Abstract

Background: Recent research shows that adverse experiences, such as economic hardships or exclusion, contribute to deterioration of health status. However, individuals currently experiencing adverse experiences are excluded from conventional health surveys, which, in addition, often focus on current social situation but rarely address past adverse experiences. This research explores the role of such experiences on health and related social inequalities based on a new set of ad hoc questions included in a regular health survey. Methods: In 2004, the National Health, Health Care and Insurance Survey included three questions on lifelong adverse experiences (LAE): financial difficulties, housing difficulties due to financial hardship, isolation. Logistic regressions were used to analyse associations between LAE, current socio-economic status (SES) (education, occupation, income) and health status (self-perceived health, activity limitation, chronic morbidity), on a sample of 4308 men and women aged ≥35 years. Results: LAE were reported by 20% of the sample. They were more frequent in low SES groups but concerned >10% of the highest income group. LAE increased the risk of poor self-perceived health, diseases and activity limitations, even after controlling for current SES [odds ratio (OR) > 2]. LAE experienced only during childhood are also linked to health. LAE account for up to 32% of the OR of activity limitations associated with the lowest quintile among women and 26% among men. Conclusions: LAE contribute to the social health gradient and explain variability within social groups. It is useful to take lifetime social factors into account when monitoring health inequalities.

Introduction

In France, social inequalities in mortality are large and persistent over time.1–3 Education, occupation and income, which reflect current social and material context, are predictors of mortality and are significantly associated with the risk of diseases or disability.4–7 However, life-course epidemiology points out that past trajectories are an important health determinant in addition to current socio-economic status (SES). The accumulation of exposure to risk factors over the life course (childhood deprivation, damaging work conditions, etc.) and their impact at critical periods of life contribute to health deterioration.8–14

Regarding the impact of social context during childhood, studies show clear associations with mortality risk,10,15 as well as various health problems such as chronic diseases and mental health problems.16–18 In France, childhood conditions are associated with mortality, poor functional health, poor self-assessed health or obesity.19–22 The health impact of childhood circumstances not only has to do with material deprivation, but also isolation, social support and attachment.23,24

In later life, adverse experiences such as hardship, downward occupational mobility or family disruptions are also significantly associated with poor health or high mortality risks.25–28 In France, mortality is associated with occupational careers or experience of isolation.22,29–31

Such adverse experiences can lead to social marginalization and can contribute, together with the current context of hardship and deprivation, to excess health risks for groups of the population considered as excluded. For Shaw and colleagues, social exclusion ‘refers not only to the economic hardship of relative economic poverty but also incorporates the notion of the process of marginalization’.32 The triggers of a marginalization process, such as job loss, migration, isolation or conflict could indeed be health damaging through a disruption in social networks, habits and support. Research in the field of exclusion and health in France has shown that the poor health status of specific groups such as homeless people or free health-care centre users, can not only be explained by the lack of material resources, poor living conditions, inadequate access to health care and health-damaging behaviours, but may also be due to psychosocial factors such as lack of emotional and social support, poor self-esteem and life control.33–35 For these groups of people, the combination of current material deprivation, psychosocial disadvantage and past experiences of disruptions and failures that led to exclusion might explain their poor health. Moreover, whilst these circumstances may be only temporary, having undergone them over the life course might still be health damaging.

Therefore, lifelong adverse experiences (LAE), leading or not to exclusion, can increase health risks beyond the current social context. They are important social factors to be considered in monitoring population health, but routine statistics lack accurate tools. The link between adverse experiences and health is generally analysed through ad hoc surveys or cohorts, which are not fully representative of the general population. Indeed, regular survey samples tend to exclude people currently experiencing them (not living in households, hard to reach, not willing to participate, etc.). And when population-based surveys incorporate information on past adverse experiences, collected through biographic tools, they have limited data on health outcomes. Finally, biographic tools are generally too large to be included on a regular basis in population health surveys. In order to analyse the link between adverse experiences and health in general population, a short set of questions on LAE was introduced in a population health survey in France in 2004. The questions relate to selected situations of material and social difficulties that might have occurred during the whole life. Therefore, this survey allows considering adverse experiences that may be temporary and do not systematically result in permanent social exclusion. This study firstly explores whether LAE are associated with health status beyond the current social situation. Second, it aims to assess how far LAE contribute to social health inequalities.

Methods

The National Health, Health Care and Insurance Survey

The National Health, Health Care and Insurance Survey (ESPS: ‘Enquête sur la Santé et la Protection Sociale’) is a biennial health interview survey coordinated by the Institute for Research and Information on Health Economics (IRDES), with a sample based on an ongoing random sample of French major health insurance beneficiaries (covering >95% of the population of private households). In 2004, ~40% of households sampled could not be reached (mostly due to incomplete or wrong addresses); 70% of the contacted households agreed to participate.36 Initially, households were contacted by telephone to obtain a key respondent to answer the core questionnaire eliciting the demographics of the household members and a selection of questions including, in the 2004 wave, the set of questions on LAE. As a second step, a self-completion health questionnaire was sent to each household member for return by mail. In 2004, 75% of the initial sample returned the questionnaire.

LAE

LAE in the general private household population were assessed through three questions aimed at identifying lifetime experiences of deprivation and hardship in terms of financial and housing difficulties, and social disruption through experiences of isolation. The question wording was as follows: has the person ever, during his/her life, (i) ‘experienced serious financial difficulties so that he/she could not meet basic needs or that he/she did not cope with these difficulties’; (ii) ‘needed to move in with relatives or friends or to move into sheltered housing as a result of financial difficulties’; (iii) ‘experienced a long-term period of isolation following an event such as a break-up, conflict or a move to another area or country’. In order to assess the long-term impact of LAE, for the last two questions, individuals were asked whether these experiences had occurred during childhood only, during adulthood only or both (financial difficulties might be less obvious to children and therefore less reliably reported as childhood experience by the surveyed persons).

Health indicators

We used the Eurostat Minimum European Health Module37 incorporated into this survey and which contains three questions covering complementary health dimensions: chronic morbidity (‘Do you have any chronic or long-lasting illness or health problem?’); self-perceived health (‘How is your health in general?’); long-term activity limitations (‘Because of health problems, to what extent have you been limited, for at least 6 months, in activities people usually do?’). Three binary indicators were built based on the three questions: reporting ‘chronic illness’ vs. ‘no chronic health illness’, reporting ‘being limited’ vs. ‘not limited’ and reporting ‘fair to very poor health’ vs. ‘good or very good’.

Indicators of current social status

To control for current SES, three indicators were used: education, income and occupation. Income was measured as household income, divided by the Organisation for Economic Co-operation and Development equivalence scale (1 for the first household member, 0.5 for the second one and 0.3 for the additional ones). Five quintiles were defined and an additional category was added corresponding to missing information (~12%). We considered four educational levels and the occupational status was measured by current occupation or the previous occupation for those retired or unemployed. We used the French occupational and social status classification: highly qualified occupations (professionals, managers and intellectual professions); skilled white-collar workers (nurses, elementary school teachers, technicians, etc.); farm owners; other self-employed (trade and craft business owner); trade and craft employees; clerical employees; skilled manual workers; unskilled manual workers and farm workers; without occupation (other than retired and unemployed).

Statistical method

Several logistic regressions adjusted for age were conducted separately for men and women.38

First, the association between LAE and each current SES indicator was analysed separately (Model 1) and simultaneously (Model 2) to assess the unequal risk of LAE.

Second, regression models 3 to 5 explore the association between LEA and the health dimensions. In Model 3, we analyse the health risks associated with each SES indicator and with LAE (univariate with control for age only). In order to confirm the association between LAE and health in all social groups, the analyses were separately reproduced in the lowest and the highest income groups. In Model 4, we analyse the health risks associated with SES indicators when they are simultaneously included in the model. Then, we include LAE in the Model 5 to see if its association with health remains significant beyond the current SES. As suggested by Van de Mheen and colleagues,39 the contribution of LAE to social health inequalities can be assessed by an index (Δ) being the percentage of decrease in the excess risk of poor health [odds ratio (OR) > 1] associated to SES between Models 4 and 5.  

formula
(Δ computed on OR accurate to three decimal points).

Third, we analyse the association between each health indicator and the period in which the LAE occurred, without and with adjustment for SES indicators (respectively Models 6 and 7).

The LAE are based on self-reported retrospective information, and therefore respondents may be more likely to report LAE that have resulted in health problems and to omit others. Furthermore, respondents currently experiencing health problems and poor psychological well-being may be more likely to ‘darken’ their past (reconstruction phenomena).23 In order to control for this, we ran additional models adjusted for current psychological distress. As no reference mental health scale was available in this survey, we used the information on self-reported morbidity based on a list of diseases and symptoms that are coded and classified (i.e. reporting depression or symptoms of depression, such as anxiety) plus the information on self-reported medication classified a posteriori by physician (intake of medication coded as psychotropic).

