Min-Hee Kim1, Won-Gyu Yoo2. 1. Institute of Health Science, Yonsei University, Republic of Korea. 2. Department of Physical Therapy, College of Biomedical Science and Engineering, Inje University, Republic of Korea.
Abstract
[Purpose] The purpose of this study was to provide data for decision making regarding the optimal and maximal hip adduction loads for clinical and fitness purposes, respectively. [Subjects] Forty-eight (24 males, 24 females) asymptomatic adults participated in this study. [Methods] Subjects performed optimal and maximal hip adduction loads. Regarding the gender, body weight and height variables, a stepwise multiple regression analysis was used to identify the most informative variables for predicting the optimal and maximal loads during the hip adduction exercise. [Results] The regression model for optimal hip adduction load (kg) was: 34.3 + 0.4 × weight - 0.27 × height (r(2)= 0.77); and the regression model for maximal hip adduction load (kg) was: 39.5 + 0.5 × weight - 0.3 × height (r(2)= 0.75). [Conclusion] These models can aid in deciding the optimal and maximal hip adduction loads for clinical and fitness purposes, respectively. Thus, the optimal hip adduction load model can be used to strengthen the hip adductor muscles or enhance core stability in clinical settings.
[Purpose] The purpose of this study was to provide data for decision making regarding the optimal and maximal hip adduction loads for clinical and fitness purposes, respectively. [Subjects] Forty-eight (24 males, 24 females) asymptomatic adults participated in this study. [Methods] Subjects performed optimal and maximal hip adduction loads. Regarding the gender, body weight and height variables, a stepwise multiple regression analysis was used to identify the most informative variables for predicting the optimal and maximal loads during the hip adduction exercise. [Results] The regression model for optimal hip adduction load (kg) was: 34.3 + 0.4 × weight - 0.27 × height (r(2)= 0.77); and the regression model for maximal hip adduction load (kg) was: 39.5 + 0.5 × weight - 0.3 × height (r(2)= 0.75). [Conclusion] These models can aid in deciding the optimal and maximal hip adduction loads for clinical and fitness purposes, respectively. Thus, the optimal hip adduction load model can be used to strengthen the hip adductor muscles or enhance core stability in clinical settings.
Entities:
Keywords:
Hip adduction; Optimal load; Regression analysis
Anatomical cadaver studies have shown that vastus medialis oblique (VMO) fibers originate
from the distal part of the adductor magnus. Thus, VMO fibers provide stability during the
contraction that occurs in hip adduction1).
Hip adduction also stretches the VMO fibers, adjusting the length and tension properties of
the muscle and increasing the contraction force2). Based on anatomical analyses, previous research has shown that hip
adductor contraction during squat exercises results in selective strengthening of the
VMO3). Another study reported that the
hip adductor muscle is connected to the internal abdominal muscle through the iliacus, psoas
major, and quadratus lumborum muscles4).
Kim and Yoo5) reported that the muscle
activities of the external oblique, internal oblique, and L5 paraspinal muscles increased
during hip adduction using a visual feedback device. Hip adductor muscle contraction also
synergistically facilitates the pelvic floor muscle activity that occurs with the
contraction of the abdominal muscle6).
Therefore, many clinicians have used various hip adduction exercises for low back pain, or
patellofemoral pain or pelvic muscle weakness patients1, 5, 6). The selection of the exercise load is a very important factor in
the effectiveness of the exercise3).
However, hip adduction load studies are few in number. Therefore, in the present study,
using regression analysis, we determined the optimal and maximal loads during hip adduction
exercise by asymptomatic subjects. The purpose of this study was to provide data for
decision making regarding the optimal and maximal hip adduction loads for clinical and
fitness purposes, respectively.
SUBJECTS AND METHODS
Forty-eight (24 males, 24 females) asymptomatic subjects with no known surgical,
musculoskeletal, or neurological history of any pathological condition in the lower
extremities participated in this study. The mean age of the participants was 24.3 ±
4.4 years, their mean height was 169.5 ± 8.4 cm, and their mean weight was 61.2 ± 12.7 kg.
This study was approved by the Inje University Faculty of Health Science Human Ethics
Committee, and all subjects provided their written informed consent to participation before
commencing the study. Subjects were instructed to bend their knees to 45° in a
height-adjustable chair and adduct their knees to their hip. Subjects performed optimal and
maximal hip adduction loads. The optimal hip adduction load was defined as sustainable load
holding for 20 s in isometric hip adduction isometric exercise. The maximal hip adduction
load was defined as sustainable load holding for 3 s with maximal effort hip adduction. The
hip adduction load was measured by PowerTrack II (JTECH Medical, Salt Lake City, UT, USA).
Hip adduction load measures were performed using an air cushion with the PowerTrack II
placed between the medial joint lines of the knees. The air-cushion was volume-adjustable.
Thus, excessive hip adduction motion could be controlled. The individual optimal and maximal
hip adduction load data were collected from five repeated tests. A resting time of 3 min was
given between each test to prevent muscle fatigue. Stepwise multiple regression analysis was
used to determine the optimal and maximal loads during the hip adduction exercise. A
stepwise multiple regression analysis was performed using gender, body weight and height
variables to identify the most informative variables for predicting the optimal and maximal
loads during the hip adduction exercise. The coefficients for the regression analysis and
the regression model for the optimal and maximal loads during the hip adduction exercise
were determined. Significance was accepted for values of < 0.05.
RESULTS
To control for the gender, body weight, and height variables, stepwise multiple regression
was performed for the optimal and maximal hip adduction loads. The regression model for
optimal hip adduction load (kg) was: 34.3 + 0.4 × weight − 0.27 × height (r2=
0.77, p<0.05); and the regression model for maximal hip adduction load (kg) was: 39.5 +
0.5 × weight − 0.3 × height (r2=0 0.75, p<0.05).
DISCUSSION
This study measured the optimal and maximal loads during hip adduction exercise in
asymptomatic subjects. The most informative variables for predicting the optimal and maximal
loads during the hip adduction exercise were determined on the basis of statistical
regression. The results show that weight and height were the most informative variables for
both optimal and maximal hip adduction loads. Using information from these models can aid in
deciding the optimal and maximal hip adduction loads for clinical and fitness purposes,
respectively. The selection of the exercise load is a very important factor for effective
exercise. A previous study investigated the influence of a resistive band on the muscles
with leg adduction performed in a variety of positions7). That study showed that hip adduction with a resistive device
increased trunk stability7). The general
goal of hip adduction training is core stability. Core stability of the trunk can be viewed
as a box, with, the diaphragm as the roof and the pelvic floor and hip muscles as the
bottom8). The abdominals comprise the
anterior part of the box and the paraspinals and gluteals the posterior part8). This co-activation of the hip adductor,
pelvic floor, and internal abdominal muscles is necessary for the occurrence of
intra-abdominal pressure9). It also
reinforces the strength of the multifidus and aids spinal stability9). Thus, the optimal hip adduction load model can be used to
strengthen the hip adductor muscles or enhance core stability in the clinical setting.
Although the independent variables of this study used simple general characteristics, the
regression coefficients of R-squared over 0.7 indicate highly reliability in predicting the
dependent variables. The variables selected by regression analysis in this study were weight
and height, which have the advantage of being measured easily in the clinic by physical
therapists. Therefore, our study results can help with the selection of the ideal hip
adduction loads in clinical situations. This study had several limitations. Maintaining
maximum loading requires significant effort and is difficult to sustain. This study
evaluated asymptomatic subjects to obtain a standard value. Therefore, the models derived
cannot be used for patients with pain.