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Americans’ Changing Lives Study. Principal Investigators: James S. House, Ph.D. Paula M. Lantz, Ph.D. History. Original Team at U-M : James House James Lepkowski, Ron Kessler, Regula Herzog et al. Funded by NIA (NIH) and Robert Wood Johnson Foundation . Purpose.

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americans changing lives study

Americans’ Changing Lives Study

Principal Investigators:

James S. House, Ph.D.

Paula M. Lantz, Ph.D.

  • Original Team at U-M :
    • James House
    • James Lepkowski, Ron Kessler, Regula Herzog et al.
  • Funded by NIA (NIH) and Robert Wood Johnson Foundation
  • To increase understanding of how individual, household and contextual socioeconomic and psychosocial factors combine to create health and health disparities across the adult life course.
  • Driven by societal goals:
    • Reducing social inequalities in health
    • Postponing morbidity and functional limitations into closing years of the life span (compression of morbidity)
acl study design
ACL Study Design
  • Longitudinal cohort study
  • Stratified multistage area probability sample:
    • Age 25 and older (non-institutionalized)
    • Contiguous U.S.
    • Over-sampled 2:1 people 60+ and Blacks
  • Representative of July, 1986 U.S. population by sex, age and region
acl wave 1
ACL Wave 1


Face-to-face interviews (~86 minutes)


Response rate: 70% households

68% individuals

acl wave 2
ACL Wave 2


Face-to-face interviews


Response rate: 83% of survivors

acl wave 3
ACL Wave 3


Telephone Interviews


Response rate: 83% of survivors

acl wave 4
ACL Wave 4


Telephone Interviews


Response rate: 77% of survivors

health outcomes variables
Health Outcomes Variables


Self-rated health (5 category)

Functional impairment (physical)

Chronic Conditions

Cognitive impairment

Depressive symptoms

acl mortality
ACL Mortality

Annual searches using National Death Index

Probable matches are certified with death certificates from states

Cause of death coded from death certificates (ICD-9 and ICD-10)

Death by Wave 4: 1,184 respondents

32.7% of weighted sample

21.4% of unweighted sample

self rated health
Self-Rated Health

Wave 1:

Excellent/Very good 64.2%

Good 20.6%

Fair/Poor 15.2%

functional impairment
Functional Impairment

No limitation 84.7% (weighted)

Difficult/unable to do heavy

work around house (Low) 6.8%

Difficult/unable to climb stairs

or walk a few blocks (Moderate) 5.3%

Confined to bed or chair (Severe) 3.2%

chronic conditions
Chronic Conditions

Life Threatening and Debilitating

0 46.6% (weighted)

1 26.0%

2 14.5%

3 7.7%

4+ 5.4%

socioeconomic position
Socioeconomic Position
  • Income R and spouse
  • Education Wave 1 only
  • Wealth
  • Work status
  • Occupation
  • Sociodemographics
health risk behaviors
Health Risk Behaviors
  • Cigarette smoking
  • Alcohol use
  • Body Mass Index
  • Physical Activity
psychosocial risk factors
Psychosocial Risk Factors
  • Social integration (informal and formal)
  • Life Satisfaction
  • Social Relationships and Supports
  • Marital Relationships and Events
  • Personality Traits
  • Productive Activities
  • Paid/Unpaid Work
psychosocial risk factors19
Psychosocial Risk Factors
  • Stress: job, financial, marital, parental
  • Negative Life Events
  • Religion and World Views
  • Perceptions of Discrimination
  • Physical/Social Environment
  • Residential History
contextual variables
Contextual Variables
  • Non-public at this point
  • Addresses at all 4 waves geocoded and linked to
    • 60+ census tract variables for Census before and after wave
    • Environmental Protection Agency Toxic Release Inventory (TRI) geocoded data of polluting and hazardous waste business es and sites
articles by acl investigators
Articles by ACL Investigators
  • Burgard SA. Brand JE. House JS. Toward a better estimation of the effect of job loss on health. Journal of Health & Social Behavior. 48(4):369-84, 2007
  • Herd P. Goesling B. House JS. Socioeconomic position and health: the differential effects of education versus income on the onset versus progression of health problems. Journal of Health & Social Behavior. 48(3):223-38, 2007
  • Robert SA. Ruel E. Racial segregation and health disparities between Black and White older adults. Journals of Gerontology Series B-Psychological Sciences & Social Sciences. 61(4):S203-11, 2006
articles by acl investigators22
Articles by ACL Investigators
  • Lantz PM. House JS. Mero RP. Williams DR. Stress, life events, and socioeconomic disparities in health. Journal of Health & Social Behavior. 46(3):274-88, 2005
  • House JS. Lantz PM. Herd P. Continuity and change in the social stratification of aging and health over the life course. Journals of Gerontology Series B-Psychological Sciences & Social Sciences. 60 Spec No 2:15-26, 2005
  • Everson-Rose SA. House JS. Mero RP. Depressive symptoms and mortality risk in a national sample: confounding effects of health status. Psychosomatic Medicine. 66(6):823-30, 2004
other acl articles
Other ACL Articles
  • Shultz KS. Wang M. The influence of specific physical health conditions on retirement decisions.International Journal of Aging & Human Development. 65(2):149-61, 2007
  • Schnittker J. Look (closely) at all the lonely people: age and the social psychology of social support. Journal of Aging & Health. 19(4):659-82, 2007
  • Hinterlong JE. Race disparities in health among older adults: examining the role of productive engagement.Health & Social Work. 31(4):275-88, 2006 Nov.
other acl articles24
Other ACL Articles
  • Burr JA. Choi NG. Mutchler JE. Caro FG. Caregiving and volunteering: are private and public helping behaviors linked? Journals of Gerontology Series B-Psychological Sciences & Social Sciences. 60(5):S247-56, 2005
  • Collins AL. Smyer MA. The resilience of self-esteem in late adulthood.Journal of Aging & Health. 17(4):471-89, 2005
  • McKee SA. Maciejewski PK. Falba T. Mazure CM. Sex differences in the effects of stressful life events on changes in smoking status. Addiction. 98(6):847-55, 2003
compression of morbidity evidence from acl






Probability of No Limitations




Low Educ

Med Educ


High Educ












Compression of Morbidity: Evidence from ACL