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BACKGROUND:Epidemiologic studies have shown a correlation between type 2 diabetes mellitus and bone mineral density,but the causal association between the two and whether it is age-related remains unknown. OBJECTIVE:To study the correlation between type 2 diabetes mellitus and whole body bone mineral density at unspecified age and at all ages based on the Mendelian randomization technique. METHODS:The genome-wide association study(GWAS)data of type 2 diabetes mellitus and bone mineral density at all ages were selected from the IEU GWAS database of the University of Bristol.The exposure data were single nucleotide polymorphisms with significant correlation with type 2 diabetes mellitus as instrumental variables,and bone mineral density at all ages was selected as the outcome variable.Two-sample Mendelian randomization analysis of type 2 diabetes mellitus and bone mineral density was performed using inverse variance weighted method,weighted median estimator,and MR-Egger regression.The βvalue was used to evaluate the causal relationship between type 2 diabetes mellitus and bone mineral density at all ages. RESULTS AND CONCLUSION:A total of 118 single nucleotide polymorphisms were extracted from the GWAS summary data as instrumental variables.The MR-Egger regression results showed that there was no horizontal pleiotropy,but there was heterogeneity.Therefore,this study was based on the inverse variance weighted results.Inverse variance weighted results showed that type 2 diabetes mellitus may be a potential protective factor for bone mineral density and is associated with age:age-unspecified bone mineral density[β=0.038,95%confidence interval(CI):1.01-1.07,P=0.002],bone mineral density over 60 years old(β=0.052,95%CI:1.01-1.09,P=0.027),bone mineral density between 45-60 years old(β=0.049,95%CI:1.01-1.09,P=0.009),bone mineral density between 30-45 years old(β=0.033,95%CI:0.99-1.07,P=0.127).bone mineral density of 15-30 years old(β=0.025,95%CI:0.95-1.10,P=0.506),bone mineral density of 0-15 years old(β=0.006,95%CI:0.96-1.04,P=0.716).Similar results were obtained from the MR-Egger regression and weighted median estimator analyses.These findings indicate that type 2 diabetes mellitus may be one of the protective factors of bone mineral density,and there is a correlation with age.
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Objective:To investigate the causal association between testosterone and nonalcoholic fatty liver disease(NAFLD) in men and women using a two-sample Mendelian randomization(MR) approach.Methods:Genetic variation in testosterone(total testosterone, bioavailable testosterone) and sex hormone-binding globulin(SHBG) in females and males was used as an instrumental variable using the genome-wide association study(GWAS) pooled data, and the inverse variance weighting method was applied. Inverse variance weighted(IVW) was used as the main analytical method, along with six univariate MR methods based on other modeling assumptions to assess the causal relationship between testosterone(total testosterone, bioavailable testosterone) as well as SHBG and NAFLD in women and men. In addition, NAFLD data from Finnish Biobank(FinnGen) were applied to validate the results of the exploratory analysis. Further, sensitivity analyses were performed to assess the level of heterogeneity, genetic pleiotropy, and stability of the instrumental variables using Cochran′ s Q test, MR-Egger regression, and leave-one-out methods. Results:The results of exploratory analysis of IVW model showed that bioavailable testosterone and SHBG were causally associated with NAFLD in women, for each unit increase in bioavailable testosterone levels, the risk of developing non-alcoholic fatty liver disease(NAFLD) rose by 24%( OR=1.24, 95% CI 1.07-1.43, P=0.004); and with each unit decrease in women′s SHBG, the NAFLD risk increased by 31%( OR=0.69, 95% CI 0.57-0.83, P<0.001). However, testosterone(total testosterone, bioavailable testosterone) as well as SHBG in men and female total testosterone did not show a causal relationship with NAFLD. The results of the other six MR methods were generally consistent with the IVW method. The results of the external validation data provided further evidence of a causal relationship between female bioavailable testosterone and SHBG and NAFLD. Conclusion:Elevated levels of bioavailable testosterone along lower levels of SHBG may increase the risk of developing NAFLD in women.
