scholarly journals Evaluation of Latent Models Assessing Physical Fitness and the Healthy Eating Index in Community Studies: Time-, Sex-, and Diabetes-Status Invariance

Nutrients ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 4258
Author(s):  
Scott B. Maitland ◽  
Paula Brauer ◽  
David M. Mutch ◽  
Dawna Royall ◽  
Doug Klein ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Measurement Equivalence ◽  
Healthy Eating Index ◽  
Model Fit ◽  
Measurement Properties ◽  
Equation Modeling ◽  
Primary Study ◽  
Analytic Methods ◽  
Factor Analytic ◽  
Diabetes Status

Accurate measurement requires assessment of measurement equivalence/invariance (ME/I) to demonstrate that the tests/measurements perform equally well and measure the same underlying constructs across groups and over time. Using structural equation modeling, the measurement properties (stability and responsiveness) of intervention measures used in a study of metabolic syndrome (MetS) treatment in primary care offices, were assessed. The primary study (N = 293; mean age = 59 years) had achieved 19% reversal of MetS overall; yet neither diet quality nor aerobic capacity were correlated with declines in cardiovascular disease risk. Factor analytic methods were used to develop measurement models and factorial invariance were tested across three time points (baseline, 3-month, 12-month), sex (male/female), and diabetes status for the Canadian Healthy Eating Index (2005 HEI-C) and several fitness measures combined (percentile VO2 max from submaximal exercise, treadmill speed, curl-ups, push-ups). The model fit for the original HEI-C was poor and could account for the lack of associations in the primary study. A reduced HEI-C and a 4-item fitness model demonstrated excellent model fit and measurement equivalence across time, sex, and diabetes status. Increased use of factor analytic methods increases measurement precision, controls error, and improves ability to link interventions to expected clinical outcomes.

scholarly journals Skipping Breakfast Is Associated with Diet Quality and the Distribution of Food Intake Throughout the Day: NHANES 2005–20016

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 534-534
Author(s):  
Owen Kelly ◽  
Stephanie Fanelli ◽  
Sara Thomas ◽  
Jessica Krok-Schoen ◽  
Satya Jonnalagadda ◽  
...  
Keyword(s):  
Food Intake ◽  
Healthy Eating ◽  
Diet Quality ◽  
Diabetes Management ◽  
Population Based ◽  
Healthy Eating Index ◽  
Dietary Intakes ◽  
Nutrient Intakes ◽  
Diabetes Status ◽  
Skipping Breakfast

Abstract Objectives Distribution of carbohydrate intakes (carb choices) throughout the day are an important aspect to diabetes management and reducing blood glucose spikes. Skipping breakfast represents a behavior of concern, providing an extension of the overnight fast and may result in elevated sugar levels later in the day. Therefore, the purpose of this study was to evaluate dietary intake differences, including carbohydrates, based on consuming breakfast or not, and by diabetes status. Methods Adults over 30 years from NHANES 2005–2016 were classified into nondiabetes (HbA1c <5.7%, n = 14,701), prediabetes (HbA1c 5.7–6.4%, n = 5855) and diabetes (HbA1c (≥6.5%, n = 2881). Dietary intakes were assessed using a multiple pass 24-hour recall to estimate intakes from the foods and beverages reported as consumed on the day prior to the NHANES visit. Breakfast was self-defined by participants. Total population-based means (95% CI) of nutrient intakes, MyPlate equivalents, and Healthy Eating Index 2015 scores from the day of intake were calculated across levels of glycemic control and skipping breakfast status. Results Across all groups, adults who reported breakfast consumption had a significantly better overall diet quality, while total intakes of whole grains and fiber were significantly lower in those who skipped breakfast. Intakes of added sugars were not significantly different between those who skipped versus consumed breakfast. Conclusions The absence of breakfast on the day of intake was related to differential intakes of several nutrients related to healthy eating and glycemic management, resulting in a poorer overall diet quality. Healthcare professionals could evaluate meal skipping patterns and its impact on overall nutrient intakes, and the distribution of food intake throughout the day, in people with diabetes, to help improve disease management. Funding Sources Abbott Nutrition.

