How Does Successful Aging Apply to Black Women? A Latent Class Analysis
View abstract on PubMed
Summary
This summary is machine-generated.Successful aging varies significantly among older Black women. This study identified six distinct aging profiles, revealing diverse experiences beyond a homogenous group.
Area Of Science
- Gerontology
- Sociology
- Public Health
Background
- Prior research indicates racial/ethnic and gender disparities in successful aging (SA).
- However, the heterogeneity of aging experiences within specific demographic groups remains underexplored.
- This study focuses on the diverse aging trajectories of older Black women.
Purpose Of The Study
- To investigate the heterogeneity of successful aging experiences among older Black women.
- To identify distinct subgroups based on various health and social factors.
- To provide a nuanced understanding of aging within this population.
Main Methods
- Utilized data from the 2010/2012 U.S. Health and Retirement Study.
- Included 1,186 Black women who completed the Psychosocial Leave-Behind Questionnaire.
- Employed latent class analysis with indicators of physical health, psychological well-being, social support/strain, and social engagement.
Main Results
- Identified six distinct latent classes of successful aging: infirm, isolated, taxed, independent, vivacious, and robust.
- The 'robust' class (16% of respondents) exhibited the highest physical and psychological well-being and social relations.
- The 'vivacious' class (23% of respondents) showed high well-being and engagement but were unpartnered, while 'infirm' and 'isolated' classes faced significant health and social challenges.
Conclusions
- Significant heterogeneity exists in the aging experiences of older Black women.
- While many face challenges, 39% of older Black women align well with successful aging frameworks.
- Future research and interventions must acknowledge and address the non-homogenous nature of aging in Black women.
Related Concept Videos
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Aging is a complex biological phenomenon influenced by various processes that affect cellular and systemic functions. Several prominent theories attempt to explain its mechanisms, highlighting cellular limitations, oxidative damage, and hormonal changes as central factors in aging.
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...

