Evaluación de la propuesta

The creation of socioeconomic advantage scores for childhood and adulthood allowed exploration of the change in socioeconomic circumstances across the life course.

Additionally, the cumulative score was used to test whether increased cumulative socioeconomic advantage over the life course is related to higher quality of life in early old age. Two different methods were used to create the scores; these are described in turn.

Binary method

The first method was used only in the descriptive statistics and to check the construct validity of the standardised rank method, described below. The binary method involved converting the eight measures of socioeconomic position used in the previous chapter into binary variables, where 0 related to socioeconomic disadvantage and 1 related to socioeconomic advantage. The conversion of the measures of socioeconomic position into binary variables is detailed in Appendix 5.3. For example, if the respondent’s main occupation was manual they were given a score of 0 and if it was non-manual they were given a score of 1. The binary variables were then summed to generate a socioeconomic

advantage score, ranging from 0 to 4 for the childhood and adulthood scores and from 0 to 8 for the cumulative (life course) socioeconomic advantage score. Each exposure to socioeconomic advantage was hypothesised to contribute to higher quality of life in a similar manner; therefore no weights were used to calculate the socioeconomic

advantage scores. Throughout this thesis, the socioeconomic advantage scores generated by the binary variables are referred to as the ‘binary method’.

Standardised rank method

The second method used to generate the socioeconomic advantage scores involved summing together the standardised socioeconomic ranks (the derivation of which was described in section 5.6.1.1). These socioeconomic ranks take into account the different socioeconomic distributions by country, gender, and cohort. As above, the

socioeconomic ranks were calculated for the four childhood socioeconomic variables and the four adulthood socioeconomic variables, and these were summed to generate a cumulative (life course) socioeconomic advantage score. The method used to generate the socioeconomic advantage scores is illustrated with an example below.

Figure 5.6 demonstrates the derivation of the education level rank score from the example in 5.6.1.1. In this scenario, the least advantaged category has three individuals and thus the mid-point (i.e. the median number of people in that category) is 1.5. With a total sample size of 25 people, standardisation to a scale from 0 to 1 (1.5÷25) gives a rank of 0.06 for the education component of the socioeconomic advantage score.

Figure 5.6: Demonstration of the derivation of the education level standardised rank score

Most advantaged Least advantaged

Standardised rank

0 10.5 21.5 25

Education level

Low (N=3) Medium (N=15) High (N=7)

Rank

0 0.06 0.42 0.86 1

1.5 3 18

Mid-point

Figure 5.7 demonstrates how the socioeconomic advantage scores were derived from the sum of the relevant individual component socioeconomic rank scores. Each

socioeconomic variable is portrayed as containing three levels (e.g. low, medium, and high education) and in this example, an individual is assumed to be in the least

advantaged category for each socioeconomic variable. Their value on the childhood socioeconomic advantage score (ranging from 0 to 4) would be 0.60, which reflects the sum of the standardised ranks for the childhood socioeconomic variables. Similarly, their score on the adulthood socioeconomic advantage score (ranging from 0 to 4) would be 0.56, equal to the sum of the standardised ranks for the adulthood socioeconomic variables. Their score on the cumulative score (ranging from 0 to 8) would therefore be 1.16, equal to the sum of the standardised ranks for all eight socioeconomic variables from across the life course. Throughout the thesis, this method to generate the socioeconomic scores is referred to as the ‘standardised rank method’.

Figure 5.7: Illustration of the standardised rank method used to generate the childhood, adulthood and cumulative socioeconomic advantage scores

Variables in italics indicate those corresponding to childhood

Childhood socioeconomic advantage score = 0.12 + 0.18 + 0.12 + 0.18 = 0.60 Adulthood socioeconomic advantage score = 0.06 + 0.18 + 0.12 + 0.20 = 0.56

Cumulative socioeconomic advantage score = 0.12 + 0.18 + 0.12 + 0.18 + 0.06 + 0.18 + 0.12 + 0.20 = 1.16

The cumulative advantage score generated via the standardised rank method was highly correlated (r= 0.83) with the equivalent score generated using the binary method, demonstrating construct validity. It also correlated with the childhood (r=0.84) and adulthood (r=0.85) socioeconomic advantage scores generated using the standardised rank method. Additionally, the cumulative advantage score was normally distributed

Standardised socioeconomic rank Variable

Number of books 0.12 Rooms per capita 0.18 Amenities 0.12

Breadwinner job 0.18

Education level ^0.06 0.42 0.86

Main occupation 0.18 Current income 0.12

Current wealth 0.20

Most advantaged Least

advantaged

0 1

(Figure 5.8) and displayed the expected relationship with the current ability to make ends meet variable. Those who reported that the household had great difficulty making ends meet had a mean cumulative advantage score of 3.4 (SD=1.1) and those reporting they were easily able to make ends meet had a mean score of 4.6 (SD=1.3).