scholarly journals A Time-, Gender-, and Disease-State Invariant Model of Fitness Across the Adult Lifespan

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 400-400
Author(s):  
Scott Maitland ◽  
Paula Brauer ◽  
David Mutch ◽  
Dawna Royall ◽  
Doug Klein ◽  
...  
Keyword(s):  
Diet Quality ◽  
Disease Risk ◽  
Measurement Equivalence ◽  
Cardiovascular Disease Risk ◽  
Disease Status ◽  
Healthy Eating Index ◽  
Disease State ◽  
Measurement Properties ◽  
Adult Lifespan ◽  
Measurement Models

Abstract In studies of community-based health behavior interventions (diet and physical activity) one goal in analysis is to show expected relationships between measures of intervention and clinically relevant outcomes. Many programs fail to show such clear links for many reasons beyond lack of intervention effectiveness. These secondary analyses were undertaken to assess if the measurement properties (stability and responsiveness) of intervention measures could have contributed to study findings. A feasibility study of lifestyle treatment of metabolic syndrome (n=293; mean age = 59yrs) had achieved 19% reversal over one year, yet neither diet quality nor fitness were associated with cardiovascular disease risk. Confirmatory factor analysis was used to examine fit of measurement models and factorial invariance was tested across three time points (baseline, 3-month, 12-month), gender (male/female), and disease status (diabetes) for the Healthy Eating Index (HEI) (Canada 2005) and several fitness measures (VO2max, flexibility, curl-ups, push-ups). The model fit for HEI was poor and could account for the lack of association seen in the original study. More development of diet quality measures is needed. The model for fitness, however, demonstrated excellent fit and displayed measurement equivalence across time, gender, and disease state. A higher degree of confidence exists when measurement equivalence/invariance is demonstrated, allowing for reliable tests of differences in comparison groups. The use of a multiple measure of fitness, including cardiorespiratory fitness, flexibility, and strength, helps eliminate limitations of using measures from a single domain or self-reported data is promising and should be considered in future work.

Cross-cultural measurement equivalence of the Healthy Eating Index adapted version for children aged 1 to 2 years

2020 ◽  
pp. 1-24
Author(s):  
SA Ribas ◽  
DMG Santos ◽  
GPC Rosa ◽  
MT Teixeira ◽  
LG Rodrigues ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Vegetable Intake ◽  
Measurement Equivalence ◽  
Healthy Eating Index ◽  
Cross Cultural ◽  
Dietary Recommendations ◽  
University Hospitals ◽  
Cross Sectional ◽  
Observer Reliability

ABSTRACT The objectives of this study were to evaluate the cross-cultural measurement equivalence of the Healthy Eating Index (HEI) for children aged 1 to 2 years and to analyse the quality of nutrition of preterm infants. This was a cross-sectional study with 106 premature infants attended in two specialized outpatient clinics of university hospitals. The quality of the diet was analysed through an adapted HEI to meet the dietary recommendations of Brazilian children aged 1 to 2 years. 24-hour recalls measured food consumption. The reliability of the instrument was evaluated by internal consistency analysis and inter-observer reliability using Conbrach’s alpha coefficient and Kappa with quadratic ponderation. The construct validity was evaluated by the Principal Component Analysis and by Spearman’s correlation coefficient with total energy and consumption of some groups’ food. The diet quality was considered adequate when the total HEI score was over 80 points. Cronbach’s alpha was 0.54. Regarding inter-observer reliability, ten items showed strong agreement (k>0.8). The items scores had low correlations with energy consumed (r ≤ 0.30), and positive and moderate correlation of fruit (r=0.67), meat (r=0.60) and variety of diet (r=0.57) with total scores. When analysing the overall quality of the diet, most patients need improvement (median 78.7 points), which can be attributed to low total vegetable intake and the presence of ultra-processed foods in the diet. The instrument showed auspicious psychometric properties, being promising to evaluate the quality of the diet in children aged 1 to 2 years.

