• Users Online: 716
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 7  |  Issue : 1  |  Page : 36-41

Productivity loss and diabetes distress among patients with type 2 diabetes seeking out patient care at a tertiary hospital in Bengaluru, South India


1 Department of Community Health, St. Johns Medical College and Hospital, Bengaluru, Karnataka, India
2 Department of Endocrinology, St. Johns Medical College and Hospital, Bengaluru, Karnataka, India
3 Department of General Medicine, St. Johns Medical College and Hospital, Bengaluru, Karnataka, India

Date of Submission16-Dec-2021
Date of Decision10-Jan-2022
Date of Acceptance10-Jan-2022
Date of Web Publication31-Mar-2022

Correspondence Address:
Ms. Kavya Pinto
T1 Habitat Serenity, Richards Town, Bengaluru - 560 005, Karnataka
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jncd.jncd_83_21

Rights and Permissions
  Abstract 


Background: Type 2 diabetes contributes to significant productivity losses in paid work and unpaid work. Patients with Type 2 diabetes also feel distressed due to the concerns about disease management, its emotional burden, physician-related issues, and regimen-related distress.
Objective: The objective of this study is to assess the productivity loss and diabetes distress among patients with Type 2 diabetes attending the outpatient department at a tertiary care setting and the association between productivity loss and diabetes distress in the study population.
Materials and Methods: A cross-sectional study was done among 121 outpatients with Type 2 diabetes at a tertiary care hospital. A semistructured interview schedule that included questions on sociodemographic profile, details about diabetes, the Institute for Medical Technology Assessment Productivity Cost Questionnaire, and Diabetes Distress Scale was administered.
Results: Around half of the study participants (47.1%) reported productivity losses either in paid and/or unpaid work. The total cost of productivity loss among 121 patients over 4 weeks was calculated to be Indian National Rupees 2,526,880. Individuals with diabetes distress levels worthy of clinical attention (moderate and high levels of distress) were found to be 20.6%. Significant emotional burden was seen among 40.5% of the study participants. Of the population who had distress due to diabetes, 60% had productivity loss.
Conclusion: Patients with type 2 diabetes have high productivity losses and distress due to diabetes. Patients with productivity losses have significantly higher levels of diabetic distress.

Keywords: Absenteeism, distress, presenteeism, productivity loss, type 2 diabetes


How to cite this article:
Pinto K, Mathur S, Fathima FN, George B, Umesh S. Productivity loss and diabetes distress among patients with type 2 diabetes seeking out patient care at a tertiary hospital in Bengaluru, South India. Int J Non-Commun Dis 2022;7:36-41

How to cite this URL:
Pinto K, Mathur S, Fathima FN, George B, Umesh S. Productivity loss and diabetes distress among patients with type 2 diabetes seeking out patient care at a tertiary hospital in Bengaluru, South India. Int J Non-Commun Dis [serial online] 2022 [cited 2022 May 20];7:36-41. Available from: https://www.ijncd.org/text.asp?2022/7/1/37/342085




  Introduction Top


Over the previous decade, the prevalence of Type 2 diabetes has risen in nations like India with an estimated 80% of diabetes deaths occurring in these low- and middle-income countries.[1]

Lost productivity at work is an important concern due to sickness, absence, disability, and premature retirement.[2]

Diabetes distress is defined as patient concerns about disease management, its emotional, physician, and regimen-related burden.[3]

Data on productivity losses and diabetic distress are lacking in India. Hence, this study was conducted to estimate the productivity loss due to diabetes, the proportion of diabetes distress, and their association in the study population.


  Materials and Methods Top


In this article, we present the results of a cross-sectional study done in the year 2019. The study population comprised of all patients attending outpatient department with Type 2 diabetes in the departments of general medicine and endocrinology in a tertiary care setting. The inclusion criteria included ages 18 and above, while the exclusion criteria were patients that were unconscious, severely ill or unable to comprehend the questions. Ethical clearance was obtained from the Institutional Ethics Committee before the commencement of the study (IEC 25/2019).

After obtaining informed consent, a pretested structured interview schedule consisting of the following sections was administered to the study participants

Section A

Sociodemographic profiling, which included name, age, sex, address, occupation, marital status, income, education, and socioeconomic status was recorded.