Results

This study is based on 1915 men and 2393 women, aged ≥35 years who responded to both the background and health questions. Table 1 provides the distribution of the sample by SES status, LEA and health indicators. In our sample, 20% of women and 18% of men reported one or more LAE, mostly long-term periods of isolation and financial difficulties. One third of those who reported housing difficulties and/or isolation (12% of women and 14% of men) experienced them in childhood only. Adverse experiences in both childhood and adulthood were rare.

Table 1

Descriptive analysis of the study sample (2004 ESPS survey)

 Male Female 
Age and SES N (%) N (%) 
Age group, years   
    35–44 518 (27.1) 691 (29.0) 
    45–54 509 (26.6) 650 (27.2) 
    55–64 392 (20.5) 442 (18.5) 
    65–74 291 (15.2) 330 (13.8) 
    ≥75 205 (10.7) 280 (11.7) 
Level of education   
    Primary (Educ 1)* 425 (22.2) 6230 (26.3) 
    Lower secondary (Educ 2) 788 (41.2) 843 (35.2) 
    Higher secondary (Educ 3) 236 (12.3) 359 (15.0) 
    Post-secondary (Educ 4) 466 (24.3) 561 (23.4) 
Occupational class   
    Highly qualified occupations (High qual.)* 390 (20.4) 220 (9.2) 
    Skilled white collar occupations (White col.) 376 (19.6) 486 (20.3) 
    Farmers 118 (6.2) 101 (4.2) 
    Self-employed (Self-empl.) 185 (9.7) 110 (4.6) 
    Clerical employees (Adm. empl.) 114 (6.0) 603 (25.2) 
    Trade and craft employees (Tr. empl.) 33 (1.7) 435 (18.2) 
    Skilled manual workers (Sk. MW) 555 (29.0) 163 (6.8) 
    Unskilled manual workers (Unsk. MW) 144 (7.5) 185 (7.7) 
    Inactive (No occ.) – (–) 90 (3.8) 
Income group   
    1st quintile (Quintile 1)* 255 (13.3) 373 (15.6) 
    2nd quintile (Quintile 2) 284 (14.8) 413 (17.6) 
    3rd quintile (Quintile 3) 346 (18.1) 417 (17.4) 
    4th quintile (Quintile 4) 340 (17.8) 422 (17.6) 
    5th quintile (Quintile 5) 470 (24.5) 465 (19.4) 
    Unknown 220 (11.5) 303 (12.7) 
Health indicators   
Self-perceived health   
    Very good or good 1379 (72.0) 1599 (66.8) 
    Fair, poor or very poor 536 (28.0) 794 (33.2) 
Chronic diseases   
    None 1271 (66.4) 1562 (65.3) 
    At least one 644 (33.6) 831 (34.7) 
Activity limitation   
    Not limited 1514 (79.1) 1855 (77.5) 
    Limited 401 (20.9) 538 (22.5) 
LAE   
LAE (At least one)   
    Have ever experienced 339 (17.7) 485 (20.3) 
Financial problem   
    Have ever experienced 155 (8.1) 246 (10.3) 
Housing problem   
    Have ever experienced 94 (4.9) 138 (5.8) 
        in childhood only 27 (1.4) 53 (2.2) 
        in adulthood only 65 (3.4) 85 (3.6) 
        in childhood and adulthood 2 (0.1) – (–) 
Period of isolation   
    Have ever experienced 176 (9.2) 259 (10.8) 
        in childhood only 83 (4.3) 121 (5.1) 
        in adulthood only 82 (4.3) 114 (4.8) 
        in childhood & adulthood 11 (0.6) 24 (1.0) 
Housing or/and isolation   
    Have ever experienced 231 (12.1) 332 (13.9) 
        in childhood only 91 (4.8) 131 (5.5) 
        in adulthood only 121 (6.3) 167 (7.0) 
        in childhood and adulthood 19 (1.0) 34 (1.4) 
Number of LAE   
    Only one type of experiences 268 (14.0) 349 (14.6) 
    Only two types of experiences 56 (2.9) 114 (4.8) 
    Only three types of experiences 15 (0.8) 22 (0.9) 
Total 1915 (100) 2393 (100) 
 Male Female 
Age and SES N (%) N (%) 
Age group, years   
    35–44 518 (27.1) 691 (29.0) 
    45–54 509 (26.6) 650 (27.2) 
    55–64 392 (20.5) 442 (18.5) 
    65–74 291 (15.2) 330 (13.8) 
    ≥75 205 (10.7) 280 (11.7) 
Level of education   
    Primary (Educ 1)* 425 (22.2) 6230 (26.3) 
    Lower secondary (Educ 2) 788 (41.2) 843 (35.2) 
    Higher secondary (Educ 3) 236 (12.3) 359 (15.0) 
    Post-secondary (Educ 4) 466 (24.3) 561 (23.4) 
Occupational class   
    Highly qualified occupations (High qual.)* 390 (20.4) 220 (9.2) 
    Skilled white collar occupations (White col.) 376 (19.6) 486 (20.3) 
    Farmers 118 (6.2) 101 (4.2) 
    Self-employed (Self-empl.) 185 (9.7) 110 (4.6) 
    Clerical employees (Adm. empl.) 114 (6.0) 603 (25.2) 
    Trade and craft employees (Tr. empl.) 33 (1.7) 435 (18.2) 
    Skilled manual workers (Sk. MW) 555 (29.0) 163 (6.8) 
    Unskilled manual workers (Unsk. MW) 144 (7.5) 185 (7.7) 
    Inactive (No occ.) – (–) 90 (3.8) 
Income group   
    1st quintile (Quintile 1)* 255 (13.3) 373 (15.6) 
    2nd quintile (Quintile 2) 284 (14.8) 413 (17.6) 
    3rd quintile (Quintile 3) 346 (18.1) 417 (17.4) 
    4th quintile (Quintile 4) 340 (17.8) 422 (17.6) 
    5th quintile (Quintile 5) 470 (24.5) 465 (19.4) 
    Unknown 220 (11.5) 303 (12.7) 
Health indicators   
Self-perceived health   
    Very good or good 1379 (72.0) 1599 (66.8) 
    Fair, poor or very poor 536 (28.0) 794 (33.2) 
Chronic diseases   
    None 1271 (66.4) 1562 (65.3) 
    At least one 644 (33.6) 831 (34.7) 
Activity limitation   
    Not limited 1514 (79.1) 1855 (77.5) 
    Limited 401 (20.9) 538 (22.5) 
LAE   
LAE (At least one)   
    Have ever experienced 339 (17.7) 485 (20.3) 
Financial problem   
    Have ever experienced 155 (8.1) 246 (10.3) 
Housing problem   
    Have ever experienced 94 (4.9) 138 (5.8) 
        in childhood only 27 (1.4) 53 (2.2) 
        in adulthood only 65 (3.4) 85 (3.6) 
        in childhood and adulthood 2 (0.1) – (–) 
Period of isolation   
    Have ever experienced 176 (9.2) 259 (10.8) 
        in childhood only 83 (4.3) 121 (5.1) 
        in adulthood only 82 (4.3) 114 (4.8) 
        in childhood & adulthood 11 (0.6) 24 (1.0) 
Housing or/and isolation   
    Have ever experienced 231 (12.1) 332 (13.9) 
        in childhood only 91 (4.8) 131 (5.5) 
        in adulthood only 121 (6.3) 167 (7.0) 
        in childhood and adulthood 19 (1.0) 34 (1.4) 
Number of LAE   
    Only one type of experiences 268 (14.0) 349 (14.6) 
    Only two types of experiences 56 (2.9) 114 (4.8) 
    Only three types of experiences 15 (0.8) 22 (0.9) 
Total 1915 (100) 2393 (100) 

*Abbreviations used in following tables

LAE were reported in all SES groups with a decreasing gradient with increasing income, educational level or qualified occupation (table 2). However, LAE are reported by >10% of our population in the highest income quintiles or qualified occupations; more frequently for women than for men. Note that farmers reported less LAE than any other occupational groups. LAE remained strongly associated with current SES after controlling for age (Model 1). Only income remained strongly associated with LAE when the other SES indicators were simultaneously controlled for (Model 2). Farmer is the only occupation with a remaining (negative) relationship, while much of the association with education disappeared.