Figure 5.8: Distribution of the cumulative (life course) socioeconomic scores by welfare regime

0.2.4 0.2.4

0 2 4 6 8 0 2 4 6 8

Southern Scandinavian

Post-communist Bismarckian

Density

Cumulative advantage score

Measuring social mobility

Inter- and intra-generational mobility

Inter-generational mobility was defined as a change in the occupational position between childhood (occupation of main breadwinner) and adulthood (the respondent’s main occupation). Intra-generational mobility was considered as a movement in the

occupational position between the occupation at aged 16 to 34 years and aged 35 to 49 years. Intra-generational mobility was also examined using occupations at aged 35 to 49 years to aged 50 to 65 years, but the prevalence of mobility between these points in the life course was low. Therefore, it was decided to concentrate analyses on mobility between the ages of 16 to 34 years and 35 to 49 years. The occupational variables were used in their manual versus non-manual classification for clarity in grouping into upward

and downward mobility categories because there is a clear distinction between the advantaged (non-manual) and disadvantaged (manual).

Social mobility using the socioeconomic advantage scores

The other method used to measure social mobility involved first categorising individuals into advantaged or disadvantaged groups. For both the childhood and adulthood socioeconomic advantage scores (derived using the standardised rank method), individuals scoring less than or equal to two (the median value) were classified as socioeconomically disadvantaged and those scoring more than two were classified as socioeconomically advantaged. Individuals were then grouped into the following socioeconomic trajectories: disadvantaged-disadvantaged; advantaged-disadvantaged;

disadvantaged-advantaged; advantaged-advantaged.

5.6.5.3 Overall results

Cumulative advantage over the life course and quality of life in early old age First, mean quality of life scores were examined according to the childhood, adulthood, and cumulative socioeconomic advantage scores derived using the binary method. In addition, Pearson’s correlation coefficients were calculated for the association between the socioeconomic advantage scores (derived using the standardised rank method) and quality of life. This was carried out in order to investigate whether there was evidence for a linear relationship between increased socioeconomic advantage and increased quality of life.

Age-adjusted multilevel models were then calculated for the association between the socioeconomic advantage scores (derived using the standardised rank method) and quality of life. The predicted mean quality of life scores were then calculated (as above) and the results for these were then graphed to aid interpretation.

Descriptive statistics were then calculated for each potential explanatory factor:

employment status, ability to make ends meet, limitations with daily activities, mood, and marital status. Age-adjusted multilevel models were calculated looking at how each factor independently influenced the association between the cumulative socioeconomic advantage score and quality of life. Then fully adjusted models were calculated.

Social mobility over the life course and quality of life in early old age Inter- and intra-generational mobility

First, the rates of inter- and intra-generational social mobility were examined and then mean quality of life scores by social mobility status were investigated. In age-adjusted multilevel models, the inter- and intra-generational mobility hypotheses were tested by including interaction terms between the occupational variables. The analysis was run using both binary manual versus non-manual occupational variables and then using their standardised socioeconomic ranks.

Social mobility using the socioeconomic advantage scores

Mean quality of life scores were calculated according to socioeconomic advantage and disadvantage during childhood, adulthood, and across the life course. Descriptive

statistics for the socioeconomic trajectories were calculated. Following this, age-adjusted multilevel models were calculated to investigate the association between the

socioeconomic trajectories and quality of life. In addition, age-adjusted multilevel models including interaction terms between childhood and adulthood socioeconomic advantage and disadvantage were calculated.

5.6.5.4 The influence of the welfare regime

Cumulative advantage over the life course and quality of life in early old age The above descriptive analyses were repeated, stratifying by welfare regime. For the multivariate analyses, interaction terms between the socioeconomic advantage scores (childhood, adulthood, and cumulative) and the welfare regime type were included to see if the type of welfare regime modified associations between the experience of

socioeconomic advantage and quality of life. Stratified single level regression models by welfare regime were performed to investigate the role of the potential mediating variables in the relationship between the cumulative advantage over the life course and quality of life.

Social mobility over the life course and quality of life in early old age To test the social mobility theory, models containing interaction terms between advantage and disadvantage at the two time points were run stratifying by welfare regime (including age and country effects). Due to the low number of individuals who experienced intra-generational mobility, stratifying this analysis by welfare regime and gender was problematic. Therefore, it was decided to concentrate on the experience of inter-generational mobility in different welfare regimes and the experience of different socioeconomic trajectories derived using the socioeconomic advantage scores. In addition, as noted in the systematic review, studies investigating inter-generational mobility were particularly lacking.