Cardiometabolic Multimorbidity Research Articles

Temporal trends in co-morbidities and cardiometabolic risk factors at the time of type 2 diabetes diagnosis in the UK.

To evaluate temporal patterns in co-morbidities, cardiometabolic risk factors and a high atherosclerotic cardiovascular disease (ASCVD) risk population at type 2 diabetes (T2D) diagnosis by age groups and sex. From the UK primary care database, 248,619 people with a new diagnosis of T2D during 2005-2016 were identified. Among people without ASCVD, high ASCVD risk was defined as two or more of current smoker, grade 2+ obesity, hypertension, dyslipidaemia or microvascular disease. Cardiometabolic multimorbidity (CMM) was defined as two or more of cardiovascular disease, microvascular disease, hypertension, dyslipidaemia, grade 2+ obesity or cancer. Temporal patterns in the distribution of cardiometabolic risk factors were evaluated. While the prevalence of ASCVD was stable over time (approximately 18%), 50% were identified to have a high ASCVD risk (26% and 38% in the 18-39 and 40-49 years age groups, respectively), with an increasing trend across all age groups. Overall, 51% had CMM at diagnosis, increasing during 2005-2016 for the 18-39 years age group by 14%-17%, for the 40-49 years age group by 27%-33%, for the 50-59 years age group by 41%-50%, for the 60-69 years age group by 56%-65%, and for the 70-79 years age group by 65%-80%. People with young-onset T2D had significantly higher HbA1c, body mass index and lipids at diagnosis (all p < .01). The proportions with an HbA1c of 7.5% or higher in the 18-39 and 40-49 years age groups were 58% and 54%, respectively, significantly and consistently higher over the last decade compared with those aged 50 years or older, with males having higher proportions of 15-26 and 10-18 percentage points, respectively, compared with females. CMM and high ASCVD risk have been increasing consistently across all age groups and in both sex, in particular CMM in those aged younger than 50 years. Our findings indicate that the European Society of Cardiology-European Association for the Study of Diabetes recommendations need to change to consider people with young-onset T2D as a high-risk group, as recommended in the Primary Care Diabetes Europe position statement.

Association of Cardiometabolic Multimorbidity and Depression With Cardiovascular Events in Early-Onset Adult Type 2 Diabetes: A Multiethnic Study in the U.S.

To evaluate the temporal patterns of cardiometabolic multimorbidity (CM) and depression in White Caucasians (WCs) and African Americans (AAs) with early-onset type 2 diabetes and their impact on long-term atherosclerotic cardiovascular disease (ASCVD). From U.S. electronic medical records, 101,104 AA and 505,336 WC subjects with type 2 diabetes diagnosed between 2000 and 2017 were identified (mean follow-up 5.3 years). Among those without ASCVD at diagnosis, risk of ASCVD and three-point major adverse cardiovascular events (MACE-3) (heart failure, myocardial infarction, or stroke) was evaluated between ethnicities by age-groups. The proportion of patients diagnosed at <50 years of age increased during 2012-2017 (AA 34-38%, WC 26-29%). Depression prevalence increased during 2000-2017 (AA 15-23%, WC 20-34%), with an increasing trend for CM at diagnosis in both groups. Compared with WC, the adjusted MACE-3 risk was significantly higher in AA across all age-groups, more pronounced in the 18-39-year age-group (hazard ratio 95% CI 1.42, 1.88), and in patients with and without depression. AAs had a 17% (1.05, 1.31) significantly higher adjusted ASCVD risk in the 18-39-year age-group only. Depression was independently associated with ASCVD and MACE-3 risk in both ethnic groups across all age-groups. Other comorbidities were independently associated with ASCVD and MACE-3 risk only among WCs. AAs have higher cardiovascular risk compared with WCs, particularly in early-onset type 2 diabetes. CM and depression at diabetes diagnosis have been increasing over the past two decades in both ethnic groups. Strategies for screening and optimal management of CM and depression, particularly in early-onset type 2 diabetes, may result in a lower cardiovascular risk.

