BACKGROUND: Diabetes is a chronic condition that significantly impacts quality of life. Poor glycemic control is associated with more diabetes complications, depression, and worse quality of life. The impact of glycemic variability on mood and quality of life has not been studied. METHODS: A descriptive exploratory design was used. Twenty-three women with type 2 diabetes wore a continuous glucose monitoring system for 72 h and completed a series of questionnaires. Measurements included (1) glycemic control shown by glycated hemoglobin and 24-h mean glucose, (2) glycemic variability shown by 24-h SD of the glucose readings, continuous overall net glycemic action (CONGA), and Fourier statistical models to generate smoothed curves to assess rate of change defined as "energy," and (3) mood (depression, anxiety, anger) and quality of life by questionnaires. RESULTS: Women with diabetes and co-morbid depression had higher anxiety, more anger, and lower quality of life than those without depression. Certain glycemic variability measures were associated with mood and quality of life. The 24-h SD of the glucose readings and the CONGA measures were significantly associated with health-related quality of life after adjusting for age and weight. Fourier models indicated that certain energy components were significantly associated with depression, trait anxiety, and overall quality of life. Finally, subjects with higher trait anxiety tended to have steeper glucose excursions. CONCLUSIONS: Data suggest that greater glycemic variability may be associated with lower quality of life and negative moods. Implications include replication of the study in a larger sample for the assessment of blood glucose fluctuations as they impact mood and quality of life.
BACKGROUND:Diabetes is a chronic condition that significantly impacts quality of life. Poor glycemic control is associated with more diabetes complications, depression, and worse quality of life. The impact of glycemic variability on mood and quality of life has not been studied. METHODS: A descriptive exploratory design was used. Twenty-three women with type 2 diabetes wore a continuous glucose monitoring system for 72 h and completed a series of questionnaires. Measurements included (1) glycemic control shown by glycated hemoglobin and 24-h mean glucose, (2) glycemic variability shown by 24-h SD of the glucose readings, continuous overall net glycemic action (CONGA), and Fourier statistical models to generate smoothed curves to assess rate of change defined as "energy," and (3) mood (depression, anxiety, anger) and quality of life by questionnaires. RESULTS:Women with diabetes and co-morbid depression had higher anxiety, more anger, and lower quality of life than those without depression. Certain glycemic variability measures were associated with mood and quality of life. The 24-h SD of the glucose readings and the CONGA measures were significantly associated with health-related quality of life after adjusting for age and weight. Fourier models indicated that certain energy components were significantly associated with depression, trait anxiety, and overall quality of life. Finally, subjects with higher trait anxiety tended to have steeper glucose excursions. CONCLUSIONS: Data suggest that greater glycemic variability may be associated with lower quality of life and negative moods. Implications include replication of the study in a larger sample for the assessment of blood glucose fluctuations as they impact mood and quality of life.
Authors: M A Van Tilburg; C C McCaskill; J D Lane; C L Edwards; A Bethel; M N Feinglos; R S Surwit Journal: Psychosom Med Date: 2001 Jul-Aug Impact factor: 4.312
Authors: Jennifer Zink; Michele Nicolo; Kellie Imm; Shayan Ebrahimian; Qihan Yu; Kyuwan Lee; Kaylie Zapanta; Jimi Huh; Genevieve F Dunton; Michael I Goran; Kathleen A Page; Christina M Dieli-Conwright; Britni R Belcher Journal: J Psychosom Res Date: 2020-05-15 Impact factor: 3.006
Authors: Thomas A Peyser; Andrew K Balo; Bruce A Buckingham; Irl B Hirsch; Arturo Garcia Journal: Diabetes Technol Ther Date: 2017-12-11 Impact factor: 6.118
Authors: Julie Wagner; Stephen Armeli; Howard Tennen; Angela Bermudez-Millan; Howard Wolpert; Rafael Pérez-Escamilla Journal: Psychosom Med Date: 2017-09 Impact factor: 4.312
Authors: Chinmay Manohar; Derek T O'Keeffe; Ling Hinshaw; Ravi Lingineni; Shelly K McCrady-Spitzer; James A Levine; Rickey E Carter; Ananda Basu; Yogish C Kudva Journal: Diabetes Technol Ther Date: 2013-08-12 Impact factor: 6.118
Authors: Monika Reddy; Ian F Godsland; Katharine D Barnard; Pau Herrero; Pantelis Georgiou; Hazel Thomson; Desmond G Johnston; Nick S Oliver Journal: J Diabetes Sci Technol Date: 2015-08-18