Independent and joint associations of cardiorespiratory fitness and lower-limb muscle strength with cardiometabolic risk in older adults

Marcyo Camara; Kenio C. Lima; Yuri A. Freire; Gabriel C. Souto; Geovani A. D. Macêdo; Raissa de M. Silva; Ludmila L. P. Cabral; Rodrigo A. V. Browne; Telma M. A. M. Lemos; Debra L. Waters; Edgar R. Vieira; Todd M. Manini; Eduardo Caldas Costa

doi:10.1371/journal.pone.0292957

Abstract

The aim of this study was to investigate the independent and joint associations of low cardiorespiratory fitness and lower-limb muscle strength with cardiometabolic risk in older adults. A total of 360 community-dwelling older adults aged 60–80 years participated in this cross-sectional study. Cardiometabolic risk was based on the diagnosis of Metabolic Syndrome and poor Ideal Cardiovascular Health according to the American Heart Association guidelines. Cardiorespiratory fitness and lower-limb muscle strength were estimated using the six-minute walk and the 30-second chair stand tests, respectively. Participants in the 20^th percentile were defined as having low cardiorespiratory fitness and lower-limb muscle strength. Poisson’s regression was used to determine the prevalence ratio (PR) and 95% confidence intervals (CI) of Metabolic Syndrome and poor Ideal Cardiovascular Health. Participants with low cardiorespiratory fitness alone and combined with low lower-limb muscle strength were similarly associated with a higher risk for Metabolic Syndrome (PR 1.27, 95% CI 1.09–1.48, and PR 1.32, 95% CI 1.10–1.58, respectively), and poor Ideal Cardiovascular Health (PR 1.76, 95% CI 1.25–2.47, and PR 1.65, 95% CI 1.19–2.28, respectively). Low lower-limb muscle strength alone was not associated with a higher risk for either Metabolic Syndrome or poor Ideal Cardiovascular Health (PR 1.23, 95% CI 0.81–1.87, and PR 1.11, 95% CI 0.89–1.37, respectively). Low cardiorespiratory fitness alone or combined with low lower-limb muscle strength, but not low lower-limb muscle strength alone, was associated with a higher cardiometabolic risk in older adults. The assessment of physical fitness may be a “window of opportunity” to identify youngest-old adults with a high cardiovascular disease risk.

Citation: Camara M, Lima KC, Freire YA, Souto GC, Macêdo GAD, Silva RdM, et al. (2023) Independent and joint associations of cardiorespiratory fitness and lower-limb muscle strength with cardiometabolic risk in older adults. PLoS ONE 18(10): e0292957. https://doi.org/10.1371/journal.pone.0292957

Editor: Yuichiro Nishida, Saga University, JAPAN

Received: April 17, 2023; Accepted: October 3, 2023; Published: October 23, 2023

Copyright: © 2023 Camara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data for this study are publicly available from the OSF repository (https://osf.io/ntzp6/).

Funding: MC - This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. ECC - To the Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brasil (CNPq) (306537/2022-2), which supports the last author through a research productivity grant from. ECC - This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES/PRINT) - Finance Code 88887.717099/2022-00. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Cardiovascular diseases (CVD) are the main cause of mortality in older adults [1, 2]. Understanding the risk factors and implementing countermeasures are pivotal to avoid adverse CVD events [3]. Metabolic Syndrome (MetS) is a combination of three or more biological risk factors for CVD (i.e., high blood pressure, fasting glucose, total cholesterol, triglycerides, and waist circumference) [4]. The Ideal Cardiovascular Health (ICH) concept proposed by the American Heart Association [5] includes both biological and behavioral components (i.e., adequate blood pressure, glucose, total cholesterol, no smoking, body mass index, physical activity level, and diet habits). Importantly, the ICH metric incorporates well-recognized behavioral risk factors, including body mass index, physical activity, and diet, which are not accounted for in traditional clinical tools used for CVD screening, such as the Framingham risk score [5]. Previous studies have reported that MetS and poor ICH are independent predictors of CVD morbidity and mortality [6–8].