Table 2

Associations between LAE and level of education, occupation and income

 Men
 
Women
 
 LAE frequency Model 1a Model 2b LAE frequency Model 1a Model 2b 
 N (%) OR [95% CI] OR [95% CI] N (%) OR [95% CI] OR [95% CI] 
Educ 4 58 (12.5) 1.0 1.0 94 (16.8) 1.0 1.0 
Educ 3 41 (17.4) 1.5 [1.0–2.3] 1.2 [0.8–2.0] 66 (18.4) 1.2 [0.8–1.6] 1.0 [0.7–1.4] 
Educ 2 150 (19.0) 1.7 [1.2–2.3] 1.1 [0.7–1.6] 180 (21.4) 1.4 [1.1–1.9] 1.1 [0.7–1.5] 
Educ 1 90 (21.2) 2.2 [1.5–3.3] 1.4 [0.8–2.2] 145 (23.0) 2.3 [1.6–3.1] 1.5 [0.9–2.3] 
High qual. 48 (12.3) 1.0 1.0 37 (16.8) 1.0 1.0 
White col. 55 (14.6) 1.2 [0.8–1.9] 1.0 [0.6–1.6] 76 (15.6) 0.9 [0.6–1.4] 0.8 [0.5–1.3] 
Farmers 10 (8.5) 0.7 [0.3–1.4] 0.4 [0.2–0.8] 6 (5.9) 0.4 [0.2–1.0] 0.2 [0.1–0.4] 
Self-empl. 38 (20.5) 1.8 [1.2–2.9] 1.4 [0.8–2.3] 19 (17.3) 1.2 [0.7–2.3] 0.8 [0.4–1.5] 
Ad. empl. 20 (17.5) 1.5 [0.9–2.7] 1.0 [0.6–1.9] 127 (21.1) 1.3 [0.9–2.0] 0.9 [0.6–1.5] 
Tr. empl. 9 (27.3) 2.7 [1.2–6.1] 1.7 [0.7–4.2] 107 (24.6) 1.7 [1.1–2.6] 0.9 [0.6–1.6] 
Sk. MW 127 (22.9) 2.1 [1.5–3.0] 1.4 [0.9–2.2] 32 (19.6) 1.3 [0.8–2.2] 0.7 [0.4–1.4] 
Unsk MW 32 (22.7) 2.0 [1.2–3.3] 1.1 [0.6–1.9] 52 (28.1) 2.1 [1.3–3.4] 1.0 [0.6–1.8] 
No occ.    29 (32.2) 3.0 [1.7–5.4] 1.4 [0.7–2.7] 
Quintile 5 50 (10.6) 1.0 1.0 62 (13.3) 1.0 1.0 
Quintile 4 45 (13.2) 1.3 [0.8–2.0] 1.2 [0.7–1.8] 62 (14.7) 1.1 [0.8–1.6] 1.1 [0.7–1.6] 
Quintile 3 68 (19.7) 2.0 [1.4–3.0] 1.8 [1.2–2.7] 82 (19.7) 1.6 [1.1–2.3] 1.4 [1.0–2.2] 
Quintile 2 63 (22.2) 2.4 [1.6–3.6] 2.1 [1.4–3.3] 90 (21.8) 1.9 [1.3–2.7] 1.7 [1.1–2.5] 
Quintile 1 71 (27.8) 3.2 [2.2–4.8] 3.0 [1.9–4.7] 138 (37.0) 4.0 [2.9–5.7] 3.8 [2.6–5.6] 
Unknown 42 (19.1) 2.0 [1.3–3.2] 1.8 [1.2–3.0] 51 (16.8) 1.4 [0.9–2.1] 1.3 [0.9–2.0] 
 Men
 
Women
 
 LAE frequency Model 1a Model 2b LAE frequency Model 1a Model 2b 
 N (%) OR [95% CI] OR [95% CI] N (%) OR [95% CI] OR [95% CI] 
Educ 4 58 (12.5) 1.0 1.0 94 (16.8) 1.0 1.0 
Educ 3 41 (17.4) 1.5 [1.0–2.3] 1.2 [0.8–2.0] 66 (18.4) 1.2 [0.8–1.6] 1.0 [0.7–1.4] 
Educ 2 150 (19.0) 1.7 [1.2–2.3] 1.1 [0.7–1.6] 180 (21.4) 1.4 [1.1–1.9] 1.1 [0.7–1.5] 
Educ 1 90 (21.2) 2.2 [1.5–3.3] 1.4 [0.8–2.2] 145 (23.0) 2.3 [1.6–3.1] 1.5 [0.9–2.3] 
High qual. 48 (12.3) 1.0 1.0 37 (16.8) 1.0 1.0 
White col. 55 (14.6) 1.2 [0.8–1.9] 1.0 [0.6–1.6] 76 (15.6) 0.9 [0.6–1.4] 0.8 [0.5–1.3] 
Farmers 10 (8.5) 0.7 [0.3–1.4] 0.4 [0.2–0.8] 6 (5.9) 0.4 [0.2–1.0] 0.2 [0.1–0.4] 
Self-empl. 38 (20.5) 1.8 [1.2–2.9] 1.4 [0.8–2.3] 19 (17.3) 1.2 [0.7–2.3] 0.8 [0.4–1.5] 
Ad. empl. 20 (17.5) 1.5 [0.9–2.7] 1.0 [0.6–1.9] 127 (21.1) 1.3 [0.9–2.0] 0.9 [0.6–1.5] 
Tr. empl. 9 (27.3) 2.7 [1.2–6.1] 1.7 [0.7–4.2] 107 (24.6) 1.7 [1.1–2.6] 0.9 [0.6–1.6] 
Sk. MW 127 (22.9) 2.1 [1.5–3.0] 1.4 [0.9–2.2] 32 (19.6) 1.3 [0.8–2.2] 0.7 [0.4–1.4] 
Unsk MW 32 (22.7) 2.0 [1.2–3.3] 1.1 [0.6–1.9] 52 (28.1) 2.1 [1.3–3.4] 1.0 [0.6–1.8] 
No occ.    29 (32.2) 3.0 [1.7–5.4] 1.4 [0.7–2.7] 
Quintile 5 50 (10.6) 1.0 1.0 62 (13.3) 1.0 1.0 
Quintile 4 45 (13.2) 1.3 [0.8–2.0] 1.2 [0.7–1.8] 62 (14.7) 1.1 [0.8–1.6] 1.1 [0.7–1.6] 
Quintile 3 68 (19.7) 2.0 [1.4–3.0] 1.8 [1.2–2.7] 82 (19.7) 1.6 [1.1–2.3] 1.4 [1.0–2.2] 
Quintile 2 63 (22.2) 2.4 [1.6–3.6] 2.1 [1.4–3.3] 90 (21.8) 1.9 [1.3–2.7] 1.7 [1.1–2.5] 
Quintile 1 71 (27.8) 3.2 [2.2–4.8] 3.0 [1.9–4.7] 138 (37.0) 4.0 [2.9–5.7] 3.8 [2.6–5.6] 
Unknown 42 (19.1) 2.0 [1.3–3.2] 1.8 [1.2–3.0] 51 (16.8) 1.4 [0.9–2.1] 1.3 [0.9–2.0] 

Men and women aged ≥35 years (Abbreviations = see full legends and associated abbreviations in Table 1); Italic = the difference is not statistically significant (95%)/Bold = OR statistically differs from 1 (95%)

a: Univariate logistic regression, adjusted on age only

b: Multivariate logistic regression, adjusted on age, education level, occupation and income

In our study population, 34% of men and women reported chronic disease or health problems, 28% of men and 33% of women reported fair-to-poor self-perceived health and 21% of men and 22% of women reported long-term activity limitations (table 1).

Model 3 shows that current low SES was significantly associated with poor self-perceived health and activity limitations for both men and women. LAE was also linked to poor health, for the three health dimensions, with a more than doubling of the ORs compared with those who did not report LAE (table 3).

