Twelve‐year sarcopenia trajectories in older adults: results from a population‐based study

Introduction

Sarcopenia is a disorder characterized by a progressive and generalized reduction in muscle mass and function, increasing the risk of negative health-related outcomes, such as injurious falls, hospital admissions, and mortality.1, 2 The last consensus of the European Working Group on Sarcopenia in Older People (EWGSOP2) in 2018 made two major revisions to the definition of such condition.1 First, sarcopenia has now been recognized as a prototypical chronic condition, in which pathogenic processes leading to a loss in muscle mass and function are likely to start at middle ages and not exclusively occur in older adults. Second, in contrast to the previous sarcopenia criteria, priority for the case identification has been given to the assessment of low muscle strength, which identifies individuals with probable sarcopenia. The combination of low muscle strength with low muscle mass or quality ascertains the presence of sarcopenia. The severity of sarcopenia is then determined by assessing possible impairments in physical performance.

These three steps reflect the continuum that well describes sarcopenia development. However, although the progression towards worse sarcopenia stages is the most frequent scenario, a possible reversion from worse to probable sarcopenia or non-sarcopenia stages may be hypothesized. As already shown for some syndromes, such as frailty,3 the development of sarcopenia may be envisioned as a dynamic process, with both possible worsening and improving transitions.

Recently, extensive literature has focused on predictors of sarcopenia, including several sociodemographic, lifestyle, and health-related aspects (e.g., chronic diseases, hormonal dysfunctions, and inflammatory status).2, 4 To our knowledge, however, only one population-based study has longitudinally evaluated the transitions between sarcopenia stages.5 In a cohort of 2928 community-dwelling septuagenarians from The Health, Aging, and Body Composition Study, potentially modifiable factors, such as physical activity and body mass index, were identified as determinants of transitions to sarcopenia. This seminal evidence provided relevant insights about the process towards sarcopenia development and the factors associated with its dynamic nature. This information may be instrumental to determine the most appropriate factors to target by means of tailored interventions and the time windows when the interventions may have greater efficacy.

In the present study, we aimed to explore 12-year transitions through sarcopenia stages defined according to the EWGSOP2 sarcopenia criteria, while identifying factors associated with such trajectories in older adults.

Methods Study population

We used data from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). This ongoing prospective population-based study includes older adults aged ≥60 years living in the Kungsholmen area of Stockholm City (Sweden). The selection of the study participants was performed using random stratified sampling, considering the following age cohorts: 60, 66, 72, 78, 81, 84, 87, 90, 93, 96, and 99+ years (further details can be found in previous publications).6, 7 The baseline assessment was performed in 2001–2004 and had a participation rate of 73.3%. In order to better capture the occurrence of age-related changes in multiple health domains, participants in the oldest age cohorts (age ≥78 years) were assessed every 3 years and the youngest ones (age 60–72 years) every 6 years. For this work, of the 3363 participants initially included in the SNAC-K, we excluded 144 individuals who had incomplete data on muscle mass and/or strength, obtaining a final sample of 3219 participants. Data from baseline to the 12-year follow-up were considered.

The SNAC-K study complies with the principles of the Declaration of Helsinki and was approved by the Regional Ethical Review Board in Stockholm. Written informed consent to participate in the study was collected from all participants or the next of kin for those with cognitive impairment.

Data collection

Baseline and follow-up assessments of the study participants were performed by nurses and physicians at the research centre or, in the case of inability to come to the centre, at home. Evaluations included face-to-face interviews, reviews of the medical records, physical examinations, and administrations of scales and questionnaires.

Sarcopenia

The presence of sarcopenia at baseline and each follow-up was assessed based on a modified version of the European Working Group's revised criteria on Sarcopenia in Older People (EWGSOP2).1 As recommended, we considered muscle strength, muscle mass, and physical performance.

Muscle strength was evaluated by testing handgrip in both hands, and the best result was considered for the analyses. For those participants who had missing data on handgrip, we considered chair stand test results. Low muscle strength was defined as handgrip <27 kg for men and <16 kg for women, or as >15 s for five rises from a chair.1 Cohen's κ value for the agreement between handgrip and chair stand test in detecting individuals with low muscle strength in our sample was 0.307 (P < 0.001).

