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Economic strain and self-rated health among lone and couple mothers in Sweden during the 1990s compared to the 1980s
Health Policy 79 (2006) 253–264
Economic strain and self-rated health among lone and couple mothers in Sweden during the 1990s compared to the 1980s Sara Fritzell ∗ , Bo Burstr¨om Department of Public Health Sciences, Division of Social Medicine, Norrbacka, 171 76 Stockholm, Sweden
Abstract Objectives: Changes on the labour market and in Swedish welfare policy during the 1990s may have affected lone mothers. This study analysed economic strain and self-rated health (SRH) among lone and couple mothers in Sweden in the 1980s and the 1990s. Participants: 22,308, mothers, 19,122 couple and 3186 lone mothers, who responded to the Swedish Survey of Living Conditions in the years 1979–1998. Methods: Exposure for economic strain was defined as having had difficulties to make ends meet in the last year, the outcome measure was less than good SRH. Prevalence rates were calculated and logistic regression analysis was used in the analysis. Adjustments were made for type of mother, age, time period, socio-economic group, income, born in Sweden/foreign born and employment. Results: Prevalence rates of economic strain and less than good SRH increased during the 1990s compared to the 1980s among lone and couple mothers. A polarisation in SRH was noted among lone mothers, with worsening health in poorer groups and improved health among better off groups. Economic strain had a substantial explanatory value for the excess risk of less than good SRH throughout the period studied. The association between economic strain and SRH did not change between lone and couple mothers between the 1980s and the 1990s or in different income groups. Conclusions: The increased prevalence of less than good SRH among sub-groups of lone mothers may in part be due to an increase of financial problems among these groups in Sweden. Economic strain was an important explanatory factor. © 2006 Elsevier Ireland Ltd. All rights reserved. Keywords: Single mother; Financial difficulties; Self-assessed health; Income; Welfare state
1. Introduction
∗
Corresponding author. Tel.: +46 8 737 37 99/70 405 51 07; fax: +46 8 30 73 51. E-mail address: [email protected] (S. Fritzell).
Several studies have shown that health status is closely connected to socio-economic status [1–5]. Lone mothers are often disadvantaged in terms of socioeconomic circumstances [6–8], and as they rely on
0168-8510/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.healthpol.2006.01.004
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only one income, they are more dependent than couple mothers on support systems of the welfare state such as social welfare and housing benefit. Sweden has employed the dual breadwinner model, supported by paid parental leave and public child care [9,10]. Of all children aged 0–17 years in Sweden, 18% live with a lone mother [11]. From an international point of view, poverty rates among lone mothers are lowest in countries like the Scandinavian social–democratic welfare states (in the typology of Esping-Andersen [12]), with high rates of employment among lone mothers and where benefits are universal and transfers generous [13–15]. Comparative studies have shown that lone mothers in Sweden experience better living conditions than in many other countries [14,16]. However, in Sweden and in other countries, there are several health risks associated with lone motherhood. They suffer increased risk of depression, premature death, severe ill-health and injury [17–19]. They are exposed to violence to a larger extent than couple mothers [20], a situation often linked to financial problems [21]. According to Hope et al. [22], the elevated psychological distress that lone mothers are exposed to in comparison to couple mothers may be related to financial hardship. Several studies have pointed out that lone mothers, together with the young and foreign born, are the losers of the welfare state cut-downs and changes implemented on the labour market in Sweden during the last decades [23–25]. Out-of-pocket charges for services and tougher qualification requirements for social benefits were additional trends that coloured the 1990s [21]. The aim of this study is to analyse economic strain and self-rated health among lone and couple mothers in Sweden in the 1980s and 1990s, with respect to: • the association between less than good SRH and economic strain among lone and couple mothers; • change over time in this association; • to what extent economic strain explains higher levels of less than good SRH among lone compared to couple mothers; • whether the association between economic strain and less than good SRH has changed in different income groups over time.
2. Subjects and methods 2.1. Study population Since 1974, Statistics Sweden have conducted yearly cross-sectional face-to-face interviews on the welfare of the population. The Swedish Survey of Living Conditions (ULF) is based on a representative random sample of the population aged 16 years and above (6000 or more individuals annually, non-response rate varying between 14 and 23%). The study population consisted of mothers aged 16–54 years with children up to and including 18 years of age living at home. In this study, data from 1979 to 1998 was used on 22,308 mothers, of whom 19,122 were classified as couple (married or cohabiting) and 3186 as lone mothers. Data on income (added from national tax registers through record linkage using personal identification numbers of survey respondents) were available from 1986 and onwards, including 15,137 couple and 1896 lone mothers. 2.2. Specification and measurement of variables Mothers living with a partner were classified as couple while those living without were classified as lone. The exposure measure studied was economic strain, a measure often used in Swedish studies [26,27]. The question posed was “During the last 12 months, have you had difficulties managing the running expenses for food, rent, bills etc?” (Yes/No). Data on economic strain are available in ULF from 1979 and onwards, with the exception of 1984 and 1985. The outcome measure was less than good self-rated health (SRH), which is considered a good proxy of future morbidity and mortality [28], and has high reliability in measuring health status in populations [29]. The question posed in ULF was “How do you consider your general health? Is it 1) Good, 2) Bad, 3) Something inbetween”. As from 1996 the question was given five response alternatives (very good, good, all right, bad, very bad). All answers less than good were regarded as less than good SRH. The change in response alternatives may have lead to a lower prevalence of less than good SRH [21]. However, this has not been established. A time period variable and the age of the respondent at the time of the interview were used together
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with employment, born in Sweden or foreign born, socio-economic status and income as independent variables. The time period variable (1980s versus 1990s) was constructed to analyse whether there was any overall change in health status between the time periods. We chose periods of time rather than year as a continuous variable since the association between time and SRH is not linear. The age of the respondent (continuous) was included to control for age and to assess the risk of less than good SRH at different ages. To allow changes in SRH status over time periods to vary across age groups an interaction variable between age and time period was included. An interaction variable between time period and economic strain was included to test whether the relative difference in the risk of poor SRH for those experiencing economic strain had changed from the first to the second time period. Further, an interaction variable between time period and motherhood type was included to test whether there was any relative difference in the risk of poor SRH for lone mothers compared to couple mothers between the time periods. An interaction variable between motherhood type and economic strain was also included, to test whether the relative difference in the risk of poor SRH for those experiencing economic strain was different for lone and couple mothers. Finally, an interaction variable between time period × motherhood type × economic strain was included, to test whether the relative difference in the risk of poor SRH for those experiencing economic strain had changed from the first to the second time period among lone and couple mothers. Employment was classified as whether the respondent had employment the week before the interview or not. Country of birth was classified as born in Sweden or foreign born. Socio-economic status was divided into five categories: higher non-manual, lower non-manual, skilled manual, unskilled manual and other according to Statistics Sweden. The classification is based on general education requirements for each occupation and respondents were classified according to their present or most recent occupation [30]. Farmers and self-employed were categorised according to the size of their business and their individual education level. Students and other mothers who could not be classified were categorised as ‘other’.
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For some analyses, income quintiles were constructed (using the whole population), based on deflated and equivalised disposable household income (income after deducting taxes and adding income transfers), supplied by Statistics Sweden from national tax registers, using consumption weights for each household according to Statistics Sweden, thus adjusting for family size and composition. The consumption weights used gave 1.65 for couples, 0.95 for lone and 0.60 for each child under 18 living with their parents. Calculation of income quintiles excluded 16–24-year olds living with their parents, as well as students, selfemployed and farmers as their income may not be representative of their living conditions. By using income quintiles rather than the absolute income level, problems of comparability over time, for instance changes introduced in the tax system1 are avoided. 2.3. Statistical analyses The cross-sectional data from ULF (years 1979–1998) were pooled into two time periods, 1979–1989 and 1990–1998. Statistical analyses were made using SAS Versions 6.12 and 8.1. Prevalences and frequencies were calculated for less than good SRH and economic strain. Calculations of economic strain and SRH in Table 1 were age standardised using the European standard population in order to increase comparability between the groups [32]. To analyse whether the differences in prevalences of background factors between the time periods were significant 95% confidence intervals were calculated. Logistic regression was used to calculate odds ratios (with 95% confidence intervals) for lone mothers to experience less than good SRH compared to couple mothers. The first model was adjusted for potential confounders, described above. The second model was also adjusted for economic strain, to investigate the degree to which economic strain mediates the excess risk of less than good SRH. Age was treated as a continuous variable. The age 20 was set to 0 in the regression models. Likewise, the time period 1979–1989 was set to 0. Logistic regression 1 In 1990–1991, a large tax reform was implemented that changed the rules on what should be taxed as income, at the same time as services not previously taxed were turned into taxable services [23]. Costs for rent also increased quite substantially [31].
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Table 1 Distribution of the study population by background factors 1979–1989 and 1990–1998 by type of mother, with 95% CI and percent change from 1979–1989 to 1990–1998, Sweden Variables
Lone mothers
Couple mothers
1979–1989
1990–1998
Percent
Percent
95% CI
1979–1989
1990–1998
95% CI
Change percent points
95% CI
Change percent points
Percent
Percent 4.0 34.2 43.7 18.1
3.6–4.5 33.1–35.2 42.6–44.8 17.3–19.0
−1.5 −3.0 +1.0 +3.4
10.3–11.4
12.5
11.8–13.2
+1.7
16.7
16.1–17.4
16.5
16.1–17.4
−0.2
+5.8 −5.8 +5.4 −6.2 +0.8
27.8 20.0 16.0 32.8 3.4
27.0–28.7 19.2–20.7 15.4–16.7 32.0–33.7 3.1–3.7
32.1 16.5 18.1 28.2 5.1
31.1–33.2 15.6–17.3 17.3–19.0 27.2–29.3 4.6–5.6
+4.3 −3.5 +2.1 −4.6 +1.7
2.6–4.5 2.9–4.9 8.9–12.1 26.0–30.8 51.4–56.7
−2.2 −0.5 −0.9 −5.6 +9.2
7.5 9.5 19.0 29.4 34.6
6.7–8.5 8.5–10.5 17.7–20.4 27.9–31.0 33.0–36.2
8.0 10.0 18.6 28.1 35.5
7.4–8.6 9.3–10.7 17.7–19.5 27.0–29.1 34.4–36.6
+0.5 +0.5 −0.4 −1.3 +0.9
53.3
50.7–56.0
+12.1
17.6
16.8–18.3
23.0
22.1–24.0
+5.4
28.7
26.3–31.2
+6.6
14.3
13.6–14.9
16.6
15.8–17.4
+2.3
95% CI
Age (years) 16–24 25–34 35–44 45–54
6.7 34.1 41.9 17.3
5.7–8.0 32.0–36.3 39.7–44.2 15.6–19.1
5.1 30.0 42.9 22.0
4.0–6.4 27.6–32.5 40.3–45.6 19.9–24.3
−1.6 −4.1 +1.0 +4.7
5.5 37.2 42.7 14.7
5.1–5.9 36.3–38.0 41.8–43.6 14.0–15.3
Foreign born
15.3
13.7–17.0
17.5
15.6–19.6
+2.2
10.8
Non-employed
15.1
13.5–16.8
26.0
23.8–28.4
+10.9
Socio-economic groupa Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
19.9 21.8 11.5 36.9 9.9
18.1–21.8 20.0–23.8 10.1–13.1 34.7–39.2 8.6–11.3
25.7 16.0 16.9 30.7 10.7
23.4–28.1 14.1–18.1 15.0–19.0 28.3–33.3 9.1–12.4
Income quintilesa,c Highest income Income 80 Income 60 Income 40 Lowest income
5.6 4.3 11.3 34.0 44.9
3.9–7.8 2.9–6.3 8.9–14.3 30.1–38.1 40.8–49.1
3.4 3.8 10.4 28.4 54.1
41.2
38.8–43.7
22.1
20.2–24.0
Experienced economic straind,e Less than good SRHe N (absolute numbers) a b c d e
1830
1356
11608
7514
Only for mothers aged 20 and above. Students and unclassified. Income data are available from 1986 and onwards. Data on economic strain are lacking from 1984 to 1985. Numbers are age standardised.
