Literature DB >> 33563261

Age- and sex-specific profiles of temporal fasting plasma glucose variability in a population undergoing routine health screening.

Agyei Helena Lartey1, Xiaona Li2,3, Zhongqi Li1, Qun Zhang2,3, Jianming Wang4.   

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 < 0.05), with an excellent fitting effect (Eta-squared =0.15). The variability of FPG showed sex differences in the percentage difference of the coefficient of variation, which was 34.1% higher in males than females. There were significant interaction effects for month*age*sex and day*age*sex.
CONCLUSIONS: Temporal 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.

Entities:  

Keywords:  Coefficient of variation; Diabetes; Fasting plasma glucose; Temporal; Variability

Mesh:

Substances:

Year:  2021        PMID: 33563261      PMCID: PMC7871645          DOI: 10.1186/s12889-021-10367-x

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   3.295


  18 in total

1.  [Impact of intensive blood glucose control with hypoglycemic sulfamides, metformin or insulin on complications of non-insulin dependent diabetes].

Authors:  P André
Journal:  Rev Epidemiol Sante Publique       Date:  1999-03       Impact factor: 1.019

Review 2.  What causes health inequality? A systematic review on the relative importance of social causation and health selection.

Authors:  Hannes Kröger; Eduwin Pakpahan; Rasmus Hoffmann
Journal:  Eur J Public Health       Date:  2015-06-18       Impact factor: 3.367

Review 3.  Glucose variability; does it matter?

Authors:  Sarah E Siegelaar; Frits Holleman; Joost B L Hoekstra; J Hans DeVries
Journal:  Endocr Rev       Date:  2009-12-04       Impact factor: 19.871

4.  Early worsening of diabetic retinopathy in the Diabetes Control and Complications Trial.

Authors: 
Journal:  Arch Ophthalmol       Date:  1998-07

5.  Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation.

Authors:  K G Alberti; P Z Zimmet
Journal:  Diabet Med       Date:  1998-07       Impact factor: 4.359

6.  Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). UK Prospective Diabetes Study (UKPDS) Group.

Authors: 
Journal:  Lancet       Date:  1998-09-12       Impact factor: 79.321

7.  Glycemic Variation and Cardiovascular Risk in the Veterans Affairs Diabetes Trial.

Authors:  Jin J Zhou; Dawn C Schwenke; Gideon Bahn; Peter Reaven
Journal:  Diabetes Care       Date:  2018-08-06       Impact factor: 19.112

8.  Follow-up of blood glucose distribution characteristics in a health examination population in Chengdu from 2010 to 2016.

Authors:  Yuting Wang; Wangdong Xu; Qiongying Zhang; Ting Bao; Hanwei Yang; Wenxia Huang; Huairong Tang
Journal:  Medicine (Baltimore)       Date:  2018-02       Impact factor: 1.889

9.  Day-to-day fasting self-monitored blood glucose variability is associated with risk of hypoglycaemia in insulin-treated patients with type 1 and type 2 diabetes: A post hoc analysis of the SWITCH Trials.

Authors:  J Hans DeVries; Timothy S Bailey; Anuj Bhargava; Gregg Gerety; Janusz Gumprecht; Simon Heller; Wendy Lane; Carol H Wysham; Bernard Zinman; Britta A Bak; Elise Hachmann-Nielsen; Athena Philis-Tsimikas
Journal:  Diabetes Obes Metab       Date:  2018-11-26       Impact factor: 6.577

10.  Influence of social determinants, diabetes knowledge, health behaviors, and glycemic control in type 2 diabetes: an analysis from real-world evidence.

Authors:  Rubén Silva-Tinoco; Teresa Cuatecontzi-Xochitiotzi; Viridiana De la Torre-Saldaña; Enrique León-García; Javier Serna-Alvarado; Arturo Orea-Tejeda; Lilia Castillo-Martínez; Juan G Gay; David Cantú-de-León; Diddier Prada
Journal:  BMC Endocr Disord       Date:  2020-08-26       Impact factor: 2.763

View more
  1 in total

1.  Postprandial Glycemic and Insulinemic Response by a Brewer's Spent Grain Extract-Based Food Supplement in Subjects with Slightly Impaired Glucose Tolerance: A Monocentric, Randomized, Cross-Over, Double-Blind, Placebo-Controlled Clinical Trial.

Authors:  Hammad Ullah; Cristina Esposito; Roberto Piccinocchi; Lorenza Francesca De Lellis; Cristina Santarcangelo; Alessandro Di Minno; Alessandra Baldi; Daniele Giuseppe Buccato; Ayesha Khan; Gaetano Piccinocchi; Roberto Sacchi; Maria Daglia
Journal:  Nutrients       Date:  2022-09-21       Impact factor: 6.706

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.