Cardiometabolic multimorbidity is associated with a worse Covid-19 prognosis than individual cardiometabolic risk factors: a multicentre retrospective study (CoViDiab II)

BackgroundCardiometabolic disorders may worsen Covid-19 outcomes. We investigated features and Covid-19 outcomes for patients with or without diabetes, and with or without cardiometabolic multimorbidity.MethodsWe collected and compared data retrospectively from patients hospitalized for Covid-19 with and without diabetes, and with and without cardiometabolic multimorbidity (defined as ≥ two of three risk factors of diabetes, hypertension or dyslipidaemia). Multivariate logistic regression was used to assess the risk of the primary composite outcome (any of mechanical ventilation, admission to an intensive care unit [ICU] or death) in patients with diabetes and in those with cardiometabolic multimorbidity, adjusting for confounders.ResultsOf 354 patients enrolled, those with diabetes (n = 81), compared with those without diabetes (n = 273), had characteristics associated with the primary composite outcome that included older age, higher prevalence of hypertension and chronic obstructive pulmonary disease (COPD), higher levels of inflammatory markers and a lower PaO2/FIO2 ratio. The risk of the primary composite outcome in the 277 patients who completed the study as of May 15th, 2020, was higher in those with diabetes (Adjusted Odds Ratio (adjOR) 2.04, 95%CI 1.12–3.73, p = 0.020), hypertension (adjOR 2.31, 95%CI: 1.37–3.92, p = 0.002) and COPD (adjOR 2.67, 95%CI 1.23–5.80, p = 0.013). Patients with cardiometabolic multimorbidity were at higher risk compared to patients with no cardiometabolic conditions (adjOR 3.19 95%CI 1.61–6.34, p = 0.001). The risk for patients with a single cardiometabolic risk factor did not differ with that for patients with no cardiometabolic risk factors (adjOR 1.66, 0.90–3.06, adjp = 0.10).ConclusionsPatients with diabetes hospitalized for Covid-19 present with high-risk features. They are at increased risk of adverse outcomes, likely because diabetes clusters with other cardiometabolic conditions.

Management of chronic cardiometabolic conditions and mental health during COVID-19

Management of chronic cardiometabolic conditions and mental health during COVID-19

Association of Cardiometabolic Multimorbidity Pattern with Dietary Factors among Adults in South Korea.

Globally, cardiometabolic multimorbidity pattern (CMP) is a complex chronic health status that negatively effects the life expectancy of adults globally, even more than single diseases. We aimed to identify multimorbidity patterns in Korean adults to clarify the associations between dietary factors and CMP. Nationally representative data of 9011 Korean adults aged 19–64 years were obtained from the Korean National Health and Nutrition Examination Survey (KNHANES) from the period 2013 to 2015. Multimorbidity patterns for CMP, inflammatory disease, cancer and other disease patterns were identified by exploratory factor analysis. Dietary factors including food and nutrient intake and dietary habits were evaluated. Multivariable-adjusted logistic regression models examined the associations between dietary factors and CMP. More than half of the multimorbidity patterns were CMP (n = 4907, 54.5%); CMP subjects were more likely to be older, male, less educated, lower income, laborers, smokers, and high-risk consumers of alcohol than those of non-CMP subjects. A higher intake of calcium (OR = 0.809, 95% CI = 0.691–0.945), potassium (OR = 0.838, 95% CI = 0.704–0.998), and fruits (OR = 0.841, 95% CI = 0.736–0.960) were inversely associated with the prevalence of CMP, while the consumption of irregular meals (OR = 1.164, 95% CI = 1.034–1.312) and skipping breakfast (OR = 1.279, 95% CI = 1.078–1.518) was positively related to a 16% and 28% higher likelihood of CMP, respectively. CMP accounts for more than half of the multimorbidity patterns in the Korean population, and lower intake of calcium, potassium, fruits, and skipping meals have strong associations with CMP.

Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort.

It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. We studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.

Is polypharmacy beneficial or detrimental for older adults with cardiometabolic multimorbidity? Pooled analysis of studies from Hong Kong and Europe.

