Incident Type 2 Diabetes Risk is Influenced by Obesity and Diabetes in Social Contacts: a Social Network Analysis

Facilitators and Barriers of Health Behaviors in Patients With Type 2 Diabetes: A Qualitative Study

PURPOSE

The purpose of the study was to explore the facilitators and barriers of health behaviors in patients with type 2 diabetes (T2D), providing a reference for the development of health behavior interventions programs.

METHODS

A qualitative descriptive research design was adopted, and interviews were conducted with 25 patients with T2D. The interview guide was developed based on the health action process approach theory. The interviews were audio-recorded and transcribed verbatim. Data analysis was performed using thematic analysis.

RESULTS

Through the analysis of interview data, 2 main themes were identified: facilitators and barriers of health behaviors, comprising 18 subthemes. The facilitators included self-efficacy, outcome expectations, risk perception, intention, action planning, coping planning, emotional regulation, proactive and sustained sense of responsibility, and multidimensional social support. The barriers included insufficient disease awareness, insufficient self-control, impact of social activities, low self-efficacy, accessibility of personal conditions, lack of problem-solving skills, lack of disease management knowledge, lack of social support, and cognitive decline.

CONCLUSIONS

When designing health behavior intervention programs for patients with T2D, it is crucial to consider both facilitators and barriers to enhance the effectiveness of the interventions to encourage patients to adopt healthy lifestyles, improve their quality of life, and reduce the occurrence of complications.

Vulnerability or Resiliency? A Two-Wave Panel Analysis of Social Network Factors Associated with Glycemic Levels among Mexican Immigrants in the Bronx, NYC, Before and During COVID-19

Latinos have high rates of type 2 diabetes mellitus (T2DM) yet are characterized as having health-promoting social networks. The impacts of COVID-19 on personal networks were complex, especially in urban areas with high proportion of immigrants such as the Bronx in NYC. Our objective was to test the extent to which network characteristics increase vulnerability or resiliency for glycemic control based on data gathered from Mexican-origin Bronx dwellers. We used two-wave panel study analyzing self-reported personal social networks (n=30participants; 600network members) and HbA1c levels via dried blood spots in 2019, before the COVID-19 pandemic, and in 2021, a time after initial lockdowns and when the pandemic was still ravaging the community of study. Regression models adjusted for individual-level variables including sociodemographic and health indicators (i.e., physical health including COVID-19 and mental health). We found that an increase in the proportion of network members with diabetes predicted an increase in participant's HbA1c levels from 2019 to 2021 (β=0.044, p < 0.05). Also, a greater proportion of network members consuming "an American diet" in 2019 predicted a decrease in participant's HbA1c levels (β=-0.028, p < 0.01), while a greater proportion of network members that encouraged participants' health in 2019 predicted an increase in participant's HbA1c levels (β=0.033, p < 0.05). Our study sheds light on specific social network characteristics relevant to individual diabetes outcomes, including potential longitudinal mechanistic effects that played out at the peak of the COVID-19 crisis.

Comparison of insulin resistance-associated parameters in US adults: a cross-sectional study

BACKGROUND

Triglyceride-glucose (TyG) is correlated with cardiovascular events caused by insulin resistance (IR). The aim of this study was to analyze the relationship between TyG and its related indicators and IR among US adults from 2007 to 2018 in the National Health and Nutrition Examination Survey (NHANES) database so as to identify more accurate and reliable predictors of IR.

METHODS

This is a cross-sectional study including 9884 participants (2255 with IR and 7629 without IR). TyG, TyG-body mass index (TyG-BMI), TyG waist circumference (TyG-WC), and TyG waist-to-height ratio (TyG-WtHR) were measured using standard formulas.

RESULTS

TyG, TyG-BMI, TyG-WC, and TyG-WtHR were significantly correlated with IR in the general population, with TyG-WC being the most strongly correlated, with an odds ratio of 8.00 (95% confidence interval 5.05-12.67) for the fourth quartile of TyG-WC compared with the first quartile in the adjusted model. Receiver operating characteristic (ROC) analysis of the participants showed that the maximum area under the TyG-WC curve was 0.8491, which was significantly higher than that of the other three indicators. Moreover, this trend was stable both among people of both genders and among patients with coronary heart disease (CHD), hypertension, and diabetes.

CONCLUSIONS

The present study confirms that the TyG-WC index is more successful than TyG alone in identifying IR. In addition, our findings demonstrate that TyG-WC is a simple and effective marker for screening the general US adult population and those with CHD, hypertension, and diabetes and can be effectively used in clinical practice.

