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

Partnership and marriage and risk of type 2 diabetes: a narrative review

In this review, we discuss how partnership and marriage influence cardiometabolic risk factors and risk of type 2 diabetes, and how couple-based approaches to type 2 diabetes prevention might complement individual-focused prevention efforts. There is some evidence that being married per se has a small positive effect on type 2 diabetes risk. Moreover, there is spousal concordance for many type 2 diabetes risk factors due to assortative mating and convergence during partnership, with weak to moderate correlations found for anthropometric measures, blood pressure, lipid concentrations, smoking, alcohol consumption and physical activity level. A meta-analysis shows that people have a higher risk of type 2 diabetes if their spouse has diabetes (OR 1.72, 95% CI 1.47, 2.02). However, despite some evidence, there is still a lack of research on similar associations in relation to progression to type 2 diabetes and diabetes complications. Several studies have suggested that behaviour changes, for example smoking cessation or weight loss, in one partner increase the likelihood that the other partner will make the same changes. Subsequent studies of couple-based interventions that focus on both partners have shown that people are more likely to adhere to a diabetes prevention programme if their partners are also involved in the programme. However, the effect of the quality of marriage on the outcome of an intervention is still unclear. Couple-based interventions are promising, but there is a lack of RCTs comparing couple-based interventions with individual-centred interventions.

Classification and identification of risk factors for type 2 diabetes

The risk factors for type 2 diabetes mellitus (T2DM) have been increasingly researched, but the lack of systematic identification and categorization makes it difficult for clinicians to quickly and accurately access and understand all the risk factors, which are categorized in this paper into five categories: Social determinants, lifestyle, checkable/testable risk factors, history of illness and medication, and other factors, which are discussed in a narrative review. Meanwhile, this paper points out the problems of the current research, helps to improve the systematic categorisation and practicality of T2DM risk factors, and provides a professional research basis for clinical practice and industry decision-making.

The association between an individual's development of non-communicable diseases and their spouse's development of the same disease: the Longitudinal Survey of Middle-aged and Elderly Persons

BACKGROUND

Studies have shown that married couples often share similar lifestyles, as well as lifestyle-associated conditions such as diabetes, hypertension, and hyperlipidemia. This study aims to prospectively investigate the association between an individual's development of a non-communicable disease and the subsequent development of the same condition in their spouse.

METHODS

This population-based cohort study utilized 12 waves of annual prospective surveys from 2005 onwards in Japan, with a discrete-time design. A total of 9,417 middle-aged couples (18,834 participants; discrete-time observations = 118,876) were included. Each participant whose spouse had developed one of six conditions was propensity score-matched with five controls whose spouses had not been diagnosed with the condition: diabetes [n = 1374 vs n = 6870], hypertension [n = 2657 vs n = 13285], hypercholesterolemia [n = 3321 vs n = 16605], stroke [n = 567 vs n = 2835], coronary heart disease (CHD) [n = 1093 vs n = 5465] or cancer [n = 923 vs n = 4615]. Using conditional logistic regression, we assessed participants' development of the same condition within three years following their spouse's diagnosis.

RESULTS

Participants whose spouses had developed diabetes, hypertension, hypercholesterolemia, or CHD were more likely to develop the same condition within three years. The odds ratios (ORs) and 95% confidence intervals (CIs) were: 1.96 (1.53-2.50), 1.20 (1.06-1.36), 1.63 (1.47-1.81) and 1.43 (1.05-1.95), respectively. No significant associations were observed in stroke [1.69 (0.80-3.58)] or cancer [1.08 (0.75-1.54)].

CONCLUSION

Spouses of individuals recently diagnosed with certain metabolic conditions are at a higher risk of developing those conditions themselves. These findings may provide valuable guidance for targeting and personalizing chronic disease screening and prevention efforts.

Assessing the economic impact of obesity and overweight on employers: identifying opportunities to improve work force health and well-being

BACKGROUND AND OBJECTIVES

Obesity is a major public health issue, significantly affecting national and individual health and economic well-being. This study quantifies the economic impact of excess body weight on employers and employees in 2023, offering insights for obesity prevention and treatment.

METHODS

We utilized data from the National Health Interview Survey, National Health and Nutrition Examination Survey, Medical Expenditure Panel Survey, and Current Population Survey. Published reports and original estimates were combined to assess the economic burden for the U.S. and across seven major industries (Construction, Education & Health, Financial Activities, Government, Manufacturing, Professional & Business Services, and Transportation & Utilities). We compared the economic outcomes for adults with obesity and overweight to those with healthy weight, focusing on direct and indirect costs. Potential savings from different weight loss scenarios were estimated using the Disease Prevention & Treatment Microsimulation Model.