Physicians often prescribe high numbers of medications for managing multiple cardiometabolic diseases. It is questionable whether polypharmacy (concurrent use of five or more medications) is beneficial or detrimental for older adults with cardiometabolic multimorbidity (co-occurrence of two or more diseases). To examine combined effects of multimorbidity and polypharmacy on hospitalization and frailty and to determine whether effect sizes of polypharmacy vary with numbers of cardiometabolic diseases. We pooled longitudinal data of community-dwelling older adults in Hong Kong, Israel, and 17 European countries. They completed questionnaires for baseline assessment from 2015 to 2018 and reassessment at 1-2-year follow-up. We performed regression analyses to address the objective. Among 44 818 participants (mean age: 69.6 years), 28.3% had polypharmacy and 34.8% suffered from cardiometabolic multimorbidity. Increased risks of hospitalization and worsening frailty were found in participants with 'multimorbidity alone' [adjusted odds ratio (AOR) 1.10 and 1.26] and 'polypharmacy alone' (AOR 1.57 and 1.68). With 'multimorbidity and 'polypharmacy' combined, participants were not at additive risks (AOR 1.53 and 1.47). In stratified analysis, with increasing numbers of cardiometabolic diseases, associations of polypharmacy with hospitalization and frailty were attenuated but remained statistically significant. Polypharmacy is less detrimental, yet still detrimental, for older adults living with cardiometabolic multimorbidity. Physicians should optimize prescription regardless of the number of diseases. Health policymakers and researchers need to consider their interrelationship in hospitalization risk predictions and in developing frailty scales.

Effectiveness of a Home-Based Telehealth Exercise Training Program for Patients With Cardiometabolic Multimorbidity: A Randomized Controlled Trial.

Exercise training has positive effects on the management of cardiometabolic conditions. Little is known about the effectiveness of home-based telehealth exercise training programs among patients with cardiometabolic multimorbidity, which is associated with functional decline and decreased health-related quality of life. The aim of this study was to determine the effectiveness of a 12-week home-based telehealth exercise training program designed to increase physical activity and exercise capacity and improve health-related quality of life in patients with cardiometabolic multimorbidity. A randomized controlled trial was conducted. Fifty eligible patients with 2 or more cardiometabolic conditions from outpatient clinics of a medical center in Northern Taiwan were randomized to either an experimental group (EG; received a 12-week home-based telehealth exercise training program) or a control group (CG; maintained usual lifestyles). The home-based telehealth exercise training program consisted of 36 individualized home-based exercise training sessions and a weekly reminder for maintenance of exercise and providing patient support. Amounts of physical activity, exercise capacity, and health-related quality of life were assessed at baseline and 12 weeks. Generalized estimating equations were used to examine the intervention effects via the interaction of time and group. The EG had higher amounts of physical activity (β = 1333, P = .004) and moderate-intensity physical activity (β = 330, P = .04) than the CG after the intervention. The EG had increased exercise capacity (VO2peak, β = 4.43, P = .04), as well as improved health-related quality of life (physical function, β = 7.55, P = .03; and physical component summary, β = 4.42, P = .03) compared with those in the CG. A 12-week home-based telehealth exercise training program is feasible and effective in increasing amounts of physical activity, elevating exercise capacity, and improving health-related quality of life in patients with cardiometabolic multimorbidity.

A scoping review of polypharmacy interventions in patients with stroke, heart disease and diabetes.

Background Patients with cardiometabolic disease, specifically, stroke, heart disease and diabetes have a high prevalence of polypharmacy. Interventions to better manage or reduce polypharmacy in these populations may help improve patient outcomes. However, there is a paucity of data in this area, which needs to be investigated. Aim of the review The purpose of this scoping review was to identify and synthesize the available evidence pertaining to polypharmacy interventions in patients with cardiometabolic disease(s) and to determine what outcomes measures are assessed in these studies. Methods We followed an evidence-based scoping review guiding framework to address our study objectives. Three electronic databases (MEDLINE, EMBASE, CINAHL) were searched for all relevant studies up to May 2019. The Cochrane Library was also searched; studies included in relevant reviews were screened for inclusion. Reference lists of all included papers were also manually reviewed to identify additional articles. Polypharmacy interventions and measures used to assess efficacy were qualitatively described. Results Overall, six studies met the inclusion criteria. The majority of interventions were clinical pharmacist interventions reporting on a variety of outcomes including surrogate markers, quality of life and patient satisfaction, drug-related problems, and healthcare utilization and costs. The findings from the included studies generally indicated positive effects but had high risk of bias. Conclusions Existing polypharmacy interventions have some efficacy at improving a variety of patient and healthcare system outcomes. Increased frequency and duration of follow-up with patients led to significant improvements in quality of life, disease control and cost-savings in outpatient and in-patient settings. However, our analysis of the identified studies suggests low-quality evidence and significant knowledge gaps regarding patients with stroke and cardiometabolic multimorbidity. This signals a need for further high-quality research to both confirm these findings and include these other high-risk patient populations to validate these findings.

