In 2014, the World Health Organization reported 422 million cases of diabetes (also known as diabetes mellitus) worldwide, a nearly 400% increase from 108 million cases in 1980 (World Health Organization 2021). Of those cases, over 95% were type-2 diabetes, the form of diabetes that is characterized by an inability to produce enough insulin or the body being unresponsive to it. Insulin is vital for handling the transfer of glucose in the bloodstream into cells for production of energy, hence why the main symptom and instigator of diabetes’s fatal consequences is high blood sugar. Another widespread health issue is depression, a mental disorder affecting 280 million across all age ranges. Depression’s symptoms include feeling sad or hopeless, lacking energy and motivation to work and do even simple tasks, and thinking about suicide among many other symptoms (World Health Organization 2021).
Both diabetes and depression are already impacting millions today, but there has also been a rising trend in both for past decades and no foreseeable end to their momentum for the future. However, scientists have been noticing a connection between these two issues, and an observational study published by Anantha Eashwar V. M., Gopalakrishnan S., and Umadevi R. in the International Journal of Community Medicine and Public Health in 2017 sought to investigate this connection further through its two goals: firstly, to determine how frequently people with type-2 diabetes mellitus (T2DM) had depression, and secondly, to provide evidence for the relationship between depression severity and glycemic control (Eashwar et al. 2017, 3400). Glycemic control can be explained as the regulation of a person’s blood sugar levels; a diabetic’s control is worse than the average non-diabetic’s due to a constant excess of glucose in the bloodstream.
The study was conducted relatively recent from December 2015 to June 2016 at an urban health training center (UHTC) owned by Sree Balaji Medical College and Hospital and located in Anakaputhur, Chennai, Tamil Nadu, India. It was approved by the Ethics Committee of Sree Balaji Medical College and Hospital and established a set of criteria for participants: only individuals who had been diagnosed with T2DM for at least six months, were eighteen years or older, and had no psychiatric illness other than depression could participate in the study (Eashwar et al. 2017, 3401). Eashwar et al. obtained informed consent from the 300 T2DM hospital patients that participated in the study to use and publish relevant parts of their health records and demographic information. Additionally, patients provided description about the treatments they were receiving for T2DM so that results could be blocked (i.e. patients’ results were sorted into categories based on shared characteristics) for a nuanced view of how individual traits and circumstances affected the relationship between diabetes and depression.
To measure the first variable, glycemic control, the study required patients take the fasting blood sugar (FBS) test and also retrospectively gathered previous test results from the past three months for comparison. Fasting blood sugar is a test to measure blood sugar after 8 to 12 hours of not consuming food; 99 mg/dl or lower is normal, 100-125 mg/dl indicates prediabetes, and 126 mg/dl or above is an abnormally high blood sugar and a sign of diabetes (Cleveland Clinic 2020). To measure the presence of depression and its severity, the study utilized the Patient Health Questionnaire-9 (PHQ-9) for depression and a fasting blood test (FBS) for glycemic control. PHQ-9 is a self-administered diagnostic test that asks questions with a number line answer range of 0 to 3 and totals each question for a score of 0 to 27, with a higher score signifying worse depression . Scores assign the patient one of the following: no depression, mild, moderate, moderately severe, or severe. The design of Eashwar et al.’s study is well-documented and the tools it uses for measuring variables are utilized commonly throughout the medical field and have been tested for reliability (Kroenke et al. 2001).
Depression was found in 39.7% of subjects in this Indian study, showing that the occurrence of depression is high in diabetics. To present all of the results transparently, the study included several tables, including one that categorized participants with depression by age, education, gender, occupation, T2DM treatments, and other factors to demonstrate that depression prevalence varied between these more specific groups. Notably, females had higher depression rates than males (61.3% to 38.7%) and illiterates had higher depression than groups with more education, hinting that, while depression is common for many with diabetes, there are certain groups more impacted.
