# Presentation: 914312

## Socioeconomic Status Differences in Trajectories of Functional Limitations: The Role of Social Security Income

- Erin B. Reidy
- National Center for Health Statistics

**Notes:**
While recent evidence suggests that socioeconomic differences in health decline during later life, substantive explanations for the convergence of health differentials are less well understood 

This research will examine one of the major redistributively-oriented policies in the United States, that of Social Security.  Investigation of the impact of Social Security benefits on the socioeconomic health gradient may be particularly fruitful as previous research indicates that health inequalities decline in later life, leading to speculation that universal programs available to the elderly may be responsible for this decline 

## Age, Socioeconomic Status, and Health

- Lifecourse variation in the relationship between socioeconomic status and health
- Convergence vs. divergence
- Prior analyses imply a linear and constant effect of socioeconomic status on health
- Income
- Captures ability to purchase material resources
- Source of income
- Advantages vs. disadvantages

**Notes:**
Past research suggests that the relationship between SES and health is not constant throughout the lifecourse, but varies with age- with the widest differentials during midlife and convergence during later life. 
Conclusions about convergence or divergence differ according to the health outcome under consideration.  In regards to the limitations in the performance of activities  of daily living, such as dressing, and eating, and instrumental activities of daily living, such as grocery shopping, most research finds a convergence of SES differentials. However, in regards to self-rated health and mortality, evidence suggests that SES differentials increase with age. 
Yet, regardless of their findings, all of this previous research implies that the trajectory of health remains fixed over time.  However, persons with functional limitations often experience significant changes in their functional status over time.  Due to their increased ability to access treatment resources and enhanced coping skills, higher SES groups may experience faster rates of recovery than lower SES groups.  Consequently, there may be little convergence in the trajectories of functional limitations after the initial onset.
Income:
	-purchase preventative and rehabilatative resources
	-ID chronic diseases earlier and delay progression to functional limit
	-leisure activities-greater motivation for recovery
 Source of income:
-evidence that source of income, particularly in later life, matters for health (wealth and assets most important for health of oldest old)
-sources related to risk of experiencing poverty (pension < risk)
Advantages vs. disadvantages:
-multiple measures of income better predictor of health v, selection/reverse causation

## Social Security Income and Health Disparities

- Convergence of disparities
- Redistributive income policy
- Insures large proportion of the older population from poverty
- Divergence or maintence of disparities
- Change in patterns of redistribution
- Relatively small contribution to absolute income
- Limited impact on health due to earlier patterns of health

**Notes:**
Compared to total income, Social Security is distributed more evenly among the elderly (Crystal and Shea 1990). Social Security income may still play a role in the convergence of socioeconomic inequalities in health by insuring a large proportion of the older population from poverty.  Without Social Security income, researchers have estimated that between 39 and 50% of the elderly population would be poor (Treas ; Social Security Administration 2000).  Further, the impact of Social Security on converging health patterns may have less to do with its redistributive nature, and more to do with the fact that 90% of the elderly receive benefits, and thus raising the income of the worst off closer to subsistence level 

However, the benefit system of Social Security was created when single-earner households was the norm.  Therefore, initially, redistribution occurred between households.  Consequently, as women have increased their labor force participation, much of this redistribution now occurs between husbands and wives, where due to the gender gap in earnings, men’s higher income is redistributed to women.  Currently, when measured between individuals, Social Security is redistributive, however when measured between households, the amount of redistribution that occurs declines significantly Thus, there is reason to suggest that over time Social Security income has become less redistributive since, due to increases in women’s labor force participation, greater numbers of households include two beneficiaries. 

May also be that benefits from SS are relatively small that their redistributive effect are wiped out due to large inequalities from pensions and other wealth.	

## Dynamic View of Health

- Significant variation in individual health status over time
- The Disablement Process (Verbrugge and Jette, 1994)
- Persons with higher socioeconomic status may have faster rates of recovery and/or slower rates of decline in functional status.
- Methodological Implications
- Prior studies infer differences in changes within individuals from between individual differences in levels of attributes

**Notes:**
Past evidence suggests that disability is a dynamic process, with significant variation in functional ability over time.  Functional limitations are the capacity to perform  fundamental physical actions, Declines in functional ability, particularly during later life, are often due to underlying chronic conditions, such as diabetes or heart disease.  Therefore, levels of functional impairment vary over time, as symptoms of the underlying chronic condition progress and retreat.  Ex./ 22% of persons with 5+ ADLs, by most standards considered a severe disability, report fewer functional limitations two years later.
Verbrugge and Jette developed a conceptual model of the disablement process in which dysfunctions in bodily systems such as cardiovascular and neurological systems directly lead to functional limitations.  Finally, the ultimate result is difficulty with ADLs.  The causal ordering of this model suggests that functional limitations are the driving force behind disabilities, and this has also been widely supported by the literature.  This main pathway is influenced by both individual risk factors and psychosocial factors. Thus, having more psychosocial resources, such as better coping mechanisms and/or higher social support can be protective barriers against disability.
LGM:  infer differences in individual change from differences in group attributes; prior 2 waves of data
If the goal of research in health inequalities is to develop policies to reduce health inequalities, then examining functional limitations rather than disabilities will produce more efficient and presumable less costly policies.  Since functional limitations drive the disability process, by examining functional limitation trajectories, we may be able to identify those points which are most amenable to health interventions. 

