Skip to main content

Depression, anxiety and stress symptoms among diabetics in Malaysia: a cross sectional study in an urban primary care setting



Diabetes mellitus is a highly prevalent condition in Malaysia, increasing from 11.6% in 2006 to 15.2% in 2011 among individuals 18 years and above. Co-morbid depression in diabetics is associated with hyperglycemia, diabetic complications and increased health care costs. The aims of this study are to determine the prevalence and predictors of depression, anxiety and stress symptoms in Type II diabetics attending government primary care facilities in the urban area of Klang Valley, Malaysia.


The study was cross sectional in design and carried out in 12 randomly selected primary care government clinics in the Klang Valley, Malaysia. A total of 2508 eligible consenting respondents participated in the study. The Depression, Anxiety and Stress Scale (DASS) 21 questionnaire was used to measure depression, anxiety and stress symptoms. Data was analyzed using the SPSS version 16 software using both descriptive and inferential statistics.


The prevalence of depression, anxiety and stress symptoms among Type II diabetics were 11.5%, 30.5% and 12.5% respectively. Using multiple logistic regression, females, Asian Indians, marital status (never married, divorced/widowed/separated), a family history of psychiatric illness, less than 2 years duration of diabetes and current alcohol consumption were found to be significant predictors of depression. For anxiety, unemployment, housewives, HbA1c level of more than 8.5%, a family history of psychiatric illness, life events and lack of physical activity were independent risk factors. Stress was significantly associated with females, HbA1c level of more than 8.5%, presence of co-morbidity, a family history of psychiatric illness, life events and current alcohol consumption. For depression (adjusted OR 2.8, 95% CI 1.1; 7.0), anxiety (adjusted OR 2.4, 95% CI 1.1;5.5) and stress (adjusted OR 4.2, 95% CI 1.8; 9.8), a family history of psychiatric illness was the strongest predictor.


We found the prevalence of depression, anxiety and stress symptoms to be high among Type II diabetics, with almost a third being classified as anxious. Screening of high risk Type II diabetics for depression, anxiety and stress symptoms in the primary care setting is recommended at regular intervals.

Peer Review reports


Diabetes and depression are two of the commonest public health problems affecting people all over the world. About 220 million people are estimated to be suffering from diabetes, majority of the burden being in low and middle income countries (LMIC) [1]. Diabetes is also responsible for about 1.256 million deaths globally in 2008, with most deaths occurring in LMIC. Unipolar depressive disorders and diabetes were ranked 3rd and 19th respectively as leading causes of disability adjusted life years (DALYs) in 2004. The former also being the leading cause of years lost due to disability (YLD). Unipolar depressive disorders are in fact projected to be the leading cause of disease burden by 2030.

In Malaysia, a middle income country, the prevalence of diabetes has increased in the last decade from 5.7% to 9.5% among individuals aged 30 years and above [2] and from 11.6% in 2006 to 15.2% in 2011 among individuals 18 years and older[3]. Of the estimated 2.6 million diabetics in Malaysia, about 715,550 (27.5%) diabetics are originating from the most populous regions in Malaysia namely the state of Selangor and the Federal Territory of Kuala Lumpur [3]. In terms of leading causes of total YLD, the Malaysian National Burden of Disease and Injury Study 2004 ranked diabetes mellitus as the third leading cause in both males (6.0%) and females (7.2%) respectively, while unipolar major depression was ranked as second and top most leading cause in males (7.2%) and females (12.7%) respectively [4].

It is well recognized that many individuals with chronic illnesses also have co-morbid unrecognized mental health disorders [5]. The International Federation of Diabetes has stressed the importance of integrating psychological care in the management of diabetes [6].

It has been estimated that the risk of getting depression in the general population is 10-25% in females and 5 – 12% in males. For individuals with chronic illnesses, the risk is higher at 25 – 33% [7]. Studies have shown that diabetics have a higher prevalence of depression than non-diabetic populations [810]. Globally, an estimated 43 million diabetics have symptoms of depression [5]. Also, diabetes is associated with anxiety disorders [11]. Being diagnosed with diabetes is a life stressor by itself. It requires a large number of physical and mental accommodations. Depression adds to the burden of managing diabetes. Furthermore, health care utilization and costs [1214] increase with the coexistence of diabetes and major depression.

Depression and anxiety are associated with hyperglycemia [1517]. While depression is associated with diabetes complications [18, 19] and increased functional disability [20, 21]. Co-morbid depression has also been shown to be associated with poor adherence to diabetes medication and dietary regimens [16, 22, 23] and reduced quality of life [24, 25]. Several studies have shown the risk of mortality to be increased by depression [2629]. The PROSPECT trial has shown that the five year risk of mortality was reduced with a depression management care program among diabetics compared to similar patients with usual care practices [30].

In Malaysia, there is paucity of epidemiological estimates on the prevalence, characterization and risk factors of depression, anxiety and stress among diabetics. An estimate of the prevalence of these conditions is the first step towards priority setting and the planning, implementation and evaluation of a depression management intervention program in diabetes care in the primary care setting. This study was carried out with the aims of determining the prevalence of depression, anxiety and stress, and its predictors among Type II diabetic outpatients attending government primary care clinics in the Klang Valley.


This was a cross sectional study carried out in 12 selected government primary care clinics located in the Klang Valley.