scholarly journals Mediterranean Diet and Healthy Eating in Subjects with Prediabetes from the Mollerussa Prospective Observational Cohort Study

Nutrients ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 252
Author(s):  
Mireia Falguera ◽  
Esmeralda Castelblanco ◽  
Marina Idalia Rojo-López ◽  
Maria Belén Vilanova ◽  
Jordi Real ◽  
...  
Keyword(s):  
Glucose Tolerance ◽  
Mediterranean Diet ◽  
Healthy Eating ◽  
Dietary Patterns ◽  
Normal Glucose Tolerance ◽  
Healthy Eating Index ◽  
Study Cohort ◽  
Cross Sectional ◽  
Normal Glucose ◽  
Multivariable Analyses

We aimed to assess differences in dietary patterns (i.e., Mediterranean diet and healthy eating indexes) between participants with prediabetes and those with normal glucose tolerance. Secondarily, we analyzed factors related to prediabetes and dietary patterns. This was a cross-sectional study design. From a sample of 594 participants recruited in the Mollerussa study cohort, a total of 535 participants (216 with prediabetes and 319 with normal glucose tolerance) were included. The alternate Mediterranean Diet score (aMED) and the alternate Healthy Eating Index (aHEI) were calculated. Bivariable and multivariable analyses were performed. There was no difference in the mean aMED and aHEI scores between groups (3.2 (1.8) in the normoglycemic group and 3.4 (1.8) in the prediabetes group, p = 0.164 for the aMED and 38.6 (7.3) in the normoglycemic group and 38.7 (6.7) in the prediabetes group, p = 0.877 for the aHEI, respectively). Nevertheless, women had a higher mean of aMED and aHEI scores in the prediabetes group (3.7 (1.9), p = 0.001 and 40.5 (6.9), p < 0.001, respectively); moreover, they had a higher mean of aHEI in the group with normoglycemia (39.8 (6.6); p = 0.001). No differences were observed in daily food intake between both study groups; consistent with this finding, we did not find major differences in nutrient intake between groups. In the multivariable analyses, the aMED and aHEI were not associated with prediabetes (odds ratio (OR): 1.19, 95% confidence interval (CI): 0.75–1.87; p = 0.460 and OR: 1.32, 95% CI: 0.83–2.10; p = 0.246, respectively); however, age (OR: 1.04, 95% CI: 1.02–1.05; p < 0.001), dyslipidemia (OR: 2.02, 95% CI: 1.27–3.22; p = 0.003) and body mass index (BMI) (OR: 1.09, 95% CI: 1.05–1.14; p < 0.001) were positively associated with prediabetes. Physical activity was associated with a lower frequency of prediabetes (OR: 0.48, 95% CI: 0.31–0.72; p = 0.001). In conclusion, subjects with prediabetes did not show a different dietary pattern compared with a normal glucose tolerance group. However, further research is needed on this issue.

A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models

2021 ◽  
pp. 001316442110089
Author(s):  
Yuanshu Fu ◽  
Zhonglin Wen ◽  
Yang Wang
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Reliability Estimation ◽  
Model Fit ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Reliability Estimates ◽  
Confirmatory Factor ◽  
Composite Reliability

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

Genetic and Environmental Influences of Dietary Indices in a UK Female Twin Cohort

2020 ◽  
Vol 23 (6) ◽  
pp. 330-337
Author(s):  
Olatz Mompeo ◽  
Rachel Gibson ◽  
Paraskevi Christofidou ◽  
Tim D. Spector ◽  
Cristina Menni ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Menopausal Status ◽  
Healthy Eating Index ◽  
Healthy Diet ◽  
Nutritional Epidemiology ◽  
Best Fitting ◽  
Heritability Estimates ◽  
Fitting Model ◽  
Dietary Indices ◽  
Health Parameters

AbstractA healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.

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