scholarly journals Application of a Latent Transition Model to Estimate the Usual Prevalence of Dietary Patterns

Nutrients ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 133
Author(s):  
Andreia Oliveira ◽  
Carla Lopes ◽  
Duarte Torres ◽  
Elisabete Ramos ◽  
Milton Severo
Keyword(s):  
Dietary Patterns ◽  
Latent Class ◽  
Transition Probabilities ◽  
Latent Class Model ◽  
Adult Population ◽  
Transition Model ◽  
Class Model ◽  
Concomitant Variables ◽  
Latent Transition ◽  
Age And Sex

Background: This study aims to derive habitual dietary patterns of the Portuguese adult population by applying two methodological approaches: a latent class model and a latent transition model. The novel application of the latent transition model allows us to determine the day-to-day variability of diet and to calculate the usual prevalence of dietary patterns. Methods: Participants are from the National Food, Nutrition and Physical Activity Survey of the Portuguese population, 2015–2016 (2029 women; 1820 men, aged ≥18 years). Diet was collected by two 24 h dietary recalls (8–15 days apart). Dietary patterns were derived by: (1) a latent class model using the arithmetic mean of food weigh intake, with concomitant variables (age and sex); (2) a latent transition model allowing the transition from one pattern to another, with the same concomitant variables. Results: Six dietary patterns were identified by a latent class model. By using a latent transition model, three dietary patterns were identified: “In-transition to Western” (higher red meat and alcohol intake; followed by middle-aged men), “Western” (higher meats/eggs and energy-dense foods intake; followed by younger men), and “Traditional-Healthier” (higher intake of fruit, vegetables and fish, characteristic of older women). Most individuals followed the same pattern on both days, but around 26% transited between “In-transition to Western” and “Western”. The prevalence of the dietary patterns using a single recall day (40%, 27%, 33%, respectively) is different from the usual prevalence obtained by the latent transition probabilities (48%, 36%, 16%). Conclusion: Three dietary patterns, largely dependent on age and sex, were identified for the Portuguese adult population: “In-transition to Western” (48%), “Western” (36%), and “Traditional-Healthier” (16%), but 26% were transient between patterns. Dietary patterns are, in general, deviating from traditional habits.

scholarly journals A latent class analysis towards stability and changes in breadwinning patterns among coupled households

2019 ◽  
Vol 7 (1) ◽  
pp. 234-246 ◽  
Author(s):  
Fulvia Pennoni ◽  
Miki Nakai
Keyword(s):  
Latent Variable ◽  
Latent Class ◽  
Wage Gap ◽  
Latent Class Model ◽  
Expectation Maximization Algorithm ◽  
Information Criteria ◽  
Class Model ◽  
Missing Responses ◽  
Concomitant Variables ◽  
Ordinal Variable

AbstractA latent class model is proposed to examine couples’ breadwinning typologies and explain the wage differentials according to the socio-demographic characteristics of the society with data collected through surveys. We derive an ordinal variable indicating the couple’s income provision-role type and suppose the existence of an underlying discrete latent variable to model the effect of covariates. We use a two-step maximum likelihood inference conducted to account for concomitant variables, informative sampling scheme and missing responses. The weighted log-likelihood is maximised through the Expectation-Maximization algorithm and information criteria are used to develop the model selection. Predictions are made on the basis of the maximum posterior probabilities. Disposing of data collected in Japan over thirty years we compare couples’ breadwinning patterns across time. We provide some evidence of the gender wage-gap and we show that it can be attributed to the fact that, especially in Japan, duties and responsibilities for the child care are supported exclusively by women.

scholarly journals Identifying Dietary Consumption Patterns from Survey Data: a Bayesian Nonparametric Latent Class Model

2021 ◽  
Author(s):  
Briana Joy Kennedy Stephenson ◽  
Francesca Dominici
Keyword(s):  
Dietary Intake ◽  
Survey Data ◽  
Low Income ◽  
Dietary Patterns ◽  
Latent Class ◽  
Latent Class Model ◽  
The United States ◽  
Sampling Weights ◽  
Class Model ◽  
The Impact

Dietary intake is one of the largest contributing factors to cardiovascular health in the United States. Amongst low-income adults, the impact is even more devastating.Dietary assessments, such as 24-hour recalls, provide snapshots of dietary habits in a study population. Questions remain on how generalizable those snapshots are in nationally representative survey data, where certain subgroups are sampled disproportionately to comprehensively examine the population. Many of the models that derive dietary patterns account for study design by incorporating the sampling weights to the derived model parameter estimates post hoc. We propose a Bayesian overfitted latent class model that accounts for survey design and sampling variability to derive dietary patterns in adults aged 20 and older. We compare these results with a subset of the population, adults considered low-income (at or below the 130% poverty income threshold) to understand if and how these patterns generalize in a smaller subpopulation. Using dietary intake data from the National Health and Nutrition Examination Surveys, we identified six dietary patterns in the US adult population. These differed in consumption features found in the five dietary patterns derived in low-income adults. Reproducible code/data are provided on GitHub to encourage further research and application in this area.

scholarly journals Customers’ Mode Choice Behaviors of Express Service Based on Latent Class Analysis and Logit Model

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Lian Lian ◽  
Shuo Zhang ◽  
Zhong Wang ◽  
Kai Liu ◽  
Lihuan Cao
Keyword(s):  
Logit Model ◽  
Choice Behavior ◽  
Latent Class ◽  
Latent Class Model ◽  
Policy Research ◽  
Multinomial Logit Model ◽  
Class Model ◽  
Taste Heterogeneity ◽  
Using Data ◽  
Service Choice

As the parcel delivery service is booming in China, the competition among express companies intensifies. This paper employed multinomial logit model (MNL) and latent class model (LCM) to investigate customers’ express service choice behavior, using data from a SP survey. The attributes and attribute levels that matter most to express customers are identified. Meanwhile, the customers are divided into two segments (penny pincher segment and high-end segment) characterized by their taste heterogeneity. The results indicate that the LCM performs statistically better than MNL in our sample. Therefore, more attention should be paid to the taste heterogeneity, especially for further academic and policy research in freight choice behavior.

scholarly journals A Comparison of Mixture Modeling Approaches in Latent Class Models With External Variables Under Small Samples

2017 ◽  
Vol 78 (6) ◽  
pp. 925-951 ◽  
Author(s):  
Unkyung No ◽  
Sehee Hong
Keyword(s):  
Sample Size ◽  
Latent Class ◽  
Latent Class Model ◽  
Mixture Modeling ◽  
Small Sample ◽  
Outcome Variable ◽  
Parameter Estimates ◽  
Class Model ◽  
Modeling Approaches ◽  
Distal Outcome

The purpose of the present study is to compare performances of mixture modeling approaches (i.e., one-step approach, three-step maximum-likelihood approach, three-step BCH approach, and LTB approach) based on diverse sample size conditions. To carry out this research, two simulation studies were conducted with two different models, a latent class model with three predictor variables and a latent class model with one distal outcome variable. For the simulation, data were generated under the conditions of different sample sizes (100, 200, 300, 500, 1,000), entropy (0.6, 0.7, 0.8, 0.9), and the variance of a distal outcome (homoscedasticity, heteroscedasticity). For evaluation criteria, parameter estimates bias, standard error bias, mean squared error, and coverage were used. Results demonstrate that the three-step approaches produced more stable and better estimations than the other approaches even with a small sample size of 100. This research differs from previous studies in the sense that various models were used to compare the approaches and smaller sample size conditions were used. Furthermore, the results supporting the superiority of the three-step approaches even in poorly manipulated conditions indicate the advantage of these approaches.

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