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Objective @#This study aimed to explore the influencing factors of dynamic changes in traditional Chinese medicine (TCM) constitution based on general statistics, Apriori-DEMATEL algorithm, and DoWhy causal inference framework methods.@*Methods@#Dynamic collection of TCM constitution identification data was conducted from the population aged 18 − 60, containing collection time and constitution type, and 11 constitution influencing factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, stress level, living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. General statistical analysis was used to analyze the relative percentage of corresponding influencing factors of different types of constitution changes, the Apriori-DEMATEL algorithm was used to analyze the correlation between 11 constitution influencing factors such as dietary habit and constitution changes, and the DoWhy causal inference framework was used to analyze the causality between dietary habit,sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, explore the frequency of constitution type transformation-change factors, and determine the key influencing factors causing dynamic changes in constitution type.@*Result@#After preprocessing, 13536 valid data points were obtained. Based on the Apriori-DEMATEL algorithm, the factors were divided into six original factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, and five result factors includ ing living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. Combining with general statistics, we found that among the original factors, changes in dietary habit, sleeping habit, sleeping duration, and stress level had a greater impact on other factors. In the process of constitution conditioning, attention should be paid to these four factors to maintain constitution balance. Among the five resultfactors, the absolute values of work/life calamity and family atmosphere were relatively large, indicating that these two factors were easily influenced by other factors. The dietary habit,sleeping habit, sleeping duration, exercise habit, emotion state, and stress level have higher centrality in changes, indicating that these six factors had important in constitution changes. According to the statistical frequency of constitution changes corresponding to each factor, we found that the changes of these six factors accounted for a large proportion of the constitution transformation frequency among Qi deficiency constitution, balanced constitution, and allergic constitution, indicating that the changes of these six factors played an important role in the changes of the three constitution types. Combined with the results of the Apriori-DEMATEL algorithm, and DoWhy causal inference framework analysis, it was inferred that dietary habit and sleeping duration indirectly lead to constitution changes by affecting the changes of other factors.@*Conclusion@#This study explored the influencing factors of dynamic changes in TCM constitution from the perspective of dynamic data and multiple analysis methods, and the results showed that the changes of dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level had a great impact on the changes of Qi deficiency constitution, balanced constitution and allergic constitution. Attention should be paid to the changesof these six factors in daily life, and corresponding improvement plans should be formulated to reduce the probability of transforming into biased constitution. Our study also provided data support and objective analysis reference for the analysis of influencing factors of dynamic changes in TCM constitution types.
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【Objective】 A two-sample Mendelian randomization method was used to explore whether there is a causal relationship between the intake of alcohol, coffee, green tea and dairy products and the incidence of prostate cancer (PCa), in order to clarify the risk factors for the incidence of PCa and find a prevention pathway for PCa. 【Methods】 Data of alcohol, coffee, green tea, dairy products and prostate cancer were collected with genome-wide association study (GWAS).The causal relationship between their intake and the risk of PCa was analyzed with two-sample Mendelian randomization (2SMR).MR analysis was conducted with inverse-variance weighting (IVW).Sensitivity analysis was performed with weighted median, MR-Egger regression, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) tests. 【Results】 Coffee intake (OR: 0.994, 95%CI: 0.990-0.999, P=0.014) and green tea intake (OR: 0.999, 95%CI: 0.998-0.999, P=0.036) were negatively correlated with the risk of PCa.Alcohol intake (OR: 0.997, 95%CI: 0.990-1.004, P=0.392) and dairy intake (OR: 1.025, 95%CI: 0.983-1.069, P=0.256) were not associated with the risk of PCa.In weighted median, MR-Egger regression, and retention one method analyses, the results were robust without heterogeneity or pleiotropy. 【Conclusion】 There was a causal association between coffee intake and green tea intake and the onset of PCa, but no causal association between alcohol intake and dairy intake and PCa onset.