analyses including income and socio-economic measures were performed for respondents aged 20 years and older, thereby excluding 41 couple mothers and 13 lone mothers from the regression analyses. The explained fraction, which in this study estimates the proportion of excess risk for less than good SRH among lone mothers explained by economic strain, was calculated from the odds ratios using the formula: (OR − 1) − (OR∗ − 1) OR − 1 where OR is the odds ratio before adjusting for the exposure in question (here, economic strain) and OR* is the odds ratio after adjustment [33]. XF =
The multiplicative interactions aimed at studying whether the influence of a certain factor varied between the two time periods. 3. Results 3.1. Socio-demographic distribution, prevalence of less than good SRH and economic strain Both lone and couple mothers reported an increased prevalence in economic strain and less than good SRH from 1979–1989 to 1990–1998 (Table 1). In both time periods, lone mothers in all socio-demographic
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The prevalence of economic strain increased in every group studied from 1979–1989 to 1990–1998, with the exception of lone mothers in the second highest income quintile (Table 3). Among lone mothers, the largest increases in economic strain were reported among unskilled manual workers, higher non-manual workers, and mothers aged 35–44 years. For couple mothers, the largest increase was among the socioeconomic group labelled ‘other’. 3.2. Logistic regression analysis of the association between economic strain and less than good SRH Fig. 1. Less than good SRH, age standardised prevalences for lone and couple mothers 1979–1998, Sweden.
categories reported less than good SRH to a higher extent than couple mothers. Furthermore, this difference in less than good SRH between motherhood types increased during the later time period as SRH of lone mothers deteriorated relatively more (as seen in Table 1 and Fig. 1). Additionally, economic strain was more prevalent among lone mothers in all sociodemographic categories during both time periods, for some categories resulting in very large differences between lone and couple mothers (e.g. income 80, higher non-manual workers; Table 3). The proportion non-employed increased significantly among lone mothers over time, while the proportion of couple mothers who were not employed remained stable. There was an increase in the prevalence of both less than good SRH and economic strain among non-employed mothers (statistically significant for couple mothers for both variables) (Tables 2 and 3). Among lone mothers, the proportion in the lowest income quintile increased significantly, this was not found among couple mothers (Table 1). Furthermore, mothers in the lowest income quintile had higher prevalence of less than good SRH and economic strain in 1990–1998 compared to 1979–1989 (statistically significant for couple mothers for both variables, and for lone mothers for economic strain) (Tables 2 and 3). The prevalence of less than good SRH among lone mothers aged 16–24 years more than doubled during 1990–1998 compared to the first period (Table 2). A decrease in prevalence of less than good SRH was found among lone mothers in the higher income quintiles during the later period.
The age adjusted OR for lone mothers compared to couple to report less than good health was 1.86 (CI 1.70–2.04) (model 0, Table 4). In model 1 we also included background factors and time period. The time period variable was positive and significant (OR 1.17, CI 1.09–1.27), indicating that the risk of less than good SRH had increased in the time period 1990–1998 compared to the first time period. The interaction variable between age and time period suggested that the relative increase in risk of less than good SRH was slightly greater in younger age groups during the later time period (model 3). The OR for the interaction variable between economic strain and time period was 0.80 (CI 0.65–0.99), indicating that the relative difference in less than good SRH between those who had and those who had not experienced economic strain had decreased in 1990–1998 compared to 1979–1989 (compare Table 2). None of the other interaction variables were significant, therefore we cannot conclude that there was any statistically significant difference in the association between economic strain and SRH for lone and couple mothers or that it varied across the time periods. We also tested interaction variables allowing less than good SRH to vary over the levels of employment (employed/not employed) (period × employment, employment × motherhood type and period × motherhood type × employment), these were however not significant (not shown). Stratified analyses for lone and couple mothers showed that economic strain was associated with less than good health for both lone and couple mothers (results not shown). Controlling for economic strain reduced the excess risk among lone mothers from 1.72
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Table 2 Prevalence rates of less than good SRH by background factor 1979–1989 and 1990–1998 by type of mother, with 95% CI and percent change from 1979–1989 to 1990–1998, Sweden Variables
Age (years) 16–24 25–34 35–44 45–54
Lone mothers
Couple mothers
1979–1989
1990–1998
Percent
Percent
16.3 21.2 23.1 27.9
95% CI 10.8–23.8 18.1–24.5 20.2–26.2 23.3–33.1
36.2 25.8 25.3 27.5
95% CI
Change percent points
25.9–48.0 21.8–30.3 21.9–28.9 22.8–32.9
+20.1 +4.6 +2.2 −0.4
1979–1989
1990–1998
Percent
Percent
11.3 10.5 14.3 21.0
95% CI 9.1–14.0 9.6–11.4 13.4–15.3 19.2–23.0
16.6 13.6 15.9 20.3
95% CI
Change percent points
12.8–21.2 12.3–15.0 14.7–17.2 18.3–22.5
+5.3 +3.1 +1.6 −0.7
All (age standardised)
22.1
20.2–24.0
28.7
26.3–31.2
+6.6
14.3
13.6–14.9
16.6
15.8–17.4
+2.3
Swedish born Foreign born
21.0 32.5
19.1–23.1 27.3–38.2
23.3 41.4
20.9–25.9 35.3–47.7
+2.3 +8.9
12.4 24.8
11.7–13.0 22.5–27.3
13.9 30.4
13.1–14.8 27.5–33.4
+1.5 +5.6
Employed Non-employed
20.7 34.8
18.7–22.7 29.4–40.6
20.5 43.3
18.2–23.2 38.3–48.6
−0.2 +8.5
12.6 19.5
11.9–13.2 17.8–21.3
14.1 25.4
13.2–15.0 23.0–27.9
+1.5 +5.9
Socio-economic groupa Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
15.5 23.1 23.0 24.8 28.9
12.0–19.6 19.2–27.5 17.8–29.1 21.7–28.2 22.8–35.9
16.4 22.7 25.4 35.7 30.6
12.9–20.7 17.6–28.7 20.2–31.5 31.2–40.4 23.6–38.5
+0.9 −0.4 +2.4 +10.9 +1.7
9.3 11.8 14.9 17.7 17.2
8.3–10.3 10.5–13.2 13.4–16.6 16.5–18.9 13.8–21.2
10.9 13.7 15.8 21.7 23.4
9.7–12.2 11.9–15.7 14.0–17.8 20.0–23.5 19.4–27.9
+1.6 +1.9 +0.9 +4.0 +6.2
Income quintilesa,c Highest income Income 80 Income 60 Income 40 Lowest income
30.0 56.5 24.6 21.3 25.6
16.7–47.9 36.8–74.4 15.5–36.7 16.0–27.8 20.5–31.5
21.7 23.5 15.0 27.2 28.6
12.3–35.6 14.0–36.8 10.0–21.8 22.9–31.8 25.5–32.0
−8.3 −33.0 −9.6 +5.9 +3.0
8.6 13.4 14.3 12.4 14.6
5.8–12.7 10.1–17.6 11.8–17.2 10.5–14.6 12.7–16.7
11.0 12.2 14.9 16.4 18.3
8.8–13.8 10.0–14.7 13.1–16.8 14.9–18.1 16.8–19.8
+2.4 −1.2 +0.6 +4.0 +3.7
18.0
15.7–20.5
20.7
17.8–23.9
+2.7
12.4
11.7–13.1
13.8
13.0–14.7
+1.4
32.5
28.8–36.5
32.0
28.6–35.5
−0.5
24.3
22.1–26.7
24.4
22.3–26.7
+0.1
Not experienced economic straind Experienced economic straind N (absolute numbers) a b c d
1829
1356
11600
7511
Only for mothers aged 20 and above. Students and unclassified. Income data are available from 1986 and onwards. Data on economic strain are lacking from 1984 to 1985.
