|Year : 2016 | Volume
| Issue : 2 | Page : 117-122
Prevalence and clinical correlation study of impaired glucose tolerance in major depressive disorder patients
Ajay Halder1, Siddhartha Sankar Saha2, Dipanwita Pandit3, Abhinanda Biswas4
1 Department of Psychiatry, Institute of Post Graduate Medical Education and Research Hospital, Kolkata, West Bengal, India
2 Department of Psychiatry, Murshidabad Medical College and Hospital, Berhampore, West Bengal, India
3 Department of Community Medicine, Medical College, Kolkata, West Bengal, India
4 Department of General Medicine, ESI Hospital, Belur, West Bengal, India
|Date of Web Publication||17-Mar-2016|
Dr. Ajay Halder
Puspak Apartment, GR-FR; FL-A, 14/17A, East Mall Road, Kolkata - 700 080, West Bengal
Source of Support: None, Conflict of Interest: None
Aims: To find the prevalence of glycemic impairment during the first visit of patients diagnosed with major depressive disorders (MDDs). To identify whether subjects with glycemic impairment have more depression at baseline. To see whether final depression outcome is influenced by baseline glycemic control status. Subjects and Methods: The study was conducted in the Department of Psychiatry, Institute of Postgraduate Medical Education and Research, Kolkata with the collaboration of Department of Biochemistry, Bangur Institute of Neurosciences, Kolkata. This is a hospital-based cohort study. One hundred and two eligible MDD patients were selected as per inclusion and exclusion criteria. Fasting blood sugar, postprandial blood sugar, glycated hemoglobin (HbA1C), etc., were estimated and depression rating scale was applied on them at the first visit. These participants were again evaluated by depression rating scale after 3 months treatment of depression and blood was collected for HbA1C estimation. Statistical analysis was done with the help of (IBM) Statistical Package for Social Science-13. Results: Sixteen percentage patients had impaired glucose tolerance test. The baseline depression score was <13 for 6 percent, and ≥18 for 78 percent of the participating subjects. After 3 months of treatment, the score was <13 for 20 percent and ≥18 for 35 percent. The baseline depression score was found to be a strong predictor of prognosis even after controlling for all the indicators of glucose metabolism. Conclusions: Persons having similar depression level at presentation had a better prognosis if they had good glycemic control at baseline.
Keywords: Diabetes mellitus, impaired glucose tolerance, major depressive disorder, patients
|How to cite this article:|
Halder A, Saha SS, Pandit D, Biswas A. Prevalence and clinical correlation study of impaired glucose tolerance in major depressive disorder patients. Int J Educ Psychol Res 2016;2:117-22
|How to cite this URL:|
Halder A, Saha SS, Pandit D, Biswas A. Prevalence and clinical correlation study of impaired glucose tolerance in major depressive disorder patients. Int J Educ Psychol Res [serial online] 2016 [cited 2019 Nov 12];2:117-22. Available from: http://www.ijeprjournal.org/text.asp?2016/2/2/117/168509
| Introduction|| |
Diabetes and depression are both common conditions in today's society. There are currently about 200 million people with diabetes worldwide. If nothing is done to slow down the epidemic, the number will exceed 333 million by the year 2025. Moreover, an estimated 121 million people currently suffer from depression: Six percentage of men and 10 percent of women will experience a depressive episode in any given year.
There is ample evidence that diabetes and depression are associated. According to a recent meta-analysis, the prevalence of depression is doubled in individuals with Type 2 diabetes compared with those without diabetes. However, the temporal relationship between depression and Type 2 diabetes and their mechanism of action remained unclear. Depression is often regarded as a comorbid condition that results from the daily burden of having diabetes and/or its complications [Figure 1]. Interestingly, there are also indications that depression in turn is an independent risk factor for the development of Type 2 diabetes.,
The reason why depression and diabetes co-occur is not clear. Possible pathophysiological mechanisms underlying this association include disturbance of the hypothalamic-pituitary-adrenocortical axis or sympathetic nervous system,, and dysregulation of the immune system.
