Method and analysis - Les déterminants de l'évolution de la qualité de vie des personnes â

Sample selection and method

The analysis was conducted with the data of the Swiss Household Panel. This longitudinal data collection started in 1999 with the aim to observe social change, in particular the dynamics of living conditions within the Swiss population (www.swisspanel.ch) (Zimmermann & Budowski 2003; Zimmermann & Tillmann 2004). Based on an initial random sample of private households living in Switzerland,

the survey is repeated yearly. All household members, aged 14 and over, are interviewed through a CATI (Computer Assisted Telephone Interviewing) procedure.

The initial sample, selected in 1999, was composed of 5,074 households and 12,931 individuals. In 2004, a complementary sample of 2,538 households and 6,569 individuals has been added and its units are followed annually ever since. The total number of individuals starting at any time between the waves 1999 and 2010 is 15,507 (82,146 observations). Out of this total number, 7,788 entered in 1999 and 3,823 during the refreshment sample in 2004; the remaining 3,896 individuals joined the SHP in between either because they turned 14 years or because they joined the household as a spouse.

Since life satisfaction has not been recorded in the first SHP wave (1999), we therefore included in the present study waves 2000 to 2010. For the present analysis, we retain the SHP subsample of 1,402 women, aged 65 to 84 years, generating 6,387 observations (mean age=69.8±5.5). The exclusion of those older than 85 years is motivated by the small number in the SHP participating women (43/7732, 0.56%), which includes only people living at home. In Switzerland, people over 85 years represent 6.5% of the population over 65, among them 27.9% are in institutions (nursing homes) (Höpflinger et al. 2011). In the SHP data between 2000 and 2010, only 4% of men and women above 65 years were 85 years and older.

Out of the 1,402 women, 579 entered the survey between ages 54 and 64 years, that is before the age of interest here, but they were included in the analysis when they turned 65 years. The average wave participation was 6.6 ± 3.1 waves. Data have been weighted by yearly transversal weights in order to represent the elderly women of general population at each calendar year.

Table 1 presents the number of observations (n=6,387) in the form of an age, period and cohort table (APC table) with cohorts in rows, ages in columns and periods (year of observation by survey) along diagonals, periods being computed as birth years plus age (P=B+A). The three ten year cohorts are highlighted by corresponding color patterns and the two age categories of the ‘young old’ (65-74 years) and the ‘old old’

(75-84 years) in different fonts (normal and italic). The middle cohort (1926-1935) has been followed over the full observed age range (65-84) and has been divided into two age categories: the 65-74 age range is compared with the more recent cohort

(born 1936-1945) and the 75-84 age range with the former one (born 1916-1925).

This means that some people were observed twice, once in the 65-74 years age category and once, as they got older, in the 75-84 years category. Respondents followed for a longer period over a larger age span may introduce a selection bias, since healthier and more educated individuals are better compliers in the SHP survey (Zimmermann 2008). To assess for a potential bias, we compared the mean life satisfaction score and the proportion of satisfied women between those of the 1926-1935 cohort aged 75-84 years at the end of their trajectory (n=313) and who had entered the study before the age of 75 years, and the new comers who entered the study after the age of 75 years (n=78).

Table 1: Age, period, cohort (APC) table matrix for the SHP 2000-2010 sub-sample of women aged 65-84 years. Birth years as rows

51 Outcome (dependent variable)

The degree of life satisfaction (LS) in general was considered here as a proxy-measure for quality of life score (QOL). The question was “In general, how satisfied are you with your life if 0 means "not at all satisfied" and 10 means "completely satisfied"”? LS was analysed either on a continuous scale or grouped into a binary dummy variable defining high satisfaction as one for a score value of 9 to10 and fair or poor satisfaction as zero for a score of 0 to 8. Prevalence of life satisfaction was reported as the proportions of subjects satisfied versus unsatisfied. SL trajectories were estimated as the individual mean scores over one year of age.

Selected covariates (explanatory variables)

Among the many reported contributors to LS, we selected the following determinants reflecting several socio-cultural dimensions: education and satisfaction with income (socio-economic resources); social support and living with a partner (social integration), self-perceived health, all self-reported in the SHP telephone questionnaire. Birth year was used to define cohort affiliation. Birth year (B) and age (A) implicitly define the period (P) (P=B+A) (APC Table 1). A distinction was made for within-individual time-varying characteristics (age, education, self-perceived health, social support, satisfaction with income, living with a partner) and for between groups of individuals, the persons’ contextual characteristics (birth year computed as the mean individual period). We also distinguished between time-invariant covariates (education, cohort, and period) and time-dependent covariates (age, self-perceived health, social support, satisfaction with income, living with a partner). The educational level was reported as the highest education achieved. Compulsory or vocational levels were considered in the analyses as lower education, while maturity and high school or apprenticeship and vocational high or academic as higher level education.