Section B

We used the Institute for Medical Technology Assessment (iMTA) Productivity Cost Questionnaire (PCQ) developed by iMTA, Netherlands.[4] The iPCQ is an instrument for evaluating health-related productivity loss. The iPCQ includes three modules measuring productivity losses of paid work due to (1) absenteeism and (2) presenteeism and productivity losses related to (3) unpaid work.

The iPCQ aims to measure absenteeism from paid work as well as the length of absenteeism using 3 questions. Long-term absence (recall period being >4 weeks) is also quantified. Presenteeism indicates decreased productivity at work. Respondents were asked if they have suffered from health problems during work and if so, for how long. They were also asked to rate their work performance on a 10-point rating scale as compared to functioning on normal working days.

Unpaid work, for example, household work and volunteer work can also be adversely affected by health-related issues. A third person criterion is applied to measure the amount of work as well as differentiate unpaid work from leisure.

The formula for no of hours lost due to presenteeism = no. of workdays impaired × (1 − [efficiency score/10]) × no of hours per workday.

Unpaid productivity loss was calculated by multiplying the number of days of unpaid work missed by the number of hours of help needed per day to make up the work.[4],[5]

The standard daily minimum wage for Karnataka state as per the labor department of the Government of Karnataka is 338 Indian National Rupees (INR) for 2019.[6] This was considered as the standard cost price of productivity per day for our analysis. The friction period was calculated assuming 60 days for salaried people and 1–2 weeks for the rest.

The total cost of productivity loss was calculated by summing the productivity losses due to presenteeism and absenteeism at work and for unpaid work.

Section C

The Diabetes Distress Scale (DDS) consists of 17 questions that cover four important dimensions of distress in diabetes: Emotional burden, regimen distress, interpersonal distress, and physician-related distress.[7] DDS17 uses a Likert scale with each item scored from 1 (no distress) to 6 (serious distress) concerning distress experienced over the last month. To score the level of distress, we summed the patient response to each item and divided by the number of items in each scale. The mean score is defined in three DDS categories: Little or no DD (DDS <2.0), moderate DD (DDS = 2.0–2.9), and high DD (DDS ≥3.0). Individuals with DDS of ≥2.0 are said to be clinically significant.[8],[9]

The sample size for the study was estimated based on the result of a study by Sharma et al. who reported that the presentism loss per year among Type 2 diabetes patients seeking care at a tertiary care hospital in the private sector in South India was found to be 4.9 ± 26.5 work days.[10] Using this as a point estimate for mean and standard deviation with the precision of 5% and confidence level of 95% and inflated to include a nonresponse of 10%. We estimated the minimum sample size required for our study to be 121.

Data were collected using handheld devices using Epicollect5 software.[11] Data were then exported to Microsoft Excel and analyzed using standard statistical software. Data were checked for normality using the normality test (Shapiro–Wilk) and plots. The sociodemographic characteristics of the study population were described using descriptive statistics such as proportions and mean and standard deviation. The proportion of people reporting productivity losses due to absenteeism and presentism and the level of distress due to diabetes in each domain were presented as percentages.

Productivity losses were calculated using the methods described in the Productivity Costs Questionnaire Manual by Productivity and Health Research Group from iMTA[4],[5] and expressed as the continuous variable in INR and described as median and interquartile range. Diabetes distress score in all domains was analyzed and described using mean and standard deviation or median and interquartile range. The association between productivity loss and distress due to diabetes was studied using the Chi-square test for association and Fischer's exact test. A P < 0.05 was considered statistically significant for all analysis.


  Results Top


Of the 121 study participants, 55.4% were female. The ages ranged from 25 to 92 years, with a mean age of 53.4 ± 11.6 years. Of the study population, 41.3% were homemakers, 9.1% and 0.8% were retired or unemployed, respectively. These three categories comprised of people without a paid job. The rest (48.8%) had a paid job and were employed in the private, public, agricultural sectors, or were daily wage sectors. The working population from the upper and upper middle class according to Modified BG Prasad Scale[12] was 64.6%. Around two-thirds (65.3%) were residents of urban areas and were from nuclear families (60.3%). Individuals have been diagnosed with diabetes for a mean of 7.5 ± 6.5 years. A large proportion of the study participants had been diagnosed for 10 years or less (75.2%) and had comorbidities (63.6%) such as hypertension, obesity, cardiovascular disease, and others. Majority of the study participants (99.2%) were on antidiabetic medication with 71.1% on one drug and 28.1% on two or more medications (including insulin and oral hypoglycemics).

