Application of Latent Class Analysis to Identify Metabolic Syndrome Components Patterns in adults: Tehran Lipid and Glucose study

Abstract Introduction Mental disorders are among the most prevalent health problems of the adult population in the world. This study aimed to identify the subgroups of staff based on mental disorders and assess the independent role of metabolic syndrome (MetS) on the membership of participants in each latent class. Methods This cross-sectional study was conducted among 694 staff of a military unit in Tehran in 2017. All staff of this military unit was invited to participate in this study. The collected data included demographic characteristics, anthropometric measures, blood pressure, biochemical parameters, and mental disorders. We performed latent class analysis using a procedure for latent class analysis (PROC LCA) in SAS to identify class membership of mental disorders using Symptom Checklist-90. Results Three latent classes were identified as healthy (92.7%), mild (4.9%), and severe (2.4%) mental disorders. Having higher age significantly decreased the odds of belonging to the mild class (adjusted OR (aOR = 0.21; 95% confidence interval (CI): 0.05–0.83) compared to the healthy class. Also, obesity decreased the odds of membership in mild class (aOR = 0.10, 95% CI: 0.01–0.92) compared to healthy class. On the other hand, being female increased the odds of being in severe class (aOR = 9.76; 95% CI: 1.35–70.65) class in comparison to healthy class. Conclusion This study revealed that 7.3% of staff fell under mild and severe classes. Considering educational workshops in the workplace about mental disorders could be effective in enhancing staff’s knowledge of these disorders. Also, treatment of comorbid mental disorders may help reduce their prevalence and comorbidity.

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Comparison of the accuracy of three diagnostic criteria and estimating the prevalence of metabolic syndrome: A latent class analysis

Journal of Research in Medical Sciences ◽

10.4103/jrms.jrms_858_18 ◽

2019 ◽

Vol 24 (1) ◽

pp. 108 ◽

Cited By ~ 1

Author(s):

Akbar Fotouhi ◽

Hossein Ebrahimi ◽

MohammadHassan Emamian ◽

Ahmad Khosravi ◽

Hassan Hashemi

Keyword(s):

Metabolic Syndrome ◽

Latent Class Analysis ◽

Diagnostic Criteria ◽

Latent Class ◽

Class Analysis

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Dietary behaviours associated with metabolic syndrome: a latent class analysis

10.21203/rs.3.rs-22802/v1 ◽

2020 ◽

Author(s):

Jung Ha Park ◽

Ju Young Kim ◽

So Hye Kim ◽

Jung Hyun Kim ◽

Young Mi Park ◽

...

Keyword(s):

Metabolic Syndrome ◽

Body Mass Index ◽

Latent Class Analysis ◽

Body Mass ◽

Emotional Eating ◽

Latent Class ◽

Eating Behaviour ◽

Dietary Behaviour ◽

Class Analysis ◽

Dietary Behaviours

Abstract Background Obese individuals have a number of dietary behaviours that might contribute to their weight-related health risks. However, obesity defined solely by body mass index may not reflect the true heterogeneity of the obese population. The aims of this study were to classify the dietary behaviours of obese individuals into subgroups and to explore the relationship between their patterns of dietary behaviour and cardiometabolic risk factors. Methods The study participants were 259 patients who visited an outpatient weight management clinic at a tertiary hospital and underwent a dietary behaviour assessment between January 2014 and February 2019. Dietary behaviours were assessed in three domains with nine categories, including choice of food (frequent eating out, instant/fast/takeaway food), eating behaviour (irregular meals, frequent snacking, including eating at night, emotional eating, and overeating/binge eating), and nutrient intake (high fat/high calorie foods, salty food, and poorly balanced diet). Latent class analysis (LCA) was used to classify the subjects according to these nine categories of dietary behaviour. Associations between latent class and metabolic syndrome were assessed in a logistic regression model. Results Based on their dietary behaviour, the subjects were classified into three LCA-driven classes, including a referent class of healthy eaters (n=118), a class of emotional eaters (n=53), and a class of irregular unhealthy eaters (n=88). Compared with the referent class, emotional eaters had a significantly higher body mass index (beta=3.40, P<0.001) and metabolic syndrome (odds ratio 2.88, 95% confidence interval 1.16–7.13). Conclusions Our finding of three LCA-driven obesity phenotypes could be useful for assessment and management of obesity and metabolic syndrome. The association between higher BMI and metabolic syndrome was stronger in emotional eaters than in healthy eaters and irregular unhealthy eaters. Emotional eaters might benefit from emotional regulation strategies.

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A latent class analysis of dietary behaviours associated with metabolic syndrome: a retrospective observational cross-sectional study

Nutrition Journal ◽

10.1186/s12937-020-00636-7 ◽

2020 ◽

Vol 19 (1) ◽

Author(s):

Jung Ha Park ◽

Ju Young Kim ◽

So Hye Kim ◽

Jung Hyun Kim ◽

Young Mi Park ◽

...

