Life's Simple 7 and ischemic heart disease in the general Australian population

Cardiovascular health assessed by the new life's essential 8 and the prevalence of urinary incontinence in adults

OBJECTIVE

To explore the association between cardiovascular health (CVH) measured by Life's Essential 8 (LE8) and the prevalence of urinary incontinence (UI).

METHOD

A cross-section study was conducted using data from the National Health and Nutrition Examination Survey 2007-2012. 22,609 people aged ≥ 20 years with complete information on LE8 metrics and UI questionnaires were enrolled. Participants were divided into three groups (low: < 50, moderate: ≥ 50 and < 80, high: ≥ 80) based on the cut-off of LE8. Weighted proportions, multivariable logistic regression analysis and stratified logistic regression were performed to examine the association between LE8 and the prevalence of three types of UI separately (stress UI (SUI), urge UI (UUI), mixed UI (MUI)) by confounding factors adjusted. Spline smooth was conducted to find whether a linear relationship existed. In addition, sensitive analyses were also conducted to observe the stability.

RESULT

A total of 22,609 adults were involved in the study, and participants were divided into three groups (low 42.2 ± 6.3, moderate 66.1 ± 8.1, high 86.8 ± 5.1) according to the cut-off points of LE8. The multivariable logistic regression suggested that LE8 is inversely associated with the prevalence of SUI (OR = 0.98, 95%CI 0.98 to 0.99), UUI (OR = 0.98, 95%CI 0.98 to 0.99), and MUI (OR = 0.98, 95%CI 0.97 to 0.98) in the fully-adjusted model. Compared with the low group, people with high scores of LE8 had a lower prevalence of SUI (OR = 0.45, 95%CI 0.37 to 0.55), UUI (OR = 0.49, 95%CI 0.40 to 0.60), and MUI (OR = 0.41, 95%CI 0.30 to 0.55). The result of the sensitive analysis showed the robustness of the main analysis.

CONCLUSION

The prevalence of UI (SUI, UUI, or MUI) is inversely associated with the LE8 score, which suggests that maintaining a good CVH with a higher LE8 score is accompanied by lower prevalence rates of UUI, SUI, and MUI.

Ideal cardiovascular health and cardiovascular-related events: a systematic review and meta-analysis

AIMS

The aim of this study was to systematically review and quantitatively summarize the evidence on the association between Life Simple's 7 (LS7) and multiple cardiovascular diseases (CVDs) and cardiometabolic diseases (CMDs).

METHODS AND RESULTS

EMBASE and PubMed were searched from January 2010 to March 2022 for observational studies that investigated the association between ideal cardiovascular health (CVH) with CVD or CMD outcomes in an adult population. Two reviewers independently selected studies according to the eligibility criteria, extracted data, and evaluated risk of bias. Data were analysed with a random-effects meta-analysis. This meta-analysis included 59 studies (1 881 382 participants). Participants with ideal CVH had a considerably lower risk of a variety of CVDs and CMDs as compared with those with poor CVH, varying from 40% lower risk for atrial fibrillation (AF) {hazard ratio [HR] = 0.60 [95% confidence interval (CI) 0.44-0.83]} to 82% lower risk for myocardial infarction [HR = 0.18 (95% CI 0.12-0.28)]. Intermediate CVH was associated with 27-57% lower risk in CVDs and CMDs compared with poor CVH, with the highest hazard for AF [HR = 0.73 (95% CI 0.59-0.91)] and the lowest hazard for peripheral arterial disease [HR = 0.43 (95% CI 0.30-0.60)].

CONCLUSION

Ideal and moderate CVH were associated with a lower incidence of CVDs and CMDs than poor CVH. Life Simple's 7 holds significant potential for promoting overall CVH and thereby contributing to the prevention of CVDs.

Trends in all-cause mortality and leading causes of death from 2009 to 2019 among older adults in China

BACKGROUND

This study aimed to determine long-term variations in mortality trends and identify the leading causes of death among older adults in China from 2009 to 2019 so as to propose interventions to further stabilise the mortality rate among older adults and facilitate healthy ageing.

METHODS

We extracted data from the China Death Surveillance database from 2009 to 2019 for all-cause mortality and cause-specific death among individuals aged ≥ 65 years. A joinpoint regression model was used to estimate mortality trends by calculating the annual percentage change (APC). A trend chi-square test was used to estimate sex differences in mortality, and descriptive analysis was used to estimate the leading causes of death. Semi-structured expert interviews were conducted to examine health interventions for older adults.

