, Benach and Artazcoz, 2004),

have also displayed weaker social inequalities among women. This result would confirm the

smaller social gradient in health among women if it was not challenged by other health

measures. Considering long-standing illness, individual social class seems able to reveal

inequalities among female population but not among male population. With respect to the

reference category as ‘service class (higher grade)’, the probability of women to report

chronic conditions is greater in intermediate classes (II, IIIa) and in lower classes (IIIb, VII),

whereas any difference is significant for men. Except for male skilled manual workers, the

influence of social class on activity restrictions (among a relatively healthy population) tends

to disappear for men and women when other individual characteristics are fixed.

Relating to educational qualifications, the patterns are very similar for men and women. As

expected, the more educated, the better self-assessed health. With respect to the reference

category as ‘University post-graduate degree’, the probability to report poor health is higher

when men and women have no qualifications (OR = 2 for men and 2.2 for women), only

primary leaving certificates or only GCSEs (OR = 1.5 and 1.8), technical or vocational

training certificate (OR = 1.3). Furthermore, the education gradient presents the same extent

for male and female populations. On the other hand, education level has a weak effect on

long-standing illness and activity restrictions. When turning to income, the probability of poor

self-assessed health increases logically when the income level decreases for both men and

women. Like the social class gradient, the household income gradient appears slightly more

pronounced for men than for women. With respect to the reference category as ‘highest

quartile’, men in the lowest quartile have significantly a higher risk of poor self-assessed

health (OR = 1.7) and activity restrictions (OR = 1.5) than their female counterparts.

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Gendered patterns in employment status and family structure

Although researchers often pointed out gender differences in social inequalities of health,

what does appear from our analyses is that social, education and material resources gradients

are globally similar for men and women, even if in some cases, social inequalities are

effectively larger among male population than among female population. But there is no

evidence that individual social position, measured here by EGP social class or highest level of

education, would do not affect women’s health, just as household social position,

approximated by income, would be more relevant to study social inequalities among women.

In fact, employment status and family structure may differentiate more strongly the gender

patterns in health.

Because of the important gender differences in employment status, it is difficult to strictly

compare its effects on men and women’s health. Compared to secure full-time workers, the

unemployed have a higher probability of poor self-assessed health (OR = 1.7), long-standing

illness (OR = 1.3) and activity restrictions (OR = 1.9). When we take into account the health

selection effect, unemployment becomes the most disadvantaged situation in term of health.

But it appears as the only one category affecting men and women’s health in a similar way.

The detrimental effect of job insecurity and threat of job loss on health (Bartley, Ferrie and

Montgomery, 2006) is evident only for men. Insecure full-time affects men’s health

negatively, compared to secure full-time contract. On the contrary, among women, job

insecurity has no significant effect on self-perceived health and long-standing illness, and

perhaps by a selection phenomenon, it could even be linked to less activity restrictions than

secure full-time. Gender differences come also from highly sex-segregated employment

status. Relating to part-time, the effect on men’s health is difficult to interpret since this

employment status concerns only 2% of men. On the other hand, it seems absolutely

necessary to take into account the heterogeneity of female part-time workers. Grouping

together all women working part time hides the fundamentally different pattern between

women voluntarily working part time and those who did not choose to do so. Women

voluntarily working part time are as healthy as women working full time, whereas women in

imposed part-time work report significantly poorer health (OR = 1.5), chronic conditions (OR

= 1.3) and limitations in usual activities (OR = 1.4). Consequently, considering a single

category for female part-time work, as most researchers do, tends to create a very mixed

group and, above all, to reduce inequalities among women. This reduction is all the more

marked since, contrary to voluntary part-time, which exists in similar proportions all along the

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social hierarchy, imposed part-time is only developed at the bottom of the scale. Even if

researchers have already noticed the existence of new part-time workers with low status, low

wages and low control (Matthews et al. 1998, Annandale Hunt 2000, Sacker et al. 2001), they

did not highlight how imposed part-time developed in lower social classes could be

detrimental for women’s health. Finally, housewives have admittedly a higher probability of

poor self-reported health (OR = 1.2), long-standing illness (OR = 1.2) and activity restrictions

