The Joint Associations of Pulmonary Function and Relative Grip Strength with Metabolic Syndrome in Lung-Healthy Older Adults: A Cross-Sectional Study

The Joint Associations of Pulmonary Function and Relative Grip Strength with Metabolic Syndrome in Lung-Healthy Older Adults: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Joint Associations of Pulmonary Function and Relative Grip Strength with Metabolic Syndrome in Lung-Healthy Older Adults: A Cross-Sectional Study Joey M. Saavedra, Elizabeth C. Lefferts, Brian Downer, Duck-chul Lee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7208912/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Age-associated losses in healthy pulmonary function may reflect a phenotype of older adulthood at elevated risk of metabolic syndrome (MetS), even in the absence of lung disease. Greater relative grip strength is inversely associated with MetS, but the independent and combined associations of pulmonary function and relative grip strength with MetS in lung-healthy older adults is unclear. Methods We estimated the odds ratios (ORs) and 95% confidence intervals (95% CIs) of MetS across pulmonary function and relative grip strength tertiles (independent associations), and across combined categories of ‘pulmonary function, relative grip strength’ (joint associations), adjusting for potential confounders. Results There were 115 (32.6%) cases of MetS among 353 participants. Compared to the upper tertile of pulmonary function, the ORs (95% CIs) of MetS for the middle and lower tertiles were 1.66 (0.92-3.00) and 1.93 (1.04–3.05), respectively, with full attenuation following adjustment for relative grip strength. Compared to the upper tertile of relative grip strength, the ORs (95% CIs) of MetS for the middle and lower tertiles were 2.51 (1.28–4.93) and 6.34 (3.17–13.04), respectively, with minimal attenuation when adjusting for pulmonary function. Compared to ‘high pulmonary function, high relative grip strength’, the ORs (95% CIs) for ‘low pulmonary function, high relative grip strength’, ‘high pulmonary function, low relative grip strength’, and ‘low pulmonary function, low relative grip strength’ were 1.15 (0.57–2.30), 3.25 (1.69–6.22), and 4.46 (2.18–9.11), respectively. Conclusions Relative grip strength is associated with MetS irrespective of pulmonary function, potentially representing a target for cardiometabolic risk reduction in older adults experiencing compression of the healthy pulmonary function reserve. Clinical trial number: not applicable Respiratory health muscular function cardiovascular risk aging Figures Figure 1 Introduction Metabolic syndrome (MetS), a clustering of five cardiometabolic risk factors [ 1 ], is a highly prevalent condition of aging, affecting nearly half of adults aged 60 and above in the United States (US) [ 2 ]. The presence of MetS significantly increases the risk of cardiovascular disease (CVD) [ 3 ], the leading cause of death in older adults [ 4 ] and ~ 12% of CVD-related deaths among this population are attributable to MetS [ 5 ]. The determinants of MetS are multifactorial, typically including the classic biological and behavioral hallmarks of aging such as low-grade inflammation [ 6 ], physical inactivity [ 7 ], and insulin resistance [ 7 ]. Approximately 1 in 5 individuals will be over the age of 65 by 2030 in the US [ 8 ], meaning the economic burden associated with MetS will likely intensify with time [ 9 ]. Early identification of at-risk phenotypes, as well as the potential modifiers of risk within such phenotypes, may therefore provide public health decision-makers with a broader array of intervention targets to mitigate the development of MetS at the population level. Abnormal pulmonary function is a prevalent morbidity of older adulthood that frequently co-occurs with MetS [ 10 ], characterized by lung performance indices from spirometry that fall below population reference values [ 11 ]. Both abnormal pulmonary function and MetS share common CVD risk factors associated with aging such as low-grade inflammation and insulin resistance [ 12 ], with recent epidemiologic evidence suggesting as much as 13% of the association between abnormal pulmonary function and heart disease is explained by prevalent MetS [ 13 ]. While the relationships between abnormal pulmonary function, MetS, and adverse health outcomes are well-characterized, the associations between normal (i.e., non-impaired) pulmonary function with MetS is underexplored, despite evidence suggesting that low-but-normal pulmonary function is potentially disadvantageous for cardiovascular health [ 14 ]. Thus, consideration of the influence played by the compression of normal pulmonary function may highlight pre-clinical phenotypes that could benefit from early interventions to mitigate the occurrence and/or progression of MetS. A strong and consistent correlate of MetS in older adults is grip strength [ 15 ], an objective surrogate of whole-body muscle functioning that is highly prognostic of cardiovascular outcomes [ 16 ]. Indeed, greater levels of grip strength, particularly grip strength relative to body weight, are inversely associated with the components of MetS that drive CVD risk [ 17 ]. Relative grip strength provides a metric that reflects the interdependence of both body size and muscular fitness on cardiometabolic health that is not robustly captured by absolute measures of grip strength [ 17 ]. However, it is unclear if the association of relative grip strength with MetS is independent of normal pulmonary function, and addressing this research gap is important for elucidating potential targets for CVD prevention in older adulthood -- a critical period of the lifespan where declines in normal pulmonary function are accelerated by the effects of aging [ 18 ]. Therefore, we investigated the independent and combined associations of pulmonary function and relative grip strength with prevalent MetS in lung-healthy older adults. We hypothesized that low pulmonary function, low relative grip strength, and the combination of 'low pulmonary function, low relative grip strength', would be associated with the highest prevalence of MetS compared to the reciprocal phenotypes of high pulmonary function, high relative grip strength, and 'high pulmonary function, high relative grip strength', respectively. Methods Study population Data were drawn from the Physical Activity and Aging Study, an ongoing, prospective cohort study established in 2015 at Iowa State University (ISU), consisting of adults aged ≥ 65 years from the central Iowa region (US Midwest). Participants are enrolled using a mixture of recruitment strategies including word of mouth, social media, targeted e-mailing to campus employees, postal mailing of marketing material, and in-person events at community organizations (e.g., churches, health fairs, senior living facilities). Enrolled participants initially complete a series of medical history questionnaires and undertake a battery of health and physical function assessments. Individuals are invited for follow-up visits on a yearly (or longer) basis, repeating the same sequence of assessments until study withdrawal or death. At the time of analysis (February 2025), there were 459 people with pulmonary function (spirometry), grip strength, metrics of MetS, and who were free from respiratory morbidities (e.g., COPD, asthma, restrictive lung disease) and/or CVD (congestive heart failure, myocardial infarction, stroke). Those with respiratory morbidities and/or CVD were excluded since both are strongly associated with MetS [ 19 , 20 ], and the objective of this study was to explore the prevalence of MetS in the context of normal pulmonary function. Of these, 38 people were excluded due to poor spirometric performance (i.e., inability to produce at least three acceptable trials) [ 21 ], and a further 62 excluded due to the presence of abnormal pulmonary function, considered any instance where one or more of the following spirometric indices were less than or equal to the lower limit of normal (LLN), using the reference equations from the Global Lung Function Initiative [ 22 ]: 1) the Forced Expiratory Volume in 1 second (FEV 1 ), 2) the Forced Vital Capacity (FVC), and/or 3) the ratio between the two (FEV 1 /FVC). Of the remaining 359 participants, we excluded 6 due to missing covariates, resulting in a final analytic sample of 353 individuals aged 65–95 years. The study was approved by the ISU Institutional Review Board (IRB ID: 15–430) and followed the ethical principles outlined in the Declaration of Helsinki [ 23 ], with individuals providing written informed consent prior to participation. Assessment of Pulmonary Function Pulmonary function was evaluated using a handheld spirometer (EasyOne Air, NDD Medical Technologies, Andover, MA) [ 24 ], following the American Thoracic Society (ATS) [ 21 ]. Spirometric acceptability and reproducibility were evaluated via algorithms built into the device, and we excluded any tests that did not earn at least a 'C' grade -- a common approach used to mitigate bias stemming from inadequate performance of the maximal breathing maneuver [ 25 ]. Since lung function variability increases with age [ 18 ], and considering our sample consisted solely of older adults, we characterized pulmonary function using standardized FEV 1 Z-scores derived from the Global Lung Initiative reference database [ 22 ], aligning with ATS recommendations [ 26 ]. We specifically chose FEV 1 as the metric of pulmonary function because it is a robust predictor of cardiovascular morbidity [ 27 ]. Finally, we created tertiles of FEV 1 Z-scores (upper, middle, lower) to evaluate the independent associations of pulmonary function with prevalent MetS, with the upper tertile (highest pulmonary function) serving as the referent. Assessment of Relative Grip Strength We evaluated maximal isometric grip strength using the Jamar Plus + 12–604 handgrip dynamometer (Lafayette Instrument, Lafayette, IN), a device with high within-instrument ( r = 0.82) and between-instrument reliability (intraclass coefficient range: 0.90–0.97) [ 28 , 29 ]. Participants were instructed to squeeze the dynamometer as hard as they could for 3 seconds with a single hand, while seated in an upright position and with the forearm bent at 90° to the body. The maximum value achieved was recorded in kilograms (kg), with the procedure then emulated on the opposite hand. Participants undertook three trials on each hand, resting for a period of 1 minute between trials. Overall grip strength was calculated by averaging the maximum values of both the dominant and non-dominant hands [ 30 ]. We divided overall grip strength by total body mass (kg) to produce a metric of relative grip strength (kg/kg body mass) that was then categorized into tertiles (upper, middle, lower) to explore independent associations with prevalent MetS, with the upper tertile (highest relative grip strength) serving as the referent. Assessment of MetS components Using the National Cholesterol Education ATP III criteria [ 1 ], we defined metabolic syndrome as having ≥ 3 of the following: 1) elevated waist circumference (≥ 102cm and ≥ 88cm for men and women, respectively); 2) elevated blood pressure (≥ 130mmHg systolic pressure or ≥ 80mmHg diastolic pressure or drug treatment for hypertension); 3) elevated blood glucose (≥ 100mg/dL fasting glucose or drug treatment for elevated glucose); 4) elevated serum triglycerides (≥ 150mg/dL or drug treatment for elevated triglycerides); and/or 5) low levels of high-density lipoprotein cholesterol (HDL-C) (< 40mg/dL and < 50mg/dL for men and women, respectively). All components were evaluated in the morning of the on-site lab visit after an overnight fast with abstinence from alcohol, caffeinated drinks, and/or tobacco-related products. Waist circumference was measured twice at the level of the umbilicus in the standing position and at the end of a normal breath following the National Health and Nutrition Examination Survey guidelines [ 31 ], with the average of the two values used to characterize waist circumference. Brachial blood pressure was assessed on the upper left arm using an automated blood pressure device (Omron Intellisense Model HEM-907XL, Omron Healthcare, Kyoto, Japan) in accordance with American Heart Association guidelines, with the average of three measures used to characterize systolic and diastolic blood pressure. A phlebotomist used standard venipuncture techniques to obtain blood serum that was subsequently analyzed for glucose, triglycerides, and HDL-C by a third party (Quest Diagnostics). Covariates We extracted covariate information from responses to the medical history questionnaire or by direct measurement during the health assessments. These specific variables were chosen based on the approaches taken by previous studies, biological plausibility, consideration of the study sample size, and goodness-of-fit statistics, with the aim of minimizing bias caused by confounding and/or overfitting. Covariates included age (years), sex (male or female), smoking status (never or former/current), heavy alcohol consumption (yes or no), and cardiorespiratory fitness (CRF) (400m walk time, mins). Heavy alcohol consumption was categorized as > 14 and > 7 drinks for men and women, respectively, based on current US guidelines [ 32 ]. We evaluated CRF using the 400m walk test, with participants instructed to walk 10 laps along a 20m, straight line course as quickly as possible (without running) [ 33 ]. The time taken to complete the total distance of 400m (minutes) was used as a surrogate marker of CRF, as validated elsewhere [ 34 ]. Statistical analysis Participant characteristics were stratified by tertiles of pulmonary function and relative grip strength, with differences in characteristics across these tertiles evaluated using linear models or chi squared tests for continuous and categorical variables, respectively. We used multivariable logistic regression to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of MetS across tertiles of pulmonary function and relative grip strength, using the upper tertile of each (theoretical best) as the referent. Model 1 adjusted for age and sex, while Model 2 adjusted for Model 1 plus smoking status, heavy alcohol consumption, and CRF. Model 3 adjusted for Model 2 in addition to the continuous measure of relative grip strength (pulmonary function analysis only) or the continuous measure of pulmonary function (relative grip strength analysis only). Model fit was evaluated through inspection of changes in residual deviance with each model, in addition to an assessment of goodness-of-fit using Hosmer-Lemeshow tests. We also calculated the P trend to evaluate the linearity of prevalent MetS across tertiles of pulmonary function and relative grip strength. Finally, the ORs (95% CIs) of MetS per one standard deviation (SD) decrement in the continuous measures of pulmonary function and relative grip strength were calculated to provide an indication of the changing odds of MetS per realistic decrement in each main exposure. We dichotomized both pulmonary function and relative grip strength to create joint exposure categories to evaluate combined associations in a manner that preserved statistical power. The upper two-thirds and lower one-third of both pulmonary function and relative grip strength served as the ‘high’ and ‘low’ categories, respectively, resulting in four categories: 1) ‘high pulmonary function, high relative grip strength’, 2) ‘low pulmonary function, high relative grip strength’, 3) ‘high pulmonary function, low relative grip strength’, and 4) ‘low pulmonary function, low relative grip strength.’ We then estimated the adjusted ORs (95% CIs) of prevalent MetS using multivariable logistic regression, with ‘high pulmonary function, high relative grip strength’ (theoretical healthiest group) serving as the referent. Next, we performed stratified analyses to evaluate the consistency of the findings among subgroups of the analytic sample. Here, the ORs (95% CIs) of prevalent MetS were estimated as a function of ‘low pulmonary function’ (lower one-third) vs. the referent of ‘high pulmonary function’ (upper two-thirds). The same approach was taken for the sub-group analysis of relative grip strength, with ORs (95% CIs) of MetS estimated as a function of ‘low relative grip strength’ (lower one-third) vs. the referent of ‘high relative grip strength’ (upper two-thirds). The sub-groups analyzed included a median split of age (< 70 and ≥ 70 years), sex (male and female), smoking status (never and former/current), heavy alcohol consumption (yes and no), and CRF (high and low, characterized as the upper two-thirds and the lowest one-third of the CRF, respectively). We also conducted three sensitivity analyses to evaluate the robustness of our findings by redefining the primary exposure variables. First, we determined the independent associations of pulmonary function and relative grip strength with MetS across quartiles of each exposure. Second, we re-characterized pulmonary function using percent-predicted values of FEV 1 since this metric is still widely used in clinical practice. Third, we standardized grip strength to lean body mass among a sub-set of participants with Dual X-ray Absorptiometry measurements (n = 344), providing a metric of relative grip strength that was less ‘diluted’ by adiposity. Finally, as an exploratory exercise, we evaluated the independent associations of pulmonary function and relative grip strength with 1) abdominal obesity, 2) elevated blood pressure, 3) elevated blood glucose, 4) elevated triglycerides, and 5) low HDL-C in isolation, adjusting for potential confounders. This approach allowed us to gauge variations in the direction and magnitude of associations between our primary exposures and components of MetS, providing an indication of outcome consistency. All analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC), with two-sided p- values < 0.05 considered significant. Results There were 115 (32.6%) cases of MetS, and the mean (SD) age was 72.8 (5.7) years, with 63.2% being female (Table 1). On average, participants in the upper tertile of pulmonary function were less likely to have a history of smoking and had smaller waist circumference, whereas participants in the highest tertile of relative grip strength had better fitness, smaller waist circumference, lower systolic blood pressure, lower blood glucose, lower triglycerides, and lower HDL-C. Baseline characteristics by MetS status are documented in eTable 1 in Additional file 1. Table 1 Participant characteristics by tertiles of pulmonary function and relative grip strength. Characteristic All Tertiles of pulmonary function a P -value Tertiles of relative grip strength b P -value Upper Middle Lower Upper Middle Lower N 353 118 118 117 --- 117 119 117 --- Age, years (SD) 72.8 (5.7) 73.1 (5.6) 72.5 (5.4) 72.7 (6.1) 0.685 71.1 (5.1) 72.1 (4.9) 75.2 (6.4) < 0.001 Female, n (%) 223 (63.2) 76 (64.4) 68 (57.6) 79 (67.5) 0.274 74 (63.3) 75 (63.0) 74 (63.3) 0.999 Smoking status, n (%) Never 270 (76.5) 78 (66.1) 96 (81.4) 96 (82.1) 0.005 95 (81.2) 88 (74.0) 87 (74.4) 0.339 Former/current 83 (23.5) 40 (33.9) 22 (18.6) 21 (18.0) 22 (18.8) 31 (26.1) 30 (25.6) Heavy alcohol consumption c , n (%) 27 (7.7) 11 (9.3) 8 (6.8) 8 (6.8) 0.704 7 (6.0) 11 (9.2) 9 (7.7) 0.641 400m walk time d , mins (SD) 4.4 (0.8) 4.4 (0.9) 4.3 (0.7) 4.5 (0.8) 0.243 4.1 (0.4) 4.4 (0.8) 4.9 (0.9) < 0.001 FEV 1 , liters (SD) 2.4 (0.6) 2.7 (0.6) 2.5 (0.5) 2.1 (0.5) < 0.001 2.5 (0.6) 2.5 (0.6) 2.3 (0.6) 0.012 FEV 1 , percent predicted (SD) 98.9 (12.5) 112.5 (7.6) 98.8 (3.1) 85.2 (5.7) < 0.001 100.9 (14.3) 99.6 (10.9) 96.1 (11.8) 0.011 FEV 1 , Z-score e (SD) -0.06 (0.75) 0.76 (0.46) -0.07 (0.19) -0.87 (0.32) < 0.001 0.06 (0.87) -0.02 (0.66) -0.22 (0.68) 0.013 Relative grip strength, kg/kg of body mass (SD) 0.40 (0.11) 0.41 (0.11) 0.41 (0.10) 0.38 (0.11) 0.073 0.50 (0.07) 0.40 (0.06) 0.30 (0.07) < 0.001 Waist circumference, cm (SD) 92.5 (13.4) 90.0 (12.3) 93.9 (13.8) 93.8 (13.8) 0.038 83.8 (10.0) 94.2 (11.3) 99.6 (13.6) < 0.001 Systolic blood pressure, mmHg (SD) 124.8 (16.9) 122.6 (14.9) 124.5 (16.4) 127.2 (19.0) 0.116 121.4 (16.2) 126.5 (18.3) 126.3 (15.6) 0.034 Diastolic blood pressure, mmHg (SD) 71.7 (10.1) 70.6 (9.7) 71.4 (9.5) 73.1 (11.0) 0.162 70.4 (9.6) 72.7 (11.0) 71.9 (9.6) 0.223 Blood glucose, mg/dL (SD) 98.1 (17.7) 96.2 (12.7) 98.4 (19.6) 99.8 (19.8) 0.291 94.1 (10.8) 98.9 (21.3) 101.3 (18.5) 0.006 Triglycerides, mg/dL (SD) 110.4 (65.3) 107.8 (73.9) 114.7 (60.6) 108.8 (60.8) 0.679 93.2 (44.0) 116.2 (82.2) 121.9 (60.5) 0.002 High-density lipoprotein cholesterol (HDL-C), mg/dL (SD) 60.6 (15.7) 61.2 (15.4) 59.3 (16.3) 61.5 (15.4) 0.506 65.3 (15.6) 60.3 (15.4) 56.3 (14.8) < 0.001 MetS f n (%) 115 (32.6) 30 (25.4) 40 (33.9) 45 (38.5) 0.096 16 (13.7) 36 (30.3) 63 (53.9) < 0.001 MetS Components Elevated waist circumference, n (%) 158 (44.8) 41 (34.8) 54 (45.8) 63 (53.9) 0.013 14 (12.0) 61 (51.3) 83 (70.9) < 0.001 Elevated blood pressure, n (%) 177 (50.1) 50 (42.4) 56 (47.5) 71 (60.7) 0.015 49 (41.9) 58 (48.7) 70 (59.8) 0.022 Elevated blood glucose, n (%) 109 (30.9) 30 (25.4) 39 (33.1) 40 (34.2) 0.286 29 (24.8) 30 (25.2) 50 (42.7) 0.003 Elevated triglycerides, n (%) 166 (47.0) 49 (41.5) 57 (48.3) 60 (51.3) 0.307 42 (35.9) 57 (47.9) 67 (57.3) 0.005 Low HDL-C, n (%) 39 (11.1) 11 (9.3) 18 (15.3) 10 (8.6) 0.199 4 (3.4) 11 (9.2) 24 (20.5) < 0.001 No. of MetS components, n (%) 0 67 (19.0) 33 (28.0) 21 (17.8) 13 (11.1) 0.101 40 (34.2) 16 (13.5) 11 (9.4) < 0.001 1 94 (26.6) 33 (28.0) 30 (25.4) 31 (26.5) 36 (30.8) 39 (32.8) 19 (16.2) 2 77 (21.8) 22 (18.6) 27 (22.9) 28 (23.9) 25 (21.4) 28 (23.5) 24 (20.5) 3 70 (19.8) 17 (14.4) 25 (21.2) 28 (23.9) 12 (10.3) 23 (19.3) 35 (29.9) 4 34 (9.6) 12 (10.2) 10 (8.5) 12 (10.3) 4 (3.4) 12 (10.1) 18 (15.4) 5 11 (3.1) 1 (0.9) 5 (4.2) 5 (4.3) 0 1 (0.8) 10 (8.6) Notes: N, number; SD, standard deviation; FEV 1 , Forced Expiratory Volume in 1 second; MetS, Metabolic Syndrome. a Obtained by spirometry and subsequently characterized using Z-scores derived from the Global Lung Function initiative (GLI). b Average of the maximum values obtained from both the left and right hands, expressed as kilograms of grip force divided by total body mass (kg/kg of body mass). c Defined as >14 or >7 alcoholic drinks per week for men and women, respectively, as defined by the National Institute on Alcohol Abuse and Alcoholism (NIAAA). d A validated surrogate of cardiorespiratory fitness (CRF) in older adults (higher values suggest lower CRF). e A standardized residual indicating the number of standard deviations a measurement falls from a population mean (lower z-scores indicate lower lung function). Both the American Thoracic Society (ATS) and the European Respiratory Society (ERS) recommend the use of z-scores in the interpretation of spirometry. c Characterized as having ≥3 of the following characteristics: elevated waist circumference (men: >102cm; women: >88cm); elevated blood pressure (≥130mmHg systolic blood pressure; ≥85mmHg diastolic blood pressure; or drug treatment for hypertension); elevated blood glucose (≥100mg/dL; or drug treatment for elevated glucose); elevated triglycerides (≥150mg/dL; or drug treatment for elevated triglycerides); low high-density lipoprotein cholesterol [HDL-C] (men: <40mg/dL; women: <50mg/dL; or drug treatment for low HDL-C), as defined by the National Cholesterol Education Adult Treatment Panel III (NCEP-ATP III). Lower pulmonary function was associated with a higher prevalence of MetS after controlling for age and sex (Model 1, P for linear trend = 0.03) (Table 2). The relationship remained significant when adjusting for additional lifestyle factors (Model 2, P for linear trend = 0.03), however the association was attenuated after controlling for relative grip strength (Model 3, P for linear trend = 0.13). Conversely, lower relative grip strength was associated with a higher prevalence of MetS after controlling for all covariates, including pulmonary function ( P for linear trend across all three models < 0.01). Table 2 Odds ratios (95% confidence intervals) of metabolic syndrome (MetS) by tertiles of pulmonary function and relative grip strength. Pulmonary function Tertile (Mean ± SD FEV 1 Z-score) a Number of participants MetS cases (%) Model 1 Model 2 Model 3 Upper (0.76 ± 0.46) 118 30 (25.4) 1.00 (reference) 1.00 (reference) 1.00 (reference) Middle (-0.07 ± 0.19) 118 40 (33.9) 1.51 (0.85–2.66) 1.66 (0.92-3.00) 1.45 (0.78–2.69) Lower (-0.87 ± 0.32) 117 45 (38.5) 1.91 (1.09–2.66) 1.93 (1.04–3.50) 1.63 (0.88–3.01) P for linear trend 0.025 0.031 0.126 Per SD decrease in FEV 1 Z-score 1.30 (1.04–1.64) 1.30 (1.02–1.66) 1.21 (0.93–1.57) Relative grip strength Tertile (Mean ± SD kg/kg of body mass) Number of participants MetS cases (%) Model 1 Model 2 Model 3 Upper (0.50 ± 0.07) 117 16 (13.7) 1.00 (reference) 1.00 (reference) 1.00 (reference) Middle (0.40 ± 0.06) 119 36 (30.3) 2.78 (1.44–5.38) 2.51 (1.28–4.93) 2.46 (1.25–4.84) Lower (0.30 ± 0.07) 117 63 (53.9) 7.75 (3.97–15.13) 6.43 (3.17–13.04) 6.04 (2.97–12.31) P for linear trend < 0.001 < 0.001 < 0.001 Per SD decrease in relative grip strength 2.77 (1.99–3.85) 2.52 (1.77–3.58) 2.45 (1.72–3.49) Notes: FEV 1 , Forced Expiratory Volume in 1 second; SD, standard deviation. a Z-scores are a standardized metric that compares measurements of lung function to a healthy, non-smoking reference population (the reference population used for this analysis was the Global Lung Function Initiative [GLI]). A Z-Score of 0 equates to the mean value of the reference population (i.e., average pulmonary function), with more negative Z-scores reflecting lower lung function. Model 1 adjusted for age (years) and sex (male or female); Model 2 adjusted for Model 1 plus smoking status (never, former/current), heavy alcohol consumption (yes/no), and cardiorespiratory fitness (400m walk time); Model 3 adjusted for Model 2 plus relative grip strength (kg/kg of body mass) in the pulmonary function analysis, and pulmonary function (FEV 1 Z-score) in the relative grip strength analysis. Results of the combined associations of pulmonary function and relative grip strength with MetS indicate an increase in the prevalence of MetS with a theoretical worsening of the combined phenotype (Fig. 1). Compared to ‘high pulmonary function, high relative grip strength’ (referent), the adjusted ORs (95% CIs) of MetS were 1.15 (0.57–2.30), 3.25 (1.69–6.22), and 4.46 (2.18–9.11), for ‘low pulmonary function, high relative grip strength’; ‘high pulmonary function, low relative grip strength’; and ‘low pulmonary function, low relative grip strength’, respectively. Compared to those with high pulmonary function (middle and upper tertiles of FEV 1 Z-score), those with low pulmonary function (lower tertile of FEV 1 Z-score) generally had higher adjusted ORs of MetS, regardless of subgroup (except for those aged < 70 years and heavy drinkers), though no associations were statistically significant after adjusting for the confounders including grip strength (Table 3). Compared to those with high relative grip strength (middle and upper tertiles of relative grip strength), those with low relative grip strength (lower tertile of relative grip strength) generally had higher adjusted ORs of MetS, regardless of subgroup (except for heavy drinkers), and all associations were significant (except for those aged < 70 years) even after adjusting for the confounders including lung function. We found no evidence of interaction among subgroups in either analysis. Table 3. Independent associations of pulmonary function (A) and relative grip strength (B) with metabolic syndrome (MetS) across subgroups of the analytic sample. Pulmonary function (PF) Subgroup Number of participants MetS cases (%) Odds ratios (95% CIs) P for interaction High PF a Low PF a Age <70 years 126 29 (23.0) 1.00 (reference) 