ORIGINAL RESEARCH

 

Anxiety, depression and psychological well-being in a cohort of South African adults with Type 2 diabetes mellitus

 

 

Samantha Ramkisson^I; Basil J. Pillay^I; Benn Sartorius^II

^IDepartment of Behavioural Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, South Africa
^IIDepartment of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, South Africa

Correspondence

 

 

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ABSTRACT

BACKGROUND: The prevalence of diabetes mellitus (DM) has increased at alarming rates globally. South Africa has the second highest number of people in Africa living with DM, with prevalence rates being among the top five countries in Africa. Accordingly, psychological issues associated with DM have been a growing focus of attention. Studies have found that patients with DM have elevated levels of anxiety and depression, and decreased levels of well-being. In South Africa, there is a paucity of studies on the psychological issues associated with DM.
OBJECTIVES: The aim of this paper was to explore the prevalence and association of anxiety, depressive features and psychological well-being in patients with Type 2 DM.
METHOD: In a cross-sectional survey, patients with Type 2 DM were recruited from public and private facilities. The Hospital Anxiety and Depression Scale (HADS), the General Health Questionnaire (GHQ-28) and WHO-5 Well-being Index (WHO-5) were administered.
RESULTS: Four hundred and one participants completed the questionnaires. On the WHO-5, 277 (69%) reported good well-being, while 124 (31%) indicated poor well-being and were considered at risk for depressive features. On the HADS, 186 (46%) had mild-to-severe depressive features and 128 (32%) had mild-to-severe anxiety. There was a strong negative correlation between the WHO-5, HADS and General Health Questionnaire (GHQ) scales, which indicated that an increase in anxiety and depressive features decreased psychological well-being.
CONCLUSION: Health-care providers should identify and treat anxiety and depression as a standard part of diabetes care. Patients should also be referred to the appropriate mental health professional as part of the management of diabetes.

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Introduction

There has been an alarming increase in diabetes mellitus (DM) prevalence rates globally. The International Diabetes Federation (IDF) revealed that in 2014 the global prevalence rate was estimated to be 8.2%, with about 382 million people living with the disease. This figure is projected to increase to 592 million by 2035.¹ The IDF projects that the global figure of 21.5 million people estimated to be living with diabetes in 2014 will increase dramatically to 41.5 million in 2035. In Africa, the prevalence rate is estimated to be 5.1%.² South Africa has a prevalence rate of 9.27% and has the second highest number of people in Africa living with the disease - an estimate of 2.6 million.³ In 2012, DM was the fifth leading cause of death in South Africa and the third leading cause of death in KwaZulu-Natal.⁴

In recent years, much attention has been paid to the psychological well-being of patients with diabetes.⁵ The cross-national Diabetes Attitudes, Wishes and Needs (DAWN) study, conducted by Peyrot et al.⁶ in Asia, Australia, Europe and North America in 2005, found that 41% of patients with DM reported poor psychological well-being. Furthermore, they found that 61% - 72% of health-care providers reported that their patients with DM had psychological problems, which included depression, anxiety, stress and burnout. Karlsen et al.⁷ found that poor psychological well-being was more prevalent among people with Type 2 diabetes compared with people with Type 1 diabetes.

The high levels of poor psychological well-being thus become an important issue to be addressed in the management of diabetes. However, Pouwer et al.⁸ state that while psychological well-being is understood to be an important goal in diabetes management, often little attention is paid to addressing these psychological aspects of the disease.

Most studies using the Hospital Anxiety and Depression Scale (HADS) found that DM is associated with increased levels of anxiety and depression.^9,10,11,12 Longitudinal studies done by Engum¹³ and Fisher et al.¹⁴ also found that patients with DM have elevated levels of anxiety and anxiety symptoms.

Anderson et al.¹⁵ and Ali et al.¹⁶ report that the odds of depression in diabetic groups were twice those of the non-diabetic comparison groups, and this did not differ by sex, type of diabetes, subject source or assessment method. Coexisting depression in people with DM is associated with decreased adherence to treatment, poor metabolic control, higher complication rates and decreased quality of life.¹⁷ As a result, patients with DM often experienced feelings of poor well-being, stress and anxiety.¹⁸ Studies also show that women report higher levels of depression, anxiety and stress compared with men.^12,19

From the above discussion, it can be seen that there is a growing body of evidence to support the view that, in addition to the medical/pharmacological management of people with diabetes, the management of psychological, psychiatric and social aspects is also essential. This is necessary given the high levels of anxiety and depression found in people with diabetes.

