Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data.

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α ). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index (ABI) metric, a transformation of α , and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α . Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical use in a large dataset.

Role of cardiovascular health factors in mediating social inequalities in the incidence of dementia in the UK: two prospective, population-based cohort studies.

Background: The contribution of modifiable risk factors to social inequalities in dementia, observed in longitudinal studies, remains unclear. We aimed to quantify the role of cardiovascular health factors, assessed using Life's Essential 8 (LE8) score, in mediating social inequalities in incidence of dementia and, for comparison, in incidence of stroke, coronary heart disease, and mortality. Methods: In this prospective, population-based cohort study, we collected data from the UK Whitehall II Study and UK Biobank databases. Participants were included if data were available on SEP, outcomes and LE8 (smoking, physical activity, diet, body mass index, blood pressure, fasting blood glucose, lipid levels, sleep duration). The primary outcome was incident dementia and secondary outcomes were stroke, coronary heart disease, and mortality. Outcomes were derived from electronic healthcare records. Socioeconomic position (SEP) was measured by occupation in Whitehall II and education in UK Biobank. Counterfactual mediation analysis was used to quantify the extent to which LE8 score explained the associations of SEP with all outcomes. Analyses involved Cox regression, accelerated failure time models, and linear regression; and were adjusted for age, sex, and ethnicity. Findings: Between 10.09.1985 and 29.03.1988, a total of 9688 participants (mean age ± SD 44.9 ± 6.0; 67% men) from the Whitehall II study, and between 19.12.2006 and 01.10.2010, 278,215 participants (mean age ± SD 56.0 ± 8.1; 47% men) from the UK Biobank were included. There were 606 and 4649 incident dementia cases over a median (interquartile range) follow-up of 31.7 (31.1-32.7) and 13.5 (12.7-14.1) years respectively in Whitehall II and UK Biobank. In Whitehall II, the hazard ratio was 1.85 [95% CI 1.42, 2.32] for the total effect of SEP on dementia and 1.20 [1.12, 1.28] for the indirect effect via the LE8, the proportion mediated being 36%. In UK Biobank, the total effect of SEP on dementia was 1.65 [1.54, 1.78]; the indirect effect was 1.11 [1.09, 1.12], and the proportion mediated was 24%. The proportions mediated for stroke, coronary heart disease, and mortality were higher, ranging between 34% and 63% in Whitehall II and between 36% and 50% in UK Biobank. Interpretation: In two well-characterised cohort studies, up to one third of the social inequalities in incidence of dementia was attributable to cardiovascular health factors. Promotion of cardiovascular health in midlife may contribute to reducing social inequalities in risk of dementia, in addition to cardiovascular diseases and all-cause mortality. This study used adult measures of SEP, further research is warranted using lifecourse measures of SEP. Funding: NIH (RF1AG062553).

Cross-sectional and longitudinal associations of obesity with disability between age 50 and 90 in the SHARE study.

BACKGROUND: Obesity is associated with disability but whether age and ageing modify this association remains unclear. We examined whether this association changes between 50 and 90 years, and whether change in disability rates over 14 years differs by body mass index (BMI) categories. METHODS: BMI and ADL-disability data on 28,453 individuals from 6 waves (2004-2018, SHARE study) were used to examine the cross-sectional absolute and relative associations, extracted at age 50, 60, 70, 80, and 90 years using logistic mixed models. Then baseline BMI and change in disability rates over 14-years were examined using logistic-mixed models. RESULTS: At age 50, the probabilities of ADL disability in individuals with BMI 30-34.9 and ≥35 kg/m² were 0.07 (0.06, 0.09) and 0.11 (0.09, 0.12), increasing to 0.47 (0.44, 0.50) and 0.55 (0.50, 0.60) at age 90; the increase in both these groups was greater than that in the normal-weight group (p for increase with age<0.001). On the relative scale the OR at age 50 in these obesity groups was 2.37 (1.79, 3.13) and 5.03 (3.38, 7.48), decreasing to 1.51 (1.20, 1.89) and 2.19 (1.50, 3.21) at age 90; p for decrease with age=0.05 and 0.02 respectively. The 14-year increase in probability of disability was greatest in those with BMI≥35 kg/m² at age 50, 60, and 70 at baseline: differences in increase compared to normal weight were 0.08 (0.02, 0.14), 0.11 (0.07, 0.15), and 0.09 (0.02, 0.16) respectively. CONCLUSIONS: ADL disability is increasingly prevalent with age in individuals with obesity. Relative measures of change obscure the association between obesity and disability due to age-related increase in disability rates in all groups.

Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data.

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index metric, an adaptation of α, and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α. Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical worth in a large dataset.

Role of age and sex in the association between BMI and functional limitations in stroke patients: Cross-sectional analysis in three European and US cohorts.

BACKGROUND: A U- or J-shaped association between BMI and different post-stroke outcomes is suggested. Thus, the aim is to evaluate the association between BMI with ADL, IADL and mobility limitations in the ageing post-stroke population at different ages, as well as the differences in this association by sex. METHODS: A total of 5,468 participants with stroke and 21,872 without stroke over 50 years of age were assessed for the number of limitations in basic or instrumental activities of daily living (ADL/IADL) as well as mobility tasks. The association between BMI at the interview (continuous time-dependent variable) and the level of limitations was assessed using a linear mixed model stratified by sex and stroke status. RESULTS: The association between BMI and ADL/IADL and mobility limitations were found to be significant in both men and women regardless of stroke status (p<0.001 for all). The association differs between those who have suffered a stroke and those who have not (p<0.001 for all). In ADL/IADL limitations, men with stroke showed a transition from an inverted J-shape to a U-shape association with age. In women, the BMI showed a less pronounced association between BMI and ADL/IADL limitations compared to men but with similar trends. A effect of sex was observed in the association between BMI and mobility, with women with and without stroke showing a linear association that differed from the inverted J-shaped or U-shaped association of men. CONCLUSION: Our results suggest that BMI is associated with limitations in ADL, IADL and mobility in stroke patients. In addition, this association differs between men and women and is also influenced by age.

Change in lipids before onset of dementia, coronary heart disease, and mortality: A 28-year follow-up Whitehall II prospective cohort study.

INTRODUCTION: The association of lipids with dementia remains a subject of debate. Using data from 7,672 participants of the Whitehall II prospective cohort study, we examined whether timing of exposure, length of follow-up, or sex modifies this association. METHODS: Twelve markers of lipid levels were measured from fasting blood and eight among them a further five times. We performed time-to-event as well as trajectory analyses. RESULTS: No associations were observed in men; in women most lipids were associated with the risk of dementia, but only for events occurring after the first 20 years of follow-up. Differences in lipid trajectories in men emerged only in the years immediately before diagnosis whereas in women total cholesterol (TC), LDL-cholesterol (LDL-C), non-HDL-cholesterol (non-HDL-C), TC/HDL-C, and LDL-C/HDL-C were higher in midlife among dementia cases before declining progressively. DISCUSSION: Abnormal lipid levels in midlife seem to be associated with a higher risk of dementia in women.

Identification of physical activity and sedentary behaviour dimensions that predict mortality risk in older adults: Development of a machine learning model in the Whitehall II accelerometer sub-study and external validation in the CoLaus study.

Background: Identification of new physical activity (PA) and sedentary behaviour (SB) features relevant for health at older age is important to diversify PA targets in guidelines, as older adults rarely adhere to current recommendations focusing on total duration. We aimed to identify accelerometer-derived dimensions of movement behaviours that predict mortality risk in older populations. Methods: We used data on 21 accelerometer-derived features of daily movement behaviours in 3991 participants of the UK-based Whitehall II accelerometer sub-study (25.8% women, 60-83 years, follow-up: 2012-2013 to 2021, mean = 8.3 years). A machine-learning procedure was used to identify core PA and SB features predicting mortality risk and derive a composite score. We estimated the added predictive value of the score compared to traditional sociodemographic, behavioural, and health-related risk factors. External validation in the Switzerland-based CoLaus study (N = 1329, 56.7% women, 60-86 years, follow-up: 2014-2017 to 2021, mean = 3.8 years) was conducted. Findings: In total, 11 features related to overall activity level, intensity distribution, bouts duration, frequency, and total duration of PA and SB, were identified as predictors of mortality in older adults and included in a composite score. Both in the derivation and validation cohorts, the score was associated with mortality (hazard ratio = 1.10 (95% confidence interval = 1.05-1.15) and 1.18 (1.10-1.26), respectively) and improved the predictive value of a model including traditional risk factors (increase in C-index = 0.007 (0.002-0.014) and 0.029 (0.002-0.055), respectively). Interpretation: The identified accelerometer-derived PA and SB features, beyond the currently recommended total duration, might be useful for screening of older adults at higher mortality risk and for diversifying PA and SB targets in older populations whose adherence to current guidelines is low. Funding: National Institute on Aging; UK Medical Research Council; British Heart Foundation; Wellcome Trust; French National Research Agency; GlaxoSmithKline; Lausanne Faculty of Biology and Medicine; Swiss National Science Foundation.