Study location

The Klang Valley generally refers to the urban areas of Kuala Lumpur, its suburbs and adjoining areas in the state of Selangor. To the North and East, it is demarcated by the Titiwangsa Mountain range, while to the West by the Straits of Malacca. The estimated population of the Klang Valley is 7.5 million [31]. The two federal territories of Kuala Lumpur and Putrajaya as well as five districts from the state of Selangor (Sepang, Hulu Langat, Gombak, Klang and Petaling) were included in the study. In each of these localities the number of clinics ranged from 1 to 13 with a total of 45 clinics.

Sample size and sampling

Sample size was calculated using both the population survey method for prevalence and for comparing two proportions using the Sample Size Calculator for Prevalence Studies [32] and the PS Software [33] respectively. The larger minimum sample size required based on both these methods was taken as the sample size for the whole study. Based on 80% study power, Type I error of 0.05, design effect of 2, a difference of 8% in two groups and a non-response of 20%, a sample size of 2261 was required.

For sampling, a two stage stratified sampling technique was employed. About 25% of the total number of clinics from each locality (with a minimum of one clinic) was randomly selected, giving a total of 12 clinics from the study area. The sample size was then proportionately distributed based on the number of clinics selected from each locality. For three localities where only one single clinic was selected, the minimum sample size was increased to at least 250 to enable clinic level analyses in future. The final minimum sample size for the study was 2446.

Study procedure

All patients attending the diabetic clinics during the study period were screened for eligibility to participate. The inclusion criteria were age 30 years and above, having Type II diabetes of at least six months (verified with medical records) and being literate in Malay (which is the official language of the country) or English. Patients with a known medically diagnosed psychiatric illness in the past (verified with medical records) or with any form of cognitive impairment such as dementia or mental retardation and females in the post-partum period were excluded. Eligible patients were then approached for written consent for the study. Prior to obtaining consent, all potential respondents were explained about the purpose of the study and the relevant procedures involved. They were assured that their blood results would be notified eventually to their attending physician. Subsequently, only consenting patients were recruited in the study.

Ethical issues

Ethical approval for the study was obtained from the Medical Research Ethics Committee, Ministry of Health Malaysia (NIHSEC 08/0809/P09). Permission to conduct the study was also obtained from the State Health Directors as well as Medical and Health Officers in charge of the selected clinics prior to the study.

Data collection tools and measurements

Socio-demographic and other relevant information were collected by five trained interviewers via face-to-face interview. Depression, anxiety and stress symptoms were measured using a self-administered short version of the Depression, Anxiety and Stress Scale (DASS), i.e., DASS 21 (Additional file 1: DAS S 21). The short version has 21 items which are divided into 7 items each assessing the symptoms of depression, anxiety and stress respectively. The DASS has been shown to have high internal consistency. The validated Malay or Bahasa Malaysia version of DASS 21 was used in this study [34]. Respondents were asked to rate their experience on each symptom over the past week on a 4-point severity scale ranging from 0 (does not apply to me), to 3 (applies to me most or all of the time). Scores for each scale were later summed up and categorized as normal, mild, moderate, severe and extremely severe according to the DASS Manual [35].

The following anthropometric and blood assay measurements were also taken:

Height and weight for Body Mass Index (BMI) - Both parameters were measured twice with the patient standing bare footed. Height (to the nearest centimeter) was measured with fixed stadiometers (Seca, Vogel & Halke, Germany) and weight (to the nearest 0.1 kilogram) was measured using an electronic floor weighing scale (Tanita HD 319 Personal Scale, Australia). BMI was classified according to the World Health Organisation guidelines [36].

Waist circumference (WC) - Measured twice using a standard tape measure as described by the National Institutes of Health (NIDDK) [37]. Abdominal obesity was defined by a waist circumference of ≥90 cm for men and ≥80cm for women [38].

Total Serum Cholesterol (TC) - Measured using the Accutrend GCT (Roche Diagnostics, Germany) from a single finger prick.

HbA1c level - Measured using the DCA Vantage Analyser (Siemens Healthcare Diagnostics Inc, USA) from the same single finger prick.

For all the measurements except TC and HbA1c an average of two readings was taken for analyses. Variables were categories based on clinical and statistical reasoning.

Pre-test and pilot study

A pre-test was conducted on 40 Type II diabetic patients selected conveniently from a government primary care facility which was not included in the study. This was purposively done to test the study questionnaire. The pilot study was then conducted after the pre-test in two other government health facilities that were also not selected for the study. The logistics and feasibility of conducting the study were explored. Weaknesses that were identified from the pre-test and pilot study were rectified.

Data management and statistical analysis

All questionnaires were checked for completeness of response at the clinic and attempts were made to improve the response rate for missing items. Data was entered manually into a database and cleaned before analyses. The Statistical Package for the Social Science (SPSS) version 16 software was used for both descriptive and inferential analysis. Items that were not answered by respondents were considered as missing. Univariate statistics such as mean values, standard deviations, frequencies and proportion percentages were derived for continuous and categorical variables respectively. Bivariate and multivariate analyses were used to measure the strength of association between the variables in the study and identify predictors for the outcomes of interest respectively. All tests were two-tailed with significance defined as p < 0.05. Odds ratios (OR) along with 95% confidence levels (CI) were derived where appropriate.


Out of 2774 eligible patients approached, 2508 subjects were successfully recruited, giving a response rate of 90.4%.

