Spousal cardiometabolic risk factors and incidence of type 2 diabetes: a prospective analysis from the English Longitudinal Study of Ageing
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In the UK, more than one million people have undiagnosed diabetes and an additional five million are at high risk of developing the disease. Given that early identification of these people is key for both primary and secondary prevention, new screening approaches are needed. Since spouses resemble each other in cardiometabolic risk factors related to type 2 diabetes, we aimed to investigate whether diabetes and cardiometabolic risk factors in one spouse can be used as an indicator of incident type 2 diabetes in the other spouse.
We analysed data from 3649 men and 3478 women from the English Longitudinal Study of Ageing with information on their own and their spouse’s diabetes status and cardiometabolic risk factors. We modelled incidence rates and incidence rate ratios with Poisson regression, using spousal diabetes status or cardiometabolic risk factors (i.e. BMI, waist circumference, systolic and diastolic BP, HDL- and LDL-cholesterol and triacylglycerols) as exposures and type 2 diabetes incidence in the index individual as the outcome. Models were adjusted for two nested sets of covariates.
Spousal BMI and waist circumference were associated with incident type 2 diabetes, but with different patterns for men and women. A man’s risk of type 2 diabetes increased more steeply with his wife’s obesity level, and the association remained statistically significant even after adjustment for the man’s own obesity level. Having a wife with a 5 kg/m2 higher BMI (30 kg/m2 vs 25 kg/m2) was associated with a 21% (95% CI 11%, 33%) increased risk of type 2 diabetes. In contrast, the association between incident type 2 diabetes in a woman and her husband’s BMI was attenuated after adjusting for the woman’s own obesity level. Findings for waist circumference were similar to those for BMI. Regarding other risk factors, we found a statistically significant association only between the risk of type 2 diabetes in women and their husbands’ triacylglycerol levels.
The main finding of this study is the sex-specific effect of spousal obesity on the risk of type 2 diabetes. Having an obese spouse increases an individual’s risk of type 2 diabetes over and above the effect of the individual’s own obesity level among men, but not among women. Our results suggest that a couples-focused approach may be beneficial for the early detection of type 2 diabetes and individuals at high risk of developing type 2 diabetes, especially in men, who are less likely than women to attend health checks.
Data were accessed via the UK Data Service under the data-sharing agreement no. 91400 (https://discover.ukdataservice.ac.uk/catalogue/?sn=5050&type=Data%20catalogue).
KeywordsCardiometabolic risk factors Obesity Primary prevention Screening Secondary prevention Spouse Type 2 diabetes Undiagnosed diabetes
English Longitudinal Study of Ageing
Incidence rate ratio
The authors are grateful to the ELSA researchers and the UK Data Archive for making the ELSA data available. The ELSA study was developed by researchers from the University College London, the Institute of Fiscal Studies and the National Centre for Social Research, UK. The developers and funders of ELSA do not bear any responsibility for the analyses or interpretations presented here. Parts of the data in this article were also presented as an abstract at the 53rd EASD Annual Meeting in 2017.
JN developed the conception of the study, contributed to the statistical analyses and the interpretation of data, and drafted, revised and finalised the article. AH contributed to the study design, was responsible for the statistical analyses, and contributed to the interpretation of data and development, revision and finalisation of the manuscript. DRW developed the conception of the study, supervised the statistical analysis, and contributed to the interpretation of the data and development, revision and finalisation of the manuscript. All authors approved the final version of the manuscript. JN and AH are the guarantors of this work.
JN’s postdoctoral fellowship was supported by the Danish Council for Independent Research (DFF – 5053-00263). AH and DRW are supported by the Danish Diabetes Academy. The Danish Diabetes Academy is funded by the Novo Nordisk Foundation.
Duality of interest
The authors declare that there is no duality of interest associated with this manuscript.
- 6.National Cardiovascular Intelligence Network (NCVIN) (2015) NHS Diabetes Prevention Programme (NHS DPP) non-diabetic hyperglycaemia. Public Health England, LondonGoogle Scholar
- 9.National Institute for Health and Care Excellence (2016) Type 2 diabetes: prevention in people at high risk: public health guideline [PH38]. Available from www.nice.org.uk/guidance/ph38/chapter/1-Recommendations#recommendation-3-risk-identification-stage-1. Accessed 27 Sep 2017
- 23.Marmot M, Oldfield, Z, Clemens, S, et al (2017) English Longitudinal Study of Ageing: Waves 0-7, 1998-2015. [data collection]. 27th Edition. UK Data Service. SN: 5050, https://doi.org/10.5255/UKDA-SN-5050-14
- 25.Carstensen B, Plummer M, Laara E, Hills M (2017) Epi: a package for statistical analysis in epidemiology. Available from https://CRAN.R-project.org/package=Epi. (version 2.24)