Low muscle mass was considered as having a calf circumference less than the 20th sex-specific percentile of our sample,5, 8 that is, <34 cm for men and <32 cm for women. These values are in line with the cut-offs for moderately/severely low calf circumference suggested by a recent study.9

A walking speed of ≤0.8 m/s was used to define low physical performance. This measure was assessed over 6 m or, for individuals who defined themselves as slow-walkers or those evaluated at home, 2.4 m. Previous studies demonstrated that evaluations of this parameter over a distance of 6 and 2.4 m in older adults are comparable.10

Following the EWGSOP2 algorithm,1 we defined ‘no sarcopenia’ as the presence of normal muscle strength and mass, ‘probable sarcopenia’ as the presence of low muscle strength and normal muscle mass, ‘non-severe sarcopenia’ as the presence of low muscle strength and mass with normal physical performance, and ‘severe sarcopenia’ as the combination of low muscle strength, low muscle mass, and low physical performance. In this study, because of the few participants with non-severe sarcopenia, we merged the non-severe and severe sarcopenia conditions into a unique ‘sarcopenia’ category.

Mortality

Information on the death dates for those who died over the 12-year study period was derived from the Swedish Cause of Death Registry.

Covariates

The following sociodemographic data were collected from each participant: age, sex, educational level (classified as high school degree or above vs. middle school or below), and living arrangement (classified as living in a nursing home vs. living in the community with a cohabitant vs. living in the community, alone). As regards risk behaviours and lifestyle characteristics, we considered smoking habits (categorized as never smoked vs. former smoker vs. current smoker), alcohol consumption [classified as none or occasional drinker vs. light to moderate (1–14 drinks/week for men and 1–7 drinks/week for women) vs. heavy (≥15/≥8 drinks/week for men and women, respectively)], and physical activity level. For the latter variable, we recorded information on the frequency and intensity of engagement in physical activities. Based on international recommendations,11, 12 we classified participants as physically inactive if they were engaged in light and/or moderate-to-intense activities ≤2–3 times/month, and as physically active if they reported at least a weekly frequency of light or moderate-to-intense activities.13 As a proxy of nutritional status,14 we computed the body mass index (BMI) at baseline from the ratio of participants' body weight and height squared (kg/m2). At each assessment, we evaluated cognitive performance through the Swedish version of the Mini-Mental State Examination (MMSE)15 and the number of chronic diseases. Physicians ascertained chronic diseases based on physical examinations, biochemical analyses, reviews of ongoing treatments, and information obtained from national inpatient and outpatient registers.16 For this study, we considered either the total number of chronic diseases or the presence of the following disease categories: cardiovascular diseases, neuropsychiatric diseases, gastrointestinal or kidney diseases, respiratory diseases, musculoskeletal diseases, endocrine or hematologic diseases, and cancer (details can be found in Supporting Information, Appendix S1).

Statistical analysis

Baseline characteristics of the sample are reported as mean and standard deviation (SD) or count (%). Characteristics were compared across individuals with no sarcopenia, probable sarcopenia, and sarcopenia through Student's t-test and χ2 or Fisher's exact test.

The transition occurrence across different sarcopenia stages (no sarcopenia, probable sarcopenia, and sarcopenia), death, and loss to follow-up was reported first in absolute values and displayed by mean of an alluvial plot. Second, 1-, 5-, and 10-year transition probabilities and the mean permanence time in each status were estimated through continuous-time multistage Markov modelling. This analysis considered all the transitions observed for each individual during the 12-year follow-up because individuals could have experienced more than one transition. Death and loss to follow-up were considered as absorbing states. We chose standard time points at 1, 5, and 10 years to derive estimates that could have a higher clinically meaningful prognostic value and may increase comparability with previous studies.10, 11 Third, we investigated factors associated with individuals' transitions over the observation period through proportional intensity models, and the strength of such associations was expressed as hazard ratios with 95% confidence intervals (for details, please see Jackson and Jackson17). Proportional intensity models generalize Cox regressions and allow to perform analyses on recurrent events.18 To improve the model convergence in this analysis, we used a quasi-Newton optimization algorithm (the Broyden–Fletcher–Goldfarb–Shanno) and a discrete-time model. For this analysis, we selected factors that presented a scientific rationale to support a potential association with sarcopenia transitions, including sociodemographic characteristics (age, sex, and education), risk behaviours (smoking and drinking habits, and physical activity level), cognitive performance (MMSE), nutritional status (baseline BMI), and multimorbidity (number of chronic diseases). These factors were firstly tested separately in unadjusted analyses and, secondly, included simultaneously in the model. For time-varying variables (physical activity level, MMSE, and the number of chronic diseases), the model considers the value at the beginning of each observed transition. The model provides estimates for all possible transitions from no sarcopenia, probable sarcopenia, and sarcopenia, with participants stable in each of these stages being the reference groups.

