南非夸祖鲁-纳塔尔省小学生体质与人体测量、心血管和社会经济风险因素之间的关系

IF 0.2 Q4 PEDIATRICS
MSc O M Olagbegi, MPhysio PhD S B Khoza, T. Nadasan, Mot P Govender
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引用次数: 0

摘要

背景儿童的身体健康状况已被确定为慢性病风险因素的预测因素,也与各种非传染性疾病和成年后过早死亡风险增加有关。研究表明PF一直在下降。在南非(SA),人们注意到了类似的趋势,并将其归因于城市化以及从传统的积极生活方式向久坐生活方式的转变。目标。研究南非夸祖鲁-纳塔尔省407名6-13岁小学生的PF水平与社会经济地位(SES)、人体测量和心血管风险因素之间的可能关联。方法。在一项横断面研究中,使用Eurofit测试组评估儿童的PF得分:坐着和伸展、站立跳远(SLJ)、仰卧起坐(SU)、5米穿梭跑(5米SRT)和板球投掷(CBT)。SES采用结构化问卷进行评估。标准化程序用于人体测量和心血管测量。结果。女孩的体重明显高于男孩(p=0.001),体重指数(BMI)(p<0.001)、腰围(WC)(p>0.001)和臀围(HC)(p<0.001)明显更高,而男孩在SLJ(p=0.030)、SUs(p=0.022)、CBT(p<001)和5m SRT(p>001)方面的表现明显更好。PF和BMI之间存在显著的低负相关(r=–0.151;p=0.002),WC(r=–0.107;p=0.031)和HC(r=0.123;p=0.013)。多项逻辑回归分析确定BMI是该小学生队列中PF低的主要预测因素(比值比1.16;95%置信区间1.01-1.33)。小学年龄儿童低PF状态的发生可能受到性别和肥胖的影响。结论。作为健康筛查过程的一部分,在政策层面对PF进行评估可能有助于更明确地描述儿童的健康状况,并有助于早期识别风险因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association between physical fitness and anthropometric, cardiovascular and socioeconomic risk factors in primary schoolchildren in KwaZulu‑Natal Province, South Africa
Background. Physical fitness (PF) status in children has been identified as a predictor of chronic disease risk factors, and has also been linked to various non-communicable diseases and an increased risk of premature death in adulthood. Studies have shown that PF has been declining. In South Africa (SA), a similar trend is noted and attributed to urbanisation and shifts from traditional active practices to sedentary lifestyles.  Objectives. To examine possible associations between PF levels and socioeconomic status (SES) and anthropometric and cardiovascular risk factors among 407 primary schoolchildren aged 6 - 13 years in KwaZulu-Natal Province, SA.  Methods. In a cross-sectional study, children’s PF scores were assessed using the Eurofit test battery: sit and reach, standing long jump (SLJ), sit-ups (SUs), 5 m shuttle run (5m-SRT) and cricket ball throw (CBT). SES was assessed using a structured questionnaire. Standardised procedures were used for anthropometric and cardiovascular measures.  Results. Girls weighed significantly more than boys (p=0.001) and had a significantly higher body mass index (BMI) (p<0.001), waist circumference (WC) (p<0.001) and hip circumference (HC) (p<0.001), while boys performed significantly better in SLJ (p=0.030), SUs (p=0.022), CBT (p<0.001) and 5m-SRT (p<0.001). A significant low negative correlation was found between PF and BMI (r=–0.151; p=0.002), WC (r=–0.107; p=0.031) and HC (r=0.123; p=0.013). Multinomial logistic regression analysis identified BMI as the main predictor of low PF (odds ratio 1.16; 95% confidence interval 1.01 - 1.33) in this cohort of primary schoolchildren. The occurrence of low PF status in children of primary school age may be influenced by gender and adiposity.  Conclusion. Assessment of PF at policy levels as part of the health screening process may help create a more explicit depiction of the health status of children and assist in early identification of risk factors. 
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CiteScore
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