|Year : 2021 | Volume
| Issue : 3 | Page : 87-92
Normative values for single-leg hop performance in Saudi healthy population
Husam Almalki1, Lee Herrington2, Richard Jones2
1 Department of Rehabilitation, King Abdulaziz Specialist Hospital, Taif, Saudi Arabia
2 Knee Biomechanics and Injury Research Unit, School of Health and Society, University of Salford, Salford, UK
|Date of Submission||11-Aug-2021|
|Date of Acceptance||20-Oct-2021|
|Date of Web Publication||13-Dec-2021|
Department of Rehabilitation, King Abdulaziz Specialist Hospital, Taif
Introduction: The purpose of functional outcome measurement is to assess the performance of patients with knee joint injuries and their ability to return to physical activity. However, normative data for these measures are limited and generally include a wide range of ages and activity levels. Normative data can be used to make comparisons with patient populations. It can also be used to compare differences between individual legs. The purpose of this study is to establish normative data for single-leg hop for distance in healthy population.
Methods: One hundred and five healthy and active male participants were recruited to participate in the study, 35 in each age group (18–24, 25–34, and 35–44 years old). Participants who voluntarily participate in the study are physically active people. They also ensured that in the past 6 months, they had not suffered any injuries to their lower limbs, which prevented them from performing daily exercises. Participants were asked to perform a single-leg hop on right and left leg and measure the hop distance by using a tape measure. The distance of the jump was calculated by dividing the hop distance by the length of the participant's leg and then multiplying by 100, the hop data is normalized to the length of the limb to obtain a percentage value.
Results: For all participants, the mean distance for single-leg hop was 136 cm. Aditionally, normalising the hop to leg length was 151%, which means the participants could hop 1.5 their leg's length. The results showed that there was no difference in the performance of the left and right legs of the middle-aged group (25–34). For the youngest and oldest age groups (18–24 and 35–44), there was a statically significant difference in the performance of the left and right legs. All of the participants scored 85% of limb symmetry index. There were significant differences in hop performance according to age, as aging results in changes and a decrease in hop performance, and in older group, hop performance decreases are considerable.
Conclusion: This study has generated normative reference data that may be used to determine the impairments linked to musculoskeletal and neuromuscular disorders, along with ways of monitoring the progression of the disorder over time.
Keywords: Hop test, normative values, return to sports
|How to cite this article:|
Almalki H, Herrington L, Jones R. Normative values for single-leg hop performance in Saudi healthy population. Saudi J Sports Med 2021;21:87-92
|How to cite this URL:|
Almalki H, Herrington L, Jones R. Normative values for single-leg hop performance in Saudi healthy population. Saudi J Sports Med [serial online] 2021 [cited 2022 Jan 22];21:87-92. Available from: https://www.sjosm.org/text.asp?2021/21/3/87/332392
| Introduction|| |
Functional symmetry between injured and uninjured legs has been studied in the literature,,,, and patients who show an acceptable level of symmetry between 85% and 100% are considered more likely to return to play. However, a problem has arisen, as several studies have revealed that, actually, the uninjured limb is sometimes much weaker than the injured matched control limb., Therefore, any assumptions concerning normality need to be tentatively formed, because the amount of time required for pre- and postoperative rehabilitation can result in weakness and atrophy in the uninjured limb and so a disparity to both its pre-injury status and to appropriate controls. This shows the importance of normative data being available, and outcomes being compared to normative values from a matched gender/age group. Normative data are useful for carrying out comparisons with the patient population, in addition to comparing right-to-left differences in an individual. Normative data can be used to better inform standard hop distance key outcome measured used clinically in the anterior cruciate ligament reconstruction patient. The main goal following an injury to the knee is the return to previous activity levels, and accurate outcome measures will help clinicians in deciding the best time for the patient to return to play safely.
Functional performance tests are useful techniques for assessing more “real world” performance, but there are questions around which types of functional tests are most appropriate. There are important points that need to be considered when implementing functional tests, for example, the uninvolved side may compensate for the affected limb., In addition, bipedal tasks can conceal functional defects and defects that occur after unilateral lower limb injuries. The single-leg hop for distance is an important unilateral functional performance test that has a great deal of support in the literature with regard to its reliability and validity. When comparing the affected lower limb with the unaffected lower limb, the (limb symmetry index [LSI]) is often used to calculate a score for single-leg hop performance. Even so, people still worry about using the unaffected limb as the sole criterion for the affected limb, because the ability of the unaffected limb may decrease during the rehabilitation process and may be affected by previous injuries or surgeries. Furthermore, athletes may have perfect limb symmetry, but they are not ready to participate in sport, because compared to healthy people, both limbs are much weaker than usual. Apart from the studies by,,, there are no normative scores for single-leg hop for distance in the literature.
The main purpose of this study is to establish the normative data scores for single-leg hop for distance, as well as the difference between left and right legs and between different ages, and place them within the range of normal population values. This will be useful for clinicians and researchers who are dealing directly with patients.