Keyword(s):

Metabolic Syndrome ◽

Latent Class Analysis ◽

Emotional Eating ◽

Latent Class ◽

Eating Behaviour ◽

The Body ◽

Dietary Behaviour ◽

Class Analysis ◽

Cross Sectional ◽

Dietary Behaviours

Abstract Background Obesity defined solely by the Body Mass Index (BMI) may not reflect the true heterogeneity of the obese population. This study aimed to classify the dietary behaviours of overweight and obese individuals and to explore the relationship between patterns of dietary behaviour and cardiometabolic risk factors. Methods A total of 259 patients who visited an outpatient weight management clinic at a tertiary hospital and underwent a dietary behaviour assessment between January 2014 and February 2019 were enrolled in the study. Dietary behaviours were assessed in three domains with nine categories, including choice of food (frequently eating out and consumption of instant/fast/takeaway food), eating behaviour (irregular meals; frequent snacking, including eating at night; emotional eating; and overeating/binge eating), and nutrient intake (high-fat/high-calorie foods, salty food, and poorly balanced diet). Latent class analysis (LCA) was used to classify the subjects according to these categories. Associations between latent class and metabolic syndrome were assessed by logistic regression. Results The subjects were classified into three LCA-driven classes, including a referent class of healthy but unbalanced eaters (n = 118), a class of emotional eaters (n = 53), and a class of irregular unhealthy eaters (n = 88). Compared with the referent class, emotional eaters had a significantly higher BMI (beta = 3.40, P < 0.001) accompanied by metabolic syndrome (odds ratio 2.88, 95% confidence interval 1.16–7.13). Conclusions Our three LCA-driven obesity phenotypes could be useful for assessment and management of obesity and metabolic syndrome. The association between emotional eaters and higher BMI and metabolic syndrome was stronger than that with other eaters. Thus, emotional regulation strategies might have benefit for emotional eater’s diet.

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PMC1 CLASSIFYING PATIENTS WITH METABOLIC SYNDROME USING THE LATENT CLASS ANALYSIS (LCA)

Value in Health ◽

10.1016/s1098-3015(10)73154-5 ◽

2009 ◽

Vol 12 (3) ◽

pp. A19

Author(s):

G Liu ◽

N Luo ◽

PL McCollam

Keyword(s):

Metabolic Syndrome ◽

Latent Class Analysis ◽

Latent Class ◽

Class Analysis

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A latent class analysis of dietary behaviours associated with metabolic syndrome: a retrospective observational cross-sectional study

10.21203/rs.3.rs-40808/v1 ◽

2020 ◽

Author(s):

Jung Ha Park ◽

Ju Young Kim ◽

So Hye Kim ◽

Jung Hyun Kim ◽

Young Mi Park ◽

...

Keyword(s):

Metabolic Syndrome ◽

Body Mass Index ◽

Latent Class Analysis ◽

Body Mass ◽

Latent Class ◽

Eating Behaviour ◽

Dietary Behaviour ◽

Class Analysis ◽

Cross Sectional ◽

Dietary Behaviours

Abstract Background: Obesity defined solely by body mass index may not reflect the true heterogeneity of the obese population. This study aimed to classify the dietary behaviours of obese individuals and to explore the relationship between patterns of dietary behaviour and cardiometabolic risk factors. Methods: A total of 259 patients who visited an outpatient weight management clinic at a tertiary hospital and underwent a dietary behaviour assessment between January 2014 and February 2019 were enrolled in the study. Dietary behaviours were assessed in three domains with nine categories, including choice of food (frequently eating out, instant/fast/takeaway food), eating behaviour (irregular meals; frequent snacking, including eating at night; emotional eating; and overeating/binge eating), and nutrient intake (high-fat/high-calorie foods, salty food, and poorly balanced diet). Latent class analysis (LCA) was used to classify the subjects according to these categories. Associations between latent class and metabolic syndrome were assessed by logistic regression. Results: The subjects were classified into three LCA-driven classes, including a referent class of healthy eaters (n=118), a class of emotional eaters (n=53), and a class of irregular unhealthy eaters (n=88). Compared with the referent class, emotional eaters had a significantly higher body mass index (beta=3.40, P<0.001) accompanied by metabolic syndrome (odds ratio 2.88, 95% confidence interval 1.16–7.13). Conclusions: Our three LCA-driven obesity phenotypes could be useful for assessment and management of obesity and metabolic syndrome. The association between higher BMI and metabolic syndrome was stronger in emotional eaters than in healthy eaters and irregular unhealthy eaters. Emotional eaters might benefit from emotional regulation strategies.

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