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In Mendelian randomization, two single SNP-trait correlation-based methods have been developed to infer the causal direction between an exposure (e.g., a gene) and an outcome (e.g., a trait), called MR Steiger's method and its recent extension called Causal Direction-Ratio (CD-Ratio). Here we propose an approach based on R2, the coefficient of determination, to combine information from multiple (possibly correlated) SNPs to simultaneously infer the presence and direction of a causal relationship between an exposure and an outcome. Our proposed method generalizes Steiger's method from using a single SNP to multiple SNPs as IVs. It is especially useful in transcriptome-wide association studies (TWASs) (and similar applications) with typically small sample sizes for gene expression (or another molecular trait) data, providing a more flexible and powerful approach to inferring causal directions. It can be applied to GWAS summary data with a reference panel. We also discuss the influence of invalid IVs and introduce a new approach called R2S to select and remove invalid IVs (if any) to enhance the robustness. We compared the performance of the proposed method with existing methods in simulations to demonstrate its advantages. We applied the methods to identify causal genes for high/low-density lipoprotein cholesterol (HDL/LDL) using the individual-level GTEx gene expression data and UK Biobank GWAS data. The proposed method was able to confirm some well-known causal genes while identifying some novel ones. Additionally, we illustrated an application of the proposed method to GWAS summary to infer causal relationships between HDL/LDL and stroke/coronary artery disease (CAD).
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Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Transcriptoma , Humanos , Estudio de Asociación del Genoma Completo/métodos , Transcriptoma/genética , Análisis de la Aleatorización Mendeliana/métodos , Modelos Genéticos , LDL-Colesterol/genética , LDL-Colesterol/sangre , FenotipoRESUMEN
BACKGROUND: Schizophrenia occurs worldwide, and the health, and economic burden is substantial. As one of the common proxies of socioeconomic status (SES), education was reported to be associated with the risk of developing schizophrenia. However, there is no causal evidence about the relationship. This paper explores the health benefits of college education for schizophrenia. METHOD: Based on exogenous variation in college enrollment across regions and cohorts induced by college enrollment expansion policy, we use instrument variable (IV) estimate strategy to estimate impacts of college education on the risk of schizophrenia with the data from Second National Sample Survey on Disability. RESULTS: We find that college education reduces the risk of developing schizophrenia by 4.2 percentage points. Some further analyses suggest the causal protective effect is only found among men, rural, and low-income individuals. CONCLUSIONS: These findings provide new evidence for the causal relationship between college education and schizophrenia, and add to the literature on the health benefits of education.
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Esquizofrenia , Masculino , Humanos , Esquizofrenia/epidemiología , Esquizofrenia/prevención & control , Clase Social , Escolaridad , China/epidemiología , PolíticasRESUMEN
BACKGROUND: Given the uncertainties surrounding the associations in previous epidemiological studies, we conducted linear and nonlinear Mendelian randomization (MR) studies to evaluate whether body mass index (BMI) associated with gastric cancer (GC) risk in European and Korean. METHODS: Genome-wide association study-summary statistics were used from the Pan-UK Biobank, the Genetic Investigation of Anthropometric Traits consortium, the K-CHIP consortium, and BioBank Japan. BMI-associated single nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs) in MR to identify the association between BMI and GC. Both linear and nonlinear MR analyses were performed. Sensitivity analyses were also conducted for individuals below or above a BMI of 24 kg/m2. RESULTS: The study used 22 and 55 SNPs as IVs for BMI in European and Korean populations, respectively. Genetically predicted BMI was positively associated with GC risk in the European population (Odds ratio per 1 kg/m2 increase; 95% CI = 1.17; 1.01-1.36 using simple median method), but no significant association was observed in the Korean population. However, the nonlinear MR identified a U-shaped association between BMI and GC in the Korean population, with both low and high BMIs associated with increased GC risk. A BMI of 24 kg/m2 presented the lowest risk. Sensitivity analyses did not yield any genome-wide significant SNPs. CONCLUSION: While MR analysis suggests a linear association between BMI and GC in those of European ancestry, nonlinear MR hints at a U-shaped association in Koreans. This suggests the association between BMI and GC risk may vary according to ethnic ancestry.
