Adaptive multi-task Positive-Unlabeled learning for joint prediction of multiple chronic diseases using online shopping behaviors

2021 ◽  
pp. 116232
Author(s):  
Yongzhen Wang ◽  
Jun Lin ◽  
Sheng Bi ◽  
Changlong Sun ◽  
Luo Si ◽  
...  
Keyword(s):  
Chronic Diseases ◽  
Online Shopping ◽  
Joint Prediction ◽  
Multiple Chronic Diseases

scholarly journals Prevalence of Multimorbidity of Chronic Noncommunicable Diseases in Brazil: Population-Based Study (Preprint)

2021 ◽  
Author(s):  
Xin Shi ◽  
Simone Maria da Silva Lima ◽  
Caroline Maria de Miranda Mota ◽  
Ying Lu ◽  
Randall S Stafford ◽  
...  
Keyword(s):  
Chronic Diseases ◽  
Household Survey ◽  
Well Being ◽  
National Sample ◽  
Population Based ◽  
Community Services ◽  
Noncommunicable Diseases ◽  
Subjective Well Being ◽  
Cross Sectional ◽  
Multiple Chronic Diseases

BACKGROUND Multimorbidity is the co-occurrence of two or more chronic diseases. OBJECTIVE This study, based on self-reported medical diagnosis, aims to investigate the dynamic distribution of multimorbidity across sociodemographic levels and its impacts on health-related issues over 15 years in Brazil using national data. METHODS Data were analyzed using descriptive statistics, hypothesis tests, and logistic regression. The study sample comprised 679,572 adults (18-59 years of age) and 115,699 elderly people (≥60 years of age) from the two latest cross-sectional, multiple-cohort, national-based studies: the National Sample Household Survey (PNAD) of 1998, 2003, and 2008, and the Brazilian National Health Survey (PNS) of 2013. RESULTS Overall, the risk of multimorbidity in adults was 1.7 times higher in women (odds ratio [OR] 1.73, 95% CI 1.67-1.79) and 1.3 times higher among people without education (OR 1.34, 95% CI 1.28-1.41). Multiple chronic diseases considerably increased with age in Brazil, and people between 50 and 59 years old were about 12 times more likely to have multimorbidity than adults between 18 and 29 years of age (OR 11.89, 95% CI 11.27-12.55). Seniors with multimorbidity had more than twice the likelihood of receiving health assistance in community services or clinics (OR 2.16, 95% CI 2.02-2.31) and of being hospitalized (OR 2.37, 95% CI 2.21-2.56). The subjective well-being of adults with multimorbidity was often worse than people without multiple chronic diseases (OR=12.85, 95% CI: 12.07-13.68). These patterns were similar across all 4 cohorts analyzed and were relatively stable over 15 years. CONCLUSIONS Our study shows little variation in the prevalence of the multimorbidity of chronic diseases in Brazil over time, but there are differences in the prevalence of multimorbidity across different social groups. It is hoped that the analysis of multimorbidity from the two latest Brazil national surveys will support policy making on epidemic prevention and management.

BIOBOARD

2018 ◽  
Vol 22 (03) ◽  
pp. 53-57
Keyword(s):  
Mental Disorders ◽  
Drug Development ◽  
Blood Sugar ◽  
Chronic Diseases ◽  
International Collaboration ◽  
Translational Medicine ◽  
Therapeutic Treatment ◽  
Bay Area ◽  
Multiple Chronic Diseases

ASIA – The first Greater Bay Area biotechnology and translational medicine international collaboration. ASIA – New insight on therapeutic treatment for mental disorders. OCEANIA – Multiple chronic diseases leave patients with adversely high costs. AMERICAS – Measuring the risks and rewards of drug development. AMERICAS – Ketone drink could help diabetics by lowering blood sugar.

Physical Activity and Sitting Time Are Specifically Associated With Multiple Chronic Diseases and Medicine Intake in Brazilian Older Adults

2018 ◽  
Vol 26 (4) ◽  
pp. 608-613 ◽  
Author(s):  
Alex S. Ribeiro ◽  
Luiz C. Pereira ◽  
Danilo R.P. Silva ◽  
Leandro dos Santos ◽  
Brad J. Schoenfeld ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Chronic Diseases ◽  
Physical Inactivity ◽  
Prevalence Ratio ◽  
Sitting Time ◽  
Older Individuals ◽  
Independent Association ◽  
Older Men And Women ◽  
Multiple Chronic Diseases