0.95 (0.36-2.48) 0.279 ≥70 years of age 227 86 (37.9) 1.00 (reference) 1.63 (0.86-3.07) Sex Male 130 50 (38.5) 1.00 (reference) 2.02 (0.86-4.75) 0.201 Female 223 65 (29.2) 1.00 (reference) 1.04 (0.54-1.99) Smoking status Never 270 87 (32.2) 1.00 (reference) 1.19 (0.66-2.13) 0.406 Former/current 83 28 (33.7) 1.00 (reference) 2.33 (0.75-7.29) Heavy alcohol consumption b Yes 27 12 (44.4) 1.00 (reference) 0.16 (0.01-3.22) 0.108 No 326 103 (31.6) 1.00 (reference) 1.51 (0.88-2.57) Cardiorespiratory fitness c High 236 54 (22.9) 1.00 (reference) 1.41 (0.70-2.84) 0.103 Low 117 61 (52.1) 1.00 (reference) 1.17 (0.53-2.57) Relative grip strength (RGS) Subgroup Number of participants MetS cases (%) Odds ratios (95% CIs) P for interaction High RGS d Low RGS d Age <70 years 126 29 (23.0) 1.00 (reference) 1.88 (0.63-5.63) 0.101 ≥70 years of age 227 86 (37.9) 1.00 (reference) 3.43 (1.84-6.39) Sex Male 130 50 (38.5) 1.00 (reference) 5.10 (2.18-11.94) 0.134 Female 223 65 (29.2) 1.00 (reference) 2.56 (1.25-5.26) Smoking status Never 270 87 (32.2) 1.00 (reference) 3.32 (1.78-6.18) 0.866 Former/current 83 28 (33.7) 1.00 (reference) 3.60 (1.19-10.87) Heavy alcohol consumption b Yes 27 12 (44.4) 1.00 (reference) 0.90 (0.11-7.67) 0.260 No 326 103 (31.6) 1.00 (reference) 3.77 (2.15-6.62) Cardiorespiratory fitness c High 236 54 (22.9) 1.00 (reference) 2.69 (1.26-5.74) 0.139 Low 117 61 (52.1) 1.00 (reference) 3.06 (1.31-7.18) The models above adjusted for age (years) except in the age-stratification, sex (male or female) except in the sex stratification, smoking status (never, former/current) except in the smoking stratification, heavy alcohol consumption (yes/no) except in the heavy alcohol stratification, cardiorespiratory fitness (400m walk time) except in the cardiorespiratory fitness stratification, pulmonary function (FEV 1 Z-score) except in in (A), and relative grip strength (kg/kg of body mass) except in (B). a The high PF phenotype was defined as the upper two-thirds of the pulmonary function (FEV 1 Z-score) distribution, with the lower third serving as low PF. b Defined as >14 or >7 alcoholic drinks per week for men and women, respectively, following the National Institute on Alcohol Abuse and Alcoholism (NIAAA) definition. c The high fit phenotype was defined as the upper two-thirds of the sex-specific 400m walk time distribution, with the lower third serving as the low fit phenotype. d The high RGS phenotype was defined as the upper two-thirds of the relative grip strength (kg/kg of body mass) distribution, with the lower third serving as low RGS. In the sensitivity analyses, the prevalence of MetS across quartiles of pulmonary function and relative grip strength remained consistent with that of the original tertile analysis (see eTable 2 in Additional file 1). Similarly, associations across tertiles of percent predicted FEV 1 and tertiles of relative grip strength (lean body mass) remained consistent with the associations observed in the main analysis (see eTable 3 in Additional file 1). Finally, the prevalence of each MetS component was greater with lower pulmonary function, but the associations were not independent of relative grip strength, except in the case of high blood pressure (see eFigure 1 in Additional file 1). The prevalence of each MetS component was greater with lower relative grip strength, and the association was independent of pulmonary function, except in the case of elevated blood pressure and elevated blood glucose (see eFigure 2 in Additional file 1). Discussion This cross-sectional study characterized the independent and combined associations of pulmonary function and relative grip strength with MetS in a cohort of 353 lung-healthy older adults. Our analyses demonstrated three key findings: 1) the prevalence of MetS is greater across lower categories of pulmonary function, but the association is not independent of relative grip strength; 2) the prevalence of MetS is greater across lower categories of relative grip strength, and the association is independent of pulmonary function; and 3) individuals with low relative grip strength have higher odds of MetS, regardless of concurrent pulmonary function status. These findings generally persisted across sub-groups and when using alternative definitions for the primary exposures, highlighting the consistency and robustness of the main observations. Thus, our data suggests that lower relative grip strength is associated with a higher prevalence of MetS in older adults, either in the presence or absence of low (but otherwise normal) pulmonary function, a respiratory phenotype not traditionally considered high-risk for cardiometabolic morbidity. The inverse associations between impaired pulmonary function and MetS are well-characterized [ 10 ], and while the mechanisms underscoring this relationship are unclear, one potential explanation is spillover of lung-derived inflammation into the systemic circulation, resulting in a cascade of metabolic and vascular disturbances (e.g., insulin resistance) that ultimately drive the etiology of MetS [ 35 ]. Indeed, the respiratory system as a potential source of inflammation is especially applicable to the findings of the present study since our older adult participants likely experienced varying degrees of cellular senescence, a proinflammatory process of aging that occurs even in the absence of lung disease [ 36 ]. While our study was not designed to evaluate such mechanistic underpinnings, we nevertheless demonstrated novelty by specifically focusing on MetS across categories of normal pulmonary function in lung-healthy older adults, suggesting the compression of pulmonary function (a process preceding the onset of lung impairment) [ 37 ] may itself be indicative of heightened susceptibility to poor metabolic health, particularly in the presence of poor grip strength [ 38 ]. Furthermore, while the risk of MetS may be amplified in the presence of lung impairment [ 10 ], MetS is not a phenotype defined by the absence of normal pulmonary function, as evidenced by the 32% prevalence of MetS in our lung-healthy sample. Since the association between normal pulmonary function and MetS was fully attenuated when adjusting for relative grip strength, our data could indicate that targeting muscular strength in lung healthy older adults before the onset of lung impairment may have favorable implications for cardiometabolic health, with such an approach likely more feasible and cost-effective than delaying interventions until the onset of lung impairment when barriers to physical activity (e.g., breathlessness) are well-established [ 39 ]. However, given the cross-sectional nature of the present study, these assertions are speculative until otherwise supported by well-designed prospective studies (e.g., randomized controlled trials). Synonymous with the results of our main analysis, we found the associations of pulmonary function with each component of MetS were likewise attenuated by relative grip strength, except in the case of hypertension. Indeed, those with the lowest pulmonary function had two times the odds of hypertension, independent of relative grip strength. Several studies have shown that lower pulmonary function is associated with hypertension in aging populations, even after adjusting for confounders such as physical activity [ 40 – 42 ]. One potential explanation for our findings could be differential usage of blood pressure medication across tertiles of pulmonary function (17.8%, 16.1%, and 23.1% for the upper, middle, and lower tertile, respectively). Medications such as beta blockers are associated with pulmonary function independent of blood pressure, with bronchoconstriction posited as a mechanism of action [ 43 ]. However, not all blood pressure medications are known to negatively influence pulmonary function, and since the present analyses did not differentiate between medication type, larger studies are needed to robustly interrogate the consistency of the association between pulmonary function and hypertension, independent of relative grip strength, in lung healthy older adults. While the association between relative grip strength and MetS in aging populations is well-characterized, the present study is the first to explore this relationship in the specific context of lung-healthy individuals. A recent meta-analysis of ~ 43,000 middle-aged and older adults found that compared to those with high relative grip strength, the OR (95% CI) of MetS for those with low relative grip strength was 2.97 (2.37–3.71) [ 44 ], an estimate of similar direction and magnitude to those elucidated in the present analyses, most notably when relative grip strength was standardized by lean body mass (see eTable 3 in Additional file 1). Muscle loss, impaired glucose metabolism, and subsequent insulin resistance leading to downstream metabolic disturbances (e.g., dyslipidemia) are commonly purported mechanisms underpinning the association between relative grip strength and MetS [ 45 ]. Indeed, compared to the upper tertile, those in the lower tertiles of relative grip strength had 15-, 9-, and 2-fold greater odds of the adiposity/lipid-linked components of MetS: abdominal obesity, low HDL-C, and elevated triglycerides, respectively (see eFigure 2 in Additional file 1), traits of metabolic dysregulation that underscore the feasibility of insulin resistance as a potential mechanism of the relative grip strength-MetS relationship. Novel to our study, however, is that the associations of relative grip strength with MetS as a standalone outcome, or when isolated to its adiposity/lipid-linked components, were independent of pulmonary function. This could be partly attributable to the healthy respiratory phenotype of our older adult sample, meaning the influence that impaired pulmonary function might otherwise have on MetS was essentially masked. Future studies should therefore explore the influence of relative grip strength on MetS across the entire spectrum of lung health (i.e., healthy and impaired) to determine if the association is truly independent of pulmonary function. Findings from such a study would provide clarity about the potential utility of muscular strength as a modifier of MetS risk in aging populations before the onset of lung impairment. The present study is also the first to explore the combined associations of pulmonary function and relative grip strength with MetS in lung healthy older adults. Our findings suggest that low relative grip strength, regardless of pulmonary function, is associated with greater odds of MetS, as well as with several individual components of MetS. Our data also suggests that 'low pulmonary function, low relative grip strength' has the highest odds of MetS relative to 'high pulmonary function, high relative grip strength.' In a conceptually similar cross-sectional study of ~ 200 older adults in Brazil, compared to 'high CRF, high muscular strength', those with 'low CRF and low muscular strength' had the highest odds of MetS [ 46 ]. In another conceptually similar study of ~ 6000 middle-aged and older adults in China, compared to 'high pulmonary function, high muscular strength', those with 'low pulmonary function, low muscular strength' had the highest risk of incident CVD [ 38 ]. Since higher CRF is associated with better indices of pulmonary function throughout older adulthood [ 47 ], and considering MetS is a major risk factor for incident CVD [ 3 ], our findings are somewhat analogous to previous research. However, additional studies are needed to validate the implications of combined 'pulmonary function, relative grip strength' phenotypes on MetS and/or its components. Such studies could provide stronger justification for interventions that concurrently target risk factors of respiratory and skeletal muscle disease, prevalent and co-occurring morbidities of aging [ 48 ], thereby aligning with national public health directives such as the "COPD National Action Plan" and the "Stronger than Sarcopenia Campaign" [ 49 , 50 ]. Our findings must be interpreted with caution given the following limitations. Firstly, the cross-sectional nature of this observational study means temporality cannot be established, and bias due to reverse causation cannot be discounted (e.g., MetS could be the antecedent to low pulmonary function). We addressed these limitations by 1) excluding individuals with respiratory and/or cardiovascular morbidities to mitigate potential confounding caused by the effects of these diseases on the exposures and/or outcome, 2) stratifying our analyses to evaluate consistency (effect modification) across sub-groups of the analytic sample, 3) performing several sensitivity analyses to assess the robustness of our findings under different analytical conditions (e.g., quartiles of pulmonary function and relative grip strength), and 4) exploring the independent associations of pulmonary function and relative grip strength with the individual components of MetS to gauge outcome variability. Nevertheless, larger prospective studies are clearly needed to better elucidate causal inferences in the pulmonary function/relative grip strength and MetS relationship in older adults. Additionally, our study was conducted in a limited sample of non-Hispanic white, well-educated, and high-functioning older adults from a Midwestern US state. While our findings are likely to have good internal validity, they are nevertheless limited in their generalizability to other older adult populations; future studies should address similar research questions in larger population-based cohorts with greater socio-demographic heterogeneity. Notwithstanding these limitations, our study is the first to provide evidence of the independent and combined associations of pulmonary function and relative grip strength with MetS in lung healthy older adults using validated and objective assessment methodologies, serving as a novel paradigm for the evaluation of cardiometabolic health risk through the lens of respiratory and muscular function. Conclusion This cross-sectional study found that the prevalence of MetS in lung healthy older adults was higher across lower categories of pulmonary function, but the association was no longer significant after further adjusting for relative grip strength. Additionally, the prevalence of MetS was higher across lower categories of relative grip strength, with the association remaining significant even after adjusting for pulmonary function. Finally, individuals with low relative grip strength, regardless of their concurrent pulmonary function status, had a significantly higher prevalence of MetS compared to those with ‘high pulmonary function, high relative grip strength’ – although individuals with both ‘low pulmonary function, low relative grip strength’ had the greatest odds of MetS overall. These findings are novel in that they frame MetS as a prevalent phenotype of low-but-normal pulmonary function, rather than simply as a phenotype of clinical lung impairment (e.g., obstructive airway disease). Our study additionally highlights the powerful associations of relative grip strength with MetS, independent of pulmonary function. Since aging is characterized by accelerated compression of the respiratory reserve (i.e., loss of normal pulmonary function), interventions that influence relative grip strength may have favorable implications for the MetS phenotype in lung-healthy older adults that might otherwise be less feasible by the time lung status becomes ‘unhealthy.’ Given the rising prevalence of chronic respiratory diseases among older adults in the US, it is likely that MetS and its associated complications will worsen with time. Larger, prospective studies should therefore build upon these initial findings to clarify the temporality of the pulmonary function/relative grip strength relationship with MetS, thereby providing stronger evidence of the utility of relative grip strength as a target for influencing cardiometabolic health in the face of a declining respiratory reserve. Declarations Clinical trial number Not applicable Acknowledgements We acknowledge the unwavering support of the PAAS participants, and we are grateful to the students and staff who contributed to the procurement and management of this data. Author contributions JMS was responsible for concept development, formal analysis, and writing. ECL was responsible for data curation and editing. BD was responsible for project supervision and editing. DCL was responsible for editing and giving final approval for publication. All authors contributed to the interpretation of results. Funding This work was supported by the National Institute on Aging under the Ruth L. Kirschstein training grant (AG T3200270). Data availability Data from this study are owned by Iowa State University, but legitimate researchers can request access by submitting an inquiry to [email protected] . Ethics approval and consent to participate This study was approved by the Institutional Review Board at Iowa State University (IRB ID: 15–430) and followed the ethical principles outlined in the Declaration of Helsinki,(23) with individuals providing written informed consent prior to participation. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. 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Eur Respir Rev. 2019;28(154):190049. http://doi.org/10.1183/16000617.0049-2019 Kiley JP, Gibbons GH. COPD National Action Plan: Addressing a Public Health Need Together. Chest. 2017;152(4):698-9. http://doi.org/10.1016/j.chest.2017.08.1155 Office on Women's Health. Stronger than Sarcopenia [Internet]. US Department of Health and Human Services; 2023 [cited 2025 May 1]. Available from: https://www.womenshealth.gov/sarcopenia/resources Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7208912","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496968109,"identity":"a23d4518-49e5-4888-a3d3-fc15458f319f","order_by":0,"name":"Joey M. Saavedra","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYBACxgYo3Q8kmJEEiNAys4GZSC1wrRsOEKuFedrxhx9+ttnIbr6Rf3RzAYON7IYDhEyfnWMs2duWZrztRjLb7RkMacbEaGGQ4DlzOBGshYfhcCIRWtIf//xz5n/i5hlgLf+J0ZJgJs1TcSBxgwRYywFitOSYWctUJBvPOPPY7PYMg2TjmYS0GAIddvONgZ1sf3vis9sFFXayfQS1NKBwDQgoBwF5ItSMglEwCkbBSAcAmApIU3KDan0AAAAASUVORK5CYII=","orcid":"","institution":"University of Texas Medical Branch","correspondingAuthor":true,"prefix":"","firstName":"Joey","middleName":"M.","lastName":"Saavedra","suffix":""},{"id":496968110,"identity":"70f0c6bb-5869-49ef-a056-1ff311a3ccc9","order_by":1,"name":"Elizabeth C. Lefferts","email":"","orcid":"","institution":"Iowa State University","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"C.","lastName":"Lefferts","suffix":""},{"id":496968111,"identity":"4fa36b9d-d9ed-4d9c-aad3-b7eaa5cfab51","order_by":2,"name":"Brian Downer","email":"","orcid":"","institution":"University of Texas Medical Branch","correspondingAuthor":false,"prefix":"","firstName":"Brian","middleName":"","lastName":"Downer","suffix":""},{"id":496968112,"identity":"f9adf904-f657-4ee5-864f-cb55527d3ed5","order_by":3,"name":"Duck-chul Lee","email":"","orcid":"","institution":"University of Pittsburgh","correspondingAuthor":false,"prefix":"","firstName":"Duck-chul","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2025-07-24 22:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7208912/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7208912/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88891151,"identity":"88626e65-36fe-4bcc-aee7-c551ff0ae5da","added_by":"auto","created_at":"2025-08-12 12:49:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":260248,"visible":true,"origin":"","legend":"\u003cp\u003eThe combined associations of pulmonary function (PF) and relative grip strength (RGS) with metabolic syndrome (MetS).\u003cbr\u003e\n Those in the upper two-thirds of pulmonary function or relative grip strength were categorized as ‘high PF’ or ‘high RGS’, respectively, while those in the lower third of each were categorized as ‘low PF’ or ‘low RGS’, respectively. The logistic regression model adjusted for age (years), sex (male or female), smoking status (never or former/current), heavy alcohol consumption (yes or no), and cardiorespiratory fitness (400m walk time).\u003c/p\u003e","description":"","filename":"Figure1BMCGeriatrics.png","url":"https://assets-eu.researchsquare.com/files/rs-7208912/v1/aeeeb01c92e6e1dcc4f649ac.png"},{"id":90289849,"identity":"5ff0a080-0c38-477e-9272-05b98d519e64","added_by":"auto","created_at":"2025-09-01 07:09:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1817985,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7208912/v1/a6fd08d5-0d2d-4d10-a215-0ebe4ca95765.pdf"},{"id":88891152,"identity":"58b529ea-563f-4e8a-81b5-d1e4fe1f5dae","added_by":"auto","created_at":"2025-08-12 12:49:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":453245,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7208912/v1/a254061a2ee1922c2372e725.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Joint Associations of Pulmonary Function and Relative Grip Strength with Metabolic Syndrome in Lung-Healthy Older Adults: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMetabolic syndrome (MetS), a clustering of five cardiometabolic risk factors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], is a highly prevalent condition of aging, affecting nearly half of adults aged 60 and above in the United States (US) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The presence of MetS significantly increases the risk of cardiovascular disease (CVD) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], the leading cause of death in older adults [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and ~ 12% of CVD-related deaths among this population are attributable to MetS [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The determinants of MetS are multifactorial, typically including the classic biological and behavioral hallmarks of aging such as low-grade inflammation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], physical inactivity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], and insulin resistance [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Approximately 1 in 5 individuals will be over the age of 65 by 2030 in the US [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], meaning the economic burden associated with MetS will likely intensify with time [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Early identification of at-risk phenotypes, as well as the potential modifiers of risk within such phenotypes, may therefore provide public health decision-makers with a broader array of intervention targets to mitigate the development of MetS at the population level.\u003c/p\u003e\u003cp\u003eAbnormal pulmonary function is a prevalent morbidity of older adulthood that frequently co-occurs with MetS [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], characterized by lung performance indices from spirometry that fall below population reference values [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Both abnormal pulmonary function and MetS share common CVD risk factors associated with aging such as low-grade inflammation and insulin resistance [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], with recent epidemiologic evidence suggesting as much as 13% of the association between abnormal pulmonary function and heart disease is explained by prevalent MetS [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. While the relationships between abnormal pulmonary function, MetS, and adverse health outcomes are well-characterized, the associations between normal (i.e., non-impaired) pulmonary function with MetS is underexplored, despite evidence suggesting that low-but-normal pulmonary function is potentially disadvantageous for cardiovascular health [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus, consideration of the influence played by the compression of normal pulmonary function may highlight pre-clinical phenotypes that could benefit from early interventions to mitigate the occurrence and/or progression of MetS.\u003c/p\u003e\u003cp\u003eA strong and consistent correlate of MetS in older adults is grip strength [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], an objective surrogate of whole-body muscle functioning that is highly prognostic of cardiovascular outcomes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Indeed, greater levels of grip strength, particularly grip strength relative to body weight, are inversely associated with the components of MetS that drive CVD risk [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Relative grip strength provides a metric that reflects the interdependence of both body size and muscular fitness on cardiometabolic health that is not robustly captured by absolute measures of grip strength [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, it is unclear if the association of relative grip strength with MetS is independent of normal pulmonary function, and addressing this research gap is important for elucidating potential targets for CVD prevention in older adulthood -- a critical period of the lifespan where declines in normal pulmonary function are accelerated by the effects of aging [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, we investigated the independent and combined associations of pulmonary function and relative grip strength with prevalent MetS in lung-healthy older adults. We hypothesized that low pulmonary function, low relative grip strength, and the combination of 'low pulmonary function, low relative grip strength', would be associated with the highest prevalence of MetS compared to the reciprocal phenotypes of high pulmonary function, high relative grip strength, and 'high pulmonary function, high relative grip strength', respectively.