Four-year stability of anthropometric and cardio-metabolic parameters in a prospective cohort of older adults

Association between triglyceride glucose-body mass index and long-term adverse outcomes of heart failure patients with coronary heart disease

BACKGROUND

The triglyceride glucose-body mass index (TyG-BMI) is recognized as a reliable surrogate for evaluating insulin resistance and an effective predictor of cardiovascular disease. However, the link between TyG-BMI index and adverse outcomes in heart failure (HF) patients remains unclear. This study examines the correlation of the TyG-BMI index with long-term adverse outcomes in HF patients with coronary heart disease (CHD).

METHODS

This single-center, prospective cohort study included 823 HF patients with CHD. The TyG-BMI index was calculated as follows: ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI. To explore the association between the TyG-BMI index and the occurrences of all-cause mortality and HF rehospitalization, we utilized multivariate Cox regression models and restricted cubic splines with threshold analysis.

RESULTS

Over a follow-up period of 9.4 years, 425 patients died, and 484 were rehospitalized due to HF. Threshold analysis revealed a significant reverse "J"-shaped relationship between the TyG-BMI index and all-cause mortality, indicating a decreased risk of all-cause mortality with higher TyG-BMI index values below 240.0 (adjusted model: HR 0.90, 95% CI 0.86-0.93; Log-likelihood ratio p = 0.003). A distinct "U"-shaped nonlinear relationship was observed with HF rehospitalization, with the inflection point at 228.56 (adjusted model: below: HR 0.95, 95% CI 0.91-0.98; above: HR 1.08, 95% CI 1.03-1.13; Log-likelihood ratio p < 0.001).

CONCLUSIONS

This study reveals a nonlinear association between the TyG-BMI index and both all-cause mortality and HF rehospitalization in HF patients with CHD, positioning the TyG-BMI index as a significant prognostic marker in this population.

Association of cardiometabolic factors and insulin resistance surrogates with mortality in participants from the Korean Genome and Epidemiology Study

BACKGROUND

Simple biochemical and anthropometric measurements such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), waist circumference (WC), and body mass index (BMI) are used to formulate insulin resistance (IR) indices. Whether these indices provide new predictive information for mortality remains unknown. This study examined the relationships of biochemical, anthropometric, and IR indices with mortality risk, as well as their predictive performance.

METHODS

The data source was the Korean Genome and Epidemiology Study (2004-2020) involving 114,957 participants whose data were linked to death records. The IR indices- triglyceride-glucose index (TyG), TyG-BMI, TyG-WC, visceral adiposity index (VAI), lipid accumulation product (LAP), and metabolic score for insulin resistance (METS-IR) were computed using standard formulae. The associations were examined using restricted cubic splines. The predictive performance was compared using the log-likelihood ratio chi-square test.

RESULTS

Body mass index was U-shaped, HDL-C was reverse J-shaped, and FBG and TG levels were J-shaped associated with all-cause mortality. Results showed U-shaped (TyG), J-shaped (TyG-BMI, VAI, LAP, and METS-IR), and reverse J-shaped (TyG-WC) associations with all-cause mortality. The percentages of new predictive information for all-cause mortality explained by the FBG level, BMI, TyG-BMI, and METIR were 3.34%, 2.33%, 1.47%, and 1.37%, respectively. Other IR indices and biochemical and anthropometric measurements provided < 1.0% of new predictive information. For cardiovascular disease mortality, the FBG, BMI, METIR, TyG-BMI, and HDL-C levels explained 2.57%, 2.12%, 1.59%, 1.30%, and 1.27% of new predictive information respectively. Moreover, the risks of cancer mortality explained by FBG level, VAI, and HDL-C level were 2.05%, 1.49%, and 1.28%, respectively.

CONCLUSIONS

Fasting blood glucose level is a superior predictor of mortality risk and may be used as a simple predictive and preventative factor.

A systematic review and meta-analysis of the stability of peripheral immune markers in healthy adults

Peripheral immune markers are widely used to predict risk for inflammatory disease. However, whether single assessments of inflammatory biomarkers represent stable individual differences remains unclear. We reviewed 50 studies (N = 48,674; 57 % male; mean age 54 (range 13-79) years) that assessed markers of inflammation on >1 occasion, with time between measures ranging from 24 h to 7+ years. Separate random effects meta-analyses were conducted for each inflammatory marker and time interval. Markers that had broad coverage across most time intervals included C-reactive protein (CRP; k = 37), interleukin (IL)-6 (k = 22), TNF-α (k = 10), and fibrinogen (Fg; k = 9). For CRP, IL-6, and TNF-α, stability estimates generally decreased with time, with strong to moderate stability over intervals <6 months (r's = 0.80-0.61), modest to moderate stability over 6 months - 3 years (r's = 0.60-0.51), and low stability for >3 years (r's = 0.39-0.30). Estimates were less reliable for Fg for time intervals ≤ 3 years although they generally followed the same pattern; more reliable findings suggested greater stability for Fg than other markers for intervals >3 years (r = 0.53). These findings suggest that single measures of inflammatory biomarkers may be an adequate index of stable individual differences in the short term (<6 months), with repeated measures of inflammatory biomarkers recommended over intervals ≥ 6 months to 3 years, and absolutely necessary over intervals >3 years to reliably identify stable individual differences in health risk. These findings are consistent with stability estimates and clinical recommendations for repeated measurement of other cardiovascular measures of risk (e.g., blood lipids, blood pressure).

