Abstract
Background
The evaluation of Hand Grip Strenght (HGS) is relevant for the early detection of muscle weakness. It can be applied as an indicator for monitoring physical performance and early identification of reduce muscle strenght.
Objective
(a) to compare hand grip strength (HGS) with other regional studies and (b) to propose regulatory classifications of HGS by age, sex in children and adolescents living in a moderate altitude region of Peru.
Methodology
A cross-sectional study was designed in school children and adolescents living in a moderate altitude region of Peru (2320 m above sea level). The sample selection was non-probabilistic (accidental), considering 1058 schoolchildren (557 boys and 501 girls) with an age range of 6 to 17 years. These schoolchildren came from public schools. Weight, height and Body Mass Index (BMI) were assessed. HGS of both hands (right, left and both hands) was evaluated. The p50th percentile was used to compare discrepancies with studies from Chile, Colombia and Peru.
Results
The median values (p50) of both hands show a linear increase with advancing age. It is expected that HGS tends to increase as children get older. The maximum HGS of both hands occurred in males at 17 years of age (38.87 kg/f). While in females it was at 15–16 years (23.56 kg/f). Discrepancies in HGS were observed when comparing the 50th percentile (P50) of schoolchildren living at moderate altitude in Peru with regional studies carried out in Chile, Colombia and Peru. HGS percentiles by age and sex were developed for the left, right and both hands (P3, P5, P15, P25, P50, P75, P85, P90, P95 and P97).
Conclusion
The study demonstrated discrepancies in HGS between schoolchildren living in a moderate altitude region of Peru and neighboring regions. This allowed us to propose percentiles to evaluate HGS by age and sex. The results suggest its use in educational and clinical contexts.
Keywords: Handgrip strength, Moderate altitude schoolchildren, Percentiles
Background
Hand grip strength (HGS) is characterized by completing a maximal isometric grip strength task. In which individuals squeeze a manual dynamometer with maximal effort for a short period (i.e., seconds) and then relax the contracted musculature [1].
This test is useful for assessing upper extremity disorders and serves to monitor post-injury evaluation. And even, it is considered as a marker of athletic performance [2].
In recent years, several studies have highlighted the importance of its use as part of the standard physical examination in children and adolescents. Showing that it can provide more complete information compared to traditional vital sign parameters in pediatric clinical settings [3]. In pediatric populations, its use is especially relevant for early detection of muscle weakness. This may be an indicator of muscle weakness and other neuromuscular disorders [4]. These indicators are useful not only for monitoring healthy growth and development. But also to predict future risks related to mobility, physical performance and musculoskeletal health and general health [4, 5].
Early identification of these problems can facilitate preventive interventions that improve quality of life at key stages of growth and development. For this, it is necessary to have reference values that allow comparison of grip strength measurements for each individual [5].
In this context, several studies at the international level, especially in South America (Peru, Chile and Colombia), have developed reference values for children and adolescents [6–8]. In fact, variations in these HGS levels suggest that norms developed for one country are not applicable to others [9]. Since the populations of different countries do not share homogeneous characteristics in social, economic, cultural, demographic, nutritional and anthropometric aspects [10].
Furthermore, in a country like Peru, which has varied geographic, climatic and ethnic regions, it is difficult to establish single standards that adequately reflect the realities of each population group. Although in the literature we found a study that proposed reference values for a region of Peru without specifying geographic variations (Bustamante et al. 2012). This makes it necessary to conduct specific research that generates reference values adapted to local characteristics. Thus allowing a more accurate assessment of the physical development and health of schoolchildren living in a region of moderate altitude in Peru.
Therefore, geographic and environmental conditions of moderate altitude may evidence varied HGS values in relation to other pediatric populations. In addition, physical fitness monitoring is also part of physical education programs emanating from ministries of education in countries in general [11].
Therefore, it is essential to establish local reference values to guide the implementation of these programs. Ensuring that they are adapted to the specific needs of school children living in moderate altitude regions of Peru. This information will allow not only to adequately monitor the physical development of children. But also to design interventions that promote an active and healthy lifestyle, contributing to the improvement of their overall well-being and the prevention of health-related problems in the future.
Consequently, the objectives of this study were: (a) to compare HGS with other regional studies and (b) to propose regulatory classifications of HGS by age and sex in children and adolescents living in a region of moderate altitude in Peru.
Methods
Type of study and sample
A cross-sectional study was designed in school children and adolescents living in a region of moderate altitude in Peru. The sample consisted of 4 public schools characterized as emblematic schools and with both levels of study: primary and secondary. The sample selection was non-probabilistic (accidental), considering 1058 schoolchildren (557 boys and 501 girls) with an age range of 6 to 17 years. These schoolchildren from public schools often belong to middle socioeconomic status.
