Markers Of Health Research Articles

Longitudinal associations of meeting the WHO physical activity guidelines and physical fitness, from preschool to childhood.

There is a well-established relationship between physical activity (PA) and physical fitness in children, being the latter an important marker for present and future health; however, there is still insufficient knowledge for the transition from the preschool age to early childhood. Therefore, this study in Swedish children aimed to investigate the estimated effect of meeting the aerobic component of the PA guidelines at 4 and/or 9 years of age on physical fitness measured at 9 years of age. PA was assessed using a wrist-worn ActiGraph accelerometer and identical data processing in 217 healthy children in Sweden (114 boys and 103 girls). Physical fitness test included cardiorespiratory (20 m shuttle run test), motor (4 × 10 m shuttle run), and muscular fitness (hand grip strength and long jump). A linear mixed model was run, investigating the interaction between meeting the PA guidelines and time (either 4 or 9 years of age) and each fitness component (at 4 and 9). Interactions by sex were also checked. Meeting the PA guidelines consistently (at 4 and 9 years) was significantly associated to better performance in physical fitness parameters for motor fitness (-0.76 s, p < 0.001) and lower body muscular fitness (+4.6 cm; p < 0.001) at 9 years. There was an interaction between meeting the PA guidelines and time point, for cardiorespiratory fitness (+4.58 laps; p < 0.001). This study shows that meeting the PA guidelines at 4 and 9 years of age is associated to higher physical fitness at 9 years of age.

(1318) - Pulse Wave Velocity in Pediatric Heart Transplant Recipients- A Marker of Vascular Health

(1318) - Pulse Wave Velocity in Pediatric Heart Transplant Recipients- A Marker of Vascular Health

The impact of egg consumption on indices of gastrointestinal health: a systematic literature review

Eggs are highly digestible, nutrient-rich and are a valuable source of protein and choline, thereby promoting a range of health benefits. Several studies have found an association between protein intake and gastrointestinal microbial diversity(1), while bacterial fermentation of undigested protein in the large bowel can produce short-chain fatty acids, such as butyrate, positively influencing host metabolic health, gut integrity and immune function(2). On the other hand, dietary choline stimulates gastrointestinal bacterial production of trimethylamine and the prothrombotic compound trimethylamine-N-oxide (TMAO)(3). Despite these established links, limited studies have explored the effects of whole egg intake on indices of gastrointestinal health. This systematic literature review aimed to synthesise research that has investigated the impact of egg-supplemented diets or egg consumption on markers of gastrointestinal health including microbiome, function and symptoms. This review was conducted in accordance with PRISMA guidelines. Five databases (Ovid Medline, Embase, CINAHL Plus, SCOPUS, and PsychInfo), and reference lists of relevant papers, were searched from inception until April 2023. Studies were included if they examined the link between whole chicken egg consumption and gastrointestinal health in healthy adults (aged&gt;16). Indices of gastrointestinal health were defined as any outcomes related to gastrointestinal factors, including symptoms, microbiome, inflammation, colonic fermentation and TMAO. Reviews and case studies were excluded. All studies underwent risk of bias assessment. Overall, 548 studies were identified and 19 studies were included after screening. Eight of these were randomised controlled trials (RCTs), 8 cross-sectional and 3 prospective cohort studies. Participants ranged in number between 20-32,166 and in age between 18–84 years. Study periods varied between 3–14 weeks for RCTs and 6 months–12.5 years for prospective cohort studies. RCTs examined intakes between 1–4 eggs/day, with the majority examining 3 eggs/day (n = 6). The primary outcome across 15 articles was TMAO levels, with most reporting no significant associations (n = 13). Five studies examined inflammation with inconsistent findings ranging from no alterations (in TNF-α, IL-8, CRP), increases (in anti-inflammatory marker LTB5, TNF-α), and decreases (in IL-6, CRP). Lastly, 7 studies explored alterations in microbiome. Two RCTs and 2 cross-sectional trials reported no alterations in microbial diversity in response to eggs. Meanwhile, 2 cross-sectional and 1 prospective study linked specific bacteria to consistent egg intake. Eggs were associated with species that produce butyrate (E.rectale, F.prausnitzii, M.smithii, and R.bromii), and protect against metabolic syndrome (A.muciniphila). This systematic review found that egg consumption did not increase levels of the undesirable biomarker TMAO and were associated with butyrate-producing bacteria. Evidence regarding the effect of egg intake on inflammation was inconsistent. This review revealed the general lack of available research investigating whole eggs and gastrointestinal health. Future carefully designed RCTs are required to improve understanding of how eggs may influence the gastrointestinal microbiome and colonic fermentation.