Table 3

ORs of poor health associated with education, occupation, income and LAE

 Poor self-perceived health
 
At least one chronic disease
 
Activity limitations
 
 Model 3a Model 4b Model 5b (c) Model 3a Model 4b Model 5b (c) Model 3 (a) Model 4 (b) Model 5 (b) (c) 
 OR [95% CI] OR [95% CI] OR [95% CI] Δ % OR [95% CI] OR [95% CI] OR [95% CI] Δ % OR [95% CI] OR [95% CI] OR [95% CI] Δ % 
Men             
Educ 4 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Educ 3 1.3 [0.9–2.0] 1.0 [0.7–1.6] 1.0 [0.7–1.6]  1.0 [0.7–1.4] 1.0 [0.7–1.4] 1.0 [0.7–1.4]  1.1 [0.7–1.7] 1.0 [0.6–1.5] 0.9 [0.6–1.5]  
Educ 2 1.9 [1.4–2.6] 1.2 [0.8–1.7] 1.2 [0.8–1.8]  0.8 [0.6–1.0] 0.8 [0.6–1.1] 0.8 [0.5–1.1]  1.4 [1.0–1.9] 1.0 [0.7–1.6] 1.0 [0.7–1.6]  
Educ 1 2.5 [1.8–3.5] 1.4 [0.9–2.1] 1.4 [0.9–2.1]  0.9 [0.7–1.3] 0.9 [0.6–1.4] 0.9 [0.6–1.4]  1.8 [1.3–2.6] 1.2 [0.8–2.0] 1.2 [0.8–1.9]  
High qual. 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
White col. 1.4 [0.9–2.0] 1.2 [0.8–1.8] 1.2 [0.8–1.8]  0.9 [0.6–1.2] 1.0 [0.6–1.3] 0.9 [0.7–1.3]  1.3 [0.9–1.9] 1.2 [0.8–1.8] 1.2 [0.8–1.8]  
Farmers 1.3 [0.8–2.1] 0.8 [0.4–1.4] 0.8 [0.5–1.5]  0.6 [0.4–1.0] 0.6 [0.4–1.0] 0.7 [0.4–1.1]  1.4 [0.8–2.3] 0.9 [0.5–1.6] 1.0 [0.6–1.8]  
Self-empl. 1.6 [1.1–2.5] 1.3 [0.8–2.0] 1.2 [0.8–2.0]  0.8 [0.5–1.2] 0.9 [0.6–1.3] 0.8 [0.5–1.3]  1.2 [0.7–1.9] 0.9 [0.6–1.6] 0.9 [0.5–1.5]  
Ad. empl. 2.8 [1.7–4.6] 2.2 [1.3–3.9] 2.2 [1.3–3.9] 1 1.5 [0.9–2.3] 1.6 [1.0–2.7] 1.6 [1.0–2.7] –1 2.0 [1.2–3.5] 1.7 [0.9–3.0] 1.6 [0.9–3.0]  
Tr. empl. 2.1 [0.8–5.2] 1.4 [0.6–3.8] 1.4 [0.5–3.5]  1.0 [0.5–2.4] 1.2 [0.5–2.8] 1.1 [0.5–2.6]  1.6 [0.6–4.4] 1.2 [0.4–3.5] 1.1 [0.4–3.3]  
Sk. MW 2.9 [2.0–4.0] 2.0 [1.3–3.1] 2.0 [1.3–3.0] 6 0.9 [0.7–1.2] 1.0 [0.7–1.5] 1.0 [0.7–1.4]  1.7 [1.2–2.5] 1.4 [0.9–2.1] 1.3 [0.8–2.0]  
Unsk MW 2.9 [1.8–4.6] 1.7 [1.0–2.9] 1.7 [0.9–2.9] 0 0.9 [0.6–1.4] 0.9 [0.5–1.5] 0.9 [0.5–1.5]  2.4 [1.4–3.9] 1.5 [0.9–2.8] 1.5 [0.9–2.8]  
Quintile 5 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Quintile 4 1.3 [0.9–1.9] 1.0 [0.7–1.4] 1.0 [0.7–1.4]  0.9 [0.6–1.2] 0.9 [0.7–1.3] 0.9 [0.6–1.3]  1.2 [0.8–1.8] 1.0 [0.7–1.6] 1.0 [0.7–1.5]  
Quintile 3 1.6 [1.1–2.2] 1.1 [0.7–1.6] 1.0 [0.7–1.5]  0.8 [0.6–1.2] 0.9 [0.6–1.2] 0.8 [0.6–1.2]  1.4 [0.9–2.0] 1.1 [0.7–1.7] 1.0 [0.7–1.6]  
Quintile 2 2.3 [1.6–3.2] 1.6 [1.1–2.3] 1.5 [1.0–2.2] 20 0.9 [0.6–1.3] 1.0 [0.7–1.4] 0.9 [0.6–1.3]  1.7 [1.2–2.5] 1.4 [0.9–2.2] 1.3 [0.8–2.0]  
Quintile 1 3.1 [2.2–4.5] 2.3 [1.5–3.5] 2.0 [1.4–3.1] 19 1.2 [0.9–1.7] 1.4 [0.9–2.0] 1.2 [0.8–1.8]  2.6 [1.8–3.9] 2.2 [1.4–3.4] 1.9 [1.2–2.9] 26 
Unknown 1.7 [1.2–2.6] 1.4 [0.9–2.1] 1.3 [0.9–2.0]  0.8 [0.6–1.2] 0.9 [0.6–1.3] 0.8 [0.6–1.2]  1.4 [1.0–2.2] 1.3 [0.8–2.0] 1.2 [0.8–1.8]  
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 2.3 [1.8–3.0]  2.0 [1.5–2.6]  2.0 [1.6–2.6]  2.0 [1.6–2.6]  2.7 [2.0–3.6]  2.4 [1.8–3.2]  
Quintile 1             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 1.0 [0.6–1.8]  1.0 [0.5–1.8]  2.1 [1.2–3.8]  2.1 [1.1–3.9]  2.1 [1.1–3.9]  2.1 [1.1–4.0]  
Quintile 5             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 1.6 [0.8–3.3]  1.6 [0.8–3.4]  2.3 [1.2–4.3]  2.4 [1.3–4.6]  1.4 [0.6–3.2]  1.5 [0.7–3.4]  
Women             
Educ 4 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Educ 3 1.3 [0.9–1.8] 1.0 [0.7–1.4] 1.0 [0.7–1.4]  0.8 [0.6–1.1] 0.8 [0.6–1.1] 0.8 [0.6–1.1]  1.3 [0.9–1.8] 1.1 [0.7–1.7] 1.1 [0.7–1.7]  
Educ 2 1.8 [1.4–2.4] 1.1 [0.8–1.6] 1.1 [0.8–1.6]  0.8 [0.7–1.0] 0.8 [0.6–1.1] 0.8 [0.6–1.1]  1.5 [1.1–2.0] 1.2 [0.8–1.7] 1.2 [0.8–1.8]  
Educ 1 2.8 [2.1–3.8] 1.5 [1.0–2.2] 1.4 [1.0–2.1] 10 0.7 [0.5–0.9] 0.7 [0.5–1.0] 0.7 [0.5–1.0]  1.7 [1.2–2.4] 1.3 [0.8–2.0] 1.2 [0.8–1.9]  
High qual. 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
White col. 1.0 [0.7–1.5] 0.9 [0.6–1.3] 0.9 [0.6–1.3]  1.0 [0.7–1.4] 1.0 [0.7–1.5] 1.0 [0.7–1.4]  1.0 [0.6–1.5] 0.8 [0.5–1.3] 0.8 [0.5–1.3]  
Farmers 1.3 [0.7–2.2] 0.6 [0.3–1.0] 0.7 [0.4–1.3]  0.4 [0.3–0.7] 0.4 [0.2–0.8] 0.5 [0.3–0.9]  0.9 [0.5–1.6] 0.5 [0.2–0.9] 0.6 [0.3–1.1]  
Self-empl. 1.5 [0.9–2.5] 0.9 [0.5–1.7] 1.0 [0.5–1.7]  0.7 [0.4–1.1] 0.7 [0.4–1.2] 0.7 [0.4–1.2]  1.6 [0.9–2.8] 1.1 [0.6–2.0] 1.1 [0.6–2.0]  
Ad. empl. 1.8 [1.2–2.7] 1.3 [0.8–2.0] 1.3 [0.8–2.0]  0.9 [0.6–1.2] 1.0 [0.7–1.5] 1.0 [0.7–1.5]  1.3 [0.8–2.0] 0.9 [0.6–1.5] 0.9 [0.5–1.5]  
Tr. empl. 2.5 [1.7–3.8] 1.4 [0.9–2.3] 1.4 [0.9–2.3]  0.9 [0.6–1.2] 1.0 [0.6–1.5] 1.0 [0.6–1.5]  1.7 [1.1–2.6] 1.1 [0.6–1.8] 1.1 [0.6–1.8]  
Sk. MW 2.3 [1.4–3.8] 1.3 [0.7–2.2] 1.3 [0.8–2.3]  0.8 [0.5–1.3] 1.0 [0.6–1.6] 1.0 [0.6–1.7]  1.1 [0.6–1.9] 0.7 [0.4–1.3] 0.7 [0.4–1.3]  
Unsk MW 3.4 [2.2–5.5] 1.7 [1.0–3.0] 1.7 [1.0–3.0] 2 1.1 [0.7–1.7] 1.2 [0.7–2.0] 1.2 [0.7–2.0]  1.8 [1.1–2.9] 1.0 [0.6–1.9] 1.0 [0.6–1.9]  
No Occ. 2.3 [1.3–4.1] 1.1 [0.6–2.1] 1.1 [0.6–2.0]  0.8 [0.5–1.4] 0.8 [0.5–1.5] 0.8 [0.5–1.5]  1.8 [1.0–3.2] 1.1 [0.5–2.1] 1.0 [0.5–2.0]  
Quintile 5 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Quintile 4 1.7 [1.2–2.3] 1.4 [1.0–2.0] 1.4 [1.0–2.0] 5 1.3 [0.9–1.7] 1.4 [1.0–1.8] 1.4 [1.0–1.8]  1.8 [1.2–2.6] 1.7 [1.2–2.5] 1.7 [1.1–2.5] 2 
Quintile 3 2.2 [1.6–3.0] 1.6 [1.1–2.3] 1.6 [1.1–2.2] 9 0.7 [0.5–1.0] 0.8 [0.6–1.1] 0.8 [0.6–1.1]  1.7 [1.2–2.5] 1.6 [1.1–2.4] 1.5 [1.0–2.3] 10 
Quintile 2 2.3 [1.7–3.2] 1.7 [1.2–2.4] 1.6 [1.1–2.2] 15 1.0 [0.7–1.3] 1.1 [0.8–1.6] 1.1 [0.8–1.5]  1.9 [1.3–2.7] 1.7 [1.1–2.5] 1.6 [1.1–2.4] 14 
Quintile 1 4.4 [3.1–6.0] 3.3 [2.3–4.7] 2.7 [1.9–3.9] 25 1.3 [1.0–1.8] 1.7 [1.2–2.4] 1.4 [1.0–2.0] 36 2.7 [1.9–3.9] 2.5 [1.7–3.8] 2.0 [1.3–3.1] 32 
Unknown 1.9 [1.3–2.7] 1.6 [1.1–2.3] 1.5 [1.1–2.2] 8 1.1 [0.8–1.4] 1.2 [0.9–1.7] 1.2 [0.8–1.7]  1.9 [1.3–2.8] 1.8 [1.2–2.7] 1.8 [1.2–2.7] 8 
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 2.9 [2.3–3.6]  2.3 [1.9–3.0]  2.0 [1.6–2.5]  1.9 [1.5–2.4]  3.1 [2.4–3.9]  2.8 [2.2–3.5]  
Quintile 1             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 3.4 [2.1–5.6]  3.1 [1.8–5.2]  2.4 [1.5–4.0]  2.3 [1.4–4.0]  4.2 [2.4–7.3]  4.2 [2.4–7.3]  
Quintile 5             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 2.9 [1.6–5.5]  3.1 [1.6–5.9]  1.4 [0.8–2.5]  1.3 [0.7–2.5]  1.6 [0.8–3.5]  1.6 [0.8–3.7]  
 Poor self-perceived health
 