(model 1, Table 4) to 1.42 (model 2). Adding economic strain to the model thus explained 42% of the excess risk of less than good SRH for lone mothers compared to couple mothers. 3.3. Logistic regression analysis of the association between income, economic strain and less than good SRH To focus solely on the association between income and SRH and to avoid collinearity we ignored all
background variables but age and family status in the regression model adjusted for income quintiles (both employment status and to some extent country of birth are associated with income level in Sweden) (Table 5). Note that data on income was only available as from 1986. Compared to the top income quintile, mothers in the lower income quintiles showed excess risk of less than good SRH, in a dose–response relation. Adding economic strain to the model decreased the odds ratios for all income quintiles, more so in the
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Table 3 Prevalence rates of economic strain by background factor 1979–1989 (except 1984 and 1985) and 1990–1998 by type of mother, with 95% CI and percent change from 1979–1989 to 1990–1998, Sweden Variables
Age (years) 16–24 25–34 35–44 45–54
Lone mothers
Couple mothers
1979–1989
1990–1998
Percent
Percent
57.1 43.9 31.2 30.6
95% CI 47.6–66.2 39.8–48.2 27.7–34.9 25.3–36.4
65.2 60.4 51.6 35.9
95% CI
Change percent points
53.5–75.4 55.6–65.1 47.5–55.6 30.7–41.5
+8.1 +16.5 +20.4 +5.3
1979–1989
1990–1998
Percent
Percent
34.4 17.4 10.2 8.3
95% CI 30.6–38.5 16.2–18.6 9.3–11.1 7.0–9.9
37.4 26.2 16.8 11.7
95% CI 32.2–43.0 24.6–28.0 15.6–18.1 10.1–13.6
Change percent points +3.0 +8.8 +6.7 +3.4
All (age standardised)
41.2
38.8–43.7
53.3
50.7–56.0
+12.1
17.6
16.8–18.3
23.0
22.1–24.0
+5.4
Swedish born Foreign born
35.8 45.1
33.2–38.5 39.0–51.4
51.1 53.2
48.2–54.0 46.8–59.4
+15.3 +8.1
12.9 23.0
12.2–13.6 20.6–25.7
18.6 29.6
17.6–19.5 26.8–32.6
+5.7 +6.6
Employed Non-employed
33.8 56.4
31.3–36.4 50.0–62.6
46.6 65.4
43.5–49.7 60.3–70.2
+12.8 +9.0
12.1 22.6
11.4–12.8 20.7–24.7
16.6 37.0
15.7–17.5 34.4–39.8
+4.5 +14.4
Socio-economic groupa Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
26.1 30.5 43.9 41.7 50.6
21.6–31.3 25.8–35.7 36.8–51.4 37.7–45.8 43.0–58.3
43.8 43.5 48.3 59.5 64.6
38.7–49.1 37.1–50.2 41.8–54.7 54.7–64.1 56.5–71.9
+17.7 +13.5 +4.4 +17.8 +14.0
9.4 10.0 15.6 17.6 25.7
8.3–10.5 8.8–11.5 13.9–17.5 16.3–19.0 21.3–30.5
13.0 17.8 21.5 23.6 43.8
11.7–14.4 15.8–20.1 19.4–23.8 21.9–25.5 38.9–48.8
+3.6 +7.8 +5.9 +6.0 +18.1
Income quintilesa,c Highest income Income 80 Income 60 Income 40 Lowest income
23.3 47.8 34.4 42.6 47.9
11.8–40.9 29.2–67.0 23.8–47.0 35.7–49.9 41.7–54.2
28.3 35.3 42.9 44.4 59.6
17.3–42.6 23.6–49.0 35.0–51.1 39.5–49.4 56.0–62.1
+5.0 −12.5 +8.5 +1.8 +11.7
4.31 6.9 10.7 14.5 20.6
2.4–7.6 4.6–10.1 8.5–13.3 12.5–16.9 18.4–23.0
8.0 7.1 11.9 20.5 29.8
6.1–10.5 5.5–9.2 10.3–13.7 18.8–22.3 28.1–31.6
+3.4 +0.2 +1.2 +6.0 +9.2
N (absolute numbers) a b c
1536
1356
9590
7504
Only for mothers aged 20 and above. Students and unclassified. Income data available from 1986 and onwards.
lower income quintiles. In this regression model as well, the excess risk for lone mothers declined after adjustment for economic strain, from 1.82 to 1.46. The explained fraction for economic strain in this model was 44%. The interaction terms for income quintile and time period allowed the association between less than good SRH and income quintile to vary between the time periods. None of the interaction terms for income quintiles and time period, nor income quintiles × time period × motherhood type, were significant, indicating that there was no significant difference in the association between income quintile and less than good SRH of mothers across the two time periods.
4. Discussion This study showed an increased prevalence of less than good SRH among both lone and couple mothers in 1990–1998 compared to 1979–1989, in line with previous studies [34]. Furthermore, in support of previous studies [7,21], we found a deterioration of SRH among vulnerable groups such as the youngest, unskilled manual workers and the non-employed. The difference in the prevalence of less than good SRH between employed and non-employed mothers increased during 1990–1998. This could be sign of an increasing health selection into and out of employment. It was more common among lone mothers than couple mothers to experience economic strain, and
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Table 4 Odds ratios with 95% CI of less than good SRH for lone mothers compared to couple mothers, adjusted for age (model 0), age, time period and background factors (model 1), age, time period, background factors and economic strain (model 2) the above and interaction terms (model 3), Sweden, 1979–1998 Variable
Model 0 Odds ratio
Model 1
Model 2
Model 3
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Couple mothers Lone mothers
1.00 1.86
1.70–2.04
1.00 1.72
1.57–1.89
1.00 1.42
1.28–1.58
1.00 1.47
1.22–1.76
Agea
1.03
1.03–1.04
1.04
1.04–1.05
1.05
1.04–1.05
1.05
1.05–1.06
1979–1989 1990–1998
1.00 1.17
1.09–1.27
1.00 1.07
0.99–1.16
1.00 1.50
1.21–1.87
Swedish born Foreign born
1.00 2.10
1.91–2.32
1.00 2.01
1.81–2.23
1.00 2.01
1.81–2.22
Employed Non-employed
1.00 2.06
1.87–2.28
1.00 1.91
1.72–2.12
1.00 1.92
1.73–2.13
Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
1.00 1.48 1.64 2.24 1.31
1.31–1.67 1.45–1.85 2.02–2.48 1.09–1.58
1.00 1.44 1.58 2.11 1.21
1.27–1.64 1.39–1.79 1.90–2.35 1.00–1.47
1.00 1.44 1.57 2.10 1.18
1.27–1.64 1.38–1.78 1.88–2.34 0.98–1.44
1.00 2.03
1.86–2.23
1.00 2.30
1.98–2.67
0.99 0.97 0.80 0.99
0.98–1.00 0.73–1.28 0.65–0.98 0.74–1.32
0.93
0.61–1.42
Not economic strain Economic strainc Period × age Period × motherhood type Period × economic strain Motherhood type × economic strain Period × motherhood type × economic strain Explained fraction for economic strain (XF)
0.42
Background factors: born in Sweden/foreign born, employed/non-employed, socio-economic group. a Age 20 = 0. b Students and unclassified. c Data are lacking from 1984 to 1985 on economic strain.
also to report less than good SRH during both time periods. Logistic regression analyses revealed that the association between economic strain, motherhood type and less than good health had not changed over time; thus, we could not conclude that the association changed over time. This may be due to the fact that “new” groups were affected by economic strain during the recession in the 1990s. Economic strain was more common in nearly all groups of mothers during the 1990s than in the 1980s, with large increases for lone mothers particularly among higher non-manual workers, mothers aged 25–44 years as well as Swedish born mothers. Lone mothers reported worse SRH during
the 1990s but the slight increase in the difference between lone mothers and couple mothers cannot be explained by any change in the association between economic strain and less than good health. Our analyses point towards lack of employment as a possible pathway. Economic strain was indeed more common among lone mothers, and had a strong association with less than good SRH. Lone mothers’ excess risk of less than good SRH in comparison with couple mothers remained even after control for potential confounders. We found no significant difference in interaction terms modelling the association between the different
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261
Table 5 Odds ratios with 95% CI of less than good SRH for lone mothers compared to couple mothers, adjusted for age (model 0), age, time period and income quintile (model 1), age, time period, income quintile and economic strain (model 2) the above and interaction terms (model 3), Sweden, 1986–1998 Variable
Model 0
Model 1
Model 2
Model 3
Odds ratio
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Couple mother Lone mother
1.00 1.96
1.75–2.20
1.00 1.82
1.62–2.04
1.00 1.46
1.29–1.65
1.00 1.92
1.42–2.60
Agea
1.02
1.02–1.03
1.03
1.02–1.04
1.04
1.03–1.05
1.05
1.04–1.07
1.06–1.30
1.00 1.12
1.01–1.24
1.00 1.83
1.01–3.34
1.01–1.73 1.21–1.96 1.41–2.25 1.67–2.64
1.00 1.31 1.50 1.66 1.82
1.00–1.72 1.17–1.91 1.32–2.10 1.45–2.30
1.00 1.84 1.80 1.58 1.88
1.14–2.97 1.16–2.78 1.03–2.41 1.23–2.85
1.00 2.14
1.92–2.39
1.00 2.80
2.18–3.58
0.98 0.95 0.75
0.97–1.00 0.42–2.15 0.47–1.19
0.73 1.24
0.55–0.98 0.72–2.14
1.00 0.63 0.86 1.10 0.98
0.35–1.14 0.50–1.47 0.65–1.85 0.59–1.64
1986–1989 1990–1998
1.00 1.76
Highest income Income 80 Income 60 Income 40 Lowest income
1.00 1.32 1.54 1.78 2.10
Not economic strain Economic strain Period × age Period × motherhood type Motherhood type × economic strain Period × economic strain Period × economic strain × motherhood type Period × highest income Period × income 80 Period × income 60 Period × income 40 Period × lowest income Period × highest income × motherhood type Period × income 80 × motherhood type Period × income 60 × motherhood type Period × income 40 × motherhood type Period × lowest income × motherhood type Explained fraction for economic strain (XF) a
1.00 0.94
0.34–2.62
0.41
0.17–1.02
0.84
0.38–1.86
0.84
0.38–1.84
0.44
Age 20 = 0.
income groups, less than good SRH and motherhood type in the two time periods. Thus, we could not conclude that there was any change in that association between the time periods. SRH among lone mothers in the lowest income quintile had not changed significantly. However, considering that the prevalence of less than good SRH is high in this group, the fact
that the proportion of lone mothers with low income has increased from 44.9 to 54.1% from 1986–1989 to 1990–1998 is worrying. Meanwhile, lone mothers in the higher income groups experienced better SRH during the later time period. This suggests an increased polarisation in SRH between sub-groups of lone mothers.
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The question on SRH was altered in 1996. Since then, the response alternatives which form less than good SRH are three out of five response alternatives compared to the earlier two of three. Less than good SRH therefore constitute a smaller proportion of the possible answers. The change in response alternatives for SRH did not result in largely altered prevalences of less than good SRH (although lowered prevalences were seen for couple mothers in 1996), but figures may still be slightly underestimated after 1996 in comparison with earlier study years. Some limitations must be mentioned. Are people ill because they are poor or are they poor because they are ill? This may of course work both ways. The matter of reverse causation is hard to elucidate from crosssectional studies, since they do not allow for determination of causal associations. Instead of increasing prevalences of financial problems among lone mothers, it could be that more mothers with financial problems become lone, but this does not seem likely. This limitation of cross-sectional data is important to keep in mind when analysing the results of this study. Studies like Benzeval [6], have indicated that there is a causal relationship between low income and ill-health. Still, more longitudinal studies are needed. Since lone mothers are a diverse group, further sub-group analysis may also be needed. The ULF survey does not take into account to what extent the children live with their respective parents. Joint custody is however common in Sweden, of all children of separated parents, 17% live as much with their father as with their mother [11]. This might lead to an underestimation of the association between economic strain and SRH. There is no information on wealth, economic support from other family members (e.g. parents), or the degree of economic strain experienced and length of exposure. Disposable income is however a proxy of the family’s capacity to participate in society. The strength of the measure economic strain in comparison to the other available measure in the data, cash margin, is that it may be considered less hypothetical and shows that the respondent’s resources have been at least temporarily exhausted. Pooling data into two time periods may even out fluctuations within the time periods. However, in this study it reflects timing of policy changes and was necessary for statistical power.
