scholarly journals Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children

SLEEP ◽  
2021 ◽  
Author(s):  
Lisa Matricciani ◽  
Catherine Paquet ◽  
François Fraysse ◽  
Anneke Grobler ◽  
Yichao Wang ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Cardiometabolic Risk ◽  
High Efficiency ◽  
Cardiometabolic Health ◽  
Maturity Stage ◽  
Cluster Membership ◽  
Geographic Clustering ◽  
Adults And Children ◽  
Study Participants ◽  
Generalised Estimating Equations

Abstract Study objectives Sleep plays an important role in cardiometabolic health. While the importance of considering sleep as a multidimensional construct is widely appreciated, studies have largely focused on individual sleep characteristics. The association between actigraphy-derived sleep profiles and cardiometabolic health in healthy adults and children has not been examined. Methods This study used actigraphy-measured sleep data collected between February 2015 and March 2016 in the Child Health CheckPoint study. Participants wore actigraphy monitors (GENEActiv Original, Cambs, UK) on their non-dominant wrist for seven days and sleep characteristics (period, efficiency, timing and variability) were derived from raw actigraphy data. Actigraphy-derived sleep profiles of 1,043 Australian children aged 11-12 years and 1337 adults were determined using K-means cluster analysis. The association between cluster membership and biomarkers of cardiometabolic health (blood pressure, body mass index, apolipoproteins, glycoprotein acetyls, composite metabolic syndrome severity score) were assessed using Generalised Estimating Equations, adjusting for geographic clustering, with sex, socioeconomic status, maturity stage (age for adults, pubertal status for children) and season of data collection as covariates. Results Four actigraphy-derived sleep profiles were identified in both children and adults: Short sleepers, Late to bed, Long sleepers, and Overall good sleepers. The Overall good sleeper pattern (characterised by adequate sleep period time, high efficiency, early bedtime and low day-to-day variability) was associated with better cardiometabolic health in the majority of comparisons (80%). Conclusion Actigraphy-derived sleep profiles are associated with cardiometabolic health in adults and children. The Overall good sleeper pattern is associated with more favourable cardiometabolic health.

scholarly journals Sex differences in the associations between adiposity distribution and cardiometabolic risk factors in overweight or obese individuals: a cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yide Yang ◽  
Ming Xie ◽  
Shuqian Yuan ◽  
Yuan Zeng ◽  
Yanhui Dong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sex Differences ◽  
Body Fat ◽  
Regression Models ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Whole Body ◽  
Anthropometric Measurement ◽  
Cardiometabolic Health ◽  
Lower Odds

Abstract Background We aimed to assess the associations between adiposity distribution and cardiometabolic risk factors among overweight and obese adults in China, and to demonstrate the sex differences in these associations. Methods A total of 1221 participants (455 males and 766 females) were included in this study. Percentage of body fat (PBF) of the whole body and regional areas, including arm, thigh, trunk, android, and gynoid, were measured by the dual-energy X-ray absorptiometry method. Central adiposity was measured by waist circumference. Clustered cardiometabolic risk was defined as the presence of two or more of the six cardiometabolic risk factors, namely, high triglyceride, low high density lipoprotein, elevated glucose, elevated blood pressure, elevated high sensitivity C-reactive protein, and low adiponectin. Linear regression models and multivariate logistic regression models were used to assess the associations between whole body or regional PBF and cardiometabolic risk factors. Results In females, except arm adiposity, other regional fat (thigh, trunk, android, gynoid) and whole-body PBF are significantly associated with clustered cardiometabolic risk, adjusting for age, smoking, alcohol drinking, physical activity, and whole-body PBF. One-SD increase in Z scores of the thigh and gynoid PBF were significantly associated with 80 and 78% lower odds of clustered cardiometabolic risk (OR: 0.20, 95%CI: 0.12–0.35 and OR: 0.22, 95%CI: 0.12–0.41). Trunk, android and whole-body PBF were significantly associated with higher odds of clustered risk with OR of 1.90 (95%CI:1.02–3.55), 2.91 (95%CI: 1.75–4.85), and 2.01 (95%CI: 1.47–2.76), respectively. While in males, one-SD increase in the thigh and gynoid PBF are associated with 94% (OR: 0.06, 95%CI: 0.02–0.23) and 83% lower odds (OR: 0.17, 95%CI: 0.05–0.57) of clustered cardiometabolic risk, respectively. Android and whole-body PBF were associated with higher odds of clustered cardiometabolic risk (OR: 3.39, 95%CI: 1.42–8.09 and OR: 2.45, 95%CI: 1.53–3.92), but the association for trunk PBF was not statistically significant (OR: 1.16, 95%CI: 0.42–3.19). Conclusions Adiposity distribution plays an important role in the clustered cardiometabolic risk in participants with overweight and obese and sex differences were observed in these associations. In general, central obesity (measured by android PBF) could be the best anthropometric measurement for screening people at risk for CVD risk factors for both men and women. Upper body fat tends to be more detrimental to cardiometabolic health in women than in men, whereas lower body fat is relatively more protective in men than in women.

