30 International Journal of Integrated Health Sciences. 2017;5(1) Original Article Relationship between Physical Activity, Anthropometry, and Forced Expiratory Volume in One Second with 6-Minute Walk Distance in Elderly Correspondence: Irna Purnamasari Sukarya, Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Universitas Padjdajaran-Dr. Hasan Sadikin General Hospital Jl. Pasteur No. 38, Bandung, Indonesia e-mail: irna.purnamasari@yahoo.com Irna Purnamasari Sukarya, Vitriana, Tertianto Prabowo Department of Physical Medicine and Rehabilitation, Faculty of Medicine, Universitas Padjadjaran-Dr. Hasan Sadikin General Hospital Abstract Objective: To examine the correlation between physical activity using the Global Physical Activity Questionnaire (GPAQ), anthropometry (body mass index/BMI), and forced expiratory volume in one second (FEV1) value with six-minute walk distance in healthy community-dwelling elderly. Methods: A cross-sectional design study with consecutive sampling was conducted. This study included sixty nine participants (30 males and 39 females), aged ≥60 years who lives at Batununggal region in Bandung, Indonesia. The data was analyzed statistically by using normality, correlation, and multiple regresion tests. Results: The results showed that there was a correlation between six- minute walk distance and BMI in females (p=0.006), and FEV1 value in males (p=0.010). No significant correlation was found between GPAQ value and six- minute walk distance in females (p=0.4074) and in males (p=0.0926). Conclusions: There was a correlation between anthropometry and FEV1 value with six-minute walk distance in healthy elderly. There was no significant correlation between physical activity and six-minute walk distance. Keywords: Anthropometric measurement, FEV1, physical activity, six-minute walk distance pISSN: 2302-1381; eISSN: 2338-4506; http://doi.org/10.15850/ijihs.v5n1.963 IJIHS. 2017;5(1):30–5 Introduction Aging is a natural phase in humans results in some changes in the body compositions and skeletal muscles. Muscle mass loss is associated with infiltration of fat and connective tissues into the muscle fibers. This leads to structural redistributions with the decrease of muscle strength and function which may affect some physical performances. Muscle strength and function may decrease 1–2% per year at 50 years of age and above, results in significant decreases of some physical functions including cardiopulmonary functions, physical activity, and quality of life in elderly.1–3 Cardiopulmonary system changes may occur in consort with significant decline of aerobic capacity in the elderly population. Previous studies stated that cardiopulmonary fitness becomes a vital factor which influences the physical performance. Cardiopulmonary fitness can decrease approximately 15% per decade after 30 years of age.1,3,4 There were several distinctive variables that significantly influence respiratory function such as age, sex, height, race, ethnic, smoking history, environment condition, measurement tools, and test methods. Aging process causes several changes in body, including respiratory muscle mass, gas exchange, and control of ventilation. Increased rigidity of the chest wall and decreased respiratory muscle strength in elderly can increase the closing capacity and decrease the forced expiration volume in one second (FEV1) on pulmonary function tests. 5 Functional fitness and physical activity Received: December 14, 2016 Revised: March 16, 2017 Accepted: March 17, 2017 :30–5 International Journal of Integrated Health Sciences. 2017;5(1) 31 assessments are inevitably required as an implication to maintain flexibility of movement and quality of life in elderly. Conceptually, functional fitness is the ability in performing daily activities normally and independently without early fatigue. Routine physical activity becomes main factor to maintain flexibility of movement that prevent chronic diseases, and the physical activity assessment along with certain related factors are important for the authorities due to the population surveillance program.1,3,6,7 Physical activity assessment can be done using objective and physiological methods, such as VO2 max indirect measurement by cardiopulmonary exercise testing. However, the most common conducted cardiopulmonary exercise testing is the six-minute walk test. The six-minute walk test is considered as an appropriate cardiopulmonary fitness test, inexpensive, and similar to daily activity.8–12 A study in west Australia which involved Caucasian participants aged 55–75 years revealed that six-minute walk distance in males was higher 59±13 than in females.11 A recent study in Brazil