The schoolchildren in the study belong to the urban region of the city of Arequipa (Peru). This city is located at 2320 m above sea level. It is located south of the capital of Peru (Lima).
The study was conducted in accordance with the Helsinki declaration for human subjects and was approved by the Ethics Committee of the Universidad Católica Santa María de Arequipa (Peru) (UCSM-096–2022). Permission was requested from the management of the 4 schools to carry out the study. Then, using the list of students enrolled in the schools, one of the investigators sent the informed consent to each of the parents and assent to the students.
All children within the established age range (6 to 17 years), those who completed the anthropometric measurements and the HGS evaluation were considered in the study. Those who were on medical rest and/or had a physical injury that prevented HGS measurement and schoolchildren with chronic diseases, neuromuscular disorders, or any other medical condition that could influence HGS assessment were excluded.
Techniques and instruments
The process of organizing the data collection was carried out by 4 physical education professionals. Each of them had extensive experience in the evaluation of anthropometric and physical measurements. Data collection was carried out at the facilities of each of the schools. It was carried out during physical education classes during school hours from Monday to Friday from 8:00 am to 1:00 pm and during the months of April to June 2023.
Anthropometric measurements were evaluated according to the recommendations of Ross & Marfell-Jones [12]. The body weight and height of schoolchildren of both sexes were evaluated. The protocol indicates that measurements were performed with shorts, T-shirt and without shoes). Weight (kg) was evaluated using a Seca digital scale with an accuracy of (100 g) and a scale of (0 to 150 kg). Standing height (m) was assessed using a Seca brand aluminum stadiometer graduated in millimeters with a scale of (0 to 2.50 m). Body Mass Index (kg/m2) was calculated using the formula: [BMI = Weight(kg)/Height(m)2].
The HGS (right and left) was evaluated using a hydraulic dynamometer with an accuracy of 0.1 kg and a scale up to 100 kgf. The model used was a JAMAR (Hydraulic Hand Dynamometer ® Model PC-5030 J1, Fred Sammons, Inc., Burr Ridge, IL: USA). To assess HGS, the protocol proposed by Richards et al. [13] was used. Volunteers remained seated (in a straight-backed chair) with their forearms restingo n the armrest. They were ased to exert as musch force as possible (by squeezing the dynamometer). Schoolchildren of both sexes performed two attempts with each hand and had a rest between both repetitions at an interval of 2 min Gómez-Campos et al. [10]. For the comfort of the examinee, the dynamometer was constantly adjusted according to age and sex. It was evaluated twice with each hand. These measurements were used to verify the relative technical error of measurement (TEM % intra-evaluator) (in both sexes it was determined from 0.8 to 1.2%).
Statistics
The data set of the studied sample, including anthropometric measurements and HGS values, was subjected to the Kolmogorov-Smirnov test to assess the normality of the distribution. Subsequently, calculations were performed using SPSS 18.0 and spreadsheets in Microsoft Excel. Descriptive statistics (mean, standard deviation and range) were calculated. Significant differences between both sexes were verified by means of the t-test for independent samples. The proposed percentiles (P3, P5, P15, P25, P50, P50, P75, P85, P90, P95 and P97) were calculated using the LMS method (30). The Box-Cox transformation was used to fit the data distribution to a normal distribution by minimizing the effects of skewness. The parameters L (skewness: lambda), M (median: mu) and S (coefficient of variation: Mu) were calculated according to the maximum penalty method [14, 15]. Calculations were performed using LMS Chart Maker version 2.3 software [16]. Comparisons between regional studies Peru [6], Chile [7] and Colombia [8] were performed using the 50th percentile for each age and sex from the fraction: 100 log (reference percentile/calculated percentile). The average of the HGS values of both hands was used. A significance level of p < 0.05 was used in all cases.
Results
Table 1 shows the anthropometric and physical characteristics of the primary (6 to 11 years) and secondary (12 to 17 years) schoolchildren. There were no significant differences between schoolchildren of both sexes at the primary level in age, weight, height and right and left HGS and both hands (p > 0.05). However, in terms of BMI, males presented higher values in relation to females (p < 0.05). At the secondary level, there were no differences in age between both sexes (p > 0.05). On the contrary, men presented higher weight, height, BMI and HGS right, left and in both hands in relation to their female counterparts (p < 0.05).
Table 1.