Socio-demographic, clinical and other characteristics of sample population

Majority of the respondents were between 50 to 59 years old (35.5%), females (61.1%), Malays (51.2%) and married (81.7%). Almost 40% had some form of secondary education and one third earned a monthly household income (MHI) of MYR 1,000 to 1,999. Slightly over one third of respondents were gainfully employed. The mean age and MHI was about 57 (56.6 ± SD 10.67) years and MYR 2,000 (1,974.6 ± SD 1,869.12) respectively (Table 1).

Table 1 Frequency distribution of respondents by socio-demographic characteristics and selected variables

Over 41% of the respondents were overweight while almost twice the proportion had abdominal obesity. Almost 30% and 40% of the respondents had an elevated TC level of >5.2 mmol and HbA1c of >8.5% respectively. Majority (61%) were diagnosed as having diabetes for 2 - <10 years (Table 1).

Almost 80% reported having at least one co-morbid condition. Majority reported having at least one family member with diabetes (73.6%) while only 1% reported having a history of mental illness in the family. As for life events, about 45% reported experiencing at least one life event in the past 6 months. Current smokers and current alcohol drinkers comprised 10% and 4% of the respondents respectively. Almost half of the respondents were classified as physically inactive (49.1%).

Depression, anxiety and stress

Overall, the prevalence of depression, anxiety and stress symptoms were 11.5%, 30.5% and 12.5% respectively. On bivariate analysis using binary logistic regression, depression was found to be significantly associated with sex, ethnicity, educational level, MHI, marital status, current job status, duration of diabetes and family history of psychiatric illness (Table 2).

Table 2 Frequency distribution of respondents by depression status and socio-demographic characteristics and other selected variables

For anxiety, all socio-demographic variables; females, Asian Indian, no formal education, MHI of MYR < 3,000, divorcees/widowers, housewives and unemployment were significant. In addition, HbA1c >8.5%, ≥ 2 years duration of diabetes, presence of psychiatric illness in the family, life events and physical inactivity were also significantly associated (Table 3).

Table 3 Frequency distribution of respondents by anxiety status and socio-demographic characteristics and other selected variables

Stress was significantly associated with sex, HbA1c, co-morbidity, diabetes in the family, psychiatric illness in the family, life events and alcohol consumption (Table 4).

Table 4 Frequency distribution of respondents by stress status and socio-demographic characteristics and other selected variables

Variables with a p value of < 0.25 in the bivariate analyses and thought to be important risk factors of depression, anxiety and stress were entered into the multivariate model. The forward likelihood ratio (LR) method was used to predict the associated variables for depression, anxiety and stress symptoms in three separate models. The presence of interaction between the explanatory variables was assessed prior to determining the final model.

In the final model six variables i.e., sex, ethnicity, marital status, duration of diabetes, psychiatric illness in the family and alcohol consumption were found to be predictors of depression (Table 5). The strongest predictor was psychiatric illness history with an adjusted odds ratio (aOR) of 2.8 times followed by marital status (aOR 2.5-2.1) and current alcohol consumption (aOR 1.8). Individuals with diabetes of less than two years duration were 1.6 times more likely to have depressive symptoms than individuals with diabetes of longer duration while females and Asian Indians were 1.4 times more likely to have depressive symptoms compared to males and Malay diabetic individuals.

Table 5 Multiple logistic regression model predicting depression, anxiety and stress symptoms among type II diabetic outpatients

In terms of anxiety (Table 5), age group, job status, HbA1c, family history of psychiatric illness, life events and leisure-time physical activity remained significant in the final model, while for stress five variables namely sex, HbA1c, co-morbidity, psychiatric illness in the family, life events and alcohol consumption were found to be significant contributors. Individuals with a family history of psychiatric illness were 2.4 times more likely to report anxiety. Anxiety was 1.4 times more likely in respondents experiencing life events, those physically inactive and with an HbA1c level of >8.5%. All diabetics who were not gainfully employed were 1.2-1.6 times more likely of experiencing anxiety.

Psychiatric illness in the family was the strongest predictor of stress having aOR of 4.2 followed by current alcohol drinkers with an aOR of 2.2. Having a highly undesirable level of HbA1c was associated with at least 1.6 times the odds of stress. Female diabetics and those with co-morbidity were 1.4 times more likely to report stress after controlling for confounders.

There was also significant correlation (p < 0.01) between depression, anxiety and stress symptoms (r = 0.360 for depression and anxiety, r =0.547 for depression and stress and r = 0.504 for anxiety and stress).


Depression, anxiety and stress

This study showed that the prevalence of depression, anxiety and stress symptoms were 11.5%, 30.5% and 12.5% respectively among Type II Diabetic outpatients in the Klang Valley, Malaysia. The prevalence of anxiety in this study was almost three fold more than that of depression and this is in keeping with current literature in which anxiety rates are frequently higher than depression [3942].

Our findings concur with other chronic disease models such as chronic obstructive pulmonary disease (COPD), whereby a study by Dahlen & Janson found that 12% and 37% of respondents with asthma and COPD had probable depression and anxiety respectively [43].

