scholarly journals Fuzzy Epidemiology: Measures for Observational Epidemiological Studies

2020 ◽  
Author(s):  
Ana Cláudia Oliveira Melo ◽  
Laisa Ribeiro de Sá ◽  
Rodrigo Pinheiro de Toledo Vianna ◽  
Ronei Marcos de Moraes
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Observational Studies ◽  
Risk Measures ◽  
Possibility Theory ◽  
Epidemiological Studies ◽  
Case Control ◽  
Case Scenario ◽  
Fuzzy Measures ◽  
Study Population

Abstract Background Epidemiological studies bring forth classic epidemiological measures calculation that are based on resulting quantities of dichotomic categorization of individuals, such as in events: diseased, non-diseased, exposed or unexposed. Dichotomic categorizations discard inherent uncertainties and subjectivities from the illness process the exposure which generate information losses on the measures. The fuzzy set theory categorizes each individual, allowing the soft transit amongst the events and considering the uncertainties and subjectivities. For the calculation of these measures, the fuzzy possibility theory is useful. Although there is already the proposition of making use of this methodology to the calculation of association and risk measures, there are no additional studies, in the literature, that characterize or apply the measures in epidemiological studies. Neither there are proposed calculations of other epidemiological measures or studies explaining the contribution of the resulting epidemiological measure of this methodology. This paper aims to increase the epidemiological measures sets to observational studies, using fuzzy set and possibility theories in the calculation of the denominated fuzzy epidemiological measures, featuring them in an original way.Methodology The proposed fuzzy measures were based in classic epidemiological measures. An observational study was simulated on a case-control type and fuzzy theories on the categorization of the individuals and for the calculation of fuzzy measures were applied. The simulations and calculations were performed by the software R.Results It was graphically observed the incorporation of uncertainties and subjectivities in the study population categorization. Comparing the classic to the fuzzy measures, it was observed that the contribution of the embedded uncertainties and subjectivities on the fuzzy measure presented a more complete final information about the illness process and exposure of the individuals. The graphic behavior of the proposed measures and of the already existent ones were characterized.Conclusion The fuzzy set epidemiological measures changes the paradigm of measures restricted to one numerical value. The information of the new fuzzy measures is seen as more trustworthy and helpful to decision making health managers, regarding which policies must be considered in accordance to the susceptible of harm and exposure in every population of each case scenario.

scholarly journals Dietary patterns and CVD: a systematic review and meta-analysis of observational studies

2015 ◽  
Vol 114 (9) ◽  
pp. 1341-1359 ◽  
Author(s):  
Míriam Rodríguez-Monforte ◽  
Gemma Flores-Mateo ◽  
Emília Sánchez
Keyword(s):  
Cohort Studies ◽  
Dietary Patterns ◽  
Observational Studies ◽  
Protective Factor ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Case Control ◽  
Case Control Studies ◽  
Chd Risk ◽  
Control Comparison

AbstractEpidemiological studies show that diet is linked to the risk of developing CVD. The objective of this meta-analysis was to estimate the association between empirically derived dietary patterns and CVD. PubMed was searched for observational studies of data-driven dietary patterns that reported outcomes of cardiovascular events. The association between dietary patterns and CVD was estimated using a random-effects meta-analysis with 95 % CI. Totally, twenty-two observational studies met the inclusion criteria. The pooled relative risk (RR) for CVD, CHD and stroke in a comparison of the highest to the lowest category of prudent/healthy dietary patterns in cohort studies was 0·69 (95 % CI 0·60, 0·78; I2=0 %), 0·83 (95 % CI 0·75, 0·92; I2=44·6 %) and 0·86 (95 % CI 0·74, 1·01; I2=59·5 %), respectively. The pooled RR of CHD in a case–control comparison of the highest to the lowest category of prudent/healthy dietary patterns was 0·71 (95 % CI 0·63, 0·80; I2=0 %). The pooled RR for CVD, CHD and stroke in a comparison of the highest to the lowest category of western dietary patterns in cohort studies was 1·14 (95 % CI 0·92, 1·42; I2=56·9 %), 1·03 (95 % CI 0·90, 1·17; I2=59·4 %) and 1·05 (95 % CI 0·91, 1·22; I2=27·6 %), respectively; in case–control studies, there was evidence of increased CHD risk. Our results support the evidence of the prudent/healthy pattern as a protective factor for CVD.