Predictive Effect of Triglyceride Glucose-Related Parameters, Obesity Indices, and Lipid Ratios for Diabetes in a Chinese Population: A Prospective Cohort Study

Objective

The purpose of this study was to evaluate the association between triglyceride glucose (TyG) index and new-onset diabetes under different glycemic states and to compare the predictive value of TyG-related parameters, obesity indices, and lipid ratios for new-onset diabetes.

Methods

Data were collected from the China Health and Retirement Longitudinal Study (CHARLS), consisting of 6,258 participants aged ≥45 years. Participants were grouped according to their glycemic states. Cox proportional hazards models and restricted cubic spline regression were used to explore the association between TyG index and diabetes. Cox proportional hazard models were applied to confirm the predictive value of the optimal marker. Receiver operating characteristic (ROC) curves were used to compare the predictive value.

Results

TyG index was positively correlated with the risk of diabetes (hazard ratio (HR), 1.75; 95% confidence interval (CI), 1.56-1.97), and the linear association existed (p < 0.001). The highest correlation with diabetes was visceral adiposity index (VAI) (HR, 2.04; 95% CI, 1.44-2.90) in normal fasting glucose (NFG) group and TyG-body mass index (TyG-BMI) (HR, 2.53; 95% CI, 1.97-3.26) in impaired fasting glucose (IFG) group. The largest area under curve (AUC) was observed in TyG-waist-to-height ratio (TyG-WHtR) in the NFG group (AUC, 0.613; 95% CI, 0.527-0.700), and TyG-BMI had the highest AUC in the IFG group (AUC, 0.643; 95% CI, 0.601-0.685).

Conclusion

The association between TyG index and new-onset diabetes was positive and linear. TyG-WHtR was a clinically effective marker for identifying the risks of diabetes in the NFG group and TyG-BMI was an effective marker to predict diabetes in the IFG group.

Impacts of Triglyceride Glucose-Waist to Height Ratio on Diabetes Incidence: A Secondary Analysis of A Population-Based Longitudinal Data

BACKGROUND

The anthropometric indices (body mass index [BMI], waist circumference [WC] and waist-to-height ratio [WHtR]), triglyceride-glucose (TyG) index and TyG-related indicators (TyG-WHtR, TyG-BMI, TyG-WC) have been well documented to be highly correlated with insulin resistance (IR) and type 2 diabetes mellitus (T2DM). However, it was not immediately obvious which indicator would be optimal for screening people at risk of T2DM. Hence, this study intended to compare the predictive effects of the aforementioned markers on T2DM and to investigate the relation between baseline TyG-WHtR and incident T2DM.

METHODS

This longitudinal study included 15464 study population who were involved in the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) study from 2004 to 2015. The TyG index was defined as ln [FPG (mg/dL) ×fasting TG (mg/dL)/2]. And the TyG-WHtR was calculated as TyG index ×WHtR. We divided the participants into four groups according to the TyG-WHtR quartiles. The primary endpoint was the incidence of diabetes.

RESULTS

After a median follow-up of 5.4 years, 2.4% (373/15464) participants developed diabetes. The incidence of diabetes increased with ascending TyG-WHtR quartiles (P for trend<0.001). Multivariable Cox proportional hazard analysis showed that a one-unit increase in TyG-WHtR was independently correlated with a 2.714-fold higher risk of diabetes [hazard ratio (HR) 2.714, 95% confidence interval (CI) 1.942-3.793; P<0.001). Stratification analysis revealed that increased TyG-WHtR (per 1-unit) was consistently correlated with diabetes incidence in different subgroups. Moreover, TyG-WHtR outperformed the other parameters by presenting the biggest area under the ROC curve (AUC) in men (AUC 0.746, 95% CI 0.716-0.776, P<0.001). However, all pairwise comparisons of AUC between TyG-WHtR and other indicators were not statistically different except TyG-WHtR vs. WHtR in women.

CONCLUSIONS

A high TyG-WHtR is an important predictor of the increased cumulative risk of diabetes development. TyG-WHtR outperforms TyG, WHtR, TyG-WC and TyG-BMI in screening individuals who are susceptible to T2DM, especially in men.

Extension to 'combined SNA and LDA methods to understand adverse medical events': Doctor and nurse perspectives

BACKGROUND

Physicians and nurses are responsible for reporting medical adverse events. Each views these events through a different lens subject to their role-based perceptions and barriers. Physicians typically engage with diagnosis and treatment while nurses primarily care for patients' daily lives and mental well-being. This results in reporting and describing medical adverse events differently.

