Alcohol consumption after health deterioration in older adults: a mixed-methods study

Objective To examine if and how older adults modify their drinking after health deterioration, and the factors that motivate changing or maintaining stable drinking behaviour. Study design Explanatory follow-up mixed-methods research. Methods The association between health deterioration and changes in alcohol consumption was examined using secondary data from the English Longitudinal Study of Ageing, a biennial prospective cohort study of a random sample of adults aged 50 years and older living in England. Data were collected through a personal interview and self-completion questionnaire across three waves between 2004 and 2009. The sample size (response rate) across the three waves was 8781 (49.9%), 7168 (40.3%) and 6623 (37.3%). The Chi-squared test was used to examine associations between diagnosis with a long-term condition or a worsening of self-rated health (e.g. from good to fair or fair to poor) and changes in drinking frequency (e.g. everyday, 5–6 days per week, etc.) and volume (ethanol consumed on a drinking day) between successive waves. In-depth interviews with 19 older adults recently diagnosed with a long-term condition were used to explore the factors that influenced change or maintenance in alcohol consumption over time. A purposive sampling strategy was used to recruit a diverse sample of current and former drinkers from voluntary and community organizations in the north of England. An inductive approach was used to analyze the data, facilitating the development of an a posteriori framework for understanding drinking change. Results There was no significant relationship between health deterioration and changes in drinking volume over time. There was however a significant association between health deterioration and changes in drinking frequency between successive waves (χ2 = 15.24, P < 0.001 and χ2 = 17.28, P < 0.001). For example, of participants reporting health deterioration between the first two waves, 47.6% had stable drinking frequency, 23.4% increased their drinking frequency and 29% reported decreased drinking frequency. In comparison, of participants reporting no health deterioration, 52.7% reported stable frequency, 20.8% increased frequency and 26.4% decreased frequency. In qualitative interviews, older adults described a wide range of factors that influence changes in drinking behaviour: knowledge gained from talking to healthcare professionals, online and in the media; tangible negative experiences that were attributed to drinking; mood and emotions (e.g. joy); the cost of alcohol; pub closures; and changes in social roles and activities. Health was just one part of a complex mix of factors that influenced drinking among older adults. Conclusion Patterns of drinking change after health deterioration in older adults are diverse, including stable, increasing and decreasing alcohol consumption over time. Although health motivations to change drinking influence behaviour in some older adults, social and financial motivations to drink are also important in later life and thus a holistic approach is required to influence behaviour

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Increase in fracture risk following unintentional weight loss in postmenopausal women: The Global Longitudinal Study of Osteoporosis in Women

Increased fracture risk has been associated with weight loss in postmenopausal women but the time course over which this occurs has not been established. The aim of this study was to examine the effects of unintentional weight loss of ?10 lb (4.5?kg) in postmenopausal women on fracture risk at multiple sites up to 5 years following weight loss. Using data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) we analyzed the relationships between self-reported unintentional weight loss of ?10 lb at baseline, year 2, or year 3 and incident clinical fracture in the years following weight loss. Complete data were available in 40,179 women (mean age?±?SD 68?±?8.3 years). Five-year cumulative fracture rate was estimated using the Kaplan-Meier method, and adjusted hazard ratios for weight loss as a time-varying covariate were calculated from Cox multiple regression models. Unintentional weight loss at baseline was associated with a significantly increased risk of fracture of the clavicle, wrist, spine, rib, hip, and pelvis for up to 5 years following weight loss. Adjusted hazard ratios showed a significant association between unintentional weight loss and fracture of the hip, spine, and clavicle within 1 year of weight loss, and these associations were still present at 5 years. These findings demonstrate increased fracture risk at several sites after unintentional weight loss in postmenopausal women. This increase is seen as early as 1 year following weight loss, emphasizing the need for prompt fracture risk assessment and appropriate management to reduce fracture risk in this population