For the study’s second purpose, it was discovered that worse glycemic control, measured by higher FBS levels, was associated with more severe depression. As shown in the table below taken from Eashwar et al.’s study, people with depression were more likely to have higher FBS levels (Eashwar et al. 2017, 3401). With the increase in depression severity, the ratio of high >125 mg/dl FBS to the normal 70-125 mg/dl displays a substantial increase from 49:142 to 5:3, consistent within each successive level of depression severity. This signifies a positive correlation between worse blood sugar control and depression. An article on Nature titled “The vicious cycle of depression and obesity” provides a grave explanation for this relationship, reasoning that cytokines, a protein that is heavily associated with depression, can cause insulin resistance to develop (Plackett 2022). From insulin resistance, there is an increased risk of diabetes and obesity, and a consequence of obesity is chronic inflammation which triggers continued production of cytokines, hence why Hubertus Himmerich, a psychiatrist at King’s College London, has called the link between depression and diabetes a vicious cycle in which the two problems continually amplify each other.
Adjacent studies such as a survey in 2006 of 18,804 diabetics done by Chaoyang Li, Earl S Ford, Tara W Strine, and Ali H Mokdad in America have concluded similar rates of depression in people with T2DM (Li et al. 2008). The aggregate estimate for individuals who filled out the PHQ-8, an older version of the PHQ-9, were found to have a 26.1% occurrence of depression. Interestingly, in the American study’s results, the authors highlighted how different races had a stark difference in depression prevalence: Asians had a far below average 1.1% prevalence while American Indians and Native Alaskans were above at 27.8%, suggesting that there are factors other than diabetes that play a significant role in depression. This result reveals a limitation to Eashwar et al.’s study, because while its design is credible, there is a lack of diversity in study participants that restricts how the study results can be applied to populations outside of the studied group in India.
What is clear from these studies on diabetes and depression as a whole is that there is undoubtedly an association between depression and diabetes that appears to be universal despite large variations depending on personal factors. The fluctuations in the American study results when considered with racial blocking shows that, in the future, follow-up studies would benefit from a less homogeneous and larger study population, because the results would be more reliably applied to the general world population. Another modification to further studies addressed by Eashwar et al. was measuring glycemic control using the HbA1C test rather than measuring FBS, since HbA1C is able to provide a more accurate average of glycemic values over the course of three months (Eashwar et al. 2017, 3401). The study points out that, while FBS is reliable for describing the association between diabetes and depression, access to the better HbA1C technology would provide closer detail. As the knowledge base of the relationship between depression and T2DM grows in volume and specificity, there is hope in the future for the development of countermeasures to these two interconnected epidemics—perhaps ones that can target or prevent both at once and bring an end to their advance.
References:
Cleveland Clinic. 2020. Fasting blood sugar: screening test for diabetes. Cleveland Clinic. https://my.clevelandclinic.org/health/diagnostics/21952-fasting-blood-sugar.
Eashwar A, Gopalakrishnan S, Umadevi R. 2017 Sep. Prevalence of depression in patients with type 2 diabetes mellitus and its association with fasting blood sugar levels, in an urban area of Kancheepuram district, Tamil Nadu. International Journal of Community Medicine and Public Health. 4(9):3399-3406. doi: 10.18203/2394-6040.ijcmph20173852. https://www.researchgate.net/publication/319258640_Prevalence_of_depression_in_patients_with_type_2_diabetes_mellitus_and_its_association_with_fasting_blood_sugar_levels_in_an_urban_area_of_Kancheepuram_district_Tamil_Nadu.
Kroenke K, Spitzer RL, Williams JBW. 2001. The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine. 16(9):606–613. doi:10.1046/j.1525-1497.2001.016009606.x.
Li C, Ford ES, Strine TW, Mokdad AH. 2007. Prevalence of depression among U.S. adults with diabetes: findings from the 2006 behavioral risk factor surveillance system. Diabetes Care. 31(1):105–107. doi:10.2337/dc07-1154. https://diabetesjournals.org/care/article/31/1/105/27823/Prevalence-of-Depression-Among-U-S-Adults-With.
Plackett B. 2022. The vicious cycle of depression and obesity. Nature. 608(7924):S42–S43. doi:10.1038/d41586-022-02207-8. https://www.nature.com/articles/d41586-022-02207-8.
World Health Organization. 2021 Sep 13. Depression. World Health https://www.who.int/news-room/fact-sheets/detail/depression.
World Health Organization. 2022 Sep 16. Diabetes. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/diabetes.
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Technology Networks. 2021 Sep 20. Early detection of autoantibodies in type 1 diabetes mellitus and treatment possibilities beyond insulin. Diagnostics from Technology Networks. https://www.technologynetworks.com/diagnostics/blog/early-detection-of-autoantibodies-in-type-1-diabetes-mellitus-and-treatment-possibilities-beyond-353685.