scholarly journals Evaluation of Child–Computer Interaction Using Fitts’ Law: A Comparison between a Standard Computer Mouse and a Head Mouse

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3826
Author(s):  
Cristina Sanchez ◽  
Vanina Costa ◽  
Rodrigo Garcia-Carmona ◽  
Eloy Urendes ◽  
Javier Tejedor ◽  
...  
Keyword(s):  
Motor Control ◽  
Inertial Sensor ◽  
Psychomotor Development ◽  
Fine Motor ◽  
Input Devices ◽  
Fitts Law ◽  
Computer Mouse ◽  
Adults And Children ◽  
Study Participants ◽  
Computer Interaction

This study evaluates and compares the suitability for child–computer interaction (CCI, the branch within human–computer interaction focused on interactive computer systems for children) of two devices: a standard computer mouse and the ENLAZA interface, a head mouse that measures the user’s head posture using an inertial sensor. A multidirectional pointing task was used to assess the motor performance and the users’ ability to learn such a task. The evaluation was based on the interpretation of the metrics derived from Fitts’ law. Ten children aged between 6 and 8 participated in this study. Participants performed a series of pre- and post-training tests for both input devices. After the experiments, data were analyzed and statistically compared. The results show that Fitts’ law can be used to detect changes in the learning process and assess the level of psychomotor development (by comparing the performance of adults and children). In addition, meaningful differences between the fine motor control (hand) and the gross motor control (head) were found by comparing the results of the interaction using the two devices. These findings suggest that Fitts’ law metrics offer a reliable and objective way of measuring the progress of physical training or therapy.

Abstract MP72: Feasibility, Safety and Acceptability of Soy-Based Diet for Pregnant Women: Preliminary Results From a Pilot Randomized Controlled Trial

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Ling Shi ◽  
Vidya Iyer ◽  
Errol Norwitz ◽  
Tiffany A Moore Simas ◽  
Nirupa Matthan ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Adverse Events ◽  
Pregnant Women ◽  
Health Effects ◽  
Cardiometabolic Risk ◽  
Controlled Trial ◽  
Cardiometabolic Health ◽  
Randomized Controlled ◽  
Pilot Randomized Controlled Trial ◽  
Whole Foods