The depressive symptom rates we found are also comparable to studies in rural America (15.8%) [44], the UAE (12.5%) [45] and Germany (10.2%) [11]. Conversely, several studies among diabetic patients had found higher rates than our study [39, 40, 46]. A study in Qatar using the same instrument as ours, i.e., DASS 21 found more than half of the diabetics have depressive, anxiety and stress symptoms [47]. The sex specific depression rates in our study were found to be within the estimated range in the general population. The differences in the rates of depression, anxiety and stress symptoms between our study and others may be attributed to differences in the screening or diagnostic instruments used, the socio-cultural differences of different populations and also the sample size of the subjects. In particular, the study from Qatar had a smaller sample size of 1788.

Our study revealed that sex, ethnicity, marital status, duration of diabetes, psychiatric illness in the family and alcohol consumption were predictors of depression. These findings are consistent with other studies which also found sex [9, 39, 40, 48, 49], ethnic minority groups [50] and duration of diabetes [47] significantly associated with depression among diabetics. It is not surprising that females have a higher prevalence and risk of depression compared to males. Many factors have been implicated for this gender difference including socio-cultural and biological factors [51]. As for ethnicity, minority ethnic groups have been found to have higher depression rates as quoted in other studies [52, 53]. It could be theorized that Asian Indians being the minority are more likely than Malays who form the majority to be exposed to a gamut of psychosocial stressors such as enhanced socioeconomic constraints, poor education and perceived discrimination. Consequently, these issues might augment distress thereby increasing the levels of depression among this group of minority. Similar findings and explanations were cited in a community based cross-sectional study in the United States comparing depression and anxiety in respondents having insomnia and respondents without among the majority Caucasians and minority African American. In that study, Taylor et al. [54] established that African Americans were more likely to have clinically significant depression and anxiety. This was attributable to the plausible exposure to greater array of stressors in the form of discrimination, socioeconomic adversities and enhanced caregiver burden for African Americans as compared to Caucasians.

Generally, it is recognized that being married is associated with less psychiatric morbidity including depression [5557]. Our finding of previously married and never married individuals being associated with depressive symptoms was compatible with a study by Aqbir et al. [48]. It is very likely that having a partner or spouse in a stable marriage offers emotional stability as well as shared burden in coping with challenges.

Incidentally a duration of less than 2 years of having diabetes was a predictor of depressive symptoms in this study. This may be attributed to inadequate or inefficient coping skills of managing diabetes by the respondents within the relatively short period since diagnosis. A related study conducted in Bahrain affirmed an association between duration of diabetes and depressive symptoms [58].

Additionally, this study elucidated the strongest predictor of depressive symptoms was having a family history or family member with psychiatric illness. It is recognized that mental illnesses in general tend to run within families [59]. In addition, in an Asian society such as ours, the responsibility of the family in caring for an ill member whether physically, emotionally or financially is very much entrenched in the culture. Hence, the caregiver’s burden is occasionally translated into physical and mental health adversities such as depression [60, 61].

In terms of alcohol consumption, our study showed that current drinking was an independent risk factor for depression albeit marginally. Several studies have established such an association [41, 42, 62].

For anxiety, our study demonstrated that having a family history of psychiatric illness was the strongest predictor. The finding is not surprising for the same reasons mentioned as for depression. That an elevated HBA1c level was an independent risk factor of anxiety in our study is also echoed by a similar association between blood glucose level and anxiety in a Mexican population [40].

With reference to current job status, this study noted that housewives and those unemployed were at risk of reporting anxiety symptoms than those who were gainfully employed. It is likely that unemployed persons lack feelings of stability and this could contribute to feelings of anxiety. However, further research is needed to show the reasons for our finding.

In this present era of modernization, anxiety has considerable influence upon the quality of life. Balancing work, family and leisure time is a challenge for both working men and women nowadays. If there was a life event preceding which could upset this delicate balance, there would definitely be an increased predilection to develop anxiety in the affected individuals. Our findings concur with several other studies conducted in this area [63, 64].

Physical activity has been shown to promote feelings of well being. Our findings harmonize with other studies showing association between physical inactivity and anxiety symptoms [39, 65]. Furthermore, regular physical activity has revealed a reduction of anxiety symptoms in those who already suffer from this disorder [66].

Our data inferred that having a family member with psychiatric illness was the strongest predictor of stress. Once again caring for a family member who has a chronic illness like mental disorders is indeed a challenging task that could increase the possibilities of adversities [60, 61].

Pertaining to alcohol consumption, current drinkers were strongly associated with stress symptoms. Studies have shown that drinking is used as means of coping with life’s stresses [67]. Child’s et al. have suggested a bidirectional relationship between alcohol use and stress [68].

Experiencing life events is inherently stressful and thus can complicate any stress level already existing in an individual [69]. Lyod et al. [70] have noted that recent severe stressors were associated with poorer glycemic control while another study found a significant correlation between stress and HbA1c [71]. Hence, our findings of life events and elevated HbA1c levels being independently associated with stress symptoms are consistent. Females were found to be at risk of stress in this study. The finding is in accordance with current literature on gender differences and stress symptoms [7274]. We did not find any association between other socio-demographic, lifestyle and clinical factors with stress symptoms.

The strength of our study lies in its large sample size and the sampling method. However, there are also limitations which need to be considered. Firstly, this being a cross sectional study does not allow for cause and effect relationships to be studied. Secondly, the DASS 21 questionnaire is only a screening tool and not diagnostic of specific psychiatric disorders. There is also the possibility of recall biases from respondents, however this was minimized by limiting the recall period to 1 week prior to the interview using DASS 21. Information such as age, past medical history and types of medication was also verified with medical records where applicable. A point to note is that the low prevalence of family history of psychiatric illness elicited from the study could be a result of under reporting as psychiatric illness is still viewed with suspicion and stigma in our society.