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In environmental epidemiological research, extensive non-random environmental exposures and complex confounding biases pose significant challenges when attempting causal inference. In recent years, the introduction of causal inference methods into observational studies has provided a broader range of statistical tools for causal inference research in environmental epidemiology. The instrumental variable (IV) approach, as a causal inference technique for effectively controlling unmeasured confounding factors, has gradually found application in the field of environmental epidemiological research. This article reviewed the basic principles of IV and summarized the current research progress and limitations of applying IV for causal inference in environmental epidemiology. IV application in the field of environmental epidemiology is still in the initial stage. Rational use of IV and effective integration with other causal inference methods will become the focus of the development of causal inference in environmental epidemiology. The aim of this paper is to provide a methodological reference and basis for future studies involving causal inference to target population health effects of environmental exposures in China.
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Objective To determine the causal relationship between acromegaly and colon cancer by using two-sample Mendelian randomization. Methods Genetic loci closely related to acromegaly in the whole genome-wide association study (GWAS) were selected as tool variables, and the genetic data of colon cancer from different GWASs were analyzed by two-sample Mendelian randomization (MR).The inverse variance weighting method (IVW) of the random effect model was used for analysis, and MR-weighted median and MR-Egger methods were used to supplement the analysis. Results were presented as OR values. Results Four SNPs closely related to acromegaly were obtained as tool variables, and the multiplicity test of tool variables showed that P=0.59.Three methods were used to estimate causal effects.The IVW analysis were OR=1.00(0.99-1.001) and P=0.42;the MR-Egger analysis results were OR=1.00(0.99-1.001) and P=0.42;and the Weighted median analysis results were OR=1.00(1.00-1.001) and P=0.03.The sensitivity test showed that the confidence interval of the tool variable SNP passed through 0, indicating the robustness of the MR results. Conclusion Acromegaly is not an independent risk factor for colon cancer.
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OBJECTIVE To investigate the causal association between ticagrelor and risk of infection METHODS Two-sample Mendelian randomization was adopted. Genetic instrumental variables were selected based on the results of the largest genome-wide association analysis to in vivo exposure of ticagrelor and its major active metabolite AR-C124910XX. The causal associations of ticagrelor and its major active metabolite AR-C124910XX with drug indications (coronary artery disease, unstable angina pectoris, myocardial infarction, stroke and ischemic stroke)were analyzed by inverse variance weighted Mendelian randomization model as a positive control for genetic instrumental variables. The causal relationship between ticagrelor and bacterial infection, acute lower respiratory infection, bacterial pneumoniae, pneumoniae,acute upper respiratory infection and sepsis were furtheranalyzed by using this method, and the robustness of the results was assessed by using heterogeneity tests and horizontal 202002030415) pleiotropy tests. RESULTS The increase of area under the curve at steady state (AUCss) of the genetic surrogated ticagrelor significantly reduced the risk of coronary artery disease, myocardial infarction and unstable angina pectoris (P<0.001). AUCss genetic instrument variables of its main active metabolite AR-C124910XX failed to pass positive control. Further analysis showed that the increase of the genetic surrogated ticagrelor exposure suggestively reduced the risk of bacterial infection [OR(95%CI)=0.80(0.65,0.99),P=0.040] and sepsis [OR (95%CI)=0.84(0.73, 0.98), P=0.023]. The results of the heterogeneity tests showed that there was no heterogeneity in the causal association of the genetic surrogated ticagrelor AUCss with bacterial infection and sepsis (P>0.05). The results of horizontal pleiotropy tests showed that the causal association of genetic surrogated ticagrelor AUCss with bacterial infection and sepsis had no effects on horizontal pleiotropy (P>0.05). CONCLUSIONS Ticagrelor has a potential role in reducing the risk of sepsis and bacterial infections.
