Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
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Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus Michelle Ang Co a, Luor Shyuan Maudrene Tan b, E Shyong Tai a, b, Konstadina Griva c, Mohamed Amir c, Kok Joon Chong a, Yung Seng Lee d, Jeannette Lee a, Eric Yin-Hao Khoo a, 1, Hwee-Lin Wee e,⁎, 1 a
Department of Medicine, National University Health System, Singapore School of Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore c Department of Psychology, National University of Singapore, Singapore d Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore e Department of Pharmacy, National University of Singapore, Singapore b
a r t i c l e
i n f o
Article history: Received 21 July 2014 Received in revised form 19 December 2014 Accepted 17 January 2015 Available online xxxx Keywords: Type 2 diabetes mellitus Health-related quality of life Psychological distress Disinhibited eating Barriers to activity Behavioral impairment
a b s t r a c t Background: Data on psychological distress (DIS), behavioral impact (BI) and health-related quality of life (HRQoL) are important yet lacking among Asian patients with Type 2 diabetes mellitus (T2DM). We aim to identify factors associated with DIS, BI and HRQoL among T2DM to better understand patient needs. Methods: DIS was measured with Diabetes Health Profile (DHP-18) Psychological Distress (DHP-PD) subscale, Problem Areas in Diabetes (PAID) and Kessler-10 (K10), BI with DHP-18 Barriers to Activity and Disinhibited Eating subscales and HRQoL with Audit of Diabetes-Dependent Quality of Life. Multiple linear regression analyses were performed to evaluate the associations between these outcomes and patient demographic, socioeconomic status, glycated hemoglobin (HbA1C) and comorbidities. Results: 213 T2DM patients (mean (SD) age: 45.0 (12.1) years, mean (SD) HbA1C: 8.3% (1.9%) and 70.0% reported at least one comorbidity) were evaluated. Poorer glycemic control was significantly associated with higher DHP-PD, PAID and worse HRQoL. Taking oral hypoglycemic agents plus insulin was independently associated with Barrier to Activity and Disinhibited Eating. Conclusion: Poorer glycemic control was only associated with diabetes-related distress (measured by DHP-PD and PAID) but not major depressive disorder (measured by K10). It may be more appropriate to screen for diabetes-related distress rather than major depressive disorder for patients with T2DM. © 2015 Elsevier Inc. All rights reserved.
1. Introduction Diabetes Mellitus (DM) is a major cause of morbidity and mortality and imposes a significant economic burden on the national health care system worldwide (Zhang et al., 2010). The prevalence of DM in adults aged above 21 was estimated at 285 million worldwide in 2010 and is projected to increase to 439 million adults by 2030 (Shaw, Sicree, & Zimmet, 2010). Expenditure on the management of DM is expected to account for 12% of the world’s total health expenditure. In Singapore, the prevalence of DM in 2010 was 11.3% (Wielink, Essink-Bot, van
Disclosure: The authors report no conflict of interest in this work. ⁎ Corresponding author at: Department of Pharmacy, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore. Tel.: +65 6516 5530; fax: +65 6778 5698. E-mail address: [email protected] (H-L. Wee). 1 Contributed equally as joint senior authors.
Kerrebroeck, & Rutten, 1997), higher than most other countries of similar Gross Domestic Product (Sicree, 2009), and was the underlying cause of 1.0% of all deaths (Wielink et al., 1997). DM was also the 10th leading cause of hospitalisation in Singapore in 2012 (Bradley et al., 1999). Besides economic burden, DM also exerts significant psychological and behavioral impact on the individuals as effective management of DM requires the individuals to take their medications according to schedule, monitor their blood glucose regularly, have a balanced diet and exercise regularly. In addition, many individuals are concerned about developing short or long term complications associated with poor glycemic control. As such, psychological distress is common among patients with DM. The prevalence of psychological distress among patients with type 2 diabetes mellitus (T2DM) in Singapore was reported at 31.1% (Tan et al., 2015; Verma, 2010). In Australia, the prevalence of psychological distress among individuals with T2DM increased from 5.9% in 2001 to 7.0% in 2008 (Atlantis, Sullivan, Sartorius, & Almeida, 2012).
http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009 1056-8727/© 2015 Elsevier Inc. All rights reserved.
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
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M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
In addition to its negative impact on glycemic control (Fisher, Glasgow, & Strycker, 2010; Fisher et al., 2010), psychological distress may also impair health-related quality of life (HRQoL) (Pouwer, 2009). It is increasingly recognized that the assessment of HRQoL is important for evaluating treatment outcomes and patient needs as HRQoL is found to predict health services utilization and mortality (Dominick, Ahern, Gold, & Heller, 2002; Singh, Nelson, Fink, & Nichol, 2005; Sprenkle, Niewoehner, Nelson, & Nichol, 2004). In line with international interest in HRQoL, there have been several local publications that evaluated factors associated with poor HRQoL among Singaporeans with DM and these include presence of DM complications (Venkataraman et al., 2013), poor glycemic control (Shim, Lee, Toh, Tang, & Ko, 2012), being female, treatment with insulin and loss of freedom to eat (Wee, 2006). However, relatively little is known about factors that are associated with psychological distress and behavioral impact among patients with DM in Singapore. Hence, the main aim of this study is to identify factors associated with psychological distress and behavioral impact while the secondary aim is to contrast the factors identified against those factors that are associated with HRQoL in the same group of patients. 2. Subjects, materials and methods 2.1. Subjects and study design A longitudinal self-administered survey with three follow-ups was conducted at a single tertiary hospital in Singapore. Patients were recruited through direct contact in the waiting areas of the DM clinic in National University Hospital. This study utilizes the data on T2DM patients from the baseline interviews performed. All adult patients aged 21–64, who were diagnosed with T2DM for at least 1 year, literate in English and able to consent and comply with study protocol were included. Patients with significant cardiovascular disease such as unstable angina or recent coronary artery bypass, liver failure defined as transaminase N 3 times upper limit of normal and renal failure with creatinine N 130 μmmol/L were excluded. Individuals who had plans to emigrate, or were on treatment for psychological or psychiatric disorders were also excluded. Trained research staff explained the study, obtained written informed consent from patients and administered the study questionnaires to the patients in one-to-one interviews. Data on demographic factors were collected using self-administered questionnaires. Ethnic group was classified as Chinese, Malay, Asian Indian or Others. Marital status was classified as “single”, “married”, “divorced/separated” or widowed”. Education level was determined based on the number of schooling years and was categorized into b 7, 7– 10 and N10 years, reflecting primary, secondary and tertiary educational levels in Singapore. Comorbidities were based on self-reports and included retinopathy, cardiovascular disease, nephropathy, neuropathy, cerebrovascular disease, anemia, peripheral vascular disease, hepatic disease and renal disease. A sample survey question included “Has a doctor, a nurse, or healthcare professional told you that you have anemia (low red blood cell count)?”.