In addition to CVD risk algorithms such as MetS and ICH, physical fitness is a strong predictor of cardiometabolic health [9]. Aging reduces cardiorespiratory fitness and muscle strength [10, 11] and both low cardiorespiratory fitness and muscle strength are independently associated with increased cardiometabolic risk in older adults [12, 13]. Interestingly, some studies have suggested a potential additive effect of combined low cardiorespiratory fitness and muscle strength to predict adverse cardiometabolic outcomes, such as arterial hypertension [14], diabetes [15], and MetS [16]. Of note, data from UK Biobank Study [17] showed an additive effect of combining cardiorespiratory fitness and muscle strength to predict CVD mortality compared to cardiorespiratory fitness or muscle strength alone in middle-aged and older adults. However, these findings do not extend to CVD risk alone; in other words, it was not possible to identify individuals’ risk of developing CVD based on specific screening tools. Investigations on the independent and combined associations of cardiorespiratory fitness and muscle strength with cardiometabolic risk in older adults may contribute to identify fitness-related phenotypes associated with a higher CVD risk. This is important because incorporating fitness levels into established CVD screening algorithms enhances the accuracy of risk prediction for both CVD and mortality [18]. Such investigations also provide insights about which type of physical exercise (aerobic, resistance, or combined) may optimize the reduction of CVD risk in this population. Therefore, this study aimed to investigate the independent and joint associations of low cardiorespiratory fitness and low muscle strength with cardiometabolic risk, using CVD risk algorithms endorsed by the American Heart Association (MetS and ICH) [4], in older adults. It was hypothesized that older adults with combined low cardiorespiratory fitness and muscle strength would have the highest cardiometabolic risk.

Methods

This cross-sectional study was reported in accordance with the STROBE (STrengthening the Reporting of OBServational Studies in Epidemiology) statement guidelines [19]. The study was conducted at the Onofre Lopes University Hospital (HUOL) and at the Department of Physical Education of the Federal University of Rio Grande do Norte (UFRN) between October 2018 and April 2019. This study was approved by the Ethics Committee in Research of HUOL (Protocol Number: 2.603.422/2018).

Participants

Community-dwelling adults aged 60–80 years from the city of Natal, RN, Brazil were recruited by advertisements on radio, e-flyers in social medias (WhatsApp, Instagram, and Facebook), healthcare units, and community centers for older adults. The informed consent was provided in written form and was read and signed by all participants upon their arrival for data collection. All participants received an identification code at the onset of recruitment. Only the research staff directly engaged in data collection had access to participants’ names. Inclusion criteria were: i) no history of CVD or major adverse cardiovascular events (i.e., acute myocardial infarction, stroke, coronary artery disease, arrhythmias, or peripheral vascular disease); ii) no musculoskeletal limitations to perform exercise; iii) no acute diabetes- or hypertension-related decompensations (i.e., fasting glucose ≥ 300 mg/dL; blood pressure ≥ 160/105 mmHg). The sample size was determined from a preliminary study [20] about the prevalence of MetS in older adults with and without low cardiorespiratory fitness and muscle strength (prevalence ratio for MetS of 1.45 in older adults with combined low cardiorespiratory fitness and muscle strength compared to those with normal values). Based on these rates, the required sample size was ≥ 324 participants with an alpha error of 5% and power of 80% (G*Power software, version 3.1.9.2). Fig 1 shows the study flowchart.

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Fig 1. Study flowchart.

https://doi.org/10.1371/journal.pone.0292957.g001

Cardiorespiratory fitness and lower-limb muscle strength

Cardiorespiratory fitness was assessed using the six-minute walk test [21]. The participants were instructed to walk the maximum possible distance in a 30-meter course over 6 minutes. The total distance walked was recorded. Previous studies have found a moderate-high correlation between the six-minute walk test and treadmill performance (r = 0.78) and peak oxygen uptake (r = 0.76) [22, 23]. The six-minute walk test has high reproducibility (r = 0.88–0.94) in older adults [22], and it is highly recommended for clinical purposes, considering its simplicity and low cost [18]. Lower-limb muscle strength was assessed using the 30-second chair stand test [21]. In this test, participants sit down and stand up from a chair as many times as possible within 30 seconds. The number of repetitions is recorded. The 30-second chair stand test exhibits moderate-to-high correlation (r = 0.77) with the one-repetition maximum leg press test and demonstrates high test-retest reliability (r = 0.89) [24]. Moreover, the chair stand test correlates with various markers of lower extremity muscle function, including muscle power, gait speed, and agility/dynamic balance [25]. Results below the 20^th percentile on the six-minute walk test and 30-second chair stand test from our cohort, based on sex and age (60–69 and 70–80 years), were used to define low cardiorespiratory fitness and low lower-limb muscle strength, respectively. Results equal to or above the 20^th percentile on the six-minute walk test and 30-second chair stand test were used to define normal cardiorespiratory fitness and normal muscle strength, respectively.