Introduction: Previous evidence suggests that soy containing foods may have beneficial effects on lipid and glycemic metabolism due to their biologically active components, including soy protein and isoflavones. Pregnancy is associated with changes in glucose and lipid metabolism, partially attributable to elevated estrogen concentrations. We have previously reported a significant, inverse association between urinary excretion of isoflavones and cardiometabolic risk markers in pregnant women, using data from the National Health and Nutrition Examination Survey (NHANES). Further studies are needed to determine the cardiometabolic health effects of soy intake in pregnant women. Hypothesis: We hypothesize that consumption of soy-based whole foods is safe and acceptable for pregnant women and has beneficial cardiometabolic health effects. Methods: A pilot randomized controlled trial (RCT) was conducted in 30 pregnant women who received counseling to consume either a high-soy or low-soy foods containing diet. Assessments (physical and anthropometric measurements, food frequency questionnaires, fasting blood samples) were conducted at 14 and 28 weeks of pregnancy, and 6 weeks’ postpartum. Monthly follow-up calls were conducted by research team coordinator to assess safety and encourage adherence. Results: Both the high-soy and low-soy groups demonstrated high adherence (80-90%), defined as consuming soy foods ≥ 15 days in the past four weeks for high-soy group and ≤ 5 days for low-soy group. Five subjects in the high-soy group reported adverse events (nausea, vomiting, diarrhea, itchy mouth); all were transient and resolved without sequelae. No adverse events were reported in the low-soy group. Skinfold thickness decreased (-4.8 mm) in the high-soy group and increased (+3.6 mm) in the low-soy group (p=0.04). There was a trend towards lower BMI in the high-soy compared to low-soy group at 28 weeks (+1.4 vs. +3.6 kg/m 2 , respectively, p=0.15) and postpartum (-1.2 vs. +0.6 kg/m 2 , respectively, p=0.14). This decrease in BMI was predominantly a loss of body fat and not lean mass. There were no significant differences between groups in fasting glucose, HDL-C, LDL-C, TG, or VLDL concentrations. Conclusions: In conclusion, results from this pilot RCT support the acceptability and safety of consuming soy-based whole foods during pregnancy. A larger-scale RCT is needed to further elucidate the effects of soy-based foods on cardiometabolic risk factors during pregnancy, as well as the transgenerational effects on their offspring.

scholarly journals Effects of Extreme Weight Loss on Cardiometabolic Health in Children With Metabolic Syndrome: A Metabolomic Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Jingxin Liu ◽  
Lin Zhu ◽  
Jing Liao ◽  
Xiaoguang Liu
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Weight Loss ◽  
Body Composition ◽  
Organic Acids ◽  
Cardiometabolic Risk ◽  
The Body ◽  
Cardiometabolic Risk Factors ◽  
Plasma Metabolites ◽  
Cardiometabolic Health

Objectives: To evaluate the effect of extreme weight loss programs on circulating metabolites and their relationship with cardiometabolic health in children with metabolic syndrome.Methods: This study was a quasi-experimental design with a pretest and post-test. Thirty children with metabolic syndrome and aged 10–17years were recruited to an extreme weight loss program (i.e., exercise combined with diet control). The primary outcomes included plasma metabolites, body composition, and cardiometabolic risk factors. A total of 324 metabolites were quantitatively detected by an ultra-performance liquid chromatography coupled to tandem mass spectrometry system, and the variable importance in the projection (VIP) value of each metabolite was calculated by the orthogonal projection to latent structures discriminant analysis. The fold change (FC) and p value of each metabolite were used to screen differential metabolites with the following values: VIP>1, p value<0.05, and |log2FC|>0.25. Pathway enrichment and correlation analyses between metabolites and cardiometabolic risk factors were also performed.Result: A large effect size was observed, presenting a weight loss of −8.9kg (Cohen’s d=1.00, p<0.001), body mass index reduction of −3.3kg/m2 (Cohen’s d=1.47, p<0.001), and body fat percent reduction of −4.1 (%) (Cohen’s d=1.22, p<0.001) after the intervention. Similar improvements were found in total cholesterol (Cohen’s d=2.65, p<0.001), triglycerides (Cohen’s d=2.59, p<0.001), low-density lipoprotein cholesterol (Cohen’s d=2.81, p<0.001), glucose metabolism, and blood pressure. A total of 59 metabolites were changed after the intervention (e.g., aminoacyl-tRNA biosynthesis, glycine, serine, and threonine metabolism; nitrogen metabolism, tricarboxylic acid cycle, and phenylalanine, tyrosine, and tryptophan biosynthesis). The changes in metabolites (e.g., amino acids, fatty acids, organic acids, and carnitine) were related to lipid metabolism improvement (p<0.05). Organic acids and carnitines were associated with changes in the body composition (p<0.05).Conclusion: Exercise combined with dietary control improved the body composition and cardiometabolic health in children with metabolic syndrome, and these changes may be related to plasma metabolites.

