, Volume 61, Issue 7, pp 1572–1580 | Cite as

Spousal cardiometabolic risk factors and incidence of type 2 diabetes: a prospective analysis from the English Longitudinal Study of Ageing

  • Jannie NielsenEmail author
  • Adam Hulman
  • Daniel R. Witte



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 availability

Data were accessed via the UK Data Service under the data-sharing agreement no. 91400 (


Cardiometabolic risk factors Obesity Primary prevention Screening Secondary prevention Spouse Type 2 diabetes Undiagnosed diabetes 



Diastolic BP


English Longitudinal Study of Ageing


Incidence rate


Incidence rate ratio


Systolic BP


Socioeconomic status



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.

Contribution statement

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.

Supplementary material

125_2018_4587_MOESM1_ESM.pdf (421 kb)
ESM (PDF 420 kb)


  1. 1.
    Knowler WC, Fowler SE, Hamman RF et al (2009) 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet 374:1677–1686CrossRefPubMedGoogle Scholar
  2. 2.
    Lindstrom J, Ilanne-Parikka P, Peltonen M et al (2006) Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the Finnish Diabetes Prevention Study. Lancet 368:1673–1679CrossRefPubMedGoogle Scholar
  3. 3.
    Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA (2008) 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 359:1577–1589CrossRefPubMedGoogle Scholar
  4. 4.
    Holman RR, Paul SK, Bethel MA, Neil HA, Matthews DR (2008) Long-term follow-up after tight control of blood pressure in type 2 diabetes. N Engl J Med 359:1565–1576CrossRefPubMedGoogle Scholar
  5. 5.
    Kearney PM, Blackwell L, Collins R et al (2008) Efficacy of cholesterol-lowering therapy in 18,686 people with diabetes in 14 randomised trials of statins: a meta-analysis. Lancet 371:117–125CrossRefPubMedGoogle Scholar
  6. 6.
    National Cardiovascular Intelligence Network (NCVIN) (2015) NHS Diabetes Prevention Programme (NHS DPP) non-diabetic hyperglycaemia. Public Health England, LondonGoogle Scholar
  7. 7.
    Mainous AG 3rd, Tanner RJ, Baker R, Zayas CE, Harle CA (2014) Prevalence of prediabetes in England from 2003 to 2011: population-based, cross-sectional study. BMJ Open 4:e005002CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Geiss LS, James C, Gregg EW, Albright A, Williamson DF, Cowie CC (2010) Diabetes risk reduction behaviors among U.S. adults with prediabetes. Am J Prev Med 38:403–409CrossRefPubMedGoogle Scholar
  9. 9.
    National Institute for Health and Care Excellence (2016) Type 2 diabetes: prevention in people at high risk: public health guideline [PH38]. Available from Accessed 27 Sep 2017
  10. 10.
    Robson J, Dostal I, Sheikh A et al (2016) The NHS Health Check in England: an evaluation of the first 4 years. BMJ Open 6:e008840CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Sargeant LA, Simmons RK, Barling RS et al (2010) Who attends a UK diabetes screening programme? Findings from the ADDITION-Cambridge study. Diabet Med 27:995–1003CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Cook EJ, Sharp C, Randhawa G, Guppy A, Gangotra R, Cox J (2016) Who uses NHS health checks? Investigating the impact of ethnicity and gender and method of invitation on uptake of NHS health checks. Int J Equity Health 15:13CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Bender AM, Jorgensen T, Pisinger C (2015) Is self-selection the main driver of positive interpretations of general health checks? The Inter99 randomized trial. Prev Med 81:42–48CrossRefPubMedGoogle Scholar
  14. 14.
    Barrett-Connor E, Suarez L (1982) Spouse concordance for fasting plasma glucose in non-diabetics. Am J Epidemiol 116:475–481CrossRefPubMedGoogle Scholar
  15. 15.
    Hippisley-Cox J, Coupland C, Pringle M, Crown N, Hammersley V (2002) Married couples’ risk of same disease: cross sectional study. BMJ 325:636CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Jurj AL, Wen W, Li HL et al (2006) Spousal correlations for lifestyle factors and selected diseases in Chinese couples. Ann Epidemiol 16:285–291CrossRefPubMedGoogle Scholar
  17. 17.
    Christakis NA, Fowler JH (2007) The spread of obesity in a large social network over 32 years. N Engl J Med 357:370–379CrossRefPubMedGoogle Scholar
  18. 18.
    Chen HJ, Liu Y, Wang Y (2014) Socioeconomic and demographic factors for spousal resemblance in obesity status and habitual physical activity in the United States. J Obes 2014:703215CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Hemminki K, Li X, Sundquist K, Sundquist J (2010) Familial risks for type 2 diabetes in Sweden. Diabetes Care 33:293–297CrossRefPubMedGoogle Scholar