Trajectories of physical and mental functioning over 25 years before onset of frailty: results from the Whitehall II cohort study.

BACKGROUND: Research on frailty, a major contributor to heterogeneity in health, is undertaken on older adults although the processes leading to frailty are likely to begin earlier in the life course. Using repeat data spanning 25 years, we examined changes in physical and mental functioning before the onset of frailty, defined using Fried's frailty phenotype (FFP). METHODS: Functioning was measured using the Short-Form 36 General Health Survey (SF-36) on nine occasions from 1991 (age range 40-63 years) to 2015 (age range 63-85 years). The poorest of four FFP scores from 2002, 2007, 2012 and 2015 was used to classify participants as frail, pre-frail, or robust. We used linear mixed models with a backward timescale such that time 0 was the person-specific date of frailty classification for frail and pre-frail participants and the end of follow-up for robust participants. Analyses adjusted for socio-demographic factors, health behaviours, body mass index and multi-morbidity status were used to compare SF-36 physical (PCS) and mental (MCS) component summary scores over 25 years before time 0 as a function of FFP classification, with estimates extracted at time 0, -5, -10, -15, -20 and -25 years. We also used illness-death models to examine the prospective association between SF-36 component summary scores at age 50 and incident FFP-defined frailty. RESULTS: Among 7044 participants of the Whitehall II cohort study included in the analysis [29% female, mean age 49.7 (SD = 6.0) at baseline in 1991], 2055 (29%) participants remained robust, and 4476 (64%) became pre-frail and 513 (7%) frail during follow-up. Frail compared with robust participants had lower SF-36 scores at t = -25 before onset of frailty with a difference of 3.4 [95% confidence interval (CI) 1.6, 5.1] in PCS and 1.8 (-0.2, 3.8) in MCS. At t = 0, the differences increased to 11.5 (10.5, 12.5) and 9.1 (8.0, 10.2), respectively. The differences in SF-36 between the robust and pre-frail groups, although smaller [at t = 0, 1.7 (1.2, 2.2) in PCS and 4.0 (3.4, 4.5) in MCS], were already observed 20 and 25 years, respectively, before the onset of pre-frailty. Prospective analyses showed that at age 50, scores in the bottom quartiles of PCS [hazard ratio (HR) compared with the top quartile = 2.39, 95% CI 1.85, 3.07] and MCS [HR = 1.49 (1.15, 1.93)] were associated with a higher risk of FFP-defined frailty at older ages. CONCLUSIONS: Differences in trajectories of physical and mental functioning in individuals who developed physical frailty at older ages were observable 25 years before onset of FFP-defined frailty. These findings highlight the need for a life course approach in efforts to prevent frailty.

The role of age, sex, and multimorbidity in 7-year change in prevalence of limitations in adults 60-94 years.

Recent data suggest a temporal trend in decline in functional limitations in older adults but whether this trend extends to the period after the 8th decade of life remains unclear. We examined change in prevalence of limitations in activities and instrumental activities of daily living (ADL and IADL) between 2008 and 2015 among adults of 60-94 years and the role of age, sex, multimorbidity; we also examined changes in severity of limitations. Data were drawn from two nationally representative surveys in 2008 (n = 13,593) and 2015 (n = 13,267). The 6-item scales of ADL and IADL were each categorized first as ≥ 1 limitations, and then to examine severity as 0, 1-2, and ≥ 3 limitations. Weighted logistic and multinomial regressions were used to estimate prevalence of limitations; the difference between surveys were extracted every 5 years between 60 and 90 years. The prevalence of ≥ 1 ADL declined between 2008 and 2015, from age 75 (- 1.2%; 95%CI = - 2.0, - 0.4%) to age 90 (- 8.8%; 95%CI = - 12.7, - 5.0%). This decline was more pronounced in men than women (p-value for interaction = 0.05) and observed primarily in those with multimorbidity (p-value for interaction = 0.06). Up to 2 ADL limitations declined from age 75 (- 1.0; 95%CI = - 1.7, - 0.3) to 90 (- 6.7; 95%CI = - 9.9, - 3.6) and from age 80 (- 0.6; 95%CI = - 1.1, 0.1) to 85 (- 1.2; 95%CI = - 2.2, - 0.1) for ≥ 3 ADL limitations. There was no substantial change in IADL limitations. These data from a high-income country with universal health care show improvement in ADL even after the 8th decade of life despite increase in multimorbidity.