Cardiometabolic risk

To assess the cardiometabolic risk, two approaches were used based on the recommendations of the American Heart Association: diagnosed MetS [4] and poor ICH [24]. MetS includes biological risk factors related to cardiometabolic disease and was defined using the American Heart Association criteria [4]; i.e., presence of at least three of the following: (i) waist circumference > 102 cm in males and > 88 cm in females; (ii) systolic blood pressure ≥ 130 mmHg and/or diastolic blood pressure ≥ 85 mmHg and/or on antihypertensive medication; (iii) HDL-cholesterol < 40 mg/dL in males and < 50 mg/dL in females; (iv) triglycerides ≥ 150 mg/dL and/or on lipid-lowering medication; (v) fasting glucose ≥ 110 mg/dL and/or on diabetes medication.

The ICH metrics include both biological and behavioral protective factors against cardiometabolic diseases and was defined following the recommendations of the American Heart Association [24]: i) blood pressure: < 120/80 mmHg without medication; ii) total cholesterol: < 200 mg/dL without medication; iii) fasting glucose: < 100 mg/dL without medication; iv) body mass index (BMI): < 25 kg/m²; v) never smoked or stopped smoking for at least 12 months; vi) appropriate intake of at least four of the following items: 1) fresh vegetables and fruits (≥ 2 times/day); 2) grains and oilseeds (≥ 1 time/day); 3) consumption of fish (≥ 3 days/week); 4) consumption of sugary drinks (≤ 4 days/week); 5) consumption of ultra-processed foods (≤ 4 days/week); vii) physical activity: ≥ 75 minutes/week of vigorous physical activity or ≥ 150 minutes/week of moderate physical activity. Poor ICH was defined as not meeting ≥5 of the above-mentioned criteria [25].

After a 12-hour overnight fasting period, blood samples were obtained by venipuncture to determine total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, and fasting glucose. LDL-cholesterol was determined according to the Friedewald formula: (total cholesterol—[HDL + triglycerides/5]). All biochemical tests were determined using commercial kits (Diagnostic Labtest-SA, São Paulo, Brazil) according to the colorimetric method/enzyme (Labtest, Labmax Plenno, Minas Gerais, Brazil). Body mass index was calculated as weight in kilograms divided by height in meters squared (kg/m²). Waist circumference (cm) was measured in the midway between the lateral iliac crest and the lowest rib margin at the end of normal expiration twice and the average value was recorded. Resting blood pressure was measured in the sitting position using an oscillometric device (Omron HEM-780-E, Kyoto, Japan) in triplicate, two minutes apart between each measurement. The average value of the last two measurements was used for analysis [26]. Physical activity level was assessed using questions about daily walking frequency, sports activities and recreational/leisure activities contained in the modified Minnesota Leisure Activity Questionnaire [27]. The activities were first classified according to their metabolic equivalents (METs), based on the compendium of physical activity [28]. The intensity of physical activity was classified according to age as “light, moderate or vigorous” [29]. Diet was assessed by a food frequency questionnaire [30], including questions about fruits, vegetables, grains, oil seeds, fishes, sugary beverages, and ultra-processed foods which adapted a list according to food groups and their level of processing according to the review of the food guide for the Brazilian population [31]. The frequency was based on Brazilian guidelines for the prevention of CVD and major adverse cardiovascular events [32, 33]. Both the physical activity level and diet were assessed during face-to-face interviews with the participants.

Covariates

Socioeconomic information was collected (sex, age, educational level, marital status, ethnicity and family income). Sedentary time was assessed using the Longitudinal Aging Study Amsterdam–Sedentary Behavior Questionnaire [34]. However, the ‘napping’ question was not considered, given that sedentary activities are only considered in the awake period [35]. More than eight hours per day of sedentary time was considered as ‘high sedentary time’ [36].