range of the population distribution (standard errors of standardized scores in the range 0.20±0.25) as well as consistent psychometric properties (Kessler, 2002). (2) Problem Areas in Diabetes (PAID) The PAID is a measure of diabetes-specific emotional distress that was developed by the Joslin Diabetes Center, Boston (Polonsky, 1995). This self-administered questionnaire consists of 20 items that cover a range of emotional problems frequently reported in both Type 1 DM (T1DM) and T2DM. Each item is scored 0 to 4 ("Not a problem" to "Serious Problem"). The sum of the 20 items is multiplied by 1.25 to yield a final score of 0–100. The PAID was positively correlated with HbA1c (Polonsky, 1995; Reddy, 2013; Tsujii, Hayashino, Ishii, & Diabetes, 2012) and has the ability to discriminate between those who were insulin treated from those who received oral medications (Welch, 1997). (3) Diabetes Health Profile (DHP-18) The DHP-18 (Meadows, 2010) is an adaptation of the original Diabetes Health Profile (DHP-1) (Meadows, 1996) for assessing the psychological and behavioral impact of living with diabetes in T2DM patients and contains 18 items (out of the original 32 items) comprising three subscales: psychological distress, barriers to activity and disinhibited eating. Barriers to activity and disinhibited eating are measures of the behavioral impact of DM on individuals. Items use a four-point Likert-type scale ranging from 0 to 3. The subscale scores are subsequently transformed to a common score range of 0 to 100, with a score of 0 representing no dysfunction and 100 representing maximum dysfunction. (4) The Audit of Diabetes-Dependent Quality of Life (ADDQoL) ADDQoL is a diabetes-specific quality of life instrument, designed to measure individuals’ perceptions of the impact of diabetes (both type 1 and type 2) on their quality of life(QoL) (Bradley, 1999). It contains two overview items and 19 domain specific items. The first overview item assesses QoL in general while the second item assesses diabetes-dependent QoL. For each of the domain-specific items, respondents are asked to provide both impact (range: − 3 [greatest negative impact] to + 1 [positive impact]) and importance (range: 0 [not at all important] to + 3 [very important]) ratings. The impact rating is multiplied by the importance rating to provide a weighted impact (WI) score, ranging from − 9 (maximum negative impact of DM) to + 3 (maximum positive impact of DM), for each domain. Five of the specific domains (working life, holidays, family life, close personal relationship and sex life) include a preliminary ‘Yes/No’ question to determine if the domains are applicable to the respondents and should be dropped from consideration if the domain is not applicable to them. The average weighted impact (AWI) score which reflects the impact of DM on QoL can be generated by averaging WI scores of all applicable domains (Bradley, 1999). The validity and reliability of ADDQoL were previously demonstrated in Singapore (Wee, 2006). 2.3. Biological measurements
2.2. Study Questionnaires (1) Kessler Psychological Distress Scale (K10) The K10 is a simple, generic measure of psychological distress employed in the World Mental Health Survey 2000 as well as annual government surveys in Australia and Canada. K10 uses a five-point Likert-type scale for each question that indicates the degree to which symptoms of distress are present among individuals. The 10 responses are added up and the maximum score of 50 indicates severe distress while the minimum score of 10 indicates no distress (Andrews, 2001). K10 has been shown to have good precision in the 90th to 99th percentile
Glycated Hemoblobin A1C (HbA1C) was measured in the hospital’s laboratory using high-performance liquid chromatography (HPLC) method. Patients’ height and weight were obtained from the patient’s paper and electronic medical records. Body Mass Index (BMI) was calculated using the formula (BMI = Weight (kg)/(Height (m)) 2. 3. Statistical analyses Individual items were imputed, summed and transformed as recommended in the DHP-18, PAID, K10 and ADDQOL user manuals (Anon, 2005; Bradley et al., 1999; Meadows, 2010; Polonsky, 1995).
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
Patients with missing DHP-18, PAID, K10 or ADDQoL scores were excluded list wise from the analysis. Mean and standard deviations were used to describe continuous variables while percentages were used to describe categorical variables. Multiple linear regression was carried out with the scores for each of the psychological distress instruments and ADDQOL as dependent variables in separate models and the following sociodemographic (age, marital status, education, ethnicity), socioeconomic (housing), and clinical (HbA1c, comorbidities, body mass index (BMI) and pharmacological treatment type (oral, insulin or combined)) variables as independent covariates. A p-value of ≤0.05 was used to indicate statistical significance in all analyses. All statistical analyses were performed using Stata 12.0 for Windows (Stata Corporation, College Station, Texas, USA).
4. Results A total of 213 patients diagnosed with T2DM fulfilled the inclusion criteria and provided complete data for analysis (Fig. 1). The socio-demographic characteristics and diabetes related comorbidities are shown in Table 1. The mean (SD) age of the patients was 45.0 (12.1) years. Majority of the participants were men (n = 135, 63.4%), and comprised of 106 (49.8%) Chinese, 24 (11.3%) Malay, 62 (29.1%) Indians and 21 (9.9%) other races. Seventy percent of respondents had HbA1c value N7.0% (indicating poor glycemic control), with a mean (SD) HbA1c of 8.3% (1.9%). Majority of patients (n = 149, 70.0%) reported at least one comorbidity. Having poorer glycemic control (increasing HbA1c) was significantly associated with PAID and DHP-18 Psychological Distress but
Fig. 1. Schematic representation of the study recruitment of patients with T2DM.