Circulating serum metabolites as predictors of dementia: a machine learning approach in a 21-year follow-up of the Whitehall II cohort study.

BACKGROUND: Age is the strongest risk factor for dementia and there is considerable interest in identifying scalable, blood-based biomarkers in predicting dementia. We examined the role of midlife serum metabolites using a machine learning approach and determined whether the selected metabolites improved prediction accuracy beyond the effect of age. METHODS: Five thousand three hundred seventy-four participants from the Whitehall II study, mean age 55.8 (standard deviation (SD) 6.0) years in 1997-1999 when 233 metabolites were quantified using nuclear magnetic resonance metabolomics. Participants were followed for a median 21.0 (IQR 20.4, 21.7) years for clinically-diagnosed dementia (N=329). Elastic net penalized Cox regression with 100 repetitions of nested cross-validation was used to select models that improved prediction accuracy for incident dementia compared to an age-only model. Risk scores reflecting the frequency with which predictors appeared in the selected models were constructed, and their predictive accuracy was examined using Royston's R2, Akaike's information criterion, sensitivity, specificity, C-statistic and calibration. RESULTS: Sixteen of the 100 models had a better c-statistic compared to an age-only model and 15 metabolites were selected at least once in all 16 models with glucose present in all models. Five risk scores, reflecting the frequency of selection of metabolites, and a 1-SD increment in all five risk scores was associated with higher dementia risk (HR between 3.13 and 3.26). Three of these, constituted of 4, 5 and 15 metabolites, had better prediction accuracy (c-statistic from 0.788 to 0.796) compared to an age-only model (c-statistic 0.780), all p<0.05. CONCLUSIONS: Although there was robust evidence for the role of glucose in dementia, metabolites measured in midlife made only a modest contribution to dementia prediction once age was taken into account.

Pre-stroke Disability and Long-Term Functional Limitations in Stroke Survivors: Findings From More of 12 Years of Follow-Up Across Three International Surveys of Aging.

Background: Almost 50% of the post-stroke disabled population already have a premorbid disability before stroke. These patients may be offered a different care pathway in the acute and subacute phase than those without pre-morbid disability. Therefore, the aim of this study was to assess the association of the severity of premorbid disability with change of limitations in basic and instrumental activities of daily living (ADL/IADL) 1 year after stroke and over the following decade. Methods: Among 3,432 participants from HRS, SHARE and ELSA cohorts with a first stroke, ADL/IADL limitations were measured at 1-2 years prior to stroke, at 1 year post-stroke, and during the chronic phase. Modified Ranking Scale (P-mRS) was used to categorize the participants by level of premorbid disability (1-2 years pre-stroke). Change in ADL/IADL limitations by P-mRS level (0-1, 2-3, and 4-5) was assessed using a piecewise linear mixed model with a breakpoint set at 1 year post-stroke, stratified by median age groups. Results: Increase in ADL limitations at 1 year post-stroke was less pronounced in P-mRS ≥2 (p < 0.005). After years of relative stability, limitations of ADL increased for all P-mRS levels (p = 0.003). In those aged ≥75 years at stroke event, the increase was similar irrespective of P-mRS (p = 0.090). There were no significant differences in IADL trajectories between P-mRS levels (p ≥ 0.127). Conclusion: These results suggest similar trajectories of functional limitations between P-mRS levels up to 9 years post-stroke, highlighting the possible benefit of including patients with pre-morbid disability to certain treatments during the acute phase.

Individual Barriers to an Active Lifestyle at Older Ages Among Whitehall II Study Participants After 20 Years of Follow-up.