which included females with average age 66 years reported that physical activity becomes an important independent predictor toward six-minute walk distance.10 Some health conditions in elderly may disturb the ability of walking and become a limitation in performing six-minute walk test, so it is important to find another way to predict the six-minute walk distance for elderly with such condition. This study aimed to observe the correlation between physical activity using Global Physical Activity Questionnaire (GPAQ), anthropometry (body mass index/BMI), and forced expiration volume in one second (FEV1) value with six- minute walk distance in healthy community- dwelling elderly population. Methods The participants involved in this study were the healthy elderly citizens at Batununggal region, Bandung, Indonesia. The inclusion criterias in this study were elderly aged ≥60 years and able to comprehend the instruction with the mini mental status examination (MMSE) score ≥24. The exclusion criterias were those who had uncontrolled cardiovascular and pulmonary diseases, stroke, uncontrolled hypertension, and those with deformities or lower extremity disorders which affect walking ability. The data of physical activity in this study were collected by conducting questionnaire distribution. The participants were asked several questions based on GPAQ through guided interview to obtain the total score of physical activity level. The questionnaire is suitable to collect information relating to the participant physical activity in sedentary and three domains: (1) occupational activity, (2) traveling from and to another place, and (3) recreational activity.6,7 Anthropometric measurements of BMI were performed using bioelectrical impedance :30–5 Table 1 Participant General Data Distribution Respondent Characteristics Females (n=39) Males (n=30) Mean (SD) Median Mean (SD) Median Age (years) 66.69 (5.72)* 65 66.83 (6.71)* 64.5 Education history (years) 11.12 (3.71)* 12 12.83 (3.87)* 12 Body weight (kg) 59.79 (12.20) 59.7 61.83 (10.32) 64.5 Body height (cm) 151.62 (5.80) 153 163.12 (4.64) 163 BMI (kg/m2) 25.94 (4.95)* 25.8 23.91 (2.64)* 24.3 6-minute walk distance (m) 391.84 (59.67) 390 444.96 (90.19) 440 FEV1(L) 1.56 (0.30) 1.59 2.12 (0.43) 2.185 GPAQ 4,169.74 (4,152.44)* 3480 2,520.66 (3,356.23)* 1680 Notes: BMI=body mass index ; FEV1=forced expiration volume in one second; GPAQ=Global Physical Activity Questionnaire *non-normally distributed data using normality Saphiro Wilks test Irna Purnamasari Sukarya, Vitriana, et al. 32 International Journal of Integrated Health Sciences. 2017;5(1) analysis (BIA/Tanita BC601, Tanita Corp, Tokyo, Japan) in kilogram and kg/m2. Forced expiration volume in one second was measured by using a spirometer (Chestgraph HI-101, Chest M.I.Inc, Tokyo, Japan). A pulse oxymeter (CTO fingertip pulse oxymeter) was applied on the thumb of left hand while performing spirometry and six-minute walk test. Before and after the six-minute walk test, several assessments were performed such as measurement of blood pressure, heart rate, and rating of perceived exertion by Borg scale. The participants were then instructed to walk on a 30-meter walking track. The distance of the six-minute walk test were recorded. The statistical test was used to determine the relationship between physical activity, anthropometry, and FEV1 value with the distance of six-minute walk test. The statistical tests used in this study were normality data, descriptive statistic, Pearson and Spearman correlation based on data distribution, and multiple regression tests between the distance of six-minute walk test and physical activity, anthropometry, and FEV1 value. This study was approved by the Health Research Ethic Committee, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia with ethical approval no 153/UN6.C1.3.2/KEPK/PN/2016. Results Eighty participants were invited to participate in this study. Eleven participants did not meet the inclusion criteria and were not included in the study. Therefore, sixty nine participants who met the inclusion criteria in this study were 30 males and 39 males (Table 1). The relationship between physical activity, anthropometry, and FEV1 value among the participants were discovered (Table 2 and 3). No significant correlation was found between GPAQ value and six-minute walk distance in females (p=0.4074) and in males (p=0.0926) (Table 2). In females, the correlation between six- minute walk distance and FEV1 (p=0.415) was not considered statistically significant but a correlation was found between six-minute walk distance and BMI (p=0.006) (Table 3). However, in males, the correlation between six-minute walk distance