Ethical considerations and risk assessment
This study had been ethically approved by the Research, Innovation, and Academic Engagement Ethical Approval Panel at the University of Salford HSCR 1617-43. Each participant in this study received a written information sheet containing detailed information about the study. This also outlines the purpose and procedures of the study, and the time required, the physical risks involved, and advised of their right to withdraw. Participants were informed that they could ask questions before, during, and after the study. After the participants decided to take part, they were checked to see if they met the inclusion criteria, then they were asked to complete and sign a consent form. All data collected from subjects were held on a secure password-protected computer. Each subject was given a reference number so that no individual details could be identified from the data (Data Protection Act, 1998). A risk assessment was conducted according to the study protocol and based on the risk assessment policy and risk control procedures.
| Methods|| |
The demographic profile of all participants involved in this study was aged between 18 and 44 and was divided into three groups:
- (18–24) years old
- (25–34) years old
- (35–44) years old.
Inclusion criteria and exclusion criteria
The subjects' requirements were that they must be recreationally active in accordance with American College of Sports Medicine guidelines (exercised at least 3–5 times a week at a moderate intensity for no <30 min). In addition, participants should not experience any lower extremity injuries in the 6 months before the test, and should not undergo any lower extremity surgery at any time during the past 6 months, and should not have cardiovascular, pulmonary, or neurological diseases that restrict physical activity.
Healthy active participants from Saudi Arabia were recruited to participate in the study, and all men belong to three different age groups (18–24), (25–34), and (35–44). Participants who voluntarily participate in this study are physically active people who do 30-min physical activity at least three times a week within the past 6 months.
Sample size and population demographics
One hundred and five healthy and active male participants were recruited to participate in the study, 35 in each age group (18–24 years, 25–34 years, and 35–44 years). The demographic characteristics by age group are shown in [Table 1].
When subjects demonstrate an interest in the research, they will learn about it and be shown all of the equipment and procedures. All questions were fully answered, and they were asked to sign the consent form if they were satisfied. Each subject was assigned a reference number, and his age, height, weight, gender, leg length, and preferred leg were all recorded on the data collection sheet. Each participant was instructed to perform a single-leg hop with both legs.
Participants were asked to perform a single-leg hop to measure distance by using a tape measure [Figure 1]. Place a 3 m tape on the ground and mark the starting line with a 0.3 m tape perpendicular to the starting line. The participants completed three practice trials, followed by three test trials with 60 s rest in between to measure single-leg hop distance. The average distance of the three tests' trials was calculated and analyzed, as described by a previous study. A successful attempt was defined as the participant hopping and landing on one leg with complete stability for 3 s. To prevent experimenter bias, subjects were not given any special instructions with regards to their hop strategy. Furthermore, participants' arm movements were not restricted during the hop tests. Participants were asked to make three maximum jump attempts in full stability 3 s after landing. If the participant hops and during landing, he touches the ground with the other leg, or if he fails to jump within a limited marked distance, the attempt is considered unsuccessful; any unsuccessful jumps was calculated and noted, but not processed. Before the test, the length of the participants' legs was measured while they were supine, using a standard tape measure to measure the length from the anterior superior iliac spine to the distal end of the medial malleolus. Leg length is used in the data analysis process to standardize the hop distance.
Contestants start with their toes on the starting line, stand on one leg, then jump horizontally, and land on the same leg, recording the distance of the jump by dividing the hop distance by the length of the participant's leg and then multiplying by 100, the hop data are normalized to the length of the limb to obtain a percentage value. After completing the test, the participant was instructed to repeat the test with the other leg.
The statistical analyses were conducted using IBM SPSS software (version 24, SPSS Inc., Chicago, IL). Descriptive statistics (mean, range of scores, and standard deviations) and scatter graphs were carried out to present the data descriptively. Shapiro–Wilk test was using to test the Normality. A paired-sample t-test and a Wilcoxon rank test were used to determine limbs differences. The effect size determines where the significant difference lies. Use Cohen's method δ, which defines as 0.2 small, 0.5 medium, and 0.8 large. The average of the three trails was calculated (P = 0.05).
Scores were stratified by the age range groups: 18–24, 25–34, and 35–44. Variations in single-hop test between age groups were compared using Kruskal–Wallis test with turkey post hoc analysis used for pairwise comparisons. The variables single-hop test were compared to previous studies.
| Results|| |
The normality test found that the single-leg jump test was not normally distributed in the age group (25–34 and 35–44 years) but was normally distributed in the age group (18–24 years).
[Table 2] illustrates the descriptive statistics of the test scores for left and right legs. In addition, it also shows a summary of the reference scores for all age groups in healthy people, including the mean and standard deviation of the hop performance. Normalization for the hop distance was calculated by dividing the distance by the length of the leg and then multiplying by 100. LSI was calculated by dividing the distance of the right-leg hop by the distance of left-leg hop then multiplying the result by 100 to obtain a percentage value.
|Table 2: Mean (standard deviation) and P value, comparison of significant (P=0.05) between right and left leg (n=35)|
Click here to view
Apart from the 25–34 age group, there is a statistically significant difference in the performance between the left and right legs [Table 2].
