Analyses for the association between Business travel and BMI Public

Abstract

Background: Employees are traveling more as part of their work nowadays. Traveling can add stress and represents a challenge to maintaining healthy habits. Crossing time zones poses additional risks of jet lag and circadian rhythm disruption. Numerous research studies show that business travelers have a higher probability of contracting infections. However, only a few studies have assessed the noninfectious outcomes associated with business travel. In this study, we focused on the health risks associated with high-frequent business travel (domestic, international travel, as well the combination of two types), and assessed the specific association between business travel frequency and BMI/obesity.

Methods: A total of 795 executives that were seen at Emory Executive Health between January 2017 and June 2018 were examined in this retrospective study. Summary statistics of demographic and lifestyle characteristics are presented overall and by gender. Univariate associations with travel frequencies (in two ways: continuous, four categories, three types: domestic, international, combination) and BMI outcomes (in three ways: continuous, Binary Obesity, Multilevel Obesity) were conducted. Univariate and multivariable analyses using multinomial logistic regression model, cumulative logit model and linear regression model assessed the specific association between travel frequency and BMI (continuous, Binary Obesity, Multilevel Obesity). Further, multinomial logistic regression model, cumulative logit model and linear regression model were compared to give a recommendation for future studies.

Conclusion: International travel frequency had a significant effect on BMI (continuous or Multilevel Obesity) among males. Specifically, the health outcomes were worse for those not travelling, travelling seldomly and those traveling extensively (more than 13 times per month in this study). In other words, the BMI displayed a U-shaped pattern of associations with the business travel frequency. In addition, among three modeling methods, multinomial logistic regression models performed best for assessing the specific association between travel frequency and BMI (Multilevel Obesity). 

Table of Contents

1. INTRODUCTION 1

2. MATERIALS AND METHODS 3

2.1 DATA COLLECTION 3

2.2 DATA ORGANIZATION 4

2.2.1 Data Cleaning 4

2.2.2 Data Merging 8

2.3 STATISTICAL METHODS 9

2.3.1 Descriptive Analysis 10

2.3.2 Univariate Associations with primary exposures/outcomes 10

2.3.3 Univariate Analysis for Multilevel Obesity and Categorical Travel Frequency 11

2.3.4 Univariate Analysis for BMI and Continuous Travel Frequency 14

2.3.5 Multivariable Analysis for Multilevel Obesity and Categorical Travel Frequency 15

2.3.6 Multivariable Analysis for BMI and Continuous Travel Frequency 16

3. RESULTS 16

3.1 DESCRIPTIVE STATISTICS 17

3.2 UNIVARIATE ASSOCIATIONS WITH PRIMARY EXPOSURES/OUTCOMES 25

3.2.1 Univariate Associations with categorical travel frequencies 25

3.2.2 Univariate Associations with continuous travel frequencies 26

3.2.3 Univariate Associations with BMI (continuous, Binary Obesity, Multilevel Obesity) 28

3.3 UNIVARIATE ANALYSIS FOR MULTILEVEL OBESITY AND CATEGORICAL TRAVEL FREQUENCY 30

3.3.1 Multinomial Regression Model 30

3.3.2 Cumulative Logit Model 34

3.4 UNIVARIATE ANALYSIS FOR BMI AND CONTINUOUS TRAVEL FREQUENCY 36

3.5 MULTIVARIABLE ANALYSIS FOR MULTILEVEL OBESITY AND CATEGORICAL TRAVEL FREQUENCY 37

3.5.1 Multinomial Regression Model 38

3.5.2 Cumulative Logit Model 42

3.6 MULTIVARIABLE ANALYSIS FOR BMI AND CONTINUOUS TRAVEL FREQUENCY 46

4. DISCUSSION 47

4.1 LIMITATIONS 49

4.1.1 Data Source 49

4.1.2 Regression Models 50

4.2 FUTURE RESEARCH 52

4.3 CONCLUSIONS 53

5. REFERENCES/BIBLIOGRAPHY 54

6. APPENDIX 55

6.1 SAS CODE FOR DATA PREPROCESSING 55

6.2 SAS CODE FOR DATA ANALYSIS 66

About this Master's Thesis

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School	Rollins School of Public Health
Department	Biostatistics
Subfield / Discipline	Biostatistics - MPH & MSPH
Degree	M.P.H.
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Public Health
Mot-clé	travel frequency obesity multinomial logistic regression cumulative logit model BMI
Committee Chair / Thesis Advisor	Reneé H. Moore, Emory University
Committee Members	Sharon Bergquist , Emory University Michele Marcus , Emory University

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