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Objective @#o evaluate the association between Crohn's disease (CD) and frailty using a Mendelian randomization (MR) approach, so as to provide the evidence for prevention and control strategies.@*Methods@#Genetic association data for CD were collected through the International Inflammatory Bowel Disease Genetics Consortium, with 20 883 samples and 12 276 506 single nucleotide polymorphism (SNP), and genetic association data for frailty were collected through a meta-analysis including 175 226 samples and 7 589 717 SNPs. A forward MR analysis was performed using the inverse-variance weighted (IVW) method with 37 CD-associated SNPs as instrumental variables, and frailty as the study outcome, and a reverse MR analysis was performed with 13 frailty-associated SNPs as instrumental variables and CD as the study outcome. The heterogeneity was assessed using the Cochran's Q test, and the horizontal pleiotropy was assessed using the MR-PRESSO global test and MR-Egger regression. In addition, the robustness of the results was verified with the leave-one-out. @*Results@#Forward MR analysis results showed that patients with genetically predicted CD had an increased risk of frailty index relative to those without CD (β=0.018, 95%CI: 0.011-0.026, P<0.05). Cochran's Q test detected no heterogeneity (P>0.05), and neither the MR-PRESSO test nor the MR-Egger regression revealed horizontal pleiotropy of instrumental variables (both P>0.05). Leave-one-out analysis showed robustness of the MR analysis results. Reverse MR analysis showed no association between frailty index and the risk of CD (OR=0.740, 95%CI: 0.206-2.661, P>0.05). @*Conclusions@#Genetically predicted CD is associated with an increased risk of frailty. It is suggested that screening and prevention of frailty should be reinforced among CD patients.
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Objective To explore the statistical performance and applicable conditions of Bayesian additive regression tree(BART)for estimating average treatment effect in observational studies.Methods The difference of estimates between BART and multivariate regression,propensity score matching,and inverse probability weighting through simulations and actual epidemiological data was compared.Results The results of these simulations showed that under the linear assumption,the performance of BART was close to that of the commonly used methods;when the relationship among variables in the data was complex and non-linear,BART performed markedly better than the others.When the ignorability assumption was not satisfied and there was unobserved confounding,all methods performed worse,but BART was still significantly better than the others and relatively robust.In the actual epidemiological data,this method was used to estimate the average treatment effect of smoking cessation on weight change.Conclusion In most observational studies,outcomes are influenced by multiple factors,making it difficult for researchers to properly specify relationships between variables.It is difficult to identify all these variables or determine the relationship between them.In terms of model fitting and result accuracy,BART is worth recommending.
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Objective In this study,we performed two sampie Mendelian Randomization to infer a causal association between Gastroesophageal reflux(GERD) and Atrial fibrillation(AF),it can effectively avoid the problems such as reverse causation and confounds in traditional epidemiology. Methods We used the Summary data of GERD and AF from published Genome wide association study(GWAS) of European Individuals. Single Nucleotide Polymorphisms (SNPs) were extracted as Instrumental Variables (IVs).The main MR methods include Inverse Variance [] Weighted(IVW),Weighted Median(WME),MR-Egger,Simple Mode,and Weighted Mode.In addition,we used the sensitivity analysis such as MR-PRESSO,Cochran's Q test etc. Results The IVW shows a causal association between GERD and AF(P<0.0001,OR=1.16,95%CI:1.10-1.23).The WME shows P<0.0001,OR=1.20,95%CI:1.11-1.30;Simple Mode shows P=0.01,OR=1.34,95%CI:1.07-1.69;Weighted Mode shows P=0.02,OR=1.33,95%CI:1.06-1.66. Conclusion This study based on genetic data supports the causal association between GERD and AF. The occurrence of GERD could increase the risk of AF.
