Many continuous variables should be analyzed using the relative scale: a case study of β2-agonists for preventing exercise-induced bronchoconstriction

Association Between Neighborhood Factors and Adult Obesity in Shelby County, Tennessee: Geospatial Machine Learning Approach

Background

Obesity is a global epidemic causing at least 2.8 million deaths per year. This complex disease is associated with significant socioeconomic burden, reduced work productivity, unemployment, and other social determinants of health (SDOH) disparities.

Objective

The objective of this study was to investigate the effects of SDOH on obesity prevalence among adults in Shelby County, Tennessee, the United States, using a geospatial machine learning approach.

Methods

Obesity prevalence was obtained from the publicly available 500 Cities database of Centers for Disease Control and Prevention, and SDOH indicators were extracted from the US census and the US Department of Agriculture. We examined the geographic distributions of obesity prevalence patterns, using Getis-Ord Gi* statistics and calibrated multiple models to study the association between SDOH and adult obesity. Unsupervised machine learning was used to conduct grouping analysis to investigate the distribution of obesity prevalence and associated SDOH indicators.

Results

Results depicted a high percentage of neighborhoods experiencing high adult obesity prevalence within Shelby County. In the census tract, the median household income, as well as the percentage of individuals who were Black, home renters, living below the poverty level, 55 years or older, unmarried, and uninsured, had a significant association with adult obesity prevalence. The grouping analysis revealed disparities in obesity prevalence among disadvantaged neighborhoods.

Conclusions

More research is needed to examine links between geographical location, SDOH, and chronic diseases. The findings of this study, which depict a significantly higher prevalence of obesity within disadvantaged neighborhoods, and other geospatial information can be leveraged to offer valuable insights, informing health decision-making and interventions that mitigate risk factors of increasing obesity prevalence.

Prognostic value of blood pressure in ambulatory heart failure: a meta-analysis and systematic review. Ambulatory blood pressure predicts heart failure prognosis

Previous primary studies have explored the association between blood pressure (BP) and mortality in ambulatory heart failure (HF) patients reporting varying and contrasting associations. The aim is to determine the pooled BP prognostic value and explore potential reasons for between-study inconsistency. We searched Medline, Cochrane, EMBASE and CINAHL from January 2005 to October 2018 for studies with ≥ 50 events (mortality and/or hospitalization) and included BP in a multivariable model in ambulatory HF patients. We pooled hazard ratios (random effects model) for systolic BP (SBP) or diastolic BP (DBP) effect on mortality and/or hospitalization risk. We used a priori defined sub-group analyses to explore heterogeneity and GRADE approach to assess the certainty of the evidence. Seventy-one eligible articles (239,467 screened) at low to moderate risk of bias included 235,752 participants. Higher SBP was associated with reduced all-cause mortality (HR 0.93, 95%CI 0.91-0.95, I2 = 87.13%, moderate certainty), all-cause hospitalization events (HR 0.91, 95%CI 0.88-0.93, I2 = 44.4%, high certainty) and their composite endpoint (HR 0.93 per 10 mmHg, 95%CI 0.91-0.94, I2 = 86.3%, high certainty). DBP did not demonstrate a statistically significant effect for all outcomes. The association strength was significantly weaker in studies following patients with either LVEF > 40%, higher average SBP (> 130 mmHg), increasing age and diabetes. All other a priori subgroup hypotheses did not explain between study differences. Higher ambulatory SBP is associated with reduced risk of all-cause mortality and hospitalization. Patients with lower BP and reduced LVEF are in a high-risk group of developing adverse events with moderate certainty of evidence.

Vitamin C May Improve Left Ventricular Ejection Fraction: A Meta-Analysis

Background

Vitamin C deprivation can lead to fatigue, dyspnea, oedema and chest pain, which are also symptoms of heart failure (HF). In animal studies vitamin C has improved contractility and mechanical efficiency of the heart. Compared with healthy people, patients with HF have lower vitamin C levels, which are not explained by differences in dietary intake levels, and more severe HF seems to be associated with lower plasma vitamin C levels. This meta-analysis looks at the effect of vitamin C on left ventricular ejection fraction (LVEF).

Methods

We searched for trials reporting the effects of vitamin C on LVEF. We assessed the quality of the trials, and pooled selected trials using the inverse variance, fixed effect options. We used meta-regression to examine the association between the effect of vitamin C on LVEF level and the baseline LVEF level.

Results

We identified 15 trials, three of which were excluded from our meta-analysis. In six cardiac trials with 246 patients, vitamin C increased LVEF on average by 12.0% (95% CI 8.1–15.9%; P < 0.001). In six non-cardiac trials including 177 participants, vitamin C increased LVEF on average by 5.3% (95% CI 2.0–8.5%; P = 0.001). In meta-regression analysis we found that the effect of vitamin C was larger in trials with the lowest baseline LVEF levels with P = 0.001 for the test of slope. The meta-regression line crossed the null effect level at a baseline LVEF level close to 70%, with progressively greater benefit from vitamin C with lower LVEF levels. Some of the included trials had methodological limitations. In a sensitivity analysis including only the four most methodologically sound cardiac trials, the effect of vitamin C was not substantially changed.

Conclusions

In this meta-analysis, vitamin C increased LVEF in both cardiac and non-cardiac patients, with a strong negative association between the size of the vitamin C effect and the baseline LVEF. Further research on vitamin C and HF should be carried out, particularly in patients who have low LVEF together with low vitamin C intake or low plasma levels. Different dosages and different routes of administration should be compared.

Usefulness of resveratrol supplementation in decreasing cardiometabolic risk factors comparing subjects with metabolic syndrome and healthy subjects with or without obesity: meta-analysis using multinational, randomised, controlled trials

Introduction

Resveratrol (RES), a natural polyphenolic compound, has been linked to some beneficial effects against cardiovascular disease (CVD).

Material and methods

We conducted a systematic search to conduct a meta-analysis on cardiometabolic risk factors modulated by RES targeting patients with metabolic syndrome (Met-S) and Obese/Healthy (O/H) subjects. The PICO (Patient, Intervention, Comparison, Outcome) research question was: Does RES among patients with Met-S and O/H subjects reduce the cardiometabolic risk? The first group was affected with MetS, which is defined as a clustering of abdominal obesity, dyslipidaemia, hyperglycaemia, and hypertension in a single individual. The second group was composed of 'obese/healthy' individuals, i.e. healthy subjects with or without obesity. We performed a literature search of MEDLINE/ PubMed, Scopus, and Google Scholar for randomised, controlled trials (RCT) that estimated the effects of RES on cardiometabolic risk factors.

Results

We found 780 articles, of which 63 original articles and reviews were identified. Data from 17 well-conducted RCT studies, comprising 651 subjects, were extracted for analysis. Overall, RES had a significant influence on Homeostatic Model Assessment-Insulin Resistance (HOMA-IR), resulting in a mean difference of -0.520665 (95% CI: -1.12791; -0.01439; p = 0.00113). In Met-S, RES significantly reduced glucose, low-density lipoprotein-cholesterol (LDL-C), and total cholesterol (T-Chol) as detected by the mean difference of -1.069 (95% CI: -2.107, -0.032; p = 0.043), -0.924 (95% CI: -1.804, -0.043; p = 0.040), and -1.246 (95% CI: -2.314, -0.178; p = 0.022), respectively.

Conclusions

Despite some heterogeneity in the populations, RES supplementation seems to improve cardiometabolic health, decreasing some risk factors (HOMA-IR, LDL-C, and T-Chol) associated with CVD.