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Table 1 Demographic characteristics of patients with T2DM analyzed. Demographics Gender Male Female Age (Years) Ethnicity Chinese Malay Asian Indian Other Marital Status Single Married Divorced/Separated Widowed Household Income (SGD) b500 b2000 2000 to 3999 4000 to 5999 N6000 Housing Type Small public housing Large public housing Private housing Educational Status b7 years 7–10 years N10 years Living Status Living alone Living with family Duration of Known Diabetes (Years) Comorbidities None At least one Breakdown: Retinopathy Cardiovascular Disease Nephropathy Neuropathy Cerebrovascular Disease Anemia Peripheral Vascular Disease Hepatic Renal Hypertension Yes No Hyperlipidemia Yes No Pharmacological Treatment Oral Insulin Combined (oral and insulin) Body Mass Index (kg/m2) HbA1C (%) Smoking History Non smoker Previous Smoker Current Smoker
N
(%)
135 78
63.4 36.6
106 24 62 21
49.8 11.3 29.1 9.9
45 132 12 8
22.8 67.0 6.1 4.1
5 24 47 37 58
2.9 14.0 27.5 21.6 33.9
91 64 42
46.2 32.5 21.3
16 67 115
8.1 33.8 58.1
8 187
4.1 95.9
64 149
30.0 70.0
28 27 17 14 12 13 6 5 1
13.2 12.7 8.0 6.6 5.6 6.1 2.8 2.4 0.5
99 114
46.5 53.5
110 103
51.6 48.4
122 7 75
59.8 3.4 36.8
139 24 29
Mean
SD
45.0
12.1
9.3
7.6
29.1 8.3
5.5 1.9
72.4 12.5 15.1
not K10 (Table 2). Being older was also significantly associated with higher PAID scores (p=0.038). Females and those living in private housing were significantly associated with higher distress scores on K10 (p=0.029 and p=0.048 respectively) but not the other two measures of psychological distress. Taking combined oral medications and insulin treatment was significantly associated with DHP-18 Barriers to Activity (p=0.003) and DHP-18 Disinhibited Eating (p= 0.012). Poorer glycemic control was the only factor associated with poor HRQoL (Table 3).
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
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M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
Table 2 Association between sociodemographic, socioeconomic and clinical factors and psychological distress measured using DHP-18, PAID and K10. K10 Co-variates Gender Male Female Age (Years) Ethnicity Chinese Malay Asian Indian Other Marital Status Single Married Divorced/Separated Widowed Housing Type Small public housing Large public housing Private housing Educational Status b7 years 7–10 years N10 years Living status Living alone Living with family Duration of Known Diabetes (Years) Pharmacological treatment Oral Insulin Combined (oral and insulin) Body Mass Index (kg/m2) HbA1C (%) Comorbidities Yes No
PAID
βK10
p
βPAID
6.08 −0.15
0.029 0.313
0.40 −0.38
0.29 −2.80 −3.03
0.947 0.381 0.504
3.55 1.18 1.45
DHP-18 βDHP_PD
p
βDHP_BTA
p
βDHP_DE
p
0.903 0.038
1.18 −0.10
0.717 0.557
2.62 −0.13
0.392 0.432
0.96 −0.20
0.728 0.19
1.54 −2.49 3.81
0.771 0.516 0.484
3.04 −1.81 3.19
0.555 0.629 0.55
0.37 −5.00 −3.66
0.94 0.157 0.464
−1.96 −4.13 −1.72
0.654 0.196 0.703
0.414 0.863 0.861
7.99 0.80 8.86
0.128 0.922 0.373
3.83 −1.26 −4.43
0.455 0.876 0.649
5.31 −1.47 −2.16
0.27 0.847 0.813
2.93 −3.81 −1.23
0.499 0.579 0.881
−1.97 −7.74
0.531 0.048
3.04 −2.84
0.422 0.545
2.74 1.35
0.46 0.768
−1.18 −5.47
0.734 0.206
−0.56 −4.64
0.858 0.234
6.62 3.54
0.236 0.537
6.95 1.62
0.301 0.814
4.45 −2.34
0.499 0.729
−5.13 −6.70
0.406 0.291
2.31 3.12
0.679 0.586
0.15 0.15
−2.43 0.00
0.754 0.798
−6.68 0.00
0.379 0.889
−1.76 0.00
0.805 0.904
−8.65 0.00
0.18 0.806
2.27 2.22 0.16 1.48
0.742 0.485 0.519 0.081
−2.64 −1.55 0.24 3.94
0.751 0.684 0.433 b0.0001
10.37 6.15 0.53 2.85
0.204 0.101 0.074 0.005
12.71 10.63 0.11 1.39
0.098 0.003 0.677 0.137
−3.70 8.05 0.26 1.09
0.593 0.012 0.29 0.197
−1.69
0.607
5.50
0.166
2.52
0.515
0.57
0.876
−1.26
0.701
−9.31 −0.01
p
p-value of ≤0.05 was used to indicate statistical significance (bolded).
