Featured Cover Kačar, Mark; Rijavec, Matija; Šelb, Julij ...
Clinical and experimental allergy,
April 2023, 2023-04-00, 20230401, Volume:
53, Issue:
4
Journal Article
Peer reviewed
Open access
The cover image is based on the Review Article Clonal mast cell disorders and hereditary α‐tryptasemia as risk factors for anaphylaxis by Mark Kačar et al., https://doi.org/10.1111/cea.14264.
Life's Simple 7 (LS7) is an easily calculated and interpreted metric of cardiovascular health based on 7 domains: smoking, diet, physical activity, body mass index, blood pressure, cholesterol, and ...fasting glucose. The Life's Essential 8 (LE8) metric was subsequently introduced, adding sleep metrics and revisions of the previous 7 domains. Although calculating LE8 requires additional information, we hypothesized that it would be a more reliable index of cardiovascular health.
Both the LS7 and LE8 metrics yield scores with higher values indicating lower risk. These were calculated among 11 609 Black and White participants free of baseline cardiovascular disease (CVD) in the Reasons for Geographic and Racial Differences in Stroke study, enrolled in 2003 to 2007, and followed for a median of 13 years. Differences in 10-year risk of incident CVD (coronary heart disease or stroke) were calculated as a function LS7, and LE8 scores were calculated using Kaplan-Meier and proportional hazards analyses. Differences in incident CVD discrimination were quantified by difference in the c-statistic.
For both LS7 and LE8, the 10-year risk was approximately 5% for participants around the 99th percentile of scores, and a 4× higher 20% risk for participants around the first percentile. Comparing LS7 to LE8, 10-year risk was nearly identical for individuals at the same relative position in score distribution. For example, the "cluster" of 2013 participants with an LS7 score of 7 was at the 35.8th percentile in distribution of LS7 scores, and had an estimated 10-year CVD risk of 8.4% (95% CI, 7.2%-9.8%). In a similar location in the LE8 distribution, the 1457 participants with an LE8 score of 60±2.5 at the 39.4th percentile of LE8 scores had a 10-year risk of CVD of 8.5% (95% CI, 7.1%-10.1%), similar to the cluster defined by LS7. The age-race-sex adjusted c-statistic of the LS7 model was 0.691 (95% CI, 0.667-0.705), and 0.695 for LE8 (95% CI, 0.681-0.709) (
for difference, 0.12).
Both LS7 and LE8 were associated with incident CVD, with discrimination of the 2 indices practically indistinguishable. As a simpler metric, LS7 may be favored for use by the general population and clinicians.
Background: In clinical practice, anthropometric measures other than BMI are rarely measured yet may be more predictive of cardiovascular (CV) risk. We analyzed the placebo group of the REWIND CV ...outcomes trial to compare several anthropometric measures as baseline predictors for cardiovascular disease (CVD)-related outcomes in participants with type 2 diabetes. Methods: Data from the REWIND trial placebo group (N=4952) were analyzed. All participants had T2D, were aged >50, and had either a previous CV event or CV risk factors and a BMI of >23 kg/m2. Cox proportional hazard models were used to investigate if BMI, waist-to-hip ratio (WHR), and waist circumference (WC) were significant risk factors for major adverse CV events (MACE)-3, CVD-related mortality, all-cause mortality, and heart failure (HF). Models were adjusted for age and sex, and additional baseline factors selected by LASSO method. Results are presented for 1 standard deviation increase of the respective anthropometric factor. Results: There were 663 MACE-3 events, 346 CVD-related deaths, 592 all-cause deaths, and 226 events of HF during the median follow-up of 5.4 years. WHR and WC, but not BMI, were identified as independent risk factors for MACE-3 (hazard ratio HR for WHR: 1.11 95% CI 1.03 to 1.21; p=0.009; HR for WC: 1.12 95% CI 1.02 to 1.22; p=0.012). WC adjusted for hip circumference (HC) showed the strongest association with MACE-3 compared to WHR, WC, or BMI unadjusted for each other (HR: 1.25 95% CI 1.06 to 1.49; p=0.009). Results for CVD-related mortality and all-cause mortality were similar. HF was predicted by WC and BMI, but not WHR (HR for WC: 1.34 95% CI 1.16 to 1.54; p<0.001; HR for BMI: 1.33 95% CI 1.17 to 1.50; p<0.001). Conclusions: In this post hoc analysis of the REWIND placebo group, WHR and WC were predictors of MACE-3, CVD-related mortality, and all-cause mortality; BMI was not. These findings indicate the need for anthropometric measures that consider body fat distribution when assessing CV risk.
Cardiovascular diseases (CVDs) are the global public health problem which has been associated with increasing prevalence of modifiable CVDs risk factors. This study aimed to describe the prevalence ...and knowledge of modifiable CVDs risk factors among vulnerable population of Central Tanzania.
A community-based cross-sectional study design was employed. A total of 749 participants were interviewed. The socio-demographic information and modifiable CVDs risk factors (behavioral and biological) were measured using a modified World Health Organization (WHO) STEPwise approach for chronic disease risk factor surveillance. Knowledge of modifiable CVDs risk factors was measured by comprehensive heart disease knowledge questionnaire. Descriptive statistics were used to describe the knowledge and prevalence of modifiable CVDs risk factors. Logistic regression analysis was used to determine the factors associated with adequate knowledge of CVDs risk factors.