Fundamental Concepts

2019 ◽  
pp. 27-77
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Probability Distributions ◽  
Possibility Theory ◽  
Multi Objective ◽  
Basic Ideas ◽  
Fuzzy Stochastic Programming

In this chapter, the authors discuss some basic concepts of probability theory and possibility theory that are useful when reading the subsequent chapters of this book. The multi-objective fuzzy stochastic programming models developed in this book are based on the concepts of advanced topics in fuzzy set theory and fuzzy random variables (FRVs). Therefore, for better understanding of these advanced areas, the authors at first presented some basic ideas of probability theory and probability density functions of different continuous probability distributions. Afterwards, the necessity of the introduction of the concept of fuzzy set theory, some important terms related to fuzzy set theory are discussed. Different defuzzification methodologies of fuzzy numbers (FNs) that are useful in solving the mathematical models in imprecisely defined decision-making environments are explored. The concept of using FRVs in decision-making contexts is defined. Finally, the development of different forms of fuzzy goal programming (FGP) techniques for solving multi-objective decision-making (MODM) problems is underlined.

Object-Oriented Publish/Subscribe for Modeling and Processing Imperfect Information

2011 ◽  
pp. 301-332
Author(s):  
Haifeng Liu ◽  
Hans Arno Jacobsen
Keyword(s):  
Set Theory ◽  
Fuzzy Set Theory ◽  
Imperfect Information ◽  
Information Dissemination ◽  
Object Oriented ◽  
Possibility Theory ◽  
Matching Problem ◽  
Fuzzy Measures ◽  
Information Providers ◽  
Selective Information

In the publish/subscribe paradigm, information providers disseminate publications to all consumers who expressed interest by registering subscriptions with the publish/subscribe system. This paradigm has found widespread applications, ranging from selective information dissemination to network management. In all existing publish/subscribe systems, neither subscriptions nor publications can capture uncertainty inherent to the information underlying the application domain. However, in many situations, knowledge of either specific subscriptions or publications is not available. To address this problem, this chapter proposes a new object-oriented publish/subscribe model based on possibility theory and fuzzy set theory to process imperfect information for expressing subscriptions, publications, or both combined. Furthermore, the approximate publish/subscribe matching problem based on fuzzy measures is defined, and the real-world A-ToPSS™ system is described.

UNCERTAIN AND FUZZY OBJECT BASES: A DATA MODEL AND ALGEBRAIC OPERATIONS

2011 ◽  
Vol 19 (02) ◽  
pp. 275-305 ◽  
Author(s):  
TRU H. CAO ◽  
HOA NGUYEN
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Object Oriented ◽  
Possibility Theory ◽  
Object Properties ◽  
Common Framework ◽  
Formal Basis ◽  
Object Oriented Systems ◽  
Is Value

Fuzzy set theory and probability theory are complementary for soft computing, in particular object-oriented systems with imprecise and uncertain object properties. However, current fuzzy object-oriented data models are mainly based on fuzzy set theory or possibility theory, and lack of a rigorous algebra for querying and managing uncertain and fuzzy object bases. In this paper, we develop an object base model that incorporates both fuzzy set values and probability degrees to handle imprecision and uncertainty. A probabilistic interpretation of relations on fuzzy sets is introduced as a formal basis to coherently unify the two types of measures into a common framework. The model accommodates both class attributes, representing declarative object properties, and class methods, representing procedural object properties. Two levels of property uncertainty are taken into account, one of which is value uncertainty of a definite property and the other is applicability uncertainty of the property itself. The syntax and semantics of the selection and other main data operations on the proposed object base model are formally defined as a full-fledged algebra.

Consumption of Artificially-sweetened Soft Drinks and Risk of Gastrointestinal Cancer: A Meta-analysis of Observational Studies

2021 ◽  
pp. 1-50
Author(s):  
Alfred Jatho ◽  
Jansen Marcos Cambia ◽  
Seung-Kwon Myung ◽  
Keyword(s):  
Cohort Studies ◽  
Observational Studies ◽  
Meta Analysis ◽  
Epidemiological Studies ◽  
Case Control ◽  
Soft Drinks ◽  
Case Control Studies ◽  
Gi Cancer ◽  
Increased Risk ◽  
Meta Analyses

Abstract Objective: There remain inconclusive findings from previous observational epidemiological studies on whether consumption of artificially-sweetened soft drinks (ASSDs) increases the risk of gastrointestinal (GI) cancer. We investigated the associations between the consumption of ASSDs and the risk of GI cancer using a meta-analysis. Design: Systematic review and meta-analysis. Setting: PubMed and EMBASE were searched using keywords until May 2020 to identify observational epidemiological studies on the association between the consumption of ASSDs and the risk of GI cancer. Subjects: Twenty-one case-control studies and 17 cohort studies with 12,397 cancer cases and 2,474,452 controls. Results: In the random-effects meta-analysis of all the studies, consumption of ASSDs was not significantly associated with the risk of overall GI cancer (odds ratio (OR)/relative risk (RR), 1.02; 95% CI, 0.92-1.14). There was no significant association between the consumption of ASSDs and the risk of overall GI cancer in the subgroup meta-analyses by study design (case-control studies: OR, 0.95; 95% CI, 0.82-1.11; cohort studies: RR, 1.14; 95% CI, 0.97-1.33). In the subgroup meta-analysis by type of cancer, consumption of ASSDs was significantly associated with the increased risk of liver cancer (OR/RR, 1.28; 95% CI,1.03-1.58). Conclusions: The current meta-analysis of observational epidemiological studies suggests that overall, there is no significant association between the consumption of ASSDs and the risk of GI cancer.

