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Predictors of Maintained Transitions Between Robustness and Prefrailty in Community-Dwelling Older Spaniards

Published:November 17, 2022DOI:https://doi.org/10.1016/j.jamda.2022.10.010

      Abstract

      Objectives

      We aimed to explore predictors of sustained transitions (those that are maintained for an extra follow-up) between robustness and prefrailty in both directions.

      Design

      Longitudinal population-based cohort.

      Setting and Participants

      Community-dwelling Spaniards 65 years or older from the Toledo Study of Healthy Ageing.

      Methods

      The Fried's frailty phenotype was measured over 3 waves (2006–2009, 2011–2013, and 2014–2017). Multiple logistic regressions compared individuals following the pattern robust-prefrail-prefrail with those who remained robust across waves, and those following the pattern prefrail-robust-robust with those who remained prefrail, for sociodemographic, clinical, life-habits, dependency for activities of daily living, upper and lower extremities’ strength variables. The Fried's items of those who remained prefrail and those who became robust were compared.

      Results

      Mean age was 72.3 years (95% CI: 71.8–72.8) and 57.9% (52.7%–63.0%) were women. After multivariate adjustment, predictors (apart from age) of the sustained transition robustness-prefrailty were as follows: number of drugs taken (odds ratio: 1.37; 95% CI: 1.14–1.65), not declaring the amount of alcohol consumed (8.32; 1.78–38.88), and grip strength (0.92 per kg; 0.86–0.99). Predictors of the sustained transition prefrailty-robustness were as follows: drinking alcohol (0.2; 0.05–0.83), uricemia (0.67; 0.49–0.93), number of chair stands in 30 seconds (1.14; 1.01–1.28), and grip strength (1.12; 1.05–1.2). Low grip strength was associated with a lower probability of regaining robustness.

      Conclusions and Implications

      Prediction of sustained transitions between the first stages of frailty development can be achieved with a reduced number of variables and noting whether the Fried's item leading to a diagnosis of prefrailty is low grip strength. Our results suggest the need to intensify interventions on deprescription, quitting alcohol, and strengthening of upper and lower limbs.

      Keywords

      Several studies
      • Kojima G.
      • Taniguchi Y.
      • Iliffe S.
      • et al.
      Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis.
      have analyzed transitions in the frailty phenotype states between 2 waves. Indeed, the papers that have revised more than 2 waves have limited themselves to analyzing pairs of consecutive measurements of frailty status
      • Gill T.M.
      • Gahbauer E.A.
      • Allore H.G.
      • Han L.
      Transitions between frailty states among community-living older persons.
      • Herr M.
      • Cesari M.
      • Landre B.
      • et al.
      Factors associated with changes of the frailty status after age 70: Findings in the MAPT study.
      • Mendonça N.
      • Kingston A.
      • Yadegarfar M.
      • et al.
      Transitions between frailty states in the very old: the influence of socioeconomic status and multi-morbidity in the Newcastle 85+ cohort study.
      • Welstead M.
      • Muniz-Terrera G.
      • Russ T.C.
      • et al.
      Inflammation as a risk factor for the development of frailty in the Lothian Birth Cohort 1936.
      • Romero-Ortuno R.
      • Hartley P.
      • Davis J.
      • et al.
      Transitions in frailty phenotype states and components over 8 years: Evidence from The Irish Longitudinal Study on Ageing.
      or frailty phenotype items.
      • Romero-Ortuno R.
      • Hartley P.
      • Davis J.
      • et al.
      Transitions in frailty phenotype states and components over 8 years: Evidence from The Irish Longitudinal Study on Ageing.
      • Xue Q.L.
      • Bandeen-Roche K.
      • Varadhan R.
      • et al.
      Initial manifestations of frailty criteria and the development of frailty phenotype in the Women’s Health and Aging Study II.
      • Stenholm S.
      • Ferrucci L.
      • Vahtera J.
      • et al.
      Natural course of frailty components in people who develop frailty syndrome: Evidence from two cohort studies.
      Although relevant, these changes can be due to measurement error or be just transient, having in mind the dynamic nature of frailty in which up to 40% of the people experience some sort of transitions, including transitions to less frail states.
      • Kojima G.
      • Taniguchi Y.
      • Iliffe S.
      • et al.
      Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis.
      ,
      • Ofori-Asenso R.
      • Lee Chin K.
      • Mazidi M.
      • et al.
      Natural regression of frailty among community-dwelling older adults: A systematic review and meta-analysis.
      This usual way of assessing transitions has the risk of overdetection. Consider for example the difference between an individual who transitions across several waves from robustness to prefrailty and remains prefrail, and one who first transitions to prefrailty and then back to robustness again. In a 2-waves analysis, both first transitions would be included in the same category, although only the former one would have experienced a true transition.
      In a previous article
      • Rodríguez-Laso Á.
      • García-García F.J.
      • Rodríguez-Mañas L.
      Transitions between frailty states and its predictors in a cohort of community-dwelling spaniards.
      we analyzed many possible predictors of changes in the frailty status between the basal and the first follow-up of a cohort of community-dwelling older people. The addition of a now available second follow-up allows us to determine whether changes were maintained over time. Predictors of these sustained changes may not be necessarily the same as those of more transient ones and, because of its stability, they are more relevant for research and clinical care purposes. The same reasoning applies to the study of the prognostic capacity of the different frailty phenotype items.
      We focus this study on change in the initial stages of frailty development in its 2 potential directions: transitioning from robustness to prefrailty and from prefrailty to robustness. Knowing the determinants of these changes is especially relevant not only because of their frequency, but because these stages of the transitions are the most amenable to successful interventions.
      The aim of this paper was to study the predictors of maintained transitions, that is, changes between 2 waves that persisted in the next one, between robustness and prefrailty in both directions throughout 8 years in a cohort of community-dwelling Spaniards. In addition, we wanted to know if any of the frailty phenotype items that led to a diagnosis of prefrailty was associated with a better or worse evolution of prefrailty.