The focus has been on structural factors influencing health, and therefore individual risk factors, such as smoking or social support, were not included in the models.2 Why have financial problems increased in Sweden, and especially among lone mothers? Several factors can be found. From the 1980s to the 1990s, the proportion employed decreased from 81 to 68% among lone mothers, while unchanged among couple mothers (data not shown). Studies have claimed that there is underemployment of lone mothers [25]. Apart from decreasing the opportunities of income from gainful employment, this is problematic since the eligibility for many transfers is connected to participation in the labour market, and those not able to enter the labour market are thus not qualified for this social safety net [35]. Levels in transfers were reduced during the recession, and adjusted upwards when the economy improved at the end of the 1990s, however, not to the initial level [21]. Not only has income declined, expenses have in many cases increased too. The costs of housing increased, and over all, there was an increase in out-of-pocket charges for services during the 1990s. This affected all families, and especially areas important to lone mothers, such as higher fees for childcare, increased patient fees and higher patient costs for pharmaceutical drugs and dental care [21]. Taking expenses for accommodation into account, in 1997 lone mothers’ disposable income (per consumption unit) amounted to 72% of that of couple mothers [36]. Studies have shown that economic problems prevent lone mothers from visiting health care facilities [37], which may cause health problems in the future. There has been a deterioration of the welfare state safety nets. Simultaneously, many lone mothers have had to rely on social welfare assistance due to lack of income from gainful employment. Obviously, economic strain is not the only factor explaining the excess risk of less than good SRH among lone mothers, however, it is a factor amenable to policy interventions. The exposure to financial problems as well as the levels of ill health seems to have increased. While the prevalence of poverty among lone mothers has increased, it has also become harder to rise from poverty [38]. This restricts the possibilities for upward social movement, 2 However, adding smoking to the model did not change the OR considerably.
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and may thereby make poverty more permanent. Not only have the poor become poorer [38], but perhaps the sick also get poorer. Of those with less than good SRH, over 60% of the lone mothers also reported economic strain during the later time period, compared to 47% of the couple mothers. It is therefore important to monitor and analyse how this development proceeds. Further studies are warranted on how mothers with poor health fare on the labour market, in terms of income and with regards to health service utilisation. The excess risk for lone mothers to have less than good SRH remained after adjustment for potential confounders. Our analyses point towards lack of employment as an increasingly important factor for less than good SRH among lone mothers, and we intend to study this further, also in relation to severe morbidity and mortality. To be attached to the labour market may bring with it social support in terms of colleagues and a sense of belonging and value. For lone mothers, this may be of special importance. Factors such as social support, cultural norms and coping skills are likely to play a part in the health of mothers and need to be studied further, especially in a changing society. 5. Conclusions The increased prevalence of less than good SRH among vulnerable groups of lone mothers may partly be a result of an increase in financial problems among lone mothers in Sweden. There are signs of an increased polarisation in health among sub-groups of lone mothers. Economic strain has substantial explanatory value for less than good SRH, and the prevalence of poverty among lone mothers has increased. However, the association between economic strain and SRH did not change between lone and couple mothers between the 1980s and the 1990s or in different income groups. During the 1990s, the Swedish welfare state did not act as a buffer against economic strain and ill-health for lone mothers to the same extent as during the 1980s. Further studies are warranted to monitor the future development. Acknowledgements Stockholm County Council and the Swedish Council for Working Life and Social Research grant 2002-
263
2448 funded this study. We would like to thank Antonio Ponce de Leon for statistical advice. The study was approved by the regional ethics committee in Stockholm, Department 5.
References [1] Lynch JW, Smith GD, Kaplan GA, et al. Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. BMJ 2000;320:1200–4. [2] Subramanian SV, Belli P, Kawachi I. The macroeconomic determinants of health. Annu Rev Public Health 2002;23:287–302. [3] Klat M, Sermet C, Le Pape A. Women’s health in relation with their family and work roles: France in the early. Soc Sci Med 2000;50:1807–25. [4] Diderichsen F, Evans T, Whitehead M. The social basis of disparities in health. In: Evans T, Whitehead M, Diderichsen F, et al., editors. Challenging inequities in health. From ethics to action. New York: Oxford University Press; 2001. p. 12–23. [5] Power C, Stansfeld SA, Matthews S, et al. Childhood and adulthood risk factors for socio-economic differentials in psychological distress: evidence from the 1958 British birth cohort. Soc Sci Med 2000;55:1989–2004. [6] Benzeval M. The self-reported health status of lone parents. Soc Sci Med 1998;46:1337–53. [7] Burstr¨om B, Diderichsen F, Shouls S, et al. Lone mothers in Sweden: trends in health and socioeconomic circumstances, 1979–1995. J Epidemiol Community Health 1999;53:750–6. [8] Lahelma E, Arber S, Kivela K, et al. Multiple roles and health among British and Finnish women: the influence of socioeconomic circumstances. Soc Sci Med 2002;54:727–40. [9] Lindvert J. A world apart, Swedish and Australian gender equality policy. Nordic J Women’s Stud 2002;2:99–107. [10] Leira A. Updating the “gender contract”? Childcare reforms in the Nordic countries in the 1990s. Nordic J Women’s Stud 2002;2:81–9. [11] Children’s time with their parents [Barnens tid med f¨or¨aldrarna]. ¨ Demographic reports 2004:1. Orebro: SCB; 2004. p. 110 [in Swedish]. [12] Esping-Andersen G. The three worlds of welfare capitalism. Cambridge: Polity Press; 1990. p. 248. [13] Ringb¨ack Weitoft G. Lone parenting, socioeconomic conditions and severe ill-health. Longitudinal register-based studies. Ph.D. thesis. Ume˚a: Ume˚a University; 2003. [14] Solera C. Income transfers and support for mothers’ employment: the link to family poverty risks. A comparison between Italy, Sweden and the U.K. Luxembourg Income Study. Working paper 192; 1999. p. 33, http://www.lisproject.org/links/cpconf/solera.pdf [2004-0708]. [15] Curtis L, Phipps S. Social transfers and the health status of mothers in Norway and Canada. Soc Sci Med 2004;58:2499–507. [16] Whitehead M, Burstr¨om B, Diderichsen D. Social policies and the pathways to inequalities in health: a comparative anal-
264
[17]
[18]
[19]
[20]
[21] [22]
[23] [24]
[25]
[26]
[27]
S. Fritzell, B. Burstr¨om / Health Policy 79 (2006) 253–264 ysis of lone mothers in Britain and Sweden. Soc Sci Med 2000;50:255–70. Ringb¨ack Weitoft G, Haglund B, Ros´en M. Mortality among lone mothers in Sweden: a population study. Lancet 2000;355:1215–9. Ringb¨ack Weitoft G, Haglund B, Hjern A. Mortality, severe morbidity and injury among long-term lone mothers in Sweden. Int J Epidemiol 2002;31:573–80. Cairney J, Boyle M, Offord DR, et al. Stress, social support and depression in single and married mothers. Soc Psychiatry Psychiatry Epidemiol 2003;38:442–9. Butterworth P. Lone mothers’ experience of physical and sexual violence: association with psychiatric disorders. Br J Psychiatry 2004;184:21–7. ˚ B¨ackman O, et al. Welfare balance sheet Palme J, Bergmark A, for the. Scand J Public Health Suppl 2003;60(Suppl.):143. Hope S, Power C, Rodgers B. Does financial hardship account for elevated psychological distress in lone mothers? Soc Sci Med 1999;49:1637–49. Social report 2001 [Social rapport 2001]. Stockholm: National Board of Health and Welfare; 2001. p. 243 [in Swedish]. G¨ahler M. Only a mother—single mothers economic living conditions in Sweden in the 1990s [Bara en mor—ensamst˚aende m¨odrars ekonomiska levnadsvillkor i 1990-talets Sverige]. In: ˚ editor. Disadvantage in the Swedish society [Of¨ard Bergmark A, i v¨alf¨arden]. SOU 2001:54. Stockholm: Graphium/Norstedts AB; 2001. p. 15–99 [in Swedish]. Bj¨ornberg U. Single mothers in Sweden: supported workers who mother. In: Duncan S, Edwards R, editors. Single mothers in an international context. London: UCL Press; 1997. p. 241–67. Persson G, Bostr¨om G, Diderichsen F, et al., editors. Health in Sweden—the national public health report 2001. Scand J Public Health Suppl 2001;58(Suppl.):1–240. Vogel J. Financial problems. In: Vogel J, H¨all L, editors. Welfare and inequality from a 20-year perspective 1975–1995 [Ekonomiska problem. I: V¨alf¨ard och oj¨amlikhet i ett 20-˚ars perspektiv 1975–1995]. Stockholm: Statistics Sweden; 1997. p. 179–96 [in Swedish].
[28] Burstr¨om B, Fredlund P. Self rated health: is it a good predictor of subsequent mortality among adults in lower as well as in higher social classes? J Epidemiol Community Health 2001;55:836–40. [29] Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24:218–24. [30] Occupations in Population and Housing Census 1985 (FoB 85) according to Nordic standard occupational classification and Swedish socio-economic classification. Reports on Statistical Co-ordination 1989:5 [Yrkesklassificeringar i FoB 85 enligt Nordisk yrkesklassificiering (NYK) och Socioekonomisk indelning (SEI)]. Stockholm: Statistics Sweden; 1989 [in Swedish]. [31] Flyghed J. Evicted to homelessness? Evictions in Sweden 1982–1994 [Vr¨akt till heml¨oshet? Vr¨akningar i Sverige 1982–1994]. Socialvetenskaplig tidskrift, vol. 2; 1995. p. 99–116 [in Swedish]. [32] Armitage P, Colton T, editors. Encyclopedia of biostatistics, vol. 4. Chichester: John Wiley & Sons; 1998. p. 2525–3502. [33] Rothman KJ, Greenland S. Modern epidemiology. 2nd ed. Philadelphia: Lippincott Raven Publishers; 1998. p. 738. [34] Burstr¨om K, Johannesson M, Diderichsen F. The value of the change in health in Sweden 1980/81 to 1996/97. Health Econ 2003;12:637–54. [35] Salonen T. Marginalisation, risk or remainder? [Marginalisering- risk eller rest?], vol. 3. Framtider. Stockholm: Institute for Future Studies; 1998. p. 10–3 [in Swedish]. [36] Landstr¨om I, Henriksson J. What is left once the housing is paid? [Vad f˚ar vi o¨ ver n¨ar boendet a¨ r betalt?} V¨alf¨ardsbulletinen, vol. 1. Stockholm: Statistics Sweden; 2001. p. 16–7 [in Swedish]. [37] Gardberger Morner C. Independently dependent. Lone mothers’ maintenance strategies [Sj¨alvst¨andigt beroende. Ensamst˚aende mammors f¨ors¨orjningsstrategier]. Thesis. G¨oteborg: Intellecta Docusys; 2003 [in Swedish]. [38] Salonen T. The child poverty in Sweden-annual report 2003 [Barnfattigdomen i Sverige- a˚ rsrapport 2003]. Stockholm: Save the Children, 2003. p. 44, www.rb.se [2004-07-14].