A Model for Make-or-Buy Decisions in Engineering Design Services Sector: A Case Study from Turkey

2018 ◽  
Vol 15 (04) ◽  
pp. 1850038
Author(s):  
Z. Aytan Ediz ◽  
M. Atilla Öner ◽  
Y. Can Erdem ◽  
Nesimi Kaplan
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Engineering Design ◽  
Administrative Support ◽  
Social Dynamics ◽  
Successful Implementation ◽  
Cluster Membership ◽  
Services Sector ◽  
Engineering Company

Make-or-buy decision is an important factor affecting the profitability of the firms in all sectors. The goal of this study is to propose a model for firms in engineering design services sector for make-or-buy decisions. A survey was conducted to determine the importance percentages given in an engineering company in make-or-buy decisions and a model was developed. The results of the case study show intriguing clusters of company personnel. As the lack of consensus among company managers and personnel may inhibit the successful implementation of the developed strategy, we use K-Means Clustering to determine the different perspectives of different groups of employees (managers, senior engineers, junior engineers, technical and administrative support personnel) which may contribute to the understanding of social dynamics of decision making within the company. 4-cluster and 5-cluster analysis results indicate the need for further study on the dynamics of cluster membership.

Baru Nut Intake and Resistance Training Practice Have Potential to Reduce the Cardiometabolic Risk Factors in Type 2 Diabetes

2021 ◽  
Vol 17 ◽  
Author(s):  
John Sebastião Cardoso da Silva ◽  
Maria Sebastiana Silva ◽  
Maria Margareth Veloso Naves
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Resistance Training ◽  
Cardiometabolic Risk ◽  
Nutritional Composition ◽  
Cardiometabolic Risk Factors ◽  
Cardiometabolic Health

Background: Type 2 diabetes mellitus (T2DM) is a disease associated with several cardiometabolic risk factors (CMRF). There is strong evidence about the benefits of oilseeds intake and the practice of resistance training (RT) in the prevention and treatment of T2DM and its associated CMRF. However, no study has evaluated the combination of these interventions yet. Baru nut, an oilseed native to the Brazilian Cerrado, stands out among oilseeds due to its healthy nutritional composition, which have the potential to reduce CMRF in T2DM. RT, in turn, provides positive changes in the composition and metabolism of muscle cells, which contributes to improving cardiometabolic health. Objective: This review aimed to summarize the effects and mechanisms related to the intake of baru nut and the practice of RT in reducing CMRF in T2DM. Method: Literature research was performed using the keywords "type 2 diabetes mellitus", "Dipteryx alata Vog", "nuts", "physical exercise" and "resistance training", isolated or associated, in Web of Science and Pubmed databases. Results: Baru nut is an oilseed with high density of nutrients and bioactive compounds with antioxidant and antihypercholesterolemic properties, and the RT is associated with beneficial effects on CMRF in T2DM individuals. Thus, the consumption of baru nut and the RT have potential to improve the insulin sensitivity, glycemic control, body composition, and serum lipid profile. Conclusion: The baru nut consumption and the RT have potential to reduce the cardiometabolic risk factors in T2DM. Both interventions are innovative and promising approaches to preserve the health of T2DM individuals.

Associations of Vigorous Gardening With Cardiometabolic Risk Markers for Middle-Aged and Older Adults

2021 ◽  
pp. 1-7
Author(s):  
Jonathan Kingsley ◽  
Nyssa Hadgraft ◽  
Neville Owen ◽  
Takemi Sugiyama ◽  
David W. Dunstan ◽  
...  
Keyword(s):  
Older Adults ◽  
Cardiometabolic Risk ◽  
Cross Sectional Study ◽  
Cardiometabolic Health ◽  
Risk Markers ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Vigorous Intensity ◽  
And Gender ◽  
Cardiometabolic Risk Markers