Anthropometric and physical characteristics of the schoolchildren studied
| Variables | Males (n = 275) | Females (n = 260) | p | ||||||
|---|---|---|---|---|---|---|---|---|---|
| X | SD | CI | X | SD | CI | ||||
| Ll | Ul | Ll | Ul | ||||||
| Primary (6 to 11 years old) | |||||||||
| Age (years) | 9.6 | 1.6 | 9.4 | 9.8 | 9.5 | 1.5 | 9.4 | 9.7 | 0.710 |
| Weight (kg) | 36.9 | 12.2 | 35.5 | 38.4 | 35.1 | 10.5 | 33.8 | 36.4 | 0.060 |
| Height (cm) | 134.4 | 12.3 | 132.9 | 135.9 | 134.4 | 11.2 | 133 | 135.7 | 0.980 |
| BMI (kg/m2) | 19.9 | 3.7 | 19.5 | 20.4 | 19.1 | 3.6 | 18.6 | 19.5 | 0.010 |
| HGS (kgf) | |||||||||
| Right | 12.6 | 4.5 | 12.1 | 13.2 | 13.7 | 13.7 | 12 | 15.4 | 0.250 |
| Left | 12 | 4.5 | 11.5 | 12.6 | 11.5 | 3.8 | 10.8 | 11.8 | 0.220 |
| Both hands | 12.54 | 4.3 | 12.02 | 13.08 | 12.29 | 4.29 | 11.76 | 12.83 | 0.600 |
| Secondary (12 to 17 years old) | |||||||||
| Males (n = 282) | Females (n = 241) | ||||||||
| Age (years) | 14.5 | 1.6 | 14.3 | 14.7 | 14.5 | 1.6 | 14.3 | 14.7 | 0.550 |
| Weight (kg) | 55.3 | 10.9 | 54 | 56.6 | 52.7 | 9.6 | 51.4 | 54 | 0.010 |
| Height (cm) | 161.9 | 8.8 | 160.8 | 162.9 | 154.1 | 5.2 | 153.3 | 154.8 | 0.000 |
| BMI (kg/m2) | 21 | 3.2 | 20.6 | 21.4 | 22.2 | 3.6 | 21.7 | 22.7 | 0.000 |
| HGS (kgf) | 2 | 0.000 | |||||||
| Right | 29.5 | 8.9 | 28.5 | 30.5 | 22.4 | 5 | 21.8 | 23.1 | 0.000 |
| Left | 29.5 | 8.9 | 28.5 | 30.6 | 22.2 | 4.5 | 21.5 | 22.8 | 0.000 |
| Both hands | 29.22 | 8.60 | 28.19 | 30.25 | 22.18 | 4.67 | 21.54 | 22.81 | 0.000 |
X Mean, SD Standard deviation, CI Confidence interval, HGS Hand grip strength, BMI Body mass index, Ul Upper limit, Ll Lower limit
Figure 1 illustrates the comparisons of HGS of both hands between the Arequipa (Peru) regional study and other studies. The HGS of schoolchildren of both sexes presents similar patterns of behavior in all age ranges. In general, it is observed that HGS in both sexes increases as chronological age advances.
Fig. 1.
Comparison of hand grip strength (HGS) in both sexes with international studies
The moderate altitude children from Arequipa in this study have a HGS development comparable to other Latin American groups. Although, they tend to have slightly lower values than children from Chile in both sexes. For example, in males, HGS values are lower from ~ 1.4 to 4.2 kgf and in females from ~ 0.64 to 2.4kgf. However, when compared to Peruvian schoolchildren [6], Arequipa schoolchildren of both sexes evidenced relatively higher values. In males from 7 to 17 years old (~ 0.53 to 4.50kgf) and in females from 6 to 17 years old (~ 0.58 to 2.9kgf). In addition, during childhood, Colombian schoolchildren have slightly higher values than those of Arequipa. Although, during adolescence, Arequipa schoolchildren (moderate altitude), reflected higher values in both sexes, varying these values in males from 0.12 to 1.79kgf, and in females ~ 0.6 to 4.37kgf. In general, the maximum HGS of both hands occurred in males at 17 years of age (38.87kgf). While in females it was at 15–16 years (23.56kgf).
Tables 2, 3 and 4 show the reference values (P3, P5, P15, P25, P50, P75, P85, P90, P95 and 97) of the HGS of the right, left and both hands. The median values (p50) show a linear increase with advancing age. It is to be expected that HGS tends to increase as children grow older and develop physically. Differences between the sexes appear from 12 years of age onwards until 17 years of age, where males show significantly higher values relative to their female counterparts. These values vary from (~ 1.3 to 16kgf).
Table 2.