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Estudio de Asociación del Genoma Completo , Neoplasias Gástricas , Humanos , Índice de Masa Corporal , Neoplasias Gástricas/epidemiología , Neoplasias Gástricas/genética , Análisis de la Aleatorización Mendeliana , Polimorfismo de Nucleótido Simple , República de Corea/epidemiologíaRESUMEN
Mendelian randomization is a technique used to examine the causal effect of a modifiable exposure on a trait using an observational study by utilizing genetic variants. The use of many instruments can help to improve the estimation precision but may suffer bias when the instruments are weakly associated with the exposure. To overcome the difficulty of high-dimensionality, we propose a model average estimator which involves using different subsets of instruments (single nucleotide polymorphisms, SNPs) to predict the exposure in the first stage, followed by weighting the submodels' predictions using penalization by common penalty functions such as least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP). The model averaged predictions are then used as a genetically predicted exposure to obtain the estimation of the causal effect on the response in the second stage. The novelty of our model average estimator also lies in that it allows the number of submodels and the submodels' sizes to grow with the sample size. The practical performance of the estimator is examined in a series of numerical studies. We apply the proposed method on a real genetic dataset investigating the relationship between stature and blood pressure.
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Variación Genética , Análisis de la Aleatorización Mendeliana , Humanos , Análisis de la Aleatorización Mendeliana/métodos , Causalidad , Fenotipo , Presión Sanguínea/genética , Polimorfismo de Nucleótido Simple , Estudio de Asociación del Genoma CompletoRESUMEN
The potentially serious economic consequences of China's severe air pollution problem cannot be overlooked, especially the impact on corporate innovation, which is a core driver guiding firms towards efficient and high-quality development. This paper explores the direct effect and mechanism of PM2.5 on firms' innovation output through the identification strategy of instrument variable. Based on the data of Listed Companies in China from 2003 to 2016, we used thermal inversion as the instrument variable for PM2.5 for estimation. The results show that each 1 ug/m3 increase in PM2.5 concentration causes an average reduction in innovation output of listed companies by about 7.0%. The test of "Porter hypothesis" shows that environmental regulation has not encouraged firms to innovate more. We further used the 2013 China Social Survey (CSS) data to verify the human capital mechanism of PM2.5 affecting firm innovation at micro level. The results show that PM 2.5 deteriorates the healthy human capital in a firm, which reduces the innovation output. This article helps to understand the relationship between air pollution and firms' innovation and to develop appropriate policies.
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Contaminación del Aire , Contaminantes Ambientales , Humanos , Contaminación del Aire/prevención & control , China , Estado de Salud , Material ParticuladoRESUMEN
The application of organic fertilizer is an important measure for improving the quality of agricultural products and realizing the sustainable development of agriculture. The original small-scale family business model in China is no longer suitable for the development of modern agriculture. Large-scale agricultural business has become the mainstream trend, accompanied by the increasingly active land-transfer market. It is, therefore, necessary to determine whether farmland scale influences farmers' organic fertilizer applications in China. Based on the analysis of the influence mechanism of farmland scale on farmers' organic fertilizer application behaviors, empirical tests were conducted using survey data from 812 citrus farmers in Sichuan Province, China. The results show that the large-scale farmers are more likely to apply organic fertilizer and increase the application intensity than small-scale farmers and that the heterogeneity of farmers also affect their organic fertilizer application behavior. The results suggest that the government should encourage farmers to conduct moderate-scale management and promote their application behavior with organic fertilizer by improving awareness, strengthening education and training, and providing financial support.
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Agricultores , Fertilizantes , Agricultura/métodos , China , Granjas , HumanosRESUMEN
The new coronavirus disease (COVID-19) has paralysed many sectors of human life, including economic, social-cultural and political processes. In the political arena, several countries have postponed elections due to the COVID-19 pandemic. Other countries, including Malawi, went ahead with their planned elections. Malawi held a presidential election at a time when the number of COVID-19 cases was increasing rapidly. In this paper, we assess the effect of the perceived risk of catching COVID-19 on willingness to vote in the Malawi presidential election that was held on 23 June 2020. Turn out in this election was ten percentage points lower than in the general elections that were held a year earlier. The paper draws on a nationally representative survey of adult Malawians (n = 1155). In our main analysis, we use instrumental variables to account for potential endogeneity. We find that nearly two thirds of Malawians thought that they were likely to catch COVID-19 at some point. Notwithstanding the COVID-19 risk, 86% of the country's citizens were willing to vote. Our analysis shows that an individual's perceived risk of catching COVID-19 is associated with a lower likelihood of voting (ß = - 0.096; p < 0.05). This suggests that voter turnout in Malawi's fresh presidential election may have been highly affected by the perceived risk of catching COVID-19. The policy implication is that instituting and enforcing primary preventive measures may help reduce the perceived risk of catching COVID-19 and mitigate voter apathy.