In a post-hoc analysis, we investigated if psychological distress was a potential mediator of the relationship between poorer glycemic control and HRQoL. The relationship between poorer glycemic control and HRQoL was no longer significant when PAID score was included as an independent variable. Likewise, the relationship between poorer glycemic control and HRQoL was no longer significant when K10 score was included as an independent variable. 5. Discussion In this first study to evaluate factors associated with psychological distress, behavioral impact and HRQoL among T2DM patients in Singapore, we found that poor glycemic control was associated with diabetes-related distress (DRD, measured with PAID and DHP-PD) and HRQoL but not major depressive disorder (MDD, measured by K10), barriers to activities and disinhibited eating, a specific aspect of the behavioral impact of DM. In addition, we found that psychological distress was a mediator of the relationship between poor glycemic control and HRQoL. In the context of diabetes, it has been shown that two forms of distress exist — major depressive disorder and diabetes-related distress. MDD is associated with clinical depression, encompassing sadness, frustration, anxiety, and a number of other negative mood states. It includes both mild and severe forms of these mood states, which may be transient or persistent (Carney & Freedland, 2002). DRD is conceptualized as distress due to the burden of living with the chronic disease such as difficulties coping with social situations (with healthcare providers, family and/or friends), treatment regimen and diet (Peyrot et al., 2005). Our study results, which showed that poorer
glycemic control is only associated to DRD and not MDD, reinforced the findings from the literature (Fisher, Glasgow, & Strycker, 2010; Fisher, Mullan, et al., 2010) and suggest that it might be more appropriate to screen for DRD in clinical practice for patients with T2DM rather than MDD (Hermanns, Kubiak, Kulzer, & Haak, 2007). While the physiological mechanism by which DRD affects glycemic control is not clear, studies have suggested that the effect of DRD on glycemic control may be via alterations in health care behavior such as reduced physical activity, poor diet, and lack of adherence to medication (Albright, Parchman, & Burge, 2001; Lin et al., 2004) which subsequently contribute to increased visceral adiposity and increased insulin resistance (Björntorp, 1991), thereby worsening the glycemic control of diabetes. As most of the current literature on physiological mechanisms has focused on MDD, more research is required to have a better understanding of the physiological mechanism by which DRD affects glycemic control but this is not the focus of the present study. In this study, while we believe that the relationship between DRD and poorer glycemic control is influenced by both physiological and behavioral components, there appears to be little association between DRD and the socio-demographic, economic, behavioral or pharmacologic variables captured other than age, gender, housing type and combination therapy. Hence, we re-iterate that a better understanding of the physiological mechanism between DRD and glycemic control is warranted. We have also observed that taking combined oral medications and insulin treatment was significantly associated with DHP-18 Barriers to Activity and Disinhibited Eating, independent of poorer glycemic control. These observations are not surprising as 1) a multi-national
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx Table 3 Association between sociodemographic, socioeconomic and clinical factors and health-related quality of life measured using ADDQoL. Co-variates Gender Male Female Age (Years) Ethnicity Chinese Malay Asian Indian Other Marital Status Single Married Divorced/Separated Widowed Housing Type Small public housing Large public housing Private housing Educational Status b7 years 7–10 years N10 years Living status Living alone Living with family Duration of Known Diabetes (Years) Pharmacologic treatment Oral Insulin Combined (oral and insulin) Body Mass Index (kg/m2) HbA1C (%) Comorbidities Yes No
βADDQoL
p-value
2.68 −0.16
0.347 0.306
5.01 2.08 5.15
0.266 0.526 0.269
3.94 2.62 −3.14
0.377 0.711 0.711
2.67 −2.27
0.41 0.571
−1.91 −9.55
0.739 0.106
−3.90 0.00
0.556 0.596
1.23 4.78 0.38 1.83
0.863 0.144 0.134 0.036
4.45
0.189
5
While this study presents important findings, we noted that there are limitations. Firstly, as this is a cross-sectional study, the causal relationship between poor glycemic control and DRD or HRQoL cannot be determined. However, we are collecting longitudinal data on these patients at 6- and 12-month post baseline assessment, which would hopefully clarify the causal relationship. Secondly, further studies are needed to determine if there may be other factors associated with psychological distress, barriers to activity, disinhibited eating and HRQoL in the non-English speaking T2DM population. Nonetheless, similar to the study by Shim et al. (2012), our study did not find any association between HRQoL and comorbidities. Thirdly, as this study was conducted in the hospital setting, the findings may not be applicable to the community setting. Fourth, as comorbidities were based on self-reports, we were unable to conduct a detailed analysis on the association between severity of comorbidity and HRQoL. 6. Conclusion
p-value of ≤0.05 was used to indicate statistical significance (bolded).
study has found that patients with more barriers to adherence, which include travelling, work, change mealtime, sports, change routine, exercise/leisure, tired/weary, weekends, etc, were more likely to be non-adherent to insulin treatment (Peyrot, Barnett, Meneghini, & Schumm-Draeger, 2012); and 2) two previous studies in the local population found that dietary freedom or the lack thereof is a major concern among both English and Chinese-speaking T2DM patients (Soon et al., 2010; Wee, Tan, Goh, & Li, 2006). However, taking combined oral medications and insulin treatment was not significantly associated with HRQoL. This suggests that even with a disease-specific HRQoL measure which assesses the impact of DM on multidimensional (physical, mental and social) aspects of life, it is still possible to miss out certain details since there are a limited number of items available to measure each specific sub-domain. Hence, the supplementation of HRQoL measures with sub-domain-specific measures may be necessary, depending on the study objectives. An important strength of this study lies in the use of three psychological distress measures (both MDD and DRD) and the consistent finding across the three measures. The observation that women were more likely to be distressed on the K10, and not other measures, suggests that women are experiencing other sources of distress that are not related to DM, for which improvement in glycemic control alone may not be sufficient to address. As mentioned in the introduction, psychological distress is a two-dimensional continuous construct and a consideration of both severity and the sources of stressors is important in the management of psychological distress among patients with diabetes. This is an important point for health care providers to take note. Another strength of this study is the multi-ethnic nature of the sample. It is encouraging to note that ethnicity was not a factor associated with psychological distress, barriers to activity, disinhibited eating and HRQoL.
In conclusion, glycemic control was the only factor associated with higher diabetes-related distress and impaired HRQoL. Helping patients achieve their target HbA1C level in a way that does not simultaneously worsen diabetes-related distress and HRQoL is clearly critical. While this has been shown to be an uphill task, further innovations in both pharmacological treatments as well as behavioral interventions are urgently required. Finally, taking combined oral medications and insulin treatment was significantly associated with barriers to activity and disinhibited eating, independent of poor glycemic control. Acknowledgments This work was partly supported by a Final Year Project grant from the Department of Pharmacy, Faculty of Science, National University of Singapore and largely supported by the Ministry of Education Singapore Academic Research Fund Tier 1 (Grant No.: FY2011-FRC3-007). References Albright, T. L., Parchman, M., & Burge, S. K. (2001). Predictors of self-care behavior in adults with type 2 diabetes: An RRNeST study. Family Medicine, 33, 354–360. Andrews, G. (2001). Interpreting scores on the Kessler Psychological Distress Scale (K10). Australian and New Zealand journal of public health, 25, 494–497. Australian Mental Health Outcomes and Classification Network: Kessler-10 training manual. Commonwealth of Australia 2005(2005).. NSW Institute of Psychiatry. Atlantis, E., Sullivan, T., Sartorius, N., & Almeida, O. P. (2012). Changes in the prevalence of psychological distress and use of antidepressants or anti-anxiety medications associated with comorbid chronic diseases in the adult Australian population, 2001–2008. The Australian and New Zealand Journal of Psychiatry, 46, 445–456. Björntorp, P. (1991). Visceral fat accumulation: The missing link between psychological factors and cardiovascular disease? Journal of Internal Medicine, 230, 195–201. Bradley, C. (1999). The development of an individualized questionnaire measure of perceived impact of diabetes on quality of life: The ADDQoL. Quality of Life Research, 8, 79–91. Bradley, C., Todd, C., Gorton, T., Symonds, E., Martin, A., & Plowright, R. (1999). The development of an individualized questionnaire measure of perceived impact of diabetes on quality of life: The ADDQoL. Quality of Life Research, 8, 79–91. Carney, R. M., & Freedland, K. E. (2002). Psychological distress as a risk factor for strokerelated mortality. Stroke, 33, 5–6. Dominick, K. L., Ahern, F. M., Gold, C. H., & Heller, D. A. (2002). Relationship of healthrelated quality of life to health care utilization and mortality among older adults. Aging Clinical and Experimental Research, 14, 499–508. Fisher, L., Glasgow, R. E., & Strycker, L. A. (2010). The relationship between diabetes distress and clinical depression with glycemic control among patients with type 2 diabetes. Diabetes Care, 33, 1034–1036. Fisher, L., Mullan, J. T., Arean, P., Glasgow, R. E., Hessler, D., & Masharani, U. (2010). Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses. Diabetes Care, 33, 23–28. Hermanns, N., Kubiak, T., Kulzer, B., & Haak, T. (2007). Clinical depression versus distress among patients with type 2 diabetes: Not just a question of semantics. Diabetes Care, 30(9), e100 (author reply e101 2007). Kessler, R. C. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32, 959–976.