In South Africa, there is a paucity of studies on the psychological issues associated with DM. We hypothesise that the presence of anxiety and depressive features decreases the well-being of patients with Type 2 diabetes. To our knowledge, a study of this nature has not been done in South Africa.

 

Method

Patients with Type 2 DM were recruited from two public facilities and five private general medical practices situated on the North Coast of KwaZulu-Natal, South Africa.

Participants

Patient volunteers, 18 years and older, diagnosed with Type 2 DM at least 6 months previously and able to speak either English or isiZulu, were included in the study. Patients who were intellectually impaired and/or who had serious medical complications that decreased their quality of life (e.g. amputations or dialysis) were excluded from the study. Four hundred and twenty-four participants were recruited over a period of 6 months. Twenty-three participants were excluded due to incomplete data. A total of 401 participants completed the questionnaires; this comprised 201 patients from the public health facilities and 200 patients from the private health facilities.

Ethical considerations

Ethics approval was obtained from the Biomedical Ethical Research Committee of the University of KwaZulu-Natal. Consent was also obtained from the Provincial Department of Health and the managers of the public facilities. Written permission was also obtained from the private doctors to conduct the research at their practices.

Procedure

A cross-sectional study design was used whereby participants were recruited consecutively until the required sample size was achieved. Trained research assistants, fluent in both English and isiZulu, explained the study in detail to patients awaiting their regular treatment appointments. Those who met the inclusion criteria were invited to participate. A written informed consent form was signed by the participant in their language of choice. The questionnaires were administered at the study sites by a trained research assistant. The participant's diabetes type was confirmed by the diabetes nurse educators and information from the medical file.

Quantitative instruments

This article is part of a larger study on psychological well-being and Type 2 diabetes which aims to explore the perceptions of support and the biopsychosocial factors associated with well-being in adults with Type 2 diabetes. This article reports on data of the HADS, the General Health Questionnaire (GHQ) and the WHO-5 Well-being Index (WHO-5).

The HADS, developed by Zigmond and Snaith²⁰ is a self-report questionnaire designed to detect anxiety and depressive states. It has 14 items with two subscales measuring symptoms of depression and symptoms of anxiety. Bjelland et al.²¹ found that the HADS performed well in assessing the symptom severity of anxiety disorders and depression in psychiatric primary-care patients and in the general population.^11,22 Cronbach's alpha values for this instrument range from α = 0.40 to α = 0.70.²¹ The Cronbach's alpha for this study was 0.83 for the HADS Anxiety scale and 0.79 for the HADS Depression scale.

The GHQ-28, developed by Goldberg, is a 28-item measure of emotional distress.²³ There are four subscales with the 28 items distributed evenly across each. The four subscales are somatic symptoms, anxiety and insomnia, social dysfunction, and severe depression. Internal reliability ranges from 0.78 to 0.95.²⁴ In this study, the Cronbach's alpha ranged from 0.86 to 0.92.

The WHO-5 has five items and covers positive mood (good spirit, relaxation), vitality (being active, waking up fresh and rested) and general interests (being interested in things). The degree to which these feelings were present in the previous 2 weeks is scored on a 6-point Likert scale ranging from 0 (not present) to 5 (constantly present). The scores are summarised, with raw scores ranging from 0 to 25 and then transformed to 0-100 by multiplying by 4 with higher scores signifying better well-being.²⁵ A score of < 52 suggests poor emotional well-being and is a sign for further testing. A score < 28 is indicative of depression. The Cronbach's alpha of the WHO-5 in this study was 0.89.

All questionnaires were translated into isiZulu by an accredited isiZulu translator. The documents were back-translated into English by an isiZulu educator.

Data analysis

The data were analysed using STATA version 13.0.²⁶ The following tests were used: t-test and Wilcoxon rank-sum test for comparing means of continuous data across two groups (e.g. public vs private sectors), the Chi-square (χ²) test or Fisher's exact for cross-tabulations of categorical variables, and the one-way ANOVA or Kruskal-Wallis equality-of-populations rank test to compare means (or summed ranks) of continuous variables across three or more groups.