As sensitivity analyses, we evaluated the association between categories of chronic diseases and sarcopenia transition probabilities, and after including only data from the 6- and 12-year assessments of the participants. A further sensitivity analysis was performed to investigate factors associated with each transition considering individuals living in the community at baseline.

Analyses were performed using R alluvial and msm packages.17, 19, 20 All tests were two tailed, and we set a P-value <0.05 for statistical significance.

Results

The study included 3219 individuals, 35.8% men, with a mean age of 74.2 (SD 11) years. A total of 63.2% among the study participants were non-sarcopenic at baseline, while 27% had probable sarcopenia, and 9.7% had sarcopenia (1.9% non-severe and 7.8% severe, data not shown). Of note, the prevalence of sarcopenia was 8.2% among community-dwelling and 51.3% among institutionalized individuals. Table 1 reports the participants' characteristics in the total sample and by sarcopenia status. People with no sarcopenia were more likely to be men, younger, more educated, physically active, and generally healthier than those in the other sarcopenia categories. They were also more likely to be former or current smokers and to have light-to-moderate or heavy alcohol consumption compared with the other sarcopenia groups. Focusing on physical performance, the prevalence of low walking speed was 10.1% among those with no sarcopenia, 54.9% among those with probable sarcopenia, and 80.3% among sarcopenic participants (for the prevalence of sarcopenia criteria in male and female participants, please see Table S1).

Table 1. Characteristics of the sample as a whole and by sarcopenia at baseline All No sarcopenia Probable sarcopenia Sarcopenia P-value n (%) 3219 (100) 2036 (63.2) 869 (27.0) 314 (9.8) Sex (male, %) 1153 (35.8) 866 (42.5) 197 (22.7) 90 (28.7) <0.001 Age (years), mean (SD) 74.20 (10.96) 69.34 (8.52) 80.85 (9.53) 87.50 (7.60) <0.001 Living arrangement (%) <0.001 Nursing home 115 (3.6) 8 (0.4) 48 (5.5) 59 (18.8) Community, living with cohabitants 1721 (53.5) 954 (46.9) 568 (65.4) 199 (63.4) Community, living alone 1383 (43.0) 1074 (52.8) 253 (29.1) 56 (17.8) Education: high school or above (%)a 2659 (83.1) 1797 (88.3) 642 (74.9) 220 (71.4) <0.001 Body mass index (kg/m2) <0.001 <18.5 88 (2.7) 22 (1.1) 17 (2.0) 49 (15.6) 18.5–24.9 1493 (46.4) 860 (42.2) 410 (47.2) 223 (71.0) 25–29.9 1252 (38.9) 880 (43.2) 332 (38.2) 40 (12.7) ≥30 386 (12.0) 274 (13.5) 110 (12.7) 2 (0.6) Active physical level (%) 2184 (67.8) 1634 (80.3) 454 (52.2) 96 (30.6) <0.001 Smoking habit (%)a <0.001 Never 1493 (46.4) 857 (42.1) 471 (54.2) 165 (52.5) Former 1213 (37.7) 829 (40.7) 290 (33.4) 94 (29.9) Current 452 (14.0) 340 (16.7) 83 (9.6) 29 (9.2) Alcohol consumption (%)a <0.001 No or occasional 1150 (35.7) 512 (25.1) 429 (49.4) 209 (66.6) Light to moderate 1721 (53.5) 1261 (61.9) 386 (44.4) 74 (23.6) Heavy 296 (9.2) 259 (12.7) 28 (3.2) 9 (2.9) No. of chronic diseases, mean (SD) 3.98 (2.44) 3.26 (2.01) 5.03 (2.53) 5.72 (2.83) <0.001 MMSE, mean (SD) 27.77 (4.28) 28.99 (1.58) 26.59 (5.19) 23.15 (7.89) <0.001 Low muscle strength (%) 1183 (36.8) 0 (0.0) 869 (100.0) 314 (100.0) <0.001 Handgrip (N), mean (SD)a 256.2 (113.6) 292.6 (102.6) 140.6 (55.3) 147.11 (57.41) <0.001 Chair stand test (s)a 28.5 (27.0) 16.8 (16.8) 44.4 (29.5) 59.90 (25.47) <0.001 Low muscle mass (%) 458 (14.3) 144 (7.1) 0 (0.0) 314 (100.0) <0.001 Calf circumference (cm) 35.8 (3.8) 36.8 (3.3) 35.9 (2.9) 29.55 (2.44) <0.001 Low walking speed (%) 927 (29.0) 203 (10.1) 472 (54.9) 252 (80.3) <0.001 Walking speed (m/s) 0.97 (0.47) 1.18 (0.33) 0.68 (0.45) 0.39 (0.38) <0.001 MMSE, Mini-Mental State Examination; SD, standard deviation. P-values refer to the comparison between individuals with different sarcopenia status. a n = 18 participants had missing data on education, n = 61 on smoking habit, n = 52 on drinking habit, n = 624 on handgrip, and n = 6 on chair stand test.

