Black-White Disparity in Late-Life Disability: Exploring the Effects of Age, Period, and Cohort

Shih-Fan Lin1, DrPH.Brian K. Finch1, Ph.D.

Audrey N. Beck1, Ph.D.Robert A. Hummer2, Ph.D.

Ryan K. Masters3, Ph.D.

1San Diego State University; 2University of Texas at Austin; 3Columbia University

BACKGROUND: ObjectivesElucidate how U.S. disability prevalence

changed among older adults age 70+ using the Age-Period-Cohort (A-P-C) models. Compare (a) unadjusted and (b) socio-

demographics and A-P-C adjusted trends.Examine the black-white disparity trend in

late-life disability using the A-P-C modelsSocio-demographics and A-P-C adjusted

disparity trends.Stratify by gender.

BACKGROUND: Outcome DefinitionOutcome: Late-life disability

ADL Disability: limitations on activities of daily living such as bathing, ambulating, and toileting.

IADL Disability: limitations on instrumental activities of daily living such as shopping, writing a check, and cooking.

BACKGROUND: The Age-Period-Cohort (APC) ModelIn the realm of demography, sociology, and

epidemiology, time can be captured by three unique temporal dimensions: Age (A), Period (P), and Cohort (C).

Each aspect of A-P-C has a unique contribution to the study of population health including disability.

BACKGROUND: Age EffectAge is a proxy for biological processes that

ultimately lead to disease, disability, and/or death.

Age may also be associated with changes in status, social roles, and social position (Yang and Land 2007).

Individuals’ aging processes can have differential impacts on population sub-groups (e.g. racial groups) over time.

BACKGROUND: Period EffectPeriod or survey year, reflects changes in

socio-cultural, economic, technological, medical, and environmental factors that may affect the entire population at a given time simultaneously, but perhaps not equally.

For example, a drought may lead to increased food prices, which may impose greater impacts on those with lower incomes than the more well-off.

BACKGROUND: Cohort EffectCohort describes a unique set of individuals who

are both born into a social system during a similar time period and experience similar formative social experiences over their life course.

Successive cohorts that experience different historical and social conditions differ in their exposure to socioeconomic, behavioral, and environmental risk factors.

The colloquial concept of generational difference is an attempt to capture the unique characteristics of distinct cohorts.

METHODS: DataIntegrated Health Interview Series (IHIS), 1982-2009

Harmonizes National Health Interview Survey (NHIS) variables to allow consistent coding across each survey to facilitate temporal analysis.

The NHIS is a repeated cross-sectional survey.Purpose: to investigate and monitor the prevalence of

important health outcomes (including disability) of the civilian non-institutionalized U.S. population.

Inclusion criteria: Older adults aged 70 and over. Age of 70 is the youngest common age cut point for which

the disability items were inquired between the 1982-2009 survey periods.

1982 is the first NHIS survey year that the disability status was inquired.

METHODS: Tackling the Identification ProblemIdentification problems occur when the predicting

variables in a regression are linearly dependent.There is an exact linear dependence between age,

period, and birth cohort.

To break the linear dependence, we group cohorts into 5-year bands.

For example, individuals who were born between 1898-1902 were collapsed into the 1900 cohort (mid-point of 1898 and 1902).

Period Age Cohort

METHODS: AnalysisUnadjusted ADL/IADL disability trends:

6 separate logistic regressions in which ADL/IADL disability (dichotomous) was regressed on A-P-C separately (e.g. ADL Disability = β0 + β1 age).

Adjusted ADL/IADL disability trends:ADL/IADL disability (dichotomous) was regressed on

A-P-C simultaneously with the addition of socio-demographic variables (e.g. Adjusted ADL disability trend: ADL Disability = β0 + β1 age + β2 period + β3 cohort + β4 race + β5 education +……… βn income).

Age was entered linearly while periods were entered as single-year dummies and cohorts were entered as 5-year bands. Omitted category for period: 1982 Omitted category for cohort: 1885

METHODS: AnalysisAdjusted disparity trends in ADL/IADL disability.

