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身体意象图表判定欠发达人群成年人超重/肥胖的有效性:Pars 队列研究结果。

Validity of Body Image Pictogram to Determine Overweight/Obesity in Adults from Less Developed Populations: Results From Pars Cohort Study.

机构信息

MPH Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.

Research Center for Traditional Medicine and History of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.

出版信息

Arch Iran Med. 2022 Dec 1;25(12):779-787. doi: 10.34172/aim.2022.123.

Abstract

BACKGROUND

Despite the evidence for validity of body image pictogram (BIP) to discriminate overweight, obese, and normal individuals, there is little evidence on the probable effect of socio-demographic variables on its validity. To investigate the effects of socioeconomic status (SES), age, ethnicity, and educational level on the validity of BIP to discriminate normal weight, overweight, and obese people.

METHODS

We used the Pars Cohort Study (PCS) data. Stunkard's BIP score was used as test measure. Participants were classified as normal (body mass index [BMI]<25), overweight (BMI=25 to 29.9), and obese (BMI≥29.9) based on their BMI (kg/m ). Area under curve (AUC) and its 95% CI were estimated and compared. Optimal cutoff points and their sensitivity, specificity, and likelihood ratio were reported.

RESULTS

A total of 9232 participants with a female/male ratio of 1.03 were included. The prevalence of overweight and obesity was 37.4% and 18.2%, respectively. Regardless of socio-demographic levels, the optimal cut-points to discriminate normal BMI from overweight, and overweight from obese participants were BIP score of four and five, respectively. Estimated AUC correlated with ethnicity (<0.001) for both genders, and with SES for females (<0.05).

CONCLUSION

Although BIP may be a valid measure to categorize the general adult population into normal, overweight and obese, its validity depends on SES and ethnicity. BIP may be available as a proxy measure for BMI categories in socio-demographically homogeneous populations but not in heterogeneous populations.

摘要

背景

尽管身体意象图像(BIP)在区分超重、肥胖和正常个体方面具有有效性的证据,但关于社会人口统计学变量对其有效性可能产生的影响的证据很少。为了研究社会经济地位(SES)、年龄、种族和教育水平对 BIP 区分正常体重、超重和肥胖人群的有效性的影响。

方法

我们使用了 Pars 队列研究(PCS)的数据。使用 Stunkard 的 BIP 评分作为测试指标。根据 BMI(kg/m ),参与者被分为正常体重(BMI<25)、超重(BMI=25 至 29.9)和肥胖(BMI≥29.9)。估计并比较了曲线下面积(AUC)及其 95%CI。报告了最佳截断点及其敏感性、特异性和似然比。

结果

共有 9232 名女性/男性比例为 1.03 的参与者纳入研究。超重和肥胖的患病率分别为 37.4%和 18.2%。无论社会人口统计学水平如何,最佳截断点是 BIP 评分 4 分和 5 分,以区分正常 BMI 与超重和超重与肥胖参与者。估计的 AUC 与性别相关(<0.001),与 SES 相关(女性<0.05)。

结论

尽管 BIP 可能是一种有效的措施,用于将一般成年人群分为正常、超重和肥胖人群,但它的有效性取决于 SES 和种族。BIP 可以作为社会人口统计学同质人群中 BMI 类别的替代指标,但不能用于异质人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/48e2/10685844/997be169b2c9/aim-25-779-g001.jpg

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