(OR = 1.4) than secure full-time workers, but usually lower than women in imposed part-time

or in unemployment. It means that, contrary to men, the poor health of housewives is not fully

explained by health selection out of the labour market. Moreover, contrary to what the role

enhancement model predicts, non-working itself is not the worse situation for women. What

is the most detrimental for women’s health is when they want to work (as the unemployed) or

to work more (as those in imposed part-time) but cannot do it. Besides, an hypothesis in terms

of frustration have ever been proposed about the unemployed: “The poor self-assessed health

of unemployed women observed in this study might therefore be explained by the fact that

they are being frustrated in their desire for paid work and the income it provides” (Macran et

al 1994, p.202). And we can presume that this frustration feeling is greater within a relatively

healthy population.

Turning finally to family structure, gender differences appear more among singles than

among couples. Indeed, with respect to the reference category as ‘living in a couple with

children’, living in a couple without children does not affect men’s and women’s health. It

confirms the protective effect of marriage and the weakest or inexistent effect of children

since individuals live in a couple (Verbrugge 1983, Ross, Mirowsky and Goldsteen, 1990;

Macran et al. 1994, Waldron et al. 1998, Khlat et al. 2000). Conversely, living alone, i.e. with

no partner or children, is a disadvantaged family structure for men as for women in term of

self-perceived health (OR = 1.4), but is linked to activity restrictions only for women (OR =

1.4) However, contrary to men, living only with children without partner’s support affect

women’s health negatively (OR = 1.4 for self-perceived health and long-standing illness). In

relation with the increase in the number of divorces, women suffer from being single-parent

(Macran et al. 1994, 1996, Khlat et al. 2000, Lahelma et al. 2002). This female disadvantage

is all so more important because men rarely experience this situation. The poor health of

single mothers contradicts the cumulative hypothesis present in the role enhancement model

and support more the idea of a “coherence rule” between marital and parental status (Khlat et

al. 2000).

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Combining employment status and social class effects on self-perceived health

Until then, we have globally compare men and women without really taking into account

female specificities on labour market. As precedent results highlight, a large part of gender

differences in health come yet from sex-segregated situations: single mothers, part-time

workers and housewives for which it does not exist male counterparts. What do we observe

when we restrict our study population to men and women experiencing the same employment

status, i.e. secure full-time work?

In this part of the paper, we limit our analyses to the self-perceived health as far as this was

the only case in which social class inequalities have appeared weaker among women than

among men. What emerges in this way is that, considering only full-time workers challenges

this first result. The differences between male and female employees in sales and service and

skilled manual workers are no longer significant. The effect of social class on self-assessed

health is now similar for men and women, what goes against the idea that individual position

has only a slight influence on women’s health (Table 5). Furthermore, household income does

not affect women’s subjective health status anymore, what confirms again the importance of

individual social position to describe women in paid work. On the contrary, material

resources still create a hierarchy among male population. When we compare ‘like with like’,

gender similarities occur also in the effect of family structure. Among full-time workers, men

who raise their children alone have, as women, a higher probability to report poor health than

parents living in a couple.

So the social class gradient is similar for men and women working full time but smaller

among women considering the whole population. This apparent contradiction is certainly due

to the aggregation of two female groups who do not have the same relationship with labour

market. That is the reason why we have decided to consider working and non-working

women separately. Interestingly, individual social class had an influence on self-perceived

health among active women, but the last occupation seems to have no effect on women’s

health when they are outside labour market as housewives or unemployed (Table 6). The

interaction between activity status and social class is even significant for classes IIIb, IV, V

and VI. The fact that individual social class has no importance for non-working women is not

surprising when social class theoretically defines access to economic resources and job

conditions. Besides, if the effect was significant, it would be in fact negative, i.e. non working

