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What difference does the dependence between durations make? Insights for population studies of aging
1Max Planck Institute for Demographic Research, Rostock, Germany.
Lifetime Data Analysis
|April 24, 1999
Summary
Bivariate selection can skew aging studies. Twin study results on aging and disease heritability may not reflect true genetic changes due to selection biases in related individuals.
Area of Science:
- Gerontology
- Biostatistics
- Genetic Epidemiology
Background:
- Interpreting age-specific changes in aging indicators from related individuals requires accounting for bivariate selection.
- Selection biases can affect hazard rates and relative risks in twin studies, potentially misrepresenting genetic influences.
Purpose of the Study:
- To investigate how bivariate selection impacts the interpretation of age-specific aging parameters in genetic-epidemiological studies.
- To clarify the relationship between observed age-dependent changes in twin studies and actual genetic determination of aging and disease susceptibility.
Main Methods:
- Statistical modeling and analysis of empirical data.
- Simulation of bivariate selection effects on aging indicators.
- Cross-sectional study design for comparing monozygotic (MZ) and dizygotic (DZ) twins.
Main Results:
- Hazard rates in surviving twins may appear lower than in singletons due to selection, even with equal survival probabilities.
- The proportion of closely related pairs increases with age in mixed populations, irrespective of individual survival chances.
- Observed differences in chronic conditions between MZ and DZ twins, and age-dependent relative risks, may be artifacts of selection, not changes in genetic influence.
Conclusions:
- Age-specific genetic parameters and relative risks from twin studies must be interpreted cautiously due to bivariate selection.
- Observed age-related changes in heritability do not necessarily indicate changes in genetic determination of disease susceptibility over time.
- Bivariate selection is a critical confounder in aging research using related individuals, particularly twins.
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