Percentiles of right HGS (kgf) in schoolchildren according to age and sex
| Age | L | M | S | P3 | P5 | P15 | P25 | P50 | P75 | P85 | P90 | P95 | P97 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Males | |||||||||||||
| 6 | −0.14 | 7.03 | 0.35 | 3.8 | 4.1 | 4.6 | 5.6 | 7.0 | 8.9 | 10.2 | 11.1 | 12.7 | 13.9 |
| 7 | 0.13 | 8.73 | 0.32 | 4.6 | 5.0 | 5.7 | 7.0 | 8.7 | 10.8 | 12.1 | 13.1 | 14.6 | 15.6 |
| 8 | 0.35 | 10.42 | 0.3 | 5.5 | 6.0 | 6.9 | 8.4 | 10.4 | 12.7 | 14.0 | 15.0 | 16.4 | 17.4 |
| 9 | 0.52 | 12.0 | 0.28 | 6.5 | 7.1 | 8.0 | 9.8 | 12.0 | 14.4 | 15.7 | 16.7 | 18.2 | 19.2 |
| 10 | 0.63 | 13.92 | 0.27 | 7.6 | 8.4 | 9.5 | 11.5 | 13.9 | 16.5 | 17.9 | 18.9 | 20.5 | 21.5 |
| 11 | 0.7 | 16.84 | 0.25 | 9.5 | 10.3 | 11.7 | 14.1 | 16.8 | 19.8 | 21.4 | 22.5 | 24.2 | 25.3 |
| 12 | 0.71 | 20.69 | 0.24 | 12.1 | 13.1 | 14.7 | 17.4 | 20.7 | 24.1 | 26.0 | 27.3 | 29.2 | 30.5 |
| 13 | 0.68 | 25.03 | 0.23 | 15.2 | 16.3 | 18.2 | 21.3 | 25.0 | 28.9 | 31.1 | 32.6 | 34.8 | 36.3 |
| 14 | 0.61 | 29.2 | 0.21 | 18.4 | 19.7 | 21.7 | 25.1 | 29.2 | 33.5 | 35.9 | 37.6 | 40.1 | 41.8 |
| 15 | 0.52 | 33.05 | 0.2 | 21.6 | 22.9 | 25.0 | 28.7 | 33.0 | 37.7 | 40.3 | 42.2 | 44.9 | 46.8 |
| 16 | 0.41 | 36.56 | 0.19 | 24.6 | 26.0 | 28.1 | 32 | 36.6 | 41.5 | 44.4 | 46.3 | 49.4 | 51.4 |
| 17 | 0.28 | 39.97 | 0.19 | 27.6 | 29.0 | 31.2 | 35.2 | 40.0 | 45.2 | 48.2 | 50.4 | 53.6 | 55.8 |
| Females | |||||||||||||
| 6 | 0.88 | 7.15 | 0.28 | 3.6 | 4.0 | 4.7 | 5.8 | 7.2 | 8.5 | 9.2 | 9.7 | 10.5 | 11.0 |
| 7 | 0.84 | 8.55 | 0.27 | 4.5 | 5.0 | 5.7 | 7.0 | 8.6 | 10.1 | 11.0 | 11.5 | 12.4 | 13.0 |
| 8 | 0.79 | 10.23 | 0.25 | 5.6 | 6.2 | 7.0 | 8.5 | 10.2 | 12.0 | 13.0 | 13.7 | 14.7 | 15.4 |
| 9 | 0.73 | 12.14 | 0.24 | 7.0 | 7.6 | 8.5 | 10.2 | 12.1 | 14.2 | 15.3 | 16.1 | 17.2 | 18.0 |
| 10 | 0.66 | 14.34 | 0.23 | 8.6 | 9.2 | 10.3 | 12.2 | 14.3 | 16.6 | 17.9 | 18.8 | 20.2 | 21.1 |
| 11 | 0.57 | 16.99 | 0.22 | 10.5 | 11.2 | 12.4 | 14.5 | 17.0 | 19.6 | 21.1 | 22.2 | 23.7 | 24.8 |
| 12 | 0.45 | 19.36 | 0.22 | 12.3 | 13.1 | 14.4 | 16.6 | 19.4 | 22.3 | 24.0 | 25.2 | 27.0 | 28.2 |
| 13 | 0.28 | 21.24 | 0.21 | 14.0 | 14.8 | 16.1 | 18.4 | 21.2 | 24.4 | 26.2 | 27.5 | 29.5 | 30.8 |
| 14 | 0.07 | 22.6 | 0.20 | 15.5 | 16.3 | 17.5 | 19.8 | 22.7 | 25.9 | 27.8 | 29.2 | 31.3 | 32.8 |
| 15 | −0.15 | 23.6 | 0.19 | 16.7 | 17.4 | 18.6 | 20.8 | 23.6 | 26.8 | 28.8 | 30.2 | 32.4 | 34.0 |
| 16 | −0.39 | 23.95 | 0.18 | 17.5 | 18.2 | 19.3 | 21.3 | 23.9 | 27.1 | 29 | 30.3 | 32.6 | 34.2 |
| 17 | −0.63 | 23.99 | 0.16 | 18.1 | 18.7 | 19.7 | 21.5 | 24.0 | 26.9 | 28.7 | 30.1 | 32.3 | 33.9 |
P Percentile, L Lambda, M Median, S Coefficient of variation
Table 3.