and BMI (p=0.476) was not considered statistically significant but a correlation was found between six-minute walk distance with FEV1 value (p=0.010). Body mass index and FEV1 were the main variables which influenced the results and showed significant correlation with six-minute walk distance. The correlation between gender and GPAQ value with six-minute walk distance was not considered statistically significant which showed that GPAQ was not included into the predictive equation. The regression analysis was repeatedly performed which included independent variables, such as BMI and FEV1. Residual descriptive statistical test was then performed by analyzing residual distribution (Saphiro Wilks test). The residual distribution was defined by the normal distribution with mean=0 (t test). In this study, the t value was 0.735328 with p>0.05 and mean=0. The residual distribution resulted W=0.966 with p=0.155. The results showed that the residual distribution was based on the normal distribution with mean=0. Furthermore, the regression test resulted a predictive equation: Six-Minute Walk Distance = 133.583 x FEV1 + 6.593 x BMI. Discussion The six-minute walk distance average value was discovered in females (391.84±59.67 meter) and in males (444.96±90.19 meter). Male participants show average 53,12 meter distance further than in females. In addition, a study reported similar results that males (690±62 meter) showed 59 meter distance further when compared to females (631±57 meter).11 Several studies relating to physical activity stated that physical activity levels in males and females are distinguished. A previous study found that physical activity in male elderly were higher than females.13 Using a self-reported physical activity method, the data determined that physical activity in males were about 0.8–21.4% higher than females. Another study with different result revealed that the physical activity using self- reported method discovers that the physical activities in female elderly were higher.14 6-minute walk distance and GPAQ Spearman T (N-2) p Value Female (n=39) 0.1365 0.8381 0.4074 Males (n=30) 0.3126 1.7412 0.0926 :30–5 Relationship between Physical Activity, Anthropometry, and Forced Expiratory Volume in One Second with 6-Minute Walk Distance in Elderly Table 2 Spearman Correlation Test between 6-Minute Walk Distance and GPAQ Value International Journal of Integrated Health Sciences. 2017;5(1) 33 Irna Purnamasari Sukarya, Vitriana, et al. This study discovers that the GPAQ value in females (4169.74±4152.44) was higher than in males (2520.66±3356.23). These results may be correlated with Indonesian’s culture which still distinguishes between male and female based on biological difference and social participation. Moreover, elderly females play an important role in the society, be able to socialize, and have insignificant decrease of activity level than in males. 15 There was no correlation found between the physical activity and six-minute walk distance in this study. Based on the Rank Spearman test results, the correlation between physical activity assessed using GPAQ and six-minute walk distance is not considered statistically significant in females and males (Table 2). This can occur because the GPAQ assessment is considered accurate only for assessing vigorous physical activity, compared to light and moderate physical activity. A review of GPAQ validity data reported that there is higher discrepancy between physical activities assessment using self-report and objective method such as accelerometer for high intensity activities. Different result may occur by other methods of physical activity assessment.7,16 Body mass index becomes a common anthropometry parameter correlated with six-minute walk distance.18,19 Walk distance can be predicted through several variables, including age, sex, body weight, body height, and BMI which influence 26–66% distance variability.9,18 This study also found that there was a correlation between six-minute walk distance with BMI in females. An alternative variable such as FEV1 value can be used as a determinant but it potentially causes bias. The correlation strength between FEV1 value and six-minute walk distance in subjects with minimal ventilation is different from the healthy subjects. However, there is a correlation between FEV1 value and :30–5 6-minute walk distance (m) Weight (kg) Height (cm) BMI (kg/m2) FEV1(L) Females (n=39) Correlation coefficient (r) -0.3159 0.265 -0.4306 -0.1342 p value 0.05 0.103 0.006* 0.415 Males (n=30) Correlation coefficient (r) 0.1143 0.4 0.1354 0.4644 p value 0.547 0.029* 0.476 0.010* Notes: BMI: body mass index ; FEV1: forced expiration volume in