La nouvelle maladie à coronavirus (COVID-19) a paralysé de nombreux secteurs de la vie humaine, y compris au niveau économique, socioculturel et politique. Au niveau politique, plusieurs pays ont reporté des élections en raison de la pandémie de COVID-19. D'autres pays, comme le Malawi, ont maintenu les élections qui étaient prévues. Le Malawi a organisé l'élection présidentielle au moment où le nombre de cas de COVID-19 augmentait rapidement. Dans cet article, nous évaluons l'effet que la perception du risque de contracter la COVID-19 a eu sur la volonté de se rendre aux urnes à l'occasion de l'élection présidentielle qui s'est tenue le 23 juin 2020 au Malawi. Le taux de participation à cette élection était inférieur de dix points de pourcentage à celui des élections générales qui ont eu lieu un an plus tôt. L'étude s'appuie sur une enquête nationale représentative des personnes adultes du Malawi (n = 1155). Dans notre analyse principale, nous utilisons des variables instrumentales pour tenir compte d'un potentiel biais d'endogénéité. Nous constatons que près de deux tiers des Malawites pensaient qu'ils étaient susceptibles de contracter la COVID-19 à un moment ou à un autre. En dépit du risque de contracter la COVID-19, 86% des citoyens et citoyennes du pays étaient prêt.es à voter. Notre analyse montre que la perception du risque qu'a une personne de contracter la COVID-19 est associée à une probabilité plus faible de se render aux urnes (ß = − 0.096; p < 0.05). Cela suggère que la participation électorale à la nouvelle élection présidentielle au Malawi a pu être fortement impactée par la perception du risque de contracter la COVID-19. En terme de politique, cela signifie que la mise en place et l'application de mesures de prévention primaire peuvent aider à réduire la perception du risque de contracter la COVID-19 et ainsi permettre d'atténuer l'apathie des électeurs.
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Association between drinking and smoking has remained controversial since the association between two studies were influenced by various confounding. Thus, our study aimed to explore the causal effect of alcohol consumption and cigarette smoking using alcohol flushing as an instrument variable, which is free from confounders. We analyzed cross-sectional survey data from 2500 Korean young adults (1600 men and 900 women). Alcohol flushing was strongly associated with log transformed alcohol consumption (F = 272). In men, alcohol non-flushers were 1.41 times (95% CI 1.28-1.55) more likely to smoke 100 cigarettes in their lifetime in logistic regression analysis. Alcohol non-flushers were also 1.3 times (95% CI 1.21-1.40) more likely to become daily smokers and 1.39 times (95% CI 1.27-1.51) more likely to be current smokers than alcohol flushers. However, in an IV analysis, no causal relationships between alcohol consumption and smoking status were found. Alcohol consumption, on the other hand, was causally associated with lowering nicotine dependence and former smoking in men. Alcohol consumption determined by alcohol flushing status does not appear to be causally linked to the smoking behavior of young adults. The relationship between alcohol consumption and nicotine dependence and smoking cessation needs further study.