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OBJECTIVE@#Traditional epidemiological studies have shown that C-reactive protein (CRP) is associated with the risk of cardiovascular diseases (CVDs). However, whether this association is causal remains unclear. Therefore, Mendelian randomization (MR) was used to explore the causal relationship of CRP with cardiovascular outcomes including ischemic stroke, atrial fibrillation, arrhythmia and congestive heart failure.@*METHODS@#We performed two-sample MR by using summary-level data obtained from Japanese Encyclopedia of Genetic association by Riken (JENGER), and we selected four single-nucleotide polymorphisms associated with CRP level as instrumental variables. MR estimates were calculated with the inverse-variance weighted (IVW), penalized weighted median and weighted median. MR-Egger regression was used to explore pleiotropy.@*RESULTS@#No significant causal association of genetically determined CRP level with ischemic stroke, atrial fibrillation or arrhythmia was found with all four MR methods (all Ps > 0.05). The IVW method indicated suggestive evidence of a causal association between CRP and congestive heart failure ( OR: 1.337, 95% CI: 1.005-1.780, P = 0.046), whereas the other three methods did not. No clear pleiotropy or heterogeneity were observed.@*CONCLUSIONS@#Suggestive evidence was found only in analysis of congestive heart failure; therefore, further studies are necessary. Furthermore, no causal association was found between CRP and the other three cardiovascular outcomes.
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Humanos , Proteína C-Reativa/metabolismo , Doenças Cardiovasculares/metabolismo , Predisposição Genética para Doença , Genótipo , Japão , Análise da Randomização Mendeliana , Polimorfismo de Nucleotídeo Único , Fatores de RiscoRESUMO
Resumo A avalição da efetividade de vacinas é feita com dados do mundo real e é essencial para monitorar o desempenho dos programas de vacinação ao longo do tempo bem como frente a novas variantes. Até o momento, a avaliação da efetividade das vacinas para COVID-19 tem sido baseada em métodos clássicos como estudos de coorte e caso controle teste-negativo, que muitas vezes podem não permitir o adequado controle dos vieses intrínsecos da alocação das campanhas de vacinação. O objetivo dessa revisão foi discutir os desenhos de estudo disponíveis para avaliação de efetividade das vacinas, enfatizando os estudos quase-experimentais, que buscam mimetizar os estudos aleatorizados ao introduzir um componente exógeno para atribuição ao tratamento, bem como suas vantagens, limitações e aplicabilidade no contexto dos dados brasileiros. O emprego de métodos quase-experimentais, incluindo as séries temporais interrompidas, o método de diferença em diferenças, escore de propensão, variáveis instrumentais e regressão descontínua, são relevantes pela possibilidade de gerar estimativas mais acuradas da efetividade de vacinas para COVID-19 em cenários como o brasileiro, que se caracteriza pelo uso de várias vacinas, com respectivos número e intervalos entre doses, aplicadas em diferentes faixas etárias e em diferentes momentos da pandemia.
Abstract The evaluation of vaccine effectiveness is conducted with real-world data. They are essential to monitor the performance of vaccination programmes over time, and in the context of the emergence of new variants. Until now, the effectiveness of COVID-19 vaccines has been assessed based on classic methods, such as cohort and test-negative case-control studies, which may often not allow for adequate control of inherent biases in the assignment of vaccination campaigns. The aim of this review was to discuss the study designs available to evaluate vaccine effectiveness, highlighting quasi-experimental studies, which seek to mimic randomized trials, by introducing an exogenous component to allocate to treatment, in addition to the advantages, limitations, and applicability in the context of Brazilian data. The use of quasi-experimental approaches, such as interrupted time series, difference-in-differences, propensity scores, instrumental variables, and regression discontinuity design, are relevant due to the possibility of providing more accurate estimates of COVID-19 vaccine effectiveness. This is especially important in scenarios such as the Brazilian, which characterized by the use of various vaccines, with the respective numbers and intervals between doses, applied to different age groups, and introduced at different times during the pandemic.
