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Background Although age is an important risk factor for both cancer and frailty, it is unclear whether cancer itself increases the risk of frailty. We aimed to assess the association between cancer and frailty in a longitudinal cohort of older Danish twins, taking familial effect into account. Methods Using the Danish Cancer Registry, cancer cases were identified among participants aged 70 and over in the Longitudinal Study of Aging Danish Twins (LSADT). Frailty was evaluated over 10 years of follow-up using the frailty index (FI) and defined as FI > 0.21. Stratified Cox regressions were performed on discordant twin pairs (pairs where one twin had incident cancer and the other was cancer-free) and on all LSADT individual twins (twin pairs and singletons) with no history of cancer. Results Among the 72 discordant pairs (n  = 144, median age at inclusion = 75) included in the study, the median FI at inclusion was 0.08 for both cancer twins and cancer-free co-twins. From the stratified Cox regression, twins with cancer had an increased hazard of developing frailty (hazard ratio [HR] = 3.67, 95% confidence interval [CI] = 1.02–13.14) compared with their cancer-free co-twins. The analyses on individual twins (n  = 4 027) provided similar results, showing an increased hazard of frailty in individuals with cancer (HR = 2.57, 95% CI = 1.77–3.74) compared with those without cancer. Conclusions We showed a higher risk of becoming frail following a cancer diagnosis in both discordant twin pairs and individual twins. These findings support the importance of monitoring frailty in older adults with cancer through geriatric assessments and the implementation of frailty interventions. [ABSTRACT FROM AUTHOR]

Background DNA methylation-derived epigenetic clocks and frailty are well-established biological age measures capturing different aging processes. However, whether they are dynamically linked to each other across chronological age remains poorly understood. Methods This analysis included 1 309 repeated measurements in 524 individuals aged 50–90 years from the Swedish Adoption/Twin Study of Aging. Frailty was measured using a validated 42-item frailty index (FI). Five epigenetic clocks were calculated, including 4 principal component (PC)-based clocks trained on chronological age (PCHorvathAge and PCHannumAge) and aging-related physiological conditions (PCPhenoAge and PCGrimAge), and a pace of aging clock (DunedinPACE). Using dual change score models, we examined the dynamic, bidirectional associations between each of the epigenetic clocks and the FI over age to test for potential causal associations. Results The FI exhibited a nonlinear, accelerated increase across the older adulthood, whereas the epigenetic clocks mostly increased linearly with age. For PCHorvathAge, PCHannumAge, PCPhenoAge, and PCGrimAge, their associations with the FI were primarily due to correlated levels at age 50 but with no evidence of a dynamic longitudinal association. In contrast, we observed a unidirectional association between DunedinPACE and the FI, where a higher DunedinPACE predicted a subsequent increase in the FI, but not vice versa. Conclusions Our results highlight a temporal order between epigenetic aging and frailty such that changes in DunedinPACE precede changes in the FI. This potentially suggests that the pace of aging clock can be used as an early marker of the overall physiological decline at system level. [ABSTRACT FROM AUTHOR]

Background: Body mass index (BMI) may not be an optimal predictor of frailty as its constituents, lean and fat mass, may have opposite associations with frailty.Methods: A linear mixed model analysis was performed in the Helsinki Birth Cohort Study (n=2000) spanning from 57 to 84 years. A 39-item frailty index (FI) was calculated on three occasions over 17 years. Body composition in late midlife included BMI, percent body fat (%BF), waist-to-hip ratio (WHR), lean mass index (LMI), and fat mass index (FMI).Results: Mean FI levels increased by 0.28%/year among men and by 0.34%/year among women. Among women, per each kg/m 2 higher BMI and each unit higher %BF the increases in FI levels per year were 0.013 percentage points (PP) steeper (95% CI=0.004, 0.023) and 0.009 PP steeper (95% CI=0.002, 0.016) from late midlife into old age. Among men, per each 0.1-unit greater WHR the increase in FI levels was 0.074 PP steeper per year (95% CI=-0.0004, 0.148). Cross-sectionally, greater FMI and LMI in late midlife were associated with higher FI levels but the direction of the association regarding LMI changed after adjustment for FMI. The categories 'high FMI & high LMI' and 'high FMI & low LMI' showed the highest FI levels relative to the category 'low FMI & low LMI'.Conclusions: In late midlife, greater adiposity (%BF) among women and abdominal obesity (WHR) among men may predispose to higher levels of frailty from late midlife into old age. Greater lean mass alone may be protective of frailty, but not in the presence of high fat mass. [ABSTRACT FROM AUTHOR]