RESULTS

In 2023, among 158 million civilian employees on nonfarm payrolls, 30% had obesity and 34% had overweight, resulting in a combined economic burden of $425.5 billion (obesity: $347.5 billion; overweight: $78 billion). This includes excess medical costs of obesity ($115 billion), presenteeism (obesity: $113.8 billion; overweight: $46.5 billion), absenteeism from obesity ($82.3 billion), excess medical costs of overweight ($31.5 billion), obesity-related disability payments ($31.1 billion), and workers' compensation payments ($5.2 billion). For a hypothetical firm with 10,000 employees (plus dependents), the annual costs were $22 million for obesity and $4.9 million for overweight, with average costs of $6472 per employee with obesity, $1244 per employee with overweight, $1514 per adult dependent with obesity, and $380 per adult dependent with overweight. Medical savings over 5 years range from $153.3 billion with a 5% weight loss to $326.1 billion with 25% weight loss at the industry level.

CONCLUSION

The substantial economic costs imposed by obesity and overweight on employers and employees highlight the need for resources dedicated to treatment and prevention, which can result in reduced medical expenses and improved productivity.

What is the impact of one's chronic illness on his or her spouse's future chronic illness: a community-based prospective cohort study

BACKGROUND

Integrating a joint approach to chronic disease management within the context of a couple has immense potential as a valuable strategy for both prevention and treatment. Although spousal concordance has been reported in specific chronic illnesses, the impact they cumulatively exert on a spouse in a longitudinal setting has not been investigated. We aimed to determine whether one's cumulative illness burden has a longitudinal impact on that of their spouse.

METHODS

Data was acquired from a community-based prospective cohort that included Koreans aged 60 years and over, randomly sampled from 13 districts nationwide. Data from the baseline assessment (conducted from November 2010 to October 2012) up to the 8-year follow-up assessment was analyzed from October 2021 to November 2022. At the last assessment, partners of the index participants were invited, and we included 814 couples in the analysis after excluding 51 with incomplete variables. Chronic illness burden of the participants was measured by the Cumulative Illness Rating Scale (CIRS). Multivariable linear regression and causal mediation analysis were used to examine the longitudinal effects of index chronic illness burden at baseline and its change during follow-up on future index and spouse CIRS scores.

RESULTS

Index participants were divided based on baseline CIRS scores (CIRS < 6 points, n = 555, mean [SD] age 66.3 [4.79] years, 43% women; CIRS ≥ 6 points, n = 259, mean [SD] age 67.7 [4.76] years, 36% women). The baseline index CIRS scores and change in index CIRS scores during follow-up were associated with the spouse CIRS scores (β = 0.154 [SE: 0.039], p < 0.001 for baseline index CIRS; β = 0.126 [SE: 0.041], p = 0.002 for change in index CIRS) at the 8-year follow-up assessment. Subgroup analysis found similar results only in the high CIRS group. The baseline index CIRS scores and change in index CIRS scores during follow-up had both direct and indirect effects on the spouse CIRS scores at the 8-year follow-up assessment.

CONCLUSIONS

The severity and course of one's chronic illnesses had a significant effect on their spouse's future chronic illness particularly when it was severe. Management strategies for chronic diseases that are centered on couples may be more effective.

Couple concordance in diabetes, hypertension and dyslipidaemia in urban India and Pakistan and associated socioeconomic and household characteristics and modifiable risk factors

BACKGROUND

Concordance in chronic disease status has been observed within couples. In urban India and Pakistan, little is known about couple concordance in diabetes, hypertension, and dyslipidaemia and associated socioeconomic characteristics and modifiable risk factors.

METHODS

We analysed cross-sectional data from 2548 couples from the Centre for cArdio-metabolic Risk Reduction in South Asia cohort in Chennai, Delhi and Karachi. We estimated couple concordance in presence of ≥1 of diabetes, hypertension and dyslipidaemia (positive concordance: both spouses (W+H+); negative concordance: neither spouse (W-H-); discordant wife: only wife (W+H-); or discordant husband: only husband (W-H+)). We assessed associations of five socioeconomic and household characteristics, and six modifiable risk factors with couple concordance using multinomial logistic regression models with couples as the unit of analysis (reference: W-H-).