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy population\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData were drawn from the Physical Activity and Aging Study, an ongoing, prospective cohort study established in 2015 at Iowa State University (ISU), consisting of adults aged ≥ 65 years from the central Iowa region (US Midwest). Participants are enrolled using a mixture of recruitment strategies including word of mouth, social media, targeted e-mailing to campus employees, postal mailing of marketing material, and in-person events at community organizations (e.g., churches, health fairs, senior living facilities). Enrolled participants initially complete a series of medical history questionnaires and undertake a battery of health and physical function assessments. Individuals are invited for follow-up visits on a yearly (or longer) basis, repeating the same sequence of assessments until study withdrawal or death. At the time of analysis (February 2025), there were 459 people with pulmonary function (spirometry), grip strength, metrics of MetS, and who were free from respiratory morbidities (e.g., COPD, asthma, restrictive lung disease) and/or CVD (congestive heart failure, myocardial infarction, stroke). Those with respiratory morbidities and/or CVD were excluded since both are strongly associated with MetS [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and the objective of this study was to explore the prevalence of MetS in the context of normal pulmonary function. Of these, 38 people were excluded due to poor spirometric performance (i.e., inability to produce at least three acceptable trials) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and a further 62 excluded due to the presence of abnormal pulmonary function, considered any instance where one or more of the following spirometric indices were less than or equal to the lower limit of normal (LLN), using the reference equations from the Global Lung Function Initiative [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]: 1) the Forced Expiratory Volume in 1 second (FEV\u003csub\u003e1\u003c/sub\u003e), 2) the Forced Vital Capacity (FVC), and/or 3) the ratio between the two (FEV\u003csub\u003e1\u003c/sub\u003e/FVC). Of the remaining 359 participants, we excluded 6 due to missing covariates, resulting in a final analytic sample of 353 individuals aged 65–95 years. The study was approved by the ISU Institutional Review Board (IRB ID: 15–430) and followed the ethical principles outlined in the Declaration of Helsinki [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], with individuals providing written informed consent prior to participation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssessment of Pulmonary Function\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePulmonary function was evaluated using a handheld spirometer (EasyOne Air, NDD Medical Technologies, Andover, MA) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], following the American Thoracic Society (ATS) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Spirometric acceptability and reproducibility were evaluated via algorithms built into the device, and we excluded any tests that did not earn at least a 'C' grade -- a common approach used to mitigate bias stemming from inadequate performance of the maximal breathing maneuver [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Since lung function variability increases with age [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and considering our sample consisted solely of older adults, we characterized pulmonary function using standardized FEV\u003csub\u003e1\u003c/sub\u003e Z-scores derived from the Global Lung Initiative reference database [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], aligning with ATS recommendations [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We specifically chose FEV\u003csub\u003e1\u003c/sub\u003e as the metric of pulmonary function because it is a robust predictor of cardiovascular morbidity [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Finally, we created tertiles of FEV\u003csub\u003e1\u003c/sub\u003e Z-scores (upper, middle, lower) to evaluate the independent associations of pulmonary function with prevalent MetS, with the upper tertile (highest pulmonary function) serving as the referent.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssessment of Relative Grip Strength\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe evaluated maximal isometric grip strength using the Jamar Plus + 12–604 handgrip dynamometer (Lafayette Instrument, Lafayette, IN), a device with high within-instrument (\u003cem\u003er\u003c/em\u003e = 0.82) and between-instrument reliability (intraclass coefficient range: 0.90–0.97) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Participants were instructed to squeeze the dynamometer as hard as they could for 3 seconds with a single hand, while seated in an upright position and with the forearm bent at 90° to the body. The maximum value achieved was recorded in kilograms (kg), with the procedure then emulated on the opposite hand. Participants undertook three trials on each hand, resting for a period of 1 minute between trials. Overall grip strength was calculated by averaging the maximum values of both the dominant and non-dominant hands [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. We divided overall grip strength by total body mass (kg) to produce a metric of relative grip strength (kg/kg body mass) that was then categorized into tertiles (upper, middle, lower) to explore independent associations with prevalent MetS, with the upper tertile (highest relative grip strength) serving as the referent.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssessment of MetS components\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUsing the National Cholesterol Education ATP III criteria [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], we defined metabolic syndrome as having ≥ 3 of the following: 1) elevated waist circumference (≥ 102cm and ≥ 88cm for men and women, respectively); 2) elevated blood pressure (≥ 130mmHg systolic pressure or ≥ 80mmHg diastolic pressure or drug treatment for hypertension); 3) elevated blood glucose (≥ 100mg/dL fasting glucose or drug treatment for elevated glucose); 4) elevated serum triglycerides (≥ 150mg/dL or drug treatment for elevated triglycerides); and/or 5) low levels of high-density lipoprotein cholesterol (HDL-C) (\u0026lt; 40mg/dL and \u0026lt; 50mg/dL for men and women, respectively). All components were evaluated in the morning of the on-site lab visit after an overnight fast with abstinence from alcohol, caffeinated drinks, and/or tobacco-related products. Waist circumference was measured twice at the level of the umbilicus in the standing position and at the end of a normal breath following the National Health and Nutrition Examination Survey guidelines [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], with the average of the two values used to characterize waist circumference. Brachial blood pressure was assessed on the upper left arm using an automated blood pressure device (Omron Intellisense Model HEM-907XL, Omron Healthcare, Kyoto, Japan) in accordance with American Heart Association guidelines, with the average of three measures used to characterize systolic and diastolic blood pressure. A phlebotomist used standard venipuncture techniques to obtain blood serum that was subsequently analyzed for glucose, triglycerides, and HDL-C by a third party (Quest Diagnostics).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCovariates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe extracted covariate information from responses to the medical history questionnaire or by direct measurement during the health assessments. These specific variables were chosen based on the approaches taken by previous studies, biological plausibility, consideration of the study sample size, and goodness-of-fit statistics, with the aim of minimizing bias caused by confounding and/or overfitting. Covariates included age (years), sex (male or female), smoking status (never or former/current), heavy alcohol consumption (yes or no), and cardiorespiratory fitness (CRF) (400m walk time, mins). Heavy alcohol consumption was categorized as \u0026gt; 14 and \u0026gt; 7 drinks for men and women, respectively, based on current US guidelines [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. We evaluated CRF using the 400m walk test, with participants instructed to walk 10 laps along a 20m, straight line course as quickly as possible (without running) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The time taken to complete the total distance of 400m (minutes) was used as a surrogate marker of CRF, as validated elsewhere [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eParticipant characteristics were stratified by tertiles of pulmonary function and relative grip strength, with differences in characteristics across these tertiles evaluated using linear models or chi squared tests for continuous and categorical variables, respectively. We used multivariable logistic regression to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of MetS across tertiles of pulmonary function and relative grip strength, using the upper tertile of each (theoretical best) as the referent. Model 1 adjusted for age and sex, while Model 2 adjusted for Model 1 plus smoking status, heavy alcohol consumption, and CRF. Model 3 adjusted for Model 2 in addition to the continuous measure of relative grip strength (pulmonary function analysis only) or the continuous measure of pulmonary function (relative grip strength analysis only). Model fit was evaluated through inspection of changes in residual deviance with each model, in addition to an assessment of goodness-of-fit using Hosmer-Lemeshow tests. We also calculated the \u003cem\u003eP\u003c/em\u003e trend to evaluate the linearity of prevalent MetS across tertiles of pulmonary function and relative grip strength. Finally, the ORs (95% CIs) of MetS per one standard deviation (SD) decrement in the continuous measures of pulmonary function and relative grip strength were calculated to provide an indication of the changing odds of MetS per realistic decrement in each main exposure.\u003c/p\u003e\u003cp\u003eWe dichotomized both pulmonary function and relative grip strength to create joint exposure categories to evaluate combined associations in a manner that preserved statistical power. The upper two-thirds and lower one-third of both pulmonary function and relative grip strength served as the ‘high’ and ‘low’ categories, respectively, resulting in four categories: 1) ‘high pulmonary function, high relative grip strength’, 2) ‘low pulmonary function, high relative grip strength’, 3) ‘high pulmonary function, low relative grip strength’, and 4) ‘low pulmonary function, low relative grip strength.’ We then estimated the adjusted ORs (95% CIs) of prevalent MetS using multivariable logistic regression, with ‘high pulmonary function, high relative grip strength’ (theoretical healthiest group) serving as the referent.\u003c/p\u003e\u003cp\u003eNext, we performed stratified analyses to evaluate the consistency of the findings among subgroups of the analytic sample. Here, the ORs (95% CIs) of prevalent MetS were estimated as a function of ‘low pulmonary function’ (lower one-third) vs. the referent of ‘high pulmonary function’ (upper two-thirds). The same approach was taken for the sub-group analysis of relative grip strength, with ORs (95% CIs) of MetS estimated as a function of ‘low relative grip strength’ (lower one-third) vs. the referent of ‘high relative grip strength’ (upper two-thirds). The sub-groups analyzed included a median split of age (\u0026lt; 70 and ≥ 70 years), sex (male and female), smoking status (never and former/current), heavy alcohol consumption (yes and no), and CRF (high and low, characterized as the upper two-thirds and the lowest one-third of the CRF, respectively).\u003c/p\u003e\u003cp\u003eWe also conducted three sensitivity analyses to evaluate the robustness of our findings by redefining the primary exposure variables. First, we determined the independent associations of pulmonary function and relative grip strength with MetS across \u003cem\u003equartiles\u003c/em\u003e of each exposure. Second, we re-characterized pulmonary function using percent-predicted values of FEV\u003csub\u003e1\u003c/sub\u003e since this metric is still widely used in clinical practice. Third, we standardized grip strength to lean body mass among a sub-set of participants with Dual X-ray Absorptiometry measurements (n = 344), providing a metric of relative grip strength that was less ‘diluted’ by adiposity.\u003c/p\u003e\u003cp\u003eFinally, as an exploratory exercise, we evaluated the independent associations of pulmonary function and relative grip strength with 1) abdominal obesity, 2) elevated blood pressure, 3) elevated blood glucose, 4) elevated triglycerides, and 5) low HDL-C in isolation, adjusting for potential confounders. This approach allowed us to gauge variations in the direction and magnitude of associations between our primary exposures and components of MetS, providing an indication of outcome consistency.\u003c/p\u003e\u003cp\u003eAll analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC), with two-sided \u003cem\u003ep-\u003c/em\u003evalues \u0026lt; 0.05 considered significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThere were 115 (32.6%) cases of MetS, and the mean (SD) age was 72.8 (5.7) years, with 63.2% being female (Table\u0026nbsp;1). On average, participants in the upper tertile of pulmonary function were less likely to have a history of smoking and had smaller waist circumference, whereas participants in the highest tertile of relative grip strength had better fitness, smaller waist circumference, lower systolic blood pressure, lower blood glucose, lower triglycerides, and lower HDL-C. Baseline characteristics by MetS status are documented in eTable 1 in Additional file 1.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eParticipant characteristics by tertiles of pulmonary function and relative grip strength.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTertiles of pulmonary function\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eTertiles of relative grip strength\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, years (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.8 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.1 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.5 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.7 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.1 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.1 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.2 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e223 (63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (64.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75 (63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (63.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNever\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e270 (76.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78 (66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (81.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96 (82.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95 (81.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88 (74.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87 (74.