‘You can change your life through sports’—physical activity interventions to improve the health and well-being of adults experiencing homelessness: a mixed-methods systematic review

ObjectivesSystematically synthesise evidence of physical activity interventions for people experiencing homelessness (PEH).DesignMixed-methods systematic review.Data sourcesEMBASE, Web of Science, CINAHL, PubMed (MEDLINE), PsycINFO, SPORTDiscus and Cochrane Library, searched from inception to...

Echo-intensity characterization at implant sites and novel diagnostic ultrasonographic markers for peri-implantitis.

To apply high-frequency ultrasound (HFUS) echo intensity for characterizing peri-implant tissues at healthy and diseased sites and to investigate the possible ultrasonographic markers of health versus disease. Sixty patients presenting 60 implants diagnosed as healthy (N = 30) and peri-implantitis (N = 30) were assessed with HFUS. HFUS scans were imported into a software where first-order greyscale outcomes [i.e., mean echo intensity (EI)] and second-order greyscale outcomes were assessed. Other ultrasonographic outcomes of interest involved the vertical extension of the hypoechoic supracrestal area (HSA), soft-tissue area (STA) and buccal bone dehiscence (BBD), among others. HFUS EI mean values obtained from peri-implant soft tissue at healthy and diseased sites were 122.9 ± 19.7 and 107.9 ± 24.7 grey levels (GL); p = .02, respectively. All the diseased sites showed the appearance of an HSA that was not present in healthy implants (area under the curve = 1). The proportion of HSA/STA was 37.9% ± 14.8%. Regression analysis showed that EI of the peri-implant soft tissue was significantly different between healthy and peri-implantitis sites (odds ratio 0.97 [95% confidence interval: 0.94-0.99], p = .019). HFUS EI characterization of peri-implant tissues shows a significant difference between healthy and diseased sites. HFUS EI and the presence/absence of an HSA may be valid diagnostic ultrasonographic markers to discriminate peri-implant health status.

The metabolic health of New Zealand vegans

The popularity of a vegan diet is growing worldwide. Data analysed from the 2018 NZ Attitudes and Values study showed that 1.1% of New Zealanders followed a vegan diet(1). Though there are potential nutrient deficiencies in a vegan diet, it is generally accepted that a vegan diet, with its emphasis on a variety of vegetables, fruit, grains, legumes, and pulses, has greater metabolic benefits than a Western-style diet high in red meat and processed foods and lower in plants(2). This observational cross-sectional study aimed to explore the dietary intake (4-day food diary) and metabolic health status (including anthropometry, blood pressure, lipids, body fat percentage, omega-3 index and glycaemic control) of adults who had been consuming a vegan diet for 2+ years. Participants (N = 212) were predominantly female (N = 155) with a mean (SD) age of 39.5 (12.4) years. Mean cardiometabolic markers of systolic and diastolic blood pressure, BMI, waist circumference, HbA1c, total cholesterol, LDL-cholesterol, HDL-cholesterol, Chol:HDL ratio and triglycerides were all below the thresholds for disease risk. Omega-3 index results &lt;4% placed most participants (86.3%) in the high-risk category for heart disease. Many female participants (71%) had &gt;30% body fat, compared to 5.3% of males. With reference to the AMDR (total fat 20-35%, carbohydrate 45-65% and protein 15-25%), the intake of total fat was at the upper end (males 34.4%, females 35.9%), carbohydrate was at the lower end (males 46.2%, females 44.7%), and protein was below the lower end (males 14.9%, females 14.2%). Saturated fat intakes ranged from 4.0-65.9 g/d, with a mean (SD) of 24.9 (10.5) g/d for males and 20.2 (9.9) g/d for females. The mean (SD) dietary fibre intake was much higher than the AI set by the Ministry of Health of 25g/d for females and 30g/d for males, at 55.0 (17.8) g/d for males and 43.4 (12.8) g/d for females, ranging from 10.9-133.9g/d. This is the first New Zealand study to examine the metabolic health and dietary intake of adult vegans. The results of cardiometabolic health markers indicate that the vegan diet confers cardioprotective benefits. However, the low Omega-3 index of most participants is concerning, which warrants longitudinal research to assess the level of risk conferred by a low Omega-3 index result in a population with no other cardiometabolic risk factors. The findings of the present study may help guide the growing New Zealand vegan community towards a nutritionally optimal vegan diet.