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
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Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
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Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus Michelle Ang Co a, Luor Shyuan Maudrene Tan b, E Shyong Tai a, b, Konstadina Griva c, Mohamed Amir c, Kok Joon Chong a, Yung Seng Lee d, Jeannette Lee a, Eric Yin-Hao Khoo a, 1, Hwee-Lin Wee e,⁎, 1 a
Department of Medicine, National University Health System, Singapore School of Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore c Department of Psychology, National University of Singapore, Singapore d Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore e Department of Pharmacy, National University of Singapore, Singapore b
a r t i c l e
i n f o
Article history: Received 21 July 2014 Received in revised form 19 December 2014 Accepted 17 January 2015 Available online xxxx Keywords: Type 2 diabetes mellitus Health-related quality of life Psychological distress Disinhibited eating Barriers to activity Behavioral impairment
a b s t r a c t Background: Data on psychological distress (DIS), behavioral impact (BI) and health-related quality of life (HRQoL) are important yet lacking among Asian patients with Type 2 diabetes mellitus (T2DM). We aim to identify factors associated with DIS, BI and HRQoL among T2DM to better understand patient needs. Methods: DIS was measured with Diabetes Health Profile (DHP-18) Psychological Distress (DHP-PD) subscale, Problem Areas in Diabetes (PAID) and Kessler-10 (K10), BI with DHP-18 Barriers to Activity and Disinhibited Eating subscales and HRQoL with Audit of Diabetes-Dependent Quality of Life. Multiple linear regression analyses were performed to evaluate the associations between these outcomes and patient demographic, socioeconomic status, glycated hemoglobin (HbA1C) and comorbidities. Results: 213 T2DM patients (mean (SD) age: 45.0 (12.1) years, mean (SD) HbA1C: 8.3% (1.9%) and 70.0% reported at least one comorbidity) were evaluated. Poorer glycemic control was significantly associated with higher DHP-PD, PAID and worse HRQoL. Taking oral hypoglycemic agents plus insulin was independently associated with Barrier to Activity and Disinhibited Eating. Conclusion: Poorer glycemic control was only associated with diabetes-related distress (measured by DHP-PD and PAID) but not major depressive disorder (measured by K10). It may be more appropriate to screen for diabetes-related distress rather than major depressive disorder for patients with T2DM. © 2015 Elsevier Inc. All rights reserved.
1. Introduction Diabetes Mellitus (DM) is a major cause of morbidity and mortality and imposes a significant economic burden on the national health care system worldwide (Zhang et al., 2010). The prevalence of DM in adults aged above 21 was estimated at 285 million worldwide in 2010 and is projected to increase to 439 million adults by 2030 (Shaw, Sicree, & Zimmet, 2010). Expenditure on the management of DM is expected to account for 12% of the world’s total health expenditure. In Singapore, the prevalence of DM in 2010 was 11.3% (Wielink, Essink-Bot, van
Disclosure: The authors report no conflict of interest in this work. ⁎ Corresponding author at: Department of Pharmacy, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore. Tel.: +65 6516 5530; fax: +65 6778 5698. E-mail address: [email protected] (H-L. Wee). 1 Contributed equally as joint senior authors.
Kerrebroeck, & Rutten, 1997), higher than most other countries of similar Gross Domestic Product (Sicree, 2009), and was the underlying cause of 1.0% of all deaths (Wielink et al., 1997). DM was also the 10th leading cause of hospitalisation in Singapore in 2012 (Bradley et al., 1999). Besides economic burden, DM also exerts significant psychological and behavioral impact on the individuals as effective management of DM requires the individuals to take their medications according to schedule, monitor their blood glucose regularly, have a balanced diet and exercise regularly. In addition, many individuals are concerned about developing short or long term complications associated with poor glycemic control. As such, psychological distress is common among patients with DM. The prevalence of psychological distress among patients with type 2 diabetes mellitus (T2DM) in Singapore was reported at 31.1% (Tan et al., 2015; Verma, 2010). In Australia, the prevalence of psychological distress among individuals with T2DM increased from 5.9% in 2001 to 7.0% in 2008 (Atlantis, Sullivan, Sartorius, & Almeida, 2012).
http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009 1056-8727/© 2015 Elsevier Inc. All rights reserved.
