Efficacy of anthropometric measures for identifying cardiovascular disease risk in adolescents: review and meta-analysis

Lichtenauer, Michael; Wheatley, Sean; James, Marrissa Martyn-St; Duncan, Michael; Cobayashi, Fernanda; Berg, Gabriela; Musso, Carla; Graffigna, Mabel; Soutelo, Jimena; Bovet, Pascal; Stergiou, George S.; Grammatikos, Evangelos; Griffiths, Claire; Ingle, Lee; Jung, Christian

doi:10.23736/s0026-4946.18.05175-7

Cited by 18 publications

(14 citation statements)

References 33 publications

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“…Blood pressure was the only variable that entered the factor analysis out of those selected as potential metabolic variables. The relationship between BMI and blood pressure is well documented [ 54 ], and blood pressure therefore fits well in a body size factor. However, blood pressure can also be an indicator for other metabolic variables [ 55 ].…”

Section: Discussionmentioning

confidence: 80%

Data driven model of midportion achilles tendinopathy health created with factor analysis

Sigurðsson

Couppé

Silbernagel

2022

BMC Musculoskelet Disord

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Background Achilles tendinopathy is a complex injury and the clinical presentation spans multiple different domains: physical and psychological symptoms, lower extremity function and tendon structure. A conceptual model of Achilles tendon health comprising these domains has been proposed in the literature. The aim of the study was to fit a model of Achilles tendinopathy using factor analysis and compare that to the conceptual model. An inclusive approach using a wide range of variables spanning multiple potential domains were included. Methods Participants (N = 99) with midportion Achilles tendinopathy were assessed with variables representing symptoms, physical function, tendon structure, metabolic syndrome, and psychologic symptoms. A Kaiser-Mayer-Olkin index was used to determine suitable variables for a subsequent exploratory factor analysis. Results A model emerged with an acceptable fit to the data (standardized root mean square of residuals = 0.078). Five uncorrelated factors emerged from the model and were labelled as biopsychosocial, lower extremity function, body size, load tolerance, and tendon structure. The total explained variance was 0.51 with the five factors explaining 0.14, 0.12, 0.10, 0.08, and 0.07 respectively. The results differed from the conceptual model as the factors of psychological variables and metabolic variables did not emerge from the analysis. Conclusion A data driven model of Achilles tendon health supports assessment of the clinical presentation over multiple domains. As the factors are uncorrelated, the results of assessment of, for example, tendon structure should not be expected to be associated with lower extremity function or biopsychosocial limitations. The results suggest that the Patient Reported Outcomes Measurement Information System, counter-movement jump height, body mass index, pain with hopping, and the tendon cross-sectional area can evaluate the five factors, respectively. Trial registration Registered on clinicaltrials.gov (Medicine NL of. ClinicalTrials.gov [Internet], 2018), ID number NCT03523325.

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Section: Discussionmentioning

confidence: 80%

Data driven model of midportion achilles tendinopathy health created with factor analysis

Sigurðsson

Couppé

Silbernagel

2022

BMC Musculoskelet Disord

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“…Circumference measurements are cheap and simple anthropometric methods, and both hip/gluteal circumference and waist circumference are good predictors of intra-abdominal fat and cardiovascular risk factors [20,21]. WC is considered the most accurate anthropometric method to predict metabolic syndrome (MetS) in children [22][23][24].…”

Section: Discussionmentioning

confidence: 99%

Reference Curves of Selected Circumferential Parameters for Czech Children Aged 6 to 11 Years

2021

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(1) Background/objective: the globally discussed current issue is the increasing body weight of the population. This trend is observed in all age categories. Pediatricians and anthropologists use BMI percentile curves to determine the optimal body weight of children, based on which the child is categorized in the category of underweight, normal weight, overweight, or obese. Medical or anthropological examinations also use some methods to determine the amount of body fat. In addition to evaluating amounts of body fat, it is important to assess its distribution. The distribution of fat in the body, especially in terms of disproportionate distribution, is a risk factor for health complications, especially in terms of metabolic and health risk. Part of monitoring children’s growth is also measuring and evaluating circumferential parameters, such as abdominal circumference, gluteal circumference, and waist circumference. This study aimed to define age- and gender-specific reference curves for waist circumference (WC), abdominal circumference (AbC), and gluteal circumference (GC) in Czech children. (2) Methods: data on children’s circumferential parameters were collected via anthropometric measurements. The research sample consisted of 2093 children aged 6–11 years (boys, n = 1008; girls, n = 1085). Only children with parental informed consent were included. The statistical analysis was performed separately by age and gender using SPSS v. 22. Anthropometric data were summarized by mean and standard deviation. The percentile curves of WC, AbC, and GC were calculated (P3, P10, P25, P50, P75, P90, P97) in R 3.4.2 software (R Foundation for Statistical Computing, Vienna, Austria) using the gamlss package. (3) Results and conclusions: the study developed age- and gender-specific percentile curves of WC, AbC, and GC for Czech children aged 6–11 years. All parameters increased with age in both boys and girls. Generally, the boys had higher WC and AbC than did girls, but girls had higher GC than did boys. Female and male median WC percentiles (M) increased from the age of 6. Both girls’ and boys’ median percentiles showed a continuous increase. We found similar trends in the median GC and AbC percentile curves. All percentile curves showed similar trends in both sexes, but the 90th and 97th WC percentiles in boys were exceptions: from the age of 10, they exceeded the values of girls, reaching their peak at the age of 11 followed by a decrease in the case of the 97th percentile and a plateau in the case of the 90th percentile. This study serves as a reference to enrich the methods of evaluation of somatic and medical status in Czech children. Up–to–date percentile curves would be a practical addition to the BMI percentiles for the screening and evaluation of overweight and obese conditions and the related risks of abdominal obesity in the pediatric population.

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“…Indicators of abdominal obesity (AO), such as waist circumference (WC) and waist-to-height ratio (WHtR), have been considered better Cardiovascular disease (CVD) discriminators than overall obesity. 5 These are simple and low-cost indicators that can be used for early intervention. 5 In Brazil, the prevalence of obesity increased from 11.8% in 2006 to 19.8% in 2018, an increase of 67.8% in thirteen years.…”

Section: Introductionmentioning

confidence: 99%

Association between abdominal obesity, screen time and sleep in adolescents

Oliveira

Maciel

Costa

et al. 2023

Jornal de Pediatria

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Efficacy of anthropometric measures for identifying cardiovascular disease risk in adolescents: review and meta-analysis

Abstract: C (2018) Efficacy of anthropometric measures for identifying cardiovascular disease risk in adolescents: review and meta-analysis. Minerva Pediatrica, 70 (4). pp. 371-382.

Cited by 18 publications

References 33 publications

Data driven model of midportion achilles tendinopathy health created with factor analysis

Data driven model of midportion achilles tendinopathy health created with factor analysis

Reference Curves of Selected Circumferential Parameters for Czech Children Aged 6 to 11 Years

Association between abdominal obesity, screen time and sleep in adolescents

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