Productivity loss

Around half of the study participants (57, 47.1%) reported productivity losses either in paid and/or unpaid work. Out of 54 participants who had paying jobs, productivity loss due to presenteeism was reported by 24 (44.4%) and due to absenteeism by eight (14.8%). Of the 30 females reporting productivity loss, 80% (24) had productivity losses in unpaid work. On the other hand, of the 27 males with productivity loss, 88.8% (24) reported loss in paid work. Proportion of study participants with various forms of productivity loss by sex is depicted in [Table 1].
Table 1: Proportion of study participants with productivity loss by sex

Click here to view


Significantly higher proportion (P = 0.08) of individuals diagnosed with diabetes for 10 years (85%) reported productivity losses compared to individuals who had diabetes for more than 10 years (15%). Productivity loss was reported by 38.6% of individuals from lower to middle class and 45.6% of individuals from upper and upper middle class.

The mean number of days worked despite illness among the 24 individuals who reported presenteeism in the past 4 weeks was 18.1 ± 11.3 days.

The total cost of productivity loss among 121 patients with Type 2 diabetes over 4 weeks was calculated to be INR 2,526,880 which amounts to 745.8 INR per capita per day. Detailed productivity loss costs are depicted in [Table 2].
Table 2: Total cost of productivity loss in Indian national rupees over 4 weeks among 121 participants

Click here to view


Diabetes distress scale

Overall diabetes distress ranged from 1 to 3.9 out of a total of 6 with a mean score of 1.6 ± 0.6. The proportion of individuals with diabetes distress levels worthy of clinical attention (moderate and high levels of distress) was found to be 20.6%. Proportion of individuals in the three categories of diabetes distress is depicted in [Table 3].
Table 3: Frequency of individuals with distress due to diabetes

Click here to view


Emotional burden score ranged from 1 to 5.6 with a median of 1.60 (1.20, 2.60). Significant emotional burden was seen among 40.5% of the study participants. A low proportion of participants reported physician-related burden (2.5%) and interpersonal-related burden (8.3%).

There was no significant difference in the overall distress score by age, gender, comorbidities, and control of diabetes. Patients aged <55 years had significantly higher emotional distress than patients aged >55 years. Males had significantly higher (P = 0.04) interpersonal distress than females. No significant difference was found for the other domains of distress with age categories and gender.

Association between productivity loss and diabetes distress

Of the population who had distress due to diabetes, 60% had productivity loss. Out of the 57 individuals who had productivity loss, the mean diabetes distress score was 1.7 ± 0.6. Mean diabetes distress score was significantly higher (P = 0.007) among those with productivity loss (1.73 ± 0.64) compared to those without production losses (1.44 ± 0.52). The association between productivity loss and mean diabetes distress score is depicted in [Table 4]. Patients with productivity loss had significantly higher (P = 0.03) emotional distress (1.73 ± 0.64) compared to patients without productivity loss (1.44 ± 0.52).
Table 4: The association between productivity loss and mean diabetes distress score

Click here to view



  Discussion Top


Diabetics in India scored low on the World Health Organization-5 Well-being Index and reported a higher perception of socioeconomic burden and personal distress.[13] Therefore, this study could be helpful in sensitizing the health-care professionals to the various burdens of a diabetic. Quantifying the cost of productivity loss is important for policy-makers in making budgetary decisions. Self-care and efficacy of treatment can increase if distress due to diabetes is correctly identified and managed by health-care providers. A study done in Australia by L Holden found that there was a greater risk of productivity loss associated with psychological distress.[14]

Our study found that the total productivity loss per capita per day was 745.8 INR. However, most studies have a much lower indirect cost. Grover et al. reports an indirect cost of INR 2,086.7 ± 5,050.03 over 6 months.[15] This discrepancy could be due to a difference in methodology and calculation.

In this study, 24.8% of participants had health insurance. A study conducted by Javalkar,[16] in Coastal Karnataka, showed that 2% of the participants utilized health insurances. The higher result could be due to the difference in study population, as our study population had a higher socioeconomic status, with 64.6% of participants from upper and upper middle class.