At least one chronic disease
 
Activity limitations
 
 Model 3a Model 4b Model 5b (c) Model 3a Model 4b Model 5b (c) Model 3 (a) Model 4 (b) Model 5 (b) (c) 
 OR [95% CI] OR [95% CI] OR [95% CI] Δ % OR [95% CI] OR [95% CI] OR [95% CI] Δ % OR [95% CI] OR [95% CI] OR [95% CI] Δ % 
Men             
Educ 4 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Educ 3 1.3 [0.9–2.0] 1.0 [0.7–1.6] 1.0 [0.7–1.6]  1.0 [0.7–1.4] 1.0 [0.7–1.4] 1.0 [0.7–1.4]  1.1 [0.7–1.7] 1.0 [0.6–1.5] 0.9 [0.6–1.5]  
Educ 2 1.9 [1.4–2.6] 1.2 [0.8–1.7] 1.2 [0.8–1.8]  0.8 [0.6–1.0] 0.8 [0.6–1.1] 0.8 [0.5–1.1]  1.4 [1.0–1.9] 1.0 [0.7–1.6] 1.0 [0.7–1.6]  
Educ 1 2.5 [1.8–3.5] 1.4 [0.9–2.1] 1.4 [0.9–2.1]  0.9 [0.7–1.3] 0.9 [0.6–1.4] 0.9 [0.6–1.4]  1.8 [1.3–2.6] 1.2 [0.8–2.0] 1.2 [0.8–1.9]  
High qual. 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
White col. 1.4 [0.9–2.0] 1.2 [0.8–1.8] 1.2 [0.8–1.8]  0.9 [0.6–1.2] 1.0 [0.6–1.3] 0.9 [0.7–1.3]  1.3 [0.9–1.9] 1.2 [0.8–1.8] 1.2 [0.8–1.8]  
Farmers 1.3 [0.8–2.1] 0.8 [0.4–1.4] 0.8 [0.5–1.5]  0.6 [0.4–1.0] 0.6 [0.4–1.0] 0.7 [0.4–1.1]  1.4 [0.8–2.3] 0.9 [0.5–1.6] 1.0 [0.6–1.8]  
Self-empl. 1.6 [1.1–2.5] 1.3 [0.8–2.0] 1.2 [0.8–2.0]  0.8 [0.5–1.2] 0.9 [0.6–1.3] 0.8 [0.5–1.3]  1.2 [0.7–1.9] 0.9 [0.6–1.6] 0.9 [0.5–1.5]  
Ad. empl. 2.8 [1.7–4.6] 2.2 [1.3–3.9] 2.2 [1.3–3.9] 1 1.5 [0.9–2.3] 1.6 [1.0–2.7] 1.6 [1.0–2.7] –1 2.0 [1.2–3.5] 1.7 [0.9–3.0] 1.6 [0.9–3.0]  
Tr. empl. 2.1 [0.8–5.2] 1.4 [0.6–3.8] 1.4 [0.5–3.5]  1.0 [0.5–2.4] 1.2 [0.5–2.8] 1.1 [0.5–2.6]  1.6 [0.6–4.4] 1.2 [0.4–3.5] 1.1 [0.4–3.3]  
Sk. MW 2.9 [2.0–4.0] 2.0 [1.3–3.1] 2.0 [1.3–3.0] 6 0.9 [0.7–1.2] 1.0 [0.7–1.5] 1.0 [0.7–1.4]  1.7 [1.2–2.5] 1.4 [0.9–2.1] 1.3 [0.8–2.0]  
Unsk MW 2.9 [1.8–4.6] 1.7 [1.0–2.9] 1.7 [0.9–2.9] 0 0.9 [0.6–1.4] 0.9 [0.5–1.5] 0.9 [0.5–1.5]  2.4 [1.4–3.9] 1.5 [0.9–2.8] 1.5 [0.9–2.8]  
Quintile 5 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Quintile 4 1.3 [0.9–1.9] 1.0 [0.7–1.4] 1.0 [0.7–1.4]  0.9 [0.6–1.2] 0.9 [0.7–1.3] 0.9 [0.6–1.3]  1.2 [0.8–1.8] 1.0 [0.7–1.6] 1.0 [0.7–1.5]  
Quintile 3 1.6 [1.1–2.2] 1.1 [0.7–1.6] 1.0 [0.7–1.5]  0.8 [0.6–1.2] 0.9 [0.6–1.2] 0.8 [0.6–1.2]  1.4 [0.9–2.0] 1.1 [0.7–1.7] 1.0 [0.7–1.6]  
Quintile 2 2.3 [1.6–3.2] 1.6 [1.1–2.3] 1.5 [1.0–2.2] 20 0.9 [0.6–1.3] 1.0 [0.7–1.4] 0.9 [0.6–1.3]  1.7 [1.2–2.5] 1.4 [0.9–2.2] 1.3 [0.8–2.0]  
Quintile 1 3.1 [2.2–4.5] 2.3 [1.5–3.5] 2.0 [1.4–3.1] 19 1.2 [0.9–1.7] 1.4 [0.9–2.0] 1.2 [0.8–1.8]  2.6 [1.8–3.9] 2.2 [1.4–3.4] 1.9 [1.2–2.9] 26 
Unknown 1.7 [1.2–2.6] 1.4 [0.9–2.1] 1.3 [0.9–2.0]  0.8 [0.6–1.2] 0.9 [0.6–1.3] 0.8 [0.6–1.2]  1.4 [1.0–2.2] 1.3 [0.8–2.0] 1.2 [0.8–1.8]  
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 2.3 [1.8–3.0]  2.0 [1.5–2.6]  2.0 [1.6–2.6]  2.0 [1.6–2.6]  2.7 [2.0–3.6]  2.4 [1.8–3.2]  
Quintile 1             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 1.0 [0.6–1.8]  1.0 [0.5–1.8]  2.1 [1.2–3.8]  2.1 [1.1–3.9]  2.1 [1.1–3.9]  2.1 [1.1–4.0]  
Quintile 5             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 1.6 [0.8–3.3]  1.6 [0.8–3.4]  2.3 [1.2–4.3]  2.4 [1.3–4.6]  1.4 [0.6–3.2]  1.5 [0.7–3.4]  
Women             
Educ 4 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Educ 3 1.3 [0.9–1.8] 1.0 [0.7–1.4] 1.0 [0.7–1.4]  0.8 [0.6–1.1] 0.8 [0.6–1.1] 0.8 [0.6–1.1]  1.3 [0.9–1.8] 1.1 [0.7–1.7] 1.1 [0.7–1.7]  
Educ 2 1.8 [1.4–2.4] 1.1 [0.8–1.6] 1.1 [0.8–1.6]  0.8 [0.7–1.0] 0.8 [0.6–1.1] 0.8 [0.6–1.1]  1.5 [1.1–2.0] 1.2 [0.8–1.7] 1.2 [0.8–1.8]  
Educ 1 2.8 [2.1–3.8] 1.5 [1.0–2.2] 1.4 [1.0–2.1] 10 0.7 [0.5–0.9] 0.7 [0.5–1.0] 0.7 [0.5–1.0]  1.7 [1.2–2.4] 1.3 [0.8–2.0] 1.2 [0.8–1.9]  
High qual. 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
White col. 1.0 [0.7–1.5] 0.9 [0.6–1.3] 0.9 [0.6–1.3]  1.0 [0.7–1.4] 1.0 [0.7–1.5] 1.0 [0.7–1.4]  1.0 [0.6–1.5] 0.8 [0.5–1.3] 0.8 [0.5–1.3]  
Farmers 1.3 [0.7–2.2] 0.6 [0.3–1.0] 0.7 [0.4–1.3]  0.4 [0.3–0.7] 0.4 [0.2–0.8] 0.5 [0.3–0.9]  0.9 [0.5–1.6] 0.5 [0.2–0.9] 0.6 [0.3–1.1]  
Self-empl. 1.5 [0.9–2.5] 0.9 [0.5–1.7] 1.0 [0.5–1.7]  0.7 [0.4–1.1] 0.7 [0.4–1.2] 0.7 [0.4–1.2]  1.6 [0.9–2.8] 1.1 [0.6–2.0] 1.1 [0.6–2.0]  
Ad. empl. 1.8 [1.2–2.7] 1.3 [0.8–2.0] 1.3 [0.8–2.0]  0.9 [0.6–1.2] 1.0 [0.7–1.5] 1.0 [0.7–1.5]  1.3 [0.8–2.0] 0.9 [0.6–1.5] 0.9 [0.5–1.5]  
Tr. empl. 2.5 [1.7–3.8] 1.4 [0.9–2.3] 1.4 [0.9–2.3]  0.9 [0.6–1.2] 1.0 [0.6–1.5] 1.0 [0.6–1.5]  1.7 [1.1–2.6] 1.1 [0.6–1.8] 1.1 [0.6–1.8]  
Sk. MW 2.3 [1.4–3.8] 1.3 [0.7–2.2] 1.3 [0.8–2.3]  0.8 [0.5–1.3] 1.0 [0.6–1.6] 1.0 [0.6–1.7]  1.1 [0.6–1.9] 0.7 [0.4–1.3] 0.7 [0.4–1.3]  
Unsk MW 3.4 [2.2–5.5] 1.7 [1.0–3.0] 1.7 [1.0–3.0] 2 1.1 [0.7–1.7] 1.2 [0.7–2.0] 1.2 [0.7–2.0]  1.8 [1.1–2.9] 1.0 [0.6–1.9] 1.0 [0.6–1.9]  
No Occ. 2.3 [1.3–4.1] 1.1 [0.6–2.1] 1.1 [0.6–2.0]  0.8 [0.5–1.4] 0.8 [0.5–1.5] 0.8 [0.5–1.5]  1.8 [1.0–3.2] 1.1 [0.5–2.1] 1.0 [0.5–2.0]  
Quintile 5 1.0 1.0 1.0  1.0 1.0 1.0  1.0 1.0 1.0  
Quintile 4 1.7 [1.2–2.3] 1.4 [1.0–2.0] 1.4 [1.0–2.0] 5 1.3 [0.9–1.7] 1.4 [1.0–1.8] 1.4 [1.0–1.8]  1.8 [1.2–2.6] 1.7 [1.2–2.5] 1.7 [1.1–2.5] 2 
Quintile 3 2.2 [1.6–3.0] 1.6 [1.1–2.3] 1.6 [1.1–2.2] 9 0.7 [0.5–1.0] 0.8 [0.6–1.1] 0.8 [0.6–1.1]  1.7 [1.2–2.5] 1.6 [1.1–2.4] 1.5 [1.0–2.3] 10 
Quintile 2 2.3 [1.7–3.2] 1.7 [1.2–2.4] 1.6 [1.1–2.2] 15 1.0 [0.7–1.3] 1.1 [0.8–1.6] 1.1 [0.8–1.5]  1.9 [1.3–2.7] 1.7 [1.1–2.5] 1.6 [1.1–2.4] 14 
Quintile 1 4.4 [3.1–6.0] 3.3 [2.3–4.7] 2.7 [1.9–3.9] 25 1.3 [1.0–1.8] 1.7 [1.2–2.4] 1.4 [1.0–2.0] 36 2.7 [1.9–3.9] 2.5 [1.7–3.8] 2.0 [1.3–3.1] 32 
Unknown 1.9 [1.3–2.7] 1.6 [1.1–2.3] 1.5 [1.1–2.2] 8 1.1 [0.8–1.4] 1.2 [0.9–1.7] 1.2 [0.8–1.7]  1.9 [1.3–2.8] 1.8 [1.2–2.7] 1.8 [1.2–2.7] 8 
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 2.9 [2.3–3.6]  2.3 [1.9–3.0]  2.0 [1.6–2.5]  1.9 [1.5–2.4]  3.1 [2.4–3.9]  2.8 [2.2–3.5]  
Quintile 1             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 3.4 [2.1–5.6]  3.1 [1.8–5.2]  2.4 [1.5–4.0]  2.3 [1.4–4.0]  4.2 [2.4–7.3]  4.2 [2.4–7.3]  
Quintile 5             
No LAE 1.0  1.0  1.0  1.0  1.0  1.0  
LEA 2.9 [1.6–5.5]  3.1 [1.6–5.9]  1.4 [0.8–2.5]  1.3 [0.7–2.5]  1.6 [0.8–3.5]  1.6 [0.8–3.7]  