Percentiles of left HGS in schoolchildren according to age and sex
| Age | L | M | S | P3 | P5 | P15 | P25 | P50 | P75 | P85 | P90 | P95 | P97 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Males | |||||||||||||
| 6 | 0.66 | 6.73 | 0.36 | 2.7 | 3.2 | 3.9 | 5.2 | 6.7 | 8.4 | 9.4 | 10.1 | 11.1 | 11.8 |
| 7 | 0.62 | 8.33 | 0.34 | 3.7 | 4.2 | 5.0 | 6.5 | 8.3 | 10.3 | 11.4 | 12.2 | 13.4 | 14.2 |
| 8 | 0.59 | 10.39 | 0.31 | 5.1 | 5.6 | 6.6 | 8.3 | 10.4 | 12.7 | 14.0 | 14.9 | 16.3 | 17.2 |
| 9 | 0.56 | 12.09 | 0.29 | 6.3 | 6.9 | 8.0 | 9.8 | 12.1 | 14.6 | 16.0 | 17 | 18.5 | 19.5 |
| 10 | 0.55 | 13.42 | 0.28 | 7.3 | 8.0 | 9.1 | 11.0 | 13.4 | 16 | 17.5 | 18.5 | 20.1 | 21.2 |
| 11 | 0.52 | 15.51 | 0.26 | 8.7 | 9.5 | 10.7 | 12.9 | 15.5 | 18.4 | 20.0 | 21.2 | 22.9 | 24.1 |
| 12 | 0.47 | 19.16 | 0.25 | 11.2 | 12.1 | 13.5 | 16.1 | 19.2 | 22.6 | 24.5 | 25.9 | 28.0 | 29.4 |
| 13 | 0.39 | 23.95 | 0.24 | 14.7 | 15.7 | 17.3 | 20.3 | 23.9 | 28.0 | 30.3 | 31.9 | 34.5 | 36.2 |
| 14 | 0.28 | 28.31 | 0.22 | 18.1 | 19.2 | 21 | 24.3 | 28.3 | 32.8 | 35.4 | 37.2 | 40.1 | 42.1 |
| 15 | 0.15 | 31.98 | 0.21 | 21.3 | 22.5 | 24.3 | 27.7 | 32.0 | 36.8 | 39.6 | 41.6 | 44.7 | 46.9 |
| 16 | 0.00 | 34.95 | 0.20 | 24.1 | 25.3 | 27.1 | 30.6 | 35.0 | 39.9 | 42.9 | 45.0 | 48.4 | 50.7 |
| 17 | −0.16 | 37.78 | 0.19 | 26.8 | 28.0 | 29.8 | 33.3 | 37.8 | 42.9 | 46.0 | 48.3 | 51.8 | 54.3 |
| Females | |||||||||||||
| 6 | 1.73 | 6.4 | 0.29 | 1.1 | 2.3 | 3.5 | 5.0 | 6.4 | 7.6 | 8.2 | 8.6 | 9.1 | 9.4 |
| 7 | 1.39 | 8.19 | 0.28 | 3.3 | 4.0 | 5.0 | 6.6 | 8.2 | 9.7 | 10.4 | 10.9 | 11.6 | 12.1 |
| 8 | 1.05 | 10.09 | 0.26 | 5.1 | 5.8 | 6.7 | 8.3 | 10.1 | 11.8 | 12.8 | 13.4 | 14.3 | 14.9 |
| 9 | 0.73 | 11.99 | 0.24 | 6.9 | 7.5 | 8.5 | 10.1 | 12.0 | 14.0 | 15.1 | 15.8 | 16.9 | 17.7 |
| 10 | 0.44 | 13.95 | 0.22 | 8.8 | 9.4 | 10.3 | 11.9 | 14.0 | 16.1 | 17.4 | 18.3 | 19.6 | 20.5 |
| 11 | 0.20 | 16.32 | 0.21 | 10.8 | 11.4 | 12.4 | 14.1 | 16.3 | 18.8 | 20.2 | 21.2 | 22.8 | 23.8 |
| 12 | 0.02 | 18.73 | 0.2 | 12.8 | 13.5 | 14.5 | 16.4 | 18.7 | 21.4 | 23.0 | 24.2 | 26.0 | 27.2 |
| 13 | −0.1 | 20.72 | 0.19 | 14.5 | 15.2 | 16.2 | 18.2 | 20.7 | 23.6 | 25.3 | 26.6 | 28.6 | 29.9 |
| 14 | −0.17 | 22.15 | 0.19 | 15.8 | 16.5 | 17.6 | 19.6 | 22.2 | 25.1 | 26.9 | 28.2 | 30.3 | 31.7 |
| 15 | −0.21 | 22.98 | 0.18 | 16.6 | 17.2 | 18.3 | 20.4 | 23.0 | 26.0 | 27.8 | 29.1 | 31.2 | 32.6 |
| 16 | −0.22 | 23.18 | 0.18 | 16.8 | 17.5 | 18.6 | 20.6 | 23.2 | 26.1 | 27.9 | 29.2 | 31.3 | 32.7 |
| 17 | −0.21 | 23.05 | 0.17 | 16.8 | 17.5 | 18.5 | 20.5 | 23.1 | 26.0 | 27.7 | 29.0 | 30.9 | 32.3 |
P Percentile, L Lambda, M Median, S Coefficient of variation
Table 4.
Percentiles de la HGS de ambas manos en escolares según edad y sexo
