Concordance of health states in couples: Analysis of self-reported, nurse administered and blood-based biomarker data in the UK Understanding Society panel

Abstract

We use self-reported health measures, nurse-administered measurements and blood-based biomarkers to examine the concordance between health states of partners in marital/cohabiting relationships in the UK. A model of cumulative health exposures is used to interpret the empirical pattern of between-partner health correlation in relation to elapsed relationship duration, allowing us to distinguish non-causal correlation due to assortative mating from potentially causal effects of shared lifestyle and environmental factors. We find important differences between the results for different health indicators, with strongest homogamy correlations observed for adiposity, followed by blood pressure, heart rate, inflammatory markers and cholesterol, and also self-assessed general health and functional difficulties. We find no evidence of a "dose-response relationship" for marriage duration, and show that this suggests - perhaps counterintuitively - that shared lifestyle factors and homogamous partner selection make roughly equal contributions to the concordance we observe in most of the health measures we examine.

Trajectories of obesity by spousal diabetes status in the English Longitudinal Study of Ageing

“…Spousal concordance in diabetes risk factors might be attributable either to people choosing a partner who is similar (assortative mating) or to joint development of risk because of the environment shared by the couple. Previous studies suggest that BMI-assortative mating occurs more frequently at the extreme of the BMI distribution [15], but also that spousal BMI and waist circumference correlations were similar regardless of length of marriage [16]. We found similar spousal BMI correlations and higher spousal waist circumference correlations than those previously reported [2,4].…”

“…Previous studies suggest that BMI-assortative mating occurs more frequently at the extreme of the BMI distribution [15], but also that spousal BMI and waist circumference correlations were similar regardless of length of marriage [16]. Previous studies suggest that BMI-assortative mating occurs more frequently at the extreme of the BMI distribution [15], but also that spousal BMI and waist circumference correlations were similar regardless of length of marriage [16].…”

Intergenerational social mobility and allostatic load in Great Britain

“…We first z-transform our biomarkers, then calculate the mean score of the transformed biomarkers, and lastly z-transform that resulting score. For robustness checks, we use a different approach where we dichotomise the biomarkers once they surpass a clinically relevant, high-risk cut-off value (cut-off values reported in online supplementary file, table A2, see also Davillas and Pudney29). Our main measure captures greater variation as it is not reliant on clinical cut-offs, thereby accounting for the full range of predisease states, not just the ‘elevated risk zone’.…”

Family lifestyle dynamics and childhood obesity: evidence from the millennium cohort study

“…These studies are based on adoption or twin studies (a very specific part of the population) and generally look only at descriptive statistics and correlations, rather than accounting for other confounding factors. In studies which use more flexible and complex statistical techniques to account for a wider range of confounding factors generally suggest that this correlation is at least equally due to non-genetic influences, such as lifestyle or behavioural influences [ 8 , 9 , 15 – 20 ]. Correlations between spouses which are less likely to be a result of genetic influences than correlations between blood relatives, provide further support for the argument that shared lifestyle significantly influences correlations between family members [ 6 , 8 ].…”