Diabetes: Sociodemographic predictors, comorbidity and causes of death

Sammanfattning: Specific aims: To examine whether the sociodemographic characteristics of patients with type 2 diabetes affect the odds of reaching the recommended treatment goals for HbA1c and blood lipids (study 1). To investigate whether the odds of coronary heart disease are higher in patients with diabetes living in deprived neighborhoods than in those living in wealthy neighborhoods (Study 2). To examine the relationship between depression, neighborhood deprivation, and risk of type 2 diabetes (study 3). To examine the association between total and cause-specific mortality and neighborhood deprivation in patients with diabetes (Study 4). Methods: In study 1, data from clinical records on 5048 people with type 2 diabetes from 25 primary health care centers in Stockholm, Sweden, were linked to national population registers. Logistic regression was used to estimate odds ratios (ORs). In study 2, the National Prescription Drug Register was used to identify the 334,406 patients with diabetes. Data were linked to the National Inpatient Register and the Population Register. Multilevel logistic regression was used to estimate the odds for coronary heart disease. In study 3, 336,340 adults from primary health care centers in Sweden were under study. Multilevel logistic regression was used to assess associations between depression and risk of type 2 diabetes across neighborhoods. In study 4, the Swedish nationwide Prescription Drug Register was used to identify 367,477 patients with diabetes who were followed for total and cause-specific mortality. Multilevel logistic regression was used in the statistical analyses. Results: Less than 50% reached the recommended levels of HbA1c, total cholesterol and low-density lipoprotein cholesterol. Individuals with the lowest income levels were less likely to reach the recommended level of HbA1c (study 1). The odds of coronary heart disease were significantly higher among patients with diabetes living in deprived neighborhoods than among those living in wealthy neighborhoods (study 2). Depression and neighborhood deprivation were significantly associated with diabetes (study 3). The OR for total and for certain cause-specific mortality increased with increasing neighborhood deprivation, after adjustments (study 4). Conclusions: Health care workers and decision-makers should be aware of the variation by neighborhood and sociodemographic characteristics in risk factor control, morbidity and mortality in patients with diabetes. These findings highlight the importance of effective preventive interventions in patients with diabetes and with a particular focus on those who are socioeconomically compromised. Further research is important to examine possible mechanisms behind these findings.