Statistical analysis

Continuous and categorical data were expressed as mean ± standard deviation (SD) and absolute and relative (%) rates, respectively. The calculation of the Mahalanobis Distance was used to identify the outliers regarding the outcome variables (i.e., Mahalanobis probability values ≤ 0.005). Independent-sample t-test, one-way ANOVA, Chi-squared and Fisher’s exact tests were used for bivariate analysis. Pearson’s correlation coefficient was used to test the correlation between cardiorespiratory fitness and muscle strength. In the multiple analysis, Poisson’s regression model with robust variance was used to calculate the prevalence ratio (PR) and its 95% confidence interval (IC) for MetS and poor ICH using low cardiorespiratory fitness or low muscle strength as predictors with normal cardiorespiratory fitness and normal muscle strength as reference groups, respectively. For this independent analysis, the models were unadjusted, adjusted for confounders (Model^a), and adjusted by confounders plus muscle strength in the model with low cardiorespiratory fitness as a predictor and by cardiorespiratory fitness in the model with low muscle strength as a predictor (Model^b). For joint associations analysis, low cardiorespiratory fitness (but normal muscle strength), low muscle strength (but normal cardiorespiratory fitness), and combined low cardiorespiratory fitness and muscle strength were the predictors (models) and combined normal cardiorespiratory fitness and muscle strength was the reference group. All multiple regression models were adjusted for the independent variables that were different between the groups with and without MetS and poor vs. ideal ICH in the bivariate analyses at p < 0.20 [37]. The following independent variables were considered as potential confounders for MetS and poor ICH: age, sex, alcohol consumption, ethnicity, income, and sedentary time. Only the significant independent variables with a p < 0.10 were retained in the multiple regression models [37], which were age, sex, and sedentary time. The assumptions of Poisson’s regression were verified, including multicollinearity. The Omnibus test was used to verify the goodness of fit of the models; a well-adjusted model is represented by a p < 0.05. The level of significance was set at p < 0.05. Statistical analysis was performed using the IBM SPSS Statistics 25.0 program (IBM, Chicago, IL, USA).

Results

Three hundred and sixty older adults were included in the final analysis (Fig 1). Seventeen participants were excluded from the study by the Mahalanobis Distance (S1 Table). Most participants were females (72.8%) and had excess weight (overweight: 19.9%; obesity: 37.9%). Almost half of the participants were Caucasian (41.7%), 24.5% had post-secondary education, and 31.2% were living alone. Few participants were current smokers (3.8%), and approximately one-third were ex-smokers (34.9%). Table 1 shows the characteristics of the participants. S2 Table shows the characteristics of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification. In addition, S3 and S4 Tables display the distribution of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification and by sex, respectively.

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Table 1. Characteristics of the participants (n = 360).

https://doi.org/10.1371/journal.pone.0292957.t001

The cut-off points for defining low cardiorespiratory fitness based on the six-minute walk test were as follows: males aged 60–69 < 492 meters; males aged 70–80 < 398 meters; females aged 60–69 < 431 meters; females aged 70–80 < 378 meters. The cut-off points for defining low lower-limb muscle strength based on the 30-second chair stand test were: males aged 60–69 < 12 repetitions; males aged 70–80 < 11 repetitions; females aged 60–69 < 11 repetitions; females aged 70–80 < 10 repetitions.

The prevalence of MetS, poor ICH and their respective individual components are shown in Table 2. The prevalence of MetS and poor ICH was 72.5% and 40.8%, respectively. The prevalence of MetS and high blood pressure was higher in older adults with low cardiorespiratory fitness and combined low cardiorespiratory fitness and lower-limb muscle strength, but not in those with low lower-limb muscle strength when compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (p < 0.05). However, abdominal obesity had higher prevalence in older adults with low cardiorespiratory fitness, low lower-limb muscle strength, and combined low cardiorespiratory fitness and lower-limb muscle strength compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (p < 0.05). In addition, the prevalence of poor ICH, high blood pressure, and BMI was higher in older adults with low cardiorespiratory fitness, low lower-limb muscle strength, and combined low cardiorespiratory fitness and lower-limb muscle strength compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (p < 0.05). In contrast, physical inactivity was more prevalent in older adults with low lower-limb muscle strength and combined low cardiorespiratory fitness and lower-limb muscle strength compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (p < 0.05).