Abstract P375: Prospective Associations of Accelerometer-measured Physical Activity and Sedentary Time With Cardiometabolic Multimorbidity in the CARDIA Study

Background: Cardiometabolic multimorbidity is rising rapidly in the US. This condition is associated with greater health care burden and risk for adverse outcomes, including mortality. We investigated the relations of sedentary time (ST), light intensity physical activity (LPA), and moderate to vigorous intensity physical activity (MVPA) with future cardiometabolic multimorbidity in mid-life. Methods: Participants were 1,863 adults (mean ± SD age=45±4 years, 58% female, 39% Black) from the Coronary Artery Risk Development in Young Adults (CARDIA) study who wore an ActiGraph 7164 accelerometer in 2005-2006 (baseline). Cardiometabolic multimorbidity was defined as ≥2 measured cardiometabolic conditions (untreated/uncontrolled hypertension and hyperlipidemia, diabetes mellitus, chronic kidney disease, and clinical cardiovascular outcomes). Separate logistic regression models provided estimates of prospective associations of accelerometer-measured ST, LPA, and MVPA with cardiometabolic multimorbidity 10 years later in participants with &lt;2 cardiometabolic conditions at baseline. Interactions by age, sex, and race were explored. Results: The highest (&gt;47.3 min/d) vs. lowest (&lt;17.5 min/d) quartile of MVPA was associated with lower odds of cardiometabolic multimorbidity (OR: 0.61; CI: 0.37, 0.99) 10-years later. This association did not differ by age, race, or sex. Overall, there was no association between ST and cardiometabolic multimorbidity. However, a significant interaction was observed by age (p value=0.03). In age-stratified analyses, among participants ≥46 years at baseline, the highest (&gt;9.3 hr/d) vs. lowest (&lt;7.1 hr/d) quartile of ST was associated with higher odds of cardiometabolic multimorbidity (OR: 2.86; CI: 1.36, 6.17). No associations were observed between LPA and cardiometabolic multimorbidity. Conclusions: In mid-life adults with &lt;2 conditions at baseline, greater daily MVPA was associated with lower odds of future cardiometabolic multimorbidity burden 10 years later.

Leisure-time physical activity and life expectancy in people with cardiometabolic multimorbidity and depression.

Whether and to what extent leisure-time physical activity at the recommended levels of 150-min moderate activity is associated with survival in people with cardiometabolic multimorbidity and depression is unknown. UK Biobank participants were classified into groups: (i) no disease; (ii) diabetes; (iii) cardiovascular disease (CVD); (iv) depression; (v) diabetes and CVD; (vi) diabetes and depression; (vii) CVD and depression; (viii) diabetes, CVD and depression. Leisure-time physical activity was categorized as active (meeting recommendations) or inactive. Survival models were applied to estimate life expectancy. A total of 480940 participants were included (median age, 58years; 46% men; 95% white), of whom 74% with cardiometabolic multimorbidity and depression were inactive. During a mean follow-up of 7years, 11006 deaths occurred. At age of 45years, being physically active was associated with 2.34 (95% confidence interval: 0.93, 3.54) additional years of life compared with being inactive in participants with diabetes; corresponding estimates were 2.28 (1.40, 3.16) for CVD; 2.15 (0.05, 4.26) for diabetes and CVD; and 1.58 (1.27, 1.89) for no disease. Participants with a combination of diabetes, CVD and depression, being active was associated with 6.81 (-1.50, 15.31) additional years compared with being inactive; corresponding estimates were 3.07 (-2.46, 8.59) for diabetes and depression; 2.34 (-1.24, 5.91) for CVD and depression; and 0.80 (-0.46, 2.05) for depression. A similar pattern was found at 65years. Meeting the recommended level of physical activity was associated with a longer life expectancy in people with cardiometabolic multimorbidity but not in those with depression.