scholarly journals Towards non-conventional methods of designing register-based epidemiological studies: An application to pediatric research

2017 ◽  
Vol 45 (17_suppl) ◽  
pp. 30-35 ◽  
Author(s):  
Tong Gong ◽  
Bronwyn Brew ◽  
Arvid Sjölander ◽  
Catarina Almqvist
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Epidemiological Studies ◽  
Case Control ◽  
Observational Research ◽  
Advantages And Disadvantages ◽  
Study Population ◽  
Family Based ◽  
Study Designs ◽  
Residual Confounding

Aims: Various epidemiological designs have been applied to investigate the causes and consequences of fetal growth restriction in register-based observational studies. This review seeks to provide an overview of several conventional designs, including cohort, case-control and more recently applied non-conventional designs such as family-based designs. We also discuss some practical points regarding the application and interpretation of family-based designs. Methods: Definitions of each design, the study population, the exposure and the outcome measures are briefly summarised. Examples of study designs are taken from the field of low birth-weight research for illustrative purposes. Also examined are relative advantages and disadvantages of each design in terms of assumptions, potential selection and information bias, confounding and generalisability. Kinship data linkage, statistical models and result interpretation are discussed specific to family-based designs. Results: When all information is retrieved from registers, there is no evident preference of the case-control design over the cohort design to estimate odds ratios. All conventional designs included in the review are prone to bias, particularly due to residual confounding. Family-based designs are able to reduce such bias and strengthen causal inference. In the field of low birth-weight research, family-based designs have been able to confirm a negative association not confounded by genetic or shared environmental factors between low birth weight and the risk of asthma. Conclusions: We conclude that there is a broader need for family-based design in observational research as evidenced by the meaningful contributions to the understanding of the potential causal association between low birth weight and subsequent outcomes.

Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship—Observational Studies

2016 ◽  
Vol 37 (10) ◽  
pp. 1141-1146 ◽  
Author(s):  
Graham M. Snyder ◽  
Heather Young ◽  
Meera Varman ◽  
Aaron M. Milstone ◽  
Anthony D. Harris ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Retrospective Cohort ◽  
Observational Studies ◽  
Case Control Study ◽  
Cost Effective ◽  
Case Control ◽  
Study Population ◽  
Study Designs ◽  
Healthcare Epidemiology ◽  
Control Study

Observational studies compare outcomes among subjects with and without an exposure of interest, without intervention from study investigators. Observational studies can be designed as a prospective or retrospective cohort study or as a case-control study. In healthcare epidemiology, these observational studies often take advantage of existing healthcare databases, making them more cost-effective than clinical trials and allowing analyses of rare outcomes. This paper addresses the importance of selecting a well-defined study population, highlights key considerations for study design, and offers potential solutions including biostatistical tools that are applicable to observational study designs.Infect Control Hosp Epidemiol 2016;1–6

Flexible Querying Techniques Based on CBR

2011 ◽  
pp. 167-190
Author(s):  
Guy De Tré ◽  
Marysa Demoor ◽  
Bert Callens ◽  
Lise Gosseye
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Possibility Theory ◽  
Case Based Reasoning ◽  
Similarity Matching ◽  
Untreated Case ◽  
Flexible Querying ◽  
Case Based

In case-based reasoning (CBR), a new untreated case is compared to cases that have been treated earlier, after which data from the similar cases (if found) are used to predict the corresponding unknown data values for the new case. Because case comparisons will seldom result in an exact-similarity matching of cases and the conventional CBR approaches do not efficiently deal with such imperfections, more advanced approaches that adequately cope with these imperfections can help to enhance CBR. Moreover, CBR in its turn can be used to enhance flexible querying. In this chapter, we describe how fuzzy set theory can be used to model a gradation in similarity of the cases and how the inevitable uncertainty that occurs when predictions are made can be handled using possibility theory resulting in what we call flexible CBR. Furthermore, we present how and under which conditions flexible CBR can be used to enhance flexible querying of regular databases.

Sign in / Sign up

Export Citation Format

Share Document