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.339\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eFormer/current\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeavy alcohol consumption\u003csup\u003ec\u003c/sup\u003e, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e400m walk time\u003csup\u003ed\u003c/sup\u003e, mins (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e, liters (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.5 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e, percent predicted (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.9 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112.5 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.8 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.2 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.9 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.6 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.1 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV\u003csub\u003e1\u003c/sub\u003e, Z-score\u003csup\u003ee\u003c/sup\u003e (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.06 (0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76 (0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.07 (0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.87 (0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06 (0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.02 (0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.22 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRelative grip strength, kg/kg of body mass (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.41 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.41 (0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38 (0.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50 (0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40 (0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30 (0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWaist circumference, cm (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.5 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.0 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.9 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.8 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.038\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83.8 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.2 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.6 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystolic blood pressure, mmHg (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.8 (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e122.6 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e124.5 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e127.2 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121.4 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.5 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126.3 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiastolic blood pressure, mmHg (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.7 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.6 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.4 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73.1 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.4 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.7 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.9 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood glucose, mg/dL (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.1 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.2 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.4 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.8 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.1 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.9 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101.3 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTriglycerides, mg/dL (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110.4 (65.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107.8 (73.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114.7 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e108.8 (60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.2 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116.2 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121.9 (60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh-density lipoprotein cholesterol (HDL-C), mg/dL (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.6 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.2 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.3 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.5 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.3 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.3 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.3 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetS\u003csup\u003ef\u003c/sup\u003e \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e115 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetS Components\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElevated waist circumference, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (70.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElevated blood pressure, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e177 (50.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (60.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (59.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElevated blood glucose, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (24.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (42.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElevated triglycerides, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e166 (47.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (47.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow HDL-C, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo. of MetS components, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94 (26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70 (19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e(3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e N, number; SD, standard deviation; FEV\u003csub\u003e1\u003c/sub\u003e, Forced Expiratory Volume in 1 second; MetS, Metabolic Syndrome.\u0026nbsp;\u003cbr\u003e\u003csup\u003ea\u003c/sup\u003eObtained by spirometry and subsequently characterized using Z-scores derived from the Global Lung Function initiative (GLI).\u003csup\u003e\u003cbr\u003e\u0026nbsp;b\u003c/sup\u003eAverage of the maximum values obtained from both the left and right hands, expressed as kilograms of grip force divided by total body mass (kg/kg of body mass). \u003csup\u003ec\u003c/sup\u003eDefined as \u0026gt;14 or \u0026gt;7 alcoholic drinks per week for men and women, respectively, as defined by the National Institute on Alcohol Abuse and Alcoholism (NIAAA). \u003csup\u003ed\u003c/sup\u003eA validated surrogate of cardiorespiratory fitness (CRF) in older adults (higher values suggest lower CRF). \u003csup\u003ee\u003c/sup\u003eA standardized residual indicating the number of standard deviations a measurement falls from a population mean (lower z-scores indicate lower lung function). Both the American Thoracic Society (ATS) and the European Respiratory Society (ERS) recommend the use of z-scores in the interpretation of spirometry.\u003csup\u003e\u0026nbsp;c\u003c/sup\u003eCharacterized as having \u0026ge;3 of the following characteristics: elevated waist circumference (men: \u0026gt;102cm; women: \u0026gt;88cm); elevated blood pressure (\u0026ge;130mmHg systolic blood pressure; \u0026ge;85mmHg diastolic blood pressure; or drug treatment for hypertension); elevated blood glucose (\u0026ge;100mg/dL; or drug treatment for elevated glucose); elevated triglycerides (\u0026ge;150mg/dL; or drug treatment for elevated triglycerides); low high-density lipoprotein cholesterol [HDL-C] (men: \u0026lt;40mg/dL; women: \u0026lt;50mg/dL; or drug treatment for low HDL-C), as defined by the National Cholesterol Education Adult Treatment Panel III (NCEP-ATP III).\u003c/p\u003e\n\u003cp\u003eLower pulmonary function was associated with a higher prevalence of MetS after controlling for age and sex (Model 1, \u003cem\u003eP\u003c/em\u003e for linear trend\u0026thinsp;=\u0026thinsp;0.03) (Table\u0026nbsp;2). The relationship remained significant when adjusting for additional lifestyle factors (Model 2, \u003cem\u003eP\u003c/em\u003e for linear trend\u0026thinsp;=\u0026thinsp;0.03), however the association was attenuated after controlling for relative grip strength (Model 3, \u003cem\u003eP\u003c/em\u003e for linear trend\u0026thinsp;=\u0026thinsp;0.13). Conversely, lower relative grip strength was associated with a higher prevalence of MetS after controlling for all covariates, including pulmonary function (\u003cem\u003eP\u003c/em\u003e for linear trend across all three models\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eOdds ratios (95% confidence intervals) of metabolic syndrome (MetS) by tertiles of pulmonary function and relative grip strength.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003ePulmonary function\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTertile\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD FEV\u003csub\u003e1\u003c/sub\u003e Z-score)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetS cases (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(-0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.51\u003c/p\u003e\n \u003cp\u003e(0.85\u0026ndash;2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003cp\u003e(0.92-3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003cp\u003e(0.78\u0026ndash;2.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(-0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.91\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(1.09\u0026ndash;2.66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.93\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.04\u0026ndash;3.50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003cp\u003e(0.88\u0026ndash;3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for linear trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePer SD decrease in FEV\u003csub\u003e1\u003c/sub\u003e Z-score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.30\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.04\u0026ndash;1.64)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.30\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.02\u0026ndash;1.66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003cp\u003e(0.93\u0026ndash;1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eRelative grip strength\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTertile\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD kg/kg of body mass)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetS cases (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.78\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.44\u0026ndash;5.38)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.51\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.28\u0026ndash;4.93)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.46\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.25\u0026ndash;4.84)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.75\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(3.97\u0026ndash;15.13)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.43\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(3.17\u0026ndash;13.04)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.04\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(2.97\u0026ndash;12.31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for linear trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePer SD decrease in relative grip strength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.77\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.99\u0026ndash;3.85)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.52\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.77\u0026ndash;3.58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.45\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.72\u0026ndash;3.49)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e FEV\u003csub\u003e1\u003c/sub\u003e, Forced Expiratory Volume in 1 second; SD, standard deviation.\u003csup\u003e\u003cbr\u003e\u0026nbsp;a\u003c/sup\u003eZ-scores are a standardized metric that compares measurements of lung function to a healthy, non-smoking reference population (the reference population used for this analysis was the Global Lung Function Initiative [GLI]). A Z-Score of 0 equates to the mean value of the reference population (i.e., average pulmonary function), with more negative Z-scores reflecting lower lung function. \u003cstrong\u003eModel 1\u0026nbsp;\u003c/strong\u003eadjusted for age (years) and sex (male or female); \u003cstrong\u003eModel 2\u0026nbsp;\u003c/strong\u003eadjusted for Model 1 plus smoking status (never, former/current), heavy alcohol consumption (yes/no), and cardiorespiratory fitness (400m walk time); \u003cstrong\u003eModel 3\u0026nbsp;\u003c/strong\u003eadjusted for Model 2 plus relative grip strength (kg/kg of body mass) in the pulmonary function analysis, and pulmonary function (FEV\u003csub\u003e1\u003c/sub\u003e Z-score) in the relative grip strength analysis. \u003csup\u003e\u003cbr\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eResults of the combined associations of pulmonary function and relative grip strength with MetS indicate an increase in the prevalence of MetS with a theoretical worsening of the combined phenotype (Fig.\u0026nbsp;1). Compared to \u0026lsquo;high pulmonary function, high relative grip strength\u0026rsquo; (referent), the adjusted ORs (95% CIs) of MetS were 1.15 (0.57\u0026ndash;2.30), 3.25 (1.69\u0026ndash;6.22), and 4.46 (2.18\u0026ndash;9.11), for \u0026lsquo;low pulmonary function, high relative grip strength\u0026rsquo;; \u0026lsquo;high pulmonary function, low relative grip strength\u0026rsquo;; and \u0026lsquo;low pulmonary function, low relative grip strength\u0026rsquo;, respectively.