28 June, 2019
Who are the women that live longer?
A new study from the Netherlands attempted to find markers that may predict higher longevity in women . A subgroup of the Netherlands Cohort Study (NLCS) consisted of those who were born in 1916-1917 and were followed until death or until reaching age 90 (in the years 2006-2007). Out of 2697 eligible women with complete data, 928 lived to be 90 and 1769 died at earlier ages. Lifestyle, dietary habits, reproductive and medical history, and cancer risk factors were collected when women were around age 70, using a self-administered 11-page questionnaire. Mortality was recorded based on a linkage with central national registries. The results were rather disappointing, as very few parameters were found to significantly correlate with longevity: age at first childbirth, and ever-use of HRT in women with an early menopause (< 50 years) were associated with the likelihood of reaching the age of 90 years. Many other variables, generally thought to be relevant to longevity, failed to show a linkage (i.e., age at menarche or at menopause, menstruation lifespan, history of childbirth).
Despite the universal wish to better understand the reasons why women live longer than men, and what might in general be the reasons for extreme longevity, this Dutch study did not provide definite answers. Interestingly for menopause specialists, ever-use of HRT in women entering menopause before age 50 did influence longevity.
Personally, I was not surprised to see the above results, since the issue of longevity is certainly very complex, involving genetic and medical, dietary, socio-economical, environmental and other factors. Just one example that might affect the outcomes of this particular cohort: the participating women were born during World War 1 and lived several years within their occupied country during World War 2. I would imagine that this might have had an impact on future health and disease, on physical and emotional parameters and on reproductive factors. Also, and not taking a view as an expert epidemiologist or a statistician, the fact that the cohort was rather small, and the variables tested were so many, makes it a-priori very difficult to reach significance for any potential association.