Estimating the effects of body mass index and central obesity on stroke in diabetics and non-diabetics using targeted maximum likelihood estimation: Atherosclerosis Risk in Communities study

Comparison of outcomes between off-pump and on-pump coronary artery bypass graft surgery using collaborative targeted maximum likelihood estimation

There are some discrepancies about the superiority of the off-pump coronary artery bypass grafting (CABG) surgery over the conventional cardiopulmonary bypass (on-pump). The aim of this study was estimating risk ratio of mortality in the off-pump coronary bypass compared with the on-pump using a causal model known as collaborative targeted maximum likelihood estimation (C-TMLE). The data of the Tehran Heart Cohort study from 2007 to 2020 was used. A collaborative targeted maximum likelihood estimation and targeted maximum likelihood estimation, and propensity score (PS) adjustment methods were used to estimate causal risk ratio adjusting for the minimum sufficient set of confounders, and the results were compared. Among 24,883 participants (73.6% male), 5566 patients died during an average of 8.2 years of follow-up. The risk ratio estimates (95% confidence intervals) by unadjusted log-binomial regression model, PS adjustment, TMLE, and C-TMLE methods were 0.86 (0.78-0.95), 0.88 (0.80-0.97), 0.88 (0.80-0.97), and 0.87(0.85-0.89), respectively. This study provides evidence for a protective effect of off-pump surgery on mortality risk for up to 8 years in diabetic and non-diabetic patients.

Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review

PURPOSE

The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments.

METHODS

We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results.

RESULTS

Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE.

CONCLUSIONS

There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.

Comparative Evaluation of Waist-to-Height Ratio and BMI in Predicting Adverse Cardiovascular Outcome in People With Diabetes: A Systematic Review

Central obesity is strongly associated with cardiovascular risk in people with diabetes. BMI does not reflect a regional fat distribution. The other anthropometric indices, which are markers of central obesity, like waist circumference and waist-hip ratio, are subject to age, sex, and ethnic variations. An index like waist-to-height ratio (WHtR), which considers central obesity, outperforms BMI in predicting cardiometabolic risk. With a single cut-off of 0.5, irrespective of age, sex, and ethnic variations, WHtR has a wide application in screening obesity in population settings. Previous systematic analyses were conducted in the general population, assessing cardiometabolic risk. The current study is the first systematic analysis to compare the applicability of WHtR and BMI in predicting both cardiovascular risk and adverse cardiovascular outcomes in people with diabetes. It includes prospective cohort studies, cross-sectional studies, and randomized control trials to generate evidence. The summary scores indicate that WHtR is probably a better indicator than BMI to assess cardiovascular risk in people with diabetes. A future meta-analysis will pave the way for more robust evidence.

Association of Body Shape Index with Cerebral Small Vessel Disease

INTRODUCTION

A body shape index (ABSI) is an anthropometric index designed to reflect the influence of visceral fat. ABSI has been previously associated with various atherosclerosis, metabolic diseases, and cardiovascular diseases; however, relatively few studies have been conducted on cerebrovascular disease. In this study, we evaluated the association between ABSI and cerebral small vessel disease (cSVD) in health check-up participants.

METHODS

We evaluated consecutive health check-up participants between January 2006 and December 2013. As subtypes of cSVD, we quantitatively measured the volume of white matter hyperintensity (WMH) and qualitatively measured the presence of silent brain infarct (SBI) and cerebral microbleed (CMB). ABSI was calculated according to the following formula: ABSI (m11/6/kg-2/3) = waist circumference (m)/(body mass index [kg/m2]2/3 × height [m]1/2).

RESULTS

A total of 3,219 health check-up participants were assessed (median age, 56 years; male sex, 54.0%). In the multivariable analysis, ABSI was significantly associated with WMH volume (β = 0.107, 95% confidence interval [CI] = 0.013-0.200), SBI (adjusted odds ratio [aOR] = 1.62, 95% CI = 1.14-2.31), and CMB (aOR = 1.64, 95% CI = 1.16-2.33) after adjusting for confounders (per 100 m11/6/kg-2/3). Furthermore, ABSI showed a dose-response relationship with the burden of each cSVD pathology.

CONCLUSIONS

High ABSI was associated with a higher burden of cSVD in health check-up participants. As ABSI showed close associations with all subtypes of cSVD, visceral fat may be a common risk factor penetrating cSVD pathologies.

Body Shape Index and Cardiovascular Risk in Individuals With Obesity

Introduction: Cardio-metabolic risks are tested to show various anthropometric measurements. This study aimed to evaluate a body shape index (ABSI) of individuals with obesity to determine the role of these measurements in cardiovascular risk prediction.

Methods: This cross-sectional study included 368 patients who were evaluated by the researcher in the polyclinic. Sociodemographic information was obtained, and anthropometric measurements were made. Body mass index (BMI), waist circumference, and ABSI were evaluated in all patients. The patient’s risk of developing cardiovascular disease was calculated from the pooled cohort equations risk calculator (PRCAE), Framingham risk score, and systematic coronary risk evaluation (SCORE) risk calculation systems.

Results: Of the 368 patients in the study, 302 (82.1%) were females, and 66 (17.9%) were males. The average age of participants was 46.2 ± 12.0 years. The median BMI of participants was 37.5 (34.0-42.4) kg/m². The median ABSI of participants was 0.0816 (0.0775-0.0849). A positive correlation was found between ABSI and Framingham risk score and PRCAE risk score (r = 0.297, p = 0.000 and r = 0.305, p = 0.000, respectively). A significant relationship was found between ABSI and Framingham, PRCAE, and SCORE risk groups (p = 0.000, p = 0.000, and p = 0.000, respectively).

Conclusions: Our study results revealed a significant association of ABSI with Framingham, PRCAE, and SCORE risk calculation systems, which helps predict cardiovascular risk.

Association of central obesity and high body mass index with function and cognition in older adults

OBJECTIVE

To investigate the association of normal BMI with central obesity (CO), high BMI with CO, high BMI without CO, and normal BMI without CO, with function and cognition in older adults.

METHODS

Cross-sectional study involving 754 participants ≥ 65 years. Data collected include demographics, cognition, and physical measurements.

RESULTS

Females had a higher prevalence of high BMI with CO and a lower prevalence of high BMI without CO than males (61.0% vs 44.6% and 4.6% vs 15.0%, respectively). Within gender, CO groups, regardless of BMI, had lower mini-mental state examination (MMSE), handgrip strength (HGS), and longer timed-up-and-go (TUG) scores. Overall, the high BMI without CO group had the highest MMSE scores, HGS, and shortest TUG. Amongst males, HGS was significantly lower in the normal BMI with CO group (B -3.28, 95% CI -6.32 to -0.23, P = 0.04). CO, regardless of normal/high BMI, had significantly longer TUG time (B 2.65, 95% CI 0.45 to 4.84, P = 0.02; B 1.07, 95% CI 0.25 to 1.88, P = 0.01, respectively) than normal BMI without CO group. CO was associated with lower MMSE scores in both genders but significant only in males with normal BMI and CO (B -1.60, 95% CI -3.15 to -0.06, P = 0.04).

CONCLUSION

CO may be a better predictor of obesity and adverse outcomes in older adults. High BMI without CO was associated with better outcomes especially in males but require further validation. Prospective longitudinal studies are needed to ascertain the impact of BMI and/or CO on function, cognition, mortality, and gender differences.