Patterns of Cardiovascular Risk Factors in Old Age and Survival and Health Status at 90

Association of Later-Life Weight Changes With Survival to Ages 90, 95, and 100: The Women's Health Initiative

BACKGROUND

Associations of weight changes and intentionality of weight loss with longevity are not well described.

METHODS

Using longitudinal data from the Women's Health Initiative (N = 54 437; 61-81 years), we examined associations of weight changes and intentionality of weight loss with survival to ages 90, 95, and 100. Weight was measured at baseline, year 3, and year 10, and participants were classified as having weight loss (≥5% decrease from baseline), weight gain (≥5% increase from baseline), or stable weight (<5% change from baseline). Participants reported intentionality of weight loss at year 3.

RESULTS

A total of 30 647 (56.3%) women survived to ≥90 years. After adjustment for relevant covariates, 3-year weight loss of ≥5% vs stable weight was associated with lower odds of survival to ages 90 (OR, 0.67; 95% CI, 0.64-0.71), 95 (OR, 0.65; 95% CI, 0.60-0.71), and 100 (OR, 0.62; 95% CI, 0.49-0.78). Compared to intentional weight loss, unintentional weight loss was more strongly associated with lower odds of survival to age 90 (OR, 0.83; 95% CI, 0.74-0.94 and OR, 0.49; 95% CI, 0.44-0.55, respectively). Three-year weight gain of ≥5% vs stable weight was not associated with survival to age 90, 95, or 100. The pattern of results was similar among normal weight, overweight, and obese women in body mass index (BMI)-stratified analyses.

CONCLUSIONS

Weight loss of ≥5% vs stable weight was associated with lower odds of longevity, more strongly for unintentional weight loss than for intentional weight loss. Potential inaccuracy of self-reported intentionality of weight loss and residual confounding were limitations.

Role of endocrine PACAP in age-related diseases

Pituitary adenylate cyclase activating polypeptide (PACAP) is a conserved neuropeptide, which confers diverse anti-aging endocrine and paracrine/autocrine effects, including anti-apoptotic, anti-inflammatory and antioxidant action. The results of the in vivo and in vitro experiments show that increasing emphasis is being placed on the diagnostic/prognostic biomarker potential of this neuropeptide in a wide array of age-related diseases. After the initial findings regarding the presence and alteration of PACAP in different body fluids in physiological processes, an increasing number of studies have focused on the changes of its levels in various pathological conditions associated with advanced aging. Until 2016 - when the results of previous human studies were reviewed - a vast majority of the studies had dealt with age-related neurological diseases, like cerebrovascular and neurodegenerative diseases, multiple sclerosis, as well as some other common diseases in elderly such as migraine, traumatic brain injury and post-traumatic stress disorder, chronic hepatitis and nephrotic syndrome. The aim of this review is to summarize the old and the new results and highlight those 'classical' and emerging clinical fields in which PACAP may become subject to further investigation as a diagnostic and/or prognostic biomarker in age-related diseases.

Low-Density Lipoprotein Cholesterol, Structural Atherosclerosis, and Functional Atherosclerosis in Older Japanese

Aggressive endothelial repair results in the progression of both structural and functional atherosclerosis, while insufficient endothelial repair worsens functional but not structural atherosclerosis. Aging increases the risk of inadequate endothelial repair. Since low-density lipoprotein cholesterol (LDLc) activates endothelial repair, LDLc may be positively associated with structural atherosclerosis but inversely associated with functional atherosclerosis in older individuals. This cross-sectional study analyzed 1458 participants aged 60 to 79 years. We defined structural atherosclerosis as a carotid intima-media thickness (CIMT) of at least 1.1 mm and functional atherosclerosis as a cardio-ankle vascular index (CAVI) of at least 9.0. LDLc was significantly positively associated with structural atherosclerosis and significantly inversely associated with functional atherosclerosis, independently of known cardiovascular risk factors. For 1 standard increment of LDLc (28 mg/dL for men and 29 mg/dL for women), the odds ratios and 95% confidence intervals after adjustment for known cardiovascular risk factors were 1.28 (1.10, 1.50) for structural atherosclerosis and 0.85 (0.75, 0.96) for functional atherosclerosis. LDLc activates endothelial repair, which results in the development of structural atherosclerosis but maintains endothelial function in older individuals. To evaluate atherosclerosis in clinical practice, the combination of structural and functional assessment of atherosclerosis could be informative.

12-month survival in nonagenarians inside the Mugello study: on the way to live a century

Background

Life expectancy has increased over the last century and a growing number of people is reaching age 90 years and over. However, data on nonagenarians’ health trends are scarce due to difficulties in investigating this specific population. This study aims to identify risk factors for one-year mortality in nonagenarians using data collected within the “Mugello Study”.

Methods

Complete information on sociodemographic data, cognitive and functional status, lifestyle, medical history, and drug use was collected from 433 nonagenarians, as well as information about survival after 1 year from the interview.

Results

The sample included 314 women (72.5%) and 119 men (27.5%) with a median age of 92 years (range 90-99 years). The mortality rate was 20.3% (88 deaths). After adjustment for age and sex, a significantly higher risk of dying within 12 months was observed in individuals with more severe cognitive impairment (HR = 5.011, p < 0.001), more severe disability in basic activities of daily living (HR = 4.193, p < 0.001), sedentary lifestyle (HR = 3.367, p < 0.001), higher number of drugs assumed (HR = 1.118, p = 0.031), and kidney dysfunction (HR = 2.609, p = 0.004). When all the variables were included in the analysis, only older age (HR = 1.079, p = 0.048), lower cognitive function (HR = 2.859, p = 0.015), sedentary lifestyle (HR = 2.030, p = 0.026), and kidney dysfunction (HR = 2.322, p = 0.018) remained significantly associated with reduced survival.

Conclusions

Data from the Mugello study support the hypothesis that survival at 12 months in nonagenarians is not a stochastic process and that older age, reduced cognitive function, sedentary lifestyle, and the presence of kidney dysfunction are associated with mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02908-9.

Modelling of longitudinal data to predict cardiovascular disease risk: a methodological review

OBJECTIVE

The identification of methodology for modelling cardiovascular disease (CVD) risk using longitudinal data and risk factor trajectories.

METHODS

We screened MEDLINE-Ovid from inception until 3 June 2020. MeSH and text search terms covered three areas: data type, modelling type and disease area including search terms such as "longitudinal", "trajector*" and "cardiovasc*" respectively. Studies were filtered to meet the following inclusion criteria: longitudinal individual patient data in adult patients with ≥3 time-points and a CVD or mortality outcome. Studies were screened and analyzed by one author. Any queries were discussed with the other authors. Comparisons were made between the methods identified looking at assumptions, flexibility and software availability.

RESULTS

From the initial 2601 studies returned by the searches 80 studies were included. Four statistical approaches were identified for modelling the longitudinal data: 3 (4%) studies compared time points with simple statistical tests, 40 (50%) used single-stage approaches, such as including single time points or summary measures in survival models, 29 (36%) used two-stage approaches including an estimated longitudinal parameter in survival models, and 8 (10%) used joint models which modelled the longitudinal and survival data together. The proportion of CVD risk prediction models created using longitudinal data using two-stage and joint models increased over time.

CONCLUSIONS

Single stage models are still heavily utilized by many CVD risk prediction studies for modelling longitudinal data. Future studies should fully utilize available longitudinal data when analyzing CVD risk by employing two-stage and joint approaches which can often better utilize the available data.