OBJECTIVE

We aimed to compare adverse medical event reports generated by physicians and nurses to better understand the differences and similarities in perspective as well as the nature of adverse medical events using social network analysis (SNA) and latent Dirichlet allocation (LDA).

METHODS

The current study examined data from the Maccabi Healthcare Community. Approximately 17,868 records were collected from 2000 to 2017 regarding medical adverse events. Data analysis used SNA and LDA to perform descriptive text analytics and understand underlying phenomenon.

RESULTS

A significant difference in harm levels reported by physicians and nurses was discovered. Shared topic keyword lists broken down by physicians and nurses were derived. Overall, communication, lack of attention, and information transfer issues were reported in medical adverse events data. Specialized keywords, more likely to be used by a physician were determined as: repeated prescriptions, diabetes complications, and x-ray examinations. For nurses, the most common special adverse event behavior keywords were vaccine problem, certificates of fitness, death and incapacity, and abnormal dosage.

CONCLUSIONS

Communication and inattentiveness appeared most frequently in medical adverse events reports regardless of whether doctors or nurses did the reporting. Findings suggest feedback and information sharing processes could be implemented as a step toward alleviating many issues. Institutional management, healthcare managers and government officials should take actions to decrease medical adverse events, many of which may be preventable.

Social networks and type 2 diabetes: a narrative review

It has been known for decades that social networks are causally related to disease and mortality risk. However, this field of research and its potential for implementation into diabetes care is still in its infancy. In this narrative review, we aim to address the state-of-the-art of social network research in type 2 diabetes prevention and care. Despite the diverse nature and heterogeneity of social network assessments, we can draw valuable lessons from the available studies. First, the structural network variable 'living alone' and the functional network variable 'lack of social support' have been associated with increased type 2 diabetes risk. The latter association may be modified by lifestyle risk factors, such as obesity, low level of physical activity and unhealthy diet. Second, smaller network size and less social support is associated with increased risk of diabetes complications, particularly chronic kidney disease and CHD. Third, current evidence shows a beneficial impact of social support on diabetes self-management. In addition, social support interventions were found to have a small, favourable effect on HbA_1c values in the short-term. However, harmonisation and more detailed assessment of social network measurements are needed to utilise social network characteristics for more effective prevention and disease management in type 2 diabetes.

Triglyceride glucose index as a tool to motivate early lifestyle modification in young adults at diabetes risk: The Baependi Heart Study

Considering that the incidence of type 2 diabetes mellitus (T2DM) has been increasing especially in developing countries and becoming a global public health problem, this study aims to evaluate the association between triglyceride glucose index (TyG) - which is a mathematical product of the fasting blood glucose and triglyceride levels - and incident T2DM in an adult sample in the Baependi Heart Study (BHS). The data were from the BHS cohort consisting of two periods: cycle 1 (2005-2006; n = 1712; 119 families) and cycle 2 (2010-2013; n = 3017; 127 families). A total of 1121 individuals (both sexes, 18-100 years) were selected if they were assessed in both cycles and not diagnosed with T2DM at baseline (cycle 1). Our findings showed that a participant's risk of developing T2DM increased almost 10 times for a one-unit increase in the TyG (odds ratio OR = 10.17, 95% CI, 7.51-13.93). The association when stratified by age was OR = 28.13 [95% CI, 14.03-56.41] for young adults, meaning that the risk of developing T2DM increased more than 28 times for a one-unit increase in the TyG. For the other groups, young middle-aged adults, old middle-aged adults, and seniors, we found OR = 4.84 [95% CI, 2.91-8.06], OR = 28.73 [95% CI, 10.63-77.65, and OR = 9.88 [95% CI, 3.16-30.90], respectively. A higher TyG implies a significant increase in the risk of developing T2DM, which could be an important screening tool to target early lifestyle intervention in Brazil.

Concordance of Cardiovascular Risk Factors and Behaviors in a Multiethnic US Nationwide Cohort of Married Couples and Domestic Partners

IMPORTANCE

Married couples and domestic partners have been reported to share similar environmental exposures, adopt similar behavior patterns, and have similar transferable characteristics. However, the degree to which couples share similar levels of cardiovascular risk factors and behaviors is uncertain.

OBJECTIVE

To assess within-couple concordance of the American Heart Association-defined Life's Simple 7 (LS7).

