SpringerLink
Log in

What makes poor diabetic control worse? A cross-sectional survey of biopsychosocial factors among patients with poorly controlled diabetes mellitus in Malaysia

  • Original Article
  • Published:
International Journal of Diabetes in Develo** Countries Aims and scope Submit manuscript

Abstract

Background

Diabetes mellitus (DM) is an increasingly prevalent condition that is associated with significant complications, especially when glycemic control is poor. This study explored what biopsychosocial factors are associated with poor vs. very poor glycemic control among Malaysian patients with sub-optimal glycated hemoglobin (HbA1c) levels.

Methods

This cross-sectional study recruited diabetic patients with poor glycemic control (HbA1c ≥ 7.0%) from the Universiti Kebangsaan Malaysia Medical Centre (UKMMC), Malaysia. The Generalized Anxiety Disorder (GAD)-7, Beck Depression Inventory (BDI) and Big Five Inventory (BFI) questionnaires assessed for anxiety, depression and personality traits, respectively. Multivariate logistic regression analysis was performed to evaluate associations between biopsychosocial factors and the occurrence of poor vs. very poor glycemic control, using the median HbA1c level of the study sample as the cutoff point.

Results

The median age of participants (n = 176) was 61.5 years. The median duration of diabetes was 15.0 years, and the median HbA1c level was 8.5%. Very poor control of diabetes (HbA1c > 8.5%) was associated with younger age, single status, retirement, hypertension and dyslipidemia in bivariate analysis. However, in the final multivariate regression model, only agreeableness was associated with very poor glycemic control (p < 0.01). There were no differences in depression and anxiety scores between the poor and very poor glycemic control groups.

Discussion

This study suggests that the agreeableness personality trait may be associated with very poor glycemic control. The effects of personality traits on glycemic control might be influenced by sociocultural factors. Further investigations are needed to provide a better understanding of this area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data Availability

The data used to support the findings of this study is available upon request from the corresponding author.

References

  1. Cho N, Shaw J, Karuranga S, Huang Y, da Rocha Fernandes J, Ohlrogge A, et al. IDF Diabetes Atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018;138:271–81.

    Article  CAS  Google Scholar 

  2. Roglic G. WHO Global report on diabetes: a summary. Int J Non-Commun Dis. 2016;1:3–8.

    Article  Google Scholar 

  3. Ducat L, Philipson LH, Anderson BJ. The mental health comorbidities of diabetes. JAMA. 2014;312:691–2.

    Article  CAS  Google Scholar 

  4. Keen AJ. The nature and impact of poor emotional wellbeing in people with diabetes. Pract Diabetes. 2019;36:132–5.

    Article  Google Scholar 

  5. American Diabetes Association. Standards of Medical Care in Diabetes—2020. Diabetes Care. 2020;43(Suppl. 1):S1–S212.

    Google Scholar 

  6. Papelbaum M, Moreira RO, Coutinho W, Kupfer R, Zagury L, Freitas S, et al. Depression, glycemic control and type 2 diabetes. Diabetol Metab Syndr. 2011;3(1):26.

    Article  CAS  Google Scholar 

  7. Eren I, Erdi O, Ozcankaya R. Relationship between blood glucose control and psychiatric disorders in type II diabetic patients. Turk Psikiyatri Derg. 2003;14(3):184–91.

    PubMed  Google Scholar 

  8. Richardson LK, Egede LE, Mueller M, Echols CL, Gebregziabher M. Longitudinal effects of depression on glycemic control in veterans with Type 2 diabetes. Gen Hosp Psychiatry. 2008;30(6):509–14.

    Article  Google Scholar 

  9. Lane JD, McCaskill CC, Williams PG, Parekh PI, Feinglos MN, Surwit RS. Personality correlates of glycemic control in type 2 diabetes. Diabetes Care. 2000;23(9):1321–5.

    Article  CAS  Google Scholar 

  10. Skinner TC, Bruce DG, Davis TME, Davis WA. Personality traits, self-care behaviours and glycaemic control in Type 2 diabetes: the Fremantle Diabetes Study Phase II. Diabet Med. 2014;31(4):487–92.