## Data

- Health and Retirement Survey (HRS)
- Longitudinal nationally representative survey of persons born between the years 1931-1941 (i.e. age 51-61 in 1992)
- Waves 1-5, 1992-2000
- Sample
- All age-eligible respondents alive at Wave 2 (1994), who transition onto Social Security during the time of the study with functional limitation information
- N = 7,384
- Future analyses will investigate the presence of selection effects due to missing data

**Notes:**
Analyses are based on 5 waves of the Health and Retirement Survey, collected between 1992 and 2000. The HRS is a longitudinal nationally representative survey of persons born between 1931 and 1941 and their spouses, regardless of age.  Baseline interviews were conducted in 1992, when this birth cohort was 51-61 years of age, and include 12,654 respondents.  Follow-up interviews were conducted every two years since.  I include data from the 1994, 1996, and 1998 and 2000 follow-up interviews. 

The analytic is restricted to age-eligible respondents alive at wave2 with all functional limitation data.  I chose to only use functional limitation data for waves 2 through 4 for two reasons:
--lagged income reduces the possibility of reverse causality
--question-wording changes from wave1 to wave2 that appeared to have a significant effect on the level of limitations reported (dramatic dip in W2 that isn’t present in other waves).
However, restriction of my sample to only those with complete case data clearly presents a bias in the results of my analyses.  In future research I plan to investigate the role of selection effects through use of multiple imputation methods.

## Dependent Variable: Functional Limitations

- Scale Items
- Walk several blocks, get up from chair, lift over 10 lbs., stoop/ kneel/or crouch, pick up dime, reach arms above shoulders, push/pull large objects
- To reduce skewness, counts of functional limitations are logged in growth curve analyses
- Scale ranges from 0 to 7
- Correlation Alpha: .90

## Independent Variables

- Socioeconomic Status
- Income
- Quintiles
- Sources of Income
- Earnings, household capital, pensions/annuities, social security retirement income
- Education
- Demographic Characteristics
- Sex, Age, Marital Status, and Self-rated Health

## Analytic Plan

- Descriptive Statistics
- Growth Curve Analyses
- Assess differences in health trajectories through a series of interactions between time and education
- Intercepts and slopes allowed to vary *across *individuals
- Thus, changes in functional limitations at the individual level are not confounded with effects that would otherwise be attributed to group differences.

## Average Functional Limitations by Sample Characteristics, 1994-2000

**Total**

**Females**

**Males**

**1931-33**

**1934-37**

**1938-41**

**Q1**

**Q2**

**Q3**

**Q4**

**Q5**

- Birth Year

- Income

- 0.0

- 0.5

- 1.0

- 1.5

- 2.0

- 2.5

## Functional Limitations by Receipt of Social Security Income

**Mean Functional Limitations**

**1994 **

**1996 **

**1998 **

**2000 **

**Social Security**

**Non-Social Security**

**Notes:**
This decrease is likely due to changes in the age and health composition of Social Security recipients in the HRS, from younger and sicker retirees to older and healthier retirees. 

## Growth Curve Analysis: Social Security Recipient Sample

|  | Model 1 | Model 2 | Model 3 |
| --- | --- | --- | --- |
| Income |  |  |  |
| Q1 | 0.60*** | 0.44*** | 0.19+ |
| Source of Income |  |  |  |
| Earnings | -0.16* | -0.16* | -0.07 |
| Social Security | 0.15* | 0.14* | 0.07 |
| Time * Earnings | 0.06* | 0.06* | 0.04+ |
| Time* Social Security | -0.06* | -0.06* | -0.04 |

**Notes:**
Through a series of income-by-time interactions, the growth curve analyses examine whether there are relative socioeconomic group differences in functional limitation growth rates.   Model 1 includes household income quintiles and sources of income.  Model 2 adds educational attainment.  Model 3 includes demographic characteristics (sex, race, marital status, and baseline self-rated health).  I do not include age in the models, since age is co-linear with time.

## Discussion

- Social Security is predictive of functional limitations
- Greater functional limitations at initial status
- Slower rate of growth in functional limitations
- Timing Matters!!!
- Early vs. “On-time” Retirement
- Lifecourse patterns of health
- Healthy People 2010
- Eliminate Health disparities
- Economic policy is health policy

**Notes:**

One of the goals of the Healthy People 2010 is to eliminate health disparities, including socioeconomic disparities.  This research suggests 

## Limitations and Future Research

- Methodological
- Limited age range
- Health Selection
- Persons with less income are more likely to die or be lost to follow-up, leaving a disproportionately healthy group of lower-income persons.
- Future analyses will explore the extent to which missing data contribute to overall findings of divergence