Impaired glucose tolerance and impaired fasting glucose
The Expert Committee recognized an intermediate group of subjects whose glucose levels, although not meeting criteria for diabetes, are nevertheless too high to be considered normal. This group is defined as having fasting plasma glucose (FPG) levels ≥100 mg/dl (5.6 mmol/L) but <126 mg/dl (7.0 mmol/L) or 2 h values in the oral glucose tolerance test (OGTT) of ≥140 mg/dl (7.8 mmol/L) but <200 mg/dl (11.1 mmol/L). Thus, FPG 100–125 mg/dl (5.6–6.9 mmol/L) = impaired fasting glucose (IFG); 2 h postload glucose 140–199 mg/dl (7.8–11.1 mmol/L) = impaired glucose tolerance (IGT); patients with IFG and/or IGT are now referred to as having “prediabetes” indicating the relatively high risk for development of diabetes in these patients.
Some use the term “increased risk for diabetes” (American Diabetes Association [ADA]) or “intermediate hyperglycemia” (WHO) rather than “prediabetes.” (Adapted from the ADA, 2007)
International variations in rates of depression in people with diabetes
In one of the few published studies of comorbid depression in the developing world, carried out in Bangladesh, Asghar et al. reported that nearly one-third (29 percent males, 30 percent females) of those with diabetes had clinically significant levels of depression, compared with only 6 percent of males and 15 percent of females without diabetes. In Pakistan, levels of depression have been reported to be lower, with prevalence rates of nearly 15 percent among those with diabetes compared to 5 percent among those without diabetes. Prevalence rates in Europe have been shown to vary although consistently higher in people with diabetes compared to those without., High rates of depression have also been observed in Australia in both individuals with Type 1 and 2 diabetes.
In the general population, risk factors for an initial depressive episode include gender, major stressful life events,,, and socioeconomic conditions. Maternal depression has been shown to increase the risk for depression in children and adolescents,, although this has not been confirmed in other studies. Low birth weight and fetal undernutrition have also been associated with both depression and diabetes., Other factors, including lifestyle and health behaviors, may also play a part in increasing risk for depression in people with diabetes.
Recurrence of depression is common in people with diabetes and episodes are likely to last longer.,,, Knowledge of having Type 2 diabetes, longer duration of diabetes,, more demanding regimens, low levels of daily activities,,, higher dependency, nutrition (e.g., low intake of omega-3 fatty acids), smoking, obesity, and perceived burden of diabetes , have all been postulated as risk factors, but the epidemiological evidence remains limited.
| Subjects and Methods|| |
- Age between 18 and 60 years
- Diagnostic and statistical manual of mental disorder-Fourth edition text revision (DSM-IV TR) diagnosed patients of major depressive disorder (MDD); first episode or not taking medicine for 1-month
- Body mass index (BMI)≥18.5 and <30.
- Presence of history of medical diseases like
- Coronary artery disease
- Diabetes mellitus
- Renal diseases
- Liver diseases
- Thyroid diseases.
- Other psychiatric disorder like past history of manic and hypomanic episode
- Female receiving oral hypoglycemic agents for other indication like-polycystic ovarian syndrome.
- DSMs fourth edition TR (APA, 2000)
- Hamilton rating scale for depression (Hamilton, 1960)
- Socioeconomic status scale.
Pareek and Trivedi scale for rural areas and Kuppuswamy's scale for urban areas were used.
