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 Table of Contents  
Year : 2020  |  Volume : 64  |  Issue : 4  |  Page : 413-416  

Prevalence of depression and the associated factors among the software professionals in Delhi: A cross-sectional study

1 Senior Resident, Department of Community Medicine and School of Public Health, PGIMER, Chandigarh, India
2 Director Professor and Head, Department of Community Medicine, Vardhman Mahavir Medical College, Safdarjung Hospital, New Delhi, India

Date of Submission17-Nov-2019
Date of Decision01-Apr-2020
Date of Acceptance28-Oct-2020
Date of Web Publication11-Dec-2020

Correspondence Address:
P Aravind Gandhi
Room No. 135, Department of Community Medicine and School of Public Health, PGIMER, Chandigarh - 160 012
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijph.IJPH_568_19

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India is home to an estimated 57 million people (18% of the global estimate) affected by depression. We conducted a cross-sectional study to determine the prevalence of depression and associated factors among software professionals in Delhi National Capital Region, during 2017–2018 with a sample size of 310. Two-stage cluster sampling was used. A predesigned, pretested, semi-structured, English questionnaire was used. Patient Health Questionnaire 9, CAGE, CAGE Adapted to Include Drugs (CAGE-AID) questionnaire, Fagerstrom test for nicotine dependence questionnaire was used. Forty percent (124) of the participants were screened to have major depressive disorder. There was a statistically significant association between depression and marital status (P = 0.041), family type (P = 0.008), alcohol use (P < 0.001), substance use (P = 0.014), multiple roles in a project (P < 0.001), and shift of work (P < 0.008). Considering the high prevalence of depression, mental health screening program, sensitization, and promotion must be incorporated into the IT industry to prevent and detect depression early.

Keywords: Delhi national capital region, depression, major depressive disorder, mental health, software professional

How to cite this article:
Gandhi P A, Kishore J. Prevalence of depression and the associated factors among the software professionals in Delhi: A cross-sectional study. Indian J Public Health 2020;64:413-6

How to cite this URL:
Gandhi P A, Kishore J. Prevalence of depression and the associated factors among the software professionals in Delhi: A cross-sectional study. Indian J Public Health [serial online] 2020 [cited 2023 Feb 2];64:413-6. Available from:

Depression is a common illness worldwide, with more than 300 million people affected.[1] The report on Global Burden of Disease estimates the point prevalence of unipolar depressive episodes to be 1.9% for men and 3.2% for women, and the 1-year prevalence has been estimated to be 5.8% for men and 9.5% for women.[2] The population-based study from India to report on depression shows that the prevalence of depression was 15.1%. India is home to an estimated 57 million people (18% of the global estimate) affected by depression.[3] At its mildest, one may simply feel persistently low in spirit, while at its most, severe depression can make one feel suicidal and that life is no longer worth living. The findings from National Mental Health Survey 2015–2016 showed that nearly 30% of those with depression have substance use disorder as a comorbid condition.[4] Depression is the first hard hit disease that was observed among the respondents, with 42.5% of the corporate employees suffering from this disease. Considering the huge burden and impact of depression and its importance as public health concern in developing and developed world, the World Health Organization declared depression: Let's Talk, as the theme of World Health day on April 07, 2017 and lead a year long campaign on depression domains.[5] Information Technology (IT) industry in India is booming, and the Software Products and IT services contribute 3.9 million employees.[6] The National Capital Region (NCR) of Delhi hosts 18% of the country' software industries.[7] Hence, we have focused to determine the prevalence of depression among software professionals in Delhi NCR and to determine the factors associated with depression in them.

The present study was a cross-sectional study done among the software professionals employed in Delhi NCR. Software professionals working for minimum 6 months in the field and 3 h/day or 15 h/week work with computer were included. The study period was from 2017 to 2018. A sample size of 310 was calculated based on the prevalence rate of 8% from Sharma et al. study,[8] precision of 4%, a design effect of 1.5, and 10% nonresponse rate. Two-stage cluster random sampling was used. Stage 1: Clusters-Software (IT) firms. The list of the firms in Delhi-NCR was obtained from National Association of Software and Service Companies (NASSCOM) website, which came to be 452. From the list, 10 firms were chosen by systematic random sampling. Stage 2: Individual samples: software professionals were chosen by systematic random sampling from the 10 firms. The eligible employees from the selected firms were line listed, firm wise, which came out to be 1652. Considering the calculated sample size of 310, a sampling interval of 5.32 was calculated. The first participant was selected from the line list, by simple random sampling with the help of lottery method, from 1 to 5. Subsequently, every fifth person from the list was selected to complete the sample size. Data were collected using a predesigned, pretested, semi-structured, computer-assisted personal interviewed, English questionnaire. It consists of parts for assessing the depression and factors associated with it. Patient Health Questionnaire 9 (PHQ 9) was used to assess the prevalence of major depressive disorder (MDD) severity of depression.[9] CAGE and CAGE-AID questionnaires were used to assess the problem alcohol use and problem substance use. Fagerstrom test for nicotine dependence questionnaire was used to assess nicotine dependency among the smokers.[10]

Data entry was done on Microsoft excel sheet and analysis was done using IBM Corp. Released 2019 (IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp). For qualitative data, proportions were calculated. The Chi-square and Fisher' exact test were applied to test the significance of association between the variables. Multivariable logistic regression was used to adjust for the effect of other significant variables. P < 0.05 is considered statistically significant.