one second; *p value <0.05 Table 3 Pearson Correlation Test between 6-Minute Walk Distance with Anthropometries and Forced Expiration Volume in One Second Beta St.Err of Beta B St.Err. of B t(64) p Value FEV1 0.155203 0.109523 35.10641 24.773889 1.41707303 0.1613 Weight -0.177682 0.11284 -1.215292 0.7717912 -1.5746377 0.1203 Height 0.981931 0.139483 2.64373 0.3755422 7.03976838 1.58E-09* Sex 0.013716 0.033823 8.78213 21.656821 0.40551354 0.6865 GPAQ 0.026762 0.027719 0.0021817 0.0022598 0.96547134 0.3379 Notes: FEV1=forced expiration volume in one second; GPAQ=Global Physical Activity Questionnaire *p value <0.05 Table 4 Forward Stepwise Regression Analysis Test with Dependent 6-Minute Walk Distance Variable with Adjusted R=0.97245103 34 International Journal of Integrated Health Sciences. 2017;5(1) six-minute walk distance found in chronic obstructive pulmonary disease subjects.18 This study discovers a correlation and a significant relationship between FEV1value (r=-0.4644; p=0.010) and six-minute walk distance in male participants. These results are similar to the study in Australia which included 70 elderly participants aged 55–75 years.11 The study reported that height and FEV1 value are independent predictors which show significant correlation with six-minute walk distance, thus, combining the variables will result 33.9% variation of walk distance. A study conducted in Singapore discovered 6-minute walk distance predictive equation without distinguishing sex.20 The predictive equation is (5.50 x % HR maks) + (6.94 x height) – (4.49 x age) – (3.51 x weight) – 473,27; with R = 0.78. Another study in 2014 in Indonesia revealed a predictive equation of 6-minute walk distance=586.254 + 0.622 weight (kg) – 0.265 height (cm) – 63.343 sex (0= male; 1= female) + 0.117 age, with R=0.606 and adjusted R2=0.345. The equation in this study meets the regression term to predict six-minute walk distance. Residual test and residual equation distribution follow the normally probability distribution with significant value is >0.05 (p=0.155) that determines the equation is considered valid and can be used. Based on the equation, the adjusted R was 95% with FEV1 was 59% (Beta=0.5906) and BMI was 39% (Beta=0.3968) toward six-minute walk distance. The equation is properly used to predict six-minute walk distance in elderly females and males. The variables contribute 98% while another 2% is predicted by using other variables. In conclusion, there was a correlation between anthropometry and FEV1 value with six-minute walk distance, therefore, there was no significant correlation between physical activity with six-minute walk distance in healthy elderly. There are several limitations in this study. The method used for assessing the physical activities was inproper to apply in elderly population due to the intensity of the activities. Further study may use other methods which are sensitive for light and moderate physical activities, or by applying an objective assessment with accelerometer. This study also did not differentiate the healthy and minimal ventilation participants, that may become a consideration in the further study to homogenize lung function to decrease bias that might be appeared in the results. References 1. Milanović Z, Pantelić S, Trajković N, Sporiš G, Kostić R, James N. Age-related decrease in physical activity and functional fitness among elderly men and women. Clin Interv Aging. 2013;8:549–56. 2. Bautmans I, Lambert M, MetsT. The six-minute walk test in community dwelling elderly: influence of health status. BMC Geriatrics [serial on the internet]. 2004 July [cited 2016 Aug 12];4(6):[about 9p.]. Available from: Relationship between Physical Activity, Anthropometry, and Forced Expiratory Volume in One Second with 6-Minute Walk Distance in Elderly :30–5 Beta St.Err of Beta B St.Err. of B t(64) p Value FEV1 0.0314 0.0475 20.1263 30.4160 0.6617 0.5105 Weight 0.4100 0.1041 6.8118 1.7302 3.9370 0.0002* Height 0.5265 0.1265 119.1030 28.6157 4.1622 0.0001* Sex 0.0432 0.0361 0.0035 0.0029 1.1944 0.2367 GPAQ 0.026762 0.027719 0.0021817 0.0022598 0.96547134 0.3379 Notes: FEV1=forced expiration volume in one second; GPAQ=Global Physical Activity Questionnaire *p value <0.05 Table 5 Forward Stepwise Regression Analysis Test with Dependent 6-Minute Walk DistanceVariable with Adjusted R=0.95280530 International Journal of Integrated Health Sciences. 2017;5(1) 35 Irna Purnamasari Sukarya, Vitriana, et al. :30–5 h t t p s : / / b m c g e r i a t r. b i o m e d c e n t ra l . c o m / articles/10.1186/1471-2318-4-6. 3. Leyk D, Rüther T, Wunderlich M, Sievert A, Essfeld D, Witzki A, et al. 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