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
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M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
In addition to its negative impact on glycemic control (Fisher, Glasgow, & Strycker, 2010; Fisher et al., 2010), psychological distress may also impair health-related quality of life (HRQoL) (Pouwer, 2009). It is increasingly recognized that the assessment of HRQoL is important for evaluating treatment outcomes and patient needs as HRQoL is found to predict health services utilization and mortality (Dominick, Ahern, Gold, & Heller, 2002; Singh, Nelson, Fink, & Nichol, 2005; Sprenkle, Niewoehner, Nelson, & Nichol, 2004). In line with international interest in HRQoL, there have been several local publications that evaluated factors associated with poor HRQoL among Singaporeans with DM and these include presence of DM complications (Venkataraman et al., 2013), poor glycemic control (Shim, Lee, Toh, Tang, & Ko, 2012), being female, treatment with insulin and loss of freedom to eat (Wee, 2006). However, relatively little is known about factors that are associated with psychological distress and behavioral impact among patients with DM in Singapore. Hence, the main aim of this study is to identify factors associated with psychological distress and behavioral impact while the secondary aim is to contrast the factors identified against those factors that are associated with HRQoL in the same group of patients. 2. Subjects, materials and methods 2.1. Subjects and study design A longitudinal self-administered survey with three follow-ups was conducted at a single tertiary hospital in Singapore. Patients were recruited through direct contact in the waiting areas of the DM clinic in National University Hospital. This study utilizes the data on T2DM patients from the baseline interviews performed. All adult patients aged 21–64, who were diagnosed with T2DM for at least 1 year, literate in English and able to consent and comply with study protocol were included. Patients with significant cardiovascular disease such as unstable angina or recent coronary artery bypass, liver failure defined as transaminase N 3 times upper limit of normal and renal failure with creatinine N 130 μmmol/L were excluded. Individuals who had plans to emigrate, or were on treatment for psychological or psychiatric disorders were also excluded. Trained research staff explained the study, obtained written informed consent from patients and administered the study questionnaires to the patients in one-to-one interviews. Data on demographic factors were collected using self-administered questionnaires. Ethnic group was classified as Chinese, Malay, Asian Indian or Others. Marital status was classified as “single”, “married”, “divorced/separated” or widowed”. Education level was determined based on the number of schooling years and was categorized into b 7, 7– 10 and N10 years, reflecting primary, secondary and tertiary educational levels in Singapore. Comorbidities were based on self-reports and included retinopathy, cardiovascular disease, nephropathy, neuropathy, cerebrovascular disease, anemia, peripheral vascular disease, hepatic disease and renal disease. A sample survey question included “Has a doctor, a nurse, or healthcare professional told you that you have anemia (low red blood cell count)?”.
range of the population distribution (standard errors of standardized scores in the range 0.20±0.25) as well as consistent psychometric properties (Kessler, 2002). (2) Problem Areas in Diabetes (PAID) The PAID is a measure of diabetes-specific emotional distress that was developed by the Joslin Diabetes Center, Boston (Polonsky, 1995). This self-administered questionnaire consists of 20 items that cover a range of emotional problems frequently reported in both Type 1 DM (T1DM) and T2DM. Each item is scored 0 to 4 ("Not a problem" to "Serious Problem"). The sum of the 20 items is multiplied by 1.25 to yield a final score of 0–100. The PAID was positively correlated with HbA1c (Polonsky, 1995; Reddy, 2013; Tsujii, Hayashino, Ishii, & Diabetes, 2012) and has the ability to discriminate between those who were insulin treated from those who received oral medications (Welch, 1997). (3) Diabetes Health Profile (DHP-18) The DHP-18 (Meadows, 2010) is an adaptation of the original Diabetes Health Profile (DHP-1) (Meadows, 1996) for assessing the psychological and behavioral impact of living with diabetes in T2DM patients and contains 18 items (out of the original 32 items) comprising three subscales: psychological distress, barriers to activity and disinhibited eating. Barriers to activity and disinhibited eating are measures of the behavioral impact of DM on individuals. Items use a four-point Likert-type scale ranging from 0 to 3. The subscale scores are subsequently transformed to a common score range of 0 to 100, with a score of 0 representing no dysfunction and 100 representing maximum dysfunction. (4) The Audit of Diabetes-Dependent Quality of Life (ADDQoL) ADDQoL is a diabetes-specific quality of life instrument, designed to measure individuals’ perceptions of the impact of diabetes (both type 1 and type 2) on their quality of life(QoL) (Bradley, 1999). It contains two overview items and 19 domain specific items. The first overview item assesses QoL in general while the second item assesses diabetes-dependent QoL. For each of the domain-specific items, respondents are asked to provide both impact (range: − 3 [greatest negative impact] to + 1 [positive impact]) and importance (range: 0 [not at all important] to + 3 [very important]) ratings. The impact rating is multiplied by the importance rating to provide a weighted impact (WI) score, ranging from − 9 (maximum negative impact of DM) to + 3 (maximum positive impact of DM), for each domain. Five of the specific domains (working life, holidays, family life, close personal relationship and sex life) include a preliminary ‘Yes/No’ question to determine if the domains are applicable to the respondents and should be dropped from consideration if the domain is not applicable to them. The average weighted impact (AWI) score which reflects the impact of DM on QoL can be generated by averaging WI scores of all applicable domains (Bradley, 1999). The validity and reliability of ADDQoL were previously demonstrated in Singapore (Wee, 2006). 2.3. Biological measurements
2.2. Study Questionnaires (1) Kessler Psychological Distress Scale (K10) The K10 is a simple, generic measure of psychological distress employed in the World Mental Health Survey 2000 as well as annual government surveys in Australia and Canada. K10 uses a five-point Likert-type scale for each question that indicates the degree to which symptoms of distress are present among individuals. The 10 responses are added up and the maximum score of 50 indicates severe distress while the minimum score of 10 indicates no distress (Andrews, 2001). K10 has been shown to have good precision in the 90th to 99th percentile
Glycated Hemoblobin A1C (HbA1C) was measured in the hospital’s laboratory using high-performance liquid chromatography (HPLC) method. Patients’ height and weight were obtained from the patient’s paper and electronic medical records. Body Mass Index (BMI) was calculated using the formula (BMI = Weight (kg)/(Height (m)) 2. 3. Statistical analyses Individual items were imputed, summed and transformed as recommended in the DHP-18, PAID, K10 and ADDQOL user manuals (Anon, 2005; Bradley et al., 1999; Meadows, 2010; Polonsky, 1995).
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
Patients with missing DHP-18, PAID, K10 or ADDQoL scores were excluded list wise from the analysis. Mean and standard deviations were used to describe continuous variables while percentages were used to describe categorical variables. Multiple linear regression was carried out with the scores for each of the psychological distress instruments and ADDQOL as dependent variables in separate models and the following sociodemographic (age, marital status, education, ethnicity), socioeconomic (housing), and clinical (HbA1c, comorbidities, body mass index (BMI) and pharmacological treatment type (oral, insulin or combined)) variables as independent covariates. A p-value of ≤0.05 was used to indicate statistical significance in all analyses. All statistical analyses were performed using Stata 12.0 for Windows (Stata Corporation, College Station, Texas, USA).