Economic strain and self-rated health among lone and couple mothers in Sweden during the 1990s compared to the 1980s Sara Fritzell ∗ , Bo Burstr¨om Department of Public Health Sciences, Division of Social Medicine, Norrbacka, 171 76 Stockholm, Sweden
Abstract Objectives: Changes on the labour market and in Swedish welfare policy during the 1990s may have affected lone mothers. This study analysed economic strain and self-rated health (SRH) among lone and couple mothers in Sweden in the 1980s and the 1990s. Participants: 22,308, mothers, 19,122 couple and 3186 lone mothers, who responded to the Swedish Survey of Living Conditions in the years 1979–1998. Methods: Exposure for economic strain was defined as having had difficulties to make ends meet in the last year, the outcome measure was less than good SRH. Prevalence rates were calculated and logistic regression analysis was used in the analysis. Adjustments were made for type of mother, age, time period, socio-economic group, income, born in Sweden/foreign born and employment. Results: Prevalence rates of economic strain and less than good SRH increased during the 1990s compared to the 1980s among lone and couple mothers. A polarisation in SRH was noted among lone mothers, with worsening health in poorer groups and improved health among better off groups. Economic strain had a substantial explanatory value for the excess risk of less than good SRH throughout the period studied. The association between economic strain and SRH did not change between lone and couple mothers between the 1980s and the 1990s or in different income groups. Conclusions: The increased prevalence of less than good SRH among sub-groups of lone mothers may in part be due to an increase of financial problems among these groups in Sweden. Economic strain was an important explanatory factor. © 2006 Elsevier Ireland Ltd. All rights reserved. Keywords: Single mother; Financial difficulties; Self-assessed health; Income; Welfare state
1. Introduction
∗
Corresponding author. Tel.: +46 8 737 37 99/70 405 51 07; fax: +46 8 30 73 51. E-mail address: [email protected] (S. Fritzell).
Several studies have shown that health status is closely connected to socio-economic status [1–5]. Lone mothers are often disadvantaged in terms of socioeconomic circumstances [6–8], and as they rely on
0168-8510/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.healthpol.2006.01.004
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only one income, they are more dependent than couple mothers on support systems of the welfare state such as social welfare and housing benefit. Sweden has employed the dual breadwinner model, supported by paid parental leave and public child care [9,10]. Of all children aged 0–17 years in Sweden, 18% live with a lone mother [11]. From an international point of view, poverty rates among lone mothers are lowest in countries like the Scandinavian social–democratic welfare states (in the typology of Esping-Andersen [12]), with high rates of employment among lone mothers and where benefits are universal and transfers generous [13–15]. Comparative studies have shown that lone mothers in Sweden experience better living conditions than in many other countries [14,16]. However, in Sweden and in other countries, there are several health risks associated with lone motherhood. They suffer increased risk of depression, premature death, severe ill-health and injury [17–19]. They are exposed to violence to a larger extent than couple mothers [20], a situation often linked to financial problems [21]. According to Hope et al. [22], the elevated psychological distress that lone mothers are exposed to in comparison to couple mothers may be related to financial hardship. Several studies have pointed out that lone mothers, together with the young and foreign born, are the losers of the welfare state cut-downs and changes implemented on the labour market in Sweden during the last decades [23–25]. Out-of-pocket charges for services and tougher qualification requirements for social benefits were additional trends that coloured the 1990s [21]. The aim of this study is to analyse economic strain and self-rated health among lone and couple mothers in Sweden in the 1980s and 1990s, with respect to: • the association between less than good SRH and economic strain among lone and couple mothers; • change over time in this association; • to what extent economic strain explains higher levels of less than good SRH among lone compared to couple mothers; • whether the association between economic strain and less than good SRH has changed in different income groups over time.
2. Subjects and methods 2.1. Study population Since 1974, Statistics Sweden have conducted yearly cross-sectional face-to-face interviews on the welfare of the population. The Swedish Survey of Living Conditions (ULF) is based on a representative random sample of the population aged 16 years and above (6000 or more individuals annually, non-response rate varying between 14 and 23%). The study population consisted of mothers aged 16–54 years with children up to and including 18 years of age living at home. In this study, data from 1979 to 1998 was used on 22,308 mothers, of whom 19,122 were classified as couple (married or cohabiting) and 3186 as lone mothers. Data on income (added from national tax registers through record linkage using personal identification numbers of survey respondents) were available from 1986 and onwards, including 15,137 couple and 1896 lone mothers. 2.2. Specification and measurement of variables Mothers living with a partner were classified as couple while those living without were classified as lone. The exposure measure studied was economic strain, a measure often used in Swedish studies [26,27]. The question posed was “During the last 12 months, have you had difficulties managing the running expenses for food, rent, bills etc?” (Yes/No). Data on economic strain are available in ULF from 1979 and onwards, with the exception of 1984 and 1985. The outcome measure was less than good self-rated health (SRH), which is considered a good proxy of future morbidity and mortality [28], and has high reliability in measuring health status in populations [29]. The question posed in ULF was “How do you consider your general health? Is it 1) Good, 2) Bad, 3) Something inbetween”. As from 1996 the question was given five response alternatives (very good, good, all right, bad, very bad). All answers less than good were regarded as less than good SRH. The change in response alternatives may have lead to a lower prevalence of less than good SRH [21]. However, this has not been established. A time period variable and the age of the respondent at the time of the interview were used together
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with employment, born in Sweden or foreign born, socio-economic status and income as independent variables. The time period variable (1980s versus 1990s) was constructed to analyse whether there was any overall change in health status between the time periods. We chose periods of time rather than year as a continuous variable since the association between time and SRH is not linear. The age of the respondent (continuous) was included to control for age and to assess the risk of less than good SRH at different ages. To allow changes in SRH status over time periods to vary across age groups an interaction variable between age and time period was included. An interaction variable between time period and economic strain was included to test whether the relative difference in the risk of poor SRH for those experiencing economic strain had changed from the first to the second time period. Further, an interaction variable between time period and motherhood type was included to test whether there was any relative difference in the risk of poor SRH for lone mothers compared to couple mothers between the time periods. An interaction variable between motherhood type and economic strain was also included, to test whether the relative difference in the risk of poor SRH for those experiencing economic strain was different for lone and couple mothers. Finally, an interaction variable between time period × motherhood type × economic strain was included, to test whether the relative difference in the risk of poor SRH for those experiencing economic strain had changed from the first to the second time period among lone and couple mothers. Employment was classified as whether the respondent had employment the week before the interview or not. Country of birth was classified as born in Sweden or foreign born. Socio-economic status was divided into five categories: higher non-manual, lower non-manual, skilled manual, unskilled manual and other according to Statistics Sweden. The classification is based on general education requirements for each occupation and respondents were classified according to their present or most recent occupation [30]. Farmers and self-employed were categorised according to the size of their business and their individual education level. Students and other mothers who could not be classified were categorised as ‘other’.
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For some analyses, income quintiles were constructed (using the whole population), based on deflated and equivalised disposable household income (income after deducting taxes and adding income transfers), supplied by Statistics Sweden from national tax registers, using consumption weights for each household according to Statistics Sweden, thus adjusting for family size and composition. The consumption weights used gave 1.65 for couples, 0.95 for lone and 0.60 for each child under 18 living with their parents. Calculation of income quintiles excluded 16–24-year olds living with their parents, as well as students, selfemployed and farmers as their income may not be representative of their living conditions. By using income quintiles rather than the absolute income level, problems of comparability over time, for instance changes introduced in the tax system1 are avoided. 2.3. Statistical analyses The cross-sectional data from ULF (years 1979–1998) were pooled into two time periods, 1979–1989 and 1990–1998. Statistical analyses were made using SAS Versions 6.12 and 8.1. Prevalences and frequencies were calculated for less than good SRH and economic strain. Calculations of economic strain and SRH in Table 1 were age standardised using the European standard population in order to increase comparability between the groups [32]. To analyse whether the differences in prevalences of background factors between the time periods were significant 95% confidence intervals were calculated. Logistic regression was used to calculate odds ratios (with 95% confidence intervals) for lone mothers to experience less than good SRH compared to couple mothers. The first model was adjusted for potential confounders, described above. The second model was also adjusted for economic strain, to investigate the degree to which economic strain mediates the excess risk of less than good SRH. Age was treated as a continuous variable. The age 20 was set to 0 in the regression models. Likewise, the time period 1979–1989 was set to 0. Logistic regression 1 In 1990–1991, a large tax reform was implemented that changed the rules on what should be taxed as income, at the same time as services not previously taxed were turned into taxable services [23]. Costs for rent also increased quite substantially [31].
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Table 1 Distribution of the study population by background factors 1979–1989 and 1990–1998 by type of mother, with 95% CI and percent change from 1979–1989 to 1990–1998, Sweden Variables
Lone mothers
Couple mothers
1979–1989
1990–1998
Percent
Percent
95% CI
1979–1989
1990–1998
95% CI
Change percent points
95% CI
Change percent points
Percent
Percent 4.0 34.2 43.7 18.1
3.6–4.5 33.1–35.2 42.6–44.8 17.3–19.0
−1.5 −3.0 +1.0 +3.4
10.3–11.4
12.5
11.8–13.2
+1.7
16.7
16.1–17.4
16.5
16.1–17.4
−0.2
+5.8 −5.8 +5.4 −6.2 +0.8
27.8 20.0 16.0 32.8 3.4
27.0–28.7 19.2–20.7 15.4–16.7 32.0–33.7 3.1–3.7
32.1 16.5 18.1 28.2 5.1
31.1–33.2 15.6–17.3 17.3–19.0 27.2–29.3 4.6–5.6
+4.3 −3.5 +2.1 −4.6 +1.7
2.6–4.5 2.9–4.9 8.9–12.1 26.0–30.8 51.4–56.7
−2.2 −0.5 −0.9 −5.6 +9.2
7.5 9.5 19.0 29.4 34.6
6.7–8.5 8.5–10.5 17.7–20.4 27.9–31.0 33.0–36.2
8.0 10.0 18.6 28.1 35.5
7.4–8.6 9.3–10.7 17.7–19.5 27.0–29.1 34.4–36.6
+0.5 +0.5 −0.4 −1.3 +0.9
53.3
50.7–56.0
+12.1
17.6
16.8–18.3
23.0
22.1–24.0
+5.4
28.7
26.3–31.2
+6.6
14.3
13.6–14.9
16.6
15.8–17.4
+2.3
95% CI
Age (years) 16–24 25–34 35–44 45–54
6.7 34.1 41.9 17.3
5.7–8.0 32.0–36.3 39.7–44.2 15.6–19.1
5.1 30.0 42.9 22.0
4.0–6.4 27.6–32.5 40.3–45.6 19.9–24.3
−1.6 −4.1 +1.0 +4.7
5.5 37.2 42.7 14.7
5.1–5.9 36.3–38.0 41.8–43.6 14.0–15.3
Foreign born
15.3
13.7–17.0
17.5
15.6–19.6
+2.2
10.8
Non-employed
15.1
13.5–16.8
26.0
23.8–28.4
+10.9
Socio-economic groupa Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
19.9 21.8 11.5 36.9 9.9
18.1–21.8 20.0–23.8 10.1–13.1 34.7–39.2 8.6–11.3
25.7 16.0 16.9 30.7 10.7
23.4–28.1 14.1–18.1 15.0–19.0 28.3–33.3 9.1–12.4
Income quintilesa,c Highest income Income 80 Income 60 Income 40 Lowest income
5.6 4.3 11.3 34.0 44.9
3.9–7.8 2.9–6.3 8.9–14.3 30.1–38.1 40.8–49.1
3.4 3.8 10.4 28.4 54.1
41.2
38.8–43.7
22.1
20.2–24.0
Experienced economic straind,e Less than good SRHe N (absolute numbers) a b c d e
1830
1356
11608
7514
Only for mothers aged 20 and above. Students and unclassified. Income data are available from 1986 and onwards. Data on economic strain are lacking from 1984 to 1985. Numbers are age standardised.