Unlocking the Benefits of Fasting: A Review of its Impact on Various Biological Systems and Human Health.

Fasting has gained significant attention in recent years for its potential health benefits in various body systems. This review aims to comprehensively examine the effects of fasting on human health, specifically focusing on its impact on different body's physiological systems. The cardiovascular system plays a vital role in maintaining overall health, and fasting has shown promising effects in improving cardiovascular health markers such as blood pressure, cholesterol levels, and triglyceride levels. Additionally, fasting has been suggested to enhance insulin sensitivity, promote weight loss, and improve metabolic health, thus offering potential benefits to individuals with diabetes and metabolic disorders. Furthermore, fasting can boost immune function, reduce inflammation, enhance autophagy, and support the body's defense against infections, cancer, and autoimmune diseases. Fasting has also demonstrated a positive effect on the brain and nervous system. It has been associated with neuroprotective properties, improving cognitive function, and reducing the risk of neurodegenerative diseases, besides the ability of increasing the lifespan. Hence, understanding the potential advantages of fasting can provide valuable insights for individuals and healthcare professionals alike in promoting health and wellbeing. The data presented here may have significant implications for the development of therapeutic approaches and interventions using fasting as a potential preventive and therapeutic strategy.

Utilizing Machine Learning to Forecast Smoking Behavior

Abstract: The examination of smoking habits, extensively studied over time, has posed challenges in accurately predicting and thoroughly analyzing its determinants. Previous research efforts struggled to precisely predict smoking behavior due to the presence of continuous target variables, which hindered the application of crucial feature selection techniques like mutual information. This study aims to tackle these hurdles through an innovative approach that integrates data preprocessing, feature engineering, and advanced machine learning methods. To address the issue of continuous target variables, our methodology involves categorizing smoking behavior into discrete groups, enabling the utilization of feature selection techniques such as mutual information scores. Logistic regression, Gaussian Naive Bayes, and Random Forest Classifier models are utilized to achieve highly accurate predictions of smoking behavior. The Select KBest method is employed to evaluate the importance of features based on mutual information scores. The investigation delves into various health markers, including BMI, haemoglobin levels, and cholesterol, offering comprehensive insights into their influence on smoking habits. Furthermore, Principal Component Analysis (PCA) is implemented to reduce dimensionality while preserving essential information from the dataset. Through this novel approach and a steadfast commitment to ethical data collection practices, our objective is to advance the comprehension of smoking behavior, surmounting past challenges, and providing valuable insights for public health initiatives and smoking cessation endeavors. The paper assesses outcomes using specified algorithms and parameters, presenting a comparative analysis to enhance the clarity and reliability of our findings.