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women belonging before to intermediate or lower classes tend to report less often poor health

than the more qualified women who stop to work. Therefore, the cost of inactivity seems

particularly substantial for women at the top of social hierarchy, what is understandable since

the interruption has important consequences on their career perspectives. Contrary to

individual social class, education generates similar inequalities among working and non-

working women, whereas household income appears more relevant for women outside labour

market. These results confirm what a precedent study of women’s health using path analysis

techniques have already shown: “The same model does not apply to women with different

levels of labour market attachment. The occupation based measure is shown to have little

relevance for describing the behaviour and health of women keeping house above that shown

by the cultural and material measures. However, an occupation based measure provides

additional insight into the mechanisms underlying the relationship between social position

and health for women in paid work” (Sacker et al., 2001, p. 779). Contradictory effects

between working and non-working women are therefore combined. In the case of individual

social class, they could reduce the extent of social inequalities among women. And this

reduction would be all the more pronounced since housewives remain a widespread situation

in a given society. On top of health selection effect more socially pronounced among male

population, the heterogeneity of female population according to their labour market

attachment could partly explained why mortality studies which concern old generations have

often pointed out the smaller social gradient among women, and also why education, relevant

for both working and non-working women, have usually been found as a good social indicator

in women’s health studies. Additionally, our results highlight the bad health of women who

combine work and family disadvantages since single mothers outside labour market (OR =

2.1) report poorer health than single mothers in paid work (OR = 1.3).

The cumulative advantages and disadvantages of social class, employment status and

family structure

Because of the epidemiological tradition, researchers in social determinants of health usually

present adjusted odds-ratio, which assume that all other variables are the same. Actually, all

other variables are not equal. For this reason, we have preferred to use the probability

predicted by the logistic model. With this representation, we are able to consider all socio-

demographic characteristics of individuals included in the models and above all to take into

account the combination of social inequalities. For example, an individual located at the top

of the social hierarchy has greater chances to be highly qualified, to earn a good living, to

14

work full time and to live in couple with children than an individual at the bottom of social

hierarchy. And men have higher chances to experience these favourable circumstances. We

may remind that when 20% of men belong to the highest social class by their occupation, this

is the case of 12% of women. Only 49% of women work full time, compared to 82% of men

and this gap is not filled even when adding the proportion of women voluntarily working part-

time (16%). Concerning family structures, women are less likely to live in a couple with

children than men; the main gender difference corresponds to the proportion of single-parent

(see Table 1).

In this way, odds-ratio and average predicted probabilities calculated with the same model

offer two different representations of social inequalities in self-perceived health. On figures 3,

we plot the odds-ratio and the average probability by social status predicted by the model 3

for men and for women. As we have already seen, the net effect of social class measured by

odds-ratio displays larger social inequalities among men. But considering all the individual

characteristics challenges this result. Whatever the social class, women have a higher risk to

perceive their health as poor. The female social gradient is then as strong as male one and

even more pronounced at the bottom of the status scale. Along the social scale, the probability

to report poor health ranges from 0.11 to 0.28 for women, respectively compared to 0.08 and

0.23 for men. The epidemiological paradigm consists in searching for the multiple risk factors

and adjusting on possible confusion factors. But, in their study of the society, sociologists

may not lose sight of the cumulative aspect of advantages and disadvantages in producing

social inequalities in health.

CONCLUSION

The underlying question of this paper was whether the smaller social inequalities in health

among women could be questioned by the varying occupational, work and family positions of

men and women. Working on a sub-sample in which individuals have not been selected on

their health status, the preliminary findings on self-perceived health confirm that social

inequalities measured by individual class are effectively weaker among women than among

men once all variables have been adjusted. Nevertheless, estimating long-standing illness, the

female social gradient is larger than male one. Furthermore, when considering only secure

full-time workers, social gradients in self-perceived health become now similar for both

genders. In fact, the smaller extent in social class inequalities among women comes

particularly from the aggregation of working and non-working women. The last occupation of

15

women outside labour market does not affect the perception of their health. Finally, when

taking into account the combination of social inequalities in work and family displays again

similar social gradient among men and women. All these results question some often-noted

“evidence”, such as the fundamental different pattern of men and women’s health, the smaller

social inequalities in health among women, the slightest importance of individual social class

in studying women’s health and maybe the representation of female population as more

homogenous and more egalitarian than male one.

