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Impact of Future Obesity Trends in the Mexican Population: Development of a Computer Simulation Model

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Impact of Future Obesity Trends in the Mexican Population: Development of a Computer Simulation Model Impact of future obesity trends in the Mexican population: Development of a computer simulation model Luz María Sánchez Romero Thesis submitted to UCL for the Degree of Doctor of Philosophy Department of Epidemiology and Public Health UCL April 2017 1 Declaration of authorship I, Luz María Sánchez Romero confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Signature: ________________________ Date:_____________________________ 2 Abstract Introduction. Mexico is one of the top 10 countries with the highest prevalence of obesity worldwide. In 2012, 22 million Mexican adults were classified as obese. As a consequence, the country has seen an increase in morbidity and mortality from obesity-associated diseases that have impacted the country’s health and economy. Objective. To develop a computer simulation model that estimates future obesity prevalence and its impact on four cardiometabolic risk factors in the Mexican adult population aged 20-79y from 2015 to 2030. Methods. Using the best and most recent available Mexican data, I developed the Mexican Obesity Forecast Model (MexOb-Model), a population-based computer simulation model that is composed of two sub-models: 1) a linear trend model that projects future prevalence of obesity; and a 2) discrete-state Markov model that estimates the impacts of rising levels of obesity on morbidity and mortality from hypertension, type 2 diabetes, hypertriglyceridaemia and hypercholesterolaemia in the adult population. Additionally, I estimated the potential health benefits of three hypothetical obesity prevalence reduction scenarios. Results. If current trends continue, by 2030 there would be 48million obese adults (20─79y) in Mexico. The prevalence of hypertension, hypertriglyceridaemia and hypercholesterolaemia in the obese population would reach >50%, and 30% for diabetes. Decreasing the projected 2030 obesity prevalence by 3% would reduce the number of disease cases in the obese population by 150,000-500,000 and would reduce the number of deaths by 16,000-30,000. If Mexico achieved a bigger reduction in obesity levels, a 10% reduction in 2015 obesity prevalence by 2030, the number of disease cases avoided could be between 2 million and 7 million and total deaths reduce by nearly 500,000. Conclusion. The country’s prevalence of obesity, and obesity-related cardiometabolic risk factors, are expected to increase. A reduction of as little as 3% in the projected prevalence of obesity could result in a significant reduction in the health burden of obesity in Mexico. 3 Acknowledgements This PhD was a special life changing experience for me, which would have not been possible without the support of a number of people. I would like to thank my funders. The National Council for Science and Technology (CONACYT) “Consejo Nacional de Ciencia y Tecnología”, Mexico and the Mexican Ministry of Health’s Technical Committee for the Selection of International Scholars “Comité Técnico de Selección de Becarios Internacionales de la Secretaría de Salud” for providing the resources which allowed me to pursue this PhD. I would also like to express my profound appreciation to my PhD supervisors for their tremendous support. Not only, did they ensure the quality of my research, but also did they and pushed me to my limits, with great success Dr. Jennifer Mindell, Prof Jennifer Head and Dr. Shaun Scholes. In particular, I would like to thank: Dr. Jennifer Mindell for her guidance in the overall conceptualization of the thesis, for making me see my research in a different light and opened up a chance for further progression. Prof Jennifer Head for her invaluable feedback on the statistical techniques, her constructive suggestions shaped my research project. I am truly indebted and thankful to Dr. Shaun Scholes for all, his contributions, patience and time devoted to the conceptualization and his advice on writing this thesis. For keep my motivation up and teaching me the importance of keeping things simple. I owe my deepest gratitude to Dr. Ardo Van De Hout for his invaluable help with the calculation of the transition probabilities for the MexOb-Model. His support was a crucial part in this thesis and smoothed the way to my final model and results. Special thanks go to my office mates, for the invaluable support during hard times. It was a blessing to have around me such fun, bright and caring people with whom to share this wonderful experience. To my parents who always had my back and gave me the love and confidence that allowed me to accomplish this big step. 4 Finally, there is one person, without whom I would have not withstood this challenge, and whose words always kept me motivated: Andross, who always supported unconditionally my choice to come to London even though that meant being apart for four years, and who understands and embraces my dedication to my academic career. You played a huge part in fulfilling this dream and I cannot thank you enough for that. 5 Table of Contents Declaration of authorship ..................................................................................................... 2 Abstract ................................................................................................................................. 3 Acknowledgements ............................................................................................................... 4 List of Abbreviations ............................................................................................................ 22 Glossary ............................................................................................................................... 23 Chapter 1. Introduction ................................................................................................... 30 Background ........................................................................................................... 30 Obesity as a worldwide problem .......................................................................... 32 1.2.1 Obesity and its health consequences ............................................................ 33 Obesity in Mexico ................................................................................................. 35 1.3.1 Epidemiological and demographic transition ................................................ 35 1.3.2 Social and environmental determinants of obesity in Mexico ...................... 36 1.3.3 Obesity trends in Mexico ............................................................................... 38 1.3.4 Burden of disease associated with obesity in Mexico ................................... 39 Economic implications of obesity ......................................................................... 41 Goals ..................................................................................................................... 44 Aims & objectives ................................................................................................. 44 1.6.1 Aim ................................................................................................................ 44 1.6.2 Objectives ...................................................................................................... 44 Outline of the thesis ............................................................................................. 45 Chapter 2. Population-based health forecasting mathematical simulation models for obesity: Results of a systematic literature review. ............................................................. 46 Background ........................................................................................................... 46 2.1.1 Characteristics of mathematical models ....................................................... 46 Systematic literature review methods .................................................................. 49 6 2.2.1 Types of study ............................................................................................... 49 2.2.2 Type of participants ....................................................................................... 49 2.2.3 Type of interventions .................................................................................... 50 2.2.4 Type of outcome measures ........................................................................... 50 2.2.5 Studies excluded ............................................................................................ 51 Results .................................................................................................................. 52 2.3.1 Study populations .......................................................................................... 53 2.3.2 Modelling methods ....................................................................................... 54 2.3.3 Unit of analysis .............................................................................................. 56 2.3.4 Transparency and validation ......................................................................... 57 2.3.5 Length of projection period ........................................................................... 76 2.3.6 Obesity model outcomes ............................................................................... 77 2.3.7 Scenarios evaluated ....................................................................................... 79 Discussion ............................................................................................................
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