770 research outputs found
A command for fitting mixture regression models for bounded dependent variables using the beta distribution
In this article, we describe the betamix command, which fits mixture regression models for dependent variables bounded in an interval. The model is a generalization of the truncated inflated beta regression model introduced in Pereira, Botter, and Sandoval (2012, Communications in Statistics—Theory and Methods 41: 907-919) and the mixture beta regression model in Verkuilen and Smithson (2012, Journal of Educational and Behavioral Statistics 37: 82-113) for variables with truncated supports at either the top or the bottom of the distribution. betamix accepts dependent variables defined in any range that are then transformed to the interval (0, 1) before estimation
BMI trajectories and the influence of missing data
31st European Congress on Obesity (ECO 2024) : Meeting Reports / Abstract
The importance of missing data in estimating BMI trajectories
Body Mass Index (BMI) trajectories are important for understanding how BMI develops over time. Missing data is often stated as a limitation in studies that analyse BMI over time and there is limited research exploring how missing data influences BMI trajectories. This study explores the influence missing data has in estimating BMI trajectories and the impact on subsequent analysis. This study uses data from the English Longitudinal Study of Ageing. Distinct BMI trajectories are estimated for adults aged 50 years and over. Next, multiple methods accounting for missing data are implemented and compared. Estimated trajectories are then used to predict the risk of developing type 2 diabetes mellitus (T2DM). Four distinct trajectories are identified using each of the missing data methods: stable overweight, elevated BMI, increasing BMI, and decreasing BMI. However, the likelihoods of individuals following the different trajectories differ between the different methods. The influence of BMI trajectory on T2DM is reduced after accounting for missing data. More work is needed to understand which methods for missing data are most reliable. When estimating BMI trajectories, missing data should be considered. The extent to which accounting for missing data influences cost-effectiveness analyses should be investigated
Evidence for central obesity risk-related thresholds for adolescents aged 11 to 18 years in England using the LMS method
Introduction
Central obesity has been shown to better indicate health risks compared to general obesity. Measures of central obesity include waist-to-height ratio (WHtR), waist-to-hip ratio (WHR) and waist circumference (WC). The National Institute of Health and Care Excellence (NICE) recently recommended the use of WHtR alongside body mass index (BMI) to identify risks in adults and children, whilst recognising the need for more evidence relating to WHtR in children. This study explores risk thresholds for central obesity measures throughout adolescence. It compares these with those currently recommended in England and discusses whether these thresholds are age- and sex-specific.
Methods
Data on adolescents aged 11 to 18 years from the Health Survey for England (HSE) during 2005 to 2014 was used to calculate WHtR, WHR and WC percentiles. Next, smoothed lambda-mu-sigma (LMS) curves were created and the percentiles which align with the adult thresholds at age 18 years identified. This allows the most appropriate risk related thresholds for each measure during adolescence to be determined.
Results
WHtR LMS curves are stable and flat throughout adolescence. WHR decreases in girls and WC increases in both boys and girls, during adolescence. Across all measures, there is slightly more fluctuation in higher percentiles, and in girls’ WHR.
Discussion
In practice, WHtR thresholds are simple to use to identify central obesity related risks. In particular, they are recommended because the same thresholds can be used for males and females and for adolescents and adults. The results support NICE guidance to use WHtR thresholds alongside BMI thresholds to identify individual risk.
Implications and contribution
This study uses central obesity measures, including waist-to-height and waist-to-hip ratios, to investigate risk-related thresholds for adolescents. It is the first to do so using English data. It provides support for current NICE recommendations to use adult waist-to-height thresholds in adults and children, alongside BMI measures in clinical and non-clinical settings
Development of methods for the mapping of utilities using mixture models: An application to asthma
Objectives:
To develop methods for mapping to preference-based measures using mixture model approaches. These methods are compared to map from the Asthma Quality of Life Questionnaire (AQLQ) to both EQ5D-5L and HUI-3 as the target health utility measures in an international dataset.
Methods:
Data from 856 patients with asthma collected as part of the Multi-Instrument Comparison (MIC) international project were used. Adjusted limited dependent variable mixture models (ALDVMMs) and beta-regression based mixture models were estimated. Optional inclusion of the gap between full health and the next value, and a mass point at the next feasible value were explored. Response-mapping could not be implemented due to missing data.