4. Results A total of 213 patients diagnosed with T2DM fulfilled the inclusion criteria and provided complete data for analysis (Fig. 1). The socio-demographic characteristics and diabetes related comorbidities are shown in Table 1. The mean (SD) age of the patients was 45.0 (12.1) years. Majority of the participants were men (n = 135, 63.4%), and comprised of 106 (49.8%) Chinese, 24 (11.3%) Malay, 62 (29.1%) Indians and 21 (9.9%) other races. Seventy percent of respondents had HbA1c value N7.0% (indicating poor glycemic control), with a mean (SD) HbA1c of 8.3% (1.9%). Majority of patients (n = 149, 70.0%) reported at least one comorbidity. Having poorer glycemic control (increasing HbA1c) was significantly associated with PAID and DHP-18 Psychological Distress but
Fig. 1. Schematic representation of the study recruitment of patients with T2DM.
3
Table 1 Demographic characteristics of patients with T2DM analyzed. Demographics Gender Male Female Age (Years) Ethnicity Chinese Malay Asian Indian Other Marital Status Single Married Divorced/Separated Widowed Household Income (SGD) b500 b2000 2000 to 3999 4000 to 5999 N6000 Housing Type Small public housing Large public housing Private housing Educational Status b7 years 7–10 years N10 years Living Status Living alone Living with family Duration of Known Diabetes (Years) Comorbidities None At least one Breakdown: Retinopathy Cardiovascular Disease Nephropathy Neuropathy Cerebrovascular Disease Anemia Peripheral Vascular Disease Hepatic Renal Hypertension Yes No Hyperlipidemia Yes No Pharmacological Treatment Oral Insulin Combined (oral and insulin) Body Mass Index (kg/m2) HbA1C (%) Smoking History Non smoker Previous Smoker Current Smoker
N
(%)
135 78
63.4 36.6
106 24 62 21
49.8 11.3 29.1 9.9
45 132 12 8
22.8 67.0 6.1 4.1
5 24 47 37 58
2.9 14.0 27.5 21.6 33.9
91 64 42
46.2 32.5 21.3
16 67 115
8.1 33.8 58.1
8 187
4.1 95.9
64 149
30.0 70.0
28 27 17 14 12 13 6 5 1
13.2 12.7 8.0 6.6 5.6 6.1 2.8 2.4 0.5
99 114
46.5 53.5
110 103
51.6 48.4
122 7 75
59.8 3.4 36.8
139 24 29
Mean
SD
45.0
12.1
9.3
7.6
29.1 8.3
5.5 1.9
72.4 12.5 15.1
not K10 (Table 2). Being older was also significantly associated with higher PAID scores (p=0.038). Females and those living in private housing were significantly associated with higher distress scores on K10 (p=0.029 and p=0.048 respectively) but not the other two measures of psychological distress. Taking combined oral medications and insulin treatment was significantly associated with DHP-18 Barriers to Activity (p=0.003) and DHP-18 Disinhibited Eating (p= 0.012). Poorer glycemic control was the only factor associated with poor HRQoL (Table 3).
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
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M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx
Table 2 Association between sociodemographic, socioeconomic and clinical factors and psychological distress measured using DHP-18, PAID and K10. K10 Co-variates Gender Male Female Age (Years) Ethnicity Chinese Malay Asian Indian Other Marital Status Single Married Divorced/Separated Widowed Housing Type Small public housing Large public housing Private housing Educational Status b7 years 7–10 years N10 years Living status Living alone Living with family Duration of Known Diabetes (Years) Pharmacological treatment Oral Insulin Combined (oral and insulin) Body Mass Index (kg/m2) HbA1C (%) Comorbidities Yes No
PAID
βK10
p
βPAID
6.08 −0.15
0.029 0.313
0.40 −0.38
0.29 −2.80 −3.03
0.947 0.381 0.504
3.55 1.18 1.45
DHP-18 βDHP_PD
p
βDHP_BTA
p
βDHP_DE
p
0.903 0.038
1.18 −0.10
0.717 0.557
2.62 −0.13
0.392 0.432
0.96 −0.20
0.728 0.19
1.54 −2.49 3.81
0.771 0.516 0.484
3.04 −1.81 3.19
0.555 0.629 0.55
0.37 −5.00 −3.66
0.94 0.157 0.464
−1.96 −4.13 −1.72
0.654 0.196 0.703
0.414 0.863 0.861
7.99 0.80 8.86
0.128 0.922 0.373
3.83 −1.26 −4.43
0.455 0.876 0.649
5.31 −1.47 −2.16
0.27 0.847 0.813
2.93 −3.81 −1.23
0.499 0.579 0.881
−1.97 −7.74
0.531 0.048
3.04 −2.84
0.422 0.545
2.74 1.35
0.46 0.768
−1.18 −5.47
0.734 0.206
−0.56 −4.64
0.858 0.234
6.62 3.54
0.236 0.537
6.95 1.62
0.301 0.814
4.45 −2.34
0.499 0.729
−5.13 −6.70
0.406 0.291
2.31 3.12
0.679 0.586
0.15 0.15
−2.43 0.00
0.754 0.798
−6.68 0.00
0.379 0.889
−1.76 0.00
0.805 0.904
−8.65 0.00
0.18 0.806
2.27 2.22 0.16 1.48
0.742 0.485 0.519 0.081
−2.64 −1.55 0.24 3.94
0.751 0.684 0.433 b0.0001
10.37 6.15 0.53 2.85
0.204 0.101 0.074 0.005
12.71 10.63 0.11 1.39
0.098 0.003 0.677 0.137
−3.70 8.05 0.26 1.09
0.593 0.012 0.29 0.197
−1.69
0.607
5.50
0.166
2.52
0.515
0.57
0.876
−1.26
0.701
−9.31 −0.01
p
p-value of ≤0.05 was used to indicate statistical significance (bolded).