\u003c/p\u003e\n\u003cp\u003eCompared to those with high pulmonary function (middle and upper tertiles of FEV\u003csub\u003e1\u003c/sub\u003e Z-score), those with low pulmonary function (lower tertile of FEV\u003csub\u003e1\u003c/sub\u003e Z-score) generally had higher adjusted ORs of MetS, regardless of subgroup (except for those aged\u0026thinsp;\u0026lt;\u0026thinsp;70 years and heavy drinkers), though no associations were statistically significant after adjusting for the confounders including grip strength (Table 3). Compared to those with high relative grip strength (middle and upper tertiles of relative grip strength), those with low relative grip strength (lower tertile of relative grip strength) generally had higher adjusted ORs of MetS, regardless of subgroup (except for heavy drinkers), and all associations were significant (except for those aged\u0026thinsp;\u0026lt;\u0026thinsp;70 years) even after adjusting for the confounders including lung function. We found no evidence of interaction among subgroups in either analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Independent associations of pulmonary function (A) and relative grip strength (B) with metabolic syndrome (MetS) across subgroups of the analytic sample.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003col\u003e\n \u003cli\u003e\u003cstrong\u003ePulmonary function (PF)\u003c/strong\u003e\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetS cases (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds ratios (95% CIs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003efor interaction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh PF\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow PF\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026lt;70 years\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e29 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e0.95 (0.36-2.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ge;70 years of age\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e86 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.63 (0.86-3.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e50 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e2.02 (0.86-4.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e65 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.04 (0.54-1.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eNever\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e87 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.19 (0.66-2.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eFormer/current\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e28 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e2.33 (0.75-7.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy alcohol consumption\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e12 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e0.16 (0.01-3.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e103 (31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.51 (0.88-2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiorespiratory fitness\u003c/strong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eHigh\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e54 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.41 (0.70-2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eLow\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e61 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.17 (0.53-2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003col start=\"2\"\u003e\n \u003cli\u003e\u003cstrong\u003eRelative grip strength (RGS)\u003c/strong\u003e\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of participants\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetS cases (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 37px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds ratios (95% CIs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003efor interaction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh RGS\u003c/strong\u003e\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow RGS\u003csup\u003ed\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026lt;70 years\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e29 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e1.88 (0.63-5.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026ge;70 years of age\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e86 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.43 (1.84-6.39)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eMale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e50 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.10 (2.18-11.94)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eFemale\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e65 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.56 (1.25-5.26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eNever\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e87 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.32 (1.78-6.18)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eFormer/current\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e28 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.60 (1.19-10.87)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy alcohol consumption\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e12 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.90 (0.11-7.67)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e103 (31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.77 (2.15-6.62)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiorespiratory fitness\u003c/strong\u003e\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eHigh\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15px;\"\u003e\n \u003cp\u003e236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e54 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.69 (1.26-5.74)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cem\u003eLow\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e61 (52.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.06 (1.31-7.18)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe models above adjusted for age (years) except in the age-stratification, sex (male or female) except in the sex stratification, smoking status (never, former/current) except in the smoking stratification, heavy alcohol consumption (yes/no) except in the heavy alcohol stratification, cardiorespiratory fitness (400m walk time) except in the cardiorespiratory fitness stratification, pulmonary function (FEV\u003csub\u003e1\u003c/sub\u003e Z-score) except in in (A), and relative grip strength (kg/kg of body mass) except in (B). \u003csup\u003ea\u003c/sup\u003eThe high PF phenotype was defined as the upper two-thirds of the pulmonary function (FEV\u003csub\u003e1\u003c/sub\u003e Z-score) distribution, with the lower third serving as low PF. \u003csup\u003eb\u003c/sup\u003eDefined as \u0026gt;14 or \u0026gt;7 alcoholic drinks per week for men and women, respectively, following the National Institute on Alcohol Abuse and Alcoholism (NIAAA) definition. \u003csup\u003ec\u003c/sup\u003eThe high fit phenotype was defined as the upper two-thirds of the sex-specific 400m walk time distribution, with the lower third serving as the low fit phenotype. \u003csup\u003ed\u003c/sup\u003eThe high RGS phenotype was defined as the upper two-thirds of the relative grip strength (kg/kg of body mass) distribution, with the lower third serving as low RGS.\u003c/p\u003e\n\u003cp\u003eIn the sensitivity analyses, the prevalence of MetS across quartiles of pulmonary function and relative grip strength remained consistent with that of the original tertile analysis (see eTable 2 in Additional file 1). Similarly, associations across tertiles of percent predicted FEV\u003csub\u003e1\u003c/sub\u003e and tertiles of relative grip strength (lean body mass) remained consistent with the associations observed in the main analysis (see eTable 3 in Additional file 1).\u003c/p\u003e\n\u003cp\u003eFinally, the prevalence of each MetS component was greater with lower pulmonary function, but the associations were not independent of relative grip strength, except in the case of high blood pressure (see eFigure 1 in Additional file 1). The prevalence of each MetS component was greater with lower relative grip strength, and the association was independent of pulmonary function, except in the case of elevated blood pressure and elevated blood glucose (see eFigure 2 in Additional file 1).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study characterized the independent and combined associations of pulmonary function and relative grip strength with MetS in a cohort of 353 lung-healthy older adults. Our analyses demonstrated three key findings: 1) the prevalence of MetS is greater across lower categories of pulmonary function, but the association is not independent of relative grip strength; 2) the prevalence of MetS is greater across lower categories of relative grip strength, and the association is independent of pulmonary function; and 3) individuals with low relative grip strength have higher odds of MetS, regardless of concurrent pulmonary function status. These findings generally persisted across sub-groups and when using alternative definitions for the primary exposures, highlighting the consistency and robustness of the main observations. Thus, our data suggests that lower relative grip strength is associated with a higher prevalence of MetS in older adults, either in the presence or absence of low (but otherwise normal) pulmonary function, a respiratory phenotype not traditionally considered high-risk for cardiometabolic morbidity.\u003c/p\u003e\u003cp\u003eThe inverse associations between impaired pulmonary function and MetS are well-characterized [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and while the mechanisms underscoring this relationship are unclear, one potential explanation is spillover of lung-derived inflammation into the systemic circulation, resulting in a cascade of metabolic and vascular disturbances (e.g., insulin resistance) that ultimately drive the etiology of MetS [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Indeed, the respiratory system as a potential source of inflammation is especially applicable to the findings of the present study since our older adult participants likely experienced varying degrees of cellular senescence, a proinflammatory process of aging that occurs even in the absence of lung disease [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. While our study was not designed to evaluate such mechanistic underpinnings, we nevertheless demonstrated novelty by specifically focusing on MetS across categories of normal pulmonary function in lung-healthy older adults, suggesting the compression of pulmonary function (a process preceding the onset of lung impairment) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] may itself be indicative of heightened susceptibility to poor metabolic health, particularly in the presence of poor grip strength [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Furthermore, while the risk of MetS may be amplified in the presence of lung impairment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], MetS is not a phenotype defined by the absence of normal pulmonary function, as evidenced by the 32% prevalence of MetS in our lung-healthy sample. Since the association between normal pulmonary function and MetS was fully attenuated when adjusting for relative grip strength, our data could indicate that targeting muscular strength in lung healthy older adults before the onset of lung impairment may have favorable implications for cardiometabolic health, with such an approach likely more feasible and cost-effective than delaying interventions until the onset of lung impairment when barriers to physical activity (e.g., breathlessness) are well-established [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. However, given the cross-sectional nature of the present study, these assertions are speculative until otherwise supported by well-designed prospective studies (e.g., randomized controlled trials).\u003c/p\u003e\u003cp\u003eSynonymous with the results of our main analysis, we found the associations of pulmonary function with each component of MetS were likewise attenuated by relative grip strength, except in the case of hypertension. Indeed, those with the lowest pulmonary function had two times the odds of hypertension, independent of relative grip strength. Several studies have shown that lower pulmonary function is associated with hypertension in aging populations, even after adjusting for confounders such as physical activity [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. One potential explanation for our findings could be differential usage of blood pressure medication across tertiles of pulmonary function (17.8%, 16.1%, and 23.1% for the upper, middle, and lower tertile, respectively). Medications such as beta blockers are associated with pulmonary function independent of blood pressure, with bronchoconstriction posited as a mechanism of action [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. However, not all blood pressure medications are known to negatively influence pulmonary function, and since the present analyses did not differentiate between medication type, larger studies are needed to robustly interrogate the consistency of the association between pulmonary function and hypertension, independent of relative grip strength, in lung healthy older adults.