Factors That May Enhance Longevity: A Literature Review and a Comprehensive Update for Aesthetic Surgeons

Occupation-Based Life Expectancy: Actuarial Fairness in Determining Statutory Retirement Age

This study examines occupation-based differences in life expectancy and the extent to which health accounts for these differences. Twentyseven-year survival follow-up data were used from the Dutch population-based Longitudinal Aging Study Amsterdam (n = 2,531), initial ages 55-85 years. Occupation was based on longest-held job. Results show that the non-skilled general, technical and transport domains had an up to 3.5-year shorter life expectancy than the academic professions, accounting for the compositional characteristics age and gender. Statutory retirement age could be made to vary accordingly, by allowing a proportionally greater pension build-up in the shorter-lived domains. Health accounted for a substantial portion of the longevity difference, ranging from 20 to 66%, depending on the health indicator. Thus, health differences between occupational domains today can be used as a means to tailor retirement ages to individuals' risks of longevity. These data provide a proof of principle for the development of an actuarially fair method to determine statutory retirement ages.

The genetic predisposition to longevity acts through behavioral phenotypes in females

The discovery of genetic factors for the predisposition of longevity is promising but their functional role and clinical relevance remain largely unclear. Based on results from a large genome-wide association study (GWAS) on human longevity (N ≈ 390,000) we identified six phenotype categories belonging to behavioral and psychiatric traits showing significant genetic correlations using LD Hub. We validated these genetic correlations on the phenotype level in a general population sample using a polygenic risk score (PRS) based on the longevity GWAS as proxy for longevity (N ≈ 8190; Study of Health in Pomerania). The behavioral phenotypes education, smoking and body mass index (BMI) were highly associated with the PRS for longevity especially in females (p_education=0.003, p_smoking=0.049, p_BMI=2.0E-4) with increased rates for higher education, lower smoking rates and decrease in BMI attributed to a higher PRS for longevity. Moreover, the psychiatric phenotypes depression and subjective health complaints showed significant associations (p_DEPR=0.032, p_SHC=0.002) in females only. Generally, a higher genetic predisposition for longevity had a stronger association with behavioral phenotypes in females than in males. It is unclear what causes the higher ``behavioral heterogeneity'' in males but different biological mechanisms might be involved. Sensitivity analyses showed that the association for the PRS for longevity with BMI and smoking were robust against adjustment with the PRS for BMI and smoking. In conclusion, our analyses demonstrated that genetic information obtained from highly powered GWAS for longevity revealed a clear behavioral signature on the phenotype level in a smaller population based sample.