Results:
In all cases, model specifications which formally modelled the gap between full health and the next value were an improvement on those which did not. Mapping to HUI3 required more components in the mixture models than mapping to EQ5D-5L due to its uneven distribution. The optimal beta-based mixture models mapping to HUI3 included a probability mass at the utility value adjacent to full health. This is not the case when estimating EQ5D-5L, due to the low proportion of observations at this point.
Conclusion:
The beta-based mixture models marginally outperformed ALDVMM in this dataset when comparing models with the same number of components. This is at the expense of requiring a larger number of parameters and estimation time. Both model types are able to closely fit the data without biased characteristic of many mapping approaches. Skilled judgment is critical in determining the optimal model. Caution is required in ensuring a truly global maximum likelihood has been identified
Family Lifestyle Dynamics and Childhood Obesity: Evidence from the Millennium Cohort Study
Using data from the Millennium Cohort Study, we investigate the dynamic relationship between underlying family lifestyle and childhood obesity during early childhood. We use a dynamic latent factor model, an approach that allows us to identify family lifestyle, its evolution over time and its influence on childhood obesity and other observable outcomes. We find that family lifestyle is persistent and has a significant influence on childhood weight status as well as other outcomes for all family members. Interventions should therefore be prolonged and persuasive and target the underlying lifestyle of a family as early as possible during childhood in order to have the greatest cumulative influence. Furthermore, the results indicate that to reduce inequalities in childhood obesity, policy makers should target disadvantaged families and design interventions specifically for these families
Understanding the role of the primary somatosensory cortex: Opportunities for rehabilitation.
Emerging evidence indicates impairments in somatosensory function may be a major contributor to motor dysfunction associated with neurologic injury or disorders. However, the neuroanatomical substrates underlying the connection between aberrant sensory input and ineffective motor output are still under investigation. The primary somatosensory cortex (S1) plays a critical role in processing afferent somatosensory input and contributes to the integration of sensory and motor signals necessary for skilled movement. Neuroimaging and neurostimulation approaches provide unique opportunities to non-invasively study S1 structure and function including connectivity with other cortical regions. These research techniques have begun to illuminate casual contributions of abnormal S1 activity and connectivity to motor dysfunction and poorer recovery of motor function in neurologic patient populations. This review synthesizes recent evidence illustrating the role of S1 in motor control, motor learning and functional recovery with an emphasis on how information from these investigations may be exploited to inform stroke rehabilitation to reduce motor dysfunction and improve therapeutic outcomes
Site assessment of Douglas Shoal ship grounding in the Great Barrier Reef
The bulk carrier Shen Neng 1 ran aground on Douglas Shoal in the Great Barrier Reef Marine Park in April 2010. At over 40 hectares, this is the largest ship grounding scar known in the Great Barrier Reef, and possibly the largest reef-related grounding in the world. Challenges for assessment of the site included its large scale and the remote nature of Douglas Shoal coupled with its high exposure to wind, wave conditions and fauna that may pose safety hazards. Marine surveys used multiple and novel methods including sediment sampling combined with visual and acoustic survey techniques
Mapping the FACT-B instrument to EQ-5D-3L in patients with breast cancer using adjusted limited dependent variable mixture models versus response mapping
Objectives
Preference based measures (PBMs) of health, such as EQ-5D-3L, are required to calculate QALYs for use in cost-effectiveness analysis, but are often not recorded in clinical studies. In these cases, mapping can be used to estimate PBMs. We model the relationship between EQ-5D-3L and Functional Assessment of Cancer Therapy - Breast Cancer (FACT-B), comparing indirect and direct mapping methods, and the use of FACT-B summary score verses subscale scores.
Methods
We use data from 3 clinical studies for advanced breast cancer providing 11,958 observations with full information on FACT-B and EQ-5D-3L. We compare direct mapping using adjusted limited dependent variable mixture models (ALDVMMs) with indirect mapping using seemingly unrelated ordered probit models. EQ-5D-3L was estimated as a function of FACT-B and other patient related covariates.
Results
The use of FACT-B subscales was better than using total FACT-B score. A good fit to the observed data was observed across the range of disease severity in all models. ALDVMMs outperform the indirect mapping. The breast cancer specific scale significantly predicts EQ-5D-3L and this subscale has large influences on pain and self-care dimensions of EQ-5D-3L.
Conclusion
This paper adds to the growing literature that demonstrates the performance of the ALDVMM method for mapping. Regardless of which model is used, the subscales of FACT-B should be included as independent variables wherever possible. The breast cancer specific subscales of FACT-B are important in predicting EQ-5D-3L. This suggests that generic cancer measures should not be used for utility mapping in patients with breast cancer
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