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Introduction: Body mass index (BMI) is a key parameter used for obesity classification and the evaluation and monitoring of individuals' health status. Obesity, described by the World Health Organization as a major global epidemic, remains one of the most significant preventable and manageable conditions contributing to increased risks of cardiovascular and metabolic diseases. In addition to BMI, anthropometric measurements such as the waist-to-hip ratio are crucial indicators for risk assessment. While numerous studies in the literature have addressed the detrimental effects of obesity on respiratory functions, no study has specifically examined the relationship between cough strength-a vital respiratory parameter that reflects expiratory muscle strength- and body composition, waist-to-hip ratio, and peripheral muscle strength. Furthermore, although several studies have investigated the association between grip strength-a recognized indicator of peripheral muscle function in healthy individuals-and cough strength, no research to date has explored the relationship between pinch grip strength and cough strength.
Objective: This study aims to investigate the relationships among body composition, waist-to-hip ratio, peripheral muscle strength, and cough strength in healthy young adults.
Methods: This study was designed as a cross-sectional analysis. After providing detailed information about the study to potential participants, written informed consent will be obtained in duplicate from those who agree to participate. Following the completion of a general assessment form that captures demographic characteristics, each participant's height will be measured using a measuring tape. Body composition parameters-including body weight, BMI, body fat percentage, total body water percentage, muscle mass, basal metabolic rate, and metabolic age-will be assessed using a bioelectrical impedance analysis device (Tanita) available at our faculty.
Waist and hip circumferences will be measured and used to calculate the waist-to-hip ratio for each participant. Peripheral muscle strength will be assessed using a hydraulic hand dynamometer and a pinch meter, while cough strength will be evaluated using a peak cough expiratory flow meter (PEF meter). All measurements will be repeated three times, with the best result recorded for analysis. Results: Statistical analysis will be performed using IBM SPSS Statistics version 30 (SPSS Inc., Chicago, IL, USA). Normality of continuous variables will be assessed through normality tests, coefficient of variation, and graphical representations (e.g., histograms, detrended plots). Descriptive statistics will be presented as mean ± standard deviation for normally distributed variables, and as median and interquartile range for non-normally distributed variables. Categorical variables will be expressed as percentages (%). Pearson correlation analysis will be used for normally distributed variables, and Spearman correlation analysis for non-normally distributed ones. The appropriate correlation coefficients and p-values will be reported. A p-value of <0.05 will be considered statistically significant.
Discussion: Interpretation will be based on the results of the statistical analyses.
Full description
Body mass index (BMI) is an important parameter used to assess and monitor the health status of individuals by classifying obesity. Obesity, defined as a major epidemic by the World Health Organization, is the most important preventable and controllable problem that increases the risk of cardiovascular and metabolic diseases. It is estimated that more than 1 billion adults worldwide will be obese by 2030 (1,2). The COVID-19 pandemic and the increasing dependence on technology are increasing the sedentary population and changing dietary habits, thereby increasing obesity rates (3,4). In addition to BMI, the waist-to-hip ratio, an anthropometric measurement, is also an important parameter in determining risk. In individuals with abdominal fat or atrophy in large muscle groups, waist circumference may be larger than hip circumference. This results in a high waist-to-hip ratio (5). Many studies conducted during the COVID-19 pandemic have reported higher COVID-19-related mortality rates in countries with obese or overweight individuals. This situation has revealed that overweight and obese individuals are a highly vulnerable group to epidemic diseases (1). Furthermore, the literature has addressed the mechanical effects of obesity on the respiratory system, and its relationship with asthma and other respiratory diseases has been discussed (6,7). It has been reported that all respiratory function parameters are negatively affected in obese individuals with a high BMI, and other physiological mechanisms affecting respiratory mechanics are not yet understood (8-11). It is known that the abdominal muscles, which are active during forced expiration, are associated with cough force, a forced expiratory maneuver. It is thought that cough force will decrease with increasing BMI and obesity, along with weakening of the abdominal wall muscles and abdominal fat accumulation. While there are studies in the literature mentioning the negative effects of obesity on respiratory function and reporting that grip strength is related to cough force in healthy individuals (12), no studies have been found on the relationship between cough force, an important respiratory parameter that reflects expiratory muscle strength, and body composition, waist/hip ratio, and peripheral muscle strength. Our study will be the first and pioneering study to investigate the relationships between body composition, waist-to-hip ratio, peripheral muscle strength, and cough strength in healthy young adults. Furthermore, the fact that body composition will be measured using the body analysis system, the gold standard method, increases the originality of our study. One of the unique merits of our study is that it will reveal the relationships between body composition, waist-to-hip ratio, peripheral muscle strength, and cough strength in individuals known to be healthy and free of chronic diseases.
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46 participants in 1 patient group
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Nazire Nur YILDIZ, Ph.D.; Nurcan AYTEKİN, Student
Data sourced from clinicaltrials.gov
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