Impact of COVID-19 Pandemic on Weight and BMI among UK Adults: A Longitudinal Analysis of Data from the HEBECO Study

COVID-19-related restrictions impacted weight and weight-related factors during the initial months of the pandemic. However, longitudinal analyses are scarce. An online, longitudinal study was conducted among self-selected UK adults (n = 1818), involving three surveys (May-June, August-September, November-December 2020), covering anthropometric, sociodemographic, COVID-19-related and behavioural measures. Data were analysed using generalised estimating equations. Self-reported average weight/body mass index (BMI) significantly increased between the May-June period and the August-September period (74.95 to 75.33 kg/26.22 kg/m2 to 26.36kg/m2, p < 0.001, respectively), and then significantly decreased to November-December (to 75.06 kg/26.27 kg/m2, p < 0.01), comparable to May-June levels (p = 0.274/0.204). However, there was great interindividual variation, 37.0%/26.7% increased (average 3.64 kg (95% confidence interval: 3.32, 3.97)/1.64 kg/m2 (1.49, 1.79)), and 34.5%/26.3% decreased (average 3.59 kg (3.34, 3.85)/1.53 kg/m2 (1.42, 1.63)) weight/BMI between May-June and November-December. Weight/BMI increase was significantly negatively associated with initial BMI, and positively associated with monthly high fat, salt and sugar (HFSS) snacks intake and alcohol consumption, and for BMI only, older age. Associations were time-varying; lower initial BMI, higher HFSS snacks intake and high-risk alcohol consumption were associated with maintaining weight/BMI increases between August-September and November-December. The average weight/BMI of UK adults fluctuated between May-June and November-December 2020. However, the substantial interindividual variation in weight/BMI trajectories indicates long-term health impacts from the pandemic, associated with food and alcohol consumption.

Stability of peripheral blood immune markers in patients with asthma

Background

Asthma is a complex disease with variable course. Efforts to identify biomarkers to predict asthma severity, the course of disease and response to treatment have not been very successful so far. We have previous suggested that PAR-2 and CRTh2 expression on specific peripheral blood cell subtypes may be biomarkers of asthma severity. We reasoned that parameters that remain stable when asthma symptoms are controlled would be the most appropriate to evaluate for their utility to predict loss of asthma control and/or severity of the disease.

Methods

Nineteen stable asthmatics were recruited from the University of Alberta Asthma clinic and followed in clinic every 3 months for a total of 4 visits. Patients had spirometry and completed the ACQ questionnaire in every visit. Blood was drawn in every visit and analyzed for a number of immune parameters by flow cytometry. These parameters included PAR-2 and CRTh2 expression on monocyte subgroups and T lymphocytes respectively, as well as numbers of eosinophils, innate lymphoid type-2 cells (ILC2) and dendritic cells. Within person stability of immune and physiological parameters was calculated using the intraclass correlation (ICC) using R version 3.4.0.

Results

FEV₁ (% predicted), FEV₁/FVC ratio, ACQ5 and ACQ7 did not differ significantly over the 4 visits, as would be expected for patients with stable asthma. Peripheral blood eosinophil numbers by Kimura stain and by flow cytometry showed ICC scores of 0.44 and 0.52 respectively, indicating moderate stability. The % of ILC2 cells in peripheral blood also showed moderate stability [ICC score of 0.45 (0.14–0.67)]. The stability for all other immune parameters was poor.

Conclusion

Among the peripheral blood immune parameters we studied, only numbers of eosinophils and ILC2 in peripheral blood were moderately stable over a year in stable asthmatics. Further studies are required to understand the reasons for the variability of the other cell types.

Effect of blood pressure and total cholesterol measurement on risk prediction using the Systematic COronary Risk Evaluation (SCORE)

BACKGROUND

To compare the reproducibility in total cholesterol (TC), systolic blood pressure (BP), and the resulting Systematic COronary Risk Evaluation (SCORE) obtained by an in-office cardio-preventive screening program (SP) and a subsequent program performed in a clinical trial examination center (EP).

METHODS

A total of 307 individuals (60.3% female, mean age = 52.8 years) participated. According to TC and BP measurements at the SP and EP, three variables were created: the SCORE^SP = single BP reading at the SP, the SCORE^EP/BP-first = first BP reading at the EP, and the SCORE^EP/BP-mean = mean second/third BP reading at the EP. Differences in TC and BP were analyzed. Associations between age, sex and mean differences between the SCORE^SP and the SCORE^EP/BP-first (M1) and the SCORE^EP/BP-mean (M2) were analyzed using multivariable linear and quantile regression.