Using purposive sampling technique attendees of psychiatry outpatient department of Institute of Postgraduate Medical Education and Research [IPGME and R], Kolkata was recruited for the study between February 2011 and January 2012 in following steps:
- One hundred and fifty persons who were diagnosed to have MDDs using DSM-IV were approached for the study. Sociodemographic data also collected in the same time using Kuppuswamy scale for urban and Pareek and Trivedi's scale for rural patients
- After being explained about the risk and benefit associated with the study in details in a language they understand properly, 130 patients provided informed consent mentioning their willingness for voluntary participation in the study
- Agreeing participants were asked to come on next morning after 8 h of fasting without altering their dietary habits. Around 8–30 am, 10 mL of blood was drawn from the cubital vein of each subject and collected in three separate vials: Ethylenediaminetetraacetic acid, Na-fluoride, and plain vial. Centrifugation, plasma separation, and analysis of blood samples were carried out in Department of Biochemistry. Application of HAM-D done thereafter and subjected to laboratory for testing HB%, urea, creatinine, lipid profile, thyroid function test, liver function tests, fasting, and postprandrial blood sugar test after taking 75 g oral glucose, glycated hemoglobin (HbA1C)
- Among 130 participants, 102 were found to be eligible for the study according to eligibility criteria and their laboratory test results. Ineligible subjects (diabetes, renal disease, liver diseases, thyroid diseases, cardiovascular diseases, etc.) were referred to concerned departments for their required treatment of their ailments
- These 102 eligible participants were again evaluated by HAM-D Scale after 3 months treatment for depression and blood was collected for HbA1C estimation. Two patients were absent during blood HbA1C estimation.
| Results|| |
[Table 2]a shows the mean HAM-D Score_3 of patient Group A was 16.37 ± 4.41 (standard deviation [SD]) whereas that of Group B was 13.86 ± 2.88 SD and difference was significant statistically (t = 1.719, P < 0.05).
[Table 3] shows the mean depression score at baseline in impaired OGTT patients was 21.75 ± 5.10 and 16.37 ± 4.41 at 3-month follow-up. On other hand, mean depression score at baseline in non-impaired OGTT was 19.72 ± 3.9 and 13.86 ± 2.88 at 3-month follow-up. The differences were statistically significant on ANOVA (P < 0.0462).
| Discussion|| |
One hundred and two eligible patients diagnosed with MDD as per DSM-IV TR attending Outpatient Department of Psychiatry, IPGME and R, Kolkata who gave consent were selected purposively for this study. The mean age of the participants was 34, and mean BMI was 21.62. Participants reported a mean period of 13.5 months as the duration of suffering from MDD. Based on the used scale, the mean depression score was 20 at baseline and 15 after 3 months of treatment. Mean HbA1C level was 5.27 at baseline and 5 after 3 months [Table 1]c and [Table 2]b. Among the participants, 55 percent were male, 75 percent married, 74 percent Hindu, 57 percent had high school or above level of education, 65 percent were from rural areas, 16 percent had IGT test, and 80 percent were middle-class people. The baseline depression score was <13 for 6 percent, and ≥18 for 78 percent of the participating subjects. After 3 months of treatment, the score was <13 for 20 percent and ≥18 for 35 percent. Over this period, 20 percent had little (<3), 45 percent had some extend and 35 percent had gross (≥7) decrease in depression score [Table 1]a and [Table 1]b. Compared to unmarried and urban residents, married and rural participants were more likely to have a higher level of depression at baseline. The baseline depression score was found to be a strong predictor of prognosis (measured by a decrease in the depression score) even after controlling for all the indicators of glucose metabolism. Better glucose tolerance was associated with better prognosis once the baseline depression score was held constant. Persons having similar depression level at presentation had a better prognosis if they had good glycemic control at baseline.
|Table 3: Repeated measure ANOVA showing comparison of baseline and 3 - month follow - up depression score between patients with impaired OGTT (n=16) and without impaired OGTT (n=84)|
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Based on Hamilton rating scale for depression, prevalence of severe depression at baseline in this study was found to be 78 percent followed by moderate depression being 15 percent and mild depression as 5 percent which is corroborative with other studies. In the present study, after adjusting for the glycemic index at baseline and change in the glycemic index over 3 months, no association was found between nonimpaired OGTT at baseline and decrease in depression score over 3 months. This association became significant when depression score at baseline was adjusted which might be indicating possible confounding by depression score affecting both nonimpaired OGTT at baseline and prognosis for depression.
