Abstract

Background:Previous observational studies have shown similarities in cardiometabolic risk factors between spouses. It is still possible that this result reflects the age similarity of spouses rather than environmental factors of spouses (e.g. cohabitation effect). To clarify the importance of mate cardiometabolic risk factors for similarity of environmental factors, it is necessary to examine whether they are observed in random male-female pairs while maintaining the age of the spousal pairs. This study aimed to determine whether the similarities found between spousal pairs for cardiometabolic risks were also observed between random male-female pairs.Methods:This cross-sectional study included 5,391 spouse pairs from Japan; data were obtained from a large biobank study. For pairings, women of the same age were randomly shuffled to create new male-female pairs of the same age as that of the original spouse pairs. Similarities in cardiometabolic risk factors between the random male-female pairs were analysed using Pearson’s correlation or age-adjusted logistic regression analyses.Results:The mean ages of the men and women were 63.2 and 60.4 years, respectively. Almost all cardiometabolic risk factors similarities were not noted in cardiometabolic risk factors, including the continuous risk factors (anthropometric traits, blood pressure, glycated haemoglobin level, and lipid traits); lifestyle habits (smoking, drinking, and physical activity); or diseases (hypertension, type 2 diabetes mellitus, and metabolic syndrome) between the random male-female pairs. The age-adjusted correlation coefficients ranged from − 0.007 for body mass index to 0.071 for total cholesterol. The age-adjusted odds ratio (95% confidence interval) for current drinkers was 0.94 (0.81 − 1.09); hypertension, 1.07 (0.93 − 1.23); and type 2 diabetes mellitus, 1.08 (0.77 − 1.50).Conclusion:In this study, few similarities in cardiometabolic risk factors were noted among the random male-female pairs. As spouse pairs may share environmental factors, intervention strategies targeting lifestyle habits and preventing lifestyle-related diseases may be effective.

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