In order to detect a small effect size (Cohen's d = 0.28)²⁷ when assessing differences in mean age, for example, by public/private sector or anxiety, depression and psychological well-being with 80% power (1-β [Type 2 error probability]) and 95% confidence (or 5% α error probability [Type 1]) using a student's i-test, a sample size of 400 participants (200 in each group) would be required.

Bivariate and multivariable ordinal logistic regression was performed to identify factors associated with ordinal well-being category after adjustment for confounders and the influence of other risk factors. The Brant Test of Parallel Regression Assumption was run to ensure that the proportional odds assumption was not violated. Potential multiple colinearity between independent variables within the model was assessed using Variance Inflating Factors (VIF). An adjusted p < 0.05 was deemed statistically significant.

 

Results

The demographic characteristics of the study sample are presented in Table 1. The mean age was M = 53.7 years (s.d. = 10.7), with a similar mean age in the public sector (M = 53.5 years; s.d. = 10.3) and private sector (M = 53.83; s.d. = 11.2; p = 0.761). The mean age of females (M = 52.83; s.d. = 10.54) was marginally statistically younger compared with males (M = 54.75; s.d. = 10.96; p = 0.054). The average duration of the disease for the entire sample was 10.3 years (s.d. = 7.9). This did not vary by sector, with a median duration of 8 years (IQR = 4-14) for the public sector and 8 years (IQR = 4-13) for the private sector.

In Table 1, there were significant differences for selected socio-demographic characteristics when comparing the private and public sectors. Females attended the public sector facilities almost three times more than males (p < 0.001). More black African patients attended the public sector services, whereas private sector services were predominantly accessed by white patients (p < 0.001). The majority of participants in the private sector were married (80%); private sector participants also had more formal education (41.50%) and more were in full-time employment (47%). The highest prevalence of DM was among the Indian racial group (68.1%).

On the WHO-5, 277 (69%) of the sample endorsed good well-being, while 124 (31%) reported poor well-being and were thus considered at risk for depression (see Table 2). More females (43; 17.70%) endorsed poor well-being than males, while 44 (22%) of the public sector sample reported poor well-being. Furthermore, participants who were married (207) had better well-being levels (75%) compared with those who had never married (24; 45.28%). Also, Indian and white groups demonstrated better well-being levels compared to the black African and mixed racial groups. Participants who had a higher educational level (77; 79.38%) or were employed (136; 74.32%) also had better well-being levels.

Mean scores comparisons of the HADS and the GHQ by gender and health sectors are displayed in Table 3. Based on the GHQ-Somatic scale, 159 (40%) participants had elevated somatic symptoms; on the GHQ-Anxiety/Insomnia scale, 149 (37.16%) reported high levels of anxiety. On the GHQ-Social Dysfunction scale, 290 (72.32%) had high levels of social dysfunction, and on the GHQ-Depression scale 78 (19%) reported severe depressive symptoms. Females (M = 25.50; s.d. = 16.11) had significantly higher mean GHQ score compared to males (M = 18.40; s.d. = 12.80). The public sector mean GHQ score (M = 25.20; s.d. = 15.84) was significantly higher than the private sector (M = 20.16; s.d. = 14.30). The Social Dysfunction scale scores were elevated both for gender and health sector.

Based on the HADS, 186 (46%) participants had mild-to-severe depressive features and 128 (32%) had mild-to-severe anxiety. Females (M = 8.08; s.d. = 4.34) had significantly higher scores on the HADS Depression scale compared to males (M = 6.46; s.d. = 4.30). The total mean score for depression scale was 7.44 (s.d. = 4.45), which was higher than the total mean scores for anxiety (M = 5.75; s.d. = 4.02). Although these scores are not diagnostic, they suggest the presence of symptoms of anxiety and depressive features.

The relationships between the WHO-5, the HADS and the GHQ scales were investigated using Spearman's rank correlation coefficient (r) as shown in Table 4. There was a strong negative correlation between the WHO-5, HADS Depression, HADS Anxiety, GHQ-Somatic GHQ-Anxiety, GHQ-Social and GHQ-Depression scales. A moderate positive correlation was found between the HADS Depression, HADS Anxiety, GHQ-Somatic, GHQ-Anxiety and GHQ-Depression scales. There was a strong positive correlation between the GHQ-Anxiety and GHQ-Somatic scales (ρ = + 0.74, p < 0.05).