RESULTS

Of the couples, 59.4% (95% CI 57.4% to 61.3%) were concordant in chronic conditions (W+H+: 29.2% (95% CI 27.4% to 31.0%); W-H-: 30.2% (95% CI 28.4%- to 32.0%)); and 40.6% (95% CI 38.7% to 42.6%) discordant (W+H-: 13.1% (95% CI 11.8% to 14.4%); W-H+: 27.6% (95% CI 25.9% to 29.4%)). Compared with couples with no conditions (W-H-), couples had higher relative odds of both having at least one condition if they had higher versus lower levels of: income (OR 2.03 (95% CI 1.47 to 2.80)), wealth (OR 2.66 (95% CI 1.98 to 3.58)) and education (wives' education: OR 1.92 (95% CI 1.29 to 2.86); husbands' education: OR 2.98 (95% CI 1.92 to 4.66)) or weight status (overweight or obesity in both spouses ORs 7.17 (95% CI 4.99 to 10.30)).

CONCLUSIONS

Positive couple concordance in major chronic conditions is high in urban India and Pakistan, especially among couples with relatively higher socioeconomic position. This suggests that prevention and management focusing on couples at high risk for concordant chronic conditions may be effective and more so in higher socioeconomic groups.

Predictive value of women's weight trajectories in determining familial cardiovascular disorders: a family-based longitudinal study

Considering the dynamic nature of body mass index (BMI) and its importance in determining cardiovascular risks, this study aimed to investigate the life-course trajectory pattern of women’s BMI and its association with cardiovascular risk factors. A total of 1356 couples with 2976 children were recruited and followed up for an average period of 20 years. Latent growth curve modeling was applied to determine women's BMI trajectories; logistic regression was used to investigate the associations between trajectory patterns and cardiovascular risk factors, including hypertension (HTN), dyslipidemia, diabetes mellitus (DM), and obesity. Women were classified into three trajectories, including normal, stage 1 obesity, and stage 2 obesity. Compared to women’s in the normal trajectory group, those in obesity trajectories had higher odds ratios for HTN, DM, and dyslipidemia. Men with obese spouses showed a higher rate of HTN 1.54 (95% CI 1.05–2.25) and DM 1.55; (95% CI 1.00–2.44). The odds of men’s obesity were higher in obese spouses (OR 1.70; 95% CI 1.10–2.62). Offspring of stage 2 obese (OR 2.39; 95% CI 1.67–3.44) and stage 1 obese (OR 4.81; 95% CI 3.16–7.34) mothers were more likely to be obese. Our findings emphasized paying more attention to women with excessive weight to promote familial cardiovascular health in the communities.

Association of Social Network Characteristics With Cardiovascular Health and Coronary Artery Calcium in South Asian Adults in the United States: The MASALA Cohort Study

Background

South Asian adults have worse cardiovascular health (CVH) and more coronary artery calcium compared with other race/ethnicities. The impact of the social environment has not been examined as a potential driver of CVH or coronary artery calcium in this population. We evaluated associations of social network characteristics with CVH and coronary artery calcium in South Asian American adults to inform strategies for CVH promotion in this at‐risk population.

Methods and Results

Using data from the MASALA (Mediators of Atherosclerosis in South Asians Living in America) cohort study, multinomial and multivariable logistic regression were used to evaluate associations of participant social network size and density, proportion of network who are kin or South Asian ethnicity and reported health of participant's identified social network members (“alters”), with participant CVH and presence of coronary artery calcium. The 699 MASALA participants included were mean age 59.2 (SD, 9.2) years and 42.9% women. After adjustment, a 1‐person larger social network size was associated with 13% higher odds of ideal CVH (odds ratio [OR], 1.13; 95% CI, 1.01–1.27). Reporting an alter with high blood pressure was associated with lower odds of ideal CVH (OR, 0.51; 95% CI, 0.29–0.88), and reporting an alter with high cholesterol was associated with lower odds of ideal CVH (OR, 0.54; 95% CI, 0.30–0.94).

Conclusions

Social network characteristics are associated with CVH in South Asian American adults. Engaging social networks may help promote CVH in this population.

Spousal metabolic risk factors and incident hypertension: A longitudinal cohort study in Iran

We investigated the association between metabolic risk factors in one spouse with incident hypertension in the other. Study sample included 1528 men and 1649 women aged ≥20 years from the Tehran lipid and glucose study with information on body mass index (BMI), waist circumference (WC), hypertension, type 2 diabetes mellitus (DM), and dyslipidemia. The hazard ratio (HR) and 95% confidence interval (95% CI) were estimated for the association of spousal metabolic factors and incident hypertension among men and women separately. A total of 604 and 566 cases of incident hypertension were observed in men and women, respectively. Among men, spousal DM was associated with a 40% (CI: 1.07-1.83) excess risk of hypertension after adjusting for the men's own and their spouse's risk factors including BMI, DM, smoking, and physical activity level. Among women, spousal DM was associated with more than two times (2.11, 1.69-2.63) higher risk of hypertension. After further adjustment for the women's own and their spouse's risk factors, the association was attenuated and remained marginally significant (1.25, 0.99-1.58; P value = .053). Having a spouse with DM increases an individual's risk of hypertension, which raises the possibility of using preexisting information of one partner to guide the screening of the other partner.