The prevalence of cardiometabolic multimorbidity and its association with physical activity, diet, and stress in Canada: evidence from a population-based cross-sectional study

BackgroundCardiometabolic multimorbidity (CM) is defined as having a diagnosis of at least two of stroke, heart disease, or diabetes, and is an emerging health concern, but the prevalence of CM at a population level in Canada is unknown. The objectives of this study were to quantify the: 1) prevalence of CM in Canada; and 2) association between CM and lifestyle behaviours (e.g., physical activity, consumption of fruits and vegetables, and stress).MethodsUsing data from the 2016 Canadian Community Health Survey, we estimated the overall and group prevalence of CM in individuals aged ≥50 years (n = 13,226,748). Multiple logistic regression was used to quantify the association between CM and lifestyle behaviours compared to a group without cardiometabolic conditions.ResultsThe overall prevalence of CM was 3.5% (467,749 individuals). Twenty-two percent (398,755) of people with diabetes reported having another cardiometabolic condition and thus CM, while the same was true for 32.2% (415,686) of people with heart disease and 48.4% (174,754) of stroke survivors. 71.2% of the sample reported eating fewer than five servings of fruits and vegetables per day. The odds of individuals with CM reporting zero minutes of physical activity was 2.35 [95% CI = 1.87 to 2.95] and having high stress was 1.89 [95% CI = 1.49 to 2.41] times the odds of the no cardiometabolic condition reference group. The odds of individuals with all three cardiometabolic conditions reporting zero minutes of physical activity was 4.31 [95% CI = 2.21 to 8.38] and having high stress was 3.93 [95% CI = 2.03 to 7.61].ConclusionThe number of Canadians with CM or at risk of CM is high and these individuals have lifestyle behaviours that are associated with adverse health outcomes. Lifestyle behaviours tend to diminish with increasing onset of cardiometabolic conditions. Lifestyle modification interventions focusing on physical activity and stress management for the prevention and management CM are warranted.

Cardiometabolic multimorbidity and depression in adults aged 45 years and older in China: longitudinal findings from the China Health and Retirement Longitudinal Study

BackgroundCardiometabolic diseases are prevalent in the older population worldwide and might have important roles in developing depression. However, few studies have investigated the associations between cardiometabolic multimorbidity and depression in older Chinese people. We aimed to examine the associations between cardiometabolic multimorbidity and depression in middle-aged and older Chinese people. MethodsWe included 15 162 participants aged 45 years or above from the China Health and Retirement Longitudinal Study (known as CHARLS). For this study, cardiometabolic multimorbidity included hypertension, heart problems, dyslipidaemia, and diabetes. We used the Center for Epidemiological Studies Depression Scale-10 to assess depression. We used generalised estimating equations to estimate the associations between cardiometabolic multimorbidity and depression. FindingsAfter adjusting for covariates, compared with no cardiometabolic multimorbidity, one (odds ratio 1·10; 95% CI 1·03–1·17), two (1·37; 1·25–1·50), three (1·55; 1·32–1·81), and four cardiometabolic multimorbidities (1·73; 1·33–2·25) were associated with depression. Compared with people with no cardiometabolic multimorbidity, those with hypertension only were not associated with depression (1·02; 0·94–1·10), whereas hypertension with one (1·34; 1·21–1·48), two (1·55; 1·31–1·82), and three cardiometabolic multimorbidities (1·73; 1·33–2·25) were associated with an increased risk of depression. For those with hypertension, compared with hypertension only, hypertension with heart problems only (1·50; 1·28–1·74), dyslipidaemia only (1·17; 1·01–1·37), diabetes only (1·32; 1·07–1·62), heart problems and dyslipidaemia (1·67; 1·38–2·01), heart problems and diabetes (2·14; 1·48–3·10), and all cardiometabolic multimorbidities (1·77; 1·35–2·31) were associated with depression. InterpretationIn middle-aged and older Chinese people, hypertension with no cardiometabolic multimorbidity is not associated with depression, whereas hypertension with cardiometabolic multimorbidity is associated with an increased risk of depression. A better understanding of the role of cardiometabolic multimorbidity on depression development might be helpful in improving the health-care plan for patients with cardiometabolic multimorbidity with a high risk of depression. FundingThe National Natural Science Foundation of China (81703304).