As part of a long term and holistic diabetes care management, we recommend that screening for depression, anxiety and stress symptoms be conducted at regular intervals for Type II diabetics with vulnerable characteristics as mentioned above. Policies need to be in place along with appropriate intervention so that these vulnerable individuals receive optimal and timely mental health care, thus translating into better overall health outcomes.


The study showed that while the prevalence of depression and stress symptoms was just over 10%, almost a third were classified as anxious. As these symptoms are highly correlated, they should be considered together when managing diabetic patients. Our findings could help primary care physicians identify high risk diabetics for screening of mental disorders. A family history of psychiatric illness was found to be a common predictor for all three symptoms. Females, current alcohol drinkers, experiencing recent life events and poor glycemic control were the other common predictors of at least two of these symptoms.


  1. 1.

    World Health Organization (WHO): The global burden of disease: 2004 update. 2008, Geneva, Switzerland: World Health Organization

    Google Scholar 

  2. 2.

    Institute for Public Health: The third national health and morbidity survey (NHMS III) 2006. Executive summary. Ministry of health Malaysia. 2008, Kuala Lumpur: Institute for Public Health (IPH)

    Google Scholar 

  3. 3.

    Institute for Public Health (IPH): National health and morbidity survey 2011 (NHMS 2011). volume II: Non communicable diseases. 2011, Kuala Lumpur: Institute for Public Health (IPH)

    Google Scholar 

  4. 4.

    Division of Burden of Disease, Institute for Public Health: Malaysian burden of disease and injury study. Health prioritization: burden of disease approach. 2006, Kuala Lumpur: Institute for Public Health (IPH), Ministry of Health Malaysia

    Google Scholar 

  5. 5.

    Mental health and chronic physical illnesses: The need for continued and integrated care. 2010, Vancouver: World Federation for Mental Health

    Google Scholar 

  6. 6.

    IDF Clinical Guidelines Task Force: Global Guideline for Type 2 diabetes. 2005, Brussels: International Diabetes Federation

    Google Scholar 

  7. 7.

     : Coping with chronic illnesses and depression., Accessed on 27 August 2012

  8. 8.

    Goldney RD, Phillips PJ, Fisher LJ, Wilson DH: Diabetes, depression, and quality of life. A population study Diabetes Care. 2004, 5 (27): 1066-1070.

    Article  Google Scholar 

  9. 9.

    Anderson RJ, Freedland KE, Clouse RE, Lustman P: The prevalence of co morbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001, 24: 1069-1078. 10.2337/diacare.24.6.1069.

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Nouwen A, Winkley K, Twisk J, Lloyd CE, Peyrot M, Ismail K, Pouwer F, for the European Depression in Diabetes (EDID) Research Consortium: Type 2 diabetes mellitus as a risk factor for the onset of depression: a systematic review and meta-analysis. Diabetologia. 2010, 53 (12): 2480-2486. 10.1007/s00125-010-1874-x.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Kruse J, Norbert S, Wolfgang T: On the association between diabetes and mental disorders in a community sample. 2003, Diabetes Care: Results from the German National Health Interview and Examination Survey, 26(6)-

    Google Scholar 

  12. 12.

    Egede LE, Zheng D, Simpon K: Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care. 2002, 25: 464-470. 10.2337/diacare.25.3.464.

    Article  PubMed  Google Scholar 

  13. 13.

    Finkelstein EA, Bray JW, Chen H, Larson MJ, Miller K, Tompkins C, Keme A, Manderscheid R: Prevalence and costs of major depression among elderly claimants with diabetes. Diabetes Care. 2003, 26: 415-420. 10.2337/diacare.26.2.415.

    Article  PubMed  Google Scholar 

  14. 14.

    Subramaniam M, Sum CF, Pek E, Stahl D, Verma S, Liow P, Chua H, Abdin E, Chong S: Comorbid depression and increased health care utilization in individuals with diabetes. Gen Hosp Psychiatry. 2009, 31 (3): 220-224. 10.1016/j.genhosppsych.2009.01.001.

    Article  PubMed  Google Scholar 

  15. 15.

    Lustmann PJ, Anderson RJ, Freedland KE, De Groot M, Carney RM, Clouse RE: Depression and poor glycemic control:a meta-analytic review of the literature. Diabetes Care. 2000, 23: 934-942. 10.2337/diacare.23.7.934.

    Article  Google Scholar 

  16. 16.

    Lustmann PJ, Clouse RE: Depression in diabetic patients: the relationship between mood and glycemic control. J Diabetes Complications. 2005, 19: 113-122.

    Google Scholar 

  17. 17.

    Anderson RJ, Grigsby AB, Freedland KE, de Groot M, McGill JB, Clouse RE, Lustman PJ: Anxiety and poor glycemic control: a meta-analytic review of the literature. Int J Psychiatry Med. 2002, 32 (3): 235-247. 10.2190/KLGD-4H8D-4RYL-TWQ8.