Ethical clearance for the study was obtained from the Institute Ethics Committee (S. No. IEC/VMMC/SJH/Thesis/October/2016/2, dated 14.10.2016). Participants were enrolled after briefing them the details about the study and obtaining a written informed consent.

The mean age of the study participants was 25.17 (standard deviation – 2.64) years, majority were males (71.3%), in the age group of 21–30 years (98.4%), belonged to Hindu religion (83.2%), natives of states other than Delhi (94.2%), degree holders in computer science (55.5%), never married (77.1%), and were living as single bachelor (55.8%).

Among the study participants, 124 (40%) were screened to have MDD according to the PHQ 9 criteria. Among the participants with MDD, the severity varied and it was divided according to the PHQ 9 scores into mild, moderately severe, and severe. 35.8% of the total participants were suffering from mild depression, 3.5% with severe depression, and 0.7% with moderately severe depression [Figure 1].
Figure 1: Distribution of study participants according to severity of depression (n = 310)

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In the present study, 55 (17.74%) and 5 (1.61%) of the participants were having problem alcohol use and problem substance use, respectively. Problem alcohol use, problem substance use, marital status, being a single bachelor, mixed shift of day and night at work, working multiple roles in a project like software designer, programmer and tester, had a statistically significant association with depression among the participants [Table 1].
Table 1: Association of major depressive disorder with different variables of the participants (n=310)

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Among the participants, 19 (6.1%) had a history of mental illness ever, 7 (2.3%) were taking medications, and 24 (7.7%) had family history of mental illness in their first degree relatives. However, these factors did not have significant association with depression [Table 1]. All the 27 (8.7%) smokers in our study were found to have only low nicotine dependence.

The prevalence of 40% MDD in the present study is not in line with the prevalence of depression found in previous studies by Sharma et al. and Shrivastava and Bobhate which ranged from 6% to 8%.[8],[11] Vimala and Madhavi and Padma et al. found that the rate of depression was 84% and 54%,[12],[13] respectively, among the IT professionals. Darshan et al. showed that 43.4% of the study participants were at the risk of developing depression.[14] The difference in the depression rates between our study and the previous studies might be due to different scales used to screen and assess the depression. It may also be due to the different timeframe, as Sharma et al. study was conducted in 2006,[8] before there was a global slowdown in the economy that affected the IT sector. The study conducted by Vimala and Madhavi had only women software professionals and was done in a different study area, whereas our study had both the sexes.[12] The study settings of Shrivastava and Bobhate and Padma et al. are different from ours.[11],[13] Darshan et al. showed the risk of developing depression, not the depression prevalence, per se.[14]

There was a statistically significant association between the depression and problem alcohol use (P < 0.001) which is in line with the findings of the study by Lee et al.[15] Similarly, Darshan et al. observed a significant difference between at risk and not-at risk groups for depression, when harmful drinking was compared.[14] However, Park et al. showed that there was no significant association between depression and hazardous drinking behavior.[16] Brière et al. through their study noted that, comorbidity of MDD-alcohol use disorder (MDD-AUD) was associated with higher risk of alcohol dependence, suicide attempt, lower global functioning, and life dissatisfaction.[17] Boden and Fergusson in their systematic review brought out a possible causal link between AUD and major depression.[18] In the present study, higher proportion of those with problem substance use (80%) were having depression as compared to the ones without problem substance use, and there was a statistically significant association between the depression and problem substance use (P = 0.014). It is similar to the findings of Vasquez et al., where it was revealed that a link between depressive symptoms and substance abuse exist.[19]

The present study had some limitations too. The software firms which were not registered with NASSCOM were not included in the sampling frame. The employees of the firms, who were posted on deputation to other cities or countries during the study period, could not be included in the sampling frame. Temporal association between the factors and depression could not established, as it was a cross-sectional study. Nicotine dependence among the nonsmoking tobacco users was not assessed.

Conclusively, the prevalence of depression among the software professionals in Delhi is high. There is an association between depression and the factors such as problem alcohol use, problem substance use, multiple roles played, and mixed shift. Hence, sensitization about the importance of mental health and its promotion must be incorporated into the IT industry employee health-care measures to prevent depression. Early identification of the depression can be done by inculcating programs such as employee' assistance scheme, peer intervention groups, and appointing occupational psychologists in firms. Further, analytical studies must be conducted to test our findings of association between depression and alcohol use, substance use, shift pattern, and multiple roles of the professional in the project.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Figure 1]

  [Table 1]

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