 

 

The mean scores for depression, anxiety and GHQ-Depression by well-being category are displayed in Table 5. Mean scores significantly increased from the normal group to the depressed group (p < 0.001). Pairwise comparisons in the HADS Depression category showed that there were significant differences between the normal and depressed groups, and the normal and low mood groups. For the HADS Anxiety and the GHQ-Depression scales, pairwise comparisons showed significant differences (p < 0.001) between low mood and depressed, normal and depressed, and normal and low mood. Among the depressed group in the well-being category, a large proportion (65%) on the HADS had moderate-to-severe depressive features. On the HADS Anxiety scale, 53% were in the moderate-to-severe depressed category of well-being. There was a significant association between the well-being categories, the HADS and the GHQ-Depression categories, where an increase in depression and anxiety scores indicated lower well-being (Fisher's exact p < 0.001).

After adjusting for age, gender, race and type of facility (Table 6), the following factors were significantly associated with lower odds (Odds Ratio: OR) of being in a better well-being category: participants attending the public sector (OR = 0.43; 95% CI: 0.23; 0.78), mild (OR = 0.44; 95% CI: 0.23; 0.85) moderate (OR = 0.21; 95% CI: 0.10; 0.44) or severe depressive features (OR = 0.07; 95% CI: 0.03; 0.22) compared with the normal category, as well as mild (OR = 0.42; 95% CI: 0.23; 0.77), moderate (OR = 0.17; 95% CI: 0.07; 0.40) or severe anxiety (OR = 0.11; 95% CI: 0.02; 0.61) compared with the normal category. Similarly, those with a GHQ-Somatic (OR = 0.74; 95% CI: 0.36; 1.51), GHQ-Anxiety (OR = 0.50; 95% CI: 0.23; 1.04), GHQ-Social Dysfunction (OR = 0.50; 95% CI: 0.22; 1.00) or GHQ-Depression (OR = 0.43; 95% CI: 0.22; 0.85) with a threshold score > 7 were also significantly less likely to be in a better well-being category, following multivariable adjustment.

 

Discussion

The aim of this study was to explore the prevalence and the relationships between anxiety, depressive features and psychological well-being in adults with Type 2 DM in the public and private health sectors.

There were no differences between the public and private sectors in terms of the mean age and the average duration of the disease. There were significantly more females attending the health-care facilities compared to males.^{28,29,30,31,32} have also documented this trend. Women tend to be more active than men when seeking health-care and health-care information³³ and tend to be more supportive of others' health-care needs but lack the support they need when managing their own health.³²

Participants of Indian race had the highest levels of DM, which supports research suggesting a higher prevalence of diabetes in this racial group.^34,35 According to Seedat³⁴ this is the result of insulin resistance, an unhealthy diet and physical inactivity. Black African participants (24.9%) had the next highest levels of DM. In recent years, the prevalence of DM has increased in black South Africans,^36,37 due to a family history of DM, high systolic blood pressure, high total cholesterol³⁷ and urbanisation, which is accompanied by a change of diet leading to raised levels of obesity.³⁶

Among public sector participants, the unemployment rate was 46.77%, which is higher than the current national unemployment rate in South Africa (26.4%) and double the KwaZulu-Natal rate (23.6%).³⁸ This suggests that patients who are unemployed understandably use the public healthcare facilities, having no alternative avenue for care due to lack of finances. However, due to an overburdened healthcare system, it is very likely that patients with DM do not receive adequate treatment and have to settle for suboptimal care.^39,40 This, in turn, increases long-term complications and medical costs.

Psychological well-being

Our findings support the view that a significant number of people with DM have poor psychological well-being. Poor psychological well-being negatively impacts a person's ability to manage diabetes, decreases their adherence to medication and increases the risk of complications later in life.^41,42 Self-management and adherence to medication are of paramount importance in achieving the prevention of diabetic complications, which is one of the core medical goals in the management of diabetes. The impact of poor psychological well-being in patients with diabetes has serious implications both medically and psychologically. This further highlights the need for the standard provision of psychological services to patients with DM.

This study showed that more women reported poor well-being compared with men. This is in keeping with the literature,^{9,19,43,44,45} suggesting that gender-role differentiation and the responsibilities of taking care of the family¹⁹ contribute to this. Furthermore, females may not have much social support in the management of the disease, although they are more likely to be supportive to others.