ADL/IADL disability was regressed on A-P-C simultaneously while interacting race (black/white) with each A-P-C and controlling for socio-demographic variables (e.g. Disparity trend by cohort: ADL Disability = β0 + β1 race + β2 age + β3 period + β4 cohort + β5 race × cohort

+ β6 education + ………βn income).Age was entered linearly and as a squared term

while periods were entered as single-year dummies and cohorts were entered as 5-year bands. Omitted category for period: 1982 Omitted category for cohort: 1895

RESULTS: ADL/IADL Disability by AgeUnadjusted Trends Adjusted Trends

70 71 72 73 74 75 76 77 78 79 80 81 82 83 840.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

ADL Disability IADL Disability

Age

Fit

ted P

robabil

ity

70 71 72 73 74 75 76 77 78 79 80 81 82 83 840.00

0.05

0.10

0.15

0.20

0.25

0.30

ADL Disability IADL Disability

Age

Fit

ted P

robabil

ity

RESULTS: ADL/IADL Disability by PeriodUnadjusted Trends Adjusted Trends

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

0.00

0.05

0.10

0.15

0.20

0.25

ADL Disability IADL Disability

Period

Fit

ted P

robabil

ity

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

0

0.05

0.1

0.15

0.2

0.25

ADL Disability IADL Disability

Period

Fit

ted P

robabil

ity

RESULTS: ADL/IADL Disability by CohortUnadjusted Trends Adjusted Trends

1885

1890

1895

1900

1905

1910

1915

1920

1925

1930

1935

1940

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

ADL Disability IADL Disability

Cohort

Fit

ted P

robabil

ity

1885

1890

1895

1900

1905

1910

1915

1920

1925

1930

1935

1940

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

ADL Disability IADL Disability

Cohort

Fit

ted P

robabil

ity

KEY FINDINGS: Disability Trends for Age and PeriodThe unadjusted predicted probabilities of

ADL and IADL disability increase substantially with age. The age effects remain strong after adjusting for period and cohort effects and socio-demographic variables.

The unadjusted and adjusted periods trends show similar results – there was a substantial decline in IADL disability between 1982 and 2009 while ADL disability remained stable over the last 3 decades.

KEY FINDINGS: Disability Trends for CohortThe unadjusted cohort trends for both

outcomes also showed continual declines across each successive cohort; however, increasing cohort trends were evidenced in the adjusted model.

More recent cohorts of U.S. older adults are becoming more disabled, net of age effect and net of changes in socio-cultural, technological, medical, economic and environmental factors captured by period effects.

RESULTS: Adjusted ADL and IADL Disparity Trends by Age and Gender

70 71 72 73 74 75 76 77 78 79 80 81 82 83 840.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

ADL Racial Disparity: Men

ADL Racial Disparity: Women

Age

Diff

ere

nce i

n F

itte

d P

rob

ab

il-

ity

(Bla

ck

- W

hit

e)

RESULTS: Adjusted ADL and IADL Disparity Trends by Period and Gender

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

ADL Racial Disparity: MenADL Racial Disparity: Women

Period

Diff

ere

nce i

n F

itte

d P

rob

ab

ilit

y(B

lack

- W

hit

e)

RESULTS: Adjusted ADL and IADL Disparity Trends by Cohort and Gender

1895

1900

1905

1910

1915

1920

1925

1930

1935

1940

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

0.10

0.12

ADL Racial Disparity: MenADL Racial Disparity: Women

Cohort

Diff

ere

nce i

n F

itte

d P

rob

ab

ilit

y(B

lack

- W

hit

e)

KEY FINDINGS: General Disparity Trends in DisabilityBlacks are more likely to experience

disability than whites. Women tend to have greater black-white

disparities than men with respect to each age, period, and cohort trend and each disability outcome.

The black-white disparities in IADL disability tend to be greater than the disparities in ADL disability.

KEY FINDINGS: Disparity Trends in Disability by Age & GenderFor both men and women, there is a

persistent increase of disparity in ADL and IADL disabilities across age.

This supports the “double jeopardy hypothesis” which suggests that both minority status and aging together contribute to double disadvantages in health (disability).

The double jeopardy effect seems to be more pronounced for black women than black men, especially for the ADL disability.

KEY FINDINGS: Disparity Trends in Disability by Period & GenderAlthough a decreasing trend of IADL

disability and a steady ADL trend were observed across each period (slide #13), there is not a consistent period-based disparity trend for ADL or IADL disability.

Fluctuations of disparity are greater for IADL than ADL disability.

There are several dips (1984, 1995, 2000, and 2004) where blacks actually had advantages over whites on both types of disability; however, the race × period interactions for these years were not significant.

KEY FINDINGS: Disparity Trends in Disability by Cohort & GenderExcept for a few cohort variations, the ADL

disparity for both men and women remained quite stable between 1905 and 1930 cohorts.

The cohort-based IADL disparity trend for men follow closely to the cohort-based ADL disparity trend.

However, there is a persistent increase (except the two most recent cohorts) of IADL disparity across each successive cohort among women. This is consistent with the general increase of IADL disability across cohorts (slide #14).

ACKNOWLEDGEMENTSThis project was supported

by Award Number R01MD004025 from the National Institute on Minority Health and Health Disparities (NIMHD).

The content of this presentation is solely the responsibility of the authors and does not necessarily represent the official views of the NIMHD or the National Institute of Health.