Prevalence and correlates of cardiometabolic multimorbidity among hypertensive individuals: a cross-sectional study in rural South Asia—Bangladesh, Pakistan and Sri Lanka

ObjectiveTo determinate the prevalence and correlates of cardiometabolic multimorbidity (CMM), and their cross-country variation among individuals with hypertension residing in rural communities in South Asia.DesignA cross-sectional study.SettingRural communities in Bangladesh,...

Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort

BackgroundMultimorbidity is associated with higher mortality, but the relationship with cancer and cardiovascular mortality is unclear. The influence of demographics and type of condition on the relationship of multimorbidity with mortality remains unknown. We examine the relationship between multimorbidity (number/type) and cause of mortality and the impact of demographic factors on this relationship.MethodsData source: the UK Biobank; 500,769 participants; 37-73 years; 53.7% female. Exposure variables: number and type of long-term conditions (LTCs) (N = 43) at baseline, modelled separately. Cox regression models were used to study the impact of LTCs on all-cause/vascular/cancer mortality during median 7-year follow-up. All-cause mortality regression models were stratified by age/sex/socioeconomic status.ResultsAll-cause mortality is 2.9% (14,348 participants). Of all deaths, 8350 (58.2%) were cancer deaths and 2985 (20.8%) vascular deaths. Dose-response relationship is observed between the increasing number of LTCs and all-cause/cancer/vascular mortality. A strong association is observed between cardiometabolic multimorbidity and all three clinical outcomes; non-cardiometabolic multimorbidity (excluding cancer) is associated with all-cause/vascular mortality. All-cause mortality risk for those with ≥ 4 LTCs was nearly 3 times higher than those with no LTCs (HR 2.79, CI 2.61–2.98); for ≥ 4 cardiometabolic conditions, it was > 3 times higher (HR 3.20, CI 2.56–4.00); and for ≥ 4 non-cardiometabolic conditions (excluding cancer), it was 50% more (HR 1.50, CI 1.36–1.67). For those with ≥ 4 LTCs, morbidity combinations that included cardiometabolic conditions, chronic kidney disease, cancer, epilepsy, chronic obstructive pulmonary disease, depression, osteoporosis and connective tissue disorders had the greatest impact on all-cause mortality. In the stratified model by age/sex, absolute all-cause mortality was higher among the 60–73 age group with an increasing number of LTCs; however, the relative effect size of the increasing number of LTCs on higher mortality risk was larger among those 37–49 years, especially men. While socioeconomic status was a significant predictor of all-cause mortality, mortality risk with increasing number of LTCs remained constant across different socioeconomic gradients.ConclusionsMultimorbidity is associated with higher all-cause/cancer/vascular mortality. Type, as opposed to number, of LTCs may have an important role in understanding the relationship between multimorbidity and mortality. Multimorbidity had a greater relative impact on all-cause mortality in middle-aged as opposed to older populations, particularly males, which deserves exploration.

Multimorbidity of cardiometabolic diseases: prevalence and risk for mortality from one million Chinese adults in a longitudinal cohort study

ObjectivesThe evolution of multimorbidity describes the continuum from a healthy status to the development of a single disease and further progression to multimorbidity with additional diseases. We investigated the evolution...

Clinical, socioeconomic, and behavioural factors at age 50 years and risk of cardiometabolic multimorbidity and mortality: A cohort study