RESULTS

We observed an overall declining trend in age-adjusted mortality rates among older adults aged ≥ 65 years in China from 2009 to 2019 (APC, -2.44; P < 0.05). In this population, the male mortality rate was higher than the female mortality rate during this period (P < 0.05). However, the mortality rate among older adults aged ≥ 85 years increased since 2014, particularly among females. Cardiovascular disease (CVD) was the leading cause of death among older adults aged 65-84 years, whereas ischaemic heart disease was the leading cause of death among individuals aged ≥ 85 years, especially among females. The majority of injuries resulting in death were caused by falls, showing an increasing trend.

CONCLUSIONS

CVD is a major cause of death among older adults aged ≥ 65 years in China, and relevant health intervention strategies should be implemented from the perspectives of physiology, psychology, and living environment. The change in the mortality trend and the distribution of cause of death among older adults aged ≥ 85 years is noteworthy; a diagnostic and management model centred around females aged ≥ 85 years should be implemented. Additionally, a multidimensional fall prevention strategy involving primary medical institutions and care services needs to be implemented to reduce the risk of falls among older adults.

Cardiovascular health in early adulthood predicts the development of coronary heart disease in individuals with type 1 diabetes: 25 year follow-up from the Pittsburgh Epidemiology of Diabetes Complications study

AIMS/HYPOTHESIS

Type 1 diabetes increases CHD risk. We examined the use of the American Heart Association's cardiovascular health metrics (blood pressure, total cholesterol, glucose/HbA_1c, BMI, physical activity, diet, smoking) to predict incidence of CHD among individuals with type 1 diabetes, with the hypothesis that a better American Heart Association health metric profile would be associated with lower incident CHD.

METHODS

Prevalence of the seven cardiovascular health metrics was determined using first and second visits from adult participants (mean age 28.6 years) in the Epidemiology of Diabetes Complications prospective cohort study of childhood-onset type 1 diabetes. An ideal metric score (0-7) was defined as the sum of all metrics within the ideal range, and a total metric score (0-14) was calculated based on poor, intermediate and ideal categories for each metric. Incident CHD development (medical record-confirmed CHD death, myocardial infarction, revascularisation, ischaemic electrocardiogram changes or Epidemiology of Diabetes Complications physician-determined angina) over 25 years of follow-up was examined by metric scores.

RESULTS

Among 435 participants, BMI, blood pressure, total cholesterol and smoking demonstrated the highest prevalence within the ideal range, while diet and HbA_1c demonstrated the lowest. During 25 years of follow-up, 177 participants developed CHD. In Cox models, each additional metric within the ideal range was associated with a 19% lower risk (p = 0.01), and each unit increase in total metric score was associated with a 17% lower risk (p < 0.01) of CHD, adjusting for diabetes duration, estimated glomerular filtration rate, albumin excretion rate, triacylglycerols, depression and white blood cell count.

CONCLUSIONS/INTERPRETATION

Among individuals with type 1 diabetes, higher cardiovascular health metric scores were associated with lower risk of incident CHD. The American Heart Association-defined cardiovascular health metrics provide straightforward goals for health promotion that may reduce CHD risk in the type 1 diabetes population. Graphical abstract.

CircRNA ACAP2 induces myocardial apoptosis after myocardial infarction by sponging miR-29

BACKGROUND

To investigate the effect of circular RNA circ ACAP2 on apoptotic phenotype of rat cardiomyocytes and its molecular mechanism.

METHODS

Left anterior descending ligation was used to establish a rat myocardial infarction (MI) model, and real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of circ ACAP2 in apoptotic rat cardiomyocytes. The stability of circ ACAP2 was tested by actinomycin D and RNase R. H9C2 cells were infected by recombinant circ ACAP2 adenovirus (rAd-circ ACAP2), and the expression of apoptotic related genes Bax and BCL-2 in H9C2 was detected. Double luciferase reporter gene experiment, RNA antisense purification experiment and RNA Pull-Down experiments verified the binding effect of circ ACAP2 and miR-29.

RESULTS

RT-qPCR results showed that the expression of circ ACAP2 was increased in cardiomyocytes of MI rats. Actinomycin D and RNase R experiment confirmed that circ ACAP2 had better stability and resistance to RNase R degradation than its host gene ACAP2 mRNA. Overexpression of circ ACAP2 promotes apoptosis. The double luciferase reporter gene assay, RNA antisense purification assay and RNA Pulldown assay consistently confirmed the specific binding effect between circ ACAP2 and miR-29, and circ ACAP2 promoted the apoptotic phenotype in rats.