We could not say that occupational class is an unimportant factor in the aetiology of women’s

health. If men and women had the same labour market attachment, we may suppose that

social influences on male and female health would be certainly more similar than different

(Carpenter, 2000). Women suffer from non-employment and under-employment. Non-

working seems to be particularly detrimental for the well-being of the more qualified women.

What is fundamentally different between men and women is precisely that, they do not

occupy the same occupations, do not have the same labour market attachments and do not live

in the same family structures. Actually, gender patterns in health are strongly differentiated

according to highly sex-segregated situations, such as part-time workers, housewives or

single-mothers, which supports to a differential exposure model than a differential

vulnerability model to account for gender differences in social inequalities in health.

A quotation from Annandale and Hunt (2000, p.23) accurately sums up our conclusions. They

wrote: “So while we may be witnessing emerging patterns of equality between some men and

women, this is accompanied by intensified forms of inequality between women (and

presumably also between men).” In particular, we have the feeling that employment status

generates important differentiations within male population and within female one. Among

full-time workers, insecure contract is clearly detrimental for men’s health. Female population

is also very heterogeneous according to their employment status. Women voluntarily working

part time are as healthy as women working full time, whereas women in imposed part-time

work report significantly poorer health. Social determinants of self-assessed health depend on

the labour market attachment of women, i.e. individual social class for women in paid work

and household income for housewives. Consequently, it seems difficult to define women’s

social position in a similar way for women inside and outside labour market. Rather than

marital status, women differentiate themselves on the basis of their work status and the issue

still remains to define the housewives’ social position.

16

These findings question the measure of social inequalities in health based on occupation only,

and advocate for taking into account the combination of social position, employment status

and family structure for a better appraisal of gender differences. “Looking separately at men’s

and women’s position in the occupational structure and at their ‘family’ circumstances may

obscure some very gendered patterns” (Annandale and Hunt 2000, p.17), as, for example,

women who combine all the disadvantages. And so, gender comparative researches have to

take into account the close combination, particularly relevant for women, between social

position, employment status and family structure. We think that future research on gender

differences in health would benefit from reformulating the initial question. It seems important

to focus on the combination of advantages and disadvantages, which tends to increase social

inequalities both within and across gender, rather than on beneficial or harmful effects of

multiple roles. With the development of job insecurity and new family structures, this

question would certainly become more and more appropriate to study health.

However, cross-sectional surveys are not really adjusted to control health selection since

initial health status is unknown. To determine the causal nature of social position, work and

family characteristics with illness, we have made the choice to exclude individuals for which

we may supposed they have been selected on their health status. In this way, our conclusions

remains necessarily partial because, as we have highlighted at the beginning, social

inequalities in health selection on labour market are larger among men than among women.

Further research using longitudinal data is then necessary to study all the mechanism of

selection and protection effects in generating gender similarities and differences in social

inequalities in health.

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20

TABLES AND FIGURES Table 1 - Distribution of independent variables for men and women (age 25-59) Column percentages Men Women All Age 25-29 10.9 11.8 11.3 30-34 15.9 15.4 15.6 35-39 15.6 16.1 15.9 40-44 16.4 15.6 16.0 45-49 14.4 15.1 14.8 50-54 18.1 17.6 17.9 55-59 8.7 8.4 8.5 Social class I- Service class (higher grade) 20.0 12.0 15.9 II- Service class (lower grade) 11.6 19.9 15.8 IIIa- Routine non-manual employees (administration and commerce)

5.5 26.9 16.2

IIIb- Routine non-manual employees (sales and service)

