Article Text
Abstract
Objective Long-term glycemic variability has recently been recognized as another risk factor for future adverse health outcomes. We aimed to evaluate the risk of gestational diabetes mellitus (GDM) according to the prepregnancy long-term fasting plasma glucose (FPG) variability.
Research design and methods A total of 164 053 women who delivered their first baby between January 1, 2012 and December 31, 2015, were selected from the Korean National Health Insurance data. All women underwent at least three national health screening examinations, and the last examination should be conducted within 2 years before their first delivery. GDM was defined as the presence of more than four times of claim of GDM (International Classification of Disease, 10th Revision (ICD-10) O24.4 and O24.9) or prescription of insulin under the ICD-code of GDM. FPG variability was assessed by variability independent of the mean (FPG-VIM), coefficient of variation, SD, and average successive variability.
Results Among the 164 053 women, GDM developed in 6627 (4.04%). Those in the higher quartiles of FPG-VIM showed a stepwise increased risk of GDM. In fully adjusted model, the ORs for GDM was 1.22 (95% CI 1.14 to 1.31) in women with the highest FPG-VIM quartile compared with those in the lowest quartile. The risk for GDM requiring insulin therapy was 48% increase in women in the highest quartile of FPG-VIM compared with those in the lowest quartile, while that for GDM not requiring insulin therapy was 19% increase. The association between high FPG variability and the risk of GDM was intensified in the obese and aged more than 35 years women.
Conclusions Increased FPG variability in the prepregnancy state is associated with the risk of GDM independent of confounding factors. Therefore, prepregnancy FPG variability might be a surrogate marker of the risk of GDM.
- gestational diabetes mellitus
- glucose
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
Footnotes
Contributors JAK, SHB, KMC, GJC, and HJY conceived and designed the study and performed the analyses. JK, EN, and SYH conducted the statistical analysis. JK, EN, GJC, HJY, and SYH acquired the data. JAK, ER, SH, YBL, and HJY wrote the first draft of the manuscript. All authors interpreted the data, contributed to the writing of the manuscript, and read and approved the final version. GJC and HJY are responsible for the integrity of the work as a whole.
Funding This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B07047587) and the grant of the Establish R&D Platform Project through the Korea University Medical Center and Korea University Guro Hospital, funded by the Korea University Guro Hospital (Grant number: O1903761).
Disclaimer The funders had no role in the study design, data collection, analysis, and interpretation, decision to publish, or preparation of the manuscript.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval The study was approved by the Korea University institutional review board (2019GR0106).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information. Additional data are available on reasonable request.