Satisfaction with the household income was reported on a 0-10 score when 0 means completely unsatisfied and 10 satisfied. Satisfied was considered as a score of 8-10 and all others ranged between somehow satisfied to unsatisfied. Satisfaction with household income was considered as a better measure than income itself: first, data on household income was not available for about 10% of participants; second, income itself provides only a rough evaluation of the economic situation during

retirement since it does not include the available wealth from cumulated fortune over the life time. Social support was reported on a 0-10 scale of 5 items for the available amount of psychological and 5 items of practical support from partner, relatives, neighbors, friends or colleagues (all outside the household) the subject perceives and can rely on in case of need. Two mean scores ranging from 0-10 out of the 10 items were coded, one as time-dependent for the mean individual score at each wave and one as fixed for the individual mean over all waves. Living with a husband or a partner versus living alone was self-reported. Self-perceived health was reported as an ordinal five categories scale and dichotomized to excellent and very good (good) versus fair, moderate or poor.

Structure for age, wave, birth year, and initial age

In longitudinal analyses the choice of the cadence of time is crucial. Period (calendar wave) and age are time-dependent covariates but fixed by the study design.

Although both “wave” and “age” can be used to cadence time and to assess longitudinal change, “age” was preferred here as a metric for time because our main interest was the aging process. Period was defined as the mean individual period (2005) and adjusted for. We do not expect major socio-environmental changes between such a short time between 2000 and 2010. “Birth year” defines the cohort and is a fixed between-subjects covariate defined as the period minus age (C=P-A).

Age was coded into two categories, 65-74 and 75-84 years and centered to 65 or 75 years respectively in order to get interpretable satisfaction scores at the intercept.

Satistical analysis

Life satisfaction (LS) score was analysed as a continuous scale for distribution comparisons and dichotomized into one for the probability of satisfaction and zero as unsatisfied. All covariates were dichotomized into ‘1’ for favourable predictors (high education, satisfied with household income, high social support, living with a partner and good self-perceived health) and into ‘0’ as the corresponding reference for un- favourable predictors. The above coding defined the direction of expected odds ratios (OR) with a high probability of satisfaction for favourable predictors expected to be than greater than one (OR>1). A descriptive analysis of LS score distribution is presented as a density function for all women aged 65-84 years between 2000 to

2010 and for two age categories (65-74 and 75-84 years) and three ten years cohorts (1936-1945, 1926-1935, 1916-1925) (Figure 1). For cross-sectional cohort differences, we compared the prevalence (%) of satisfied individuals and the prevalence of determinants between successive cohorts of identical age categories.

The association between LS and each binomial explanatory variable across the cohorts within two identical age categories were estimated in terms of odds ratios (OR) and their ninety five per cent confidence intervals (95% CI). Interaction terms between each covariate and cohort were estimated and reported in case of significance (non-zero interaction). The multilevel logistic model was chosen as it makes inference with conservative standard errors (SE), provided that individual observations are repeated over time. We used the SAS Proc Genmod procedure (Table 2).

Patterns of LS trajectory as a continuous scale across cohorts of identical age were estimated using a) the multilevel mixed unconditional mean model with no covariates in level-1 model and a random intercept for between subjects variation, and b) the multilevel mixed growth model in which we added in level-1 age as time-variant variable, dummies for cohorts as time-invariant and the ‘age by cohort’ interaction.

The unconditional multilevel mixed mean model was used to separate the amount of variability due to within- (level-1) or to between-subjects (level-2), and reported as the class correlation coefficient (ρ). The mixed growth model assessed the intra-individual variability explained by aging (within-variance) in each cohort and the inter-individual heterogeneity in the intercept and slope (Table 3, Figure 2).

We explored then the univariate effect of each covariate on the individual LS trajectory (slope) stratified by age and cohort categories. When the LS slope differed across the levels of the covariate, we tested the interaction term (age by covariate) (Table 4, Figure 3).

Finally we applied a hierarchical age-period-cohort (HAPC) mixed model with age, cohort as two dummies and all dichotomous covariates as fixed in level-1, and subjects and period as random in level-2. Covariates were added first one by one and then all together. Interactions between covariates and age were assessed and introduced to the full model if they were significant. Estimates indicate the effect of age or one or all covariates on LS adjusted for the others (Table 5, Figure 4).

We hypothesized that LS varies individually as persons get older (within-variance), but that individuals from different cohorts may experience different aging patterns due to their life course experiences through different periods in a changing society (between variance). For that reason we introduced age and cohort as fixed and random. We expect former cohorts (compared to more recent cohorts of the same age) who were less educated and more exposed to cumulative social strains during childhood or early adulthood to be less demanding but also probably less adaptive to harder situations when affected by declining health or social resources in older age.