In a post-hoc analysis, we investigated if psychological distress was a potential mediator of the relationship between poorer glycemic control and HRQoL. The relationship between poorer glycemic control and HRQoL was no longer significant when PAID score was included as an independent variable. Likewise, the relationship between poorer glycemic control and HRQoL was no longer significant when K10 score was included as an independent variable. 5. Discussion In this first study to evaluate factors associated with psychological distress, behavioral impact and HRQoL among T2DM patients in Singapore, we found that poor glycemic control was associated with diabetes-related distress (DRD, measured with PAID and DHP-PD) and HRQoL but not major depressive disorder (MDD, measured by K10), barriers to activities and disinhibited eating, a specific aspect of the behavioral impact of DM. In addition, we found that psychological distress was a mediator of the relationship between poor glycemic control and HRQoL. In the context of diabetes, it has been shown that two forms of distress exist — major depressive disorder and diabetes-related distress. MDD is associated with clinical depression, encompassing sadness, frustration, anxiety, and a number of other negative mood states. It includes both mild and severe forms of these mood states, which may be transient or persistent (Carney & Freedland, 2002). DRD is conceptualized as distress due to the burden of living with the chronic disease such as difficulties coping with social situations (with healthcare providers, family and/or friends), treatment regimen and diet (Peyrot et al., 2005). Our study results, which showed that poorer
glycemic control is only associated to DRD and not MDD, reinforced the findings from the literature (Fisher, Glasgow, & Strycker, 2010; Fisher, Mullan, et al., 2010) and suggest that it might be more appropriate to screen for DRD in clinical practice for patients with T2DM rather than MDD (Hermanns, Kubiak, Kulzer, & Haak, 2007). While the physiological mechanism by which DRD affects glycemic control is not clear, studies have suggested that the effect of DRD on glycemic control may be via alterations in health care behavior such as reduced physical activity, poor diet, and lack of adherence to medication (Albright, Parchman, & Burge, 2001; Lin et al., 2004) which subsequently contribute to increased visceral adiposity and increased insulin resistance (Björntorp, 1991), thereby worsening the glycemic control of diabetes. As most of the current literature on physiological mechanisms has focused on MDD, more research is required to have a better understanding of the physiological mechanism by which DRD affects glycemic control but this is not the focus of the present study. In this study, while we believe that the relationship between DRD and poorer glycemic control is influenced by both physiological and behavioral components, there appears to be little association between DRD and the socio-demographic, economic, behavioral or pharmacologic variables captured other than age, gender, housing type and combination therapy. Hence, we re-iterate that a better understanding of the physiological mechanism between DRD and glycemic control is warranted. We have also observed that taking combined oral medications and insulin treatment was significantly associated with DHP-18 Barriers to Activity and Disinhibited Eating, independent of poorer glycemic control. These observations are not surprising as 1) a multi-national
Please cite this article as: Co, M.A., et al., Factors associated with psychological distress, behavioral impact and health-related quality of life among patients with type 2 diabetes mellitus, Journal of Diabetes and Its Complications (2015), http://dx.doi.org/10.1016/j.jdiacomp.2015.01.009
M.A. Co et al. / Journal of Diabetes and Its Complications xxx (2015) xxx–xxx Table 3 Association between sociodemographic, socioeconomic and clinical factors and health-related quality of life measured using ADDQoL. Co-variates Gender Male Female Age (Years) Ethnicity Chinese Malay Asian Indian Other Marital Status Single Married Divorced/Separated Widowed Housing Type Small public housing Large public housing Private housing Educational Status b7 years 7–10 years N10 years Living status Living alone Living with family Duration of Known Diabetes (Years) Pharmacologic treatment Oral Insulin Combined (oral and insulin) Body Mass Index (kg/m2) HbA1C (%) Comorbidities Yes No
βADDQoL
p-value
2.68 −0.16
0.347 0.306
5.01 2.08 5.15
0.266 0.526 0.269
3.94 2.62 −3.14
0.377 0.711 0.711
2.67 −2.27
0.41 0.571
−1.91 −9.55
0.739 0.106
−3.90 0.00
0.556 0.596
1.23 4.78 0.38 1.83
0.863 0.144 0.134 0.036
4.45
0.189
5
While this study presents important findings, we noted that there are limitations. Firstly, as this is a cross-sectional study, the causal relationship between poor glycemic control and DRD or HRQoL cannot be determined. However, we are collecting longitudinal data on these patients at 6- and 12-month post baseline assessment, which would hopefully clarify the causal relationship. Secondly, further studies are needed to determine if there may be other factors associated with psychological distress, barriers to activity, disinhibited eating and HRQoL in the non-English speaking T2DM population. Nonetheless, similar to the study by Shim et al. (2012), our study did not find any association between HRQoL and comorbidities. Thirdly, as this study was conducted in the hospital setting, the findings may not be applicable to the community setting. Fourth, as comorbidities were based on self-reports, we were unable to conduct a detailed analysis on the association between severity of comorbidity and HRQoL. 6. Conclusion
p-value of ≤0.05 was used to indicate statistical significance (bolded).
study has found that patients with more barriers to adherence, which include travelling, work, change mealtime, sports, change routine, exercise/leisure, tired/weary, weekends, etc, were more likely to be non-adherent to insulin treatment (Peyrot, Barnett, Meneghini, & Schumm-Draeger, 2012); and 2) two previous studies in the local population found that dietary freedom or the lack thereof is a major concern among both English and Chinese-speaking T2DM patients (Soon et al., 2010; Wee, Tan, Goh, & Li, 2006). However, taking combined oral medications and insulin treatment was not significantly associated with HRQoL. This suggests that even with a disease-specific HRQoL measure which assesses the impact of DM on multidimensional (physical, mental and social) aspects of life, it is still possible to miss out certain details since there are a limited number of items available to measure each specific sub-domain. Hence, the supplementation of HRQoL measures with sub-domain-specific measures may be necessary, depending on the study objectives. An important strength of this study lies in the use of three psychological distress measures (both MDD and DRD) and the consistent finding across the three measures. The observation that women were more likely to be distressed on the K10, and not other measures, suggests that women are experiencing other sources of distress that are not related to DM, for which improvement in glycemic control alone may not be sufficient to address. As mentioned in the introduction, psychological distress is a two-dimensional continuous construct and a consideration of both severity and the sources of stressors is important in the management of psychological distress among patients with diabetes. This is an important point for health care providers to take note. Another strength of this study is the multi-ethnic nature of the sample. It is encouraging to note that ethnicity was not a factor associated with psychological distress, barriers to activity, disinhibited eating and HRQoL.
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