Figure 1 illustrates the study participants' transitions across sarcopenia stages over the 12-year follow-up (the total number of individuals involved in each transition is reported in Table S2). Based on these observations, we estimated 1-, 5-, and 10-year transition probabilities. As shown in Table 2, the probability of non-sarcopenic individuals maintaining their status was 90.4% at 1 year and decreased up to 40.4% at 10 years. Conversely, they have 10 year probabilities of 17.1% and 5.1% of developing probable sarcopenia and sarcopenia, respectively. Considering participants with probable sarcopenia, the chance of maintaining their status decreased from 79.3% at 1 year to 14.5% at 10 years. Conversely, their probability of developing sarcopenia reached 10.3% at 5 years, likewise reverting to no sarcopenia (10.7%). The chance of sarcopenic participants to remain sarcopenic ranged from 67.8% to 3.4% at 1 and 10 years, respectively, while the corresponding probabilities of dying increased from 21.4% to 70.9%. The probability of reverting from sarcopenia to probable sarcopenia was 8.2% and 4.7% at 5 and 10 years, respectively, while the 10-year probability to revert to no sarcopenia was 3.5%.

image

Alluvial plot illustrating the transitions between sarcopenia stages in the SNAC-K study participants over a 12 year follow-up (n = 3219). NA, not available data on sarcopenia.

Table 2. Estimated 1-, 5-, and 10-year sarcopenia transition probabilities From No sarcopenia Probable sarcopenia Sarcopenia 1- year probability of transition (%) to No sarcopenia 90.4 3.9 1.1 Probable sarcopenia 6.5 79.3 5.2 Sarcopenia 1.0 6.7 67.8 Death 0.9 5.7 21.4 Loss to follow-up 1.3 4.4 4.6 5- year probability of transition (%) to No sarcopenia 62.0 10.7 3.4 Probable sarcopenia 17.4 34.3 8.2 Sarcopenia 4.2 10.3 15.6 Death 8.4 27.7 59.1 Loss to follow-up 8.0 16.9 13.7 10-year probability of transition (%) to No sarcopenia 40.4 10.7 3.5 Probable sarcopenia 17.1 14.5 4.7 Sarcopenia 5.1 5.6 3.4 Death 21.0 44.2 70.9 Loss to follow-up 16.4 25.0 17.5 Probabilities are estimated considering all observed transitions over the 12 year follow-up, using continuous-time multistate Markov models.

Overall, the mean permanence time in each status before experiencing any transition was 9.69 years for no sarcopenia, 4.22 years for probable sarcopenia, and 2.55 years for sarcopenia (Table S3).