BackgroundMultimorbidity is increasingly common and is associated with adverse health outcomes, highlighting the need to broaden the single-disease framework that dominates medical research. We examined the role of midlife clinical characteristics, socioeconomic position, and behavioural factors in the development of cardiometabolic multimorbidity (at least 2 of diabetes, coronary heart disease, and stroke), along with how these factors modify risk of mortality.Methods and findingsData on 8,270 men and women were drawn from the Whitehall II cohort study, with mean follow-up of 23.7 years (1985 to 2017). Three sets of risk factors were assessed at age 50 years, each on a 5-point scale: clinical profile (hypertension, hypercholesterolemia, overweight/obesity, family history of cardiometabolic disease), occupational position, and behavioural factors (smoking, alcohol consumption, diet, physical activity). The outcomes examined were cardiometabolic disease (diabetes, coronary heart disease, stroke), cardiometabolic multimorbidity, and mortality. We used multi-state models to examine the role of risk factors in 5 components of the cardiometabolic disease trajectory: from healthy state to first cardiometabolic disease, from first cardiometabolic disease to cardiometabolic multimorbidity, from healthy state to death, from first cardiometabolic disease to death, and from cardiometabolic multimorbidity to death. A total of 2,501 participants developed 1 of the 3 cardiometabolic diseases, 511 developed cardiometabolic multimorbidity, and 1,406 died. When behavioural and clinical risk factors were considered individually, only smoking was associated with all five transitions. In a model containing all 3 risk factor scales, midlife clinical profile was the strongest predictor of first cardiometabolic disease (hazard ratio for the least versus most favourable profile: 3.74; 95% CI: 3.14–4.45) among disease-free participants. Among participants with 1 cardiometabolic disease, adverse midlife socioeconomic (1.54; 95% CI: 1.10–2.15) and behavioural factors (2.00; 95% CI: 1.40–2.85), but not clinical characteristics, were associated with progression to cardiometabolic multimorbidity. Only midlife behavioural factors predicted mortality among participants with cardiometabolic disease (2.12; 95% CI: 1.41–3.18) or cardiometabolic multimorbidity (3.47; 95% CI: 1.81–6.66). A limitation is that the study was not large enough to estimate transitions between each disease and subsequent outcomes and between all possible pairs of diseases.ConclusionsThe importance of specific midlife factors in disease progression, from disease-free state to single disease, multimorbidity, and death, varies depending on the disease stage. While clinical risk factors at age 50 determine the risk of incident cardiometabolic disease in a disease-free population, midlife socioeconomic and behavioural factors are stronger predictors of progression to multimorbidity and mortality in people with cardiometabolic disease.

Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe

SummaryBackgroundAlthough overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight.MethodsWe pooled individual-participant data for BMI and incident cardiometabolic multimorbidity from 16 prospective cohort studies from the USA and Europe. Participants included in the analyses were 35 years or older and had data available for BMI at baseline and for type 2 diabetes, coronary heart disease, and stroke at baseline and follow-up. We excluded participants with a diagnosis of diabetes, coronary heart disease, or stroke at or before study baseline. According to WHO recommendations, we classified BMI into categories of healthy (20·0–24·9 kg/m2), overweight (25·0–29·9 kg/m2), class I (mild) obesity (30·0–34·9 kg/m2), and class II and III (severe) obesity (≥35·0 kg/m2). We used an inclusive definition of underweight (<20 kg/m2) to achieve sufficient case numbers for analysis. The main outcome was cardiometabolic multimorbidity (ie, developing at least two from: type 2 diabetes, coronary heart disease, and stroke). Incident cardiometabolic multimorbidity was ascertained via resurvey or linkage to electronic medical records (including hospital admissions and death). We analysed data from each cohort separately using logistic regression and then pooled cohort-specific estimates using random-effects meta-analysis.FindingsParticipants were 120 813 adults (mean age 51·4 years, range 35–103; 71 445 women) who did not have diabetes, coronary heart disease, or stroke at study baseline (1973–2012). During a mean follow-up of 10·7 years (1995–2014), we identified 1627 cases of multimorbidity. After adjustment for sociodemographic and lifestyle factors, compared with individuals with a healthy weight, the risk of developing cardiometabolic multimorbidity in overweight individuals was twice as high (odds ratio [OR] 2·0, 95% CI 1·7–2·4; p<0·0001), almost five times higher for individuals with class I obesity (4·5, 3·5–5·8; p<0·0001), and almost 15 times higher for individuals with classes II and III obesity combined (14·5, 10·1–21·0; p<0·0001). This association was noted in men and women, young and old, and white and non-white participants, and was not dependent on the method of exposure assessment or outcome ascertainment. In analyses of different combinations of cardiometabolic conditions, odds ratios associated with classes II and III obesity were 2·2 (95% CI 1·9–2·6) for vascular disease only (coronary heart disease or stroke), 12·0 (8·1–17·9) for vascular disease followed by diabetes, 18·6 (16·6–20·9) for diabetes only, and 29·8 (21·7–40·8) for diabetes followed by vascular disease.InterpretationThe risk of cardiometabolic multimorbidity increases as BMI increases; from double in overweight people to more than ten times in severely obese people compared with individuals with a healthy BMI. Our findings highlight the need for clinicians to actively screen for diabetes in overweight and obese patients with vascular disease, and pay increased attention to prevention of vascular disease in obese individuals with diabetes.FundingNordForsk, Medical Research Council, Cancer Research UK, Finnish Work Environment Fund, and Academy of Finland.

