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Females live longer than males, and there are sex disparities in physical health and disease incidence. However, sex differences in biological aging have not been consistently reported and may differ depending on the measure used. This study aimed to determine the correlations between epigenetic age acceleration (AA), and other markers of biological aging, separately in males and females. We additionally explored the extent to which these AA measures differed according to socioeconomic characteristics, clinical markers, and diseases. Epigenetic clocks (HorvathAge, HannumAge, PhenoAge, GrimAge, GrimAge2, and DunedinPACE) were estimated in blood from 560 relatively healthy Australians aged ≥ 70 years (females, 50.7%) enrolled in the ASPREE study. A system-wide deficit accumulation frailty index (FI) composed of 67 health-related measures was generated. Brain age and subsequently brain-predicted age difference (brain-PAD) were estimated from neuroimaging. Females had significantly reduced AA than males, but higher FI, and there was no difference in brain-PAD. FI had the strongest correlation with DunedinPACE (range r: 0.21 to 0.24 in both sexes). Brain-PAD was not correlated with any biological aging measures. Significant correlations between AA and sociodemographic characteristics and health markers were more commonly found in females (e.g., for DunedinPACE and systolic blood pressure r= 0.2, p< 0.001) than in males. GrimAA and Grim2AA were significantly associated with obesity and depression in females, while in males, hypertension, diabetes, and chronic kidney disease were associated with these clocks, as well as DunedinPACE. Our findings highlight the importance of considering sex differences when investigating the link between biological age and clinical measures.

An international systematic review concluded that individuals with poor social health (social isolation, lack of social support or loneliness) are 30% more likely to develop coronary heart disease (CHD) and stroke. Notably, the two included Australian papers reported no association between social health and CHD or stroke. We undertook a systematic review and meta‐analysis to investigate the association between social isolation, lack of social support and loneliness and cardiovascular disease (CVD) incidence among people living in Australia and New Zealand. Four electronic databases were systematically searched for longitudinal studies published until June 2020. Two reviewers undertook title/abstract screen and one reviewer undertook full‐text screen and data extraction. Quality was assessed using the Newcastle – Ottawa Quality Assessment Scale. Of the 725 unique records retrieved, five papers met our inclusion criteria. These papers reported data from three Australian longitudinal datasets, with a total of 2137 CHD and 590 stroke events recorded over follow‐up periods ranging from 3 to 16 years. Reports of two CHD and two stroke outcomes were suitable for meta‐analysis. The included papers reported no association between social health and incidence of CVD in all fully adjusted models and most unadjusted models. Our systematic review is inconclusive as it identified only a few studies, which relied heavily on self‐reported CVD. Further studies using medical diagnosis of CVD, and assessing the potential influence of residential remoteness, are needed to better understand the relationship between social health and CVD incidence in Australia and New Zealand.

Background: Cognitive aging is a dynamic process in late life with significant heterogeneity across individuals.Objective: To review the evidence for latent classes of cognitive trajectories and to identify the associated predictors and outcomes.Methods: A systematic search was performed in MEDLINE and EMBASE for articles that identified two or more cognitive trajectories in adults. The study was conducted following the PRISMA statement.Results: Thirty-seven studies were included, ranging from 219 to 9,704 participants, with a mean age of 60 to 93.4 years. Most studies (n?=?30) identified distinct cognitive trajectories using latent class growth analysis. The trajectory profile commonly consisted of three to four classes with progressively decreasing baseline and increasing rate of decline—a ‘stable-high’ class characterized as maintenance of cognitive function at high level, a ‘minor-decline’ class or ‘stable-medium’ class that declines gradually over time, and a ‘rapid-decline’ class with the steepest downward slope. Generally, membership of better classes was predicted by younger age, being female, more years of education, better health, healthier lifestyle, higher social engagement and lack of genetic risk variants. Some factors (e.g., education) were found to be associated with cognitive function over time only within individual classes.Conclusion: Cognitive aging in late life is a dynamic process with significant inter-individual variability. However, it remains unclear whether similar patterns of cognitive aging are observed across all cognitive domains. Further research into unique factors which promote the maintenance of high-cognitive function is needed to help inform public policy.

•The association of first-generation disease-modifying therapy with disability was significantly different between nations, being positively associated with greater disability in New Zealand participants but not Australians (pinteraction = 0.015).•No differences between nations were seen in the relationship between disease-modifying therapy and relapse.•Importantly, while expected differences were seen in disability, likely reflecting the requirement for more active disease to qualify for government subsidy of disease-modifying therapy in NZ, no differences were seen for either fatigue or quality of life.