The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese
In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | Nutrients |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6643/13/12/4356 |
| _version_ | 1797501749950414848 |
|---|---|
| author | Fang Li Lizhang Chen |
| author_facet | Fang Li Lizhang Chen |
| author_sort | Fang Li |
| collection | DOAJ |
| description | In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690–0.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes. |
| first_indexed | 2024-03-10T03:24:02Z |
| format | Article |
| id | doaj.art-0bbdd228d47046e0b8c5a842a82da647 |
| institution | Directory Open Access Journal |
| issn | 2072-6643 |
| language | English |
| last_indexed | 2024-03-10T03:24:02Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nutrients |
| spelling | doaj.art-0bbdd228d47046e0b8c5a842a82da6472023-11-23T09:56:35ZengMDPI AGNutrients2072-66432021-12-011312435610.3390/nu13124356The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic ChineseFang Li0Lizhang Chen1Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, ChinaDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, ChinaIn order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690–0.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes.https://www.mdpi.com/2072-6643/13/12/4356prediabetesdiabetestrajectories of body mass indextrajectories of mid-upper arm circumferencegrowth mixture modelingcohort study |
| spellingShingle | Fang Li Lizhang Chen The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese Nutrients prediabetes diabetes trajectories of body mass index trajectories of mid-upper arm circumference growth mixture modeling cohort study |
| title | The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese |
| title_full | The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese |
| title_fullStr | The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese |
| title_full_unstemmed | The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese |
| title_short | The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese |
| title_sort | association between trajectories of anthropometric variables and risk of diabetes among prediabetic chinese |
| topic | prediabetes diabetes trajectories of body mass index trajectories of mid-upper arm circumference growth mixture modeling cohort study |
| url | https://www.mdpi.com/2072-6643/13/12/4356 |
| work_keys_str_mv | AT fangli theassociationbetweentrajectoriesofanthropometricvariablesandriskofdiabetesamongprediabeticchinese AT lizhangchen theassociationbetweentrajectoriesofanthropometricvariablesandriskofdiabetesamongprediabeticchinese AT fangli associationbetweentrajectoriesofanthropometricvariablesandriskofdiabetesamongprediabeticchinese AT lizhangchen associationbetweentrajectoriesofanthropometricvariablesandriskofdiabetesamongprediabeticchinese |