Characteristics of baseline measurements were presented as means (standard deviations, SDs) and proportions. Longitudinal changes of BAs were presented in plots with individual level measurements illustrated by dots, lines, and broken lines. Average trajectories of BAs were estimated through mixed linear regression models as described above, each of which included fixed effects of the intercept, CA, and sex, and a random effect of intercept at the individual and twin-pair level. P-values for sex effects were obtained from fixed effects within the mixed linear model. In addition, an interaction term between each BA and CA in natural spline was introduced to the model, and P-values for sex interaction were determined by the likelihood ratio test comparing the models with and without the interaction term.

We estimated the repeated measures correlation coefficients between age and nine BAs using all complete measurements (Bakdash and Marusich, 2017). The correlation analyses were then replicated for CA and nine BA residuals to examine the correlations between the parts of BA residuals. We then transformed correlation coefficients to scaled squared Euclidean distances and performed hierarchical cluster analysis on BAs and BA residuals via Ward’s method.

We used the Cox regression model to estimate the association between baseline BAs and the risk of all-cause mortality. When repeated measurements were available, only the first BA assessment was included and referred to as the baseline BA. In all models, we used attained age as the underlying time scale and the five groups of birth year as strata. Left truncation and right censoring were accounted for in the estimations; that is individuals entering into the cohort is conditional on their survival at baseline ages, and follow-up time may stop before death occurs. Follow-up time started from the first available measurement (baseline measurement) and ended at the date when they died or were censored on August 16, 2018. In addition, robust standard errors were introduced to adjust for relatedness within twin pairs and subjects. To achieve a direct comparison of BA effects in relation to mortality risk, we standardized all nine BAs to the mean of zero and SD of one across all available measurements and replicated the transformation in the BA residuals, such that the estimated hazard ratios (HRs) could be interpreted as the relative risk of death associated with a one-SD increase in the level of BA or BA residual. In the first part of the survival analyses, all models accounted for only one BA (one-BA models). For those who had their BAs assessed for multiple times, the first available measurement was treated as the baseline measurement. For each BA, we estimated the association of BAs and BA residuals with mortality risk using two models, a univariate model and a multivariate model with sex, education, BMI, and smoking status as additional covariates. In the second part of the survival analyses, all nine BAs were accounted for altogether in the same survival model (multi-BA models). Similarly, two models with or without adjustment for common risk factors were estimated. Only BA residuals were taken into consideration in the second part of survival analyses to avoid biased results caused by collinearity within BAs.

P values were two-sided, and statistical significance was defined as p<0.05. All analyses were conducted using Stata 15.1 and R 3.6.0.

Note: The content above has been extracted from a research article, so it may not display correctly. Click HERE to view the original source.

Please log in to submit your questions online.
Your question will be posted on the Bio-101 website. We will send your questions to the authors of this protocol and Bio-protocol community members who are experienced with this method. you will be informed using the email address associated with your Bio-protocol account.

We use cookies on this site to enhance your user experience. By using our website, you are agreeing to allow the storage of cookies on your computer.