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Humanos , Vacinas , COVID-19 , Vacinas contra COVID-19 , SARS-CoV-2RESUMO
Objective To investigate the causal association between hip circumference (HC) and type 2 diabetes mellitus (T2DM) based on Mendelian randomization. Methods The genetic variants data of the HC and T2DM from the Genetic Investigation of Anthropometric Traits (GIANT) and DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) database were matched according to the single nucleotide polymorphism (SNP) rsID. Genetic loci strongly related to the HC were used as instrumental variables; and the inverse-variance weighting, MR-Egger regression model and weighting median method were carried out to analyze the causal effect of HC on T2DM. Results Fifty-two, nine and fifteen SNPs were matched in the total cohort, female cohort and male cohort, respectively. Heterogeneity test suggested the SNPs were homogeneous. We found HC to be positively associated with T2DM risk (OR=1.065, 95% CI: 1.030-1.100, OR=1.103, 95% CI: 1.057-1.150 and OR=1.583, 95% CI: 1.273-1.968, respectively) in above three cohorts, respectively. Sensitivity analysis showed the results were robust. Conclusions There is a relationship between HC and T2DM of people, and HC may be the risk factor of T2DM.
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A leishmaniose visceral (LV) é uma doença sistêmica de transmissão vetorial. No Brasil, ela é causada pelo protozoário Leishmania infantum e é transmitida por flebotomíneos do gênero Lutzomyia, tendo os cães como a principal fonte de infecção em áreas urbanas. Historicamente a LV era conhecida como uma doença endêmica rural, porém desde a década de 1980, ela atingiu proporções endêmicas e epidêmicas em grandes cidades brasileiras. Desde então vários fatores são considerados como norteadores da expansão da LV, como variáveis socioeconômicas, climáticas e ambientais. Mais especificamente sobre o efeito do desmatamento e perturbações antrópicas no ambiente, a maioria do que se encontra na literatura tem natureza qualitativa ou utiliza de abordagens reducionistas, sem considerar a complexidade da dinâmica de uma doença infecciosa de transmissão vetorial e de caráter zoonóticos. Na presente dissertação, investigamos o efeito do desmatamento na ocorrência de Lutzomyia longipalpis (Lu. longipalpis), leishmaniose visceral canina (LVC) e leishmaniose visceral humana (LVH), tomando como exemplo o estado de São Paulo. Para isso, utilizamos uma abordagem contrafactual para estimar os efeitos (geral, direto e indireto) do desmatamento na ocorrência do Lu. longipalpis/LVC/LVH. Isso foi feito em dois passos, primeiro estimamos os parâmetros por meio de um algoritmo de Metropolis-Hastings duplo e, por fim, estimamos os efeitos causais através de um amostrador de Gibbs, por meio do pacote autognet no R.Vimos que municípios desmatados apresentam 2.63, 2.07 e 3.18 maiores chances de apresentar o vetor, LVC e LVH, respectivamente quando comparados com os municípios que não apresentaram desmatamento. Foi observada também uma forte influência da presença do vetor, LVC e LVH dos municípios vizinhos na ocorrência dos mesmos em municípios previamente livres dos desfechos (6.67, 4.26 e 4.27). Já sob mudanças hipotéticas de prevalência do desmatamento de 50% para 0% no estado, são esperadas quedas na prevalência do vetor, LVC e LVH de 11%, 6.67% e 29.87% respectivamente. O desmatamento influi na ocorrência do vetor, doença em cães e humanos por duas principais vias, (i) alterando o funcionamento do ecossistema e estrutura da comunidade, permitindo a reprodução e colonização do vetor; e (ii) promovendo uma aproximação entre todos os componentes do ciclo da LV. De tal modo, para correto controle da LV e doenças infecciosas como um todo, é imprescindível um desenvolvimento ecologicamente correto com soluções viáveis para as compensações entre a agricultura, urbanização e conservação. urbanização e conservação.
