Social Network Characteristics Are Associated With Type 2 Diabetes Complications: The Maastricht Study.

Brinkhues S, Dukers-Muijrers NHTM, Hoebe CJPA, van der Kallen CJH, Koster A, Henry RMA, Stehouwer CDA, Savelkoul PHM, Schaper NC, Schram MT.

 

OBJECTIVE:

The relation between clinical complications and social network characteristics in type 2 diabetes mellitus (T2DM) has hardly been studied. Therefore, we examined the associations of social network characteristics with macro- and microvascular complications in T2DM and investigated whether these associations were independent of glycemic control, quality of life, and well-known cardiovascular risk factors.

RESEARCH DESIGN AND METHODS:

Participants with T2DM originated from the Maastricht Study, a population-based cohort study (n = 797, mean age 62.7 ± 7.6 years, 31% female). Social network characteristics were assessed through a name generator questionnaire. Diabetes status was determined by an oral glucose tolerance test. Macro- and microvascular complications were defined as a history of cardiovascular disease and the presence of impaired vibratory sense and/or retinopathy and/or albuminuria, respectively. We assessed cross-sectional associations of social network characteristics with macro- and microvascular complications by use of logistic regression adjusted for age, HbA1c, quality of life, and cardiovascular risk factors, stratified for sex.

RESULTS:

A smaller network size, higher percentages of family members, and lower percentages of friends were independently associated with macrovascular complications in both men and women. A smaller network size and less informational support were independently associated with microvascular complications in women, but not in men.

CONCLUSIONS:

This study shows that social network characteristics were associated with macro- and microvascular complications. Health care professionals should be aware of the association of the social network with T2DM outcomes. In the development of strategies to reduce the burden of disease, social network characteristics should be taken into account.

https://www.ncbi.nlm.nih.gov/pubmed/29907582