Another finding on well-being in this study was that married participants reported better well-being. According to Cohen et al.⁴⁶ and Vlassoff,³² males with diabetes receive more support from their wives compared with the females with diabetes, who receive less support from their spouses. Supporting this view, the results show that participants who were never married had poorer psychological well-being.

There were differences on the report of well-being among the racial groups. It was found that white people and Indian groups reported better psychological well-being compared with the black racial group. Factors such as socio-economic status and educational level are likely to contribute to such differences. In South Africa, the black racial group has the highest rate of unemployment compared with the white and Indian groups,⁴⁷ which limits access to adequate medical care. Greater awareness and knowledge about the disease improve compliance with medication regimes.^18,48 Knowledge and information about DM can be obtained through the Internet; however, more than half of the population do not have Internet access.⁴⁹ This further hampers knowledge and awareness about the disease.

Anxiety and depressive features

The prevalence rates in our study were much higher compared with studies in developed countries like the United Kingdom and the United States^10,11,43,50 and similar to studies in developing countries like Pakistan and China.^9,51 Furthermore, in our study we found that the prevalence of depressive features was higher than that of anxiety. Anderson et al.¹⁵ and Ali et al.⁵² reported that people with Type 2 diabetes had elevated rates of depression. The high rates of anxiety and depressive features are a cause for concern and need to be taken into consideration by health-care providers when treating DM.

In keeping with literature, we found that females reported higher levels of depressive features compared with males.^{9,12,15,43,53} A contributory factor is the added burden of having a demanding chronic condition while having to performing gender role-specific tasks such as child-bearing and taking care of the family. As pointed out by Ngcobo and Pillay,⁵³ the lack of resources for women in South Africa hinders or prevents early treatment and access. Improving women's accessibility to health-care, and thereby their health, will appreciably impact on the general health status of families and communities.

Psychological well-being, anxiety and depressive features

The strong negative correlation between the WHO-5, HADS Depression, HADS Anxiety, GHQ-Somatic, GHQ-Anxiety, GHQ-Social and GHQ-Depression scales indicates that an increase in anxiety and depressive features results in a decrease in psychological well-being. As expected, this finding supports our hypothesis that the presence of anxiety and depressive features decreases well-being. The strong positive correlation between the GHQ-Anxiety and GHQ-Somatic scales is understandable because patients with diabetes have many somatic complaints; these could lead to diabetic complications, thereby increasing anxiety and depressive levels. Pillay and Cassimjee⁵⁴ support the view that there is a high incidence of depressive and anxiety disorders in patients who are seen in general practice; however, a large proportion of these are not identified. Studies by Wu et al.⁵⁵ found that anxiety correlated positively with diabetic complications.

Our study found that patients attending the public sector, and patients who have symptoms of anxiety and depressive features, have lower levels of well-being. This highlights the need for health services to place greater emphasis on the psychological needs and treatment of patients with diabetes in the public health sector. Patients with diabetes should routinely undergo screening of their mental health status. Addressing psychological needs will improve medical outcomes, self-management and regimen adherence, thereby preventing long-term complications of diabetes.

Limitations

Although the study aimed to be representative of all racial groups, some racial groups had small sample sizes. The cross-sectional design limits causal associations between anxiety, depressive features and psychological well-being. Self-administered questionnaires were used in this study, but a diagnostic interview remains the gold standard in research and clinical practice.

 

Conclusion

The findings in this study supported our hypotheses about anxiety, depressive features and psychological well-being of patients with diabetes. These are important findings when considering the management of patients with diabetes. The findings suggest that for effective treatment of DM, healthcare providers must be able to identify and treat anxiety and depression as common components of diabetes care. Routine screening for anxiety and depression is necessary for patients with diabetes. It is also suggested that patients be referred to the appropriate mental health professionals as part of the management of diabetes.

 

Acknowledgements

We would like to thank Stanger Hospital, the KwaDukuza Clinic, the Ballito Medical Centre and the private medical practices which gave us permission to conduct the research at their facilities.

Competing interests

This study was funded by the National Research Foundation (NRF) and the University of KwaZulu-Natal.

Authors' contributions

All authors equally contributed to the research and writing of this article.