    Article  PubMed  Google Scholar 

  18. 18.

    de Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ: Association of depression and diabetes complications: a meta-analysis. Psychosom Med. 2001, 63: 619-630.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Bruce DG, Davis WA, Starkstein SE, Davis TM: A prospective study of depression and mortality in patients with type 2 diabetes: the Fremantle diabetes study. Diabetologia. 2005, 48 (12): 2532-2539. 10.1007/s00125-005-0024-3.

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Egede LE: Diabetes, major depression and functional disability among U.S. adults. Diabetes Care. 2004, 27: 421-428. 10.2337/diacare.27.2.421.

    Article  PubMed  Google Scholar 

  21. 21.

    Schmitz N, Wang JL, Malla A, Lesage A: Joint effect of depression and chronic conditions on disability: results from a population-based study. Psychosom Med. 2007, 69: 332-338. 10.1097/PSY.0b013e31804259e0.

    Article  PubMed  Google Scholar 

  22. 22.

    Ciechanowski PS, Katon WJ, Russo JE: Depression and diabetes: impact of depressive symptoms on adherence, function and costs. Arch Intern Med. 2000, 160: 3278-3285. 10.1001/archinte.160.21.3278.

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Kilbourne AM, Reynolds CF, Good CB, Sereika SM, Justice AC, Fine MJ: How does depression influence diabetes medication adherence in older patients?. Am J Geriatr Psychiatry. 2005, 13 (3): 202-210.

    Article  PubMed  Google Scholar 

  24. 24.

    Brown GC, Brown MM, Sharma S, Brown H, Gozum M, Denton P: Quality of life associated with diabetes mellitus in an adult population. J Diabetes Complications. 2000, 14 (1): 18-24. 10.1016/S1056-8727(00)00061-1.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Das-Munshi J, Stewart R, Khalida I, Bebbington PE, Jenkins R, Prince MJ: Diabetes, common mental disorders, and disability: findings from the UK national. Surv Psychiatr Morbidity Psychosom Med. 2007, 69: 543-550.

    Google Scholar 

  26. 26.

    Black SA, Markides KS, Ray LA: Depression increased incidence of adverse outcomes in older Mexican Americans with tuype 2 diabetes. Diabetes Care. 2003, 26: 2822-2828. 10.2337/diacare.26.10.2822.

    Article  PubMed  Google Scholar 

  27. 27.

    Zhang X, Norris SL, Gregg EW, Cheng YJ, Beckles G, Kahn HS: Depressive symptoms, and mortality among person with and without diabetes. Am J Epidemiol. 2005, 161: 652-660. 10.1093/aje/kwi089.

    Article  PubMed  Google Scholar 

  28. 28.

    Katon WJ, Rutter C, Simon G, Lin EHB, Ludman E, Ciechanowski P, Kinder L, Young B, Korff MV: The association of comorbid depression with mortality in patients with type 2 diabetes. Diabetes Care. 2004, 28: 2668-2672.

    Article  Google Scholar 

  29. 29.

    Egede LE, Nietert P, Zheng D: Depression and all-cause and coronary heart disease mortality among adults with and without diabetes. Diabetes Care. 2005, 28: 1339-1345. 10.2337/diacare.28.6.1339.

    Article  PubMed  Google Scholar 

  30. 30.

    Bogner HR, Morales KH, Post EP, Bruce ML: Diabetes, depression, and death. A randomized controlled trial of a depression treatment program for older adults based in primary care (PROSPECT). Diabetes Care. 2007, 30 (12): 3005-3010. 10.2337/dc07-0974.

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

     : Klang Valley., Accessed on 20 January 2013

  32. 32.

    Naing L, Winn T, Rusli BN: Sample size calculator for prevalence studies, Version 1.0.01. 2006,,

    Google Scholar 

  33. 33.

    Dupont WD, Plummer W: PS power and sample size program available for free on the Internet. Controlled Clin Trials. 1997, 18: 274-10.1016/S0197-2456(97)00074-3.

    Article  Google Scholar 

  34. 34.

    Musa R, Fadzil MA, Zain Z: Translation, validation and psychometric properties of Bahasa Malaysia version of the Depression, Anxiety and Stress Scales (DASS). ASEAN J Psychiatr. 2007, 8 (2): 82-89.

    Google Scholar 

  35. 35.

    Lovibond SH, Lovibond PF: Manual for the depression anxiety stress scales. Volume 2nd Edition. 1995, Sydney: Psychology Foundation

    Google Scholar 

  36. 36.

    World Health Organization: Obesity: preventing and managing the global epidemic. Report of a WHO consultation (WHO technical report series, 894). WHO technical report series. Volume 894. 2000, Geneva: World Health Organization

    Google Scholar 

  37. 37.

    Weight and waist measurement: tools for adults. 2008, U.S Department of Health and Human Services, National Institute of Diabetes and Digestive and Kidney Disease

  38. 38.

    WHO/IOTF/IASO: The Asia pacific perspective: redefining obesity and its treatment. 2000, Hong Kong: Health Communications Australia Pty Limited

    Google Scholar 

  39. 39.

    Khuwaja AK, Lalani S, Dhanani R, Azam SI, Rafique G, White F: Anxiety and depression among outpatients with type 2 diabetes: a multi-centre study of prevalence and associated factors. Diabetol & Metab Syndr. 2010, 2 (72): 2-7.

    Google Scholar 

  40. 40.