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional study with a longitudinal substudy of employees and spouses (or domestic partners) who participated in an employer-sponsored health assessment program throughout the United States between October 2014 and December 2018. Data were analyzed from November 1, 2019, to August 4, 2020.

EXPOSURES

Having a spouse or domestic partner.

MAIN OUTCOMES AND MEASURES

The LS7 risk factors and behaviors (smoking status, body mass index, exercise, diet, total cholesterol, blood pressure, and fasting glucose) were assessed by questionnaires, examinations, and laboratory tests. LS7 categories were scored as 2 for ideal, 1 for intermediate, or 0 for poor and summed to generate a CV health score.

RESULTS

The study included 10 728 participants (5364 couples): 7% were African American, 11% Hispanic, 21% Asian, and 54% White (median [interquartile range] age, 50 [41-57] years for men and 47 [39-55] for women). For most couples, both members were in the ideal category or both were in a nonideal category. Concordance ranged from 53% (95% CI, 52%-54%) for cholesterol to 95% (95% CI, 94%-95%) for diet. For the CV health score, in 79% (95% CI, 78%-80%) of couples both members were in a nonideal category, which was associated mainly with unhealthy diet (94% [95% CI, 93%-94%] of couples) and inadequate exercise (53% [95% CI, 52%-55%] of couples). However, in most couples, both members were in the ideal category for smoking status (60% [95% CI, 59%-61%] of couples) and glucose (56% [95% CI, 55%-58%]). Except for total cholesterol, when 1 member of a couple was in the ideal category, the other member was likely also to be in the ideal category: the adjusted odds ratios for also being in the ideal category ranged from 1.3 (95% CI, 1.1-1.5; P ≤ .001) for blood pressure to 10.6 (95% CI, 7.4-15.3; P ≤ .001) for diet. Concordance differed by ethnicity, socioeconomic status, and geographic location. A 5-year longitudinal analysis of 2186 couples found modest changes in concordance of blood pressure (from 55% [95% CI, 53%-57%] to 59% [95% CI, 57%-61%]; P < .001 for trend) and fasting glucose (from 64% [95% CI, 62%-66%] to 59% [95% CI, 57%-61%]; P < .001 for trend) with no change in other factors.

CONCLUSIONS AND RELEVANCE

In this study, high concordance of nonideal behaviors was found within couples; behavioral modification programs may benefit both the targeted and the nontargeted member of a couple.

Combined SNA and LDA methods to understand adverse medical events

OBJECTIVE

To compare primary medical adverse event keywords from reporters (e.g. physicians and nurses) and harm level perspectives to explore the underlying behaviors of medical adverse events using social network analysis (SNA) and latent Dirichlet allocation (LDA) leading to process improvements.

DESIGN

Used SNA methods to explore primary keywords used to describe the medical adverse events reported by physicians and nurses. Used LDA methods to investigate topics used for various harm levels. Combined the SNA and LDA methods to discover common shared topic keywords to better understand underlying behaviors of physicians and nurses in different harm level medical adverse events.

SETTING

Maccabi Healthcare Community is the second largest healthcare organization in Israel.

DATA

17,868 medical adverse event data records collected between 2000 and 2017.

METHODS

Big data analysis techniques using social network analysis (SNA) and latent Dirichlet allocation (LDA).

RESULTS

Shared topic keywords used by both physicians and nurses were determined. The study revealed that communication, information transfer, and inattentiveness were the most common problems reported in the medical adverse events data.

CONCLUSIONS

Communication and inattentiveness were the most common problems reported in medical adverse events regardless of healthcare professional reporting or harm levels. Findings suggested that an information-sharing and feedback mechanism should be implemented to eliminate preventable medical adverse events. Healthcare institutions managers and government officials should take targeted actions to decrease these preventable medical adverse events through quality improvement efforts.

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.

Team Collaboration Networks and Multidisciplinarity in Diabetes Care: Implications for Patient Outcomes

Prevalence of type 2 diabetes mellitus (T2DM) has almost doubled in recent decades and commonly presents comorbidities and complications. T2DM is a multisystemic disease, requiring multidisciplinary treatment provided by teams working in a coordinated and collaborative manner. The application of social network analysis techniques in the healthcare domain has allowed researchers to analyze interaction between professionals and their roles inside care teams. We studied whether the structure of care teams, modeled as complex social networks, is associated with patient progression. For this, we illustrate a data-driven methodology and use existing social network analysis metrics and metrics proposed for this research. We analyzed appointment and HbA1c blood test result data from patients treated at three primary health care centers, representing six different practices. Patients with good metabolic control during the analyzed period were treated by teams that were more interactive, collaborative and multidisciplinary, whereas patients with worsening or unstable metabolic control were treated by teams with less collaboration and more continuity breakdowns. Results from the proposed metrics were consistent with the previous literature and reveal relevant aspects of collaboration and multidisciplinarity.

