Identifying patients with type 2 diabetes with a higher likelihood of erectile dysfunction: the role of the interaction between clinical and psychological factors
Abstract
Purpose:
We estimated the prevalence of erectile dysfunction in patients with type 2 diabetes and identified subgroups of patients in which the interaction among clinical, psychological and sociodemographic characteristics determined an increased likelihood of erectile dysfunction.
Materials and Methods:
The presence of erectile dysfunction was based on patient self-reporting. Clinical information was collected by participating physicians. The severity of depressive symptoms was investigated using the Center for Epidemiological Studies Depression scale. To evaluate interactions among the variables investigated and identify distinct, homogeneous subgroups of patients with different odds ratios for erectile dysfunction a tree growing technique was used.
Results:
In the 1,460 patients studied the prevalence of severe and mild-moderate erectile dysfunction was 34% and 24%, respectively. While severe erectile dysfunction was mainly related to the severity of diabetes, mild-moderate dysfunction was independent of clinical variables and only associated with the severity of depressive symptoms. The tree growing technique led to the identification of 6 classes characterized by a marked difference in the prevalence of severe erectile dysfunction of between 19% and 65%. Patients on diet alone showed the lowest prevalence of erectile dysfunction and were considered the reference category, while patients treated with insulin who had neuropathy represented the subgroup with the highest likelihood of erectile dysfunction (OR = 7.2, 95% CI 3.9 to 13.2). In patients treated with oral agents the odds ratio for erectile dysfunction was 2.7 (95% CI 1.8 to 3.9) for those with severe depressive symptoms and 1.9 (95% CI 1.3 to 2.7) for current/former smokers with low depressive symptoms. Patient age, retinopathy and cardiac-cerebrovascular disease were globally predictive variables associated with an increased likelihood of erectile dysfunction.
Conclusions:
Our data illustrate the interplay of clinical and psychological factors in determining the risk of erectile dysfunction in type 2 diabetes and can help identify those for whom much greater attention is needed to detect erectile problems.
References
- 1 : The epidemiology of erectile dysfunction and its risk factors. Int J Androl1997; 20: 323. Google Scholar
- 2 : The aetiology and management of erectile, ejaculatory, and fertility problems in men with diabetes mellitus. Diabet Med1996; 13: 700. Crossref, Medline, Google Scholar
- 3 NIH Consensus Conferenaaa Impotence. NIH Consensus Development Panel on Impotence. JAMA1993; 270: 83. Google Scholar
- 4 : Erectile dysfunction in diabetic subjects in Italy. Gruppo Italiano Studio Deficit Erettile nei Diabetici. Diabetes Care1998; 21: 1973. Google Scholar
- 5 : Sexual function in men with diabetes type 2: association with glycemic control. J Urol2000; 163: 788. Link, Google Scholar
- 6 : Prevalence of and risk factors for erectile dysfunction in Hong Kong diabetic patients. Diabet Med2001; 18: 732. Google Scholar
- 7 : The impact of blood glucose self-monitoring on metabolic control and quality of life in type 2 diabetic patients: an urgent need for better educational strategies. Diabetes Care2001; 24: 1870. Google Scholar
- 8 : Erectile dysfunction and quality of life in type 2 diabetic patients: a serious problem too often overlooked. Diabetes Care2002; 25: 284. Google Scholar
- 9 : The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas1977; 1: 385. Google Scholar
- 10 : Symptoms of depression in two communities. Psychol Med1976; 6: 551. Google Scholar
- 11 : Stratifying patients at risk of diabetic complications: an integrated look at clinical, socioeconomic, and care-related factors. SID-AMD Italian Study Group for the Implementation of the St. Vincent Declaration. Diabetes Care1998; 21: 1439. Google Scholar
- 12 :
Constructing prediction trees from data: the RECPAM approach . In: Proceedings from the Prague 1991 Summer School on Computational Aspects of Model Choice. Heidelberg: Physica-Verlag1992: 105. Google Scholar - 13 : Impotence and its medical and psychosocial correlates: results of the Massachusetts Male Aging Study. J Urol1994; 151: 54. Link, Google Scholar
- 14 : The relationship between depressive symptoms and male erectile dysfunction: cross-sectional results from the Massachusetts Male Aging Study. Psychosom Med1998; 60: 458. Google Scholar
- 15 : Drug-related erectile dysfunction. Adverse Drug React Toxicol Rev1999; 18: 5. Google Scholar
- 16 : Sexual dysfunction in the Unites States: prevalence and predictors. JAMA1999; 281: 537. Google Scholar
- 17 : Screening for depression in primary care clinics: the CES-D and the BDI. Int J Psychiatry Med1990; 20: 259. Google Scholar
- 18 : The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care2001; 24: 1069. Google Scholar
- 19 : The mutually reinforcing triad of depressive symptoms, cardiovascular disease, and erectile dysfunction. Am J Cardiol2000; 86: 41F. Google Scholar
From the Department of Clinical Pharmacology and Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri, Consorzio Mario Negri Sud, S. Maria Imbaro, Italy, and Tufts University School of Medicine, Boston, Massachusetts