The prevalence of béhavioral risk factors were; current smokers and alcohol consumers were 4.4% and 18.0% respectively, use of raw salt was 43.7%, consumption of fruit/vegetables < 5 days per week was 56.9%. The prevalence of Biological CVDs risk factors was as follows: Overall, 63.5% (33.3% overweight and 29.9% obese) were overweight or obese, 4.5% were diabetic and 43.4% were hypertensive. Only 35.4% of participants had adequate knowledge of CVDs risk factors. Being a male (AOR = 1.44, 95%CI = 1.01-2.06, p < .05), having primary education (AOR = 6.43, 95%CI = 2.39-17.36, p < .0001), being employed (AOR = 1.59, 95%CI = 1.00-2.52, p < .05), ever checked blood pressure (AOR = 0.59, 95%CI = 0.42-0.84, p < .001), family history of hypertension (AOR = 0.38, 95%CI = 0.25-0.57, p < .0001) determined adequate knowledge of CVDs risk factors.
This study has revealed a high prevalence of modifiable CVDs risk factors and low knowledge of CVDs risk factors. Community health promotion interventions to increase population knowledge of CVDs risk factors are recommended for the efficacious reduction of CVDs in the country.
Musculoskeletal Disorders (MSDs) have a significant impact on people's lives as well as their workplaces, organizations, families, society, and national economy. Therefore, the main objective of this ...study is to investigate the impacts of different risk factors in developing MSD problems. Structural equation modelling has been used to examine the effects of different risk factors on developing MSD problems. Five hypotheses were developed for workplace, personal, biomechanical, psychosocial, and organisational risk factors to examine the positive relation with MSD problems generation. Results showed that biomechanical risk factors, including repetitive motion, vibration, force, posture, and deviation from neutral body alignment, have significant impacts on the development of MSD problems. Similar results were found for workplace, personal, psychosocial, and organisational risk factors. Therefore, either the single risk factor or collectively contributes significantly to MSD problems generation. Decision-makers can use this study to analyse the impacts of different factors on the generation of MSD problems within their industries or organizations. To the best of the author's knowledge, this study is the first and foremost approach to determine the impacts of the critical risk factors on developing MSD problems through an organised and scientific approach.
Abstract
Background
Data on risk factors for coronavirus disease 2019 (COVID-19)–associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors ...independently associated with COVID-19–associated hospitalizations.
Methods
Community-dwelling adults (aged ≥18 years) in the United States hospitalized with laboratory-confirmed COVID-19 during 1 March–23 June 2020 were identified from the COVID-19–Associated Hospitalization Surveillance Network (COVID-NET), a multistate surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity, severe obesity, chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRRs) for hospitalization.
Results
Among 5416 adults, hospitalization rates (all reported as aRR 95% confidence interval) were higher among those with ≥3 underlying conditions (vs without) (5.0 3.9–6.3), severe obesity (4.4 3.4–5.7), chronic kidney disease (4.0 3.0–5.2), diabetes (3.2 2.5–4.1), obesity (2.9 2.3–3.5), hypertension (2.8 2.3–3.4), and asthma (1.4 1.1–1.7), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65 or 45–64 years (vs 18–44 years), males (vs females), and non-Hispanic black and other race/ethnicities (vs non-Hispanic whites).
Conclusions
Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.
Severe obesity, chronic kidney disease, diabetes, obesity, hypertension, asthma, age ≥45 years, male sex, and non-Hispanic black and other race/ethnicity are associated with increased risk of coronavirus disease 2019–associated hospitalizations.
Background While there have been several school‐based physical activity (PA) interventions targeting improvement in cardiovascular disease (CVD) risk factors, few have assessed long‐term effects. The ...aim of this paper was therefore to determine intervention effects on CVD risk factors 5 years after cessation. Methods Two schools were assigned to intervention (n = 125) or control (n = 134). The intervention school offered 210 min/week more PA than the control school over two consecutive years (fourth and fifth grades). Follow‐up assessment was conducted 5‐year post‐intervention (10th grade) where 180–210 (73%–85%) children provided valid data. Outcomes were CVD risk factors: triglyceride, total‐to‐high‐density‐lipoprotein‐cholesterol ratio (TC:HDL ratio), insulin resistance, blood pressure (BP), waist circumference, and cardiorespiratory fitness (VO2peak). Variables were analyzed individually and as a composite score through linear mixed models, including random intercepts for children. Results Analyses revealed significant sustained 5‐year intervention effects for HDL (effect sizes ES = 0.22), diastolic BP (ES = 0.48), VO2peak (ES = 0.29), and composite risk score (ES = 0.38). These effects were similar to the immediate results following the intervention. In contrast, while TC:HDL ratio initially decreased post‐intervention (ES = 0.27), this decrease was not maintained at 5‐year follow‐up (ES = 0.09), whereas WC was initially unchanged post‐intervention (ES = 0.02), but decreased at 5‐year follow‐up (ES = 0.44). Conclusion The significant effects of a 2‐year school‐based PA intervention remained for CVD risk factors 5 years after cessation of the intervention. As cardiometabolic health can be maintained long‐term after school‐based PA, this paper demonstrates the sustainability and potential of schools in the primary prevention of future CVD risk in children.
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