Importance: Identification of individual-level barriers associated with decreased activity in older age is essential to inform effective strategies for preventing the health outcomes associated with high sedentary behavior and lack of physical activity during aging. Objective: To assess cross-sectional and prospective associations of a large set of factors with objectively assessed sedentary time and physical activity at older age. Design, Setting, and Participants: This population-based cohort study was conducted among participants in the Whitehall II accelerometer substudy with accelerometer data assessed in 2012 to 2013. Among 4880 participants invited to the accelerometer substudy, 4006 individuals had valid accelerometer data. Among them, 3808 participants also had factors assessed in 1991 to 1993 (mean [SD] follow-up time, 20.3 [0.5] years), 3782 participants had factors assessed in 2002 to 2004 (mean [SD] follow-up time, 9.1 [0.3] years), and 3896 participants had factors assessed in 2012 to 2013 (mean follow up time, 0 years). Data were analyzed from May 2020 through July 2021. Exposures: Sociodemographic factors (ie, age, sex, race and ethnicity, occupational position, and marital status), behavioral factors (ie, smoking, alcohol intake, and fruit and vegetable intake), and health-related factors (ie, body mass index, 36-Item Short Form Health Survey (SF-36) physical and mental component summary scores [PCS and MCS], and number of chronic conditions) were assessed among 3808 individuals in 1991 to 1993; 3782 individuals in 2002 to 2004; and 3896 individuals in 2012 to 2013. High alcohol intake was defined as more than 14 units of alcohol per week, and high fruit and vegetable intake was defined as twice daily or more. Main Outcomes and Measures: Accelerometer-assessed time spent in sedentary behavior, light-intensity physical activity (LIPA), and moderate to vigorous physical activity (MVPA) in 2012 to 2013 were analyzed in 2021 using multivariate linear regressions. Results: A total of 3896 participants (986 [25.3%] women; age range, 60-83 years; mean [SD] age, 69.4 [5.7] years) had accelerometer data and exposure factors available in 2012 to 2013. Older age, not being married or cohabiting, having overweight, having obesity, more chronic conditions, and poorer SF-36 PCS, assessed in midlife or later life, were associated with increased sedentary time at the expense of time in physical activity. Mean time differences ranged from 9.8 min/d (95% CI, 4.1 to 15.6 min/d) of sedentary behavior per 10-point decrease in SF-36 PCS to 51.4 min/d (95% CI, 37.2 to65.7 min/d) of sedentary behavior for obesity vs reference range weight, from -6.2 min/d (95% CI, -8.4 to -4.1 min/d) of LIPA per 5 years of age to -28.0 min/d (95% CI, -38.6 to -17.4 min/d) of LIPA for obesity vs reference range weight, and from -5.3 min/d (95% CI, -8.2 to -2.4 min/d) of MVPA per new chronic condition to -23.4 min/d (95% CI, -29.2 to -17.6 min/d) of MVPA for obesity vs reference range weight in 20-year prospective analyses for men. There was also evidence of clustering of behavioral factors: high alcohol intake, high fruit and vegetable consumption, and no current smoking were associated with decreased sedentary time (mean time difference in cross-sectional analysis in men: -12.7 min/d [95% CI, -19.8 to -5.5 min/d]; -6.0 min/d [95% CI, -12.3 to -0.2]; and -37.4 min/d [95% CI, - 56.0 to -18.8 min/d], respectively) and more physical activity. Conclusions and Relevance: This study found a large range of individual-level barriers associated with a less active lifestyle in older age, including sociodemographic, behavioral, and health-related factors. These barriers were already evident in midlife, suggesting the importance of early implementation of targeted interventions to promote physical activity and reduce sedentary time.

Association between age at onset of multimorbidity and incidence of dementia: 30 year follow-up in Whitehall II prospective cohort study.

