scholarly journals Developing a whole systems obesity classification for the UK Biobank Cohort

2020 ◽  
Author(s):  
Stephen Clark ◽  
Mark Birkin ◽  
Nik Lomax ◽  
Michelle Morris
Keyword(s):  
Physical Activity ◽  
Systems Approach ◽  
Multinomial Logistic Regression ◽  
Overweight And Obesity ◽  
Healthy Weight ◽  
Uk Biobank ◽  
Global Challenge ◽  
Effective Interventions ◽  
The Uk ◽  
Whole Systems

The number of people who are obese and overweight presents a global challenge, and the development of effective interventions is hampered by a lack of research which takes in to account a joined up, whole systems approach to understanding the drivers of the phenomena. We need to better understand the collective characteristics and behaviours of the overweight and obese population and how these differ from those who maintain a healthy weight. Using the UK Biobank cohort of 500 000 adults, we develop an obesity classification system using k-means clustering. Variable selection from UK Biobank is informed by the Foresight whole system obesity map across key domains (Societal Influences, Individual Psychology, Individual Physiology, Individual Physical Activity, Physical Activity Environment). This paper presents the first study of UK Biobank participants to adopt this whole systems approach. Our classification identifies six groups of people, similar in respect to their exposure to known drivers of obesity: ‘Younger, active and working hard’, ‘Retirees with good lifestyle’ , ‘Stressed, sedentary and struggling’, Older with poor lifestyle’, ‘Younger, busy professionals’ and ‘Younger, fitter families’. Pen portraits are developed to describe the characteristics of these different groups. Multinomial logistic regression is used to demonstrate that the classification can effectively detect groups of individuals more likely to be overweight or obese. The group identified as ‘Younger, fitter families’ are observed to have a higher proportion of healthy weight, while three groups have increased relative risk of being overweight or obese: ‘Younger, active and working hard’, ‘Stressed, sedentary and struggling’ and ‘Older with poor lifestyles’. This work presents an innovative new approach to better understand the whole systems drivers of obesity which has the potential to produce meaningful tools for policy makers to better target interventions across the whole system to reduce overweight and obesity.

scholarly journals Can a data driven obesity classification system identify those at risk of severe COVID-19 in the UK Biobank cohort study?

2020 ◽  
Author(s):  
Stephen Clark ◽  
Mark Birkin ◽  
Nik Lomax ◽  
Michelle Morris
Keyword(s):  
Short Communication ◽  
Systems Approach ◽  
Large Degree ◽  
Uk Biobank ◽  
Individual Level ◽  
Research Initiative ◽  
The Uk ◽  
Degree Of Differentiation ◽  
Test Outcomes ◽  
Whole Systems

In this short communication we demonstrate how an individual level classification built using a Whole Systems approach to an understanding of obesity can be used to profile individual’s exposure, treatment and mortality for COVID-19. The cohort is the UK Biobank and the information on COVID-19 test outcomes, hospitalisations and mortality are provided as part of this research initiative. We find that the cohort profiles accurately against the understood heightened risk factors for COVID-19, namely age, gender, ethnicity, obesity and deprivation. This confidence in these data then allows us to profile the participants in each of the classification clusters for these COVID-19 outcomes. We see that there is a large degree of differentiation between the classes. The article finishes by highlighting how this classification can help in prioritising care, treatments and vaccine delivery.

The Amsterdam Healthy Weight Approach: A whole systems approach for tackling child obesity in cities

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
K den Hertog ◽  
V Busch
Keyword(s):  
Public Health ◽  
Success Factors ◽  
Systems Approach ◽  
Health Sector ◽  
Child Obesity ◽  
Overweight And Obesity ◽  
Lessons Learned ◽  
Healthy Weight ◽  
Healthy Environment ◽  
Whole Systems