Sex differences in the association between spousal metabolic risk factors with incidence of type 2 diabetes: a longitudinal study of the Iranian population

BACKGROUND

We investigated whether metabolic risk factors in one spouse were associated with an excessive risk of type 2 diabetes in the other.

METHODS

The study cohort (1999-2018) included 1833 men and 1952 women, aged ≥ 20 years with information on both their own and their spouse's diabetes status and metabolic risk factors including body mass index (BMI), waist circumference, systolic and diastolic blood pressure, triglyceride to high-density lipoprotein cholesterol ratio, and type 2 diabetes. The associations between spousal metabolic risk factors and type 2 diabetes were estimated using Cox regression models adjusted for the three nested sets of covariates.

RESULTS

We found 714 (360 men and 354 women) incident cases of type 2 diabetes, after more than 15 years of follow-up. Among women, having a husband with diabetes was associated with a 38% (hazard ratio (HR) 1.38; 95% confidence interval (CI) 1.03, 1. 84) increased risk of type 2 diabetes, adjusted for age, socioeconomic status, individual's own value of the respective spousal exposure variable, family history of diabetes, and physical activity level. After further adjustment for the woman's own BMI level, the husband's diabetes was associated with 23% (HR 1.23; 0.92, 1.64) higher risk of type 2 diabetes in wives, values which did not reach statistical significance. No significant associations were found between spousal metabolic risk factors and incidence of type 2 diabetes among index men.

CONCLUSION

We found a sex-specific effect of spousal diabetes on the risk of type 2 diabetes. Having a husband with diabetes increased an individual's risk of type 2 diabetes. Our results might contribute to the early detection of individuals at high risk of developing type 2 diabetes, particularly, in women adversely affected by their partner's diabetes.

Spousal diabetes status as a risk factor for incident type 2 diabetes: a prospective cohort study and meta-analysis

AIMS

It is unclear if the presence of type-2 diabetes in one spouse is associated with the development of diabetes in the other spouse. We studied the concordance of diabetes among black and white participants in the Atherosclerosis Risk in Communities (ARIC) study and summarized existing studies in a meta-analysis.

METHODS

We conducted a prospective cohort analysis of ARIC data from 8077 married men and women (mean age 54 years) without diabetes at baseline (1987-1989). Complementary log-log models that accounted for interval censoring was used to model the hazard ratio (HR) for the association of spousal diabetes status with the incidence of diabetes. For the meta-analysis, we searched MEDLINE and EMBASE for observational studies published through December 2018 that evaluated spousal concordance for diabetes.

RESULTS

During a median follow-up of 22 years, 2512 incident cases of diabetes were recorded. In models with adjustment for general adiposity, spousal cardiometabolic factors and other diabetes risk factors, adults who had a spouse with diabetes had elevated risk for incident diabetes compared to those without a spouse diagnosed with diabetes (HR 1.20, 95% confidence interval 1.02-1.41). This association did not differ by sex or race. Summarized estimates from the 17 studies (489,798 participants from 9 countries) included in the meta-analysis showed a positive association between spousal diabetes status and the development of diabetes (Pooled odds ratio 1.88, 95% CI 1.52-2.33).

CONCLUSIONS

Results from this large prospective biracial cohort and meta-analysis provides evidence that spouses of persons with diabetes are a high-risk group for diabetes.

Spouses, social networks and other upstream determinants of type 2 diabetes mellitus

Diabetes risk factors outside the individual are receiving increasing attention. In this issue of Diabetologia, Nielsen et al (DOI: https://doi.org/10.1007/s00125-018-4587-1 ) demonstrate that an individual's obesity level is associated with incident type 2 diabetes in their spouse. This is in line with studies providing evidence for spousal and peer similarities in lifestyle behaviours and obesity. Non-random mating and convergence over time are two explanations for this phenomenon, but shared exposure to more upstream drivers of diabetes may also play a role. From a systems-science perspective, these mechanisms are likely to occur simultaneously and interactively as part of a complex system. In this commentary, we provide an overview of the wider system-level factors that contribute to type 2 diabetes.