Abstract P212: Adherence Trends to a Remotely Supervised Weight Loss and Exercise Training Intervention to Improve Rheumatoid Arthritis Cardiovascular Risk

Introduction: Individuals with rheumatoid arthritis (RA) have an increased risk for cardiometabolic disease. By improving traditional markers of cardiometabolic health, interventions that induce weight loss and increase physical activity may also reduce RA-related cardiometabolic disease risk. However, to achieve these health benefits, an individual must adhere to such interventions. To understand whether sustained behavioral modification is feasible for individuals with RA, assessing adherence to prescribed intervention components is needed. Hypothesis: We hypothesized that adherence to a daily step goal would be greater than adherence to more intensive intervention components. Methods: Older adults with RA and overweight/obesity (n = 20) were randomized and completed 16 weeks of “usual care” Counseling Health as Treatment (CHAT) or remotely Supervised Weight loss and Exercise Training (SWET). The SWET program consisted of caloric restriction (7% weight loss goal), aerobic training (AT; 150 minutes/week), and resistance training (RT; twice weekly). Both groups were given a daily goal of 6,000 steps. Pearson correlation analyses assessed for a relationship between baseline measures and average daily step count. Results: Participants were on average 66.7 ± 5.4 years old, Caucasian (65.0%), men (80.0%), with obesity (body mass index: 32.4 ± 2.9 kg/m 2 ). For SWET and CHAT, respectively, average daily step adherence was 117.8% (7065.6 ± 2117.0 steps/day) and 118.2% (7093.4 ± 2965.4 steps/day) (Figure 1A). Average adherence to SWET-only components was 84.0 ± 0.5% for AT, 83.0 ± 0.2% for RT, and 93.9 ± 0.1% for weigh-ins (Figure 1B). Step count adherence was unrelated to baseline measures. Conclusions: Step count adherence 1) was similar in both groups despite the intervention delivery strategy, and 2) exceeded other more intensive SWET intervention components (i.e., AT and RT). Findings highlight step counts as an achievable and sustainable RA exercise goal.

Abstract MP17: Sustained Improvements in Liver Fat Reduction and Cardiometabolic Health at Nine Months After a 12 Week Digital Health Program in Individuals With Non-Alcoholic Fatty Liver Disease - A Feasibility Study

Introduction: Behavioral changes can improve health outcomes, but maintaining improvements can be challenging. A 12-week digital health program for Non-Alcoholic Fatty Liver Disease (NAFLD) was previously shown to be feasible in terms of patient engagement, program retention, and improvements in clinical markers of liver and cardiometabolic health. Here, we report on retention and clinical measurements after a 6-month maintenance program. Hypothesis: We hypothesized that improvements in cardiometabolic health can be sustained six months beyond an active program’s duration. Methods: A prospective, open label, single arm, 12-week long study was first conducted, where a digital health program was delivered through the Sidekick app with emphasis on disease education, lowering dietary carbohydrates, increasing activity levels, reducing stress and lifestyle coaching. Individuals with either BMI&gt;30, metabolic syndrome or type 2 diabetes were screened for NAFLD with a FibroScan assessment. Data collection included demographics, anthropometric and clinical measurements, MRI-PDFF for liver fat content, dual-energy X-ray absorptiometry for body composition and blood tests. Measurements were done at baseline, 12 weeks and nine months. Once the 12-week program concluded, a six-month maintenance program was initiated with no new educational materials and the health coaching ceased. During the maintenance program the participants retained access to the app with recurring educational content. Summary statistics were calculated for all participants who started the health program. Missing values at follow-up were imputed using baseline observation carried forward. Results: In total, 38 individuals were included in the study and 34 (89%) completed the 12-week program, of which 28 (83%) attended the third and final follow-up visit at nine months. The median population age was 59.5 [IQR 46.3,68.8] years and 23 (60.5%) were females. At month nine the mean weight loss compared to baseline was 4.0 kg (SD=5.0) (p&lt;0.001) with 5.2% (SD=10.0) reduction in fat mass (p&lt;0.001). The average relative liver fat reduction was 18.4% (SD=30.5) (p&lt;0.001). Systolic blood pressure decreased by 8.3 mmHg on average (SD=13.4) (p&lt;0.001), diastolic blood pressure by 2.5 mmHg (SD=6.0) (p=0.015) and waist circumference by 4.7 cm (SD=7.1) (p&lt;0.001). According to a sensitivity analysis the observed changes were not explained by changes in medication. Previous changes in triglyceride levels were not maintained. In the final week, 50% (19/38) of the users were retained in the app. Conclusion: This study suggests that improvements after a 12-week digital health program can be sustained at nine months despite coaching cessation. We observed sustained improvements for weight loss, liver fat, blood pressure and body composition. This approach could provide a new tool to obtain and maintain improvements in NAFLD.

