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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)
+ 00.33.1.41.17.57.55 (fax) cousteaux@ensae.fr
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Please do not cite or quote without the author’s permission.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.
1
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).
4
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.
6
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.
7
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
8
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
11
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
13
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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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 *
IIIb- Routine non-manual employees (sales and service)
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)
Ref. Ref. Ref. Ref. Ref. Ref.
II- Service class (lower grade)
0.09 0.16 * 0.10 0.20 ** 0.09 0.19 **
IIIa- Routine non-manual employees (administration and commerce)
0.02 0.15 * 0.03 0.19 ** 0.03 0.18 **
IIIb- Routine non-manual employees (sales and service)
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
Technical or vocational training certificate
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
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
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)
Ref. Ref. Ref. Ref. Ref. Ref.
II- Service class (lower grade)
0.20 0.11 0.08 0.08 0.06 0.06
IIIa- Routine non-manual employees (administration and commerce)
0.55 *** 0.20 0.29 0.08 0.32 0.07
IIIb- Routine non-manual employees (sales and service)
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 *
Technical or vocational training certificate
-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
Number of observations % correct
16151 60
16151 62
16151 63
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
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 **
IIIb- Routine non-manual employees (sales and service)
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 ***
Technical or vocational training certificate
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
Number of observations % correct
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.
II- Service class (lower grade)
0.28 ** -0.15
IIIa- Routine non-manual employees (administration and commerce)
0.29 ** -0.07
IIIb- Routine non-manual employees (sales and service)
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 ***
Technical or vocational training certificate
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
Number of observations % correct
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
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