Spousal concordance in pathophysiological markers and risk factors for type 2 diabetes: a cross-sectional analysis of The Maastricht Study

• Main Authors: Miranda T Schram, Coen D A Stehouwer, Nicolaas C Schaper, Omar Silverman-Retana, Stephanie Brinkhues, Adam Hulman, Simone Eussen, Pieter Dagnelie, Martien C J M van Dongen
• Format: Article
• Language: English
• Published: BMJ Publishing Group 2021-08-01
• Series: BMJ Open Diabetes Research & Care
• Online Access: https://drc.bmj.com/content/9/1/e001879.full

Introduction We compared the degree of spousal concordance in a set of detailed pathophysiological markers and risk factors for type 2 diabetes to understand where in the causal cascade spousal similarities are most relevant.Research design and methods This is a cross-sectional analysis of couples who participated in The Maastricht Study (n=172). We used quantile regression models to assess spousal concordance in risk factors for type 2 diabetes, including four adiposity measures, two dimensions of physical activity, sedentary time and two diet indicators. We additionally assessed beta cell function and insulin sensitivity and glucose metabolism status with fasting and 2-hour plasma glucose and hemoglobin A1c.Results The strongest spousal concordance (beta estimates) was observed for the Dutch Healthy Diet Index (DHDI) in men. A one-unit increase in wives’ DHDI was associated with a 0.53 (95% CI 0.22 to 0.67) unit difference in men’s DHDI. In women, the strongest concordance was for the time spent in high-intensity physical activity (HPA); thus, a one-unit increase in husbands’ time spent in HPA was associated with a 0.36 (95% CI 0.17 to 0.64) unit difference in women’s time spent in HPA. The weakest spousal concordance was observed in beta cell function indices.Conclusions Spousal concordance was strongest in behavioral risk factors. Concordance weakened when moving downstream in the causal cascade leading to type 2 diabetes. Public health prevention strategies to mitigate diabetes risk may benefit from targeting spousal similarities in health-related behaviors and diabetes risk factors to design innovative and potentially more effective couple-based interventions.