Background Frailty is a complex, dynamic geriatric condition, but limited evidence has shown how genes and environment may contribute to its longitudinal changes. We sought to investigate sources of individual differences in the longitudinal trajectories of frailty, considering potential selection bias when including a sample of oldest-old twins. Methods Data were from 2 Swedish twin cohort studies: a younger cohort comprising 1 842 adults aged 29–96 years followed up to 15 waves, and an older cohort comprising 654 adults aged ≥79 years followed up to 5 waves. Frailty was measured using the frailty index (FI). Age-based latent growth curve models were used to examine longitudinal trajectories, and extended to a biometric analysis to decompose variability into genetic and environmental etiologies. Results A bilinear model with an inflection point at age 75 best described the data, indicating a fourfold to fivefold faster FI increase after 75 years. Twins from the older cohort had significantly higher mean FI at baseline but slower rate of increase afterward. FI level at age 75 was moderately heritable in both men (42%) and women (55%). Genetic influences were relatively stable across age for men and increasing for women, although the most salient amplification in FI variability after age 75 was due to individual-specific environmental influences for both men and women; conclusions were largely consistent when excluding the older cohort. Conclusion Increased heterogeneity of frailty in late life is mainly attributable to environmental influences, highlighting the importance of targeting environmental risk factors to mitigate frailty in older adults. [ABSTRACT FROM AUTHOR]

Background: Early-life exposures have been associated with the risk of frailty in old age. We investigated whether early-life exposures predict the level and rate of change in a frailty index (FI) from midlife into old age.Methods: A linear mixed model analysis was performed using data from 3 measurement occasions over 17 years in participants from the Helsinki Birth Cohort Study (n = 2 000) aged 57-84 years. A 41-item FI was calculated on each occasion. Information on birth size, maternal body mass index (BMI), growth in infancy and childhood, childhood socioeconomic status (SES), and early-life stress (wartime separation from both parents) was obtained from registers and health care records.Results: At age 57 years the mean FI level was 0.186 and the FI levels increased by 0.34%/year from midlife into old age. Larger body size at birth associated with a slower increase in FI levels from midlife into old age. Per 1 kg greater birth weight the increase in FI levels per year was -0.087 percentage points slower (95% confidence interval = -0.163, -0.011; p = 0.026). Higher maternal BMI was associated with a higher offspring FI level in midlife and a slower increase in FI levels into old age. Larger size, faster growth from infancy to childhood, and low SES in childhood were all associated with a lower FI level in midlife but not with its rate of change.Conclusions: Early-life factors seem to contribute to disparities in frailty from midlife into old age. Early-life factors may identify groups that could benefit from frailty prevention, optimally initiated early in life. [ABSTRACT FROM AUTHOR]

Background: Frailty assessment in the Swedish health system relies on the Clinical Frailty Scale (CFS), but it requires training, in-person evaluation, and is often missing in medical records. We aimed to develop an electronic frailty index (eFI) from routinely collected electronic health records (EHRs) and assess its association with adverse outcomes in hospitalized older adults.Methods: EHRs were extracted for 18 225 patients with unplanned admissions between 1 March 2020 and 17 June 2021 from 9 geriatric clinics in Stockholm, Sweden. A 48-item eFI was constructed using diagnostic codes, functioning and other health indicators, and laboratory data. The CFS, Hospital Frailty Risk Score, and Charlson Comorbidity Index were used for comparative assessment of the eFI. We modeled in-hospital mortality and 30-day readmission using logistic regression; 30-day and 6-month mortality using Cox regression; and length of stay using linear regression.Results: Thirteen thousand one hundred and eighty-eight patients were included in analyses (mean age 83.1 years). A 0.03 increment in the eFI was associated with higher risks of in-hospital (odds ratio: 1.65; 95% confidence interval: 1.54-1.78), 30-day (hazard ratio [HR]: 1.43; 1.38-1.48), and 6-month mortality (HR: 1.34; 1.31-1.37) adjusted for age and sex. Of the frailty and comorbidity measures, the eFI had the highest area under receiver operating characteristic curve for in-hospital mortality of 0.813. Higher eFI was associated with longer length of stay, but had a rather poor discrimination for 30-day readmission.Conclusions: An EHR-based eFI has robust associations with adverse outcomes, suggesting that it can be used in risk stratification in hospitalized older adults. [ABSTRACT FROM AUTHOR]

Background: Frailty is a strong predictor of adverse outcomes. However, longitudinal drivers of frailty are not well understood. This study aimed at investigating the longitudinal trajectories of a frailty index (FI) from adulthood to late life and identifying the factors associated with the level and rate of change in FI.Methods: An age-based latent growth curve analysis was performed in the Swedish Adoption/Twin Study of Aging (N = 1,842; aged 29-102 years) using data from up to 15 measurement waves across 27 years. A 42-item FI was used to measure frailty at each wave.Results: A bilinear, two-slope model with a turning point at age 65 best described the age-related change in FI, showing that the increase in frailty was more than twice as fast after age 65. Underweight, obesity, female sex, overweight, being separated from one's co-twin during childhood, smoking, poor social support, and low physical activity were associated with a higher FI at age 65, with underweight having the largest effect size. When tested as time-varying covariates, underweight and higher social support were associated with a steeper increase in FI before age 65, whereas overweight and obesity were associated with less steep increase in FI after age 65.Conclusions: Factors associated with the level and rate of change in frailty are largely actionable and could provide targets for intervention. As deviations from normal weight showed the strongest associations with frailty, future public health programs could benefit from monitoring of individuals with abnormal BMI, especially those who are underweight. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to develop a functional aging index (FAI) that taps four body systems: sensory (vision and hearing), pulmonary, strength (grip strength), and movement (gait speed) and to test the predictive value of FAI for entry into care and mortality.Method: Growth curve models and Cox regression models were applied to data from 1,695 individuals from three Swedish longitudinal studies of aging. Participants were aged 45-93 at intake and data from up to eight follow-up waves were available.Results: The rate of change in FAI was twice as fast after age 75 as before, women demonstrated higher mean FAI, but no sex differences in rates of change with chronological age were identified. FAI predicted entry into care and mortality, even when chronological age and a frailty index were included in the models. Hazard ratios indicated that FAI was a more important predictor of entry into care for men than women, whereas it was a stronger predictor of mortality for men than women.Conclusions: Measures of biological aging and functional aging differ in their predictive value for entry into care and mortality for men and women, suggesting that both are necessary for a complete picture of the aging process across genders. [ABSTRACT FROM AUTHOR]