 

References

1. International Diabetes Federation. IDF Diabetes Atlas. 6th ed. Available from https://www.idf.org/sites/default/files/Atlas-poster-2014_EN.pdf        [ Links ]

2. International Diabetes Federation. IDF Diabetes Atlas. 6th ed. revised. 2014. Available from http://www.idf.org/sites/default/files/DA-regional-factsheets-2014_FINAL.pdf        [ Links ]

3. International Diabetes Federation. IDF Diabetes Atlas. 6th ed. Brussels: IDF; 2013.         [ Links ]

4. Statistics South Africa. Mortality and causes of death in South Africa, 2012: Findings from death notification. 2014. Available from http://www.statssa.gov.za/publications/P03093/P030932012.pdf        [ Links ]

5. Snoek FJ, Skinner TC. Psychological counselling in problematic diabetes: Does it help? Diabet Med. 2002;19(4):265-273. http://dx.doi.org/10.1046/j.1464-5491.2002.00678.x        [ Links ]

6. Peyrot M, Rubin RR, Lauritzen T, Snoek FJ, Matthews DR, Skovlund SE. Psychosocial problems and barriers to improve diabetes management: Results of the Cross-National Diabetes Attitudes, Wishes and Needs (DAWN) Study. Diabet Med. 2005;22:1379-1385. http://dx.doi.org/10.1111/j.1464-5491.2005.01644.x        [ Links ]

7. Karlsen B, Bru E, Hanestad BR. Self-reported psychological well-being and disease related strains among adults with diabetes. Psychol Health. 2002;17(4):459-473. http://dx.doi.org/10.1080/0887044022000004948        [ Links ]

8. Pouwer F, Snoek FJ, van der Ploeg HM, Ader HJ, Heine RJ. Monitoring of psychological well-being in outpatients with diabetes: Effects on mood, HbA(1c), and the patient's evaluation of the quality of diabetes care: A randomized controlled trial. Diabetes Care. 2001;24(11):1929-1935. http://dx.doi.org/10.2337/diacare.24.11.1929        [ Links ]

9. Khuwaja AK, Lalani S, Dhanani R, Azam IS, 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.         [ Links ]

10. Collins MM, Corcoran P, Perry IJ. Anxiety and depression symptoms in patients with diabetes. Diabet Med. 2009;26(2):153-161. http://dx.doi.org/10.1111/j.1464-5491.2008.02648.x        [ Links ]

11. Lloyd CE, Dyer PH, Barnett AH. Prevalence of symptoms of depression and anxiety in a diabetes clinic population. Diabet Med. 2000;17(3):198-202. http://dx.doi.org/10.1046/j.1464-5491.2000.00260.x        [ Links ]

12. Bener A, Al-Hamaq AOAA, Dafeeah EE. High prevalence of depression, anxiety and stress symptoms among diabetes mellitus patients. Open Psychiatr J. 2011;5:5-12. http://dx.doi.org/10.2174/1874354401105010005        [ Links ]

13. Engum A. The role of depression and anxiety in onset of diabetes in a large population-based study. J Psychosom Res. 2007;62(1):31-38. http://dx.doi.org/10.1016/j.jpsychores.2006.07.009        [ Links ]

14. Fisher L, Skaff MM, Mullan JT, Arean P, Glasgow R, Masharani U. A longitudinal study of affective and anxiety disorders, depressive affect and diabetes distress in adults with Type 2 diabetes. Diabet Med. 2008;25(9):1096-1101. http://dx.doi.org/10.1111/j.1464-5491.2008.02533.x        [ Links ]

15. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: A meta-analysis. Diabetes Care. 2001;24 (6):1069-1078. http://dx.doi.org/10.2337/diacare.24.6.1069        [ Links ]

16. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K. The prevalence of co-morbid depression in adults with Type 2 diabetes: A systematic review and meta-analysis. Diabet Med. 2006;23(11):1165-1173. http://dx.doi.org/10.1111/j.1464-5491.2006.01943.x        [ Links ]

17. Egede LE, Ellis C. Diabetes and depression: Global perspectives. Diabetes Res Clin Pract. 2010;87(3):302-312. http://dx.doi.org/10.1016/j.diabres.2010.01.024        [ Links ]

18. Skinner TC. Psychological barriers. Eur J Endocrinol. 2004;151. http://dx.doi.org/10.1530/eje.0.151t013        [ Links ]