    Tovilla-Zárate C, Juárez-Rojop I, Peralta Jimenez Y, Jiménez MA, Vázquez S, Bermúdez-Ocaña D, Ramón-Frías T, Genis Mendoza AD, García SP, Narváez LL: Prevalence of anxiety and depression among outpatients with type 2 diabetes in the Mexican population. PLoS One. 2012, 7 (5): e36887-10.1371/journal.pone.0036887.

    Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Tann SS, Yabiku ST, Okamoto SK, Yanow J: TriADD: the risk for alcohol abuse, depression, and diabetes multimorbidity in the American Indian and Alaskan native population. Am Indian Alsk Native Ment Health Res. 2007, 14 (1): 1-23.

    Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Collins MM, Corcoran P, Perry IJ: Anxiety and depression symptoms in patients with diabetes. Diabet Med. 2009, 26 (2): 153-161. 10.1111/j.1464-5491.2008.02648.x.

    CAS  Article  PubMed  Google Scholar 

  43. 43.

    Dahlén I, Janson C: Anxiety and depression Are related to the outcome of emergency treatment in patients with obstructive pulmonary disease. Chest. 2002, 122 (5): 1633-1637. 10.1378/chest.122.5.1633.

    Article  PubMed  Google Scholar 

  44. 44.

    Bell RA, Smith SL, Arcury TA, Snively BM, Stafford JM, Quandt SA: Prevalence and correlates of depressive symptoms among rural older African Americans, native Americans, and whites with diabetes. Diabetes Care. 2005, 2: 823-829.

    Article  Google Scholar 

  45. 45.

    Sulaiman N, Hamdan A, Tamim H, Mahmood DA, Young D: The prevalence and correlates of depression and anxiety in a sample of diabetic patients in Sharjah United Arab Emirates. BMC Fam Pract. 2010, 11 (80):,

    Google Scholar 

  46. 46.

    De Groot M, Doyle T, Hockman E, Wheeler C, Pinkerman B, Shubrook J, Gotfired R, Schwartz F: Depression among type 2 diabetes rural applachian clinic attendees. Diabetes Care. 2007, 30 (6): 1602-1604. 10.2337/dc06-1599.

    Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Abdulbari B, OAA Al-Hamaq A, Dafeeah EE: High prevalence of depression, anxiety and stress symptoms among diabetes mellitus patients. Open Psychiatr J. 2011, 5: 5-12. 10.2174/1874354401105010005.

    Article  Google Scholar 

  48. 48.

    Agbir TM, Audu MD, Adebowale TO, Goar SG: Depression among medical outpatients with diabetes: A cross-sectional study at Jos University Teaching Hospital, Jos. Nigeria Ann Afr Med. 2010, 9: 5-10. 10.4103/1596-3519.62617.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    Nichols GA, Brown JB: Unadjusted and adjusted prevalence of diagnosed depression in type 2 diabetes. Diabetes Care. 2003, 26 (3): 744-749. 10.2337/diacare.26.3.744.

    Article  PubMed  Google Scholar 

  50. 50.

    Pouwer F, Geelhoed-Duijvestijn PHLM, Tack CJ, Bazelmans E, Beekman A-J, Heine RJ, Snoek FJ: Prevalence of comorbid depression is high in out-patients with Type 1 or Type 2 diabetes mellitus. Results from three out-patient clinics in the Netherlands. Diabet Med. 2010, 27 (2): 217-224. 10.1111/j.1464-5491.2009.02903.x.

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    Piccinelli M, Wilkinson G: Gender differences in depression: critical review. Br J Psychiatr. 2000, 177: 486-492. 10.1192/bjp.177.6.486.

    CAS  Article  Google Scholar 

  52. 52.

    Dunlop DD, Song J, Lyons JS, Manheim LM, Chang RW: Racial/ethnic differences in rates of depression among preretirement adults. Am J Public Health. 2003, 93 (11): 1945-1952. 10.2105/AJPH.93.11.1945.

    Article  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Fisher L, Laurencin G, Chesla CA, Skaff MM, Mullan JT, Gardiner PS, Chun Kevin M: Depressive affect among four ethnic groups of male patients with type 2 diabetes. Diabetes Spectr. 2004, 17 (4): 215-219. 10.2337/diaspect.17.4.215.

    Article  Google Scholar 

  54. 54.

    Taylor DJ, Lichstein KL, Durrence HH, Reidel BW, Bush AJ: Epidemiology of insomnia, depression, and anxiety. Sleep. 2005, 28 (11): 1457-1464.

    PubMed  Google Scholar 

  55. 55.

    St John PD, Montgomery PR: Marital status, partner satisfaction, and depressive symptoms in older men and women. Can J Psychiatr. 2009, 54 (7): 487-492.

    Google Scholar 

  56. 56.

    Afifi TO, Cox BJ, Enns MW: Mental health profiles among married, never-married, and separated/divorced mothers in a nationally representative sample. Soc Psychiatry Psychiatr Epidemiol. 2006, 41: 122-129. 10.1007/s00127-005-0005-3.

    Article  PubMed  Google Scholar 

  57. 57.

    Stutzer A, Bruno SF: Does marriage make people happy, or do happy people get married?. J Socio Econ. 2006, 35: 326-347. 10.1016/j.socec.2005.11.043.

    Article  Google Scholar 

  58. 58.