      Methods

      Data for this paper come from the Toledo Study on Healthy Ageing (TSHA), a population-based, prospective longitudinal cohort study of individuals aged >65 years living in the province of Toledo (Spain).
      • Garcia-Garcia F.J.
      • Gutierrez Avila G.
      • Alfaro-Acha A.
      • et al.
      The prevalence of frailty syndrome in an older population from Spain. The Toledo Study for Healthy Aging.
      Individuals living in nursing homes were excluded. Data belong to the first (2006–2009), second (2011–2013), and third (2014–2017) waves of the study. In each wave, all attempts were made to interview individuals in the same order they were interviewed in the previous one. Frailty was measured according to the criteria of Fried et al.
      • Fried L.P.
      • Tangen C.M.
      • Walston J.
      • et al.
      Frailty in older adults: evidence for a phenotype.
      Weakness was defined as the worse quintile of maximum grip strength on the dominant hand adjusted for sex and body mass index (BMI), and slowness as the worse quintile of gait speed, adjusted for sex and height. Individuals were considered to have “low energy” when they provided a positive answer to any of the following 2 questions from the Center for Epidemiologic Studies Depression Scale (CES-D scale)
      • Orme J.
      • Reis J.
      • Herz E.
      Factorial and discriminate validity of the Center for Epidemiological Studies depression (CES-D) scale.
      : “I felt that anything I did was a big effort” and “I felt that I could not keep on doing things” at least 3 to 4 days a week. Low physical activity was operationalized as being in the worse quintile of the Physical Activity Scale for the Elderly (PASE) score
      • Washburn A.
      • Smith K.W.
      • Jette A.M.
      • Janney C.A.
      The physical activity scale for the elderly (PASE): Development and evaluation.
      and weight loss as having experienced unintentional weight loss of 4.5 kg or more in the past year. Quintiles were calculated for the baseline wave and the cutoff values found used in the second and third waves. According to the number of criteria present, individuals were classified as nonfrail (0 criteria), prefrail (1–2 criteria), and frail (3–5 criteria). We checked all possible combinations of the frailty phenotype and death throughout the 3 waves but considered only changes between frailty states that were maintained over more than 1 wave. In this paper, we report on the 2 most frequent sustained transitions: prefrail-robust-robust and robust-prefrail-prefrail.
      Predictors were measured at baseline. (1) Self-reported predictors were age, gender, education level, civil status, and living arrangements. (2) A count of the number of the following diseases reported in medical records or by the participant: myocardial infarction–cardiac arrest, heart failure, angor, atrial fibrillation, peripheral vascular disease, hypertension, stroke, diabetes mellitus, Parkinson disease, chronic obstructive pulmonary disease, asthma, peptic ulcer disease, renal failure–dialysis–renal transplant, rheumatoid arthritis, osteoarthritis of hips or knees, cirrhosis–severe hepatic disease, and cancer (including blood and skin cancers). (3) Self-perceived health, categorized as good or not good. (4) Number of depressive symptoms according to the Geriatric Depression Scale.
      • Sheikh J.I.
      • Yesavage J.A.
      Geriatric Depression Scale (GDS). Recent evidence and development of a shorter version.
      (5) Alcohol (categorical, where those drinking at risk were men who drank 28 or more units of alcohol per week and women who drank 17 or more units per week) and tobacco consumption. (6) Physical activity according to the PASE scale.
      • Washburn A.
      • Smith K.W.
      • Jette A.M.
      • Janney C.A.
      The physical activity scale for the elderly (PASE): Development and evaluation.
      (7) Number of falls in the previous year and need of any medical assistance for the fall. (8) Visual impairment that made it difficult to read or sew, carry out activities of daily living, or almost produced blindness, and hearing impairment that prevented from taking part in a group conversation, an individual conversation at a normal volume and distance, or maintaining a conversation altogether. (9) Dependence for any basic (BADL-Katz index)
      • Katz S.
      • Ford A.B.
      • Moskowitz R.W.
      • et al.
      Studies of illness in the aged. The Index of ADL: A standardized measure of biological and psychosocial function.
      or instrumental (IADL-Lawton index)
      • Lawton M.P.
      • Brody E.M.
      Assessment of older people: self-maintaining and instrumental activities of daily living.
      activities of daily living.
      Objectively measured predictors were as follows. (1) Cognitive status, measured with the Mini Mental State Examination.
      • Folstein M.P.
      • Folstein S.E.
      • McHugh P.R.
      Mini-Mental State: A practical method for grading the cognitive state of patient for the clinician.
      ,
      • Escribano-Aparicio M.V.
      • Pérez-Dively M.
      • García-García F.J.
      • et al.
      Validación del MMSE de Folstein en una población española de bajo nivel educativo.
      (2) BMI, obtained through dividing the weight in kilograms (measured with a SECA precision scale) by the height in meters squared (measured with a stadiometer on a wall without skirting board) and categorized as underweight (BMI <18.5), normal weight (≥18.5<25), overweight (≥25<30), and obesity degrees I (≥30<35), II (≥35<40), and III (≥40). (3) A count of the drugs presented by individuals as currently consumed and with an ATC code. (4) Gait speed (meters/second), measured along a 3-meter distance according to the standards of the Short Physical Performance Battery.
      • Guralnik J.M.
      • Simonsick E.M.
      • Ferrucci L.
      • et al.
      A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.
      (5) Grip strength (kilograms), measured as the best out of 3 trials with a Jamar hydraulic dynamometer in the dominant hand, according to the standards of the Hispanic Established Populations for Epidemiologic Studies of the Elderly.
      • Ottenbacher K.J.
      • Branch L.G.
      • Ray L.
      • et al.
      The reliability of upper- and lower-extremity strength testing in a community survey of older adults.
      (6) Number of stands from a chair in 30 seconds with arms folded over the chest. (7) The best of 3 trials of shoulder (abduction), hip (flexion), and knee (extension) strength measured with a Muscular Mass Test (MMT) device. (8) Hemoglobin (g/dL) and anemia (having less than 13 g/dL in men or 12 g/dL in women), fasting glycemia (mg/dL) and hyperglycemia (more than 126 mg/dL), uricemia (mg/dL), and glomerular filtration (mL/min per 1.73 m2), calculated from serum creatinine, age, and sex according to the equation in the paper by Levey et al.
      • Levey A.S.
      • Stevens L.A.
      • Schmid C.H.
      • et al.
      A new equation to estimate glomerular filtration rate.
      The study obtained approval from the local ethics committee, and the participants signed a written informed consent.

      Statistical Analyses

      Clustering of the sample and multiple imputation by chained equations of missing values were handled with the R packages “survey”
      • Lumley T.
      Analysis of complex survey samples.
      and “MICE,”
      • van Buuren S.
      • Groothuis-Oudshoorn K.
      mice: Multivariate Imputation by Chained Equations in R.
      respectively. No imputation was performed for the frailty variable. The predictors with missing values were imputed, using as predictors the rest of the variables, transformed if needed. Continuous variables were imputed with predictive mean matching and categorical variables with a multinomial logit model, which ensure that imputed values are within original ranges. The number of imputed samples was 42. Variables were described through means or percentages with their 95% CIs depending on the type of variable. Because of the complex survey structure of the data, standard test (means comparison, chi square) for the comparisons between types of trajectories could not be performed and were substituted by the coefficient of the independent variable “type of trajectory” in simple linear (quantitative predictors) or logistic (binary predictors) regressions.
      Two multivariate logistic regressions were performed. In the first analysis, individuals that remained robust at the 3 measurement points were compared with those individuals who became prefrail in the second wave and remained so in the third one. In the second analysis, those who remained prefrail at the 3 waves were compared with those who became robust at the second wave and remained so at the third.
      For both analyses, 4 models were calculated: First, a bivariate model; second, the same model adding the variable age; third, a model with all variables that showed a P value less than .2 in the previous model; and finally, a reduced model in which we removed sequentially nonsignificant variables in the full model whose deletion did not change by more than 10% the coefficients of significant (P < .05) or close to the significance level variables. We studied linearity with scatterplot smoothing and density estimation, and tried splines and power, logarithmic, and inverse transformations when needed.
      Finally, we studied which of the items of Fried et al
      • Fried L.P.
      • Tangen C.M.
      • Walston J.
      • et al.
      Frailty in older adults: evidence for a phenotype.
      were associated with the persistent recovery of robustness compared with a persistent prefrail state, first with a χ2 test and then with a logistic regression of the different presenting items of Fried et al
      • Fried L.P.
      • Tangen C.M.
      • Walston J.
      • et al.
      Frailty in older adults: evidence for a phenotype.
      in the first wave (including having 2 items with and without low grip strength) on becoming robust, adjusted by age and gender.
      We carried out analyses with the statistical package R, version 4.0.2.
      R Core Team
      R: A language and environment for statistical computing.