Abstract In search for successful overweight and obesity prevention, extensive research has shown that programs focused on individual behavior change are not effective enough. Many of the underlying determinants of overweight and obesity have social, environmental and economic origins, and extend even beyond the influence of the health sector and public health. This calls for a whole systems approach that covers a multi-sectoral, multi-stakeholder collaboration, where communities, professionals, government and industry are involved and are all part of the solution. The Amsterdam Healthy Weight Approach (AHWA), initiated in 2012, is a local government led approach that has the objective to encourage healthy weight for children in a healthy environment. With a long-term vision, aimed at lasting change, the AHWA aims at developing interventions, changing policies and educating and informing both professionals and target groups within the communities that are most heavily burdened with the issue of child obesity (and related complex health/wellbeing issues). The strength of the AHWA lies in adopting a whole systems approach (WSA), in which the key is, to collaborate in an integrated, multi-level, multi sectoral way, with a variety of stakeholders from within and outside the field of public health. The aim of the presentation is to inform participants from cities around the globe about the success factors, lessons learned and valuable elements of implementing the AHWA, and to provide tools which they can use in discussing their own approaches and bring these to a higher level of effectiveness

scholarly journals Association Between Dietary Consumption, Anthropometric Measures And Body Composition Of Rural And Urban Ghanaian Adults; A Comparative Cross Sectional Study.

2019 ◽  
Author(s):  
Nana Ama Frimpomaa Agyapong ◽  
Reginald Adjetey Annan ◽  
Charles Apprey ◽  
Linda Nana Esi Aduku ◽  
Catherina Elizabeth Swart
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Multinomial Logistic Regression ◽  
Overweight And Obesity ◽  
P Value ◽  
Obesity Prevalence ◽  
Anthropometric Measures ◽  
Cross Sectional ◽  
Dietary Consumption ◽  
Rural And Urban

Abstract Background: Overweight and obesity have become threats to public health in all regions across the globe. Policies to regulate the food environment and promote healthy food consumption can reduce the prevalence obesity but in Ghana there is not enough data to elicit a policy response. This study assessed the association between dietary consumption, anthropometric measures, body composition and physical activity among rural and urban Ghanaian adults. Methods: This was a cross-sectional study involving 565 Ghanaian adults. Structured questionnaires were used to collect socio-demographic information. Dietary consumption was assessed using household food frequency questionnaire and 24-hour recall. Height, weight, BMI, waist circumference and body composition of all participants were also measured. The World Health Organization’s Global Physical Activity Questionnaire (GPAQ) was used to assess physical activity levels. Mann Whitney U test was used to analyze differences in anthropometric measurements, body composition and dietary consumption among rural and urban participants. Principal component analysis was used to analyze household food frequency data and nutrient analysis template was used to analyze 24-hour recall. Chi-square was used to measure differences in obesity prevalence by community and gender. Multinomial logistic regression was used to model the risk factors associated with obesity. Results: The prevalence of overweight and obesity using BMI were 29.9 and 22.9 respectively. The use of waist circumference measurement resulted in the highest overall obesity prevalence of 41.5%. Prevalence of obesity was higher among females compared to males across all measures with the exception of visceral fat that showed no significant difference. Four different patterns were derived from principal component analysis. Among urban participants, component 3 (staple pattern) showed a significant negative correlation with visceral fat (r -0.186, p-value 0.013) and BMI (r -0.163, p-value 0.029). Multinomial logistic regression showed that males (AOR 19.715, CI 9.723-39.978, p-value < 0.001) had higher odds of being of normal weight compared to females. Conclusion: Prevalence of overweight and obesity continue to rise in Ghana, especially among females. Public education and screening as well as interventions that regulate the food environment and make affordable and available healthy food options are needed to control the rise in obesity prevalence.

scholarly journals The Validity and Value of Self-reported Physical Activity and Accelerometry in People With Schizophrenia: A Population-Scale Study of the UK Biobank

2017 ◽  
Vol 44 (6) ◽  
pp. 1293-1300 ◽  
Author(s):  
Joseph Firth ◽  
Brendon Stubbs ◽  
Davy Vancampfort ◽  
Felipe B Schuch ◽  
Simon Rosenbaum ◽  
...  
Keyword(s):  
Physical Activity ◽  
Uk Biobank ◽  
Population Scale ◽  
The Uk

