Leo D. Westbury

Background: Comorbidity is common in older adults and is associated with lower physical activity (PA) and greater frailty risk. We assessed whether relationship status affects these relationships, using the Southampton Longitudinal Study of Ageing. Methods: 448 community-dwelling older participants (median age of 80 years) were analysed. A questionnaire ascertained relationship status, number of comorbidities, PA (Physical Activity Scale for the Elderly) and frailty components (weight loss, self-reported exhaustion, low PA, low self-reported walking speed, difficulty carrying 10 lb). Associations of number of comorbidities with physical activity and number of frailty components were examined using linear and Poisson regression, respectively. Models were adjusted for age, sex, BMI and smoking status and included an interaction term between number of comorbidities and relationship status. Sex-stratified analyses without interactions were also performed. Results: Evidence of interaction effects were weak (p > 0.14 for both tests). Among females, higher comorbidity was related to lower PA and a greater number of frailty components: difference in PA (95% CI) and multiplicative increase in number of frailty components (95% CI) per additional comorbidity was −0.10 (−0.17,−0.03) and 1.25 (1.16,1.34) respectively. Effect sizes for PA and number of frailty components were broadly similar among females when stratified according to relationship status. Associations were weaker among males (p > 0.27 for all associations). Conclusions: Evidence of relationship status modifying these associations was weak. Females with greater comorbidity had lower physical activity and more frailty components. Differences in observed strength of associations between males and females may reflect different comorbidity profiles.

Background: Few studies have examined changes in diet quality into old age, and related these changes to musculoskeletal outcomes. We examined this among Hertfordshire Cohort Study participants. Methods: In total, 178 individuals provided diet quality scores derived in 1998–2004, 2011 and 2017 (median age 64.0, 74.7 and 80.7) using principal component analysis of food frequency questionnaires; higher scores indicated healthier diets (more fruit and vegetables, oily fish and wholemeal bread, and less white bread, added sugar, full-fat dairy products, chips and processed meat). Pearson correlations between diet quality scores at each time-point were computed. Group-based trajectory modelling of diet quality scores was implemented; trajectory groups as predictors of musculoskeletal outcomes (history of hip/knee replacement, osteoporosis, fall in previous year, low grip strength, low gait speed) in 2017 were examined using logistic regression with age and sex included as covariates. Results: Diet quality showed moderate stability over time (0.64 < r < 0.74). Three trajectory groups were identified: low (29%), medium (51%), and high diet quality (20%). A higher diet quality group was related to greater odds (95% CI) of hip/knee replacement (1.85 (1.05, 3.26) per higher category); associations with other musculoskeletal outcomes were weak (p > 0.17). Conclusions: Weak associations were observed between diet quality trajectories and musculoskeletal outcomes. However, higher diet quality was related to increased likelihood of hip/knee joint replacement, potentially due to confounding by socioeconomic position. The stability of diet quality suggests individuals with poorer diets around age 65 are likely to maintain these patterns into old age and may benefit from targeted interventions.

Aims: To determine if the relationship between joint pain and sleep quality among individuals with osteoarthritis (OA) differs according to physical activity level among older adults. Methods: 169 community-dwelling older adults in the UK Hertfordshire Cohort Study (aged 71–80) with radiographic knee OA completed a questionnaire. This included: the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC); the Pittsburgh Sleep Quality Index (PSQI); the Longitudinal Aging Study Amsterdam Physical Activity Questionnaire; and the Hospital Anxiety and Depression (HAD) Scale. Logistic regression was used to examine the WOMAC knee pain score in relation to having poor sleep quality (PSQI > 5) with adjustment for sex, age, and anxiety and depression scores; analyses were performed with and without stratification by physical activity category (bottom sex-specific tertile vs. not). Results: Knee pain prevalence (WOMAC pain score > 0) was 40.7% among men and 46.6% among women; 37.0% of men and 50.0% of women reported poor sleep quality (PSQI > 5). Higher WOMAC pain scores were related to increased risk of poor sleep quality; odds ratio (95% CI) per unit increase in pain score: 1.15 (1.01,1.32), p = 0.038). Relationships were similar across physical activity levels. Conclusions: Relationships between joint pain and poor sleep quality among older adults with radiographic knee OA were similar, regardless of physical activity level. Our results highlight the high prevalence of both sleep disturbance and significant knee pain in this group, illustrating the need to consider supportive measures as appropriate in this population.