This study investigates the associations of vigorous-intensity gardening time with cardiometabolic health risk markers. This cross-sectional study (AusDiab) analyzed 2011–2012 data of 3,664 adults (55% women, mean [range], age = 59.3 [34–94] years) in Australia. Multiple linear regression models examined associations of time spent participating in vigorous gardening (0, <150 min/week, ≥150 min/week) with a clustered cardiometabolic risk (CMR) score and its components, for the whole sample and stratified by age and gender. Of participants, 61% did no vigorous gardening, 23% reported <150 min/week, and 16% reported ≥150 min/week. In the whole sample, spending ≥150 min/week in vigorous gardening was associated with lower CMR (lower CMR score, waist circumference, diastolic blood pressure, and triglycerides) compared with no vigorous gardening. Stratified analyses suggested that these associations were almost exclusively observed for older adults and women. These findings suggest the public health potential of vigorous-intensity gardening in reducing CMR.

Abstract MP11: Systematic Discovery Of Thousands Of Gene-Environment Interactions For Cardiometabolic Serum Biomarkers

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Kenneth E Westerman
Keyword(s):  
Genetic Variants ◽  
Cardiometabolic Risk ◽  
Interaction Analysis ◽  
Environmental Exposures ◽  
Cardiometabolic Health ◽  
Environment Interaction ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
A Genome ◽  
The Mean

Background: Gene-environment interaction (GEI) analysis enables us to understand how genetic variants modify the effects of environmental exposures on cardiometabolic risk factors, providing a foundation for genome-based precision medicine. Ideally, these interactions could be mapped comprehensively across all measured genetic variants, exposures, and outcomes, but this approach is computationally intensive and statistically underpowered. Recent studies have shown that variance-quantitative trait loci (vQTLs), or genetic variants that associate with differential variance of an outcome, are substantially enriched for underlying GEIs. Here, we sought to first identify vQTLs for cardiometabolic traits, then use this smaller genetic search space to uncover novel gene-environment interactions across thousands of environmental exposures. Methods: A two-stage, multi-ancestry analysis was conducted in 355,790 unrelated participants from the UK Biobank. First, we performed a genome-wide vQTL scan for each of 20 serum metabolic biomarkers, including but not limited to lipids, lipoproteins, and glycemic measures. This scan used Levene’s test to identify genetic markers whose genotypes are associated with the variance, rather than the mean, of the biomarker. Next, we collected over 2000 variables corresponding to socioeconomic, dietary, lifestyle, and clinical exposures, and conducted an interaction analysis for each combination of exposure and vQTL-biomarker pair. For each stage, the analysis was initially stratified by ancestry then meta-analyzed to generate the primary set of results. Results: vQTLs were identified at 514 independent regions in the genome, with most of these genetic variants already known to affect the mean biomarker level. In the subsequent gene-environment interaction analysis, we found 2,162 significant interactions passing a stringent significance threshold adjusted for multiple testing ( p < 0.05 / 578 vQTL-biomarker pairs / 2140 exposures = 4х10 -8 ). Some of these expanded on existing findings; for example, genetic marker rs2393775 in the HNF1A gene interacted with education level (as a proxy for socioeconomic status) to influence hsCRP ( p = 1.3х10 -10 ), building on a previous finding that HNF1A variants modify the effect of perceived stress on cardiovascular outcomes. Others highlighted novel biology, such as an interaction between variants near the fatty liver-associated gene TM6SF2 and oily fish intake on total and LDL-cholesterol levels ( p = 6.6х10 -9 ). Conclusions: Our systematic GEI discovery effort identified thousands of interactions that may impact cardiometabolic risk, both expanding on previous research and identifying novel biological mechanisms. This catalog of vQTLs and interactions can inform future mechanistic studies and provides a knowledge base for genome-centered precision approaches to cardiometabolic health.

