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印度曼尼普尔邦梅泰成年人的身体成分参数和人体测量体型与体型类型的相关性。

Correlation of body composition parameters and anthropometric somatotypes with body types among the Meitei adults of Manipur, India.

机构信息

Department of Anthropology, UGC - SRF, Manipur University, Imphal, India.

RMO, Nemcare Superspeciality Hospital, Guwahati, India.

出版信息

Ann Hum Biol. 2021 Mar;48(2):160-165. doi: 10.1080/03014460.2021.1919205.

Abstract

BACKGROUND

Body composition and types are often considered essential health indicators for lifestyle-related disease. Assessment of body type based on is regarded as a prerequisite in Ayurveda.

AIM

To correlate body compositions and somatotypes with body types.

SUBJECTS AND METHODS

A cross-sectional study on 463 adult individuals was done. Anthropometric and body composition parameters were measured. Heath-Carter somatotypes and body types were also determined. Tests of association were calculated. Correlation and concordance analysis was also done to infer the correlation between body composition parameters and body types.

RESULTS

have significantly higher body weight, body mass index (BMI), body fat percentage and body fat mass. have the lowest mean values in all body composition parameters with in the intermediate position compared to the other types. There is a strong and positive statistical association between body types and body composition parameters, except height. Cohen's Kappa analysis reveals there is a fair concordance between body types and somatotype.

CONCLUSIONS

assessment can explain an individual's fatness as it correlates with body composition parameters and could be used to predict risk susceptibility to various complex disorders.

摘要

背景

体成分和体型通常被认为是与生活方式相关疾病的重要健康指标。基于体型的评估被认为是阿育吠陀的前提。

目的

将体成分和体型与阿育吠陀体型相关联。

受试者和方法

对 463 名成年个体进行了横断面研究。测量了人体测量学和体成分参数。还确定了 Heath-Carter 体型和阿育吠陀体型。计算了关联性检验。进行了相关性和一致性分析,以推断体成分参数与阿育吠陀体型之间的相关性。

结果

体型的体重、体重指数(BMI)、体脂肪百分比和体脂肪量显著较高。与其他体型相比,体型的所有体成分参数的平均值最低,体型处于中间位置。阿育吠陀体型与体成分参数之间存在很强的正统计关联,除了身高。Cohen's Kappa 分析表明,阿育吠陀体型和体型之间存在适度的一致性。

结论

评估可以解释个体的肥胖程度,因为它与体成分参数相关,可用于预测对各种复杂疾病的易感性。

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