We investigated associations between ‘healthy dietary pattern’ scores, at ages 36, 43, 53 and 60–64 years, and body composition at age 60–64 years among participants from the MRC National Survey of Health and Development (NSHD). Principal component analyses of dietary data (food diaries) at age 60–64 years were used to calculate diet scores (healthy dietary pattern scores) at each age. Higher scores indicated healthier diets (higher consumption of fruit, vegetables and wholegrain bread). Linear regression was used to investigate associations between diet scores at each age and height-adjusted dual-energy X-ray absorptiometry-measured fat and lean mass measures at age 60–64 years. Analyses, adjusting for sex and other potential confounders (age, smoking history, physical activity and occupational class), were implemented among 692 men and women. At age 43, 53 and 60–64 years, higher diet scores were associated with lower fat mass index (FMI) and android:gynoid fat mass ratio; for example, in fully adjusted analyses, a standard deviation ( sd) increase in diet score at age 60–64 years was associated with an SD difference in mean FMI of −0·18 (95 % CI: −0·25, −0·10). In conditional analyses, higher diet scores at ages 43, 53 and 60–64 years (than expected from diet scores at younger ages) were associated with lower FMI and android:gynoid fat mass ratio in fully adjusted analyses. Diet scores at age 36 years had weaker associations with the outcomes considered. No associations regarding appendicular lean mass index were robust after full adjustment. This suggests that improvements in diet through adulthood are linked to beneficial effects on adiposity in older age.

Aims: We examined whether admission risk increases at a certain threshold of number of systems medicated or whether any increase confers greater admission risk in either sex in a community-dwelling cohort of older persons in Hertfordshire. This study uses a longitudinal retrospective study design. Methods: Data from 2997 men and women (aged 59–73 at baseline) were analyzed. Participants were followed up from baseline (1998–2004) until December 2018 using Hospital Episode Statistics and mortality data, reporting clinical outcomes using ICD-10 coding. Number of systems medicated in relation to mortality (all-cause, cancer-related, cardiovascular-related) and admission (any, neurological, cardiovascular, and respiratory) were examined using Cox regression. Results: Apart from cancer-related mortality among women, more systems medicated predicted increased risk of all events among both sexes (p ≤ 0.001). For ‘any’, cardiovascular and respiratory admissions, there were increases in risk for each category of number of systems medicated. For example, compared to men with no systems medicated, those with 1, 2 and > 2 systems medicated had hazard ratios (95% CI) for cardiovascular admissions of 1.82 (1.57,2.12), 2.39 (2.00,2.84) and 3.45 (2.84,4.20) respectively; estimates among women were 1.74 (1.44,2.11), 2.35 (1.92,2.88) and 3.40 (2.79,4.13). Conclusions: Increases in numbers of systems medicated conferred greater risk of admission in both sexes. Interventions aimed at reducing the burden of chronic disease in mid-late adulthood are required.

Aim: To examine the relationship between level of morbidity burden and long‐term risk of fractures, falls, and joint replacements in the community‐dwelling participants of the Hertfordshire Cohort Study. Methods: Data were analyzed from 2997 individuals (age 59–73 at baseline). Outcomes (fractures, falls, and lower limb joint replacements) were identified using ICD‐10 and OPCS‐4 codes from Hospital Episode Statistics data, available from baseline (1998–2004) until December 2018. Number of systems medicated (marker of morbidity level) in relation to risk of outcomes was examined using sex‐stratified Cox regression. Results: Among both men and women, a greater number of systems medicated was related to increased risk of falls ( P < 0.001) and lower limb joint replacements ( P < 0.003). More systems medicated was only related to increased risk of fracture among women ( P ‐values for trend of Geriatr Gerontol Int 2024; 24: 912–917 .

Background: Low grip strength and gait speed are associated with mortality. However, investigation of the additional mortality risk explained by these measures, over and above other factors, is limited. Aim: We examined whether grip strength and gait speed improve discriminative capacity for mortality over and above more readily obtainable clinical risk factors. Methods: Participants from the Health, Aging and Body Composition Study, Osteoporotic Fractures in Men Study, and the Hertfordshire Cohort Study were analysed. Appendicular lean mass (ALM) was ascertained using DXA; muscle strength by grip dynamometry; and usual gait speed over 2.4–6 m. Verified deaths were recorded. Associations between sarcopenia components and mortality were examined using Cox regression with cohort as a random effect; discriminative capacity was assessed using Harrell’s Concordance Index (C-index). Results: Mean (SD) age of participants (n = 8362) was 73.8(5.1) years; 5231(62.6%) died during a median follow-up time of 13.3 years. Grip strength (hazard ratio (95% CI) per SD decrease: 1.14 (1.10,1.19)) and gait speed (1.21 (1.17,1.26)), but not ALM index (1.01 (0.95,1.06)), were associated with mortality in mutually-adjusted models after accounting for age, sex, BMI, smoking status, alcohol consumption, physical activity, ethnicity, education, history of fractures and falls, femoral neck bone mineral density (BMD), self-rated health, cognitive function and number of comorbidities. However, a model containing only age and sex as exposures gave a C-index (95% CI) of 0.65(0.64,0.66), which only increased to 0.67(0.67,0.68) after inclusion of grip strength and gait speed. Conclusions: Grip strength and gait speed may generate only modest adjunctive risk information for mortality compared with other more readily obtainable risk factors.

