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Year : 2019  |  Volume : 44  |  Issue : 2  |  Page : 171-172

Assessing health-related quality of life in patients with diabetes mellitus at a Tertiary Care Center in Central Delhi

Department of Medicine, Lady Hardinge Medical College, Sucheta Kriplani Hospital, New Delhi, India

Date of Submission02-Sep-2018
Date of Acceptance18-Mar-2019
Date of Web Publication27-Jun-2019

Correspondence Address:
Dr. Mishita Goel
H. No. 340, Old Housing Board, Sector-13, Karnal - 132 001, Haryana
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijcm.IJCM_273_18

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How to cite this article:
Goel M, Dhuldhule S, Prakash A, Ghotekar LH. Assessing health-related quality of life in patients with diabetes mellitus at a Tertiary Care Center in Central Delhi. Indian J Community Med 2019;44:171-2

How to cite this URL:
Goel M, Dhuldhule S, Prakash A, Ghotekar LH. Assessing health-related quality of life in patients with diabetes mellitus at a Tertiary Care Center in Central Delhi. Indian J Community Med [serial online] 2019 [cited 2021 May 9];44:171-2. Available from: https://www.ijcm.org.in/text.asp?2019/44/2/171/261519


Diabetes mellitus (DM) is a chronic disease with increasing prevalence due to the changes in lifestyle resulting in physical inactivity, and increased obesity. As quality of life (QoL) represents the effect of an illness on a patient, as perceived by the patient, and yields complementary information to medical or epidemiological data, it is often used as an outcome measurement. QoL has also been characterized as the ultimate goal of all health interventions. QoL leads to diminished self-care, which in turn leads to worsened glycemic control, increased risks for complications, and exacerbation of diabetes overwhelming in both the short and long run.[1] In response to this concern, a considerable body of literature has emerged to evaluate health-related quality of life (HRQoL) and its determinants in diabetic patients. However, data regarding QoL of patients with diabetes in India has been relatively meager. We assessed HRQoL among 100 outdoor adult patients with either type 1 or type 2 DM, its predictors and the impact of socioeconomic and other factors such as age, sex, and coexisting illnesses at a tertiary care center.

Using a semi-structured interview schedule, data on personal details, treatment history, and relevant clinical history were collected. HRQoL was assessed using a licensed Hindi version of the SF-36 questionnaire. One hundred patients were recruited by convenience sampling. The patients' responses were scored using Quality Metric scoring software provided by the SF 36 organization along with the licensure. Overall, QoL was assessed in eight dimensions of the SF-36. The software provided a score ranging from 0 to 100 for each domain as well as for physical component summary (PCS) and mental component summary (MCS).[2] The data obtained were analyzed to evaluate the correlation between obtained scores and various clinical data.

Of the 100, 64 were female patients. Mean age of individuals was 51.95 ± 11.75 years. There were 40 elderly patients (age ≥ 55), 52 middle-aged patients (age: 35–54 years) and 8 young patients (age <35) in the sample. The majority of patients had type 2 DM (n = 97). About 57% of patients had a history of hypertension, 8% had a history of coronary artery disease (CAD), and 8% had both. About 22% of patients were smokers. We found that bodily pain seemed to increase with increasing body weight (r = 0.385) and BMI (r = 0.342) [Table 1]. Elderly patients had significantly lower physical functioning scores (57 ± 27.4) as compared to middle-aged (70 ± 22.3) and young patients (60 ± 28.7, P = 0.045). No statistically significant correlation was found between QoL domain scores and duration of diabetes, presence of comorbidities or history of alcohol or smoking. Increasing waist to hip circumference ratio seemed to significantly correlate with increasing emotional role functioning (0.204) and MCS (r = 0.231). Female diabetics were found to have higher scores in the social role functioning domain (81.94 ± 19.92 vs. 71.3 ± 26.3, P = 0.03).
Table 1: Correlation between domain scores and patient characteristics

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In all individuals, a statistically significant positive correlation was found between PCS and MCS. The current study found that QoL in diabetics is not significantly affected by age, disease duration, smoking status, or history of hypertension. These findings were similar to that observed by Kazemi-Galougahi et al.[3] In the systematic review conducted by Wändell,[4] type 2 diabetes patients with heart disease showed lower HRQoL than those without it. In the systematic review conducted by Kiadaliri et al.,[5] it was found that smokers had worse QoL than their nonsmoker counterparts. In the same review, most studies found a negative association between age and HRQoL. However, our study found no significant differences in HRQoL based on the age, but females were found to have higher social role functioning. Before starting the study, we believed that HRQoL in diabetics would worsen with age, disease duration, history of hypertension, CAD, higher weight, and BMI. We also believed that smoking and alcohol consumption should negatively impact the QoL of diabetic patients. After completion of the study, it was found that HRQoL did not vary significantly with the above parameters. Waist/Hip circumference ratio was interestingly found to correlate with emotional role functioning and mental component scores. Females were found to have slightly better QoL than male diabetics. However, it was also noted that the mean disease duration of male diabetics was higher than that of females. Thus, this may be a confounding factor accounting for females having slightly better QoL, although a statistically significant correlation between disease duration and QoL was not established as mentioned earlier.

Although our analysis was limited in scope, we hope that larger studies will validate the findings of our study and elucidate more data on factors relating to QoL in diabetics, which is a growing patient population with important implications for public health.


The authors would like to acknowledge the contribution of the SF-36 organization for providing access to an approved version of the SF-36 survey in Hindi as well as the Quality Metric Software used for scoring patient responses.

Financial support and sponsorship

This project was completed as part of ICMR Short Term Studentship Program-2014 (Ref-No. 2014-04531).

Conflicts of interest

There are no conflicts of interest.

   References Top

Huang IC, Hwang CC, Wu MY, Lin W, Leite W, Wu AW. Diabetes-specific or generic measures for health-related quality of life? Evidence from psychometric validation of the D-39 and SF-36. Value Health 2008;11:450-61.  Back to cited text no. 1
McHorney CA, Ware JE Jr., Lu JF, Sherbourne CD. The MOS 36-item short-form health survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care 1994;32:40-66.  Back to cited text no. 2
Kazemi-Galougahi MH, Ghaziani HN, Ardebili HE, Mahmoudi M. Quality of life in type 2 diabetic patients and related effective factors. Indian J Med Sci 2012;66:230-7.  Back to cited text no. 3
  [Full text]  
Wändell PE. Quality of life of patients with diabetes mellitus. An overview of research in primary health care in the Nordic countries. Scand J Prim Health Care 2005;23:68-74.  Back to cited text no. 4
Kiadaliri AA, Najafi B, Mirmalek-Sani M. Quality of life in people with diabetes: A systematic review of studies in Iran. J Diabetes Metab Disord 2013;12:54.  Back to cited text no. 5


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