analyses including income and socio-economic measures were performed for respondents aged 20 years and older, thereby excluding 41 couple mothers and 13 lone mothers from the regression analyses. The explained fraction, which in this study estimates the proportion of excess risk for less than good SRH among lone mothers explained by economic strain, was calculated from the odds ratios using the formula: (OR − 1) − (OR∗ − 1) OR − 1 where OR is the odds ratio before adjusting for the exposure in question (here, economic strain) and OR* is the odds ratio after adjustment [33]. XF =
The multiplicative interactions aimed at studying whether the influence of a certain factor varied between the two time periods. 3. Results 3.1. Socio-demographic distribution, prevalence of less than good SRH and economic strain Both lone and couple mothers reported an increased prevalence in economic strain and less than good SRH from 1979–1989 to 1990–1998 (Table 1). In both time periods, lone mothers in all socio-demographic
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The prevalence of economic strain increased in every group studied from 1979–1989 to 1990–1998, with the exception of lone mothers in the second highest income quintile (Table 3). Among lone mothers, the largest increases in economic strain were reported among unskilled manual workers, higher non-manual workers, and mothers aged 35–44 years. For couple mothers, the largest increase was among the socioeconomic group labelled ‘other’. 3.2. Logistic regression analysis of the association between economic strain and less than good SRH Fig. 1. Less than good SRH, age standardised prevalences for lone and couple mothers 1979–1998, Sweden.
categories reported less than good SRH to a higher extent than couple mothers. Furthermore, this difference in less than good SRH between motherhood types increased during the later time period as SRH of lone mothers deteriorated relatively more (as seen in Table 1 and Fig. 1). Additionally, economic strain was more prevalent among lone mothers in all sociodemographic categories during both time periods, for some categories resulting in very large differences between lone and couple mothers (e.g. income 80, higher non-manual workers; Table 3). The proportion non-employed increased significantly among lone mothers over time, while the proportion of couple mothers who were not employed remained stable. There was an increase in the prevalence of both less than good SRH and economic strain among non-employed mothers (statistically significant for couple mothers for both variables) (Tables 2 and 3). Among lone mothers, the proportion in the lowest income quintile increased significantly, this was not found among couple mothers (Table 1). Furthermore, mothers in the lowest income quintile had higher prevalence of less than good SRH and economic strain in 1990–1998 compared to 1979–1989 (statistically significant for couple mothers for both variables, and for lone mothers for economic strain) (Tables 2 and 3). The prevalence of less than good SRH among lone mothers aged 16–24 years more than doubled during 1990–1998 compared to the first period (Table 2). A decrease in prevalence of less than good SRH was found among lone mothers in the higher income quintiles during the later period.
The age adjusted OR for lone mothers compared to couple to report less than good health was 1.86 (CI 1.70–2.04) (model 0, Table 4). In model 1 we also included background factors and time period. The time period variable was positive and significant (OR 1.17, CI 1.09–1.27), indicating that the risk of less than good SRH had increased in the time period 1990–1998 compared to the first time period. The interaction variable between age and time period suggested that the relative increase in risk of less than good SRH was slightly greater in younger age groups during the later time period (model 3). The OR for the interaction variable between economic strain and time period was 0.80 (CI 0.65–0.99), indicating that the relative difference in less than good SRH between those who had and those who had not experienced economic strain had decreased in 1990–1998 compared to 1979–1989 (compare Table 2). None of the other interaction variables were significant, therefore we cannot conclude that there was any statistically significant difference in the association between economic strain and SRH for lone and couple mothers or that it varied across the time periods. We also tested interaction variables allowing less than good SRH to vary over the levels of employment (employed/not employed) (period × employment, employment × motherhood type and period × motherhood type × employment), these were however not significant (not shown). Stratified analyses for lone and couple mothers showed that economic strain was associated with less than good health for both lone and couple mothers (results not shown). Controlling for economic strain reduced the excess risk among lone mothers from 1.72
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Table 2 Prevalence rates of less than good SRH by background factor 1979–1989 and 1990–1998 by type of mother, with 95% CI and percent change from 1979–1989 to 1990–1998, Sweden Variables
Age (years) 16–24 25–34 35–44 45–54
Lone mothers
Couple mothers
1979–1989
1990–1998
Percent
Percent
16.3 21.2 23.1 27.9
95% CI 10.8–23.8 18.1–24.5 20.2–26.2 23.3–33.1
36.2 25.8 25.3 27.5
95% CI
Change percent points
25.9–48.0 21.8–30.3 21.9–28.9 22.8–32.9
+20.1 +4.6 +2.2 −0.4
1979–1989
1990–1998
Percent
Percent
11.3 10.5 14.3 21.0
95% CI 9.1–14.0 9.6–11.4 13.4–15.3 19.2–23.0
16.6 13.6 15.9 20.3
95% CI
Change percent points
12.8–21.2 12.3–15.0 14.7–17.2 18.3–22.5
+5.3 +3.1 +1.6 −0.7
All (age standardised)
22.1
20.2–24.0
28.7
26.3–31.2
+6.6
14.3
13.6–14.9
16.6
15.8–17.4
+2.3
Swedish born Foreign born
21.0 32.5
19.1–23.1 27.3–38.2
23.3 41.4
20.9–25.9 35.3–47.7
+2.3 +8.9
12.4 24.8
11.7–13.0 22.5–27.3
13.9 30.4
13.1–14.8 27.5–33.4
+1.5 +5.6
Employed Non-employed
20.7 34.8
18.7–22.7 29.4–40.6
20.5 43.3
18.2–23.2 38.3–48.6
−0.2 +8.5
12.6 19.5
11.9–13.2 17.8–21.3
14.1 25.4
13.2–15.0 23.0–27.9
+1.5 +5.9
Socio-economic groupa Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
15.5 23.1 23.0 24.8 28.9
12.0–19.6 19.2–27.5 17.8–29.1 21.7–28.2 22.8–35.9
16.4 22.7 25.4 35.7 30.6
12.9–20.7 17.6–28.7 20.2–31.5 31.2–40.4 23.6–38.5
+0.9 −0.4 +2.4 +10.9 +1.7
9.3 11.8 14.9 17.7 17.2
8.3–10.3 10.5–13.2 13.4–16.6 16.5–18.9 13.8–21.2
10.9 13.7 15.8 21.7 23.4
9.7–12.2 11.9–15.7 14.0–17.8 20.0–23.5 19.4–27.9
+1.6 +1.9 +0.9 +4.0 +6.2
Income quintilesa,c Highest income Income 80 Income 60 Income 40 Lowest income
30.0 56.5 24.6 21.3 25.6
16.7–47.9 36.8–74.4 15.5–36.7 16.0–27.8 20.5–31.5
21.7 23.5 15.0 27.2 28.6
12.3–35.6 14.0–36.8 10.0–21.8 22.9–31.8 25.5–32.0
−8.3 −33.0 −9.6 +5.9 +3.0
8.6 13.4 14.3 12.4 14.6
5.8–12.7 10.1–17.6 11.8–17.2 10.5–14.6 12.7–16.7
11.0 12.2 14.9 16.4 18.3
8.8–13.8 10.0–14.7 13.1–16.8 14.9–18.1 16.8–19.8
+2.4 −1.2 +0.6 +4.0 +3.7
18.0
15.7–20.5
20.7
17.8–23.9
+2.7
12.4
11.7–13.1
13.8
13.0–14.7
+1.4
32.5
28.8–36.5
32.0
28.6–35.5
−0.5
24.3
22.1–26.7
24.4
22.3–26.7
+0.1
Not experienced economic straind Experienced economic straind N (absolute numbers) a b c d
1829
1356
11600
7511
Only for mothers aged 20 and above. Students and unclassified. Income data are available from 1986 and onwards. Data on economic strain are lacking from 1984 to 1985.
(model 1, Table 4) to 1.42 (model 2). Adding economic strain to the model thus explained 42% of the excess risk of less than good SRH for lone mothers compared to couple mothers. 3.3. Logistic regression analysis of the association between income, economic strain and less than good SRH To focus solely on the association between income and SRH and to avoid collinearity we ignored all
background variables but age and family status in the regression model adjusted for income quintiles (both employment status and to some extent country of birth are associated with income level in Sweden) (Table 5). Note that data on income was only available as from 1986. Compared to the top income quintile, mothers in the lower income quintiles showed excess risk of less than good SRH, in a dose–response relation. Adding economic strain to the model decreased the odds ratios for all income quintiles, more so in the
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Table 3 Prevalence rates of economic strain by background factor 1979–1989 (except 1984 and 1985) and 1990–1998 by type of mother, with 95% CI and percent change from 1979–1989 to 1990–1998, Sweden Variables
Age (years) 16–24 25–34 35–44 45–54
Lone mothers
Couple mothers
1979–1989
1990–1998
Percent
Percent
57.1 43.9 31.2 30.6
95% CI 47.6–66.2 39.8–48.2 27.7–34.9 25.3–36.4
65.2 60.4 51.6 35.9
95% CI
Change percent points
53.5–75.4 55.6–65.1 47.5–55.6 30.7–41.5
+8.1 +16.5 +20.4 +5.3
1979–1989
1990–1998
Percent
Percent
34.4 17.4 10.2 8.3
95% CI 30.6–38.5 16.2–18.6 9.3–11.1 7.0–9.9
37.4 26.2 16.8 11.7
95% CI 32.2–43.0 24.6–28.0 15.6–18.1 10.1–13.6
Change percent points +3.0 +8.8 +6.7 +3.4
All (age standardised)
41.2
38.8–43.7
53.3
50.7–56.0
+12.1
17.6
16.8–18.3
23.0
22.1–24.0
+5.4
Swedish born Foreign born
35.8 45.1
33.2–38.5 39.0–51.4
51.1 53.2
48.2–54.0 46.8–59.4
+15.3 +8.1
12.9 23.0
12.2–13.6 20.6–25.7
18.6 29.6
17.6–19.5 26.8–32.6
+5.7 +6.6
Employed Non-employed
33.8 56.4
31.3–36.4 50.0–62.6
46.6 65.4
43.5–49.7 60.3–70.2
+12.8 +9.0
12.1 22.6
11.4–12.8 20.7–24.7
16.6 37.0
15.7–17.5 34.4–39.8
+4.5 +14.4
Socio-economic groupa Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
26.1 30.5 43.9 41.7 50.6
21.6–31.3 25.8–35.7 36.8–51.4 37.7–45.8 43.0–58.3
43.8 43.5 48.3 59.5 64.6
38.7–49.1 37.1–50.2 41.8–54.7 54.7–64.1 56.5–71.9
+17.7 +13.5 +4.4 +17.8 +14.0
9.4 10.0 15.6 17.6 25.7
8.3–10.5 8.8–11.5 13.9–17.5 16.3–19.0 21.3–30.5
13.0 17.8 21.5 23.6 43.8
11.7–14.4 15.8–20.1 19.4–23.8 21.9–25.5 38.9–48.8
+3.6 +7.8 +5.9 +6.0 +18.1
Income quintilesa,c Highest income Income 80 Income 60 Income 40 Lowest income
23.3 47.8 34.4 42.6 47.9
11.8–40.9 29.2–67.0 23.8–47.0 35.7–49.9 41.7–54.2
28.3 35.3 42.9 44.4 59.6
17.3–42.6 23.6–49.0 35.0–51.1 39.5–49.4 56.0–62.1
+5.0 −12.5 +8.5 +1.8 +11.7
4.31 6.9 10.7 14.5 20.6
2.4–7.6 4.6–10.1 8.5–13.3 12.5–16.9 18.4–23.0
8.0 7.1 11.9 20.5 29.8
6.1–10.5 5.5–9.2 10.3–13.7 18.8–22.3 28.1–31.6
+3.4 +0.2 +1.2 +6.0 +9.2
N (absolute numbers) a b c
1536
1356
9590
7504
Only for mothers aged 20 and above. Students and unclassified. Income data available from 1986 and onwards.