Their expected pattern of LS in terms of mixed modeling should be a higher intercept but a greater decline over age. More recent more demanding cohorts are expected to be less satisfied but probably more adaptive due to their higher education and social status, therefore their LS score should remain more stable over aging.

All the statistical analyses were carried out using SAS software version 9.2.

Results

Age and cohort distributions of respondents

The total number of observations (subjects) was 6’387 (1’402) (Table 1).

Respectively for cohorts 1936-1945, 1926-1935 and 1916-1925, the total numbers of observations (and subjects) were 2’520 (653), 3’047 (523), and 820 (226).

Among the 523 women of the 1926-1935 cohort, 132 were included only in the 65-74 years age category, 313 were included in both age categories and 78 entered the survey when they were older than 75 years and therefore were included only in the 75-84 age category. In this older age category, the mean life satisfaction score was somewhat higher, but not significantly, among subjects who entered later (8.4±1.7) than among those who had entered at ages 65-74 years (8.1±1.8) (p=0.10). The proportion of satisfied subjects (score 9-10) was also higher but the difference was not significant (52% versus 41%, p=0.06). Participants followed since ages 65-74 were slightly more educated (62.2% versus 56.4%, p=0.35) but perceived their health as less good (54.3% versus 64.1%, p=0.11). Since none of these differences was significant, we considered that taking together ages 75-84 years of cohort 1926-1935, whether subjects were followed longer or only since the age of 75, did not

represent a selection bias. At least we can exclude the hypothesis that women starting at age 65-74 and followed over a longer period until 75-84 years would be more satisfied due to the drop out of the unsatisfied ones eventually becoming sick;

less satisfied remained indeed in the study while new participants entering later on tended to be more satisfied and healthier. Unhappy and unhealthy individuals are probably more reluctant to enter the survey.

Life satisfaction levels and trajectories of life satisfaction

The life satisfaction score distribution is left skewed (-1.2) with a median at 8 and an overall mean of 8.2±1.6, 8% of participants have a score below 5. LS was therefore dichotomized as dummies for satisfied (score 9-10, 70% of subjects) versus unsatisfied (score 0-8, 30%). Among the ‘young old’ (65-74 years), the mean life satisfaction score did not significantly vary across cohorts (8.2±1.6, p=0.61). Among the ‘old old’ (75-84 years), women from the former cohort (born between 1916-1925) were slightly more satisfied (8.3±1.7) than the ones belonging to the more recent cohort (1926-1935) (8.1±1.7, p=0.10) (Figure 1). Accordingly, the proportions of satisfied subjects were higher in former cohorts, significantly so in the 75-84 years old (47.1% versus 41.5%, p=0.001), but not significantly in those aged 65-74 years (43.6% versus 41.4%, p=0.4) (Table 2). Overall, elderly women in Switzerland are rather satisfied with their life.

Figure 1: Life satisfaction score density distribution, by age categories (65-74 and 75-84 years) and birth cohorts. SHP 2000-2010, women 65-84 years old

Table 2: Life satisfaction and selected characteristics - proportions and associations, by age categories and birth cohorts. SHP 2000-2010, women 65-84 years old. (Numbers are proportions, odds ratios (OR) and 95% confidence intervals (95%CI) for the probability of being satisfied)

Birth cohorts

1936-1945 1926-1935 1916-1925 p-value¹ 65-74 Proportions (%)

1 p-value with conservative standard errors (SAS PROC GENMOD procedure)

2 score 9-10 versus 0-8

3 score 8-10 versus 0-7

4 mean individual score 5.5-10 versus 0-5.4 of 10 items of social support

5 excellent and very good versus fair, poor and very poor

The unconditional mean model revealed that, in both age categories, a great deal of the total variance (57%) is due to between subjects variation (Table 3, Model 1). In the growth model with age centered at the youngest age in each age group (65 or 75 years), the estimate for age (adjusted for the mean period) was slightly negative, but not significantly so, within both age categories. The part of within-individual variance due to age was very small (about 1%) and not significant in both age categories (Table 3, Model 2). However, after introducing the dummies for cohort, recent cohorts were significantly less satisfied with life in both age categories. In both the ‘young old’

and the ‘old old’, LS scores were significantly lower for the more recent cohorts

(1936-1945 versus 1926-1935 or 1926-1935 versus 1916-1925) by about -0.3 or -0.5 LS score units respectively. At the same time, earlier cohorts showed a significant decline of LS with age (around -0.05 per year, p<0.001) (Table 3, Model 3), indicating that the decline with age is cohort specific (Figure 2).

