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Socioeconomic deprivation and its impact on diabetes care

Lyndi Wiltshire

The effects of social deprivation on anxiety and depression, and the effects of these common mental disorders on diabetes self-care.

When we review the impact of being vulnerable and hard to reach on diabetes care, we need to recognise all the problems associated with coming from a lower socioeconomic group. There is a wealth of evidence now available that the issues posed will have a major impact on an individual’s wellbeing. The increased prevalence of common mental disorders affecting the ability to self-manage diabetes makes for a very difficult predicament. To be able to provide holistic care, we have to understand the impact this evidence will have so that we can support our patients better.

The results of the Mental Health and Wellbeing in England Survey have now been published (McManus et al, 2016), and they provide some sobering thoughts to consider when dealing with the health of vulnerable adults with diabetes. We are aware that poverty and unemployment tend to increase the duration of episodes of common mental disorders in people with diabetes; however, it is not clear whether these factors cause the onset of an episode or vice versa.

Debt and financial strain are certainly associated with depression and anxiety, and increasingly the evidence is suggestive of a causal association (Mind, 2008; Meltzer et al, 2013). These will all have an impact on the ability to self-manage diabetes.

There are a wide range of other factors known to be associated with common mental disorders, including the following:

  • Female gender (Weich et al, 1998).
  • Work stress (Stansfeld et al, 1999).
  • Social isolation (Bruce and Hoff, 1994).
  • Ethnicity (Weich et al, 2004).
  • Poor housing and fuel poverty (Harris et al, 2010; Hills, 2012).
  • Negative life events (e.g. bullying, violence, bereavement, job loss).
  • Childhood adversity, including emotional neglect and physical and sexual abuse (Fryers and Brugha, 2013).
  • Institutional care.
  • Low birth weight (Loret de Mola et al, 2014).
  • Poor physical health.
  • Family history of depression.
  • Poor interpersonal and family relationships, a partner in poor health or being a carer (Stansfeld et al, 2014).
  • Problems with alcohol and illicit drugs (Salokangas and Poutanen, 1998).

Reducing the prevalence of disorders such as depression and anxiety is a major public health challenge (Davies, 2014). These disorders range in severity from mild to severe and are often associated with physical and social problems. They can result in physical impairment and problems with social and occupational functioning, and they are a significant source of distress to patients and those around them. Both anxiety and depression often remain undiagnosed, especially when they are comorbid with long-term conditions such as diabetes (Kessler et al, 2002), and sometimes individuals do not seek or receive treatment. If left untreated, they are more likely to lead to further long-term physical, social and occupational disability, and premature mortality (Zivin et al, 2015).

Although there is evidence for effective treatment of depression and anxiety (NICE, 2006), this seems to have had little impact on the prevalence of these disorders. This may be because they are relapsing conditions that can recur many years after an earlier episode, because the stressors that cause them endure or because people do not always seek or adhere to treatment. In the case of depression, relapse within 10 years of the first presentation is common (Thornicroft and Sartorius, 1993).

The development of effective strategies for the prevention of common mental disorders has been limited by a lack of evidence on how risk factors act in combination (Clark et al, 2012). However, multifactorial risk algorithms for predicting major depression and anxiety disorders have been published (King et al, 2008), and they are already influencing prevention efforts in primary care (Bellón et al, 2016).

The Mental Health and Wellbeing in England Survey compared differences in the likelihood of receiving mental health treatments between different household incomes (Figure 1). Although we cannot directly transfer the findings to diabetes care, this is interesting information and outcomes may be similar in our diabetes caseload.

We are fortunate in this issue to have a very interesting article by Simon Anderson and colleagues reviewing another area of diabetes that social deprivation can affect: symptomatic neuropathic pain. We are under constant pressure to improve outcomes for people with diabetes, and this article suggests that targeting resources at areas of relative disadvantage is an important step.

One simple measure to reduce health inequality among ethnic minorities is to address language barriers when providing information. As Andrew Willis and his colleagues describe, work at University Hospitals Leicester to adapt their materials for non-English-literate patients has resulted in the publication of Gujarati and Bengali translations of their tool to self-assess risk of type 2 diabetes. Improving users’ conceptual understanding of the information contained in the risk score may increase engagement and help with diabetes prevention.

REFERENCES:

Bellón JÁ, Conejo-Cerón S, Moreno-Peral P et al (2016) Intervention to prevent major depression in primary care: a cluster randomized trial. Ann Intern Med 164: 656–65
Bruce ML, Hoff RA (1994) Social and physical health risk factors for first-onset major depressive disorder in a community sample. Soc Psychiatry Psychiatr Epidemiol 29: 165–71
Clark C, Pike C, McManus S et al (2012) The contribution of work and non-work stressors to common mental disorders in the 2007 Adult Psychiatric Morbidity Survey. Psychol Med 42: 829–42
Davies S (2014) Annual Report of the Chief Medical Officer 2013. Public mental health priorities: Investing in the evidence. Department of Health, London. Available at: http://bit.ly/1CMzfT7 (accessed 07.11.16)
Fryers T, Brugha T (2013) Childhood determinants of adult psychiatric disorder. Clin Pract Epidemiol Ment Health 9: 1–50
Harris J, Hall J, Meltzer H et al (2010) Health, mental health and housing conditions in England. National Centre for Social Research, London. Available at: http://bit.ly/2fTp7VG (accessed 07.11.16)
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NICE (2006) Computerised cognitive behaviour therapy for depression and anxiety (TA97). NICE, London. Available at: www.nice.org.uk/guidance/ta97 (accessed 07.11.16)
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Zivin K, Yosef M, Miller EM et al (2015) Associations between depression and all-cause and cause-specific risk of death: a retrospective cohort study in the Veterans Health Administration. J Psychosom Res 78: 324–31

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