lower income quintiles. In this regression model as well, the excess risk for lone mothers declined after adjustment for economic strain, from 1.82 to 1.46. The explained fraction for economic strain in this model was 44%. The interaction terms for income quintile and time period allowed the association between less than good SRH and income quintile to vary between the time periods. None of the interaction terms for income quintiles and time period, nor income quintiles × time period × motherhood type, were significant, indicating that there was no significant difference in the association between income quintile and less than good SRH of mothers across the two time periods.
4. Discussion This study showed an increased prevalence of less than good SRH among both lone and couple mothers in 1990–1998 compared to 1979–1989, in line with previous studies [34]. Furthermore, in support of previous studies [7,21], we found a deterioration of SRH among vulnerable groups such as the youngest, unskilled manual workers and the non-employed. The difference in the prevalence of less than good SRH between employed and non-employed mothers increased during 1990–1998. This could be sign of an increasing health selection into and out of employment. It was more common among lone mothers than couple mothers to experience economic strain, and
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Table 4 Odds ratios with 95% CI of less than good SRH for lone mothers compared to couple mothers, adjusted for age (model 0), age, time period and background factors (model 1), age, time period, background factors and economic strain (model 2) the above and interaction terms (model 3), Sweden, 1979–1998 Variable
Model 0 Odds ratio
Model 1
Model 2
Model 3
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Couple mothers Lone mothers
1.00 1.86
1.70–2.04
1.00 1.72
1.57–1.89
1.00 1.42
1.28–1.58
1.00 1.47
1.22–1.76
Agea
1.03
1.03–1.04
1.04
1.04–1.05
1.05
1.04–1.05
1.05
1.05–1.06
1979–1989 1990–1998
1.00 1.17
1.09–1.27
1.00 1.07
0.99–1.16
1.00 1.50
1.21–1.87
Swedish born Foreign born
1.00 2.10
1.91–2.32
1.00 2.01
1.81–2.23
1.00 2.01
1.81–2.22
Employed Non-employed
1.00 2.06
1.87–2.28
1.00 1.91
1.72–2.12
1.00 1.92
1.73–2.13
Higher non-manual Lower non-manual Skilled manual Unskilled manual Otherb
1.00 1.48 1.64 2.24 1.31
1.31–1.67 1.45–1.85 2.02–2.48 1.09–1.58
1.00 1.44 1.58 2.11 1.21
1.27–1.64 1.39–1.79 1.90–2.35 1.00–1.47
1.00 1.44 1.57 2.10 1.18
1.27–1.64 1.38–1.78 1.88–2.34 0.98–1.44
1.00 2.03
1.86–2.23
1.00 2.30
1.98–2.67
0.99 0.97 0.80 0.99
0.98–1.00 0.73–1.28 0.65–0.98 0.74–1.32
0.93
0.61–1.42
Not economic strain Economic strainc Period × age Period × motherhood type Period × economic strain Motherhood type × economic strain Period × motherhood type × economic strain Explained fraction for economic strain (XF)
0.42
Background factors: born in Sweden/foreign born, employed/non-employed, socio-economic group. a Age 20 = 0. b Students and unclassified. c Data are lacking from 1984 to 1985 on economic strain.
also to report less than good SRH during both time periods. Logistic regression analyses revealed that the association between economic strain, motherhood type and less than good health had not changed over time; thus, we could not conclude that the association changed over time. This may be due to the fact that “new” groups were affected by economic strain during the recession in the 1990s. Economic strain was more common in nearly all groups of mothers during the 1990s than in the 1980s, with large increases for lone mothers particularly among higher non-manual workers, mothers aged 25–44 years as well as Swedish born mothers. Lone mothers reported worse SRH during
the 1990s but the slight increase in the difference between lone mothers and couple mothers cannot be explained by any change in the association between economic strain and less than good health. Our analyses point towards lack of employment as a possible pathway. Economic strain was indeed more common among lone mothers, and had a strong association with less than good SRH. Lone mothers’ excess risk of less than good SRH in comparison with couple mothers remained even after control for potential confounders. We found no significant difference in interaction terms modelling the association between the different
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Table 5 Odds ratios with 95% CI of less than good SRH for lone mothers compared to couple mothers, adjusted for age (model 0), age, time period and income quintile (model 1), age, time period, income quintile and economic strain (model 2) the above and interaction terms (model 3), Sweden, 1986–1998 Variable
Model 0
Model 1
Model 2
Model 3
Odds ratio
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Odds ratio
95% CI
Couple mother Lone mother
1.00 1.96
1.75–2.20
1.00 1.82
1.62–2.04
1.00 1.46
1.29–1.65
1.00 1.92
1.42–2.60
Agea
1.02
1.02–1.03
1.03
1.02–1.04
1.04
1.03–1.05
1.05
1.04–1.07
1.06–1.30
1.00 1.12
1.01–1.24
1.00 1.83
1.01–3.34
1.01–1.73 1.21–1.96 1.41–2.25 1.67–2.64
1.00 1.31 1.50 1.66 1.82
1.00–1.72 1.17–1.91 1.32–2.10 1.45–2.30
1.00 1.84 1.80 1.58 1.88
1.14–2.97 1.16–2.78 1.03–2.41 1.23–2.85
1.00 2.14
1.92–2.39
1.00 2.80
2.18–3.58
0.98 0.95 0.75
0.97–1.00 0.42–2.15 0.47–1.19
0.73 1.24
0.55–0.98 0.72–2.14
1.00 0.63 0.86 1.10 0.98
0.35–1.14 0.50–1.47 0.65–1.85 0.59–1.64
1986–1989 1990–1998
1.00 1.76
Highest income Income 80 Income 60 Income 40 Lowest income
1.00 1.32 1.54 1.78 2.10
Not economic strain Economic strain Period × age Period × motherhood type Motherhood type × economic strain Period × economic strain Period × economic strain × motherhood type Period × highest income Period × income 80 Period × income 60 Period × income 40 Period × lowest income Period × highest income × motherhood type Period × income 80 × motherhood type Period × income 60 × motherhood type Period × income 40 × motherhood type Period × lowest income × motherhood type Explained fraction for economic strain (XF) a
1.00 0.94
0.34–2.62
0.41
0.17–1.02
0.84
0.38–1.86
0.84
0.38–1.84
0.44
Age 20 = 0.
income groups, less than good SRH and motherhood type in the two time periods. Thus, we could not conclude that there was any change in that association between the time periods. SRH among lone mothers in the lowest income quintile had not changed significantly. However, considering that the prevalence of less than good SRH is high in this group, the fact
that the proportion of lone mothers with low income has increased from 44.9 to 54.1% from 1986–1989 to 1990–1998 is worrying. Meanwhile, lone mothers in the higher income groups experienced better SRH during the later time period. This suggests an increased polarisation in SRH between sub-groups of lone mothers.
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The question on SRH was altered in 1996. Since then, the response alternatives which form less than good SRH are three out of five response alternatives compared to the earlier two of three. Less than good SRH therefore constitute a smaller proportion of the possible answers. The change in response alternatives for SRH did not result in largely altered prevalences of less than good SRH (although lowered prevalences were seen for couple mothers in 1996), but figures may still be slightly underestimated after 1996 in comparison with earlier study years. Some limitations must be mentioned. Are people ill because they are poor or are they poor because they are ill? This may of course work both ways. The matter of reverse causation is hard to elucidate from crosssectional studies, since they do not allow for determination of causal associations. Instead of increasing prevalences of financial problems among lone mothers, it could be that more mothers with financial problems become lone, but this does not seem likely. This limitation of cross-sectional data is important to keep in mind when analysing the results of this study. Studies like Benzeval [6], have indicated that there is a causal relationship between low income and ill-health. Still, more longitudinal studies are needed. Since lone mothers are a diverse group, further sub-group analysis may also be needed. The ULF survey does not take into account to what extent the children live with their respective parents. Joint custody is however common in Sweden, of all children of separated parents, 17% live as much with their father as with their mother [11]. This might lead to an underestimation of the association between economic strain and SRH. There is no information on wealth, economic support from other family members (e.g. parents), or the degree of economic strain experienced and length of exposure. Disposable income is however a proxy of the family’s capacity to participate in society. The strength of the measure economic strain in comparison to the other available measure in the data, cash margin, is that it may be considered less hypothetical and shows that the respondent’s resources have been at least temporarily exhausted. Pooling data into two time periods may even out fluctuations within the time periods. However, in this study it reflects timing of policy changes and was necessary for statistical power.