    Article  CAS  Google Scholar 

  11. Phillips AS, Guarnaccia CA. The five-factor model of personality and self-reported versus biomarker diabetic control. J Health Psychol. 2016;21(10):2328–38.

    Article  Google Scholar 

  12. Stratton IM, Adler AI, Neil HAW, Matthews DR, Manley SE, Cull CA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. Br Med J. 2000;321(7258):405–12.

    Article  CAS  Google Scholar 

  13. Stettler C, Allemann S, Jüni P, Cull CA, Holman RR, Egger M, et al. Glycemic control and macrovascular disease in types 1 and 2 diabetes mellitus: meta-analysis of randomized trials. Am Heart J. 2006;152(1):27–38.

    Article  CAS  Google Scholar 

  14. Goldberg LR. An alternative “description of personality”: the big-five factor structure. J Pers Soc Psychol. 1990;59(6):1216–29.

    Article  CAS  Google Scholar 

  15. Soto CJ, John OP. Ten facet scales for the Big Five Inventory: convergence with NEO PI-R facets, self-peer agreement, and discriminant validity. J Res Pers. 2009;43(1):84–90.

    Article  Google Scholar 

  16. Muhamad H, Roodenburg J, Moore DW. The adaptation of the Big Five Inventory in measuring Malaysian youths’ personality traits. Int J Adv Appl Sci. 2018;5(7):8–14.

    Article  Google Scholar 

  17. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–7.

    Article  Google Scholar 

  18. Rutter LA, Brown TA. Psychometric properties of the generalized anxiety disorder scale-7 (GAD-7) in outpatients with anxiety and mood disorders. J Psychopathol Behav Assess. 2017;39(1):140–6.

    Article  Google Scholar 

  19. Sidik SM, Arroll B, Goodyear-Smith F. Validation of the GAD-7 (Malay version) among women attending a primary care clinic in Malaysia. J Prim Health Care. 2012;4(1):5–11.

    Article  Google Scholar 

  20. Beck AT, Steer RA, Brown GK. Beck depression inventory-II. San Antonio: Psychological Corporation; 1996.

    Google Scholar 

  21. Muhktar F, Oei TP. Exploratory and confirmatory factor validation and psychometric properties of the Beck Depression Inventory for Malays (BDI-Malay) in Malaysia. Mal J Psych. 2008;17(1):1–13.

  22. van Ginkel JR, Linting M, Rippe RCA, van der Voort A. Rebutting existing misconceptions about multiple imputation as a method for handling missing data. J Pers Assess. 2020;102(3):297–308.

    Article  Google Scholar 

  23. Meeyai S. Logistic regression with missing data: a comparison of handling methods, and effects of percent missing values. J Traffic Logist Eng. 2016;4(2):128–34.

    Google Scholar 

  24. Heisler M, Faul JD, Hayward RA, Langa KM, Blaum C, Weir D. Mechanisms for racial and ethnic disparities in glycemic control in middle-aged and older Americans in the health and retirement study. Arch Intern Med. 2007;167(17):1853–60.

    Article  Google Scholar 

  25. El-Kebbi IM, Cook CB, Ziemer DC, Miller CD, Gallina DL, Phillips LS. Association of younger age with poor glycemic control and obesity in urban African Americans with type 2 diabetes. Arch Intern Med. 2003;163(1):69–75.

    Article  Google Scholar 

  26. Toh MPHS, Wu CX, Leong HSS. Association of younger age with poor glycemic and cholesterol control in Asians with type 2 Diabetes Mellitus in Singapore. J Endocrinol Metab. 2011;1(1):27–37.

    CAS  Google Scholar 

  27. Ohishi M. Hypertension with diabetes mellitus: physiology and pathology. Hypertens Res. 2018;41(6):389–93.

    Article  Google Scholar 

  28. Ginsberg HN, MacCallum PR. The obesity, metabolic syndrome, and type 2 diabetes mellitus pandemic: Part I. Increased cardiovascular disease risk and the importance of atherogenic dyslipidemia in persons with the metabolic syndrome and type 2 diabetes mellitus. J Cardiometab Syndr. 2009;4(2):113–9.