RESULTS

TC and BP values from the SP were significantly higher than those from the EP. Among individuals with a decreased SCORE value at the EP (compared to the SP), younger age was associated with a higher improvement in risk estimation compared with older age. Female sex was associated with higher risk improvement in the SCORE between the SP and the EP compared with male sex. Associations between both demographics and M1 (M2) achieved statistical significance at the 75.0th (50th) percentile.

CONCLUSIONS

The reproducibility of results in cardiovascular risk prediction seems to be influenced by the accuracy of BP measurement. It seems that younger individuals and females are more likely to benefit from accuracy compared with older individuals and males.

Reproducibility of Accelerometer-Assessed Physical Activity and Sedentary Time

INTRODUCTION

Accelerometers are used increasingly in large epidemiologic studies, but, given logistic and cost constraints, most studies are restricted to a single, 7-day accelerometer monitoring period. It is unknown how well a 7-day accelerometer monitoring period estimates longer-term patterns of behavior, which is critical for interpreting, and potentially improving, disease risk estimates in etiologic studies.

METHODS

A subset of participants from the Women's Health Study (N=209; mean age, 70.6 [SD=5.7] years) completed at least two 7-day accelerometer administrations (ActiGraph GT3X+) within a period of 2-3 years. Monitor output was translated into total counts, steps, and time spent in sedentary, light-intensity, and moderate to vigorous-intensity activity (MVPA) and bouted-MVPA (i.e., 10-minute bouts). For each metric, intraclass correlations (ICCs) and 95% CIs were calculated using linear-mixed models and adjusted for wear time, age, BMI, and season. The data were collected in 2011-2015 and analyzed in 2015-2016.

RESULTS

The ICCs ranged from 0.67 (95% CI=0.60, 0.73) for bouted-MVPA to 0.82 (95% CI=0.77, 0.85) for total daily counts and were similar across age, BMI, and for less and more active women. For all metrics, classification accuracy within 1 quartile was >90%.

CONCLUSIONS

These data provide reassurance that a 7-day accelerometer-assessment protocol provides a reproducible (and practical) measure of physical activity and sedentary time. However, ICCs varied by metric; therefore, future prospective studies of chronic diseases might benefit from existing methods to adjust risk estimates for within-person variability in activity to get a better estimate of the true strength of association.

Association between perceived weight discrimination and physical activity: a population-based study among English middle-aged and older adults

OBJECTIVE

To examine the association between perceived weight discrimination and physical activity in a large population-based sample.

DESIGN

Data were from 2423 men and 3057 women aged ≥50 years participating in Wave 5 (2010/11) of the English Longitudinal Study of Ageing. Participants reported experiences of weight discrimination in everyday life and frequency of light, moderate and vigorous physical activities. We used logistic regression to test associations between perceived weight discrimination and physical activity, controlling for age, sex, socioeconomic status and body mass index (BMI).

RESULTS

Perceived weight discrimination was associated with almost 60% higher odds of being inactive (OR 1.59, 95% CI 1.05 to 2.40, p=.028) and 30% lower odds of engaging in moderate or vigorous activity at least once a week (OR 0.70, 95% CI 0.53 to 0.94, p=.017).

CONCLUSIONS

Independent of BMI, individuals who perceive unfair treatment on the basis of their weight are less physically active than those who do not perceive discrimination. This has important implications for the health and well-being of individuals who experience weight-based discrimination, and may also contribute to a cycle of weight gain and further mistreatment.

Perceived weight discrimination and chronic biochemical stress: A population-based study using cortisol in scalp hair

OBJECTIVE

There is increasing evidence for weight-based discrimination against persons with obesity. This study aimed to examine the physiological impact of perceived weight discrimination on cortisol in hair, an indicator of chronic stress exposure.

METHODS

Data were from 563 nonsmoking individuals with obesity (body mass index, BMI ≥30 kg/m² ) participating in the English Longitudinal Study of Ageing. Experiences of discrimination were reported via questionnaire, and hair cortisol concentrations were determined from the scalp-nearest 2-cm hair segment. Height and weight were objectively measured. ANCOVAs tested associations between perceived weight discrimination and hair cortisol concentration overall and by degree of obesity. All analyses were adjusted for age, sex, ethnicity, socioeconomic status, and BMI.

RESULTS

Mean hair cortisol concentrations were 33% higher in those who had experienced weight discrimination than those who had not (mean log pg/mg 1.241 vs. 0.933, F = 12.01, P = 0.001). The association between weight discrimination and hair cortisol was particularly pronounced in individuals with severe (class II/III) obesity (1.402 vs. 0.972, F = 11.58, P = 0.001).

CONCLUSIONS

Weight discrimination is associated with the experience of stress at a biological level. Chronic exposure to elevated levels of cortisol may play a role in generating a vicious circle of weight gain and discrimination and contribute to obesity-associated health conditions.