Body surface scan anthropometrics are associated with grip strength in the general population

Background and aimBody shape and anthropometrics are well-known risk factors for cardiovascular diseases (CVD) and mortality. Hand-grip strength (HGS) is also a meaningful marker of health and a promising predictor of CVD and mortality. There is a lack of studies that have systematically investigated associations between body shape and anthropometrics with HGS. In a population-based study, we investigated if anthropometric markers derived from 3D body scanning are related to HGS. Methods and resultsWe used the data of 1,599 individuals aged 36 to 93 years, who participated in the Study of Health in Pomerania. A total of 87 anthropometric markers, determined by a 3D body scanner, were included in the analysis. Anthropometric measurements were standardized and used as exposure variables. HGS was measured with a hand dynamometer and used as outcome. Sex-stratified linear regression models adjusted for age and height were used to relate standardized anthropometrics and HGS. Anthropometric markers were ranked according to -log-p-values.In men, left and right forearm circumference, left arm length to neck (C7), left forearm length, and forearm-fingertip length were most strongly related to HGS. In women, right forearm circumference, forearm-fingertip length, shoulder breadth, left forearm circumference, and right wrist circumference showed the most significant associations with HGS. The final prediction models contained 13 anthropometric markers in males (R2=0.54) and eight anthropometric markers in females (R2=0.37). ConclusionsThe identified parameters may help estimate HGS in the clinical setting. However, studies in clinical settings are essential to validating our findings.

Effect of a Dietary Intervention on Insulin Requirements and Glycemic Control in Type 1 Diabetes: A 12-Week Randomized Clinical Trial.

This study compared the effects of a low-fat vegan diet to those of a portion-controlled diet in people with type 1 diabetes. Over 12 weeks, the average total daily dose of insulin decreased significantly and insulin sensitivity increased significantly in the vegan group, while no significant changes were observed in the group receiving the portion-controlled diet. Total and LDL cholesterol decreased in the vegan group, as did the ratio of blood urea nitrogen to creatinine. A1C decreased in both groups. These findings suggest that a low-fat vegan diet may yield improvements in insulin sensitivity, insulin requirements, glycemic control, and markers of cardiovascular and renal health compared with a portion-controlled diet in people with type 1 diabetes.

Causal Association of Telomere Length and Loss of Bone: a Directional Mendelian Randomization Study of Multi-Outcomes.

This study employed a genome-wide association study (GWAS) to investigate the relationship between telomere length and marginal bone loss (MBL), a marker of bone health and aging. Telomere length, a biological indicator of aging, was analyzed alongside several serum markers of bone loss. Following a screen for appropriate instrumental variables, telomere length was designated as the exposure variable. We conducted the main analysis using random-effects inverse variance weighting (IVW) and supplemented it with MR Egger, weighted median, simple mode, and weighted mode analyses, employing a total of five methods. Positive outcomes underwent scrutiny through heterogeneity analysis, horizontal multiplicity analysis, and leave-one-out plot. Subsequently, the effective gene locus was chosen for a reverse MR analysis, with positive results serving as the exposure variable. We found a causal relationship between telomere length and the expression of osteocalcin (OC), matrix metalloproteinase-3 (MMP-3), and matrix metalloproteinase-12 (MMP-12), key markers of bone metabolism. Our findings suggest that telomere wear and shortening may contribute to increased activity of OC, MMP-3, and MMP-12, thus affecting bone metabolism. However, reverse Mendelian randomization analysis did not indicate a significant impact of OC, MMP-3, and MMP-12 on telomere length, implying a unidirectional relationship. Overall, this meta-analysis underscores the association between telomere length and bone loss, highlighting the importance of timing and duration of telomere wear and shortening in influencing bone metabolism.