Background: Frailty indices (FIs) measure variation in health between aging individuals. Researching FIs in resources with large-scale genetic and phenotypic data will provide insights into the causes and consequences of frailty. Thus, we aimed to develop an FI using UK Biobank data, a cohort study of 500,000 middle-aged and older adults.Methods: An FI was calculated using 49 self-reported questionnaire items on traits covering health, presence of diseases and disabilities, and mental well-being, according to standard protocol. We used multiple imputation to derive FI values for the entire eligible sample in the presence of missing item data (N = 500,336). To validate the measure, we assessed associations of the FI with age, sex, and risk of all-cause mortality (follow-up ≤ 9.7 years) using linear and Cox proportional hazards regression models.Results: Mean FI in the cohort was 0.125 (SD = 0.075), and there was a curvilinear trend toward higher values in older participants. FI values were also marginally higher on average in women than in men. In survival models, 10% higher baseline frailty (ie, a 0.1 FI increment) was associated with higher risk of death (hazard ratio = 1.65; 95% confidence interval: 1.62-1.68). Associations were stronger in younger participants than in older participants, and in men than in women (hazard ratios: 1.72 vs. 1.56, respectively).Conclusions: The FI is a valid measure of frailty in UK Biobank. The cohort's data are open access for researchers to use, and we provide script for deriving this tool to facilitate future studies on frailty. [ABSTRACT FROM AUTHOR]

Background: Only scarce data exist on the association between obesity and disability in the oldest old. The purpose of this prospective study is to examine if body mass index and waist circumference (WC) are associated with incident mobility and activities of daily living (ADL) disability in nonagenarians.Methods: We used longitudinal data from the Vitality 90+ Study, which is a population-based study conducted at the area of Tampere, Finland. Altogether 291 women and 134 men, aged 90-91 years, had measured data on body mass index and/or WC and did not have self-reported mobility or ADL disability at baseline. Incident mobility and ADL disability was followed-up on median 3.6 years (range 0.6-7.8 years). Mortality was also followed-up. Multinomial logistic regression models were used for the analyses, as death was treated as an alternative outcome. The follow-up time was taken into account in the analyses.Results: Neither low or high body mass index, nor low or high WC, were associated with incident mobility disability. In women, the lowest WC tertile (<82 cm) was associated with an increased probability of incident ADL disability when compared to the middle WC tertile (odds ratio 3.98, 95% CI 1.35-11.77).Conclusions: Obesity is not associated with incident mobility or ADL disability in nonagenarians. Instead, low WC is associated with an increased risk of developing ADL disability in nonagenarian women. [ABSTRACT FROM AUTHOR]

Background: Low socioeconomic status is associated both with poorer functioning and elevated levels of inflammatory and cardiometabolic biomarkers; however, knowledge of such relations for the oldest old is limited. Our aim was to study whether education is associated with cardiometabolic (cholesterol levels, body mass index, and leptin) and inflammatory (C-reactive protein, interleukin-6, interleukin-1Ra) biomarkers for the 90-year-olds who participated in the Vitality 90+ study. In addition, we investigated whether these biomarkers explain educational inequalities in functioning.Methods: All persons in Tampere, Finland, who were born in 1909 or 1910, were invited to participate, irrespective of their health status or dwelling place. The sample consisted of 262 participants who went through the home interview and blood tests. The socioeconomic status indicator used was the highest education, and physical functioning was assessed using the Barthel index. The association of education with individual and combined biomarker scores, and with functioning, was analyzed cross-sectionally applying generalized linear models.Results: The low- and mid-level-educated participants had greater odds of belonging to the high risk group in cardiometabolic biomarkers than did the high-educated. Differences were statistically significant in three individual biomarkers (high-density lipoprotein-cholesterol, leptin, and body mass index) and in a cardiometabolic score. There were no educational differences in inflammatory biomarkers. When all biomarkers were combined, they mediated educational differences in functioning on an average of 23%. After controlling for smoking, alcohol use and diseases, biomarkers mediated part of the differences between the mid-level- and high-educated.Conclusions: High education was associated with better cardiometabolic biomarkers and functioning among the 90-year-olds. In part, educational inequalities in functioning were explained by cardiometabolic biomarkers. [ABSTRACT FROM AUTHOR]