BMI trajectories in middle to old age: methodological developments, missing data and cost-effectiveness

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The UK's aging population and increasing obesity prevalence are two of the most significant public health challenges. Currently, more than 3 million people aged 80 years and over live in the UK, and this figure is projected to exceed 8 million by 2050 at increasing costs to the Department of Work and Pensions and the National Health Service. Obesity rates have almost trebled in the last 30 years at a cost of over £3 billion a year and, if forecasting is correct, over half our population will be obese by 2050. Significant obesity related co-morbidities (e.g. diabetes, osteoarthritis, cardiovascular disease), coupled with multiple health problems associated with aging (e.g. Alzheimer's disease, arthritis and cancer), places older people at significant risk. While there is a focus on obesity research in young people and the general adult population, there is relatively little research into how obesity develops into old age and the consequences of obesity in older adults. It is useful to predict BMI trajectories in patients with different characteristics in order to inform public health policies. If predictions can be made for a patient's future BMI, then these long-term estimates can be used in economic models in order to estimate how cost-effective potential interventions, actions or policies are expected to be. For policy purposes, it is critical to understand how these effects develop over time, and longitudinal analyses are relied upon to provide these long-term predictions. A number of cost-effectiveness analyses have used BMI trajectories, including models for diabetes. Previous research has investigated mean BMI trajectories and has shown that they differ as patients go from middle age to older age. However, it is well known that obesity prevalence and BMI differ between different social groups and that an individual's environment can have a large influence on their weight. This project will identify different groups of individuals who are likely to experience different types of BMI trajectories. Medical literature suggests that there are certain types of individual who are more likely to see a drop in BMI as they enter old age, known as the 'obesity paradox' because BMI drops but body fat percentage increases. In this group of people, BMI might be misleading and measures of muscle mass (such as grip strength) could be an important in identifying individuals with similar BMI trajectories but different risks of obesity. These different trajectories will also be linked with long term health outcomes, including a range of diseases and death. Missing data can be a particular problem when researching the elderly due to illness, memory loss and access to individuals in care homes. This could mean that in a sample of individuals over the age of 50 years, more elderly individuals are under-represented. In order to account for the potential underrepresentation of certain individuals, analysis should account for missing data and this study will investigate the influence that missing data might have on estimated BMI trajectories.The study will use data from the English Longitudinal Study of Aging (ELSA) and the analysis described above will provide more detailed evidence for health care professionals helping to identify those most at risk of morbidities and mortality by the BMI trajectories that they are expected to follow. The results will also be used to inform cost-effectiveness analyses, which can help policy makers to determine the most cost-effective interventions to help improve the health of future generations as they enter old age. I will use a diabetes prevention model as a case study, to illustrate how potential diabetes prevention interventions might influence patients with different characteristics and to demonstrate the impact that missing data could have on policy if it remained unaccounted for.