Figure 2: QOL trajectory on age by birth cohort. SHP 2000-2010, women 65-84 years old

Age 65-74 years birth year 1936-1945 (recent) in solid black Age 65-74 years birth year 1926-1935 (former) in dashed black Age 75-84 years birth year 1926-1935 (recent) in solid grey Age 75-84 years birth year 1916-1925 (former) in dashed grey

Table 3: Estimates from a mixed unconditional mean model, unconditional growth model and controlled for cohort model of life satisfaction, by age categories net of period effect. SHP 2000-2010, women 65-84 years old (cf Figure 2)

Age 65-74 years Age 75-84 years

Model 1 Model 2 Model 3 Model 1 Model 2 Model 3

Level-2 intercept in period 0.01 (0.007)* 0.008 (0.006) 0.006 (0.004)

0 0 0

ρ 56.9% ³ 0.07% ⁴ 0.07% ⁵ 57.4% ³ 0.14% ⁴ 0.4% ⁵

BIC 15026.9 15024.0 15018.3 8004.0 8002.9 7996.3

1 Age centered to 65 years for age category 65-74 and to 75 years for age category 75-84

2 For age 65-74 years recent cohort is 1936-1945 versus former cohort 1926-1935, and for age 75-84 years recent cohort is 1926-1935 versus former cohort 1916-1925

3 part of total variance due to between subjects and periods

4 part of variance due to age net of individual and period variances

5 part of variance due to age and cohort net of individual and period variances

A substantial part of total variance is due to between subjects but almost half is still within subjects. The part of variance due to age is small and most of the residual variance should be explained by covariates.

60 Determinants of life satisfaction distribution

Distributions of the selected determinants are presented in Table 2, stratified by the two age categories and comparing trends between the two observed cohorts. The historical trend in educational attainment can be observed across cohorts, with the earliest one having the lowest proportion of educated women (54.2% in the higher education category) and the most recent one (1936-1945) having the highest proportion of educated women (69.1%). Regarding the living situation, the ‘old old’

women from the earliest cohort are the least likely to live with a spouse (28.9%), significantly less than the more recent cohort of the same age (36.4%). Among the

‘young old’, living with a spouse or partner is more prevalent, but again a significant difference exists between the two cohorts (50.6% of the 1926-1935 cohort versus 63.1% of the 1936-1945 cohort). Though the difference is not statistically not significant, the satisfaction with income tends to be slightly higher among more recent cohorts; it remains at the same level for both age categories. Social support is significantly higher among women from more recent cohorts and older women (75-84 years) report clearly less support. Self-perceived health is slightly higher among more recent cohorts (not significant); older women (75-84 years) report poorer health, but still almost two thirds of them consider themselves in good health at that age.

All covariates are positively associated to life satisfaction (Table 2, OR and 95%CI in parenthesis). High education, high social support, living together as a couple and good self-perceived health increase the probability of LS by about 50% to 100% and high satisfaction with income by about 300%. None of the interactions between covariates and the cohort categories in both age categories was significant (all covariates by cohort interactions with p>0.05). This indicates that the mean effect of covariates is stable across cohorts and age. These results suggest that it is important to adjust for the effect of covariates when assessing LS age trajectories across cohorts, but that it is not necessary to include interaction terms.

More recent cohorts were in general less satisfied with life than former cohorts of the same age, but they were also more educated, more satisfied with their income, had higher social support and were living more often with a spouse, and were slightly healthier (Table 2). Therefore, analyses that do not adjust for those covariates

positively influencing life satisfaction would bias the association between LS and the cohort category towards the null. The higher satisfaction score among former cohorts should in fact be even higher than observed, had former cohorts enjoyed the same advantages as the more recent ones. Among the 65-74 years category, the unadjusted probability of life satisfaction was slightly higher for the former cohort (OR=1.1; 95%CI=0.9-1.4), when adjusted for covariates the odds ratio was higher and significant (OR=1.2; 1.0-1.4). Among the 75-84 years category, this difference was higher and significant (OR=1.4, 95%CI=1.1-1.8 and aOR=1.6; 95%CI=1.2-2.1).

In short, there is a significant difference in life satisfaction between cohorts at identical ages, with former cohorts more satisfied than more recent ones who were indeed better off in terms of socio-economic status and health at identical ages. The importance of the individual part explaining LS is also evident from the within-individual variance (56%) reported earlier out of the unconditional mean model.

Determinants of age related life satisfaction trajectories

Beyond an analysis of levels of life satisfaction at specific ages for different cohorts, longitudinal data further allow to assess the influence of determinants on the evolution of life satisfaction: how do these determinants affect the relative decline or stability of life satisfaction over time? Life satisfaction trajectories on age were assessed for all selected covariates (Figure 3): education, satisfaction with income, social support, living together as a couple and self-reported health (Table 4 for detailed results). Results are reported along the following questions: 1) does the level

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