  20. 20.
    Raghavan S, Pachucki MC, Chang Y et al (2016) Incident type 2 diabetes risk is influenced by obesity and diabetes in social contacts: a social network analysis. J Gen Intern Med 31:1127–1133CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Leong A, Rahme E, Dasgupta K (2014) Spousal diabetes as a diabetes risk factor: a systematic review and meta-analysis. BMC Med 12:12CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Steptoe A, Breeze E, Banks J, Nazroo J (2013) Cohort profile: the English Longitudinal Study of Ageing. Int J Epidemiol 42:1640–1648CrossRefPubMedGoogle Scholar
  23. 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,
  24. 24.
    Carstensen B (2007) Age-period-cohort models for the Lexis diagram. Stat Med 26:3018–3045CrossRefPubMedGoogle Scholar
  25. 25.
    Carstensen B, Plummer M, Laara E, Hills M (2017) Epi: a package for statistical analysis in epidemiology. Available from (version 2.24)
  26. 26.
    Cunningham SA, Adams SR, Schmittdiel JA, Ali MK (2017) Incidence of diabetes after a partner’s diagnosis. Prev Med 105:52–57CrossRefPubMedGoogle Scholar
  27. 27.
    Khan A, Lasker SS, Chowdhury TA (2003) Are spouses of patients with type 2 diabetes at increased risk of developing diabetes? Diabetes Care 26:710–712CrossRefPubMedGoogle Scholar
  28. 28.
    Patel SA, Dhillon PK, Kondal D et al (2017) Chronic disease concordance within Indian households: a cross-sectional study. PLoS Med 14:e1002395CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Ask H, Rognmo K, Torvik FA, Roysamb E, Tambs K (2012) Non-random mating and convergence over time for alcohol consumption, smoking, and exercise: the Nord-Trondelag Health Study. Behav Genet 42:354–365CrossRefPubMedGoogle Scholar
  30. 30.
    Katzmarzyk PT, Perusse L, Rao DC, Bouchard C (1999) Spousal resemblance and risk of 7-year increases in obesity and central adiposity in the Canadian population. Obes Res 7:545–551CrossRefPubMedGoogle Scholar
  31. 31.
    Cobb LK, McAdams-DeMarco MA, Gudzune KA et al (2016) Changes in body mass index and obesity risk in married couples over 25 years: the ARIC cohort study. Am J Epidemiol 183:435–443CrossRefPubMedGoogle Scholar
  32. 32.
    Manson JE, Rimm EB, Stampfer MJ et al (1991) Physical activity and incidence of non-insulin-dependent diabetes mellitus in women. Lancet 338:774–778CrossRefPubMedGoogle Scholar
  33. 33.
    Wei M, Gibbons LW, Mitchell TL, Kampert JB, Lee CD, Blair SN (1999) The association between cardiorespiratory fitness and impaired fasting glucose and type 2 diabetes mellitus in men. Ann Intern Med 130:89–96CrossRefPubMedGoogle Scholar
  34. 34.
    Ekelund U, Franks PW, Sharp S, Brage S, Wareham NJ (2007) Increase in physical activity energy expenditure is associated with reduced metabolic risk independent of change in fatness and fitness. Diabetes Care 30:2101–2106CrossRefPubMedGoogle Scholar
  35. 35.
    Jacobi D, Caille A, Borys JM et al (2011) Parent-offspring correlations in pedometer-assessed physical activity. PLoS One 6:e29195CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Flagg LA, Sen B, Kilgore M, Locher JL (2014) The influence of gender, age, education and household size on meal preparation and food shopping responsibilities. Public Health Nutr 17:2061–2070CrossRefPubMedGoogle Scholar
  37. 37.
    White E, Hurlich M, Thompson RS et al (1991) Dietary changes among husbands of participants in a low-fat dietary intervention. Am J Prev Med 7:319–325CrossRefPubMedGoogle Scholar
  38. 38.
    Gorin AA, Wing RR, Fava JL et al (2008) Weight loss treatment influences untreated spouses and the home environment: evidence of a ripple effect. Int J Obes 32:1678–1684CrossRefGoogle Scholar
  39. 39.
    Abbasi A, Sahlqvist AS, Lotta L et al (2016) A systematic review of biomarkers and risk of incident type 2 diabetes: an overview of epidemiological, prediction and aetiological research literature. PLoS One 11:e0163721CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Kautzky-Willer A, Harreiter J, Pacini G (2016) Sex and gender differences in risk, pathophysiology and complications of type 2 diabetes mellitus. Endocr Rev 37:278–316CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Global Health Section, Department of Public HealthUniversity of CopenhagenCopenhagen K.Denmark
  2. 2.Hubert Department of Global Health, Rollins School of Public HealthEmory UniversityAtlantaUSA
  3. 3.Department of Public HealthAarhus UniversityAarhusDenmark
  4. 4.Danish Diabetes AcademyOdenseDenmark

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