Relationships between physical activity, food choices, gender and BMI in Southern Californian teenagers

2017 ◽  
Vol 31 (5) ◽  
Author(s):  
Jaclyn B. Gaylis ◽  
Susan S. Levy ◽  
Shiloah Kviatkovsky ◽  
Rebecca DeHamer ◽  
Mee Young Hong
Keyword(s):  
Physical Activity ◽  
Healthy Lifestyle ◽  
Food Choices ◽  
Cross Sectional Study ◽  
Red Meat ◽  
Overweight And Obesity ◽  
Healthy Food ◽  
Processed Meat ◽  
Healthy Weight ◽  
Cross Sectional

Abstract Given the increased prevalence of pediatric obesity and risk of developing chronic disease, there has been great interest in preventing these conditions during childhood by focusing on healthy lifestyle habits, including nutritious eating and physical activity (PA). The purpose of this study was to determine the relationship between PA, body mass index (BMI) and food choices in adolescent males and females. This cross-sectional study, using a survey questionnaire, evaluated 1212 Southern Californian adolescents’ self-reported PA, BMI and food frequency. Results revealed that even though males are more active than females, they have higher BMI percentile values (p < 0.05). Females consumed salad, vegetables and fruit more frequently than males (p < 0.05), where males consumed hamburgers, pizza, red meat, processed meat, eggs, fish, fruit juice, soda and whole milk more frequently than females (p < 0.05). Overweight/obese teens consumed red meat, processed meat and cheese more frequently than healthy weight teens (p < 0.05), yet there was no difference in PA between healthy and overweight/obese teens. These results demonstrate that higher levels of PA may not counteract an unhealthy diet. Even though PA provides numerous metabolic and health benefits, this study suggests that healthy food choices may have a protective effect against overweight and obesity. Healthy food choices, along with PA, should be advocated to improve adolescent health by encouraging maintenance of a healthy weight into adulthood.

Associations of BMI and Serum Urate with Developing Dementia: A Prospective Cohort Study

2020 ◽  
Vol 105 (12) ◽  
pp. e4688-e4698
Author(s):  
Zhi Cao ◽  
Chenjie Xu ◽  
Hongxi Yang ◽  
Shu Li ◽  
Fusheng Xu ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Cohort Study ◽  
Lower Risk ◽  
Serum Urate ◽  
Healthy Weight ◽  
Uk Biobank ◽  
Health Records ◽  
Increased Risk ◽  
The Uk

Abstract Context Recent studies have suggested that a higher body mass index (BMI) and serum urate levels were associated with a lower risk of developing dementia. However, these reverse relationships remain controversial, and whether serum urate and BMI confound each other is not well established. Objectives To investigate the independent associations of BMI and urate, as well as their interaction with the risk of developing dementia. Design and Settings We analyzed a cohort of 502 528 individuals derived from the UK Biobank that included people aged 37–73 years for whom BMI and urate were recorded between 2006 and 2010. Dementia was ascertained at follow-up using electronic health records. Results During a median of 8.1 years of follow-up, a total of 2138 participants developed dementia. People who were underweight had an increased risk of dementia (hazard ratio [HR] = 1.91, 95% confidence interval [CI]: 1.24–2.97) compared with people of a healthy weight. However, the risk of dementia continued to fall as weight increased, as those who were overweight and obese were 19% (HR = 0.81, 95%: 0.73–0.90) and 22% (HR = 0.78, 95% CI: 0.68–0.88) were less likely to develop dementia than people of a healthy weight. People in the highest quintile of urate were also associated with a 25% (HR = 0.75, 95% CI: 0.64–0.87) reduction in the risk of developing dementia compared with those who were in the lowest quintile. There was a significant multiplicative interaction between BMI and urate in relation to dementia (P for interaction = 0.004), and obesity strengthens the protective effect of serum urate on the risk of dementia. Conclusion Both BMI and urate are independent predictors of dementia, and there are inverse monotonic and dose-response associations of BMI and urate with dementia.

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