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Table 2. Prevalence of Metabolic Syndrome and poor Ideal Cardiovascular Health in the community-dwelling older adults (n = 360).

https://doi.org/10.1371/journal.pone.0292957.t002

Table 3 shows the prevalence ratios for MetS and poor ICH in older adults with low cardiorespiratory fitness or low lower-limb muscle strength compared to those with normal cardiorespiratory fitness and lower-limb muscle strength, respectively. In the multiple-adjusted analysis, low cardiorespiratory fitness was associated with higher prevalence ratios for MetS and poor ICH, even when adjusted for lower-limb muscle strength (p < 0.05). Low lower-limb muscle strength was associated with higher prevalence ratios for MetS and poor ICH (unadjusted model and adjusted model by age, sex, and sedentary time; p < 0.05), but when adjusted by cardiorespiratory fitness the association was not significant (p = 0.927 for MetS; p = 0.831 for ICH). The Pearson’s correlation coefficient between cardiorespiratory fitness and lower-limb muscle strength was moderate (r = 0.580; p< 0,001).

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Table 3. Independent association of cardiorespiratory fitness and lower-limb muscle strength with Metabolic Syndrome and poor Ideal Cardiovascular Health in community-dwelling older adults (n = 360).

https://doi.org/10.1371/journal.pone.0292957.t003

Fig 2A and S5 Table show the prevalence ratios for MetS in older adults with low cardiorespiratory fitness, low lower-limb muscle strength, and combined low cardiorespiratory fitness and lower-limb muscle strength compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (reference group). In the multiple-adjusted analysis, older adults with low cardiorespiratory fitness (1.32, 95% CI 1.10–1.58) and combined low cardiorespiratory fitness and lower-limb muscle strength (1.27, 95% CI 1.09–1.48) had a higher prevalence ratio for MetS, which was not observed in those with low lower-limb muscle strength.

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Fig 2. Joint associations of cardiorespiratory fitness and lower-limb muscle strength with Metabolic Syndrome (panel A) and poor Ideal Cardiovascular Health (panel B) in community-dwelling older adults (n = 360).

Data are expressed as prevalence ratio (PR) and 95% confidence interval (CI). Models adjusted for age, sex, and sedentary time. Goodness-of-fit (Omnibus test): p < 0,05. Abbreviations: CRF, cardiorespiratory fitness; MS, lower-limb muscle strength.

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Fig 2B and S6 Table show the PR for poor ICH in older adults with low cardiorespiratory fitness, low lower-limb muscle strength, and combined low cardiorespiratory fitness and lower-limb muscle strength compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (reference group). In the multiple-adjusted analysis, only older adults with low cardiorespiratory fitness alone (1.76, 95% CI 1.25–2.47) and combined low cardiorespiratory fitness and lower-limb muscle strength (1.65, 95% CI 1.19–2.28) showed a higher PR for poor ICH. No significant associations were observed for those with low lower-limb muscle strength.

Discussion

Our main finding was that low cardiorespiratory fitness alone or combined with low lower-limb muscle strength, but not low lower-limb muscle strength alone, was associated with a higher cardiometabolic risk in older adults. This result was consistent using both CVD risk algorithms (i.e., MetS and ICH). However, our data suggest that combined low cardiorespiratory fitness and lower-limb muscle strength did not have an additive effect to predict the cardiometabolic risk compared to low cardiorespiratory fitness alone.

Our results suggest that low cardiorespiratory fitness is the driver of the association between poor physical fitness with increased cardiometabolic risk (Fig 2 and Table 3). Data from Aerobics Center Longitudinal Study [38] including mostly middle-aged adults have demonstrated that higher cardiorespiratory fitness was cross-sectionally associated with better cardiovascular health as assessed by ICH. Furthermore, increments of cardiorespiratory fitness were associated with improvements of ICH score [38]. Hassinen et al. [39] reported that low cardiorespiratory fitness, measured by respiratory gas analysis, was associated with higher MetS risk in middle-aged and older adults. Using factor analysis, the authors suggested that low cardiorespiratory fitness was a feature of MetS. Our study adds to the body of evidence showing that the association of low cardiorespiratory fitness with higher cardiometabolic risk in older adults seems to occur independently of the lower-limb muscle strength levels.

