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ABSTRACT: Background
Fasting plasma glucose (FPG) variability is a significant predictor of mortality, especially in patients with poor glycemic control. This study aimed to explore the temporal age- and sex-specific profiles of temporal FPG variability in a Chinese population undergoing routine health screening and to guide the development of targeted public health interventions for the prevention and control of diabetes.Methods
In this cross-sectional study, we used a general linear model to compare differences in temporal FPG values between sexes and across age groups in 101,886 Nanjing residents who underwent a routine physical health examination at the Health Management Center, the First Affiliated Hospital of Nanjing Medical University, in 2018. The variability of FPG as a function of time, age, and sex, independently and in combination, was analyzed.Results
The participants included 57,455 (56.4%) males and 44,431 (43.6%) females, with a mean?±?SD age of 42.8?±?15.0?years. The average?±?SD FPG level was 5.5?±?1.1?mmol/L. The monthly variation contributed to 22% of the overall FPG variability. A significant main effect for the age group was observed (F?=?7.39, P?ConclusionsTemporal variability in FPG is evident in the general Chinese population and is affected by both age and sex. To avoid complications associated with FPG variability, interventions should be directed at females and males at specific ages for optimal control of FPG variability and to reduce the risk of diabetes and cardiovascular events.
SUBMITTER: Lartey AH
PROVIDER: S-EPMC7871645 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Lartey Agyei Helena AH Li Xiaona X Li Zhongqi Z Zhang Qun Q Wang Jianming J
BMC public health 20210209 1
<h4>Background</h4>Fasting plasma glucose (FPG) variability is a significant predictor of mortality, especially in patients with poor glycemic control. This study aimed to explore the temporal age- and sex-specific profiles of temporal FPG variability in a Chinese population undergoing routine health screening and to guide the development of targeted public health interventions for the prevention and control of diabetes.<h4>Methods</h4>In this cross-sectional study, we used a general linear mode ...[more]