OBJECTIVE: To examine the association of midlife and late life multimorbidity, including severity of multimorbidity, with incident dementia. DESIGN: Prospective cohort study. SETTING: Civil service departments in London (Whitehall II study, study inception in 1985-88). PARTICIPANTS: 10 095 participants, aged 35 to 55 at baseline. MAIN OUTCOME MEASURE: Incident dementia at follow-up between 1985 and 2019. Cause specific Cox proportional hazards regression was used to examine the association of multimorbidity overall and at age 55, 60, 65, and 70 with subsequent dementia, taking into account the competing risk of death. RESULTS: The prevalence of multimorbidity (≥2 chronic diseases) was 6.6% (655/9937) at age 55 and 31.7% (2464/7783) at age 70; 639 cases of incident dementia occurred over a median follow-up of 31.7 years. After adjustment for sociodemographic factors and health behaviours, multimorbidity at age 55 was associated with subsequent risk of dementia (difference in incidence rate per 1000 person years 1.56, 95% confidence interval 0.62 to 2.77; hazard ratio 2.44, 95% confidence interval 1.82 to 3.26). The association weakened progressively with older age at onset of multimorbidity. At age 65, onset of multimorbidity before age 55 was associated with 3.86 (1.80 to 6.52) per 1000 person years higher incidence of dementia (hazard ratio 2.46, 1.80 to 2.26) and onset between 60 and 65 was associated with 1.85 (0.64 to 3.39) per 1000 person years higher incidence (1.51, 1.16 to 1.97). Severity of multimorbidity (≥3 chronic diseases) at age 55 was associated with a 5.22 (1.14 to 11.95) per 1000 person years higher incidence of dementia (hazard ratio 4.96, 2.54 to 9.67); the same analyses at age 70 showed 4.49 (2.33 to 7.19) per 1000 person years higher incidence (1.65, 1.25 to 2.18). CONCLUSION: Multimorbidity, particularly when onset is in midlife rather than late life, has a robust association with subsequent dementia. The increasingly younger age at onset of multimorbidity makes prevention of multimorbidity in people with a first chronic disease important.

Sex differences in functional limitations and the role of socioeconomic factors: a multi-cohort analysis.

BACKGROUND: Women are more likely to have functional limitations than are men, partly because of greater socioeconomic disadvantage. However, how sex differences vary by severity of functional limitations remains unclear. We examined sex differences in functional limitations, with attention to socioeconomic factors and severity of limitations. METHODS: Longitudinal data on limitations in basic activities of daily living (ADL) and instrumental activities of daily living (IADL) and mobility activities were drawn from 62 375 participants from 14 countries. For ADL, IADL, and mobility, participants were categorised based on number of limited activities (0, 1, 2, or ≥3). Sex differences in limitations in four birth cohorts (1895-1929, 1930-38, 1939-45, and 1946-60) were analysed before and after adjustment for socioeconomic factors (education and labour force status). FINDINGS: The prevalence of IADL and ADL limitations was higher in women than in men. After adjustment for socioeconomic factors, this sex difference was attenuated. The sex difference in IADL limitations at age 75 years (in the 1895-1929 cohort) was 3·7% before adjustment for socioeconomic factors (95% CI 2·6-4·7) and 1·7% (1·1-2·2) after adjustment. For ADL, the sex difference in limitations at age 75 years (in the 1895-1929 cohort) was 3·2% (2·3-4·1) before adjustment for socioeconomic factors and 1·4% (0·9-1·8) after adjustment. Sex differences in mobility limitations (16·1%, 95% CI 14·4-17·7) remained after adjustment for socioeconomic factors (14·3%, 12·7-15·9). After age 85 years, women were more likely to have three or more IADL or mobility limitations and men were more likely to have one or two limitations. INTERPRETATION: Socioeconomic factors largely explain sex differences in IADL and ADL limitations but not mobility. Sex differences in mobility limitations in midlife are important targets for future research and interventions. FUNDING: National Institute on Aging, UK National Institute for Health Research, European Commission, and US Social Security Administration.

Terminal decline in objective and self-reported measures of motor function before death: 10 year follow-up of Whitehall II cohort study.