    Article  Google Scholar 

  29. Krauss RM. Lipids and lipoproteins in patients with type 2 diabetes. Diabetes Care. 2004;27(6):1496–504.

    Article  CAS  Google Scholar 

  30. Wu L, Parhofer KG. Diabetic dyslipidemia. Metab. 2014;63(12):1469–79.

    Article  CAS  Google Scholar 

  31. Waller D, Johnston C, Molyneaux L, Brown-Singh L, Hatherly K, Smith L, et al. Glycemic control and blood glucose monitoring over time in a sample of young australians with type 1 diabetes: the role of personality. Diabetes Care. 2013;36(10):2968–73.

    Article  Google Scholar 

  32. Kim BS, Hong S. A psychometric revision of the Asian Values Scale using the Rasch model. Meas Eval Couns Dev. 2004;37(1):15–27.

    Article  Google Scholar 

  33. Khor G-L. Food availability and the rising obesity prevalence in Malaysia. IeJSME. 2012;6(suppl 1):S61–S8.

    Google Scholar 

  34. Walker RJ, Garacci E, Palatnik A, Ozieh MN, Egede LE. The longitudinal influence of social determinants of health on glycemic control in elderly adults with diabetes. Diabetes Care. 2020;43(4):759–66.

    Article  Google Scholar 

  35. Walker RJ, Garacci E, Campbell JA, Egede LE. The influence of daily stress on glycemic control and mortality in adults with diabetes. J Behav Med. 2019. https://doi.org/10.1007/s10865-019-00109-1.

  36. Stuckey HL, Vallis M, Kovacs Burns K, Mullan-Jensen CB, Reading JM, Kalra S, et al. “I do my best to listen to patients”: qualitative insights into DAWN2 (Diabetes Psychosocial Care From the Perspective of Health Care Professionals in the Second Diabetes Attitudes, Wishes and Needs Study). Clin Ther. 2015;37(9):1986–1998.e12.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dr. Nurul Hazwani Hatta, Dr. Puteri Arnawati and Dr. Amelia Yasmin Zulkifli for their involvement in data collection for this study.

Funding

This work was funded by the Young Lecturers Incentive Grant (GGPM-2019-024) from the Research University Fund of the National University of Malaysia, as well as the University of Toronto Comprehensible Research Experience for Medical Students (CREMS) and Medial Alumni Association (MAA).

Author information

Authors and Affiliations

  1. Department of Psychiatry, Universiti Kebangsaan Malaysia Medical Centre (UKMMC), Jalan Yaacob Latif, Bandar Tun Razak, Cheras, Wilayah Persekutuan, 56000, Kuala Lumpur, Malaysia

    Luke Sy-Cherng Woon & Hatta Sidi

  2. Faculty of Medicine, University of Toronto, 1 King’s College Circle, Toronto, ON, M5S 1A8, Canada

    Roslyn Laurie Mainland, Emily Samantha Kaunismaa & Paula Junggar Gosse

  3. Centre for Addiction and Mental Health, Faculty of Medicine, University of Toronto, 1 King’s College Circle, Toronto, ON, M5S 1A8, Canada

    Arun Ravindran

Authors
  1. Luke Sy-Cherng Woon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roslyn Laurie Mainland
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Emily Samantha Kaunismaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Paula Junggar Gosse
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Arun Ravindran
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hatta Sidi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Paula Junggar Gosse, Emily Samantha Kaunismaa, Roslyn Laurie Mainland and Luke Sy-Cherng Woon. The first draft of the manuscript was written by Luke Sy-Cherng Woon and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hatta Sidi.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethics approval

The questionnaire and methodology for this study were approved by the Research Ethics Committee of the Faculty of Medicine, Universiti Kebangsaan Malaysia (Ethics approval number: UKM FPR.SPI 800-2/28/166/FF-2019-342).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent to publish

Not applicable.

Code availability

Not applicable.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Woon, L.SC., Mainland, R.L., Kaunismaa, E.S. et al. What makes poor diabetic control worse? A cross-sectional survey of biopsychosocial factors among patients with poorly controlled diabetes mellitus in Malaysia. Int J Diabetes Dev Ctries 41, 476–483 (2021). https://doi.org/10.1007/s13410-020-00918-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13410-020-00918-0

Keywords

Search

Navigation