Objective
Related evidences of metabolically unhealthy profile of adults with normal weight are not well characterized in the Chinese population. This is because they cannot be effectively identified by regular measurements (such as body mass index [BMI]). To overcome this gap in literature, this study aimed at investigating the association between body composition and metabolically unhealthy profile in Chinese adults with normal weight.
Methods
A total of 5427 individuals with normal-weight were recruited from 15820 people living in Ningxia Hui Autonomous Region in Northwest China. Normal-weight was defined as a BMI of 18.5–23.9 kg/m2. Metabolically unhealthy profile was assessed by the National Cholesterol Education Program Adult Treatment Panel III (ATP III). Metabolically unhealthy normal-weight (MUHNW) profile was defined in individuals who had normal weight and at least two cardiometabolic risk factors. Generalized linear model was used to investigate the association between body composition measured by bioelectrical impedance and metabolically unhealthy profile in adults with normal-weight.
Results
The percentage of metabolically unhealthy profile was 35.86% in adults with normal weight. Different MUHNW distributions were found between males and females depending on age. The percentage of the MUHNW profile significantly increased in women after the age of 55, contrary to men. The association between body composition and MUHNW was affected by age and sex. The increased adiposity indices (fat mass index [FMI], visceral fat level [VFL], waist circumference [WCF]), and reduced skeletal muscle mass ratio [SMR] showed significant differences between MUHNW and metabolically healthy with normal weight (MHNW) (p < 0.05).
Conclusion
The distribution of MUHNW differed between ages and sexes. FMI, VFL, WCF and SMR could be responsible for the MUHNW adults, providing a new insight into the potential metabolic risks for the adults with normal weight in China. This directs us in the management of the MUHNW for their early prevention.
Background
Diet is a modifiable risk factor for cardiovascular diseases (CVD), but there is still a lack of tools to assess dietary intakes of this high-risk population in Ningxia, China.
Objective
We aim to evaluate the validity and reliability of the semi-quantitative food frequency questionnaire (SFFQ) in the groups in Ningxia using a 24-hour dietary recall method.
Method
Two hundred five participants were included in the analysis. The two FFQs were 6 months apart, and during this time two 24-hour dietary recalls (24HDRs) were completed. Statistical methods were compared using inter-class correlation coefficient, unadjusted, energy-adjusted, de-attenuated correlation coefficient, quartile classification, weighted K values, and 95% limits of agreement (LOA).
Results
The inter-class correlation coefficients between FFQ1 and FFQ2 ranged from 0.25 to 0.73. The number of subjects classified as identical or adjacent was 72.2 to 85.9%. The crude correlation coefficient between FFQs and 24HDRs was 0.30 ~ 0.81, the energy-adjusted correlation coefficient was 0.16 ~ 0.83, and the de-attenuated correlation coefficient was 0.19 ~ 0.98. Weighted k statistics and Bland-Altman plots showed acceptable agreement between FFQs and 24HDRs.
Conclusion
The FFQ developed for the population at high risk of cardiovascular and cerebrovascular diseases in areas of Ningxia can be used to measure the dietary intake of nutrients and food groups reliably and validly.
Objectives: To evaluate the distribution and changes in different obesity metabolic phenotypes, as well as their impact on the incidence of type 2 diabetes mellitus (T2DM) in a northwest Chinese population sample.Methods: Data comes from prospective cohort study (n = 1,393, mean follow up = 9.46 years). Participants were classified into four groups through a combination of the Chinese Diabetes Society (CDS) diagnostic criteria for metabolic syndrome with anthropometric measurements: metabolically healthy normal weight (MHNW), metabolically healthy overweight/obese (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy overweight/obese (MUO). Cox regression models with time-dependent covariates were used to evaluate changes in obesity metabolic phenotypes and risk of T2DM.Results: Participants in MUO state had the highest risk of developing T2DM, the incidence density was 12.10/1,000 person-year. The MHO and MUO groups showed an increased risk of incident diabetes based on body mass index (BMI) (HR, 1.29; 95% CI, 1.03–1.61; p = 0.026 and HR, 1.20; 95% CI, 1.02–1.40; p = 0.024 respectively.) Besides, the MHO group had an increased risk of incident diabetes based on waist circumference (WC) (HR, 1.41; 95% CI, 1.10–1.80; p = 0.006).Conclusion: Diabetes is more frequent in the MHO and MUO groups and co-occurrence of obesity and metabolic abnormalities (MA) contributes to the development of T2DM.
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