[Table 3] shows the percentage of participants who reached the LSI value. It seems that all participants have reached an LSI of 85%.
|Table 3: Percentage of participants reaching the limb symmetry index value|
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The Kruskal–Wallis test was performed to explore the effect of age on hop performance, which was measured by the life orientation test. Participants were divided into three groups according to their age (the first group: 18–24 years old; the second group: 25–34 years old; the third group 35–44 years old). The age groups (18–24), (25–34) and (35–44) were statistically significant at P = 0.05 level [Table 4].
|Table 4: Comparison of significant (P=0.05) between age groups in hop test|
Click here to view
| Discussion|| |
The goals of this study were to:
- Establish normative references for single-leg hop distance and LSI in healthy active individuals based on age groups
- Examine the differences in performance between the right and left legs in the single-leg long hop for distance
- Look into the differences in single-leg hop performance between age groups.
As previously stated, the primary goal of this study is to establish normative data for single-leg hops. Previous normative data scores were limited because their research only included the high school population. [Table 2] shows the baseline data that researchers and clinicians can use to compare to the benchmarks. It aids in evaluating treatment plans based on patient characteristics; data can be compared with patients of similar age.
This study demonstrates the raw and normalized scores, which, while useful for comparing an individual's raw and normalized scores, are not particularly useful when performing cross-comparisons with other groups or individuals. It has been observed in previous studies that taller individuals generally jump further in the single-leg hop test,, so it can be assumed that the difference in leg length will cause the hop distance to vary, so normalizing the hop distance score based on leg length would be useful and help reduce the variation between subjects. This should make it easier to compare scores between individuals as well as between limbs for the same subject.
In this study, normalizing the hop to leg length for all participants was 151%, which is a little lower than the previous research findings', which was 176.9% and 187.8%,, respectively. Furthermore, the mean single-leg hop distance score for all participants in this study was 136 cm, which is slightly less than the hopped distance in the literature, which was 155 cm 163 cm, 181 cm, 177 cm,,,, respectively. Despite these findings, the comparison has some flaws because the studies included samples of varying ages and activity levels.
The findings revealed that there was no difference in performance between the right and left legs in the middle-aged group (25–34). The performance was significantly different for the youngest and oldest age groups (18–24 and 35–44), though the effect sizes were small and the changes were not functionally significant because they fell within the standard error of measurement values found in other studies,,, for single-leg hop for distance (4.56–7.93 cm); additionally, the difference is less than the standard deviation of the recommended normative value. As a result, these changes are more likely to be the result of measurement errors than of poor performance.
The LSI score of all participants in this study was 85%, which is similar to Noyes et al., who discovered that the LSI was 85% or higher in a single-leg hop and discovered that the mean LSI of a single-leg hop for distance was 100.35%, with 100% of healthy participants demonstrating that the LSI was at least 90%. As a result of these findings, it may be beneficial to raise the LSI standard to 90% rather than the previous recommendation of 85%. Although, 103.4% of LSI was achieved in the current study is greater than the findings of previous studies, which was 99.4% and 100.4% [8, 15], respectively, but lower than the results of which was (94.5%). It was still difficult to determine which limbs were dominant and which were not. This is because some people consider the dominant leg to be the leg that is on the ground when kicking, whereas others consider it to be the leg that is on the ground when kicking. Although specific standards must be developed for this, the dominant leg can be determined based on previous production or performance (such as hop distance) during the functional task. If an individual has a strength advantage in one leg but a performance advantage in the other leg in a functional task, it will be difficult to determine which leg is dominant. We calculated the LSI in this study by dividing the performance of the right leg by the performance of the left leg and then multiplying the result by 100, as described in a previous study.
An examination of the relationship between hop performance and age has revealed some specific relationships, most notably the significant difference in hop performance according to age, as aging results in changes and a decrease in hop performance, and hop performance decreases are significant in older adulthood. Between age groups, there were statistically significant differences in left- and right-leg hop performance. The differences in hop distance between the youngest and oldest age groups were more than 40 cm, which could have clinical implications because 40 cm accounts for up to 35% of the hop performance, as shown in the current study. The difference in hop distance to leg length between age groups was 32%, which could have clinical implications because 32% is 25% of hop performance in the current study.
As a result, the significance of using age-matched reference data for specific functional tests is clear, as this should help to avoid over or underrepresentation of individuals' performance ability.
The current study's limitation is that the analysis by age subgroup reduced the statistical power of the analyses. Furthermore, because this study only included Saudi male participants, the findings cannot be generalized to both genders or healthy people from other countries.
| Conclusion|| |
Performance differences between the right and left legs were statistically significant. Furthermore, there is limb symmetry; LSI was >85% between the right and left legs. There were statistically significant differences in performance between age groups.
This study has generated normative reference data that can be used to determine impairments associated with musculoskeletal and neuromuscular disorders, as well as ways to track disease progression over time. Reference values and associated age scores can be used to create more accurate outcome measures and improve responsiveness in clinical trials.
When determining whether a patient's functional characteristics and performance are abnormal, clinicians face a challenge due to the lack of normative values for functional assessment. The current study's findings should assist clinicians in comparing age-specific functional performance to improve patient health, assess performance levels, and return to participation standards.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]