OBJECTIVES: To examine multiple objective and self-reported measures of motor function for their associations with mortality. DESIGN: Prospective cohort study. SETTING: UK based Whitehall II cohort study, which recruited participants aged 35-55 years in 1985-88; motor function component was added at the 2007-09 wave. PARTICIPANTS: 6194 participants with motor function measures in 2007-09 (mean age 65.6, SD 5.9), 2012-13, and 2015-16. MAIN OUTCOME MEASURES: All cause mortality between 2007 and 2019 in relation to objective measures (walking speed, grip strength, and timed chair rises) and self-reported measures (physical component summary score of the SF-36 and limitations in basic and instrumental activities of daily living (ADL)) of motor function. RESULTS: One sex specific standard deviation poorer motor function in 2007-09 (cases/total, 610/5645) was associated with an increased mortality risk of 22% (95% confidence interval 12% to 33%) for walking speed, 15% (6% to 25%) for grip strength, 14% (7% to 23%) for timed chair rises, and 17% (8% to 26%) for physical component summary score over a mean 10.6 year follow-up. Having basic/instrumental ADL limitations was associated with a 30% (7% to 58%) increased mortality risk. These associations were progressively stronger when measures were drawn from 2012-13 (mean follow-up 6.8 years) and 2015-16 (mean follow-up 3.7 years). Analysis of trajectories showed poorer motor function in decedents (n=484) than survivors (n=6194) up to 10 years before death for timed chair rises (standardised difference 0.35, 95% confidence interval 0.12 to 0.59; equivalent to a 1.2 (men) and 1.3 (women) second difference), nine years for walking speed (0.21, 0.05 to 0.36; 5.5 (men) and 5.3 (women) cm/s difference), six years for grip strength (0.10, 0.01 to 0.20; 0.9 (men) and 0.6 (women) kg difference), seven years for physical component summary score (0.15, 0.05 to 0.25; 1.2 (men) and 1.6 (women) score difference), and four years for basic/instrumental ADL limitations (prevalence difference 2%, 0% to 4%). These differences increased in the period leading to death for timed chair rises, physical component summary score, and ADL limitations. CONCLUSION: Motor function in early old age has a robust association with mortality, with evidence of terminal decline emerging early in measures of overall motor function (timed chair rises and physical component summary score) and late in basic/instrumental ADL limitations.

Comparison of the predictive accuracy of multiple definitions of cognitive impairment for incident dementia: a 20-year follow-up of the Whitehall II cohort study.

BACKGROUND: Studies generally use cognitive assessment done at one timepoint to define cognitive impairment in order to examine conversion to dementia. Our objective was to examine the predictive accuracy and conversion rate of seven alternate definitions of cognitive impairment for dementia. METHODS: In this prospective study, we included participants from the Whitehall II cohort study who were assessed for cognitive impairment in 2007-09 and were followed up for clinically diagnosed dementia. Algorithms based on poor cognitive performance (defined using age-specific and sex-specific thresholds, and subsequently thresholds by education or occupation levels) and objective cognitive decline (using data from cognitive assessments in 1997-99, 2002-04, and 2007-09) were used to generate seven alternate definitions of cognitive impairment. We compared predictive accuracy using Royston's R 2, the Akaike information criterion (AIC), sensitivity, specificity, and Harrell's C-statistic. FINDINGS: 5687 participants, with a mean age of 65·7 years (SD 5·9) in 2007-09, were included and followed up for a median of 10·5 years (IQR 10·1-10·9). Over follow-up, 270 (4·7%) participants were clinically diagnosed with dementia. Cognitive impairment defined using both cognitive performance and decline had higher hazard ratios (from 5·08 [95% CI 3·82-6·76] to 5·48 [4·13-7·26]) for dementia than did definitions based on cognitive performance alone (from 3·25 [2·52-4·17] to 3·39 [2·64-4·36]) and cognitive decline alone (3·01 [2·37-3·82]). However, all definitions had poor predictive performance (C-statistic ranged from 0·591 [0·565-0·616] to 0·631 [0·601-0·660]), primarily due to low sensitivity (21·6-48·4%). A predictive model containing age, sex, and education without measures of cognitive impairment had better predictive performance (C-statistic 0·783 [0·758-0·809], sensitivity 74·2%, specificity 72·2%) than all seven definitions of cognitive impairment (all p<0·0001). INTERPRETATION: These findings suggest that cognitive impairment in early old age might not be useful for dementia prediction, even when it is defined using longitudinal data on cognitive decline and thresholds of poor cognitive performance additionally defined by education or occupation. FUNDING: National Institutes of Health, UK Medical Research Council.

Asthma is associated with frailty among community-dwelling adults: the GAZEL cohort.