      Results

      A total of 2475 individuals were eligible. The frailty phenotype could be measured at baseline in 1750 and complete information on the 3 waves was obtained from 949. The most frequent trajectories experienced by these individuals are presented in Figure 1. The figure shows that transitions back to the previous state, which would be indistinguishable from more persistent transitions in a 2-waves analysis, are very frequent: 58 individuals experienced the pattern robust-prefrail-prefrail, compared with 57 following the pattern robust-prefrail-robust; 80 individuals followed the pattern prefrail-robust-robust, and 50 experienced the prefrail-robust-prefrail pattern.
      Figure thumbnail gr1
      Fig. 1Flow chart of the follow-up assessment of the Toledo Study on Healthy Ageing and most frequent transitions. The abbreviations represent the sequence of frailty states at each wave of the study. R = Robust, P = Prefrail, F = Frail.
      Compared with those who could not be assessed for frailty at baseline or whose follow-up information was incomplete, those with full follow-up information (but who were not dead) were 2 years younger (P < .001), more frequently married but less frequently widowed (73.3 vs 67.8%, 19% vs 24.9%, P = .044), less dependent for BADL (6.2% vs 18.4%, P < .001), and with less frequent visual impairment (14.2% vs 17.7%, P = .013). There were no differences in gender, education level, number of drugs taken, self-perceived health, or hearing impairment.
      Variables with the highest proportion of missing values (Table 1) were those that required a blood extraction (12%), followed by cognitive status (10%), depression (10%), and number of diseases (8%). Descriptive values were extremely similar for the nonimputed (data not shown) and imputed samples (Table 1). Mean age was 72.3 years (95% CI: 71.8–72.8) and 57.9% (52.7–63) were women. The education level was very low and most individuals were married. Almost three-quarters referred a good level of health, the average number of diseases was 1.6 (1.3–1.8) and of drugs 3.9 (3.7–4.2). The mean BMI was in the overweight range, with only 13.4% (10.1–16.7) having a normal weight. The great majority had never consumed alcohol or tobacco. Vision or hearing impairment affected 12%, and almost half were dependent for at least 1 IADL, although only 3.7% (1.8%–5.5%) were dependent for at least 1 BADL. The average gait speed was 2 decimeters below the considered normal speed. Average biochemic levels were in the normal range.
      Table 1Description of Variables and Proportion of Missing Values at Baseline (Wave 2006–2009)
      % Missing (n = 387)Imputed Sample (n = 387)
      Age072.3 (71.8–72.8)
      Women057.9 (52.7–63)
      Education0.5
       No studies62.3 (52.1–72.5)
       Less than primary17.9 (12.2–23.7)
       Primary9.3 (5.2–13.4)
       Secondary4.9 (2–7.8)
       University5.5 (2.1–8.8)
      Civil status0
       Married74.9 (70.5–79.3)
       Widow17.3 (13.9–20.7)
       Single6.2 (3.8–8.6)
       Divorced/separated1.6 (0–3.1)
      Living arrangements0.2
       With spouse73.4 (68.6–78.1)
       Couple living with son/daughter1.8 (0.4–3.2)
       With son4.1 (2.5–5.8)
       With daughter2.3 (1–3.7)
       With brother/nephew1.6 (0.3–2.8)
       Alone16.8 (13.1–20.5)
      Number of diseases7.51.6 (1.3–1.8)
      Number of drugs03.9 (3.7–4.2)
      Self-perceived health0
       Good73.9 (68.3–79.5)
       Not good26.1 (20.5–31.7)
      MMSE score10.125 (24.4–25.6)
      GDS score9.82 (1.6–2.3)
      Body Mass Index (kg/height in m2)029.5 (28.9–30)
      Body Mass Index0
       Normal weight (≥18.5,<25)13.4 (10.1–16.7)
       Overweight (≥25, <30)45.2 (41–49.4)
       Obesity I (≥30, <35)32.3 (27–37.6)
       Obesity II (≥35,<40)6.7 (4.4–9.1)
       Obesity III (≥40)2.3 (1–3.8)
      Alcohol2.6
       Teetotaller68.9 (63.1–74.8)
       Former drinker8.2 (5.2–11.2)
       Not at risk10.6 (4.8–16.4)
       At risk0.8 (0–2)
       Does not declare consumption11.4 (6.8–16)
      Smoking1
       Never smoker69.2 (63.9–74.5)
       Former smoker22.4 (18.2–26.6)
       Current smoker8.4 (5.6–11.2)
      PASE081.7 (74.5–88.9)
      Number of falls past year0.50.3 (0.2–0.3)
      Falls requiring health care0.5
       No falls82.8 (78.3–87.3)
       Yes6.5 (4.3–8.6)
       No10.7 (6–15.5)
      Vision impairment012.1 (8.5–15.8)
      Hearing impairment012.7 (7.7–17.6)
      Dependent for BADL13.7 (1.8–5.5)
      Dependent for IADL4.748.7 (42–55.3)
      Gait speed (m/s)00.63 (0.61–0.66)
      Chair stands1.811.1 (10.6–11.6)
      Grip strength (kg)024.5 (23.4–25.6)
      Shoulder strength (kg)117.2 (16–18.3)
      Hip strength (kg)020.4 (18.9–21.9)
      Knee strength (kg)014.7 (13.5–16)
      Hemoglobin (g/dL)12.414.4 (14.3–14.6)
      Glycemia (mg/dL)12.1105.2 (101.7–108.8)
      Uricemia (mg/dL)12.15 (4.9–5.1)
      Glomerular filtration (mL/min/1.73 m2)12.180.8 (78.9–82.8)
      Mean/percentage (95% confidence interval).
      GDS, Geriatric Depression Scale; MMSE, Mini Mental Status Examination; PASE, Physical Activity Scale for the Elderly.
      Table 2 shows the differences between those who remained robust for the full follow-up and those who developed persistent prefrailty. The latter were older, took more drugs, had more depressive symptoms, did not declare more often the amount of alcohol consumed, performed less physical activity, and had a lower grip strength and glomerular filtration. In the reduced (and full) multivariate logistic model (Table 3), only an increasing age over 77 years (odds ratio, 95% CI: 2.1, 1.51–2.91), each extra drug taken (1.37, 1.14–1.65), and not declaring the amount of alcohol consumed (8.32, 1.78–38.88) significantly increased the risk of developing persistent prefrailty, whereas each additional kilogram of grip strength (0.92, 0.86–0.99) protected from experiencing that transition.
      Table 2Comparison of Individuals Who Remained Robust and Transitioned to Prefrailty and Remained Prefrail, and of Individuals Who Remained Prefrail and Transitioned to Robustness and Remained Robust, in 3 Waves of the Toledo Study of Healthy Ageing
      RRR (n = 180)RPP (n = 58)PPPP (n = 69)PRR (n = 80)P