The older adults with low cardiorespiratory fitness, alone or combined with low lower-limb muscle strength, had a higher prevalence of high blood pressure, abdominal obesity, high BMI, MetS, and poor ICH compared to those with normal cardiorespiratory fitness and lower-limb muscle strength (Table 2). Cardiorespiratory fitness results from a complex interaction of various systems, mainly cardiovascular, respiratory, and neuromuscular. It is expected that individuals with low cardiorespiratory fitness have an impaired ability to properly integrate the chain involving the above-mentioned systems to translate into physical effort [18]. This may be partially explained by the deleterious effects elicited by the cardiometabolic risk factors, such as high blood pressure and excess body fat. It should be noted that the older adults included in our study were free of CVD. However, based on both CVD risk algorithms used in the current study, our findings suggest that those older adults with low cardiorespiratory fitness may be at a higher risk to develop CVD, which is supported by the findings of the UK Biobank Study [40], i.e., low cardiorespiratory fitness was associated with a higher incidence of CVD over a 6-year follow-up in middle-aged and older adults (aged 40–69 years).

The absence of significant associations of low lower-limb muscle strength with either MetS or poor ICH was unexpected. Cumulative evidence has shown significant associations of low muscle strength (grip strength) with higher cardiometabolic risk ([41], incidence of CVD [42–45], and cardiovascular mortality [45, 46]. Kawamoto et al. [41] and Lee et al. [47] have found that middle-aged and older adults with higher grip strength showed lower risk for MetS. Ramírez-Vélez et al. [48] reported that higher grip strength was associated with better ICH scores in older adults. We believe that some aspects could partially explain the disagreement between ours and previous findings. Although grip strength and chair stand tests are valid and reliable measures of muscle strength [9, 21, 49] there is poor agreement using grip strength and chair stand tests to identify older adults with low muscle strength [50, 51]. These differences between the assessment methods and their implications for muscle strength may also account for some of the discrepancies between the results from our study and previous investigations. More importantly, given that cardiorespiratory fitness was not assessed in the above-mentioned studies [42, 44–47] it is possible that individuals with combined low cardiorespiratory fitness and muscle strength have been included in the “low muscle strength” group. Previous investigations have showed that the adjustment by cardiorespiratory fitness attenuate or even eliminate the association of muscle strength with MetS [52–54], which supports our assumption.

In our study, the presence of low lower-limb muscle strength did not contribute to the increase in cardiometabolic risk of those older adults who already had low cardiorespiratory fitness. Contrary to our findings, Jurca et al. [16] and Kim et al. [54] have reported that combined high cardiorespiratory fitness and muscle strength showed the lowest MetS risk compared to low cardiorespiratory fitness and muscle strength in adult males. In a longitudinal study, Jurca et al. [53] observed that adult males with combined high cardiorespiratory fitness and muscle strength demonstrated the lowest incidence of MetS. More recently, Kim et al. [17] demonstrated that combined high cardiorespiratory fitness and muscle strength showed the lowest risk for CVD in middle-aged and older adults. However, Jurca et al. [16] and Kim et al. [54] have showed that the combination of low cardiorespiratory fitness and high muscle strength was not associated with lower MetS risk, while high cardiorespiratory fitness and low muscle strength was associated. Jurca et al. [53] have showed that the inverse association of muscle strength and MetS was attenuated after adjusting for cardiorespiratory fitness and Kim et al. [17] have found that while cardiorespiratory fitness was inversely associated with CVD mortality when adjusted by muscle strength, the opposite did not occur. Taken together, independent of an additive effect, the combined assessment of cardiorespiratory fitness and muscle strength predicts consistently the CVD risk in older adults, although muscle strength has a lower predictive role.

Noteworthy, most of our participants were youngest-old adults in their first decade of transition between middle to old age, a period in each several aging-related physiological changes that increase the risk for CVD are emerging, particularly in females [55–57]. Indeed, the prevalence of biological and behavioral risk factors for CVD increases dramatically from middle to old age. In Brazil, the prevalence of hypertension (aged 45–64 years: 30.9–49.4%; aged 65+ years: 61%), type 2 diabetes (aged 45–64 years: 11.1–17.1%; aged 65+ years: 28.4%), and physical inactivity (aged 45–64 years: 46.3%-56.5; aged 65+ years: 73%) is > 20% higher in older adults compared to middle-aged individuals [58]. Thus, preventive actions against CVD, including physical exercise, should be strongly encouraged for youngest-old adults identified with low cardiorespiratory fitness alone or combined with low lower-limb muscle strength. To reduce the cardiometabolic risk, our findings support the idea that the exercise programs should be primarily focused in improving the cardiorespiratory fitness. However, as combined exercise training elicits more comprehensive benefits on physical fitness and cardiometabolic health [59–62], both aerobic and resistance exercise training should be considered for older adults identified as high risk for adverse CVD events, i.e., those with low cardiorespiratory fitness alone or in combination with low lower limb muscle strength. This is in accordance with the World Health Organization 2020 guidelines on physical activity and sedentary behavior, which strongly recommend the inclusion of multicomponent exercise programs for older adults [63].