Deep learning of movement behavior profiles and their association with markers of cardiometabolic health

BackgroundTraditionally, existing studies assessing the health associations of accelerometer-measured movement behaviors have been performed with few averaged values, mainly representing the duration of physical activities and sedentary behaviors. Such averaged values cannot naturally capture the complex interplay between the duration, timing, and patterns of accumulation of movement behaviors, that altogether may be codependently related to health outcomes in adults. In this study, we introduce a novel approach to visually represent recorded movement behaviors as images using original accelerometer outputs. Subsequently, we utilize these images for cluster analysis employing deep convolutional autoencoders.MethodsOur method involves converting minute-by-minute accelerometer outputs (activity counts) into a 2D image format, capturing the entire spectrum of movement behaviors performed by each participant. By utilizing convolutional autoencoders, we enable the learning of these image-based representations. Subsequently, we apply the K-means algorithm to cluster these learned representations. We used data from 1812 adult (20–65 years) participants in the National Health and Nutrition Examination Survey (NHANES, 2003–2006 cycles) study who worn a hip-worn accelerometer for 7 seven consecutive days and provided valid accelerometer data.ResultsDeep convolutional autoencoders were able to learn the image representation, encompassing the entire spectrum of movement behaviors. The images were encoded into 32 latent variables, and cluster analysis based on these learned representations for the movement behavior images resulted in the identification of four distinct movement behavior profiles characterized by varying levels, timing, and patterns of accumulation of movement behaviors. After adjusting for potential covariates, the movement behavior profile characterized as “Early-morning movers” and the profile characterized as “Highest activity” both had lower levels of insulin (P < 0.01 for both), triglycerides (P < 0.05 and P < 0.01, respectively), HOMA-IR (P < 0.01 for both), and plasma glucose (P < 0.05 and P < 0.1, respectively) compared to the “Lowest activity” profile. No significant differences were observed for the “Least sedentary movers” profile compared to the “Lowest activity” profile.ConclusionsDeep learning of movement behavior profiles revealed that, in addition to duration and patterns of movement behaviors, the timing of physical activity may also be crucial for gaining additional health benefits.

Effects of Prune (Dried Plum) Supplementation on Cardiometabolic Health in Postmenopausal Women: An Ancillary Analysis of a 12-Month Randomized Controlled Trial, The Prune Study

BackgroundEstrogen withdrawal during menopause is associated with an unfavorable cardiometabolic profile. Prunes (dried plums) represent an emerging functional food and have been previously demonstrated to improve bone health. However, our understanding of the effects of daily prune intake on cardiometabolic risk factors in postmenopausal women is limited. ObjectivesWe conducted an ancillary investigation of a randomized controlled trial (RCT), The Prune Study, to evaluate the effect of 12-mo prune supplementation on cardiometabolic health markers in postmenopausal women. MethodsThe Prune Study was a single-center, parallel-design, 12-mo RCT in which postmenopausal women were allocated to no-prune control, 50 g/d prune, or 100 g/d prune groups. Blood was collected at baseline, 6 mo, and 12 mo/post to measure markers of glycemic control and blood lipids. Body composition was assessed at baseline, 6 mo, and 12 mo/post using dual-energy X-ray absorptiometry. Linear mixed-effects models were used to evaluate the effect of time, treatment, and their interaction on cardiometabolic health markers, all quantified as exploratory outcomes. ResultsA total of 183 postmenopausal women (mean age, 62.1 ± 4.9 y) completed the entire 12-mo RCT: control (n = 70), 50 g/d prune (n = 67), and 100 g/d prune (n = 46). Prune supplementation at 50 g/d or 100 g/d did not alter markers of glycemic control and blood lipids after 12 mo compared with the control group (all P > 0.05). Furthermore, gynoid percent fat and visceral adipose tissue (VAT) indices did not significantly differ in women consuming 50 g/d or 100 g/d prunes compared with the control group after 12 mo of intervention. However, android total mass increased by 3.19% ± 5.5% from baseline in the control group, whereas the 100 g/d prune group experienced 0.02% ± 5.6% decrease in android total mass from baseline (P < 0.01). ConclusionsPrune supplementation at 50 g/d or 100 g/d for 12 mo does not improve glycemic control and may prevent adverse changes in central adiposity in postmenopausal women.This trial was registered at clinicaltrials.gov as NCT02822378.