      Age71.174.7<.0017571<.001
      Women56.151.7.5465866.3.324
      Education
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       No studies5754.475.468.8
       Less than primary21.121.414.511.3
       Primary10.112.17.37.5
       Secondary55.22.96.3
       University6.86.906.3
      Civil status
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       Married75.672.476.873.8
       Widow1524.118.816.3
       Single7.23.54.47.5
       Divorced/separated2.2002.5
      Living arrangements
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       With spouse73.370.676.872.5
       Couple living with son/daughter3.31.800
       With son2.85.24.46.3
       With daughter2.21.74.41.3
       With brother/nephew1.101.53.8
       Alone17.220.71316.3
      Number of diseases1.41.7.17421.5.047
      Number of drugs3.24.8<.0014.84.1.115
      Self-perceived health
       Good82.270.7.05862.367.5.421
       Not good17.829.337.732.5
      MMSE score25.525.9.55624.224.76
      GDS score1.21.9.0282.92.8.866
      Body Mass Index (kg/height in m2)29.229.4.66330.129.5.451
      Body Mass Index
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       Normal weight (≥18.5,<25)11.1191315
       Overweight (≥25, <30)51.732.843.541.3
       Obesity I (≥30, <35)30.64027.535
       Obesity II (≥35,<40)5.65.211.66.3
       Obesity III (≥40)1.13.54.42.5
      Alcohol
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       Teetotaller73.855.461.274.4
       Former drinker6.710.613.65.4
       Not at risk8.97.516.112
       At risk1.101.50.1
       Does not declare consumption9.526.57.68.1
      Smoking
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       Never smoker66.160.37379.3
       Former smoker24.524.12415.2
       Current smoker9.415.535.5
      PASE97.379.9.00164.563.843
      Number of falls past year0.20.4.1880.30.4.426
      Falls requiring health care
      The survey package does not allow to obtain the P value for a set of dummy variables.
      The survey package does not allow to obtain the P value for a set of dummy variables.
       No falls87.682.478.376.3
       Yes4.48.610.16.3
       No7.9911.617.5
      Vision impairment7.88.6.88817.420.708
      Hearing impairment9.415.5.32818.812.5.368
      Dependent for BADL at baseline1.13.6.1018.75.1.394
      Dependent for IADL at baseline38.551.3.13175.946<.001
      Gait speed (m/s)0.70.7.4280.520.55.489
      Chair stands12.410.8.083810.001
      Grip strength (kg)27.523.8.01318.423.6<.001
      Shoulder strength (kg)18.217.5.63113.717.6.008
      Hip strength (kg)20.821.8916.922.2.02
      Knee strength (kg)15.815.1.4711.614.8.021
      Hemoglobin (g/dL)14.514.4.57614.214.4.214
      Glycemia (mg/dL)103111.079106105.785
      Uricemia (mg/dL)4.95.1.6075.34.8.029
      Glomerular filtration (mL/min/1.73 m2)81.875.4.00278.784.4.029
      Mean/percentage. Bold indicates statistical significance.
      GDS, Geriatric Depression Scale; MMSE, Mini Mental Status Examination; PASE, Physical Activity Scale for the Elderly; PPP, prefrail over the 3 waves; PRR, prefrail-robust-robust in the 3 waves; RPP, robust-prefrail-prefrail in the 3 waves; RRR, robust over the 3 waves.
      The survey package does not allow to obtain the P value for a set of dummy variables.
      Table 3Logistic Models of the Persistent Transition From Robustness to Prefrailty
      BivariateAge AdjustedFull ModelReduced Model
      Age (per additional year in each spline)
       ≤771.14 (1.04–1.25)
      P < .001.
      1.08 (0.96–1.23)1.09 (0.97–1.23)
       >771.96 (1.27–3.03)
      P < .01.
      2.1 (1.49–2.97)
      P < .001.
      2.1 (1.51–2.91)
      P < .001.
      Women0.84 (0.47–1.49)1.03 (0.52–2.07)
      Education (ref. no studies)
       Less than primary1.06 (0.45–2.51)0.96 (0.41–2.24)
       Primary1.26 (0.43–3.69)1.34 (0.4–4.49)
       Secondary1.09 (0.23–5.19)1.31 (0.28–6.15)
       University1.06 (0.33–3.47)1.31 (0.34–5.02)
      Civil status (ref. married)
       Widowed1.68 (0.71–3.96)0.84 (0.33–2.15)
       Single/separated/divorced0.38 (0.09–1.55)0.34 (0.07–1.64)
      Living arrangements (ref. with spouse only)
       Alone1.25 (0.57–2.74)0.62 (0.27–1.45)
       With others0.95 (0.36–2.53)0.94 (0.26–3.49)
      Number of diseases1.2 (0.93–1.56)1.23 (0.93–1.63)
      Number of drugs1.32 (1.18–1.47)
      P < .001.
      1.36 (1.18–1.55)
      P < .001.
      1.36 (1.1–1.68)
      P < .01.
      1.37 (1.14–1.65)
      P < .01.
      Not good self-perceived health1.92 (0.98–3.76)1.92 (0.9–4.12)0.64 (0.24–1.74)
      MMSE score1.03 (0.94–1.13)1.06 (0.96–1.17)
      GDS score1.26 (1.05–1.52)
      P < .05.
      1.23 (0.98–1.53)1.1 (0.82–1.49)
      Body Mass Index (kg/height in m2)1.02 (0.95–1.09)1.06 (0.98–1.15)
      Alcohol (ref. teetotaller)
       Former drinker2.11 (0.72–6.17)0.76 (0.27–2.14)1.26 (0.28–5.7)1.21 (0.28–5.32)
       Drinker0.99 (0.32–3.13)0.71 (0.17–2.95)3.07 (0.45–20.89)3.29 (0.5–21.79)
       Does not declare consumption3.74 (1.22–11.47)
      P < .05.
      3.72 (1.01–13.66)
      P < .05.
      8.97 (1.93–41.57)
      P < .01.
      8.32 (1.78–38.88)
      P < .01.
      Smoking (ref. never smoker)
       Former smoker1.08 (0.5–2.32)1.04 (0.45–2.43)
       Current smoker1.8 (0.72–4.48)2.1 (0.69–6.41)
      PASE0.99 (0.98–1)
      P < .01.
      0.99 (0.98–1)1 (0.99–1.01)
      Number of falls past year1.41 (0.95–2.09)1.49 (0.94–2.35)1.45 (0.79–2.64)
      Falls requiring health care (ref. no falls)
       Yes2.06 (0.69–6.2)1.86 (0.68–5.1)
       No1.2 (0.34–4.26)1.36 (0.34–5.4)
      Vision impairment1.12 (0.23–5.32)0.92 (0.12–6.94)
      Hearing impairment1.76 (0.57–5.47)1.01 (0.32–3.18)
      Dependent for BADL at baseline3.31 (0.79–13.84)2.87 (0.65–12.62)
      Dependent for IADL at baseline1.68 (0.86–3.3)1.25 (0.59–2.65)
      Gait speed (m/s)0.54 (0.11–2.63)0.7 (0.15–3.3)
      Chair stands0.93 (0.85–1.01)0.95 (0.86–1.04)
      Grip strength (kg)0.95 (0.92–0.99)
      P < .05.
      0.96 (0.91–1.01)0.92 (0.86–0.99)
      P < .05.
      0.92 (0.86–0.99)
      P < .05.
      Shoulder strength (kg)0.99 (0.96–1.03)1 (0.96–1.04)
      Hip strength (kg)1 (0.97–1.03)1.01 (0.98–1.03)
