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      Analysis of body composition between girls aged 10 to 15 years with or without onset of menarche in Nanyang

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          Abstract

          Objective To compare body composition of girls aged 10 to 15 years with or without onset of menarche in Nanyang, and to provide a reliable basis for effective adolescent health care.

          Methods From August to December 2020 and from March to October 2021, cluster random sampling was adopted in 13 areas of Nanyang City to select 1 523 girls. Questionnaire survey and body composition (Japan Bailida MC–180) were conducted.

          Results BMI, body fat percentage, trunk fat percentage, muscle mass and bone mass of girls aged 10 to 15 years in Nanyang City gradually increased with age, the water content in the body decreased with age. BMI, fat percentage, trunk fat percentage, muscle mass and bone mass in girls experienced menarche were higher, while water content in the body was lower than those without menarche. Significant difference in BMI between the menarche and without menarche of girls were found in those aged 11 to 15 years ( t = 2.07, 2.03, 2.43, 2.45, 2.52, P<0.05). Significant differences in fat rate, trunk fat rate, muscle mass and bone mass between the menarche and without menarche were found in girls aged 12 to 15 years fat percentage, trunk fat percentage muscle mass bone mass ( P<0.05). Among girls aged 10, 14 and 15-year-old, significant difference in body water percentage were observed in the two groups of girls with or without menarche ( t = 2.75, 2.35, 2.37, P<0.05). Average age at menarche showed significant urban-rural differences among girls aged 10, 11 and 14-year-old (χ 2 = 4.34, 3.45, 6.73, P<0.05).

          Conclusion Changes in body composition including BMI, body fat percentage, muscle mass, bone mass and body water percentage during the transition to menarche in girls is helpful to predict menarche in girls. Age of menarche is related to nutritional status, BMI, physical exercise, snack and beverage intake.

          Abstract

          【摘要】 目的 了解南阳市 10~15 岁月经来潮与未来潮女生体成分的年龄变化特点, 预测月经初潮时间, 为及时开展青 春期的卫生保健工作提供可靠依据。 方法 于 2020 年 8—12 月及 2021 年 3—10 月, 对南阳市 13 个县市区采取抽签法随 机整群抽样抽取 1 523 名女生, 先通过问卷调査获取研究对象基本情况, 然后利用日本百利达MC–180体成分分析仪对研 究对象进行体成分测定。 结果 南阳市 10~15 岁女生体质量指数(BMI)、脂肪率、躯干脂肪率、肌肉量、骨量随着年龄的 增长而逐渐增加, 体内水分率随着年龄的增长逐渐减少。来潮女生的BMI、脂肪率、躯干脂肪率、肌肉量、骨量均髙于未来 潮女生, 体内水分率低于未来潮女生。其中 11~15 岁已来潮女生与未来潮女生之间 BMI 差异均有统计学意义 ( t 值分别为 2.07, 2.03, 2.43, 2.45, 2.52, P 值均<0.05); 12~15 岁已来潮女生与未来潮女生之间脂肪率、躯干脂肪率、肌肉量、骨量差异 均有统计学意义 ( P 值均<0.05); 10, 14, 15 岁未来潮女生与已来潮女生间体内水分率差异均有统计学意义 ( t 值分别为 2.75, 2.35, 2.37, P 值均<0.05); 10, 11, 14 岁同年龄组农村女生和城市女生月经来潮率差异有统计学意义 (χ 2 值分别为 4.34, 3.45, 6.73, P 值均<0.05)。 结论 女生月经初潮前后 BMI、脂肪率、躯干脂肪率、肌肉量、骨量、体内水分率等体成分年 龄变化特点有助于月经初潮的预判, 月经初潮年龄与营养状况、BMI、体育锻炼、零食及饮料摄人等因素有关。

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          Author and article information

          Journal
          CJSH
          Chinese Journal of School Health
          Chinese Journal of School Health (China )
          1000-9817
          01 November 2022
          01 November 2022
          : 43
          : 11
          : 1713-1716
          Affiliations
          [1] 1Department of Anatomy, Nanyang Medical College, Nanyang (473000), Henan Province, China
          Author notes
          *Corresponding author: LIU Rongzhi, E-mail: liurongzhi@ 123456sina.com
          Article
          j.cnki.1000-9817.2022.11.027
          10.16835/j.cnki.1000-9817.2022.11.027
          9251652e-ccfa-402e-ad64-f05ad3d663d7
          © 2022 Chinese Journal of School Health

          This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

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          Self URI (journal-page): http://www.cjsh.org.cn
          Categories
          Journal Article

          Ophthalmology & Optometry,Pediatrics,Nutrition & Dietetics,Clinical Psychology & Psychiatry,Public health
          Menarche,Body mass index,Body composition,Students,Female,Regression analysis

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