Men and women, aged ≥35 years (Abbreviations = see full legends and associated abbreviations in Table 1); Italic = the difference is not statistically significant (95%)/Bold = OR statistically differs from 1 (95%)

a: Univariate logistic regression, adjusted on age only

b: Multivariate logistic regression, adjusted on age, education level, occupation and income

c: Percentage decrease in ORs significantly higher than 1: Δ = (OR model 4 – OR model 5)/(OR model 4 – 1). Calculations based on ORs accurate to three decimal points

In the multivariate Model 4, only low income and low qualified occupations remained significantly associated with self-perceived health and low income to activity limitation. The excess risks were significant for all the income quintiles for women. Including LAE, in Model 5, induces only a slight attenuation of the occupational and income group’s OR. LAE was still strongly associated with deteriorated health for both sexes and for each health indicator while controlling for other SES.

Finally, focusing on the lowest income group, the association between LAE and poor health status remains significant for most health indicators (except self-perceived health among men). In the highest income group, LAE still impacted significantly on poor perceived health among women and chronic diseases in among men (table 3).

The comparison of the OR associated with SES indicators in Models 4 and 5 shows to what extent LAE contributed to the excess risk associated with the SES. It actually explained a small part of the inequalities for male clerical employees and unskilled manual workers (respectively 1 and 6% of the OR for poor self-perceived health), but up to a quarter of the excess risks associated with the lowest income quintile (20% of the OR for poor self-perceived health and 26% of the OR for activity limitations). For women, the contribution of LAE to excess risk in the lowest income group is much larger, explaining up to 25% of the OR for poor self-perceived health, 32% for activity limitations and 36% for chronic diseases.

More detailed analysis (available upon request) showed that each of the three types of LAE contributed to the overall association with health (borderline significant effects for perceived health and chronic disease for men). Moreover, incorporating indicators of current psychological distress led to a slight (not significant) reduction in the link between LAE and health, suggesting this may contribute to the association.

Finally, Models 6 and 7 provided evidence of the long-lasting influence of LAE (table 4): after controlling for age and current social status, both LAE occurring during adulthood only and LAE occurring during childhood only were significantly associated with the risk of poor health (except poor self-perceived health for men reporting LAE in adulthood only). The results suggest a cumulative risk associated with having experienced LAE both in childhood and in adulthood.