Assessment of distress should be integrated in the health-care plan for diabetics in India. According to the National Recommendation 60 of psychosocial management of diabetes in India,[17] Kalra et al. suggests the usage of standardized scales such as DDS by physicians in their clinical assessment.

A cross-sectional study was done by Kumar et al.[18] in 2017 to find an association between diabetes distress and the adherence to antidiabetic medications among Type 2 Diabetes patients in Coastal South India. Data were collected from patients attending hospitals affiliated to Kasturba Medical College, Mangalore in the past 18 years. They concluded that early identification of diabetes distress can improve adherence to medication. It was observed that majority of the participants had a low regimen distress, physician distress and interpersonal distress; however, high emotional distress was present among a higher number of participants. This corroborates with the results of our study.

Sankar et al.[19] in a cross-sectional study to assess diabetes distress and its associations with various parameters among Type 2 diabetes patients in a multispecialty hospital in South India, found that the prevalence of diabetes distress was 27.9% overall.

Similarly, our study found that 20.6% of participants suffered from diabetes distress. Sankar et al.[19] also found that emotional burden was high among the study population. A study was done by Gahlan et al.[20] in 2017 on prevalence and determinants of diabetes distress in Type 2 diabetes patients in a tertiary care center in North India. The study suggested that among diabetic patients, emotion-related distress was the most prevalent. Our study corroborates these findings.

Studies on association between productivity loss and distress due to diabetes in India are lacking. This highlights the importance of our study. Productivity loss can be a factor in increased levels of distress due to diabetes and therefore should be managed effectively. A study was done by Xu et al. investigating the association between diabetes distress and productivity among patients with uncontrolled Type 2 diabetes mellitus in the primary healthcare institutions.[21] Their study found that diabetes distress was positively associated with work and life productivity loss (P = 0.01). Our study found that of the population who had distress due to diabetes, 60% reported productivity loss (P = 0.14). The mean distress score reported by participants with productivity loss was 1.73 ± 0.64 (P < 0.01).


  Conclusion Top


We conclude that around half of the study participants (57, 47.1%) reported productivity losses either in paid and/or unpaid work. Most females (80%) experienced unpaid loss and most males (88.8%) experienced loss at paid work. Our results showed that unpaid loss due to diabetes was high (22.3%). Productivity losses due to presenteeism (19.8%) were more than absenteeism (6.6%). The number of individuals with moderate or severe distress due to diabetes was low (20.6%). Participants reported the low values of physician related, regimen related and interpersonal distress while reports of emotional distress were higher (40.5%). Of the population who had distress due to diabetes, 60% reported productivity loss.

The limitation of our study is that data on productivity losses were subjective and self-reported. We were unable to check the occupational health records to capture the data on absenteeism as such records do not exist in the unorganized sector. In addition, recruitment of study participants was by purposive sampling. Despite these limitations, our study is important as data on productivity losses are scarce from the Indian settings. Further research is needed in this area to document productivity loss and distress due to diabetes so that it can be used for policy-making decisions including resource allocation.

Ethical approval statement

Ethical clearance was obtained from the Institutional Ethics Committee before the commencement of the study (IEC 25/2019).

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Roglic G. WHO Global report on diabetes: A summary. Int J Noncommun Dis 2016;1:3.  Back to cited text no. 1
    
2.
Ng YC, Jacobs P, Johnson JA. Productivity losses associated with diabetes in the US. Diabetes Care 2001;24:257-61.  Back to cited text no. 2
    
3.
Breton MC, Guénette L, Amiche MA, Kayibanda JF, Grégoire JP, Moisan J. Burden of diabetes on the ability to work: A systematic review. Diabetes Care 2013;36:740-9.  Back to cited text no. 3
    
4.
Bouwmans C, Hakkaart-Van Roijen L, Koopmanschap M, Krol M, Severens H, Brouwer W. Productivity Cost Questionnaire. Erasmus University Rotterdam: Institute for Medical Technology Assesment; 2013.  Back to cited text no. 4
    
5.
Bouwmans C, Krol M, Severens H, Koopmanschap M, Brouwer W, Hakkaart-van Roijen L. The iMTA productivity cost questionnaire: A standardized instrument for measuring and valuing health-related productivity losses. Value Health 2015;18:753-8.  Back to cited text no. 5
    