We also could not find any association between change in the glycemic index over 3 months and prognosis for depression after controlling each clinical parameter affecting glucose metabolism which might be due to the possible issue of multicollinearity. HbA1C usually reflects average glucose level in an individual over a span of previous 4 weeks to 3 months and is widely used for estimating the effectiveness of medical therapy. Thus, change in the glycemic index over 3 months and glycemic index at baseline might not be different.
Research suggests that other factors including lifestyle and health behaviors may also play a part in increasing risk for depression in people with diabetes. However, the temporal association between these variables remains unclear and requires further investigation. In our study, we did not find any associations between the decrease in depression score over 3 months and patient sociodemographic characteristics. But extrapolation of these findings beyond the present study should be done with caution as this study was conducted among a special group of patients suffering from MDDs attending a Tertiary Care Hospital in Kolkata which might not be a generalized as this is not a representative sample of patients with depressive disorders.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047-53.
Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet 1997;349:1498-504.
Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care 2001;24:1069-78.
Musselman DL, Betan E, Larsen H, Phillips LS. Relationship of depression to diabetes types 1 and 2: epidemiology, biology, and treatment. Biol Psychiatry 2003;54:317-29.
Talbot F, Nouwen A. A review of the relationship between depression and diabetes in adults: is there a link? Diabetes Care 2000;23:1556-62.
Björntorp P, Holm G, Rosmond R. Hypothalamic arousal, insulin resistance and Type 2 diabetes mellitus. Diabet Med 1999;16:373-83.
Björntorp P. Do stress reactions cause abdominal obesity and comorbidities? Obes Rev 2001;2:73-86.
Kiecolt-Glaser JK, Glaser R. Depression and immune function: central pathways to morbidity and mortality. J Psychosom Res 2002;53:873-6.
Asghar S, Hussain A, Ali SM, Khan AK, Magnusson A. Prevalence of depression and diabetes: a population-based study from rural Bangladesh. Diabet Med 2007;24:872-7.
Zahid N, Asghar S, Claussen B, Hussain A. Depression and diabetes in a rural community in Pakistan. Diabetes Res Clin Pract 2008;79:124-7.
Pouwer F, Skinner TC, Pibernik-Okanovic M, Beekman AT, Cradock S, Szabo S, et al
. Serious diabetes-specific emotional problems and depression in a Croatian-Dutch-English Survey from the European Depression in Diabetes [EDID] Research Consortium. Diabetes Res Clin Pract 2005;70:166-73.
de Jonge P, Roy JF, Saz P, Marcos G, Lobo A, ZARADEMP Investigators. Prevalent and incident depression in community-dwelling elderly persons with diabetes mellitus: Results from the ZARADEMP project. Diabetologia 2006;49:2627-33.
Hislop AL, Fegan PG, Schlaeppi MJ, Duck M, Yeap BB. Prevalence and associations of psychological distress in young adults with Type 1 diabetes. Diabet Med 2008;25:91-6.
Brown GW, Bifulco A, Harris TO. Life events, vulnerability and onset of depression: some refinements. Br J Psychiatry 1987;150:30-42.
Kessler RC. The effects of stressful life events on depression. Annu Rev Psychol 1997;48:191-214.
Kendler KS, Karkowski LM, Prescott CA. Causal relationship between stressful life events and the onset of major depression. Am J Psychiatry 1999;156:837-41.
Carvalhais SM, Lima-Costa MF, Peixoto SV, Firmo JO, Castro-Costa E, Uchoa E. The influence of socio-economic conditions on the prevalence of depressive symptoms and its covariates in an elderly population with slight income differences: The Bambuí Health and Aging Study (BHAS). Int J Soc Psychiatry 2008;54:447-56.
Pilowsky DJ, Wickramaratne PJ, Rush AJ, Hughes CW, Garber J, Malloy E, et al.
Children of currently depressed mothers: a STAR*D ancillary study. J Clin Psychiatry 2006;67:126-36.
Jaser SS, Whittemore R, Ambrosino JM, Lindemann E, Grey M. Mediators of depressive symptoms in children with type 1 diabetes and their mothers. J Pediatr Psychol 2008;33:509-19.