19. Sriram V, Sridha GR, Madhu K. Gender differences in living with Type 2 Diabetes. Int J Diab Dev Ctries. 2001;21.         [ Links ]

20. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361-370. http://dx.doi.org/10.1111/j.1600-0447.1983.tb09716.x        [ Links ]

21. Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the hospital anxiety and depression scale. An updated literature review. J Psychosom Res. 2002;52(2):69-77. http://dx.doi.org/10.1016/S0022-3999(01)00296-3        [ Links ]

22. Carroll BT, Kathol RG, Noyes R, Wald TG, Clamon GH. Screening for depression and anxiety in cancer patients using the hospital anxiety and depression scale. Gen Hosp Psychiatr. 1993;15(2):69-74. http://dx.doi.org/10.1016/0163-8343(93)90099-A        [ Links ]

23. Sterling M. General Health Questionnaire- 28 (GHQ-28). J Physiother. 2011;57:259. http://dx.doi.org/10.1016/S1836-9553(11)70060-1        [ Links ]

24. Jackson C. The General Health Questionnaire. Occup Med. 2006;57(1):79. http://dx.doi.org/10.1093/occmed/kql169        [ Links ]

25. Snoek FJ. WHO (Five) Well-Being Index 2006.         [ Links ]

26. StataCorp. Stata Statistical Software: Release 13. 2013. College Station, TX: StataCorp LP.         [ Links ]

27. Cohen J. Statistical power analysis for the behavioral sciences (2. Auflage). Hillsdale, NJ: Erlbaum; 1988.         [ Links ]

28. Pillay BJ. A study of the relation between health attitudes, values and beliefs and health seeking behaviour with special reference to a representative sample of Black South Africans (unpublished PHD-MED thesis). University of KwaZulu- Natal. South Africa; 1993.         [ Links ]

29. Galdas PM, Cheater F, Marshall P. Men and health help-seeking behaviour: Literature review. J Adv Nurs. 2005;49(6):616-623. http://dx.doi.org/10.1111/j.1365-2648.2004.03331.x        [ Links ]

30. Hjelm K, Atwine F. Health-care seeking behaviour among persons with diabetes in Uganda: An interview study. BMC Int Health Hum Rights. 2011;11:11. http://dx.doi.org/10.1186/1472-698X-11-11        [ Links ]

31. Mufunda E, Albin B, Hjelm K. Differences in health and illness beliefs in Zimbabwean men and women with diabetes. Open Nurs J. 2012;6:117-125. http://dx.doi.org/10.2174/1874434601206010117        [ Links ]

32. Vlassoff C. Gender differences in determinants and consequences of health and illness. J Health Popul Nutr. 2007;25(1):47-61.         [ Links ]

33. Norcross WA, Ramirez C, Palinkas LA. The influence of women on the health care-seeking behavior of men. J Fam Pract. 1996;43(5):475-480.         [ Links ]

34. Seedat YK. Review: Diabetes mellitus in South African Indians. Br J Diabetes Vasc Dis. 2005;5(5):249-251. http://dx.doi.org/10.1177/14746514050050050201        [ Links ]

35. Motala AA, Pirie FJ, Gouws E, Amod A, Omar MAK. High incidence of Type 2 diabetes mellitus in South African Indians. Diabet Med. 2003(20):23-30. http://dx.doi.org/10.1046/j.1464-5491.2003.00782.x        [ Links ]

36. Peer N, Steyn K, Lombard C, Lambert EV, Vythilingum B, Levitt NS. Rising diabetes prevalence among urban-dwelling black South Africans. PLoS One. 2012;7 (9):e43336. http://dx.doi.org/10.1371/journal.pone.0043336        [ Links ]

37. Motala AA, Esterhuizen T, Gouws E, Pirie FJ, Omar MA. Diabetes and other disorders of glycemia in a rural South African community: Prevalence and associated risk factors. Diabetes Care. 2008;31(9):1783-1788. http://dx.doi.org/10.2337/dc08-0212        [ Links ]

38. Statistics South Africa. Quarterly Labour Force Survey: Quarter 1 2015. 2015. Available from http://www.statssa.gov.za/publications/P0211/P02111stQuarter2015.pdf        [ Links ]

39. Steyn K, Fourie J, Temple N. Chronic diseases of lifestyle in South Africa: 1995-2005. Technical Report. Cape Town: South African Medical Research Council; 2006.         [ Links ]