      Knee strength (kg)0.99 (0.95–1.02)1.01 (0.97–1.04)
      Hemoglobin (g/dL)0.92 (0.7–1.22)0.89 (0.63–1.26)
      Glycemia (mg/dL)1.01 (1–1.02)1.01 (1–1.02)1 (0.99–1.02)
      Uricemia (mg/dL)1.07 (0.83–1.37)1.01 (0.79–1.29)
      Glomerular filtration (mL/min/1.73 m2)0.97 (0.95–0.99)
      P < .01.
      0.98 (0.96–1)0.98 (0.95–1.01)0.98 (0.95–1.01)
      Odds ratios with their 95% CI. In bold, results statistically significant at at least P < .05. n = 238.
      GDS, Geriatric Depression Scale; MMSE, Mini Mental Status Examination; PASE, Physical Activity Scale for the Elderly.
      P < .05.
      P < .01.
      P < .001.
      Table 2 also shows the comparison between those who remained prefrail and those who regained robustness in the 2 latter waves. Those who became robust were younger; had fewer diseases; were less frequently dependent for IADL; performed more chair stands; had more strength in their hands, shoulders, hips, and knees; and had a lower uricemia and higher glomerular filtration. Table 4 shows that, in the fully adjusted model, each additional year of age (0.8, 0.72–0.89), each additional milligram per deciliter of uricemia (0.67, 0.49–0.93), and drinking alcohol (0.2, 0.05–0.83) significantly decreased the chances of becoming robust, whereas each additional chair stand (1.14, 1.01–1.28) and kilogram of grip strength (1.12, 1.05–1.2) increased them.
      Table 4Logistic Models of the Persistent Transition From Prefrailty to Robustness
      BivariateAge AdjustedFull and Reduced Model
      Age0.77 (0.7–0.86)
      P < .001.
      0.8 (0.72–0.89)
      P < .001.
      Women1.42 (0.71–2.87)1.52 (0.69–3.34)
      Education (ref. no studies)
       Less than primary0.85 (0.35–2.08)1.4 (0.44–4.45)
       Primary1.13 (0.27–4.81)0.73 (0.14–3.85)
       Secondary or more4.73 (1.06–21.05)
      P < .05.
      2.85 (0.59–13.77)
      Civil status (ref. married)
       Widowed0.9 (0.36–2.25)1.27 (0.45–3.57)
       Single/separated/divorced2.4 (0.43–13.28)1.88 (0.25–14.25)
      Living arrangements (ref. with spouse only)
       Alone1.32 (0.53–3.27)1.62 (0.51–5.22)
       With others1.17 (0.37–3.72)1.23 (0.38–4)
      Number of diseases0.76 (0.59–0.99)
      P < .05.
      0.75 (0.56–1)0.85 (0.58–1.26)
      Square root of number of drugs0.64 (0.42–0.98)
      P < .05.
      0.63 (0.38–1.06)0.57 (0.29–1.13)
      Not good self-perceived health0.8 (0.46–1.39)1.01 (0.55–1.83)
      MMSE score0.99 (0.9–1.08)0.94 (0.84–1.06)
      GDS score0.99 (0.87–1.12)1 (0.87–1.14)
      Body Mass Index (kg/height in m2)0.98 (0.92–1.04)0.96 (0.9–1.03)
      Alcohol (ref. teetotaller)
       Former drinker0.33 (0.1–1.09)0.27 (0.08–0.93)
      P < .05.
      0.17 (0.03–1.11)
       Drinker0.56 (0.21–1.48)0.63 (0.18–2.24)0.2 (0.05–0.83)
      P < .05.
       Does not declare consumption0.87 (0.22–3.41)1.05 (0.19–5.91)0.55 (0.11–2.74)
      Smoking (ref. never smoker)
       Former smoker0.58 (0.24–1.42)0.64 (0.23–1.75)
       Current smoker1.68 (0.29–9.58)1.38 (0.15–12.38)
      PASE1 (0.99–1.01)1 (0.99–1.01)
      Number of falls past year1.16 (0.84–1.61)1.49 (0.96–2.29)
      Falls requiring health care (ref. no falls)
       Yes0.63 (0.19–2.06)0.82 (0.26–2.58)2 (0.52–7.64)
       No1.55 (0.6–3.99)2.93 (0.83–10.3)2.82 (0.58–13.69)
      Vision impairment1.19 (0.48–2.92)1.09 (0.41–2.92)
      Hearing impairment0.62 (0.21–1.77)0.93 (0.33–2.6)
      Dependent for BADL at baseline0.56 (0.15–2.11)1 (0.16–6.16)
      Dependent for IADL at baseline0.27 (0.14–0.52)
      P < .001.
      0.33 (0.16–0.67)
      P < .01.
      0.45 (0.19–1.04)
      Gait speed (m/s)1.79 (0.32–9.94)1.07 (0.19–6)
      Chair stands1.14 (1.06–1.24)
      P < .01.
      1.13 (1.03–1.23)
      P < .01.
      1.14 (1.01–1.28)
      P < .05.
      Grip strength (kg)1.07 (1.03–1.11)
      P < .001.
      1.06 (1.02–1.11)
      P < .01.
      1.12 (1.05–1.2)
      P < .01.
      Shoulder strength (kg)1.05 (1.01–1.09)
      P < .05.
      1.04 (0.99–1.08)
      Hip strength (kg)1.04 (1.01–1.07)
      P < .05.
      1.03 (0.99–1.07)
      Knee strength (kg)1.05 (1–1.11)
      P < .05.
      1.05 (0.99–1.11)
      Hemoglobin (g/dL)1.16 (0.91–1.47)1.1 (0.83–1.45)
      Glicemia (mg/dL)1 (0.98–1.01)1 (0.98–1.01)
      Uricemia (mg/dL)0.76 (0.59–0.99)
      P < .05.
      0.77 (0.62–0.95)
      P < .05.
      0.67 (0.49–0.93)
      P < .05.
      Glomerular filtration (mL/min/1.73 m2)1.03 (1–1.06)
      P < .05.
      1.01 (0.98–1.04)
      Odds ratios with their 95% CI. In bold, results statistically significant at at least P < .05. n = 149.
      GDS, Geriatric Depression Scale; MMSE, Mini Mental Status Examination; PASE, Physical Activity Scale for the Elderly.
      P < .05.
      P < .01.
      P < .001.
      There was a statistical association (P = .002) between recovering or not from prefrailty and the pattern of frailty item(s) in the first wave. Those who remained prefrail along the 3 waves presented more often with a low grip strength (33.8% vs 7.6%, P < .001) and less often with low physical activity (9.2% vs 21.5%, P = .025) than those who recovered. The rest of the differences were not statistically significant: 2 of the items of Fried et al,
      • Fried L.P.
      • Tangen C.M.
      • Walston J.
      • et al.
      Frailty in older adults: evidence for a phenotype.
      including low grip strength 13.8 vs 6.3, P = .182; 2 items excluding low grip strength 7.7% vs 12.7%, P = .340; slow gait speed 18.5 vs 22.8, P = .524; exhaustion 9.2% vs 17.7%, P = .146; weight loss 7.7 vs 11.4, P = .401. After adjusting for age and gender, compared with those with 2 frailty items not including the low grip strength item that was the second most frequent category, those with low grip strength had an odds ratio of 0.66 (95% CI: 0.53–0.82; P < .001) of becoming robust, those with low grip strength and an additional item an odds ratio of 0.73 (95% CI: 0.55–0.98; P = .045), and those with low physical activity an odds ratio of 1.02 (95% CI: 0.76–1.35; P = .914). No other item of Fried et al
      • Fried L.P.
      • Tangen C.M.
      • Walston J.
      • et al.
      Frailty in older adults: evidence for a phenotype.
      showed a statistically significant result.