2.5 19.7 11.2

IV- Small proprietors 11.2 5.6 8.4 V- Lower grade technicians and supervisors 11.5 2.1 6.8 VI- Skilled manual workers 22.0 4.8 13.4 VII- Semi- and unskilled manual workers 15.7 9.0 12.3 Highest level of education None 15.0 14.9 14.9 Primary leaving certificate, GCSE 12.7 17.1 14.9 Technical or vocational training certificate 33.2 25.5 29.4 A-level 13.7 15.9 14.8 University post-graduate degree 25.4 26.6 26.0 Household income quartile 1 (lowest) 23.0 26.0 24.5 2 25.2 24.8 25.0 3 25.4 24.9 25.2 4 (highest) 26.4 24.3 25.3 Employment status Full-time (stable contract) 81.9 49.4 65.5 Full-time (temporary contract) 5.0 4.6 4.8 Part-time (chosen) 1.4 16.2 8.9 Part-time (imposed) 1.1 4.5 2.8 Unemployed 6.9 8.0 7.5 Non-working 3.7 17.3 10.5 Family structure Couple with children 59.0 54.4 56.6 Couple, no children 23.3 22.8 23.1 Single, children 1.8 10.3 6.1 Single, no children 13.6 10.1 11.8 Other 2.3 2.4 2.4

Number of observations 7781 8370 16151 Source: Enquête Santé, INSEE, 2002-2003 Field : Men and women between 25 and 59

21

Figure 1 –Selection on labour market for health reasons

0

1

2

3

4

5

6

7

8

9

I IV II V VI IIIb IIIa VII

Social class

odds

-rat

io

Men

Women

Models control for age Source: Enquête Santé, INSEE, 2002-2003 Field : Men and women between 25 and 59 Figure 2 – Self-perceived health, long-standing illness and activity restriction among men and women

0

5

10

15

20

25

30

35

Poor self-perceived health

Long-standingillness

Activity restriction

%

Men Women

Source: Enquête Santé, INSEE, 2002-2003 Field : Men and women between 25 and 59

22

Table 2 – Logistic regression models with ‘less than good’ self-perceived health as outcome Model 1 Model 2 Model 3 Men Women Men Women Men Women Intercept -2.71 *** -2.89 *** -2.99 *** Sex Men Ref. Ref. Ref. Women 0.36 ** 0.41 ** 0.40 ** Social class I- Service class (higher grade)

Ref. Ref. Ref. Ref. Ref. Ref.

II- Service class (lower grade)

0.60 *** 0.35 *** 0.42 *** 0.19 0.41 *** 0.20 *

IIIa- Routine non-manual employees (administration and commerce)

0.91 *** 0.68 *** 0.50 *** 0.23 * 0.48 *** 0.24 *


1.28 *** 0.92 *** 0.78 *** 0.25 * 0.69 *** 0.29 **

IV- Small proprietors 0.80 *** 0.58 *** 0.39 *** 0.07 0.41 *** 0.19 V- Lower grade technicians and supervisors

0.68 *** 0.34 0.40 *** 0.01 0.41 *** -0.01

VI- Skilled manual workers 1.32 *** 0.93 *** 0.81 *** 0.31 * 0.78 *** 0.31 * VII- Semi- and unskilled manual workers

1.17 *** 1.13 *** 0.56 *** 0.36 ** 0.51 *** 0.36 **

Highest level of education None 0.70 *** 0.81 *** 0.71 *** 0.79 *** Primary leaving certificate, GCSE

0.37 *** 0.61 *** 0.41 *** 0.60 ***

Technical or vocational training certificate

0.20 * 0.29 *** 0.24 ** 0.30 ***

A-level 0.13 0.18 * 0.17 0.19 * University post-graduate degree

Ref. Ref. Ref. Ref.

Household income quartile

1 (lowest) 0.58 *** 0.45 *** 0.54 *** 0.30 *** 2 0.30 *** 0.27 *** 0.30 *** 0.21 ** 3 0.23 ** 0.17 ** 0.23 ** 0.15 * 4 (highest) Ref. Ref. Ref. Ref. Employment status Full-time (stable contract) Ref. Ref. Full-time (temporary contract)

0.26 * 0.01

Part-time (chosen) -0.01 -0.05 Part-time (imposed) -0.03 0.39 *** Unemployed 0.51 *** 0.57 *** Non-working -0.29 * 0.17 ** Family structure Couple with children Ref. Ref. Couple, no children 0.09 0.09 Single, children 0.34 0.33 *** Single, no children 0.31 *** 0.32 *** Other 0.17 0.07