40. van der Hoeven M, Kruger A, Greeff M. Differences in health care seeking behaviour between rural and urban communities in South Africa. Int J Equity in Health. 2012;11(31). http://dx.doi.org/10.1186/1475-9276-11-31        [ Links ]

41. Diabetes UK. Minding the gap. The provision of psychological support and care for people with diabetes in the UK. 2008.         [ Links ]

42. Debono M, Cachia E. The impact of diabetes on psychological well being and quality of life. The role of patient education. Psychol Health Med. 2007;12(5):545-555. http://dx.doi.org/10.1080/13548500701235740        [ Links ]

43. Thomas J, Jones G, Scarini I, Brantley P. A descriptive and comparative study of the prevalence of depressive and anxiety disorders in low-income adults with Type 2 diabetes and other chronic illnesses. Diabetes Care. 2003;26(8). http://dx.doi.org/10.2337/diacare.26.8.2311        [ Links ]

44. Smith KJ, Beland M, Clyde M, Gariepy G, Page V, Badawi G, et al. Association of diabetes with anxiety: A systematic review and meta-analysis. J Psychosom Res. 2013;74(2):89-99. http://dx.doi.org/10.1016/jjpsychores.2012.11.013        [ Links ]

45. Eiser JR, Riazi A, Eiser. C, Hammersley S, Tooke JE. Predictors of psychological well- being in type1 and type 2 diabetes. Psychol Health. 2001;16:99-110. http://dx.doi.org/10.1080/08870440108405492.         [ Links ]

46. Cohen O, Birnbaum GE, Meyuchas R, Levinger Z, Florian V, Mikulincer M. Attachment orientations and spouse support in adults with type 2 diabetes. Psychol Health Med. 2005;10(2):161-165. http://dx.doi.org/10.1080/1354850042000326575.         [ Links ]

47. Statistics South Africa. Quarterly Labour Force Survey Quarter 2 2015. 2015. Available from http://www.statssa.gov.za/publications/P0211/P02112ndQuarter2015.pdf        [ Links ]

48. Mshunqane N, Stewart AV, Rothberg AD. Type 2 diabetes management: Patient knowledge and health care team perceptions, South Africa. Afr J Prim Health Care Fam Med. 2012;4(1):392. http://dx.doi.org/10.4102/phcfm.v4i1.392        [ Links ]

49. Statistics South Africa. General Household Survey 2014. 2015. Available from http://www.statssa.gov.za/publications/P0318/P03182014.pdf        [ Links ]

50. Ali S, Taub NA, Skinner TC, Davies MJ, Khunti K. Depression and anxiety and the 10-year risk for cardiovascular morbidity and mortality in a multi-ethnic population with Type 2 diabetes in primary care. Diabet Med. 2011;28(Suppl. 1):1-31.         [ Links ]

51. Lee S, Chiu A, Tsang A, Chow CC, Chan WB. Treatment-related stresses and anxiety-depressive symptoms among Chinese outpatients with type 2 diabetes mellitus in Hong Kong. Diabetes Res Clin Pract. 2006;74(3):282-288. http://dx.doi.org/10.1016/j.diabres.2006.03.026        [ Links ]

52. Ali S, Stone M, Skinner TC, Robertson N, Davies M, Khunti K. The association between depression and health-related quality of life in people with type 2 diabetes: A systematic literature review. Diabetes Metab Res Rev. 2010;26(2):75-89. http://dx.doi.org/10.1002/dmrr.1065        [ Links ]

53. Ngcobo M, Pillay BJ. Depression in African women presenting for psychological services at a general hospital. Afr J Psychiatr. 2008;11:133-137. http://dx.doi.org/10.4314/ajpsy.v11i2.30266        [ Links ]

54. Pillay BJ, Cassimjee MH. Anxiety and depression in an urban general practice. J Anxiety Depression. 2000;3(2):4-5.         [ Links ]

55. Wu SF, Young LS, Yeh FC, Jian YM, Cheng KC, Lee MC. Correlations among social support, depression, and anxiety in patients with type-2 diabetes. J Nurs Res. 2013;21(2):129-38.         [ Links ]

 

 

Correspondence:
Samantha Ramkisson
samantha.ramkisson@gmail.com

Received: 31 Dec. 2015
Accepted: 12 Apr. 2016
Published: 08 July 2016