| Age | L | M | S | P3 | P5 | P10 | P15 | P25 | P50 | P75 | P85 | P90 | P95 | P97 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Males | ||||||||||||||
| 6 | −0.21 | 6.99 | 0.34 | 3.9 | 4.1 | 4.6 | 5.0 | 5.6 | 7.0 | 8.8 | 10.0 | 11.0 | 12.5 | 13.7 |
| 7 | 0.13 | 8.68 | 0.32 | 4.7 | 5.1 | 5.7 | 6.2 | 7.0 | 8.7 | 10.7 | 12.0 | 12.9 | 14.4 | 15.4 |
| 8 | 0.34 | 10.46 | 0.3 | 5.6 | 6.1 | 7.0 | 7.6 | 8.5 | 10.5 | 12.7 | 14.0 | 15.0 | 16.5 | 17.5 |
| 9 | 0.45 | 12.19 | 0.28 | 6.7 | 7.3 | 8.2 | 8.9 | 10.0 | 12.2 | 14.6 | 16.0 | 17 | 18.6 | 19.6 |
| 10 | 0.56 | 14.07 | 0.27 | 7.8 | 8.5 | 9.6 | 10.4 | 11.6 | 14.1 | 16.7 | 18.2 | 19.2 | 20.8 | 21.9 |
| 11 | 0.62 | 16.7 | 0.25 | 9.5 | 10.3 | 11.6 | 12.6 | 14.0 | 16.7 | 19.6 | 21.3 | 22.4 | 24.2 | 25.3 |
| 12 | 0.62 | 20.3 | 0.24 | 12 | 12.9 | 14.4 | 15.5 | 17.1 | 20.3 | 23.7 | 25.6 | 26.9 | 28.9 | 30.2 |
| 13 | 0.55 | 24.52 | 0.23 | 15.1 | 16.2 | 17.9 | 19.1 | 20.9 | 24.5 | 28.4 | 30.6 | 32.1 | 34.4 | 36.0 |
| 14 | 0.42 | 28.65 | 0.21 | 18.5 | 19.6 | 21.4 | 22.7 | 24.7 | 28.7 | 33.0 | 35.4 | 37.1 | 39.8 | 41.5 |
| 15 | 0.25 | 32.47 | 0.2 | 21.8 | 23 | 24.9 | 26.2 | 28.3 | 32.5 | 37.1 | 39.8 | 41.7 | 44.6 | 46.6 |
| 16 | 0.02 | 35.95 | 0.19 | 25.2 | 26.3 | 28.2 | 29.5 | 31.6 | 36.0 | 40.8 | 43.7 | 45.8 | 49 | 51.2 |
| 17 | −0.26 | 39.31 | 0.18 | 28.5 | 29.7 | 31.5 | 32.8 | 34.9 | 39.3 | 44.4 | 47.5 | 49.7 | 53.3 | 55.7 |
| Females | ||||||||||||||
| 6 | 1.34 | 6.78 | 0.27 | 2.8 | 3.4 | 4.2 | 4.8 | 5.5 | 6.8 | 8.0 | 8.6 | 9.0 | 9.6 | 10.0 |
| 7 | 1.14 | 8.4 | 0.26 | 4.1 | 4.7 | 5.5 | 6.1 | 6.9 | 8.4 | 9.9 | 10.6 | 11.1 | 11.9 | 12.4 |
| 8 | 0.95 | 10.23 | 0.25 | 5.6 | 6.2 | 7.0 | 7.7 | 8.6 | 10.2 | 11.9 | 12.9 | 13.5 | 14.4 | 15.0 |
| 9 | 0.76 | 12.18 | 0.23 | 7.2 | 7.8 | 8.7 | 9.3 | 10.3 | 12.2 | 14.1 | 15.2 | 15.9 | 17.0 | 17.7 |
| 10 | 0.57 | 14.22 | 0.22 | 8.9 | 9.5 | 10.5 | 11.2 | 12.2 | 14.2 | 16.4 | 17.6 | 18.4 | 19.7 | 20.6 |
| 11 | 0.39 | 16.62 | 0.21 | 10.8 | 11.5 | 12.5 | 13.2 | 14.4 | 16.6 | 19.1 | 20.5 | 21.5 | 23.0 | 24.0 |
| 12 | 0.22 | 19.01 | 0.2 | 12.8 | 13.5 | 14.6 | 15.3 | 16.6 | 19.0 | 21.8 | 23.3 | 24.5 | 26.2 | 27.4 |
| 13 | 0.05 | 20.97 | 0.2 | 14.5 | 15.2 | 16.3 | 17.1 | 18.4 | 21.0 | 23.9 | 25.7 | 26.9 | 28.9 | 30.2 |
| 14 | −0.12 | 22.4 | 0.19 | 15.8 | 16.5 | 17.7 | 18.5 | 19.8 | 22.4 | 25.5 | 27.3 | 28.6 | 30.7 | 32.2 |
| 15 | −0.28 | 23.28 | 0.18 | 16.8 | 17.5 | 18.6 | 19.4 | 20.7 | 23.3 | 26.4 | 28.2 | 29.6 | 31.7 | 33.3 |
| 16 | −0.44 | 23.52 | 0.17 | 17.4 | 18.0 | 19.0 | 19.8 | 21.0 | 23.5 | 26.5 | 28.4 | 29.7 | 31.9 | 33.4 |
| 17 | −0.59 | 23.42 | 0.17 | 17.6 | 18.2 | 19.2 | 19.9 | 21.0 | 23.4 | 26.3 | 28.1 | 29.4 | 31.6 | 33.1 |
P Percentile, L Lambda, M Median, S Coefficient of variation
Discussion