CONCLUSIONS

The expression of circ ACAP2 increased in cardiomyocytes after MI and promoted apoptosis by binding to miR-29.

The circular RNA ZNF292 alleviates OGD-induced injury in H9c2 cells via targeting BNIP3

The research aims to explore the roles and regulatory mechanisms of the circular RNA (circRNA) ZNF292 (circZNF292) in OGD-induced damage in H9c2 cells. The H9c2 cells were treated by OGD and/or transfected with circZNF292, si-circZNF292, pc-Bcl-2/adenovirus E1B-19 kDa-interacting protein 3 (BNIP3) or corresponding controls. Cell viability was detected with the CCK-8. The protein expression levels of the Bax, caspase-3, Beclin-1, p62, LC3, BNIP3, Wnt3a, β-catenin and mammalian target of rapamycin (mTOR) were individually determined via western blot. qRT-PCR was used to examine the circZNF292 expression level. The apoptotic rate was determined by the Annexin V-FITC/PI with flow cytometer. The production of the circZNF292 was promoted by OGD. Abundant circZNF292 released OGD-induced damage by up-regulating cell viability and Wnt3a/β-catenin or mTOR proteins, but down-regulating apoptosis and autophagy. circZNF292 had an opposite effect on these elements mentioned above. Besides, BNIP3 was negatively adjusted by the circZNF292. The BNIP3 overproduction destroyed the protective effect of circZNF292 on H9c2. circZNF292 released OGD-induced damage in the H9c2 cells by targeting the BNIP3 through Wnt/β-catenin and mTOR activation.

How to use replicate weights in health survey analysis using the National Nutrition and Physical Activity Survey as an example

OBJECTIVE

To conduct nutrition-related analyses on large-scale health surveys, two aspects of the survey must be incorporated into the analysis: the sampling weights and the sample design; a practice which is not always observed. The present paper compares three analyses: (1) unweighted; (2) weighted but not accounting for the complex sample design; and (3) weighted and accounting for the complex design using replicate weights.

DESIGN

Descriptive statistics are computed and a logistic regression investigation of being overweight/obese is conducted using Stata.

SETTING

Cross-sectional health survey with complex sample design where replicate weights are supplied rather than the variables containing sample design information.

PARTICIPANTS

Responding adults from the National Nutrition and Physical Activity Survey (NNPAS) part of the Australian Health Survey (2011-2013).

RESULTS

Unweighted analysis produces biased estimates and incorrect estimates of se. Adjusting for the sampling weights gives unbiased estimates but incorrect se estimates. Incorporating both the sampling weights and the sample design results in unbiased estimates and the correct se estimates. This can affect interpretation; for example, the incorrect estimate of the OR for being a current smoker in the unweighted analysis was 1·20 (95 % CI 1·06, 1·37), t= 2·89, P = 0·004, suggesting a statistically significant relationship with being overweight/obese. When the sampling weights and complex sample design are correctly incorporated, the results are no longer statistically significant: OR = 1·06 (95 % CI 0·89, 1·27), t = 0·71, P = 0·480.

CONCLUSIONS

Correct incorporation of the sampling weights and sample design is crucial for valid inference from survey data.

Could Cardiovascular Health Metrics Account for Age and Sex Disparities in Self-Reported Ischemic Heart Disease Prevalence?

The American Heart Association has outlined seven modifiable cardiovascular health (CVH) metrics. However, the sex and age disparities in the association between those CVH metrics and ischemic heart disease (IHD) prevalence are unclear. Our study sought to examine the possible sex and age variations in the association between CVH metrics and IHD prevalence using an Australian nationally representative survey. We used the core sample of the 2011⁻2012 Australian Health Survey, and 7499 adults with fasting plasma glucose (FPG) and total cholesterol values were included. We used Poisson regression analysis to measure the associations between individual metrics and IHD prevalence. Our study used both stratification and interaction analyses to compare the magnitude of associations between sex and age groups. Then, we calculated the population attributable fractions to measure the contribution of each metric to IHD prevalence. In addition, we applied logistic regression analysis to examine the influences of ideal CVH metrics number on IHD prevalence and used stratification and interaction analyses. Body mass index, physical activity, blood pressure, and FPG have greater effects on IHD prevalence in young adults compared to older adults. We failed to detect the sex variations in CVH metrics and IHD prevalence. The ideal CVH metrics number was inversely correlated to IHD prevalence and it has similar effects in four subgroups. These CVH metrics do not explain the sex and age disparities in IHD prevalence and the topic need further explorations.