Table 3 shows the factors associated with sarcopenia transitions in our sample (for the univariate analyses and for transitions to loss to follow-up, please see Tables S4 and S5). Factors directly associated with the progression of no sarcopenia to worse sarcopenia stages were older age, male sex, current smoking, and a higher number of chronic diseases. Considering BMI, each 1 kg/m2 increase was associated with a higher probability of progressing from no sarcopenia to probable sarcopenia and a lower chance of developing sarcopenia. For probable sarcopenia, older age and male sex were positively associated with the likelihood of developing sarcopenia, while inverse associations were observed for former smoking habits and higher BMI. The chance of reverting from probable to no sarcopenia decreased with older age and a higher number of chronic diseases. At the same time, it increased with higher physical activity and cognitive function. For sarcopenic individuals, no factors were significantly associated with the chance of reverting to probable or no sarcopenia. In all sarcopenia groups, older age, male sex, and a higher number of chronic diseases were associated with higher mortality, while the contrary was observed for an active physical level and higher cognitive function. No substantial differences were observed after excluding institutionalized individuals (Table S6), as well as after including only the 6- and 12-year assessments of the participants (data not shown). Among the categories of chronic conditions, the presence of musculoskeletal diseases was associated with a higher risk of developing probable sarcopenia, while cancer seemed to increase both the probability of progressing to and reversing from probable sarcopenia (Table S7).

Table 3. Factors associated with transitions from no sarcopenia, probable sarcopenia, and sarcopenia Multivariable hazard ratio (95% confidence interval) of transition From no sarcopenia to From probable sarcopenia to From sarcopenia to Probable sarcopenia Sarcopenia Death No sarcopenia Sarcopenia Death No sarcopenia Probable sarcopenia Death Age (years) 1.08 (1.07–1.10) 1.11 (1.07–1.14) 1.07 (1.05–1.08) 0.98 (0.96–1.00) 1.04 (1.01–1.06) 1.07 (1.05–1.08) 0.99 (0.93–1.06) 0.96 (0.93–1.00) 1.04 (1.02–1.07) Sex (male vs. female) 0.73 (0.60–0.90) 1.84 (1.16–2.91) 1.83 (1.42–2.34) 0.93 (0.61–1.40) 1.99 (1.31–3.01) 1.49 (1.16–1.91) 0.77 (0.22–2.65) 0.48 (0.19–1.19) 2.00 (1.45–2.77) Education (high vs. low) 1.30 (0.98–1.72) 1.07 (0.59–1.92) 1.15 (0.83–1.60) 0.87 (0.55–1.37) 1.04 (0.64–1.68) 0.80 (0.63–1.02) 1.21 (0.33–4.42) 1.42 (0.58–3.47) 0.87 (0.63–1.19) Smoking habits (ref: never) Former 0.86 (0.71–1.04) 1.32 (0.81–2.16) 1.11 (0.85–1.44) 0.84 (0.60–1.20) 0.65 (0.43–0.98) 1.10 (0.88–1.37) 0.55 (0.14–2.07) 0.58 (0.26–1.31) 1.03 (0.75–1.42) Current 0.89 (0.67–1.19) 2.13 (1.22–3.74) 1.98 (1.45–2.71) 0.96 (0.56–1.62) 0.77 (0.38–1.57) 1.76 (1.22–2.52) 1.15 (0.29–4.59) 0.51 (0.15–1.74) 1.10 (0.69–1.74) Alcohol (ref: no/occasional) Light to moderate 1.06 (0.87–1.31) 0.93 (0.57–1.51) 0.75 (0.57–0.97) 1.44 (0.99–2.10) 1.05 (0.71–1.56) 0.84 (0.67–1.04) 0.81 (0.28–2.35) 1.75 (0.88–3.47) 0.77 (0.57–1.05) Heavy 0.88 (0.59–1.32) 0.85 (0.35–2.05) 0.82 (0.55–1.22) 0.77 (0.28–2.11) 0.75 (0.28–2.01) 1.06 (0.67–1.68) 0.93 (0.08–10.25) 1.77 (0.31–9.97) 0.60 (0.29–1.25) Physical level (active vs. inactive) 0.97 (0.77–1.21) 0.73 (0.44–1.20) 0.52 (0.41–0.67) 1.84 (1.19–2.84) 0.82 (0.56–1.21) 0.77 (0.62–0.95) 0.86 (0.29–2.53) 2.01 (0.92–4.41) 0.74 (0.55–1.00) MMSE 1.03 (0.97–1.08) 0.96 (0.87–1.06)

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