Association of Cardiometabolic Multimorbidity With Mortality.

The prevalence of cardiometabolic multimorbidity is increasing. To estimate reductions in life expectancy associated with cardiometabolic multimorbidity. Age- and sex-adjusted mortality rates and hazard ratios (HRs) were calculated using individual participant data from the Emerging Risk Factors Collaboration (689,300 participants; 91 cohorts; years of baseline surveys: 1960-2007; latest mortality follow-up: April 2013; 128,843 deaths). The HRs from the Emerging Risk Factors Collaboration were compared with those from the UK Biobank (499,808 participants; years of baseline surveys: 2006-2010; latest mortality follow-up: November 2013; 7995 deaths). Cumulative survival was estimated by applying calculated age-specific HRs for mortality to contemporary US age-specific death rates. A history of 2 or more of the following: diabetes mellitus, stroke, myocardial infarction (MI). All-cause mortality and estimated reductions in life expectancy. In participants in the Emerging Risk Factors Collaboration without a history of diabetes, stroke, or MI at baseline (reference group), the all-cause mortality rate adjusted to the age of 60 years was 6.8 per 1000 person-years. Mortality rates per 1000 person-years were 15.6 in participants with a history of diabetes, 16.1 in those with stroke, 16.8 in those with MI, 32.0 in those with both diabetes and MI, 32.5 in those with both diabetes and stroke, 32.8 in those with both stroke and MI, and 59.5 in those with diabetes, stroke, and MI. Compared with the reference group, the HRs for all-cause mortality were 1.9 (95% CI, 1.8-2.0) in participants with a history of diabetes, 2.1 (95% CI, 2.0-2.2) in those with stroke, 2.0 (95% CI, 1.9-2.2) in those with MI, 3.7 (95% CI, 3.3-4.1) in those with both diabetes and MI, 3.8 (95% CI, 3.5-4.2) in those with both diabetes and stroke, 3.5 (95% CI, 3.1-4.0) in those with both stroke and MI, and 6.9 (95% CI, 5.7-8.3) in those with diabetes, stroke, and MI. The HRs from the Emerging Risk Factors Collaboration were similar to those from the more recently recruited UK Biobank. The HRs were little changed after further adjustment for markers of established intermediate pathways (eg, levels of lipids and blood pressure) and lifestyle factors (eg, smoking, diet). At the age of 60 years, a history of any 2 of these conditions was associated with 12 years of reduced life expectancy and a history of all 3 of these conditions was associated with 15 years of reduced life expectancy. Mortality associated with a history of diabetes, stroke, or MI was similar for each condition. Because any combination of these conditions was associated with multiplicative mortality risk, life expectancy was substantially lower in people with multimorbidity.

Mortality in Iranian Patients with Parkinson's Disease: Cumulative Impact of Cardiovascular Comorbidities as One Major Risk Factor.

Mortality rate, life expectancy, survival, and the impact of comorbidities on them in people with Parkinson's disease (PD) need to be assessed in settings with different sociodemographic backgrounds. We investigated mortality features in Iranian PD patients focusing on the role of cardiovascular multimorbidity on their survival. Data on mortality and comorbidity profile was gathered in a cohort of 190 individuals with idiopathic PD referred to a Movement Disorders Clinic. Standardized mortality ratio (SMR) compared to the Tehran general population was 3.44 and the life expectancy at birth was 67.4 (95% CI: 59.1–75.8) yr. Patients with at least one cardiovascular comorbidity had a shorter survival time after PD onset (14.0 versus 29.2 yr, p = 0.012). The hazard ratio for death increased 2.8 times (95% CI: 1.5–5.2, p = 0.002) with one additional cardiovascular comorbidity. Among all comorbid conditions, stroke showed the strongest independent effect on mortality in PD patients [HR = 13.1 (95% CI: 2.4–71.7), p = 0.003]. Conclusively, life expectancy was slightly lower in Iranian PD patients compared to the general population, while the SMR was high. Cardiometabolic multimorbidity substantially decreased survival in people with PD. Our study highlights the need for assessment, prevention, and treatment of cardiovascular morbidities in parkinsonian patients, given their effect on survival.