The focus has been on structural factors influencing health, and therefore individual risk factors, such as smoking or social support, were not included in the models.2 Why have financial problems increased in Sweden, and especially among lone mothers? Several factors can be found. From the 1980s to the 1990s, the proportion employed decreased from 81 to 68% among lone mothers, while unchanged among couple mothers (data not shown). Studies have claimed that there is underemployment of lone mothers [25]. Apart from decreasing the opportunities of income from gainful employment, this is problematic since the eligibility for many transfers is connected to participation in the labour market, and those not able to enter the labour market are thus not qualified for this social safety net [35]. Levels in transfers were reduced during the recession, and adjusted upwards when the economy improved at the end of the 1990s, however, not to the initial level [21]. Not only has income declined, expenses have in many cases increased too. The costs of housing increased, and over all, there was an increase in out-of-pocket charges for services during the 1990s. This affected all families, and especially areas important to lone mothers, such as higher fees for childcare, increased patient fees and higher patient costs for pharmaceutical drugs and dental care [21]. Taking expenses for accommodation into account, in 1997 lone mothers’ disposable income (per consumption unit) amounted to 72% of that of couple mothers [36]. Studies have shown that economic problems prevent lone mothers from visiting health care facilities [37], which may cause health problems in the future. There has been a deterioration of the welfare state safety nets. Simultaneously, many lone mothers have had to rely on social welfare assistance due to lack of income from gainful employment. Obviously, economic strain is not the only factor explaining the excess risk of less than good SRH among lone mothers, however, it is a factor amenable to policy interventions. The exposure to financial problems as well as the levels of ill health seems to have increased. While the prevalence of poverty among lone mothers has increased, it has also become harder to rise from poverty [38]. This restricts the possibilities for upward social movement, 2 However, adding smoking to the model did not change the OR considerably.
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and may thereby make poverty more permanent. Not only have the poor become poorer [38], but perhaps the sick also get poorer. Of those with less than good SRH, over 60% of the lone mothers also reported economic strain during the later time period, compared to 47% of the couple mothers. It is therefore important to monitor and analyse how this development proceeds. Further studies are warranted on how mothers with poor health fare on the labour market, in terms of income and with regards to health service utilisation. The excess risk for lone mothers to have less than good SRH remained after adjustment for potential confounders. Our analyses point towards lack of employment as an increasingly important factor for less than good SRH among lone mothers, and we intend to study this further, also in relation to severe morbidity and mortality. To be attached to the labour market may bring with it social support in terms of colleagues and a sense of belonging and value. For lone mothers, this may be of special importance. Factors such as social support, cultural norms and coping skills are likely to play a part in the health of mothers and need to be studied further, especially in a changing society. 5. Conclusions The increased prevalence of less than good SRH among vulnerable groups of lone mothers may partly be a result of an increase in financial problems among lone mothers in Sweden. There are signs of an increased polarisation in health among sub-groups of lone mothers. Economic strain has substantial explanatory value for less than good SRH, and the prevalence of poverty among lone mothers has increased. However, the association between economic strain and SRH did not change between lone and couple mothers between the 1980s and the 1990s or in different income groups. During the 1990s, the Swedish welfare state did not act as a buffer against economic strain and ill-health for lone mothers to the same extent as during the 1980s. Further studies are warranted to monitor the future development. Acknowledgements Stockholm County Council and the Swedish Council for Working Life and Social Research grant 2002-
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2448 funded this study. We would like to thank Antonio Ponce de Leon for statistical advice. The study was approved by the regional ethics committee in Stockholm, Department 5.
References [1] Lynch JW, Smith GD, Kaplan GA, et al. Income inequality and mortality: importance to health of individual income, psychosocial environment, or material conditions. BMJ 2000;320:1200–4. [2] Subramanian SV, Belli P, Kawachi I. The macroeconomic determinants of health. Annu Rev Public Health 2002;23:287–302. [3] Klat M, Sermet C, Le Pape A. Women’s health in relation with their family and work roles: France in the early. Soc Sci Med 2000;50:1807–25. [4] Diderichsen F, Evans T, Whitehead M. The social basis of disparities in health. In: Evans T, Whitehead M, Diderichsen F, et al., editors. Challenging inequities in health. From ethics to action. New York: Oxford University Press; 2001. p. 12–23. [5] Power C, Stansfeld SA, Matthews S, et al. Childhood and adulthood risk factors for socio-economic differentials in psychological distress: evidence from the 1958 British birth cohort. Soc Sci Med 2000;55:1989–2004. [6] Benzeval M. The self-reported health status of lone parents. Soc Sci Med 1998;46:1337–53. [7] Burstr¨om B, Diderichsen F, Shouls S, et al. Lone mothers in Sweden: trends in health and socioeconomic circumstances, 1979–1995. J Epidemiol Community Health 1999;53:750–6. [8] Lahelma E, Arber S, Kivela K, et al. Multiple roles and health among British and Finnish women: the influence of socioeconomic circumstances. Soc Sci Med 2002;54:727–40. [9] Lindvert J. A world apart, Swedish and Australian gender equality policy. Nordic J Women’s Stud 2002;2:99–107. [10] Leira A. Updating the “gender contract”? Childcare reforms in the Nordic countries in the 1990s. Nordic J Women’s Stud 2002;2:81–9. [11] Children’s time with their parents [Barnens tid med f¨or¨aldrarna]. ¨ Demographic reports 2004:1. Orebro: SCB; 2004. p. 110 [in Swedish]. [12] Esping-Andersen G. The three worlds of welfare capitalism. Cambridge: Polity Press; 1990. p. 248. [13] Ringb¨ack Weitoft G. Lone parenting, socioeconomic conditions and severe ill-health. Longitudinal register-based studies. Ph.D. thesis. Ume˚a: Ume˚a University; 2003. [14] Solera C. Income transfers and support for mothers’ employment: the link to family poverty risks. A comparison between Italy, Sweden and the U.K. Luxembourg Income Study. Working paper 192; 1999. p. 33, http://www.lisproject.org/links/cpconf/solera.pdf [2004-0708]. [15] Curtis L, Phipps S. Social transfers and the health status of mothers in Norway and Canada. Soc Sci Med 2004;58:2499–507. [16] Whitehead M, Burstr¨om B, Diderichsen D. Social policies and the pathways to inequalities in health: a comparative anal-
264
[17]
[18]
[19]
[20]
[21] [22]
[23] [24]
[25]
[26]
[27]
S. Fritzell, B. Burstr¨om / Health Policy 79 (2006) 253–264 ysis of lone mothers in Britain and Sweden. Soc Sci Med 2000;50:255–70. Ringb¨ack Weitoft G, Haglund B, Ros´en M. Mortality among lone mothers in Sweden: a population study. Lancet 2000;355:1215–9. Ringb¨ack Weitoft G, Haglund B, Hjern A. Mortality, severe morbidity and injury among long-term lone mothers in Sweden. Int J Epidemiol 2002;31:573–80. Cairney J, Boyle M, Offord DR, et al. Stress, social support and depression in single and married mothers. Soc Psychiatry Psychiatry Epidemiol 2003;38:442–9. Butterworth P. Lone mothers’ experience of physical and sexual violence: association with psychiatric disorders. Br J Psychiatry 2004;184:21–7. ˚ B¨ackman O, et al. Welfare balance sheet Palme J, Bergmark A, for the. Scand J Public Health Suppl 2003;60(Suppl.):143. Hope S, Power C, Rodgers B. Does financial hardship account for elevated psychological distress in lone mothers? Soc Sci Med 1999;49:1637–49. Social report 2001 [Social rapport 2001]. Stockholm: National Board of Health and Welfare; 2001. p. 243 [in Swedish]. G¨ahler M. Only a mother—single mothers economic living conditions in Sweden in the 1990s [Bara en mor—ensamst˚aende m¨odrars ekonomiska levnadsvillkor i 1990-talets Sverige]. In: ˚ editor. Disadvantage in the Swedish society [Of¨ard Bergmark A, i v¨alf¨arden]. SOU 2001:54. Stockholm: Graphium/Norstedts AB; 2001. p. 15–99 [in Swedish]. Bj¨ornberg U. Single mothers in Sweden: supported workers who mother. In: Duncan S, Edwards R, editors. Single mothers in an international context. London: UCL Press; 1997. p. 241–67. Persson G, Bostr¨om G, Diderichsen F, et al., editors. Health in Sweden—the national public health report 2001. Scand J Public Health Suppl 2001;58(Suppl.):1–240. Vogel J. Financial problems. In: Vogel J, H¨all L, editors. Welfare and inequality from a 20-year perspective 1975–1995 [Ekonomiska problem. I: V¨alf¨ard och oj¨amlikhet i ett 20-˚ars perspektiv 1975–1995]. Stockholm: Statistics Sweden; 1997. p. 179–96 [in Swedish].
[28] Burstr¨om B, Fredlund P. Self rated health: is it a good predictor of subsequent mortality among adults in lower as well as in higher social classes? J Epidemiol Community Health 2001;55:836–40. [29] Lundberg O, Manderbacka K. Assessing reliability of a measure of self-rated health. Scand J Soc Med 1996;24:218–24. [30] Occupations in Population and Housing Census 1985 (FoB 85) according to Nordic standard occupational classification and Swedish socio-economic classification. Reports on Statistical Co-ordination 1989:5 [Yrkesklassificeringar i FoB 85 enligt Nordisk yrkesklassificiering (NYK) och Socioekonomisk indelning (SEI)]. Stockholm: Statistics Sweden; 1989 [in Swedish]. [31] Flyghed J. Evicted to homelessness? Evictions in Sweden 1982–1994 [Vr¨akt till heml¨oshet? Vr¨akningar i Sverige 1982–1994]. Socialvetenskaplig tidskrift, vol. 2; 1995. p. 99–116 [in Swedish]. [32] Armitage P, Colton T, editors. Encyclopedia of biostatistics, vol. 4. Chichester: John Wiley & Sons; 1998. p. 2525–3502. [33] Rothman KJ, Greenland S. Modern epidemiology. 2nd ed. Philadelphia: Lippincott Raven Publishers; 1998. p. 738. [34] Burstr¨om K, Johannesson M, Diderichsen F. The value of the change in health in Sweden 1980/81 to 1996/97. Health Econ 2003;12:637–54. [35] Salonen T. Marginalisation, risk or remainder? [Marginalisering- risk eller rest?], vol. 3. Framtider. Stockholm: Institute for Future Studies; 1998. p. 10–3 [in Swedish]. [36] Landstr¨om I, Henriksson J. What is left once the housing is paid? [Vad f˚ar vi o¨ ver n¨ar boendet a¨ r betalt?} V¨alf¨ardsbulletinen, vol. 1. Stockholm: Statistics Sweden; 2001. p. 16–7 [in Swedish]. [37] Gardberger Morner C. Independently dependent. Lone mothers’ maintenance strategies [Sj¨alvst¨andigt beroende. Ensamst˚aende mammors f¨ors¨orjningsstrategier]. Thesis. G¨oteborg: Intellecta Docusys; 2003 [in Swedish]. [38] Salonen T. The child poverty in Sweden-annual report 2003 [Barnfattigdomen i Sverige- a˚ rsrapport 2003]. Stockholm: Save the Children, 2003. p. 44, www.rb.se [2004-07-14].