Research design and participants:
This cross-sectional study was conducted based on the second stage of the Bushehr elderly health (BEH) program. The methodology of the BEH program has previously been reported in detail [22, 23]. The BEH program is a prospective cohort study in Bushehr, south of Iran, targeting a population of 60 and over. Among 3297 who were selected through multistage stratified random sampling, 3000 were accepted to participate in the first phase of the study (participants rate was 91%). The first stage was conducted from March 2013 to October 2014, and the second phase, focusing on musculoskeletal and cognitive outcomes, started in 2015 with 2368 who were following the first stage (response rate was 81%).
Measurement of laboratory parameters:
Venous blood samples were collected from the participants following 8–12 h of fasting condition. Red blood cell count (RBC), hemoglobin (Hgb), WBC, PLT were assessed by an automated hematology analyzer, Medonic CA620 (Menarini Diagnostic Srl, Florence, Italy). Blood urea nitrogen (BUN), creatinine (Cr), uric acid, alkaline phosphatase (Alk-p), fasting plasma glucose (FPG), and lipid profile were assessed by an auto-analyzer using commercial kits (ParsAzmun, Karaj, Iran). Hemoglobin A1c (HbA1c) was measured by the CERA-STAT system (CERAGEMMEDISYS,chungcheongnam-do, Korea).
Measures and definition of sarcopenia:
Sarcopenia was defined based on the current revised edition of the European Working Group on sarcopenia in Older People (EWGSOP2), issued recently and defined as having low muscle mass and low muscle strength; it is also characterized as severe if the previous criteria were extant with poor physical performance. Dual x-ray absorptiometry (DXA, Discovery WI, Hologic, Bedford, Virginia, USA) was used to measure fat mass and muscle mass with minimal radiation exposure. Appendicular skeletal muscle mass (ASM) for each participant was calculated as the sum of upper and lower limb muscle mass. The skeletal muscle mass index (SMI) was defined as ASM/height2 (kg/m2). According to previous studies, the cut-off point for low muscle mass was defined as SMI< 7.0 kg/m2 for men and < 5.4 kg/m2 for women in the Iranian population. Muscle strength was assessed based on handgrip strength and chair stand measures. Handgrip strength was measured three times for each hand using a digital dynamometer. The handgrip strength threshold was 26 kg for men and 18 kg for women. In this study, the chair stand test was used to assess the lower extremity muscle strength. For the measuring chair stand test, participants were asked to keep their arms folded across their chest; then, if participants could perform the first test, they were asked to stand up and sit down five times without using arms. Time was recorded for each participant from the initial sitting to the final standing position, and the cut-off point was defined as chair stand test time > 15 seconds. Physical performance was evaluated by short physical performance battery (SPPB) and usual gait speed. SPPB is a group of tests evaluating physical performance by combining the result of the chair stand, gait speed, and balance tests described elsewhere. For measuring the usual gait speed, participants were asked to walk for 4.57 m at a normal pace twice; then, the fastest record was used. Poor physical performance was defined as SPPB ≤ 8 point score or gait speed ≤ 0.8 m/s.
Metabolic syndrome (MetS) was defined according to the revised edition of national cholesterol education program adult treatment panel III (NCEP-ATP III), and cognitive function was assessed using the mini-mental state examination (MMSE), mini-cog, and categorical verbal fluency test (CFT), which have been described in the previous study . The chronic diseases included liver disease, lung disease, cardiovascular disease, thyroid diseases, osteoarthritis (OA), rheumatoid arthritis (RA), which were defined as self-reported or medication use. Chronic renal failure was defined as glomerular filtration rate (GFR) below 60; hypertension (HTN) as medication use, systolic blood pressure ≥ 140 mmHg, or diastolic blood pressure ≥ 90 mmHg), and diabetes mellitus (DM), as HbA1C≥6.5, FPG ≥ 126 mg/dl or taking anti-diabetic medication). Use of Anti-inflammatory medication was defined as the implementation of non-steroidal anti-inflammatory drugs (NSAID), azathioprine, mesalazine, sulfasalazine, methotrexate, mycophenolate mofetil, corticosteroids, colchicine, and tacrolimus. Use of anti-PLT medication was defined as the use of aspirin (ASA), clopidogrel, and dipyridamole. The use of anti-hyperlipidemic medication comprised the implementation of statins (atorvastatin, lovastatin, and simvastatin) or fibrates (gemfibrozil and fenofibrate). The use of HTN medication was characterized by the implementation of angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), alpha-blocker medications, beta-blockers, calcium channel blockers (CCBs), diuretic medications, and nitrates medications. Other covariates included age (years), gender (male/female), marital status (single, married, divorced, and widow), and smoking, which included no history of smoking, smoking regularly if the participant had a history of smoking at least one cigarette per day in a week, and the lower rate known as smoking occasionally. Still, as other covariates, body mass index (BMI ) was calculated by dividing weight (kg) to height squared (m2); waist to hip circumference ratio (WHR), which was calculated by dividing waist circumference (WC) to hip circumference (HC), and disability was assessed by instrumental activities of daily living (IADL) using Lawton scale questionnaires, translated into Persian.
The normality of all variables was assessed by the Kolmogorov–Smirnov test. PLT, WBC and PWR were divided into four quartiles as fellows: Q1 ≤ 220, 220 <Q2 < 259, 259≤ Q3≤ 300, and Q4> 300 (103 / for PLT; Q1 ≤ 6.1, 6.1 <Q2 < 7.3, 7.3≤ Q3≤ 8.4, and Q4> 8.4 (103/ for WBC, and Q1 ≤29.46, 29.46< Q2 < 36, 36≤ Q3≤ 43.28, and Q4> 43.28 for PWR. Categorical variables were presented by the frequency and percentage, and the mean and standard deviation (SD) were used for continuous variables. Differences in quartiles were evaluated by running one-way analysis of variance (ANOVA) and chi-square (X2) for continuous variables and categorical variables, respectively. Multivariable linear and logistic regression analyses were used to evaluate the association between PLT, sarcopenia, and sarcopenia parameters. Covariates that had a significant clinical and pathophysiological association with desired outcomes were first assessed by univariate regression models; then, statistically significant covariates were used in multivariate logistic regression analyses. Covariates were adjusted as: model 1= age, marital, and gender; model 2= model 1 + smoking, metabolic syndrome, cognitive disorder, and the number of chronic diseases; model 3 = model2 + Anti-inflammatory medications, anti-PLT medications, anti-diabetic medications, anti-hyperlipidemic medications, HTN medications, IADL, waist to hip ratio (WHR), and BMI; model 4= model 3 + laboratory parameters (HGB, WBC, HbA1c, HDL-cholesterol, ALK-P, TG, uric acid, and creatinine). Stata MP (version 15) was used, and a two-sided p-value of <0.05 was taken as statistically significant for all analyses. P-values for trends were obtained from adjusted models by assigning quartiles as continuous variables.