      Discussion

      To our knowledge, this is the study that, to date, has analyzed more predictive factors of transitions between 2 frailty states that persist over more than 1 follow-up. Predictors are not that many, and several of them are common to those predicting changes between 2 waves
      • Rodríguez-Laso Á.
      • García-García F.J.
      • Rodríguez-Mañas L.
      Transitions between frailty states and its predictors in a cohort of community-dwelling spaniards.
      providing consistency to the findings: age, number of drugs taken, not reporting the amount of alcohol consumed, and grip strength for the transition from robustness to prefrailty, and age, grip strength, drinking alcohol, number of chair stands, and uricemia for the reverse pathway. In addition, we established that a diagnosis of prefrailty based on the presence of low grip strength is a predictor of a worse evolution of prefrailty.
      Polypharmacy has been reported as a risk factor for the development of frailty even after adjustment for multimorbidity and other variables but has been usually measured as a categorical variable with a cutoff of ≥5
      • de Breij S.
      • van Hout H.P.J.
      • de Bruin S.R.
      • et al.
      Predictors of frailty and vitality in older adults aged 75 years and over: Results from the Longitudinal Aging Study Amsterdam.
      • Palmer K.
      • Villani E.R.
      • Vetrano D.L.
      • et al.
      Association of polypharmacy and hyperpolypharmacy with frailty states: a systematic review and meta-analysis.
      • Saum K.
      • Schöttker B.
      • Meid A.D.
      • et al.
      Is polypharmacy associated with frailty in older people? Results from the ESTHER Cohort Study.
      • Wang R.
      • Chen L.
      • Fan L.
      • et al.
      Incidence and effects of polypharmacy on clinical outcome among patients aged 80+: a five-year follow-up study.
      • Gnjidic D.
      • Hilmer S.N.
      • Blyth F.M.
      • et al.
      High-risk prescribing and incidence of frailty among older community-dwelling men.
      or ≥6.
      • Mendonça N.
      • Kingston A.
      • Yadegarfar M.
      • et al.
      Transitions between frailty states in the very old: the influence of socioeconomic status and multi-morbidity in the Newcastle 85+ cohort study.
      Jamsen et al
      • Jamsen K.M.
      • Bell J.S.
      • Hilmer S.N.
      • et al.
      Effects of changes in number of medications and drug burden index exposure on transitions between frailty states and death: the Concord Health and Ageing in Men Project cohort study.
      found a hazard ratio of 1.04 (95% CI: 1.00–1.09) for the transition from robustness to prefrailty for each additional drug consumed. It was lower than ours, but their study was carried out only in men and did not study persistent transitions.
      Our results point to the need to change the focus when dealing with this preventable frailty risk factor from a dichotomous concept of polypharmacy, which has been defined arbitrarily in at least 111 different numerical ways,
      • Masnoon N.
      • Shakib S.
      • Kalisch-Ellett L.
      • Caughey G.E.
      What is polypharmacy? A systematic review of definitions.
      toward the consideration of the actual number of drugs used. Under this light, any reduction in the number of unnecessarily prescribed drugs (ie, deprescription) could have the potential of reducing the risk of developing prefrailty. Supporting this claim, a recent meta-analysis summarized the positive effects on several health outcomes of deprescription
      • Ibrahim K.
      • Cox N.J.
      • Stevenson J.M.
      • et al.
      A systematic review of the evidence for deprescribing interventions among older people living with frailty.
      and a study specifically reported an average reduction of 1.35 points (95% CI: −2.22 to −0.48) in the Edmonton Frail Scale score, which has a range of 17 points, after implementing a deprescription intervention in residential aged care facilities.
      • Ailabouni N.
      • Mangin D.
      • Nishtala P.S.
      DEFEAT-polypharmacy: deprescribing anticholinergic and sedative medicines feasibility trial in residential aged care facilities.
      The association of alcohol consumption with prefrailty is controversial. Jazbar et al
      • Jazbar J.
      • Locatelli I.
      • Kos M.
      The association between medication or alcohol use and the incidence of frailty: a retrospective cohort study.
      and Woods et al
      • Woods N.F.
      • LaCroix A.Z.
      • Gray S.L.
      • et al.
      Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study.
      found that nonhazardous drinking in older age was associated with a significantly lower incidence of prefrailty compared with no alcohol consumption, whereas hazardous consumption showed a nonsignificant lower incidence. Ortolá et al
      • Ortolá R.
      • García-Esquinas E.
      • León-Muñoz L.M.
      • et al.
      Patterns of alcohol consumption and risk of frailty in community-dwelling older adults.
      found that only heavy drinkers showed a decreased risk of developing frailty. Although the 3 studies adjusted for several health conditions, there is room for the results being explained by unaccounted for reverse causality, whereby older adults with health problems choose to limit or reduce their alcohol consumption because of ill health even before the presentation of frailty. A healthy survivor effect, in which only those drinkers who are healthy reach old age, cannot be ruled out either. Strandberg et al
      • Strandberg A.Y.
      • Trygg T.
      • Pitkälä K.H.
      • Strandberg T.E.
      Alcohol consumption in midlife and old age and risk of frailty: Alcohol paradox in a 30-year follow-up study.
      did not find an association of any level of alcohol consumption in older age with prefrailty in a study carried out only in men, whereas high alcohol consumption in midlife was significantly associated with risk of both prefrailty and frailty in old age.
      Our study found that drinkers had a significantly lower likelihood of regaining robustness compared with abstainers. This finding should be mainly attributed to moderate drinkers because in the database before imputation, at-risk individuals (men and women who drank at least 28 and 17 units of alcohol per week, respectively) were only 2 among those who remained robust, 1 among those who remained prefrail, and nil in the groups that transitioned. Trevisan et al
      • Trevisan C.
      • Veronese N.
      • Maggi S.
      • et al.