Relationship of device measured physical activity type and posture with cardiometabolic health markers: pooled dose–response associations from the Prospective Physical Activity, Sitting and Sleep Consortium

Aims/hypothesisThe aim of this study was to examine the dose–response associations of device-measured physical activity types and postures (sitting and standing time) with cardiometabolic health.MethodsWe conducted an individual participant harmonised meta-analysis of 12,095 adults (mean ± SD age 54.5±9.6 years; female participants 54.8%) from six cohorts with thigh-worn accelerometry data from the Prospective Physical Activity, Sitting and Sleep (ProPASS) Consortium. Associations of daily walking, stair climbing, running, standing and sitting time with a composite cardiometabolic health score (based on standardised z scores) and individual cardiometabolic markers (BMI, waist circumference, triglycerides, HDL-cholesterol, HbA1c and total cholesterol) were examined cross-sectionally using generalised linear modelling and cubic splines.ResultsWe observed more favourable composite cardiometabolic health (i.e. z score <0) with approximately 64 min/day walking (z score [95% CI] −0.14 [−0.25, −0.02]) and 5 min/day stair climbing (−0.14 [−0.24, −0.03]). We observed an equivalent magnitude of association at 2.6 h/day standing. Any amount of running was associated with better composite cardiometabolic health. We did not observe an upper limit to the magnitude of the dose–response associations for any activity type or standing. There was an inverse dose–response association between sitting time and composite cardiometabolic health that became markedly less favourable when daily durations exceeded 12.1 h/day. Associations for sitting time were no longer significant after excluding participants with prevalent CVD or medication use. The dose–response pattern was generally consistent between activity and posture types and individual cardiometabolic health markers.Conclusions/interpretationIn this first activity type-specific analysis of device-based physical activity, ~64 min/day of walking and ~5.0 min/day of stair climbing were associated with a favourable cardiometabolic risk profile. The deleterious associations of sitting time were fully attenuated after exclusion of participants with prevalent CVD and medication use. Our findings on cardiometabolic health and durations of different activities of daily living and posture may guide future interventions involving lifestyle modification.Graphical

Social class stigma and poorer health behaviors: Evidence from the eating in America study

Although the association between objective markers of low socioeconomic status (SES) and poor health is well established, one underexamined possibility is that over and above objective SES, social class stigma—experiences and anticipation of discrimination based on social class—might undermine people's ability to engage in healthy behaviors. Participants (N = 2022) were recruited between December 2019 and January 2020 via a national Qualtrics panel that was census-matched to the U.S. population in age, gender, income, race/ethnicity, and census region. Participants completed measures of class stigma, alcohol use, disordered eating, comfort eating, sleep disturbance, physical activity, and demographics. Controlling for objective SES and demographics, generalized linear regression models indicated that class stigma was associated with significantly greater alcohol use, disordered eating, greater comfort eating, and sleep disturbance but not less physical activity. Class stigma was not associated with health behaviors after full adjustment for weight/racial discrimination and psychological factors. Results from this investigation suggest that beyond one's objective SES, the stigma associated with having low class may also contribute to poorer health behaviors.

Correlation of handgrip strength with quality of life-adjusted pulmonary function in adults.