Visceral leishmaniasis (VL) is a systemic vector-borne disease. In Brazil, it caused by the protozoan Leishmania infantum and is transmitted by sandflies of the genus Lutzomyia, with dogs as the principal source of infection in urban areas. Historically, VL was known as a rural endemic disease, since the 80's it has become endemic and epidemic in large Brazilian cities. Since then, many factors were hypothesised as driving VL expansion, as socioeconomic, climatic and environmental variables. More specifically, concerning deforestation and human-made actions in the environment, most studies tend to be qualitative in nature or use traditional reductionist approaches, ignoring the complexities that are inherent of vector-borne zoonotic infectious diseases. The present study aimed to investigate the effect of deforestation in the occurrence of Lutzomyia longipalpis, canine visceral leishmaniasis (CVL), and human visceral leishmaniasis (HVL), taking as a motivating example the São Paulo state (Brazil). To this end, we chose a counterfactual approach to estimate the effects (overall, direct and indirect) of deforestation in the occurrence of vector/CVL/HVL. We did it in two steps; first, we estimated the parameters through a double Metropolis-Hastings algorithm and, finally, we estimated the causal effects through a Gibbs sampler, using the autognet package in R. We observe that deforested cities show 2.63, 2.07, and 3.18 higher odds of vector/CVL/HVL occurrence, respectively, when compared to non-deforested municipalities. We also see a significant influence of vector, CVL, and HVL presence in the neighbours in its appearance in previous naive cities, 6.67, 4.26, 4,27 respectively. Lastly, under hypothetical changes in deforestation's prevalence from 50% to 0% in the whole state, is expected a decrease in its prevalence of the vector, LVC and LVH of 11%, 6.67% and 29.87% respectively. Deforestation in the occurrence of infectious diseases and, more specifically, VL importance, is two-folded: (i) changing's the ecosystem equilibrium and community structure, allowing its vector to reproduce and colonise; (ii) promoting a close contact through the VL cycle components. In such a way, for correct control of VL and infectious disease as a whole, it is essential an eco-friendly development with viable solutions for trade-offs between agriculture, urbanization and conservation.
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Conservação dos Recursos Naturais , Doenças Negligenciadas , Doenças Transmitidas por Vetores/epidemiologia , Leishmaniose Visceral/epidemiologiaRESUMO
Epidemiology is a branch of science that mainly involves in the etiology studies of non-randomness phenomenon among homogenous populations. In this paper, we use causal-thinking, supported by its tool-Directed Acyclic Graphs, to illustrate how the estimation of effects is affected by the issues as relations between effect and association, time sequences between variables and their measured counterparts, natural picture of dynamic population, formation of susceptible population, selection of study population, impact of covariates and types of cases etc., on the estimation of effects. This type of thinking may help us to re-capture the epidemiological theories, methods and related applications. Thus, causal-thinking should be strengthened.
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Mediation analysis is mainly used to explore the causal mechanism between independent variable X and dependent variable Y. It determines whether mediator M plays a role and evaluate the role’s degree in the causal path by decomposing the causal path between the independent variable X and the dependent variable Y. However, the classical mediation analysis is generally used for single mediator. This paper introduces a new mediation analysis method for multiple mediators.
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Objective@#To introduce the methods for sensitivity analysis, discuss and compare the advantages and disadvantages of different methods.@*Methods@#The difference between confounding function method and bounding factor method in accuracy of identifying unmeasured confounding factors in observational studies through simulation trials and actual clinical data was compared.@*Results@#The results of simulation trials and actual clinical data showed that when there was unmeasured confounding between exposure (X) and outcome (Y), the results of confounding function and the bounding factor analysis were similar in terms of the effect of unmeasured confounding factor to lead to the complete change of the magnitude and direction of the observed effect value. However, the confounding function method needed smaller confounding effect to fully interpret the observed effect value than the bounding factor needed. In addition, the bounding factor method needed to analyze two confounding parameters, while only one parameter was needed in the confounding function method. The confounding function method was simpler and more sensitive than the bounding factor method.@*Conclusion@#For real-world observational data, the sensitivity analysis process is essential in analyzing the causal effects between exposure (X) and outcome (Y). In terms of the calculation process and result interpretation the sensitivity analysis method of confounding function is worth to recommend.