      Factors influencing transitions between frailty states in elderly adults: The Progetto Veneto Anziani Longitudinal Study.
      found the opposite effect of low-moderate drinking for this transition between 2 waves. In our study, drinking was associated with a higher nonsignificant risk of transitioning to prefrailty and the risk was almost 3 times higher and statistically significant for those not declaring the amount of alcohol consumed. It is hard to say whether the latter ones were moderate or at-risk consumers.
      The rest of the results give even more relevance to some of the predictors of change between 2 waves that our group described recently.
      • Rodríguez-Laso Á.
      • García-García F.J.
      • Rodríguez-Mañas L.
      Transitions between frailty states and its predictors in a cohort of community-dwelling spaniards.
      Grip strength would be a predictor of persistent changes in both directions between robustness and prefrailty, in addition to predicting transitions between 2 waves. This is not surprising considering that it is an item of the frailty phenotype, but it is remarkable that other items that contribute to the scale, like gait speed and physical activity, did not show any association. Nevertheless, we have confirmed that a higher number of chair stands, a measure of lower limb power, predicts a sustained recovery from prefrailty over a longer period. We have not corroborated our previous finding that the association of the number of chair stands was only evident above 5. This suggests that the 2 commonest ways to measure this type of power, time to perform 5 chair stands and the number of chair stands performed in 30 seconds, may be used to predict frailty transitions over time.
      The finding about the relationship between a lower uricemia and recovery from prefrailty is aligned with what was reported some years ago in other Spanish cohort of older people (ENRICA), in which the authors found a direct association between high uric acid levels and risk of developing frailty in a follow-up of 3.5 years.
      • García-Esquinas E.
      • Guallar-Castillón P.
      • Carnicero J.A.
      • et al.
      Serum uric acid concentrations and risk of frailty in older adults.
      This intriguing finding may reflect the proinflammatory, pro-oxidant, and endothelial dysfunction effects of uric acid,
      • Feng Z.
      • Lugtenberg M.
      • Franse C.
      • et al.
      Risk factors and protective factors associated with incident or increase of frailty among community-dwelling older adults: A systematic review of longitudinal studies.
      which would justify the deleterious effects of high levels of uric acid and the protective effects of low levels that increase the likelihood of recovery from prefrailty.
      Our results suggest that the item of Fried et al
      • Fried L.P.
      • Tangen C.M.
      • Walston J.
      • et al.
      Frailty in older adults: evidence for a phenotype.
      presented by those who are prefrail, but not the number of items, may predict the future development of prefrailty. Presenting with low grip strength, alone or combined with any other item, is associated with a bad prognosis. This is in agreement with the association between a stronger grip and the recovery to robustness commented above. Xue et al
      • Xue Q.L.
      • Bandeen-Roche K.
      • Varadhan R.
      • et al.
      Initial manifestations of frailty criteria and the development of frailty phenotype in the Women’s Health and Aging Study II.
      did not find any association for any item, but their results refer to changes between 2 waves only. Low grip strength is a diagnostic criterion of sarcopenia
      • Studenski S.A.
      • Peters K.W.
      • Alley D.E.
      • et al.
      The FNIH Sarcopenia Project: Rationale, study description, conference recommendations, and final estimates.
      that may be differentiating prefrail sarcopenic individuals from prefrail nonsarcopenic ones. Our group has already suggested the existence of 2 types of frailty, sarcopenic and nonsarcopenic frailty, with different health outcomes.
      • Davies B.
      • Walter S.
      • Rodríguez-Laso A.
      • et al.
      Differential association of frailty and sarcopenia with mortality and disability: insight supporting clinical subtypes of frailty.
      The main strength of our analysis is that it studied several predictors, including many functional measures, of sustained transitions over more than 1 follow-up of a well-studied frailty scale in community-dwelling individuals. We have limited our analyses to the first transitions in the frailty continuum, which were the most frequent ones and where interventions are more effective. It would have been interesting to study the predictors of other persistent transitions, but only 12 prefrail individuals and 4 robust individuals transitioned to a persistent frail state, and, among the frail individuals, only 6 transitioned to sustained prefrailty and 1 to a robust state, which precluded carrying out multivariable analyses. Loss to follow-up other than death is our major limitation. This high attrition rate is not surprising considering that this is a cohort mostly of older people and that the total follow-up time was approximately 8 years. Similar rates have been reported in other long-term epidemiological studies of older people.
      • Jacobsen E.
      • Ran X.
      • Liu A.
      • et al.
      Predictors of attrition in a longitudinal population-based study of aging.
      ,
      • Singh B.
      • Pandey N.M.
      • Garg R.K.
      • et al.
      Sample attrition rate of a community study: An analysis of Lucknow urban and rural elderly follow-up over a period of 9 years.
      We have found evidence that those not followed-up were older and with more visual and BADL impairment. Therefore, they probably would have developed the most advanced transitions between prefrailty and frailty and not the ones studied in this paper. Because our objective was not to provide frequencies of the different transitions, but study the variables associated with them, we consider that our results remain generalizable to any population transitioning between robustness and prefrailty. Because of the design of the fieldwork, intervals between assessments varied among individuals, but 90% of those who participated in the 3 waves had been followed for between 6.5 and 9.5 years. We have not assessed the associations of other variables linked in the literature to frailty, like vitamin D, inflammatory markers, or particular clinical conditions, because we did not want to overfit models.