Number of observations% correct

16151 65

16151 67

16151 68

Source: Enquête Santé, INSEE, 2002-2003 Field : Men and women between 25 and 59 Models control for age *** significant at 0.01,** significant at 0.05, *significant at 0.10 Significant difference between male and female parameters at 0.10

23

Table 3 – Logistic regression models with ‘long-standing illnesses’ as outcome Model 1 Model 2 Model 3 Men Women Men Women Men Women Intercept -0.95 *** -0.94 *** -0.96 *** Sex Men Ref. Ref. Ref. Women -0.08 -0.04 -0.12 Social class I- Service class (higher grade)



0.09 0.16 * 0.10 0.20 ** 0.09 0.19 **


0.02 0.15 * 0.03 0.19 ** 0.03 0.18 **


0.02 0.25 *** 0.01 0.25 ** -0.02 0.24 **

IV- Small proprietors -0.01 -0.01 -0.02 0.02 -0.01 0.06 V- Lower grade technicians and supervisors

0.09 0.21 0.10 0.23 0.10 0.22

VI- Skilled manual workers 0.03 0.22 * 0.01 0.23 -0.01 0.22 VII- Semi- and unskilled manual workers

0.08 0.36 *** 0.05 0.34 *** 0.03 0.33 ***

Highest level of education None 0.07 0.11 0.06 0.12 Primary leaving certificate, GCSE

-0.08 0.05 -0.07 0.06


0.03 -0.01 0.04 0.01

A-level -0.12 -0.16 ** -0.12 -0.14 * University post-graduate degree

Ref. Ref. Ref. Ref.

Household income quartile 1 (lowest) 0.04 -0.08 0.02 -0.15 * 2 -0.03 -0.05 -0.03 -0.08 3 -0.02 -0.10 -0.02 -0.11 4 (highest) Ref. Ref. Ref. Ref. Employment status Full-time (stable contract) Ref. Ref. Full-time (temporary contract)

0.22 * 0.01

Part-time (chosen) -0.05 0.13 * Part-time (imposed) -0.25 0.26 ** Unemployed 0.29 *** 0.27 ***Non-working -0.04 0.17 ** Family structure Couple with children Ref. Ref. Couple, no children 0.06 0.09 Single, children -0.06 0.12 Single, no children 0.02 0.32 ***Other -0.15 -0.19

Number of observations % correct

16151 59

16151 59

16151 60


24

Table 4 – Logistic regression models with ‘activity restrictions’ as outcome Model 1 Model 2 Model 3 Men Women Men Women Men Women Intercept -3.13 *** -3.25 *** -3.32 *** Sex Men Ref. Ref. Ref. Women 0.23 0.34 0.31 Social class I- Service class (higher grade)



0.20 0.11 0.08 0.08 0.06 0.06


0.55 *** 0.20 0.29 0.08 0.32 0.07


0.43 0.17 0.10 -0.05 0.03 -0.05

IV- Small proprietors 0.25 0.07 -0.06 -0.08 -0.01 -0.01 V- Lower grade technicians and supervisors

0.26 0.31 0.06 0.21 0.08 0.19

VI- Skilled manual workers 0.75 *** 0.18 0.38 ** -0.02 0.34 * -0.07 VII- Semi- and unskilled manual workers

0.44 *** 0.56 *** 0.05 0.31 -0.01 0.28

Highest level of education None 0.25 0.22 0.24 0.17 Primary leaving certificate, GCSE

0.14 0.27 * 0.19 0.25 *


-0.02 -0.07 0.29 ** -0.08

A-level -0.06 0.01 0.01 0.01 University post-graduate degree

Ref. Ref. Ref. Ref.