Handgrip strength (HGS) is acknowledged as a key indicator of overall physical fitness and is associated with various health outcomes. This research investigates the correlation between HGS and quality of life (QoL), focusing on its relation to pulmonary function in the general adult population. The study involved 19,402 participants aged 40 and above, spanning from 2014 to 2019, who underwent pulmonary function and HGS tests. Participants were categorized based on lung function, and regression analyses were employed to examine the relationship between HGS and QoL, with adjustments made for lung function. The average age of the cohort was 58.2 years, comprising 44.6% males and 41.2% smokers. Out of the 18,708 participants who completed the European Quality of Life Scale-Five Dimensions (EQ-5D-3L) assessment, higher severity levels in mobility, self-care, usual activities, pain or discomfort, and anxiety or depression were linked to lower HGS in both sexes. Additionally, among the 3,723 participants who completed the Health-related Quality of Life Instrument with 8 Items (HINT-8) assessment, higher severity levels in pain, work, and depression were associated with lower HGS in men. In women, higher severity levels in climbing stairs, pain, vitality, and work correlated with lower HGS. As problems indicated by EQ-5D worsened, there was a consistent decrease in handgrip strength (HGS) across both genders. The HINT-8 assessment further revealed that increased severity in pain and work-related issues led to reduced HGS in both men and women. This study highlights the relationship between HGS and Quality of Life (QoL), taking lung function into consideration, and underscores the importance of HGS as a potential marker of physical health and fitness.

Associations of Dietary Intake with Cardiovascular Risk in Long-Term "Plant-Based Eaters": A Secondary Analysis of a Cross-Sectional Study.

A plant-based diet rich in whole foods and fiber is beneficial for cardiovascular (CV) health. This impact is often linked to specific food groups and their preparation methods, reflecting the overall dietary pattern. However, research on the long-term effects of a carefully designed plant-based diet on adults transitioning from a typical Western lifestyle is limited. Notably, studies on people managing CV risk factors effectively are scarce. As part of a cross-sectional study, we examined 151 individuals committed to a long-term, well-designed plant-based diet and active lifestyle. We investigated how specific food groups and macronutrient intake are related to various CV health markers. In this secondary analysis, our comprehensive approach encompassed several methods: 3-day weighted dietary records, fasting blood lipid and blood pressure measurements, body composition assessments, and evaluations of lifestyle status. We adjusted our analysis for multiple variables, such as age, sex, current body mass index, smoking status, physical activity, and time (years) following the plant-based diet. Our findings revealed several associations between macronutrient intake (per 50 g) and CV risk markers, although these associations were generally weak. Individuals who consumed more whole grains and fruits had lower levels of total, low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C) cholesterol. We also found associations between the intake of legumes and nuts/seeds and reduced HDL-C levels. These findings suggested that these food groups might influence the lipid profile, contributing to CV health in a plant-based diet. A greater intake of spices/herbs was associated with lower uric acid levels, while diets rich in plant-based fast food and pasta (made from white flour) were associated with higher uric acid levels. A greater intake of various macronutrients, such as fiber, carbohydrates (from whole-food sources), proteins, and different types of fats (saturated fatty acids [SFAs], monounsaturated fatty acids [MUFAs], and polyunsaturated fatty acids [PUFAs]), was associated with lower levels of total cholesterol, LDL-C (only for carbohydrates), and HDL-C. We found a unique negative correlation between PUFA intake and LDL-C, suggesting that PUFAs might significantly affect LDL-C levels. In contrast, increased fiber, protein and SFA consumption were associated with increased uric acid levels. These findings support the impact of dietary patterns on CV risk factors, highlighting that even small amounts of unhealthy food groups can significantly influence specific CV risk markers, regardless of the overall diet.

An evaluation of heart rate monitoring with in-ear microphones under motion

With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate detection systems. Heart rate is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable heart rate monitoring with wearable devices has therefore gained increasing attention in recent years. Existing heart rate detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient heart rate monitoring. We first collected heart rate-induced sounds in the ear canal using an in-ear microphone under seven stationary activities and two full-body motion activities (i.e., walking, and running). Then, we devised a novel deep learning based motion artefact (MA) mitigation framework to denoise the in-ear audio signals, followed by a heart rate estimation algorithm to extract heart rate. With data collected from 15 subjects over nine activities, we demonstrate that hEARt, our end-to-end approach, achieves a mean absolute error (MAE) of 1.88 ± 2.89 BPM, 6.83 ± 5.05 BPM, and 13.19 ± 11.37 BPM for stationary, walking, and running, respectively, opening the door to a new non-invasive and affordable heart rate monitoring with useable performance for daily activities. Not only does hEARt outperform previous in-ear heart rate monitoring work, but it outperforms reported in-ear PPG performance.