      Conclusions and Implications

      Our paper highlights a reduced number of variables that may be of utmost interest to determine the long-term prognosis of patients in the first stages of frailty transitions. Because most of them are also amenable to intervention, it also indicates avenues for intervention, like deprescription, advice on quitting alcohol, and strengthening of upper and lower limbs. It also stresses the importance of registering whether the diagnosis of prefrailty is based on the presence of low grip strength, because this is an indicator of a worse prognosis.

      Acknowledgments

      The sponsor's role was supporting the analysis and preparation of the manuscript.

      References

        • Kojima G.
        • Taniguchi Y.
        • Iliffe S.
        • et al.
        Transitions between frailty states among community-dwelling older people: A systematic review and meta-analysis.
        Ageing Res Rev. 2019; 50: 81e88
        • Gill T.M.
        • Gahbauer E.A.
        • Allore H.G.
        • Han L.
        Transitions between frailty states among community-living older persons.
        Arch Intern Med. 2006; 166: 418e423
        • Herr M.
        • Cesari M.
        • Landre B.
        • et al.
        Factors associated with changes of the frailty status after age 70: Findings in the MAPT study.
        Ann Epidemiol. 2019; 34: 65-70.e1
        • Mendonça N.
        • Kingston A.
        • Yadegarfar M.
        • et al.
        Transitions between frailty states in the very old: the influence of socioeconomic status and multi-morbidity in the Newcastle 85+ cohort study.
        Age Ageing. 2020; 49: 974-981
        • Welstead M.
        • Muniz-Terrera G.
        • Russ T.C.
        • et al.
        Inflammation as a risk factor for the development of frailty in the Lothian Birth Cohort 1936.
        Exp Gerontol. 2020; 139: 111055
        • Romero-Ortuno R.
        • Hartley P.
        • Davis J.
        • et al.
        Transitions in frailty phenotype states and components over 8 years: Evidence from The Irish Longitudinal Study on Ageing.
        Arch Gerontol Geriatr. 2021; 95: 104401
        • Xue Q.L.
        • Bandeen-Roche K.
        • Varadhan R.
        • et al.
        Initial manifestations of frailty criteria and the development of frailty phenotype in the Women’s Health and Aging Study II.
        J Gerontol A Biol Sci Med Sci. 2008; 63: 984-990
        • Stenholm S.
        • Ferrucci L.
        • Vahtera J.
        • et al.
        Natural course of frailty components in people who develop frailty syndrome: Evidence from two cohort studies.
        J Gerontol A Biol Sci Med Sci. 2019; 74: 667-674
        • Ofori-Asenso R.
        • Lee Chin K.
        • Mazidi M.
        • et al.
        Natural regression of frailty among community-dwelling older adults: A systematic review and meta-analysis.
        Gerontologist. 2020; 60: e286-e298
        • Rodríguez-Laso Á.
        • García-García F.J.
        • Rodríguez-Mañas L.
        Transitions between frailty states and its predictors in a cohort of community-dwelling spaniards.
        J Am Med Direc Assoc. 2022; 23: 524.e11
        • Garcia-Garcia F.J.
        • Gutierrez Avila G.
        • Alfaro-Acha A.
        • et al.
        The prevalence of frailty syndrome in an older population from Spain. The Toledo Study for Healthy Aging.
        J Nutr Health Aging. 2011; 15: 852e856
        • Fried L.P.
        • Tangen C.M.
        • Walston J.
        • et al.
        Frailty in older adults: evidence for a phenotype.
        J Gerontol A Biol Sci Med Sci. 2001; 56: M146-M156
        • Orme J.
        • Reis J.
        • Herz E.
        Factorial and discriminate validity of the Center for Epidemiological Studies depression (CES-D) scale.
        J Clin Psychol. 1986; 42: 28-33
        • Washburn A.
        • Smith K.W.
        • Jette A.M.
        • Janney C.A.
        The physical activity scale for the elderly (PASE): Development and evaluation.
        J Clin Epidemiol. 1993; 46: 153-162
        • Sheikh J.I.
        • Yesavage J.A.
        Geriatric Depression Scale (GDS). Recent evidence and development of a shorter version.
        in: Brink T.L. Clinical Gerontology: A Guide to Assessment and Intervention. The Haworth Press Inc, New York1986
        • Katz S.
        • Ford A.B.
        • Moskowitz R.W.
        • et al.
        Studies of illness in the aged. The Index of ADL: A standardized measure of biological and psychosocial function.
        JAMA. 1963; 185: 914-919
        • Lawton M.P.
        • Brody E.M.
        Assessment of older people: self-maintaining and instrumental activities of daily living.
        Gerontologist. 1969; 9: 179-186
        • Folstein M.P.
        • Folstein S.E.
        • McHugh P.R.
        Mini-Mental State: A practical method for grading the cognitive state of patient for the clinician.
        J Psychiatr Res. 1975; 12: 189-198
        • Escribano-Aparicio M.V.
        • Pérez-Dively M.
        • García-García F.J.
        • et al.
        Validación del MMSE de Folstein en una población española de bajo nivel educativo.
        Rev Esp de Geriatr Gerontol. 1999; 34: 319-326
        • Guralnik J.M.
        • Simonsick E.M.
        • Ferrucci L.
        • et al.
        A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission.
        J Gerontol. 1994; 49: M85-M94
        • Ottenbacher K.J.
        • Branch L.G.
        • Ray L.
        • et al.
        The reliability of upper- and lower-extremity strength testing in a community survey of older adults.
        Arch Phys Med Rehabil. 2002; 83: 1423-1427
        • Levey A.S.
        • Stevens L.A.
        • Schmid C.H.
        • et al.
        A new equation to estimate glomerular filtration rate.
        Ann Intern Med. 2009; 150: 604-612
        • Lumley T.
        Analysis of complex survey samples.
        J Statistical Soft. 2004; 9: 1-19
        • van Buuren S.
        • Groothuis-Oudshoorn K.
        mice: Multivariate Imputation by Chained Equations in R.
        J Statistical Soft. 2011; 45: 1-67
        • R Core Team
        R: A language and environment for statistical computing.
        2020 (R Foundation for Statistical Computing, Vienna, Austria)
        https://www.R-project.org/
        Date accessed: March 9, 2021
        • de Breij S.
        • van Hout H.P.J.
        • de Bruin S.R.
        • et al.
        Predictors of frailty and vitality in older adults aged 75 years and over: Results from the Longitudinal Aging Study Amsterdam.
        Gerontology. 2021; 67: 69-77
        • Palmer K.
        • Villani E.R.
        • Vetrano D.L.
        • et al.
        Association of polypharmacy and hyperpolypharmacy with frailty states: a systematic review and meta-analysis.
        Eur Geriatr Med. 2019; 10: 9-36
        • Saum K.
        • Schöttker B.
        • Meid A.D.
        • et al.
        Is polypharmacy associated with frailty in older people? Results from the ESTHER Cohort Study.
        J Am Geriatr Soc. 2017; 65: e27-e32
        • Wang R.
        • Chen L.
        • Fan L.
        • et al.
        Incidence and effects of polypharmacy on clinical outcome among patients aged 80+: a five-year follow-up study.
        PLoS One. 2015; 10: e0142123
        • Gnjidic D.
        • Hilmer S.N.
        • Blyth F.M.
        • et al.
        High-risk prescribing and incidence of frailty among older community-dwelling men.
        Clin Pharmacol Ther. 2012; 91: 521-528
        • Jamsen K.M.
        • Bell J.S.
        • Hilmer S.N.
        • et al.
        Effects of changes in number of medications and drug burden index exposure on transitions between frailty states and death: the Concord Health and Ageing in Men Project cohort study.
        J Am Geriatr Soc. 2016; 64: 89-95
        • Masnoon N.
        • Shakib S.
        • Kalisch-Ellett L.
        • Caughey G.E.
        What is polypharmacy? A systematic review of definitions.
        BMC Geriatr. 2017; 17: 230
        • Ibrahim K.
        • Cox N.J.
        • Stevenson J.M.
        • et al.
        A systematic review of the evidence for deprescribing interventions among older people living with frailty.
        BMC Geriatr. 2021; 21: 258
        • Ailabouni N.
        • Mangin D.
        • Nishtala P.S.
        DEFEAT-polypharmacy: deprescribing anticholinergic and sedative medicines feasibility trial in residential aged care facilities.
        Int J Clin Pharm. 2019; 41: 167-178
        • Jazbar J.
        • Locatelli I.
        • Kos M.
        The association between medication or alcohol use and the incidence of frailty: a retrospective cohort study.
        BMC Geriatr. 2021; 21: 25
        • Woods N.F.
        • LaCroix A.Z.
        • Gray S.L.
        • et al.
        Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study.
        J Am Geriatr Soc. 2005; 53: 1321-1330
        • Ortolá R.
        • García-Esquinas E.
        • León-Muñoz L.M.
        • et al.
        Patterns of alcohol consumption and risk of frailty in community-dwelling older adults.
        J Gerontol A Biol Sci Med Sci. 2016; 71: 251-258
        • Strandberg A.Y.
        • Trygg T.
        • Pitkälä K.H.
        • Strandberg T.E.
        Alcohol consumption in midlife and old age and risk of frailty: Alcohol paradox in a 30-year follow-up study.
        Age Ageing. 2018; 47: 248-254
        • Trevisan C.
        • Veronese N.
        • Maggi S.
        • et al.
        Factors influencing transitions between frailty states in elderly adults: The Progetto Veneto Anziani Longitudinal Study.
        J Am Geriatr Soc. 2017; 65: 179e184
        • García-Esquinas E.
        • Guallar-Castillón P.
        • Carnicero J.A.
        • et al.
        Serum uric acid concentrations and risk of frailty in older adults.
        Exp Gerontol. 2016; 82: 160e165
        • Feng Z.
        • Lugtenberg M.
        • Franse C.
        • et al.
        Risk factors and protective factors associated with incident or increase of frailty among community-dwelling older adults: A systematic review of longitudinal studies.
        PLoS One. 2017; 12: e0178383
        • Studenski S.A.
        • Peters K.W.
        • Alley D.E.
        • et al.
        The FNIH Sarcopenia Project: Rationale, study description, conference recommendations, and final estimates.
        J Gerontol A Biol 335 Sci Med Sci. 2014; 69: 547-558
        • Davies B.
        • Walter S.
        • Rodríguez-Laso A.
        • et al.
        Differential association of frailty and sarcopenia with mortality and disability: insight supporting clinical subtypes of frailty.
        J Am Med Direc Assoc. 2022; 23: 1712-1716
        • Jacobsen E.
        • Ran X.
        • Liu A.
        • et al.
        Predictors of attrition in a longitudinal population-based study of aging.
        Int Psychogeriatr. 2021; 33: 767-778
        • Singh B.
        • Pandey N.M.
        • Garg R.K.
        • et al.
        Sample attrition rate of a community study: An analysis of Lucknow urban and rural elderly follow-up over a period of 9 years.
        Indian J Psychiatry. 2019; 61: 290-294