BackgroundHand grip strength (HGS) is associated with a number of causes resulting in cardiovascular death, in addition to bone fragility, and the presence of sarcopenia. The goal of our study was to analyze HGS of students based on chronological and biological age and propose normative standards for children and adolescents from Chile.MethodsWe studied 4604 school children of both sexes between the ages of 6.0 and 17.9 years of age. Weight, standing height, sitting height, and hand grip strength (HGS- right and left) were measured. The Body Mass Index (BMI) was calculated, and the biological age was calculated by using age at peak height velocity (APHV).ResultsWhen arranged by chronological age, no significant differences occurred in HGS between both sexes of school children from age 6 to 12 years of age. However, from ages 13 to 17, males showed greater HGS than females. Significant differences also emerged between both sexes and at all levels for biological age (APHV). For males, chronological age explained the HGS occurring between 0.74 to 0.75% and for females between 0.54 to 0.59%. For males, biological age explained the HGS for the range of 0.79 to 0.80% and 0.62 to 0.67% for females. The normative data for HGS for both sexes is expressed in percentiles.ConclusionsHGS during childhood and adolescence needs be analyzed and interpreted in terms of biological age rather than chronological age. The normative data to evaluate the HGS are a tool that can help professionals working in clinical and epidemiological contexts.
BackgroundThe Dual Energy X-Ray Absorptiometry (DXA) is the gold standard for measuring BMD and bone mineral content (BMC). In general, DXA is ideal for pediatric use. However, the development of specific standards for particular geographic regions limits its use and application for certain socio-cultural contexts. Additionally, the anthropometry may be a low cost and easy to use alternative method in epidemiological contexts. The goal of our study was to develop regression equations for predicting bone health of children and adolescents based on anthropometric indicators to propose reference values based on age and sex.Methods3020 students (1567 males and 1453 females) ranging in ages 4.0 to 18.9 were studied from the Maule Region (Chile). Anthropometric variables evaluated included: weight, standing height, sitting height, forearm length, and femur diameter. A total body scan (without the head) was conducted by means of the Dual Energy X-Ray Absorptiometry. Bone mineral density (BMD) and the bone mineral content (BMC) were also determined. Calcium consumption was controlled for by recording the intake of the three last days prior to the evaluation. Body Mass Index (BMI) was calculated, and somatic maturation was determined by using the years of peak growth rate (APHV).ResultsFour regression models were generated to calculate bone health: for males BMD = (R2 = 0.79) and BMC = (R2 = 0.84) and for the females BMD = (R2 = 0.76) and BMC = (R2 = 0.83). Percentiles were developed by using the LMS method (p3, p5, p15, p25, p50, p75, p85, p95 and p97).ConclusionsRegression equations and reference curves were developed to assess the bone health of Chilean children and adolescents. These instruments help identify children with potential underlying problems in bone mineralization during the growth stage and biological maturation.
Objectives: The goal of this study was to develop regression equations to estimate LM with anthropometric variables and to propose percentiles for evaluating by age and sex. Methods: A cross sectional study was conducted with 2,182 Chilean students (1,347 males and 835 females). Ages ranged from 5.0 to 17.9 years old. A total body scan was carried out with the double energy X-ray anthropometry (DXA) to examine and measure lean muscle mass of the entire body. Weight, height, and the circumference of the relaxed right arm were also measured. Results: Four anthropometric equations were generated to predict lean mass for both sexes ( R 2 = 83–88%, SEE = 3.7–5.0%, precision = 0.90–0.93, and accuracy = 0.99). The Lambda-mu-sigma method was used to obtain the sex-specific and age-specific percentile curves of lean mass (p3, p5, p10, p15, p25, p50, p75, p85, p90, p95, and p97). Conclusion: The four proposed equations were acceptable in terms of precision and accuracy to estimate lean mass in children and adolescents. The percentiles were created by means of anthropometric equations and real values for DXA. These are fundamental tools for monitoring LM in Chilean children and adolescents of both sexes.
IntroductionMeasurement of hand grip strength (HGS) has been proposed as a key component of frailty and has also been suggested as a central biomarker of healthy aging and a powerful predictor of future morbidity and mortality.Objectives(a) To determine whether a nonlinear relationship model could improve the prediction of handgrip strength (HGS) compared to the linear model and (b) to propose percentiles to evaluate HGS according to age and sex for a regional population of Chile from infancy to senescence.MethodsA cross-sectional descriptive study was developed in a representative sample of the Maule region (Chile). The volunteers amounted to 5,376 participants (2,840 men and 2,536 women), with an age range from 6 to 80 years old. Weight, height, HGS (right and left hand) according to age and sex were evaluated. Percentiles were calculated using the LMS method [(L (Lambda; asymmetry), M (Mu; median), and S (Sigma; coefficient of variation)].Results and discussionThere were no differences in HGS from 6 to 11 years of age in both sexes; however, from 12 years of age onwards, males presented higher HGS values in both hands (p < 0.05). The linear regression between age with HGS showed values of R2 = 0.07 in males and R2 = 0.02 in females. While in the non-linear model (cubic), the values were: R2 = 0.50 to 0.51 in men and R2 = 0.26 in women. The percentiles constructed by age and sex were: P5, P15, P50, P85, and P95 by age range and sex. This study demonstrated that there is a nonlinear relationship between chronological age with HGS from infancy to senescence. Furthermore, the proposed percentiles can serve as a guide to assess and monitor upper extremity muscle strength levels at all stages of life.
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