Table 4

ORs of poor health associated with period of housing difficulties or long period of isolation

 Poor self-perceived health
 
At least one chronic disease
 
Activity limitations
 
 Model 6a Model 7b Model 6a Model 7b Model 6a Model 7b 
 OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] 
Men       
LAE never 1.0 1.0 1.0 1.0 1.0 1.0 
    in childhood only 2.4 [1.5–3.8] 2.3 [1.5–3.7] 1.9 [1.2–3.0] 2.0 [1.3–3.1] 2.4 [1.5–3.9] 2.4 [1.5–3.9] 
    in adulthood only 1.6 [1.1–2.5] 1.4 [0.9–2.2] 1.7 [1.2–2.6] 1.7 [1.1–2.6] 2.3 [1.5–3.6] 2.1 [1.4–3.3] 
    in childhood and adulthood 16 [5.1–53] 15 [4.5–51] 6.1 [2.2–17] 6.0 [2.1–17] 8.1 [3.0–22] 6.7 [2.4–19] 
Women       
LAE never 1.0 1.0 1.0 1.0 1.0 1.0 
    in childhood only 2.4 [1.6–3.5] 2.3 [1.6–3.4] 2.0 [1.4–2.9] 1.9 [1.3–2.8] 2.1 [1.4–3.1] 2.0 [1.3–3.0] 
    in adulthood only 2.2 [1.5–3.0] 1.7 [1.2–2.5] 1.9 [1.3–2.6] 1.8 [1.3–2.6] 3.4 [2.4–4.8] 3.0 [2.1–4.3] 
    in childhood and adulthood 7.1 [3.3–15] 6.1 [2.8–13] 3.4 [1.7–6.8] 3.3 [1.6–6.9] 6.1 [3.0–13] 5.9 [2.9–12] 
 Poor self-perceived health
 
At least one chronic disease
 
Activity limitations
 
 Model 6a Model 7b Model 6a Model 7b Model 6a Model 7b 
 OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] 
Men       
LAE never 1.0 1.0 1.0 1.0 1.0 1.0 
    in childhood only 2.4 [1.5–3.8] 2.3 [1.5–3.7] 1.9 [1.2–3.0] 2.0 [1.3–3.1] 2.4 [1.5–3.9] 2.4 [1.5–3.9] 
    in adulthood only 1.6 [1.1–2.5] 1.4 [0.9–2.2] 1.7 [1.2–2.6] 1.7 [1.1–2.6] 2.3 [1.5–3.6] 2.1 [1.4–3.3] 
    in childhood and adulthood 16 [5.1–53] 15 [4.5–51] 6.1 [2.2–17] 6.0 [2.1–17] 8.1 [3.0–22] 6.7 [2.4–19] 
Women       
LAE never 1.0 1.0 1.0 1.0 1.0 1.0 
    in childhood only 2.4 [1.6–3.5] 2.3 [1.6–3.4] 2.0 [1.4–2.9] 1.9 [1.3–2.8] 2.1 [1.4–3.1] 2.0 [1.3–3.0] 
    in adulthood only 2.2 [1.5–3.0] 1.7 [1.2–2.5] 1.9 [1.3–2.6] 1.8 [1.3–2.6] 3.4 [2.4–4.8] 3.0 [2.1–4.3] 
    in childhood and adulthood 7.1 [3.3–15] 6.1 [2.8–13] 3.4 [1.7–6.8] 3.3 [1.6–6.9] 6.1 [3.0–13] 5.9 [2.9–12] 

Men and women, aged ≥35 years; Italic = the difference is not statistically significant (95%)/Bold = OR statistically differs from 1 (95%)

a: Univariate logistic regression, adjusted on age only

b: Multivariate logistic regression, adjusted on age, education level, occupation and income

Discussion

This study shows that 20% of the population over age 35 years reported LAE and provide evidence of a strong and long-lasting association between LAE and deteriorated health for a number of health dimensions. LAE are more frequent in the most disadvantaged groups. They largely contribute to the income gradient in health and also explain a part of the excess risks associated with low qualified occupations. However, we also found >10% LAE in the highest income quintile and they are significantly linked to poor perceived health among female advantaged groups and chronic diseases among male advantaged groups.

Although 20% reporting LAE seems high, it appears to be consistent with estimates from the late 1990s for France.40 Furthermore, this 20% may even be an underestimate due to the survey methodology. Since the ESPS is a household survey which, like most conventional population health surveys, was conducted on a selected population who could be contacted and agreed to participate, it misses those who are currently experiencing adverse circumstances, specifically people not living in a household, and those who did not respond due to social and/or health problems. Second, the study sample excludes persons who did not return the health questionnaire, which may be similarly related to social and/or health problems. However, as we had data from the background questionnaire, we could test the magnitude of bias due to non-response to the health questionnaire by considering that non-respondents were (i) all in poor health status and (ii) all in good health status. Neither of these scenarios significantly changed our conclusions: the effect of LAE on health was slightly increased with the ‘missing in good health’ assumption and decreased with the ‘missing in poor health’ assumption. Our questions may also overestimate LAE related health risks due to their retrospective nature and the possible a posteriori reconstruction effect, with those in poor health and distress being more likely to darken their past experiences. However, our results were not significantly modified by incorporating information on current psychological distress.

Despite these limitations, LAE were found to be strongly associated with poor health status for a number of health dimensions. The higher risk of poor health could be due to various possible determinants: deleterious effect of economic hardship,11,12,23,41 stressful events,11,13,14 job loss,31 disruption or isolation.24,26,28,30 The increased health risks may also be explained by a reverse causation process: long-term health problems may have been responsible for adverse experiences such as job loss,42 decreasing earnings,43,44 isolation, family breakups, etc. However, our results show that LAE occurring during childhood only were significantly associated with the risk of poor health status to the same extent or more so than LAE occurring in adulthood only. The findings support the hypothesis of a causal influence of LAE on health status given that LAE reported only in childhood may be less suspected of reverse causality. Furthermore, the results suggest a cumulative impact of having experienced LAE at several periods of the life course.

Being much more frequent in lower social groups, LAE are a risk factor that contributes to the social health gradient, consistent with previous research.45 With regard to current SES, LAE are strongly associated with low income; first, because current economic hardship is one of the dimensions directly included in our LAE measurement. Secondly, past periods of economic hardship also accounted for in the LAE measurement, are known to be predictors of subsequent economic hardships.44 Given the strong association between LAE and income and the strong association between income and health status, our findings show a major contribution of adverse life events to the income health inequalities, especially among women, for whom they account for about a third of the OR of chronic diseases and activity limitations associated with the lowest income quintile.

Interestingly, the adjustment for SES induced only a slight decrease in the association between LAE and health status. This finding stresses the fact that current SES and LAE do not correspond to the same social health determinants. LAE bring different insights, including past experiences that might not have conducted to permanent hardship but still impact health, independently of current social situation. This study highlights that LAE are an important health determinant above and beyond the current socio-economic situation. It pleads for the inclusion of this life social factor in the set of social dimensions regularly used for monitoring social health inequalities as well as inequalities within social groups. Further analyses on health-care use, health-related behaviours and health trajectories in relation to LAE are also needed to properly design public health policies on equity.

Key points

  • We explore the association between LAE and health status in the French general population and analyse their contribution to social health inequalities.

  • The use of a short set of LAE questions included in a French population health survey in 2004 identifies 20% of adults having an increased risk of poor health.

  • LAE is significantly associated with poor health status, beyond current social status

  • LAE experienced in childhood only are still a determinant of health in adulthood

  • LAE are more frequently reported by low socio-economic groups and contribute to social health inequalities.