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Mendelian randomization (MR) approach follows the Mendel′s law of inheritance, which is called "Parental alleles randomly assigned to the offspring", and refers to use genetic variants as an instrumental variable to develop causal inference between the exposure factor and the outcome from observational study. In recent years, with the rapid development of genome-wide association study (GWAS) and various omics data,the disclosure of a large number of aggregated data provides an opportunity for the wide application of MR approach in causal inference. We introduce three methods widely used in MR and then apply them to explore causal relationship between blood metabolites and depressive. The advantages and disadvantages of three methods in causal inference are compared in order to provide reference for the application of MR in observational studies.
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OBJECTIVES: The aim of this study was to evaluate the effect of pre-hypertension and its sub-classification on the development of diabetes. METHODS: In this cohort study, 2,941 people 40 to 64 years old without hypertension or diabetes were followed from 2009 through 2014. According to the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC)-7 criteria, we classified participants into normal and pre-hypertension groups. The effect of pre-hypertension on the 5-year incidence rate of diabetes was studied using inverse probability of treatment weighting. We modeled the exposure and censored cases given confounding factors such as age, sex, body mass index, smoking, economic status, and education. RESULTS: The 5-year incidence rate of diabetes among people with pre-hypertension and those with normal blood pressure (BP) was 12.7 and 9.7%, respectively. The risk ratio (RR) for people with pre-hypertension was estimated to be 1.13 (95% confidence interval [CI], 0.90 to 1.41). The RRs among people with normal BP and high-normal BP, according to the JNC-6 criteria, compared to those with optimal BP were 0.96 (95% CI, 0.73 to 1.25) and 1.31 (95% CI, 1.01 to 1.72), respectively. CONCLUSIONS: Our results showed that participants who had higher levels of BP (high-normal compared to optimal BP) had a higher risk of diabetes development. With regard to the quantitative nature of BP, using the specifically distinguishing of stage 1 hypertension or high-normal BP may be a more meaningful categorization for diabetes risk assessment than the JNC-7 classification.
Assuntos
Pressão Sanguínea , Índice de Massa Corporal , Classificação , Estudos de Coortes , Diabetes Mellitus , Educação , Hipertensão , Incidência , Irã (Geográfico) , Articulações , Modelos Estruturais , Razão de Chances , Pré-Hipertensão , Estudos Prospectivos , Medição de Risco , Fumaça , FumarRESUMO
OBJECTIVES: The aim of this study was to evaluate the effect of pre-hypertension and its sub-classification on the development of diabetes.METHODS: In this cohort study, 2,941 people 40 to 64 years old without hypertension or diabetes were followed from 2009 through 2014. According to the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC)-7 criteria, we classified participants into normal and pre-hypertension groups. The effect of pre-hypertension on the 5-year incidence rate of diabetes was studied using inverse probability of treatment weighting. We modeled the exposure and censored cases given confounding factors such as age, sex, body mass index, smoking, economic status, and education.RESULTS: The 5-year incidence rate of diabetes among people with pre-hypertension and those with normal blood pressure (BP) was 12.7 and 9.7%, respectively. The risk ratio (RR) for people with pre-hypertension was estimated to be 1.13 (95% confidence interval [CI], 0.90 to 1.41). The RRs among people with normal BP and high-normal BP, according to the JNC-6 criteria, compared to those with optimal BP were 0.96 (95% CI, 0.73 to 1.25) and 1.31 (95% CI, 1.01 to 1.72), respectively.CONCLUSIONS: Our results showed that participants who had higher levels of BP (high-normal compared to optimal BP) had a higher risk of diabetes development. With regard to the quantitative nature of BP, using the specifically distinguishing of stage 1 hypertension or high-normal BP may be a more meaningful categorization for diabetes risk assessment than the JNC-7 classification.