\u003c/p\u003e\u003cp\u003eWhile the association between relative grip strength and MetS in aging populations is well-characterized, the present study is the first to explore this relationship in the specific context of lung-healthy individuals. A recent meta-analysis of ~\u0026thinsp;43,000 middle-aged and older adults found that compared to those with high relative grip strength, the OR (95% CI) of MetS for those with low relative grip strength was 2.97 (2.37\u0026ndash;3.71) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], an estimate of similar direction and magnitude to those elucidated in the present analyses, most notably when relative grip strength was standardized by lean body mass (see eTable 3 in Additional file 1). Muscle loss, impaired glucose metabolism, and subsequent insulin resistance leading to downstream metabolic disturbances (e.g., dyslipidemia) are commonly purported mechanisms underpinning the association between relative grip strength and MetS [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Indeed, compared to the upper tertile, those in the lower tertiles of relative grip strength had 15-, 9-, and 2-fold greater odds of the adiposity/lipid-linked components of MetS: abdominal obesity, low HDL-C, and elevated triglycerides, respectively (see eFigure 2 in Additional file 1), traits of metabolic dysregulation that underscore the feasibility of insulin resistance as a potential mechanism of the relative grip strength-MetS relationship. Novel to our study, however, is that the associations of relative grip strength with MetS as a standalone outcome, or when isolated to its adiposity/lipid-linked components, were independent of pulmonary function. This could be partly attributable to the healthy respiratory phenotype of our older adult sample, meaning the influence that impaired pulmonary function might otherwise have on MetS was essentially masked. Future studies should therefore explore the influence of relative grip strength on MetS across the entire spectrum of lung health (i.e., healthy and impaired) to determine if the association is truly independent of pulmonary function. Findings from such a study would provide clarity about the potential utility of muscular strength as a modifier of MetS risk in aging populations before the onset of lung impairment.\u003c/p\u003e\u003cp\u003eThe present study is also the first to explore the combined associations of pulmonary function and relative grip strength with MetS in lung healthy older adults. Our findings suggest that low relative grip strength, regardless of pulmonary function, is associated with greater odds of MetS, as well as with several individual components of MetS. Our data also suggests that 'low pulmonary function, low relative grip strength' has the highest odds of MetS relative to 'high pulmonary function, high relative grip strength.' In a conceptually similar cross-sectional study of ~\u0026thinsp;200 older adults in Brazil, compared to 'high CRF, high muscular strength', those with 'low CRF and low muscular strength' had the highest odds of MetS [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In another conceptually similar study of ~\u0026thinsp;6000 middle-aged and older adults in China, compared to 'high pulmonary function, high muscular strength', those with 'low pulmonary function, low muscular strength' had the highest risk of incident CVD [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Since higher CRF is associated with better indices of pulmonary function throughout older adulthood [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], and considering MetS is a major risk factor for incident CVD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], our findings are somewhat analogous to previous research. However, additional studies are needed to validate the implications of combined 'pulmonary function, relative grip strength' phenotypes on MetS and/or its components. Such studies could provide stronger justification for interventions that concurrently target risk factors of respiratory and skeletal muscle disease, prevalent and co-occurring morbidities of aging [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], thereby aligning with national public health directives such as the \"COPD National Action Plan\" and the \"Stronger than Sarcopenia Campaign\" [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur findings must be interpreted with caution given the following limitations. Firstly, the cross-sectional nature of this observational study means temporality cannot be established, and bias due to reverse causation cannot be discounted (e.g., MetS could be the antecedent to low pulmonary function). We addressed these limitations by 1) excluding individuals with respiratory and/or cardiovascular morbidities to mitigate potential confounding caused by the effects of these diseases on the exposures and/or outcome, 2) stratifying our analyses to evaluate consistency (effect modification) across sub-groups of the analytic sample, 3) performing several sensitivity analyses to assess the robustness of our findings under different analytical conditions (e.g., quartiles of pulmonary function and relative grip strength), and 4) exploring the independent associations of pulmonary function and relative grip strength with the individual components of MetS to gauge outcome variability. Nevertheless, larger prospective studies are clearly needed to better elucidate causal inferences in the pulmonary function/relative grip strength and MetS relationship in older adults. Additionally, our study was conducted in a limited sample of non-Hispanic white, well-educated, and high-functioning older adults from a Midwestern US state. While our findings are likely to have good internal validity, they are nevertheless limited in their generalizability to other older adult populations; future studies should address similar research questions in larger population-based cohorts with greater socio-demographic heterogeneity. Notwithstanding these limitations, our study is the first to provide evidence of the independent and combined associations of pulmonary function and relative grip strength with MetS in lung healthy older adults using validated and objective assessment methodologies, serving as a novel paradigm for the evaluation of cardiometabolic health risk through the lens of respiratory and muscular function.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis cross-sectional study found that the prevalence of MetS in lung healthy older adults was higher across lower categories of pulmonary function, but the association was no longer significant after further adjusting for relative grip strength. Additionally, the prevalence of MetS was higher across lower categories of relative grip strength, with the association remaining significant even after adjusting for pulmonary function. Finally, individuals with low relative grip strength, regardless of their concurrent pulmonary function status, had a significantly higher prevalence of MetS compared to those with \u0026lsquo;high pulmonary function, high relative grip strength\u0026rsquo; \u0026ndash; although individuals with both \u0026lsquo;low pulmonary function, low relative grip strength\u0026rsquo; had the greatest odds of MetS overall. These findings are novel in that they frame MetS as a prevalent phenotype of low-but-normal pulmonary function, rather than simply as a phenotype of clinical lung impairment (e.g., obstructive airway disease). Our study additionally highlights the powerful associations of relative grip strength with MetS, independent of pulmonary function. Since aging is characterized by accelerated compression of the respiratory reserve (i.e., loss of normal pulmonary function), interventions that influence relative grip strength may have favorable implications for the MetS phenotype in lung-healthy older adults that might otherwise be less feasible by the time lung status becomes \u0026lsquo;unhealthy.\u0026rsquo; Given the rising prevalence of chronic respiratory diseases among older adults in the US, it is likely that MetS and its associated complications will worsen with time. Larger, prospective studies should therefore build upon these initial findings to clarify the temporality of the pulmonary function/relative grip strength relationship with MetS, thereby providing stronger evidence of the utility of relative grip strength as a target for influencing cardiometabolic health in the face of a declining respiratory reserve.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the unwavering support of the PAAS participants, and we are grateful to the students and staff who contributed to the procurement and management of this data. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJMS was responsible for concept development, formal analysis, and writing. ECL was responsible for data curation and editing. BD was responsible for project supervision and editing. DCL was responsible for editing and giving final approval for publication. All authors contributed to the interpretation of results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Institute on Aging under the Ruth L. Kirschstein training grant \u0026nbsp;(AG T3200270).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from this study are owned by Iowa State University, but legitimate researchers can request access by submitting an inquiry to [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board at Iowa State University (IRB ID: 15\u0026ndash;430) and followed the ethical principles outlined in the Declaration of Helsinki,(23) with individuals providing written informed consent prior to participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003cbr\u003e\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eSealy Center on Aging, University of Texas Medical Branch, Galveston, TX\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Kinesiology, Iowa State University, Ames, IA\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDepartment of Population Health and Health Disparities, University of Texas Medical Branch, Galveston, TX\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003eDepartment of Health and Human Development, University of Pittsburgh, Pittsburgh, PA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGrundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. 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The longitudinal association between physical activity, strength and fitness, and lung function: A UK Biobank cohort study. Respir Med. 2023;220:107476. http://doi.org/10.1016/j.rmed.2023.107476\u003c/li\u003e\n\u003cli\u003eBenz E, Trajanoska K, Lahousse L, Schoufour JD, Terzikhan N, De Roos E, et al. Sarcopenia in COPD: A systematic review and meta-analysis. Eur Respir Rev. 2019;28(154):190049. http://doi.org/10.1183/16000617.0049-2019\u003c/li\u003e\n\u003cli\u003eKiley JP, Gibbons GH. COPD National Action Plan: Addressing a Public Health Need Together. Chest. 2017;152(4):698-9. http://doi.org/10.1016/j.chest.2017.08.1155\u003c/li\u003e\n\u003cli\u003eOffice on Women\u0026apos;s Health. Stronger than Sarcopenia [Internet]. US Department of Health and Human Services; 2023 [cited 2025 May 1]. Available from: https://www.womenshealth.gov/sarcopenia/resources\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Respiratory health, muscular function, cardiovascular risk, aging","lastPublishedDoi":"10.21203/rs.3.rs-7208912/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7208912/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAge-associated losses in healthy pulmonary function may reflect a phenotype of older adulthood at elevated risk of metabolic syndrome (MetS), even in the absence of lung disease. Greater relative grip strength is inversely associated with MetS, but the independent and combined associations of pulmonary function and relative grip strength with MetS in lung-healthy older adults is unclear.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe estimated the odds ratios (ORs) and 95% confidence intervals (95% CIs) of MetS across pulmonary function and relative grip strength tertiles (independent associations), and across combined categories of \u0026lsquo;pulmonary function, relative grip strength\u0026rsquo; (joint associations), adjusting for potential confounders.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThere were 115 (32.6%) cases of MetS among 353 participants. Compared to the upper tertile of pulmonary function, the ORs (95% CIs) of MetS for the middle and lower tertiles were 1.66 (0.92-3.00) and 1.93 (1.04\u0026ndash;3.05), respectively, with full attenuation following adjustment for relative grip strength. Compared to the upper tertile of relative grip strength, the ORs (95% CIs) of MetS for the middle and lower tertiles were 2.51 (1.28\u0026ndash;4.93) and 6.34 (3.17\u0026ndash;13.04), respectively, with minimal attenuation when adjusting for pulmonary function. Compared to \u0026lsquo;high pulmonary function, high relative grip strength\u0026rsquo;, the ORs (95% CIs) for \u0026lsquo;low pulmonary function, high relative grip strength\u0026rsquo;, \u0026lsquo;high pulmonary function, low relative grip strength\u0026rsquo;, and \u0026lsquo;low pulmonary function, low relative grip strength\u0026rsquo; were 1.15 (0.57\u0026ndash;2.30), 3.25 (1.69\u0026ndash;6.22), and 4.46 (2.18\u0026ndash;9.11), respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eRelative grip strength is associated with MetS irrespective of pulmonary function, potentially representing a target for cardiometabolic risk reduction in older adults experiencing compression of the healthy pulmonary function reserve.\u003c/p\u003e\u003ch2\u003eClinical trial number:\u003c/h2\u003e\u003cp\u003enot applicable\u003c/p\u003e","manuscriptTitle":"The Joint Associations of Pulmonary Function and Relative Grip Strength with Metabolic Syndrome in Lung-Healthy Older Adults: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 12:48:57","doi":"10.21203/rs.3.rs-7208912/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"af13e9cb-756e-497d-828d-2b4fdb8183df","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-01T07:08:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 12:48:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7208912","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7208912","identity":"rs-7208912","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}