Our study has some strengths and limitations. As strengths, we have used two CVD risk algorithms endorsed by the American Heart Association [4]. Both MetS and ICH score were determined by using direct measures of blood pressure, waist circumference, and blood sample. We have included older adults free of CVD, which allowed us to analyze the association of cardiorespiratory fitness and muscle strength with cardiometabolic risk without the well-known deleterious impact of CVD on these fitness components. As limitations, this is cross-sectional study, which precludes to establish a cause-effect relationship of cardiorespiratory fitness and muscle strength with cardiometabolic risk. Although we have used validated tests to assess cardiorespiratory fitness and muscle strength [9, 18, 22, 23, 49], they are not considered “gold-standard”. In addition, 30-s chair stand test is a specific proxy of lower-limb muscle strength. Physical activity and sedentary time were assessed by self-reported measures, and not by objectively-measured methods, such as accelerometry. Approximately 75% of our sample were females, which precluded an exploration into association analyses by sex. Finally, as one of the inclusion criteria was “without limitations to perform exercise”, we did not include older adults who had very low cardiorespiratory fitness and muscle strength levels. Therefore, our findings should be interpreted with caution and not generalized to other populations.

Conclusion

Low cardiorespiratory fitness alone or combined with low lower-limb muscle strength, but not low lower-limb muscle strength alone, was associated with a higher cardiometabolic risk in older adults aged 60–80 years old. The assessment of physical fitness may be a “window of opportunity” to identify youngest-old adults with a high CVD risk and to establish preventive countermeasures (i.e., exercise training).

Supporting information

S1 Table. Characteristics of the outliers (n = 17).

https://doi.org/10.1371/journal.pone.0292957.s001

(DOCX)

S2 Table. Characteristics of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification (n = 360).

https://doi.org/10.1371/journal.pone.0292957.s002

(DOCX)

S3 Table. Distribution of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification (n = 360).

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(DOCX)

S4 Table. Distribution of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification by sex (n = 360).

https://doi.org/10.1371/journal.pone.0292957.s004

(DOCX)

S5 Table. Joint associations of cardiorespiratory fitness and lower-limb muscle strength with Metabolic Syndrome in community-dwelling older adults (n = 360).

https://doi.org/10.1371/journal.pone.0292957.s005

(DOCX)

S6 Table. Joint associations of cardiorespiratory fitness and lower-limb muscle strength with poor Ideal Cardiovascular Health in community-dwelling older adults (n = 360).

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(DOCX)

S1 Checklist. STROBE statement—Checklist of items that should be included in reports of observational studies.

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(DOCX)

Acknowledgments

We are grateful to the older adults who volunteered for this study.

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Figures

Abstract

Introduction

Methods

Participants

Cardiorespiratory fitness and lower-limb muscle strength

Cardiometabolic risk

Covariates

Statistical analysis

Results

Discussion

Conclusion

Supporting information

S1 Table. Characteristics of the outliers (n = 17).

S2 Table. Characteristics of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification (n = 360).

S3 Table. Distribution of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification (n = 360).

S4 Table. Distribution of the participants according to the cardiorespiratory fitness and lower-limb muscle strength classification by sex (n = 360).

S5 Table. Joint associations of cardiorespiratory fitness and lower-limb muscle strength with Metabolic Syndrome in community-dwelling older adults (n = 360).

S6 Table. Joint associations of cardiorespiratory fitness and lower-limb muscle strength with poor Ideal Cardiovascular Health in community-dwelling older adults (n = 360).

S1 Checklist. STROBE statement—Checklist of items that should be included in reports of observational studies.

Acknowledgments

References