Abstract P240: Discrimination Mediates the Adverse Effect of Neighborhood Problems on Cardiometabolic Risk Among Latino/a Adults

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Maryam Hussain
Keyword(s):  
Sex Education ◽  
Cardiometabolic Risk ◽  
Negative Impact ◽  
High Body Mass Index ◽  
Mediating Effect ◽  
Health Study ◽  
Future Research ◽  
Cardiometabolic Health ◽  
Positive Health ◽  
Neighborhood Problems

Introduction: Latino/as in the US on average present with low high-density lipoprotein (HDL) cholesterol and high body-mass index (BMI), putting them at higher risk for future cardiometabolic disease. Neighborhoods have been implicated, directly and indirectly, in poorer cardiometabolic health among ethnic minorities. US Latino/as often live in neighborhoods where they may not have access to engage in positive health behaviors, such as proper diet and physical activity. However, the mediating role of discrimination experienced in these neighborhoods has hardly been examined within the context of Latino/a cardiometabolic health. Methods: We analyzed data from the Texas City Stress and Health Study. Participants were self-identified Latino/a/Hispanic ( N = 500, 61.8% female, M age = 49.08, SD age = 15.80) who reported on their perceived experience of discrimination (higher scores reflecting more discrimination) and their perception of their neighborhood (higher scores reflecting more positive environment) validated survey measures. A trained phlebotomist drew blood in a clinic or in the participant’s home between 8 and 11 AM after fasting for HDL (mg/dL). Blood samples were centrifuged to obtain plasma, which was stored at –70°C until testing. All specimen were batch analyzed and read blind-coded. Additionally, they took clinical measures of participant’s height and weight, to calculate BMI (adjusted for sex). To estimate the mediating effect of discrimination through perception of neighborhood on cardiometabolic risk, path analysis with bootstrapped linear regression models were conducted. We conducted analyses unadjusted and adjusted for age, sex, education, and nativity. All analyses were conducted in the PROCESS macro in SPSS. Results: Participants on average had high HDL levels ( M mg/dL = 51.00, SD = 15.59). Males on average were overweight ( M BMI = 29.78, SD = 5.49) and females ( M BMI = 31.42, SD = 7.27) on average were obese. Bootstrapped estimates showed that perception of neighborhood fully mediated the effect of discrimination on HDL (b = -.43, SE = .18 p = .015) and BMI (b = .02, SE = .01, p = .023), unadjusted for covariates. Although the fully mediated model for BMI withstood adjustment for covariates, the model for HDL did not withstand adjustment. Conclusion: Discrimination accounts for the negative impact that neighborhood problems have on poor cardiometabolic health among adult Latino/as. Future research should examine how positive neighborhood interactions (e.g., walking clubs or playgroups) can mitigate the adverse effects on cardiometabolic health among this at-risk population.

Cluster Analysis with General Latent Class Model

2011 ◽  
pp. 225-230
Author(s):  
Dingxi Qiu ◽  
Edward C. Malthouse
Keyword(s):  
Cluster Analysis ◽  
Statistical Models ◽  
Latent Variable ◽  
Latent Class ◽  
Latent Class Model ◽  
Teaching Style ◽  
Teaching Styles ◽  
Binary Responses ◽  
Cluster Membership ◽  
Wide Range

Cluster analysis is a set of statistical models and algorithms that attempt to find “natural groupings” of sampling units (e.g., customers, survey respondents, plant or animal species) based on measurements. The observable measurements are sometimes called manifest variables and cluster membership is called a latent variable. It is assumed that each sampling unit comes from one of K clusters or classes, but the cluster identifier cannot be observed directly and can only be inferred from the manifest variables. See Bartholomew and Knott (1999) and Everitt, Landau and Leese (2001) for a broader survey of existing methods for cluster analysis. Many applications in science, engineering, social science, and industry require grouping observations into “types.” Identifying typologies is challenging, especially when the responses (manifest variables) are categorical. The classical approach to cluster analysis on those data is to apply the latent class analysis (LCA) methodology, where the manifest variables are assumed to be independent conditional on the cluster identity. For example, Aitkin, Anderson and Hinde (1981) classified 468 teachers into clusters according to their binary responses to 38 teaching style questions. This basic assumption in classical LCA is often violated and seems to have been made out of convenience rather than it being reasonable for a wide range of situations. For example, in the teaching styles study two questions are “Do you usually allow your pupils to move around the classroom?” and “Do you usually allow your pupils to talk to one another?” These questions are mostly likely correlated even within a class.

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