The initial objective of the study was to compare the HGS of children and adolescents from a moderate altitude region of Peru with other regional studies. The results of the study evidence that HGS values are slightly lower than those of children in Chile [7] in both sexes. Furthermore, in relation to Peruvian schoolchildren [6], children and adolescents of moderate altitude (Arequipa), show higher values in both sexes and at all ages. This suggests a better performance in HGS throughout childhood and adolescence.
We also verified that Colombian schoolchildren [8] showed a slight advantage in HGS during childhood over schoolchildren at moderate altitude (Arequipa). However, during adolescence, Colombian schoolchildren showed lower values in relation to their counterparts at moderate altitude (Arequipa).
The findings of this study revealed disparities in the trajectory of HGS levels in relation to countries such as Chile and Colombia, and even with the Peruvian study. These results indicate that there are contextual factors (such as nutrition, physical activity, socioeconomic and sociocultural conditions, lifestyle, environmental pollution, among others) that could be involved in the development of HGS [17–20].
In recent years, several international studies have been performed in various countries around the world, seeking to compare HGS values between young children and adults [7, 21, 22]. These findings have evidenced discrepancies between countries and regions, which reinforces the results of the present study. Although they suggest the need to provide attention to the factors affecting such discrepancies.
Overall, the results of this study point to differences in HGS performance in schools between neighboring countries. This underlines the need to develop and propose native reference values to assess and monitor schoolchildren living at moderate altitude in Peru. For this region presents unique characteristics, such as specific environmental conditions. For example, physical growth patterns are typical of this region, and are associated with plasticity processes due to the sensitivity of the environment [23, 24]. Therefore, implementing reference values for schoolchildren in this region could contribute to the identification of specific needs and in the design of appropriate interventions in school-based physical education programs in this region.
From that perspective, the second objective of the study was to propose reference values of HGS by age, sex in children and adolescents living in a moderate altitude region of Peru. In fact, several recent studies consider reference values as a valuable source of information for the clinical evaluation of HGS and for comparison with studies from other countries [7, 22, 25].