6.
Karnataka Labour Journal, March to June 2019. Available from: https://labour.gov.in/sites/default/files/MW%20PDF.pdf. [Last accessed on 2021 Jul 08].  Back to cited text no. 6
    
7.
Breton MC, Guénette L, Amiche MA, Kayibanda JF, Grégoire JP, Moisan J. Burden of diabetes on the ability to work: A systematic review. Diabetes Care 2013;36:740-9.  Back to cited text no. 7
    
8.
Fisher L, Hessler DM, Polonsky WH, Mullan J. When is diabetes distress clinically meaningful? Establishing cut points for the Diabetes Distress Scale. Diabetes Care 2012;35:259-64.  Back to cited text no. 8
    
9.
Polonsky WH, Fisher L, Earles J, Dudl RJ, Lees J, Mullan J, et al. Assessing psychosocial distress in diabetes: Development of the diabetes distress scale. Diabetes Care 2005;28:626-31.  Back to cited text no. 9
    
10.
Sharma K. Burden of non communicable diseases in India: Setting priority for action. Int J Med Sci Public Health 2013;2:7-11.  Back to cited text no. 10
    
11.
Gohil R, Sharma S, Sachdeva S, Gupta S, Dhillon MS. EpiCollect 5: A Free, Fully Customizable Mobile-Based Application for Data Collection in Clinical Research. J Postgrad Med Edu Res 2020;12:1-4.  Back to cited text no. 11
    
12.
Pandey VK, Pradeep A, Rakesh K. Modified BG Prasad's socio-economic classification-2018: The need of an update in the present scenario. Indian J Community Health 2018;30:82-4.  Back to cited text no. 12
    
13.
Peyrot M, Rubin RR, Lauritzen T, Snoek FJ, Matthews DR, Skovlund SE. Psychosocial problems and barriers to improved diabetes management: Results of the Cross-National Diabetes Attitudes, Wishes and Needs (DAWN) study. Diabet Med 2005;22:1379-85.  Back to cited text no. 13
    
14.
Holden L, Scuffham PA, Hilton MF, Ware RS, Vecchio N, Whiteford HA. Health-related productivity losses increase when the health condition is co-morbid with psychological distress: Findings from a large cross-sectional sample of working Australians. BMC Public Health 2011;11:417.  Back to cited text no. 14
    
15.
Grover S, Avasthi A, Bhansali A, Chakrabarti S, Kulhara P. Cost of ambulatory care of diabetes mellitus: A study from north India. Postgrad Med J 2005;81:391-5.  Back to cited text no. 15
    
16.
Javalkar SR. The economic burden of health expenditure on diabetes mellitus among urban poor: A cross sectional study. Int J Community Med Public Health 2019;6:1162-6.  Back to cited text no. 16
    
17.
Kalra S, Sridhar GR, Balhara YP, Sahay RK, Bantwal G, Baruah MP, et al. National recommendations: Psychosocial management of diabetes in India. Indian J Endocrinol Metab 2013;17:376-95.  Back to cited text no. 17
    
18.
Kumar N, Unnikrishnan B, Thapar R, Mithra P, Kulkarni V, Holla R, et al. Distress and its effect on adherence to antidiabetic medications among type 2 diabetes patients in coastal South India. J Nat Sci Biol Med 2017;8:216-20.  Back to cited text no. 18
    
19.
Sankar P, Sasikumar P, Medayil R, Jacob R, Sasidharan S. High prevalence of distress among patients with Type 2 diabetes (T2DM)—A hospital-based, cross-sectional study from South India. Diabetes 2018;67(Supplement_1).  Back to cited text no. 19
    
20.
Gahlan D, Rajput R, Gehlawat P, Gupta R. Prevalence and determinants of diabetes distress in patients of diabetes mellitus in a tertiary care centre. Diabetes Metab Syndr 2018;12:333-6.  Back to cited text no. 20
    
21.
Xu Y, Tong GY, Lee JY. Investigation on the association between diabetes distress and productivity among patients with uncontrolled type 2 diabetes mellitus in the primary healthcare institutions. Prim Care Diabetes 2020;14:538-44.  Back to cited text no. 21
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
   Abstract
  Introduction
   Materials and Me...
  Results
  Discussion
  Conclusion
   References
   Article Tables

 Article Access Statistics
    Viewed380    
    Printed6    
    Emailed0    
    PDF Downloaded6    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]