Thompson C, Syddall H, Rodin I, Osmond C, Barker DJ. Birth weight and the risk of depressive disorder in late life. Br J Psychiatry 2001;179:450-5.
Paile-Hyvärinen M, Räikkönen K, Forsén T, Kajantie E, Ylihärsilä H, Salonen MK, et al
. Depression and its association with diabetes, cardiovascular disease, and birth weight. Ann Med 2007;39:634-40.
Kovacs M, Obrosky DS, Goldston D, Drash A. Major depressive disorder in youths with IDDM. A controlled prospective study of course and outcome. Diabetes Care 1997;20:45-51.
Peyrot M, Rubin RR. Persistence of depressive symptoms in diabetic adults. Diabetes Care 1999;22:448-52.
Knol MJ, Heerdink ER, Egberts AC, Geerlings MI, Gorter KJ, Numans ME, et al.
Depressive symptoms in subjects with diagnosed and undiagnosed type 2 diabetes. Psychosom Med 2007;69:300-5.
Palinkas LA, Barrett-Connor E, Wingard DL. Type 2 diabetes and depressive symptoms in older adults: a population-based study. Diabet Med 1991;8:532-9.
Icks A, Kruse J, Dragano N, Broecker-Preuss M, Slomiany U, Mann K, et al.
Are symptoms of depression more common in diabetes? Results from the Heinz Nixdorf Recall study. Diabet Med 2008;25:1330-6.
Padgett DK. Sociodemographic and disease-related correlates of depressive morbidity among diabetic patients in Zagreb, Croatia. J Nerv Ment Dis 1993;181:123-9.
Bruce DG, Davis WA, Davis TM. Longitudinal predictors of reduced mobility and physical disability in patients with type 2 diabetes: the Fremantle Diabetes Study. Diabetes Care 2005;28:2441-7.
Wikblad KF, Wibell LB, Montin KR. Health and unhealth in chronic disease. Scand J Caring Sci 1991;5:71-7.
Pawaskar MD, Anderson RT, Balkrishnan R. Self-reported predictors of depressive symptomatology in an elderly population with type 2 diabetes mellitus: a prospective cohort study. Health Qual Life Outcomes 2007;5:50.
Lysy Z, Da Costa D, Dasgupta K. The association of physical activity and depression in Type 2 diabetes. Diabet Med 2008;25:1133-41.
Anstey KJ, von Sanden C, Sargent-Cox K, Luszcz MA. Prevalence and risk factors for depression in a longitudinal, population-based study including individuals in the community and residential care. Am J Geriatr Psychiatry 2007;15:497-505.
Fitten LJ, Ortiz F, Fairbanks L, Rosenthal M, Cole GN, Nourhashemi F, et al.
Depression, diabetes and metabolic-nutritional factors in elderly Hispanics. J Nutr Health Aging 2008;12:634-40.
Luijendijk HJ, Stricker BH, Hofman A, Witteman JC, Tiemeier H. Cerebrovascular risk factors and incident depression in community-dwelling elderly. Acta Psychiatr Scand 2008;118:139-48.
Moreira RO, Marca KF, Appolinario JC, Coutinho WF. Increased waist circumference is associated with an increased prevalence of mood disorders and depressive symptoms in obese women. Eat Weight Disord 2007;12:35-40.
Polonsky WH, Anderson BJ, Lohrer PA, Welch G, Jacobson AM, Aponte JE, et al
. Assessment of diabetes-related distress. Diabetes Care 1995;18:754-60.
Black SA. Increased health burden associated with comorbid depression in older diabetic Mexican Americans. Results from the Hispanic Established Population for the Epidemiologic Study of the Elderly survey. Diabetes Care 1999;22:56-64.
American Psychiatric Association (APA). Diagnostic and Statistical Manual of Mental Disorders. 4th
ed. Text Revision. Washigton, DC: APA; 2000.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62.
[Table 1], [Table 2], [Table 3]