Household income quartile

1 (lowest) 0.52 *** 0.16 0.40 ** -0.02 2 0.13 0.22 * 0.09 0.16 3 0.13 -0.07 0.12 -0.09 4 (highest) Ref. Ref. Ref. Ref. Employment status Full-time (stable contract) Ref. Ref. Full-time (temporary contract)

0.48 ** -0.58 **

Part-time (chosen) -0.29 0.09 Part-time (imposed) -0.96 0.31 * Unemployed 0.78 *** 0.62 *** Non-working -0.02 0.36 *** Family structure Couple with children Ref. Ref. Couple, no children 0.07 0.06 Single, children -0.01 0.31 ** Single, no children 0.13 0.08 Other 0.27 -0.01


16151 60

16151 62

16151 63


25

Table 5 – Logistic regression models for full-time workers Poor self-perceived

health Men Women Intercept -3.09 *** Sex Men Ref. Women 0.57 ** Social class I- Service class (higher grade) Ref. Ref. II- Service class (lower grade) 0.47 *** 0.30 * IIIa- Routine non-manual employees (administration and commerce)

0.50 ** 0.44 **


0.61 ** 0.55 ***

IV- Small proprietors 0.39 ** 0.43 ** V- Lower grade technicians and supervisors

0.41 ** 0.41

VI- Skilled manual workers 0.78 *** 0.76 ***VII- Semi- and unskilled manual workers

0.46 *** 0.46 **

Highest level of education None 0.80 *** 0.73 ***Primary leaving certificate, GCSE

0.55 *** 0.42 ***


0.37 *** 0.18

A-level 0.33 ** 0.18 University post-graduate degree

Ref. Ref.

Household income quartile 1 (lowest) 0.55 *** 0.16 2 0.25 ** 0.07 3 0.19 * 0.07 4 (highest) Ref. Ref. Family structure Couple with children Ref. Ref. Couple, no children 0.16 0.16 Single, children 0.55 ** 0.26 * Single, no children 0.31 *** 0.31 ** Other 0.23 0.13


10609 67.5

Source: Enquête Santé, INSEE, 2002-2003 Field : Men and women in secure full-time work between 25 and 59 Models control for age *** significant at 0.01,** significant at 0.05, *significant at 0.10 Significant difference between male and female parameters at 0.10

26

Table 6 – Logistic regression models for women Poor self-perceived

health Working Non-

working Intercept -2.60 *** Employment status Working Ref. Non-working 0.24 Social class I- Service class (higher grade)

Ref. Ref.


0.28 ** -0.15


0.29 ** -0.07


0.44 *** -0.24

IV- Small proprietors 0.28 -0.37 V+VI- Lower grade technicians and supervisors and Skilled manual workers

0.46 ** -0.45

VII- Semi- and unskilled manual workers

0.42 ** -0.01

Highest level of education None 0.81 *** 0.87 ***Primary leaving certificate, GCSE

0.58 *** 0.77 ***


0.22 * 0.58 ***

A-level 0.15 0.38 * University post-graduate degree

Ref. Ref.

Household income quartile 1 (lowest) 0.27 ** 0.56 ***2 0.14 0.57 ***3 0.16 0.19 4 (highest) Ref. Ref. Family structure Couple with children Ref. Ref. Couple, no children 0.13 0.03 Single, children 0.24 ** 0.72 ***Single, no children 0.33 *** 0.40 ** Other 0.12 0.05


8370 67

Source: Enquête Santé, INSEE, 2002-2003 Field : Women between 25 and 59 Models control for age *** significant at 0.01,** significant at 0.05, *significant at 0.10 Significant difference between working and non-working parameters at 0.10

27

Figure 3 – Two representations of social inequalities in self-perceived health

0

0,5

1

1,5

2

2,5

I II IIIa IIIb IV V VI VII

Social class

odds

-rat

io

Source : Enquête Santé, INSEE, 2002-2003 Field : Men and women between 25 and 59 Note : Odds-ratio by social class from the model 3

0

0,05

0,1

0,15

0,2

0,25

0,3

I II IIIa IIIb IV V VI VII

Social class

Ave

rage

pre

dict

ed p

roba

bilit

y

Men

Women

Source : Enquête Santé, INSEE, 2002-2003 Field : Men and women between 25 and 59 Note : Average probabilities by social class predicted with the model 3 for each man (or woman) considering his (or her) individual characteristics

28

men and women’s health: the cumulative advantages and ... · and sex (lanoé and...

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