References

1
Saurel-Cubizolles
MJ
Chastang
JF
Menvielle
G
, et al.  . 
Social inequalities in mortality by cause among men and women in France
J Epidemiol Community Health
 , 
2009
, vol. 
63
 (pg. 
197
-
202
)
2
Leclerc
A
Chastang
JF
Menvielle
G
Luce
D
Socioeconomic inequalities in premature mortality in France: have they widened in recent decades?
Social science and medicine
 , 
2006
, vol. 
62
 (pg. 
2035
-
45
)
3
Cambois
E
Occupational and educational mortality differentials: magnitude and trends over last decades
Demographic Res
 , 
2004
, vol. 
S2
 (pg. 
278
-
304
)
4
Cambois
E
Robine
J-M
Hayward
M
Social inequalities in disability-free life expectancy in the French male population (1980-1991)
Demography
 , 
2001
, vol. 
38
 (pg. 
513
-
24
)
5
Mackenbach
JP
Stirbu
I
Roskam
AJ
, et al.  . 
Socioeconomic inequalities in health in 22 European countries
N Engl J Med
 , 
2008
, vol. 
358
 (pg. 
2468
-
81
)
6
Leclerc
A
Kaminski
M
Lang
T
Inégaux face à la santé. Du constat à l'action
 , 
2008
Paris
Inserm/La découverte
7
Jusot
F
The shape of the relationship between mortality and income in France
Annales d'Economie et de Statistique (special issue ‘Health - Insurance- Equity’)
 , 
2006
, vol. 
83–84
 (pg. 
89
-
122
)
8
Kuh
DLJ
Ben Sholmo
Y
A life course approach to chronic disease epidemiology
 , 
1997
Oxford
Oxford University Press
9
Davey Smith
G
Hart
C
Watt
G
, et al.  . 
Life time in socio-economic position and mortality: prospective observational study
Br Med J
 , 
1997
, vol. 
314
 (pg. 
547
-
52
)
10
Hayward
MD
Gorman
BK
The long arm of childhood: the influence of early-life social conditions on men's mortality
Demography
 , 
2004
, vol. 
41
 (pg. 
87
-
107
)
11
Kahn
JR
Pearlin
LI
Financial strain over the life course and health among older adults
J Health Soc Behav
 , 
2006
, vol. 
47
 (pg. 
17
-
31
)
12
McDonough
P
Berglund
P
Histories of poverty and self-rated health trajectories
J Health Soc Behav
 , 
2003
, vol. 
44
 (pg. 
198
-
214
)
13
Lantz
PM
House
JS
Mero
RP
Williams
DR
Stress, life events, and socioeconomic disparities in health: results from the Americans' Changing Lives Study
J Health Soc Behav
 , 
2005
, vol. 
46
 (pg. 
274
-
88
)
14
Pearlin
LI
Schieman
S
Fazio
EM
Meersman
SC
Stress, health, and the life course: some conceptual perspectives
J Health Soc Behav
 , 
2005
, vol. 
46
 (pg. 
205
-
19
)
15
Elo
I
Preston
S
Effects of early life conditions on adult mortality: a review
Population Index
 , 
1992
, vol. 
58
 (pg. 
186
-
212
)
16
Blackwell
MD
Hayward
M
Crimmins
E
Does childhood health affect chronic morbidity in later life?
Soc Sci Med
 , 
2001
, vol. 
52
 (pg. 
1269
-
84
)
17
Gilman
S
Kawachi
I
Fitzmaurice
G
Buka
S
Socioeconomic status in childhood and the lifetime risk of major depression
Int J Epidemiol
 , 
2002
, vol. 
31
 (pg. 
359
-
67
)
18
Gliksman
MD
Kawaschi
I
Hunter
D
, et al.  . 
Childhood socioeconomic status and risk of cardiovascular disease in middle aged US women: a prospective study
J Epidemiol Community Health
 , 
1995
, vol. 
49
 (pg. 
10
-
15
)
19
Trannoy
A
Tubeuf
S
Jusot
F
Devaux
M
Inequality in opportunities in health in France: a first pass
Health Econ
 , 
2010
, vol. 
19
 (pg. 
921
-
38
)
20
Khlat
M
Jusot
F
Ville
I
Social origins, early hardship and obesity: a strong association in women, but not in men?
Soc Sci Med
 , 
2009
, vol. 
68
 (pg. 
1692
-
9
)
21
Melchior
M
Lert
F
Martin
M
Ville
I
Socioeconomic position in childhood and in adulthood and functional limitations in midlife: data from a nationally-representative survey of French men and women
Soc Sci Med
 , 
2006
, vol. 
63
 (pg. 
2813
-
24
)
22
Melchior
M
Berkman
LF
Kawachi
I
, et al.  . 
Lifelong socioeconomic trajectory and premature mortality (35-65 years) in France: findings from the GAZEL Cohort Study
J Epidemiol Community Health
 , 
2006
, vol. 
60
 (pg. 
937
-
44
)
23
Stansfeld
S
Head
J
Bartley
M
Fonagy
P
Social position, early deprivation and the development of attachment
Soc Psychiatry Psychiatric Epidemiol
 , 
2008
, vol. 
43
 (pg. 
516
-
26
)
24
Caspi
A
Harrington
H
Moffitt
TE
, et al.  . 
Socially isolated children 20 years later: risk of cardiovascular disease
Arch Pediatr Adolesc Med
 , 
2006
, vol. 
160
 (pg. 
805
-
11
)
25
Moore
DE
Hayward
MD
Occupational careers and mortality of elderly men
Demography
 , 
1990
, vol. 
27
 (pg. 
31
-
53
)
26
Zhang
Z
Hayward
MD
Gender, the marital life course, and cardiovascular disease in late midlife
J Marriage Family
 , 
2006
, vol. 
68
 (pg. 
639
-
57
)
27
Bartley
M
Plewis
I
Accumulated labour market disadvantage and limiting long-term illness: data from the 1971-1991 Office for National Statistics' Longitudinal Study
Int J Epidemiol
 , 
2002
, vol. 
31
 (pg. 
336
-
41
)
28
Hughes
ME
Waite
LJ
Marital biography and health at mid-life
J Health Soc Behav
 , 
2009
, vol. 
50
 (pg. 
344
-
58
)
29
Cambois
E
Careers and mortality: Evidences on how far occupational mobility predicts differentiated risks
Soc Sci Med
 , 
2004
, vol. 
58
 (pg. 
2545
-
58
)
30
Berkman
LF
Melchior
M
Chastang
JF
, et al.  . 
Social integration and mortality: a prospective study of French employees of Electricity of France-Gas of France: the GAZEL Cohort
Am J Epidemiol
 , 
2004
, vol. 
159
 (pg. 
167
-
74
)
31
Saurel-Cubizolles
MJ
Bardot
F
Berneron
B
, et al.  . 
al
Ce
Etat de santé perçu et perte d’emploi
Travail, santé, vieillissement: relations et évolutions colloque des 18 et 19 novembre 1999
 , 
2001
Paris Toulouse
Octarès
(pg. 
53
-
68
)
32
Shaw
M
Dorling
D
Davey Smith
G
Marmot
M
Wilkinson
RG
Poverty, social exclusion, and minorities
Social determinants of health
 , 
1999
Oxford
Oxford University Press
(pg. 
211
-
39
)
33
Kovess
V
Mangin-Lazarus
C
The prevalence of psychiatric disorders and use of care by homeless people in Paris
Soc Psychiatry Psychiartr Epidemiol
 , 
1999
, vol. 
34
 (pg. 
580
-
7
)
34
Parizot
I
Chauvin
P
The access to care of underserved populations: a research among free clinics patients in the Paris area
Revue d’Epidémiologie et de Santé Publique
 , 
2003
, vol. 
51
 (pg. 
577
-
88
)
35
Pascal
J
Abbey-Huguenin
H
Leux
C
, et al.  . 
Social vulnerability and unmet preventive care needs in outpatients of two French public hospitals
Eur J Public Health
 , 
2009
, vol. 
19
 (pg. 
403
-
11
)
36
Allonier
C
Dourgnon
P
Rochereau
T
L'Enquete Santé Protection Sociale 2004, un outil d'analyse pluridisciplinaire de l'acces aux soins, de la couverture maladie et de l'etat de sante des Français
Questions d'Economie de la Sante
 , 
2006
, vol. 
105
 (pg. 
1
-
4
)
37
Cox
B
Van Oyen
H
Cambois
E
, et al.  . 
The reliability of the Minimum European Health Module
Int J Public Health
 , 
2009
, vol. 
54
 (pg. 
55
-
60
)
38
Arber
S
Comparing inequalities in women’s and men’s health: Britain in the 1990s
Soc Sci Med
 , 
1997
, vol. 
44
 (pg. 
773
-
87
)
39
Van den Mheen
H
Stronks
K
Van den Bos
J
Mackenbach
JP
The contribution of childhood environment to the explanation of socioeconomic inequalities in health in adult life: a retrospective study
Soc Sci Med
 , 
1997
, vol. 
44
 (pg. 
13
-
24
)
40
Haut Comité de la Santé Publique
La progression de la précarité en France et ses effets sur la santé
 , 
1998
Paris
La Documentation Française
41
McDonough
P
Duncan
GJ
Williams
D
House
J
Income dynamics and adult mortality in the United States, 1972 through 1989
Am J Public Health
 , 
1997
, vol. 
87
 (pg. 
1476
-
83
)
42
Jusot
F
Khlat
M
Rochereau
T
Sermet
C
Job loss from poor health, smoking and obesity: a national prospective survey in France
J Epidemiol Community Health
 , 
2008
, vol. 
62
 (pg. 
332
-
7
)
43
Chandola
T
Bartley
M
Sacker
A
, et al.  . 
Health selection in the Whitehall II study, UK
Soc Sci Med
 , 
2003
, vol. 
56
 (pg. 
2059
-
72
)
44
Lollivier
S
Verger
D
Trois apports des données longitudinales à l'analyse de la pauvreté
Economie et statistique
 , 
2005
, vol. 
383–5
 (pg. 
245
-
82
)
45
Hatch
S
Dohrenwend
B
Distribution of traumatic and other stressful life events by race/ethnicity, gender, SES and age: a review of the research
Am J Community Psychol
 , 
2007
, vol. 
40
 (pg. 
313
-
32
)

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