Registry studies have suggested associations between relationship status and fracture risk. We considered associations between relationship status and incident fracture in the Hertfordshire Cohort Study, comprising community-dwelling older adults, and explored associations between socioeconomic and lifestyle factors with relationship status. 2997 participants completed a baseline questionnaire (1998–2004) and clinic visit. Participants were followed up until December 2018 using Hospital Episode Statistics, which report clinical outcomes using codes from the 10th revision of the International Classification of Diseases (ICD-10); these codes were used to ascertain incident fractures. Relationship status (not currently married/cohabiting vs currently married/cohabiting) at baseline was examined in relation to incident fracture using Cox regression. Associations between baseline characteristics and relationship status were examined using logistic regression. Mean baseline age was 66.2 years. 80% were married/cohabiting at baseline; 15% had an incident fracture (mean (SD) follow-up duration: 14.4 (4.5) years). The following were related to greater likelihood of not being married/cohabiting: older age (women only); higher BMI (women only); current smoking; high alcohol consumption (men only); poorer diet quality (men only); lower physical activity; leaving school before age 15 (women only); and not owning one’s home. Those not married/cohabiting had greater risk of incident fracture compared to those who were (age-adjusted hazard ratios (95% CI) 1.58 (1.06, 2.38) among men, 1.35 (1.06, 1.72) among women); associations were attenuated after accounting for the above factors associated with relationship status in the corresponding sex. This suggests that differences in health profiles and lifestyle according to relationship status may explain the association between relationship status and fracture risk.

Small noncoding RNAs (sncRNAs) are implicated in age‐associated pathologies, including sarcopenia and insulin resistance (IR). As potential circulating biomarkers, most studies have focussed on microRNAs (miRNAs), one class of sncRNA. This study characterized the wider circulating sncRNA transcriptome of older individuals and associations with sarcopenia and IR. sncRNA expression including miRNAs, transfer RNAs (tRNAs), tRNA‐associated fragments (tRFs), and piwi‐interacting RNAs (piRNAs) was measured in serum from 21 healthy and 21 sarcopenic Hertfordshire Sarcopenia Study extension women matched for age (mean 78.9 years) and HOMA2‐IR. Associations with age, sarcopenia and HOMA2‐IR were examined and predicted gene targets and biological pathways characterized. Of the total sncRNA among healthy controls, piRNAs were most abundant (85.3%), followed by tRNAs (4.1%), miRNAs (2.7%), and tRFs (0.5%). Age was associated (FDR < 0.05) with 2 miRNAs, 58 tRNAs, and 14 tRFs, with chromatin organization, WNT signaling, and response to stress enriched among gene targets. Sarcopenia was nominally associated ( p < .05) with 12 tRNAs, 3 tRFs, and 6 piRNAs, with target genes linked to cell proliferation and differentiation such as Notch Receptor 1 ( NOTCH1 ), DISC1 scaffold protein ( DISC1 ), and GLI family zinc finger‐2 ( GLI2 ). HOMA2‐IR was nominally associated (p<0.05) with 6 miRNAs, 9 tRNAs, 1 tRF, and 19 piRNAs, linked with lysine degradation, circadian rhythm, and fatty acid biosynthesis pathways. These findings identify changes in circulating sncRNA expression in human serum associated with chronological age, sarcopenia, and IR. These may have clinical utility as circulating biomarkers of ageing and age‐associated pathologies and provide novel targets for therapeutic intervention.

Background: Demographic changes worldwide are leading to pressures on health services, with hospital admissions representing an important contributor. Here, we report admission types experienced by older people and examine baseline risk factors for subsequent admission/death, from the community-based Hertfordshire Cohort Study. Methods: 2997 participants (1418 women) completed a baseline questionnaire and clinic visit to characterize their health. Participants were followed up from baseline (1998–2004, aged 59–73 years) until December 2018 using UK Hospital Episode Statistics and mortality data, which report clinical outcomes using ICD-10 coding. Baseline characteristics in relation to the risk of admission/death during follow-up were examined using sex-stratified univariate logistic regression. Results: During follow-up, 36% of men and 26% of women died and 93% of men and 92% of women had at least one hospital admission; 6% of men and 7% of women had no admissions and were alive at end of follow-up. The most common types of admission during follow-up were cardiovascular (ever experienced: men 71%, women 68%) and respiratory (men 40%, women 34%). In both sexes, baseline risk factors that were associated (p < 0.05) with admission/death during follow-up were older age, poorer SF-36 physical function, and poorer self-rated health. In men, manual social class and a history of smoking, and in women, higher BMI, not owning one’s home, and a minor trauma fracture since age 45, were also risk factors for admission/death. Conclusions: Sociodemographic factors were related to increased risk of admission/death but a small proportion experienced no admissions during this period, suggesting that healthy ageing is achievable.