INTRODUCTION: Early management of chronic respiratory diseases (CRDs) and frailty have been identified as key targets towards healthy ageing, but the association between CRDs and frailty has been poorly investigated. We studied the association between asthma and frailty in adults of the GAZEL cohort using different definitions of asthma over the 26 years of follow-up. METHODS: Current asthma definitions are based on yearly self-reports of symptoms or medication (in 2015, constant reports or at least one report between 1990 and 2015), or on a detailed respiratory symptoms questionnaire in 2002. Frailty definition is based on weakness, fatigue, unintentional weight loss, low physical activity and mobility in 2015. Frail participants had three criteria or more, pre-frail 1 or 2, and robust 0. Multinomial regression models adjusted for age, sex, body mass index, smoking, education, marital status and comorbidities were performed. RESULTS: In 2015, 12 345 adults (73% men, 61 to 77 years old) were included: 3% of them reported current asthma, 1.6% had constant reports during the follow-up and 9% reported current asthma at least once. In 2015, 6% were frail, 34% pre-frail and 13% of current asthmatics and 6% of non-asthmatics were frail (adjusted OR (aOR) 2.19 (1.44 to 3.34)). Significant associations were also found with the 2002 definition (aOR 2.24 (1.73 to 2.90)), constant reports (aOR 3.67 (1.70 to 7.93)) or at least once (aOR 1.50 (1.15 to 1.98)). Current asthma was also associated with pre-frailty with the 2002 definition (aOR 1.46 (1.26 to 1.68)). DISCUSSION: Participants with asthma had increased risk of frailty. A better understanding of their relationship could help to define and evaluate strategies for a better ageing of asthmatics.

Association Between Life-Course Obesity and Frailty in Older Adults: Findings in the GAZEL Cohort.

OBJECTIVE: This study aimed to assess the relationship between weight history during adulthood and frailty in late life in men and women participating in the GAZEL (GAZ and ELectricité) cohort. METHODS: This cohort study included 8,751 men and 3,033 women (aged 61 to 76 years) followed up since 1989. Modified Fried's frailty criteria (weakness, fatigue, unintentional weight loss, low physical activity, and impaired mobility) were assessed in 2015. Reported BMI was determined each year to characterize: obesity status in 2015, obesity duration over the 1990 to 2015 period, and trajectories of BMI. Associations between frailty and weight history were assessed using multinomial regression. RESULTS: In 2015, 12% of men had obesity, 1.8% severe obesity, and 0.4% morbid obesity; for women, these percentages were 11%, 2.2%, and 0.8%, respectively. Individuals with obesity were more likely to be frail than those with normal BMI and the risk of frailty increased with each additional year of obesity (adjusted odds ratio 1.04 [1.00-1.08] for men and 1.07 [1.02-1.13] for women). Trajectories of BMI revealed that both long-term obesity and onset of obesity in late adulthood were associated with frailty. CONCLUSIONS: Current and past obesity appear to be important determinants of frailty. Early weight management may be beneficial in old age.

Factors associated with changes of the frailty status after age 70: Findings in the MAPT study.

PURPOSE: Frailty has become a major issue in the prevention of functional decline and disability in aged populations. Using repeated measurements of frailty over 3 years, this work aimed to describe transitions between frailty states and associated factors. METHODS: This study used the data from the Multidomain Alzheimer Preventive Trial and included the 842 participants aged 70 and over who did not receive the multidomain intervention. Frailty was assessed using the phenotype proposed by Fried et al. at baseline and at 6, 12, 24, and 36 months. Factors influencing the transitions across frailty states were examined using multistate modeling. RESULTS: The study population included 548 women and 294 men, mean age 75.4 ± 4.5 years. At baseline, 430 (53%) participants were nonfrail, 349 (43%) prefrail, and 28 (4%) frail. A total of 2271 pairs of consecutive measurements of frailty status were available over the 3 years of follow-up, with no change in frailty status in 1548 of them (68%), a worsening of frailty status in 426 of them (19%), and an improvement in frailty status in the remaining 297 (13%). Polypharmacy (i.e., ≥6 drugs) and probable depression were associated with incident prefrailty. Female gender was systematically associated with a lower probability of recovering from prefrailty and frailty. Older age, overweight, comorbidity, and abnormal C-reactive protein also reduced the probability of recovery from frailty or prefrailty. CONCLUSIONS: This study sheds light on factors that should be further investigated in future research to help the prevention and management of frailty.