The purpose of the study was to clarify the independent association between sedentary behavior and physical activity with multiple chronic diseases and medicine intake in older individuals. Sedentary behavior and physical activity were measured by questionnaires. Diseases and medication use were self-reported. Poisson’s regression was adopted for main analysis, through crude and adjusted prevalence ratio and confidence interval of 95%. For men, sedentary time >4 hr/day presented a 76% higher prevalence of ≥2 chronic diseases, while physical inactivity increases the likelihood of using ≥2 medicines in 95%. For women, sedentary behavior >4 hr/day presented an 82% and 43% greater prevalence for ≥2 chronic diseases and the intake of ≥2 medicines, respectively. Sedentary behavior represents an independent associated factor of multiple chronic diseases in older men and women. In addition, inactivity for men and sedentarism for women are associated with the amount of medicine intake.

Modeling Chronic Diseases in Relation to Risk Factors

2019 ◽  
Author(s):  
Pieter van Baal ◽  
Hendriek Boshuizen
Keyword(s):  
Risk Factors ◽  
Simulation Model ◽  
Chronic Diseases ◽  
Simulation Modeling ◽  
Disease Modeling ◽  
Healthcare Spending ◽  
Communicable Diseases ◽  
Future Research ◽  
Non Communicable Diseases ◽  
Multiple Chronic Diseases

In most countries, non-communicable diseases have taken over infectious diseases as the most important causes of death. Many non-communicable diseases that were previously lethal diseases have become chronic, and this has changed the healthcare landscape in terms of treatment and prevention options. Currently, a large part of healthcare spending is targeted at curing and caring for the elderly, who have multiple chronic diseases. In this context prevention plays an important role, as there are many risk factors amenable to prevention policies that are related to multiple chronic diseases. This article discusses the use of simulation modeling to better understand the relations between chronic diseases and their risk factors with the aim to inform health policy. Simulation modeling sheds light on important policy questions related to population aging and priority setting. The focus is on the modeling of multiple chronic diseases in the general population and how to consistently model the relations between chronic diseases and their risk factors by combining various data sources. Methodological issues in chronic disease modeling and how these relate to the availability of data are discussed. Here, a distinction is made between (a) issues related to the construction of the epidemiological simulation model and (b) issues related to linking outcomes of the epidemiological simulation model to economic relevant outcomes such as quality of life, healthcare spending and labor market participation. Based on this distinction, several simulation models are discussed that link risk factors to multiple chronic diseases in order to explore how these issues are handled in practice. Recommendations for future research are provided.

scholarly journals A Qualitative Interpretation of Challenges Associated with Helping Patients with Multiple Chronic Diseases Identify Their Goals

2016 ◽  
Vol 6 (2) ◽  
pp. 120-126 ◽  
Author(s):  
Pauline Boeckxstaens ◽  
Sara Willems ◽  
Mieke Lanssens ◽  
Charlotte Decuypere ◽  
Guy Brusselle ◽  
...  
Keyword(s):  
Chronic Diseases ◽  
Goal Setting ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Chronic Obstructive ◽  
Personal Goals ◽  
Obstructive Pulmonary Disease ◽  
Clinical Method ◽  
The Individual ◽  
Multiple Chronic Diseases

Background Patients with multiple chronic diseases are usually treated according to disease-specific guidelines, with outcome measurements focusing mostly on biomedical indicators (e.g. blood sugar levels or lung function). However, for multimorbidity, a goal-oriented approach focusing on the goals defined by the individual patient, may be more suitable. Despite the clear theoretical and conceptual advantages of including patient-defined goals in clinical decision-making for multimorbidity, it is not clear how patients define their goals and which aspects play a role in the process of defining them. Objective To explore goal-setting in patients with multimorbidity. Design Qualitative analysis of interviews with 19 patients diagnosed with chronic obstructive pulmonary disease and comorbidities. Results Patients do not naturally present their goals. Their goals are difficult to elicit, even when different interviewing techniques are used. Four underlying hypotheses which may explain this finding were identified from the interviews: (1) patients cannot identify with the concept of goal-setting; (2) goal-setting is reduced due to acceptation; (3) actual stressors predominate over personal goal-setting; and (4) patients may consider personal goals as selfish. Conclusions Our findings advocate for specific attention to provider skills and strategies that help patients identify their personal goals. The hypotheses on why patients may struggle with defining goals may be useful to prompt patients in this process and support the development of a clinical method for goal-oriented care.

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