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

AIMS

To examine whether the development of obesity with age was different for individuals with and without a spouse with diabetes.

METHODS

We analysed data from the English Longitudinal Study of Ageing [n= 7123, median (interquartile range) age 59 (53-67) years, 51% men], which included four clinical examination waves between 1998 and 2012. The main exposure was having a spouse with diabetes. Outcomes of interest were BMI and waist circumference. We fitted quadratic age-related trajectories using mixed-effect models stratified by sex and adjusted for education, smoking and the corresponding interaction terms between age and spousal diabetes status.

RESULTS

The baseline spousal diabetes prevalence was 4.4%. Men with a wife with diabetes experienced a steeper increase in BMI (1.6 kg/m² ) between ages 50 to 65 years than men with a wife without diabetes (0.9 kg/m² ). Women with a husband with diabetes had a similarly shaped BMI trajectory to women with a husband without diabetes, but their average BMI levels were higher between ages 55 and 65 years. Waist circumference trajectories showed a similar shape by spousal diabetes status for men and women, although individuals with a spouse with diabetes had higher waist circumference values throughout follow-up.

CONCLUSIONS

We found a positive association between spousal diabetes status and obesity development, which differed by sex among middle-aged individuals. Evidence from couple-based interventions is needed to test whether the latter could improve the current individual-focused public health strategies for obesity prevention.

A scalable online tool for quantitative social network assessment reveals potentially modifiable social environmental risks

Social networks are conduits of support, information, and health behavior flows. Existing measures of social networks used in clinical research are typically summative scales of social support or artificially truncated networks of ≤ 5 people. Here, we introduce a quantitative social network assessment tool on a secure open-source web platform, readily deployable in large-scale clinical studies. The tool maps an individual's personal network, including specific persons, their relationships to each other, and their health habits. To demonstrate utility, we used the tool to measure the social networks of 1493 persons at risk of multiple sclerosis. We examined each person's social network in relation to self-reported neurological disability. We found that the characteristics of persons surrounding the participant, such as negative health behaviors, were strongly associated with the individual's functional disability. This quantitative assessment reveals the key elements of individuals' social environments that could be targeted in clinical trials.

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

AIMS/HYPOTHESIS

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS/INTERPRETATION

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 ( https://discover.ukdataservice.ac.uk/catalogue/?sn=5050&type=Data%20catalogue ).

Triglyceride glucose-waist circumference, a novel and effective predictor of diabetes in first-degree relatives of type 2 diabetes patients: cross-sectional and prospective cohort study

BACKGROUND

Body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI), triglyceride glucose index (TyG), TyG-BMI, and TyG-WC have been reported as markers of insulin resistance or type 2 diabetes mellitus (T2DM). However, little is known about the associations between the aforementioned markers and the risk of prediabetes and diabetes in first-degree relatives (FDRs) of T2DM patients.

METHODS

1544 FDRs of T2DM patients (635 men and 909 women) were enrolled in the initial cross-sectional study and all of them finished corresponding examinations. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to compare and identify the associations of the six parameters (BMI, WC, VAI, TyG, TyG-BMI and TyG-WC) with the prevalence of prediabetes and diabetes. Subsequently, 452 of them were followed-up for an average of 5 years. Cox proportional hazard regression model was applied to confirm the predictive value of the optimal marker.

RESULTS

Among the indices, TyG-WC was more strongly associated with the prevalence of prediabetes and diabetes. Compared with participants in the lowest quartile of TyG-WC, the adjusted odds ratio and 95 % CIs for prediabetes and diabetes was 11.19 (7.62-16.42) for those in the top quartile of TyG-WC. Moreover, the largest AUC was also observed in TyG-WC (0.765, 95 % CIs 0.741-0.789, P < 0.001). The robust predictive value of TyG-WC was further confirmed in the follow-up study (HR: 7.13, 95 % CIs 3.41-14.90, P < 0.001).

CONCLUSIONS

TyG-WC is a novel and clinically effective marker for early identifying the risks of prediabetes and diabetes in FDRs of T2DM patients.