The references proposed in this study may contribute to improving accuracy of detecting muscle weakness according to age and sex. This is especially relevant in populations that may be exposed to unique environmental factors, such as altitude. For uses and applications of HGS assessment have often been used as a parameter to assess upper extremity functional status as part of upper extremity treatment and/or trauma [26, 27]. As well as an indicator to establish health status and/or biomarker to predict mortality, disability and disease risks [28] associated with the diagnosis muscle frailty at various stages of life [10, 27].
These values allow comparison of muscle performance between different populations and are essential to identify deviations that could indicate health problems in schoolchildren living in regions of moderate altitude. To this end, the cut-off points considered in this study were based on previous studies [7, 10, 29]. Where p5 to p15 can be interpreted with a low level of HGS. Between p15 to p85 as adequate and >p85 as high HGS.
Overall, the use and implementation of this valuable tool are a reasonable alternative in terms of cost and can be easily administered to a large number of subjects simultaneously [7]. In addition, it can serve as a low-cost test and can be considered as the most suitable for resource-limited settings [4]. As are the Peruvian government public schools, where the need for effective and economical tools is particularly urgent to address public health problems and promote the physical well-being of students at the primary and secondary level.
In sum, to our knowledge, this is the first study to propose reference values in a large sample size in a Peruvian region. Thus, it can serve as a baseline for future research looking for longitudinal changes. In addition, this study contributes extensively to the scientific literature. Since it provides relevant data from a little studied and explored population such as schoolchildren living in regions of moderate altitude. These percentiles can serve as a tool to monitor schoolchildren from infancy to adolescence. It can also be used to design intervention programs aimed at improving muscular weakness in schoolchildren.
Notwithstanding the above, this study has some limitations, given that a cross-sectional design was used. This prevents the analysis of cause-and-effect relationships and, consequently, the follow-up of secular changes. In addition, the sample selection was non-probabilistic. This prevents the generalization of the results to other sociocultural contexts in Peru. Future studies should consider this aspect, since probabilistic sampling allows for more robust and generalizable reference values and minimizes selection bias. We also highlight that it was not possible to control for some confounding variables, such as levels of physical activity, nutritional habits, and socioeconomic status of the schoolchildren. Controlling for these factors would have helped to better analyze and interpret our findings. Future studies should take these relevant aspects into consideration, as it could provide a comprehensive understanding of muscle health in moderate altitude schoolchildren.
In summary, future studies should focus on developing studies that analyze the classification of health criteria in different population contexts. They should also evaluate the predictive capacity regarding physical and functional health, as this information can lead to monitoring the health status of pediatric populations.
Conclusion
The results of the study have shown discrepancies in HGS among schoolchildren from different geographic regions. The schoolchildren studied showed HGS values higher than those of schoolchildren from Chile and, in some cases, those from Colombia during adolescence. This evidence allowed the construction of percentiles to evaluate HGS by age and sex from 6 to 17 years of age. Their use and application in educational and clinical contexts for the evaluation and monitoring of muscle health in schoolchildren is suggested.
Acknowledgements
We would like to express our gratitude to all the participating students, teachers, and schools for their tremendous support.
Abbreviations
- HGS
Hand Grip Strenght
- X
Mean
- SD
Standard deviation
- CI
Confidence Interval
- BMI
Body mass index
Authors’ contributions
M.C.B., R.G.C., and R.V.E. contributed to the design of the research study. J.S.T., A.V.F., L.T.P., and J.G.B., collected data. M.C.B., R.G.C., R.V.E., and J.S.T., contributed to the discussion, wrote the manuscript and reviewed/edited the manuscript. M.C.B. and R.G.C edited and reviewed the manuscript. All authors revised and agreed on the views expressed in the manuscript.
Funding
No funding received.
Data availability
The datasets supporting the conclusions of this research article are available by emailing the corresponding author.
Declarations
Ethics approval and consent to participate
The study protocol was approved by the Ethic Committee of the Universidad Católica Santa María 096-2022. All experiments were performed in accordance with relevant guidelines and regulations (such as the Declaration of Helsinki). Parents and guardians provided informed written consent for their children under the age of 16 participating in the study. In addition, all students under and over the age of 16 in the study provided written informed consent acknowledging their consent to participate and their understanding of the research procedures and objectives.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Marco Cossio-Bolaños, Email: mcossio1972@hotmail.com.
Rossana Gomez-Campos, Email: rossaunicamp@gmail.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets supporting the conclusions of this research article are available by emailing the corresponding author.