    Almawi W, Tamim H, Al-Sayed N, Arekat MR, Al-Khateeb GM, Baqer A, Tutanji HCK: Association of comorbid depression, anxiety and stress disorders with type 2 diabetes in Bahrain, a country with a very high prevalence of type 2 diabetes. J Endocrinol Invest. 2008, 31: 1020-1024.

    CAS  Article  PubMed  Google Scholar 

  59. 59.

    Barlow-Stewart K, Emery J, Metcalfe S: Psychiatric conditions. Genetics in family medicine; the Australian handbook of general practitioners. 2007, Canberra: Biotechnology Australia, Commonwealth Department of Industry, Tourism and Resources, 269-274.

    Google Scholar 

  60. 60.

    Bookwala J, Yee JL, Schulz R: Caregiving and detrimental mental and physical health outcomes. 2000, New York: Kluwer

    Google Scholar 

  61. 61.

    Vanderwerker LC, Laff RE, Kadan-Lottick NS, McColl S, Prigerson HG: Psychiatric disorders and mental health service Use among caregivers of advanced cancer patients. J Clin Oncol. 2005, 23 (28): 6899-6907. 10.1200/JCO.2005.01.370.

    Article  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Graham K, Massak A, Demers A, Rehm J: Does the association between alcohol consumption and depression depend on how they are measured?. Alcohol Clin Exp Res. 2007, 31 (1): 78-88. 10.1111/j.1530-0277.2006.00274.x.

    Article  PubMed  Google Scholar 

  63. 63.

    Krantz G, Östergren PO: Double exposure: the combined impact of domestic responsibilities and job strain on common symptoms in employed Swedish women. Eur J Public Health. 2001, 11: 413-419. 10.1093/eurpub/11.4.413.

    CAS  Article  PubMed  Google Scholar 

  64. 64.

    Romosan F, Lenci M, Stoica I, Dehelean L: Stressful life events and anxiety disorders. Timisoara Med J. 2004, 54 (1): 36-38.

    Google Scholar 

  65. 65.

    Hong X, Li J, Xu F, Tse LA, Liang Y, Wang Z, Yu IT, Griffiths S: Physical activity inversely associated with the presence of depression among urban adolescents in regional China. BMC Public Health. 2009, 9 (148):,

    Google Scholar 

  66. 66.

    Zoeller RF: Physical activity: depression, anxiety, physical activity, and cardiovascular disease: What's the connection. Am J Lifestyle Med. 2007, 1 (3): 175-180. 10.1177/1559827607300518.

    Article  Google Scholar 

  67. 67.

    Bressert S: Stress and drinking. Psych Central. 2012,, Accessed on 30 August 2012

    Google Scholar 

  68. 68.

    Child's E, O'Connor S, De Wit H: Bidirectional interactions between acute psychosocial stress and acute intravenous alcohol in healthy Men. Alcohol Clin Exp Res. 2011, 35 (10): 1794-1803. 10.1111/j.1530-0277.2011.01522.x.

    Article  Google Scholar 

  69. 69.

     : The truth about stress., Accessed on 26 August 2012

  70. 70.

    Lloyd CE, Dyer PH, Lancashire RJ, Harris T, Daniels JE, Barnett AH: Association between stress and glycemic control in adults with type 1 (insulin-dependent) diabetes. Diabetes Care. 1999, 22 (8): 1278-1283. 10.2337/diacare.22.8.1278.

    CAS  Article  PubMed  Google Scholar 

  71. 71.

    Kramer JR, Ledolter J, Manos GN, Bayless ML: Stress and metabolic control in diabetes mellitus: methodological issues and an illustrative analysis. Ann Behav Med. 2000, 22 (1): 17-28. 10.1007/BF02895164.

    CAS  Article  PubMed  Google Scholar 

  72. 72.

     : The prevalence of depression, anxiety & stress in young adults with diabetes., accessed 26 August 2012

  73. 73.

    Andreou E, Alexopoulos Evangelos C, Lionis C, Varvogl L, Gnardellis C, Chrousos George P, Darviri C: Perceived stress scale: reliability and validity study in Greece. Int J Environ Res Public Health. 2011, 8: 3287-3298. 10.3390/ijerph8083287.

    Article  PubMed  PubMed Central  Google Scholar 

  74. 74.

    Gender and Stress., Accessed on 20 January 2013

Pre-publication history

  1. The pre-publication history for this paper can be accessed here:

Download references


The authors wish to thank the Director General of the Ministry of Health Malaysia for his permission in publishing the study findings.

Author information



Corresponding author

Correspondence to Gurpreet Kaur.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

GK was involved in the conception and design of the project, management of data collection/entry, cleaning, statistical analyses and manuscript writing/revising. TGH assisted in the project management, data collection and manuscript writing/revising. SA was involved in the design of the project, assisted in coordination of data collection and manuscript writing/revising. ASK assisted in the project design, conducted the data collection and manuscript writing and revising. KC assisted in the design of the project, data management and statistical analyses. All authors read and approved the final manuscript.

Electronic supplementary material

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Kaur, G., Tee, G.H., Ariaratnam, S. et al. Depression, anxiety and stress symptoms among diabetics in Malaysia: a cross sectional study in an urban primary care setting. BMC Fam Pract 14, 69 (2013).

Download citation


  • Depression
  • Anxiety
  • Stress
  • Prevalence
  • Predictors
  • Diabetes
  • Outpatients
  • Urban
  • Malaysia