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Handgrip Strength-Related Factors Affecting Health Outcomes in Young Adults: Association with Cardiorespiratory Fitness

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Handgrip Strength-Related Factors Affecting Health Outcomes in Young Adults: Association with Cardiorespiratory Fitness Hindawi BioMed Research International Volume 2021, Article ID 6645252, 10 pages https://doi.org/10.1155/2021/6645252 Research Article Handgrip Strength-Related Factors Affecting Health Outcomes in Young Adults: Association with Cardiorespiratory Fitness Mingchao Zhou ,1 Fubing Zha ,1 Yuan Chen ,2 Fang Liu ,1 Jing Zhou ,1 Jianjun Long ,1 Wei Luo ,1 Meiling Huang ,1 Shaohua Zhang ,3 Donglan Luo ,3 Weihao Li ,1 and Yulong Wang 1 1The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China 2The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, Medical College, Shantou University, Shantou, Guangdong, China 3Shenzhen Dapeng New District Nan’ao People’s Hospital, Shenzhen, China Correspondence should be addressed to Yulong Wang; [email protected] Received 17 December 2020; Revised 22 March 2021; Accepted 9 April 2021; Published 22 April 2021 Academic Editor: Lei Jiang Copyright © 2021 Mingchao Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objectives. Handgrip strength (HS) is a risk factor of all-cause mortality and cardiovascular diseases. However, the influencing factors and mechanisms contributing to this correlation remain unclear. Therefore, we aimed to explore factors related to HS and investigated the mechanism underlying its risk predictive value. Methods. This was a prospective, cross-sectional study. One hundred forty-five participants were recruited from December 2019 to November 2020. HS was measured using a hydraulic hand dynamometer and adjusted for body mass index (HSBMI) and body surface area (HSBSA). Body composition was assessed via bioimpedance spectroscopy. Physical fitness was measured using a cardiopulmonary exercise test system. Univariate, multiple linear regression analyses and receiver operator characteristic curve (ROC) were conducted to evaluate the associations between various participant characteristics and HS. Results. The average participant age was : : 21 68 ± 2 61 years (42.8% were male). We found positive correlations between HSBMI/HSBSA and VO2max,VEmax, Loadmax, p : and METmax in both sexes ( <005). Lean-tissue, protein, total water, and inorganic salt percentages were positively correlated, and fat percentage was negatively correlated with HSBMI in men and with HSBMI and HSBSA in women p : β : ( <005). Multiple regression revealed that VO2max was independently associated with HSBSA in both sexes ( =0215, 0.173; 95%confidence interval ½CI =0:032 − 0:398, 0.026-0.321; p =0:022, 0.022, respectively) and independently associated β : % : − : p : with HSBMI in women ( =0016, 95 CI = 0 004 0 029, =0011). ROC analysis showed that HSBMI and HSBSA can ½ : p : moderately identify normal VO2max in men (area under curve AUC =0754, 0.769; =0002, 0.001, respectively) and : p : marginally identify normal VO2max in women (AUC = 0 643, 0.635; =0029, 0.042, respectively). Conclusions.BMI-and fl fi BSA-adjusted HS could serve as indicators of physical health, and HSBSA may moderately re ect cardiorespiratory tness levels in healthy young adults, particularly in males. Clinical trials registry site and number: China Clinical Trial Center (ChiCTR1900028228). 1. Introduction commonly used to evaluate sports performance in athletes [2]. In addition, HS is a risk factor for unfavorable health Handgrip strength (HS) is a simple measurement and a use- outcomes and is associated with all-cause mortality and car- ful indicator of physical strength. HS has been found to be diovascular diseases (CVD), not only in older individuals but strongly correlated with maximum upper and lower body also in young adults [3–5]. Low HS (defined as <26 kg for strength and overall muscle strength [1]. Therefore, HS is men and <16 kg for women) is significantly correlated with 2 BioMed Research International a high risk of premature mortality, an increased incidence of 2.2. Participants. Study participants were recruited using a disability, prolonged length of stay after hospitalization or convenience sample of young adult interns in the hospital. surgery [6], and high risk of cancer [7]. Therefore, HS Based on the sample size calculation method for a multiple measurement can provide abundant information for health regression study (https://www.danielsoper.com), a minimum assessments [8]. However, the factors or mechanisms under- sample size of 70 participants of each sex was needed to lying the association between HS and health outcomes achieve 90% power and to detect an effect size (Cohen’s f 2) remain unclear [9]. of 0.26 attributable to 5 independent variables using an F- Previous studies have shown that HS depends on age, sex, Test (multiple regression analysis) with a significance level body size, socioeconomic status, and physical activity levels (alpha) of 0.05. Combined with a 10% shedding rate, 154 [10, 11]; malnutrition and sarcopenia can significantly affect subjects were needed for this study. The participants were HS [12]. However, these factors are insufficient in explaining recruited from December 2019 to November 2020 based on the health assessment and risk prediction value of HS. Fur- the following inclusion and exclusion criteria. The inclusion thermore, these factors lead to a high heterogeneity of HS criterion was healthy young adults (aged 18–24 years) with between different populations and create difficulty in draw- a stable physical condition. The exclusion criteria were (1) ing comparative conclusions among them. Therefore, to congenital heart disease, (2) history of cardiac arrest, (3) neu- more effectively identify HS-related factors affecting health rological or muscular disorders, (4) fever or infection, and (5) outcomes, HS adjusted for body mass index and body surface allergy to electrode pads. Before data collection, participants fl area (HSBMI/HSBSA) has been used to reduce the in uence of were informed of the objectives and methodology of the heterogeneity on the results [13]. study, and written informed consent was obtained. Tea or fi VO2max, a representation of cardiorespiratory tness coffee was prohibited for at least 3 h before the tests. Tests (CRF), is closely correlated to physical health. Low VO2max were performed in an evaluation room with a temperature is recognized as a strong and independent risk factor for of 22–25°C. Except for scientific purposes, personal informa- all-cause mortality, CVD [14], diabetes mellitus [15], and tion and experimental data were kept strictly confidential. neoplasia [16] in healthy adults, and accordingly, VO2max was consistent with HS affecting health outcomes in healthy 2.3. Variables. Data for the following parameters were population [17, 18]. A recent study indicated a strong associ- recorded within 72 hours after admission (baseline): (1) ation between HS and VO2max in paraplegic men [12]. There- demographic factors, such as sex and age (years); (2) anthro- fore, we speculate that HS and CRF may be correlated with pometric factors, such as height (m), weight (kg), body mass each other, thereby interactively affecting the health out- index (BMI, kg/m2), body surface area (BSA), and resting comes in the general population. The aforementioned factors heart rate (HRrest, bpm); (3) body composition, including may influence HS and contribute to the risk predictive value lean-tissue percentage (%), fat percentage (%), protein of HS. The aim of this study was to explore the potential percentage (%), total water percentage (%), and inorganic indicators associated with HS, especially the possible interre- salt percentage (%); (4) physical fitness, including AT lationships between HS and CRF. (ml/kg·min), VO2max (ml/kg·min), HRrest (rpm), HRAT (rpm), HRmax (rpm), RERmax,VEmax (ml/min), Loadmax Δ (W), Psysmax (mmHg), Pdiamax (mmHg), METmax, VO2/ 2. Materials and Methods ΔLoad, ventilatory equivalent for carbon dioxide (VE/ ffi VCO2), and oxygen uptake e ciency slope (OUES); and (5) 2.1. Study Design. This was a prospective, cross-sectional living habits, such as smoking status (current smoker or non- study. This study is part of the “Study for the application smoker) and exercise habits (sedentary, exercise 1–2 times a value of grip strength on the unaffected side in patients week, exercise ≥3 times a week). BMI was calculated as body with stroke”, which involves two steps. The first step is weight/height in meters squared (kg/m2). BSA was calculated to explore the correlation between HS and CRF in healthy using pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiMosteller formula ð 2Þ ð Þ ð Þ young adults, the aim of the current study. The next step [BSA m = heigth cm × weigth kg /3600] [19]. HRrest is to test whether the association between grip strength was calculated as the average heart rate during 10 min of and cardiorespiratory fitness persists in stroke patients, quiet sitting. Body compositions were measured using a which will be undertaken in the future. Our overall goal body bioimpedance spectroscopy (X-one; Youjiu, Shanghai, is to extrapolate the associations found in healthy young China). Physical fitness was measured via a cardiopulmonary adults to stroke patients and to provide a useful predictive exercise test (CPET) evaluation system (MasterScreen; tool for stroke patients who have difficulty undertaking Ergoline, Germany).
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