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Fumar Cigarrillos , Consumo de Bebidas Alcohólicas/epidemiología , Estudios Transversales , Femenino , Rubor/epidemiología , Rubor/etiología , Humanos , Masculino , Humo , Adulto JovenRESUMEN
BACKGROUND: Temperament is associated with circulating inflammatory biomarkers, such as C-reactive protein (CRP), which has been associated with various health conditions, including depression. This study aims to investigate whether genetic disposition for increased circulating CRP concentration may influence temperament over the life-course. METHODS: Using a longitudinal cohort that began in 1980-the Cardiovascular Risk in Young Finns Study (YFS)-we included 920 participants (59.8% female) aged 3-12 years old at baseline (childhood), and the same participants again at ages 30-39 years old (adulthood) in this study. We used both ordinary least-squares regression (OLS linear regression) and instrumental variable (IV) regression to assess associations between CRP concentration and temperament dimensions (negative emotionality, activity, and sociability). To represent genetically determined risk for increase in circulating CRP concentration, we calculated a weighted genetic risk score (GRS) which reflects risk for increased circulating CRP concentration. RESULTS: In OLS linear regression analyses, we found that increased circulating CRP concentration in childhood was associated with slightly higher scores for sociability in childhood (19% increase, CI â= â7-32%) and adulthood (13% increase, CI â= â2-27%), and lower activity scores in adulthood (15% decrease, CI â= â3-25%). For all IV regressions, there were no apparent associations between GRS and temperament in either childhood or adulthood (all p>0.3). The Durbin-Wu-Hausman test for endogeneity produced p-values (all>0.05) that suggest there is no evidence for disagreement between the OLS and IV estimates. CONCLUSIONS: We found no clear evidence for an association of GRS for elevated CRP with childhood or adulthood emotionality, activity, or sociability, although circulating CRP was associated with some of these traits.
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The role of public spending on health in reducing socioeconomic inequalities in healthcare is an emerging area of research, little supporting empirical evidence is available from low- and middle-income countries. This study examined: (1) the relationship between public spending on health per capita and the decision whether to seek healthcare or not, (2) the relationships between public spending on health per capita and choice of medical provider, and (3) whether these relationships varied by socioeconomic groups in India. Our study utilized the nationally representative 71st National Sample Survey of India, using 26,142 people who had been ailing in the past 15 days, the survey took place between the 1st of January and June 30, 2014. Two regression-based approaches were used to examine the association between public spending and choice of medical providers: (1) Multilevel multinomial regression; and (2) Instrumental variable regression. We examined the differential impacts of public spending on healthcare utilisation by socioeconomic groups. Increased public spending on health was not associated with changes in ailing people's decision whether to seek care or not (p > 0.05 in all analyses). However, increased public spending on health was associated with reductions in patients choosing private medical providers [adjusted odds ratio = 0.88 (95%CI 0.85-0.91) for outpatient private clinics] compared to outpatient government clinics. These associations may be greater among the lower economic groups compared with their counterparts. Across India, higher levels of government investment in health services are recognised by healthcare users and shown in their pattern of healthcare utilisation. That an increase in public spending on health results in a decrease in the use of private providers, particularly outpatient facilities with no inpatient capabilities, provides strong evidence for the effectiveness of 'regulation by competition'. This is a strong argument for focusing health system strengthening, and strategies for achieving universal healthcare on public investment.
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Gastos en Salud , Servicios de Salud , Personal de Salud , Humanos , India , Factores SocioeconómicosRESUMEN
Non-adherence to assigned treatment is a common issue in cluster randomised trials. In these settings, the efficacy estimand may also be of interest. Many methodological contributions in recent years have advocated using instrumental variables to identify and estimate the local average treatment effect. However, the clustered nature of randomisation in cluster randomised trials adds to the complexity of such analyses. In this paper, we show that the local average treatment effect can be estimated via two-stage least squares regression using cluster-level summaries of the outcome and treatment received under certain assumptions. We propose the use of baseline variables to adjust the cluster-level summaries before performing two-stage least squares in order to improve efficiency. Implementation needs to account for the reduced sample size, as well as the possible heteroscedasticity, to obtain valid inferences. Simulations are used to assess the performance of two-stage least squares of cluster-level summaries under cluster-level or individual-level non-adherence, with and without weighting and robust standard errors. The impact of adjusting for baseline covariates and of appropriate degrees of freedom correction for inference is also explored. The methods are then illustrated by re-analysing a cluster randomised trial carried out in a specific UK primary care setting. Two-stage least squares estimation using cluster-level summaries provides estimates with small to negligible bias and coverage close to nominal level, provided the appropriate small sample degrees of freedom correction and robust standard errors are used for inference.
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Tamaño de la Muestra , Sesgo , Análisis por Conglomerados , Análisis de los Mínimos CuadradosRESUMEN
Physical activity is crucial for maintaining and improving health, especially at advanced ages. While retirement increases the amount of time available for physical activity, there is only limited evidence regarding the causal effect of retirement on recommended levels of physical activity. Addressing this gap in the literature, we use data from the U.S. Health and Retirement Study to estimate the causal impact of retirement on meeting the federal government's 2008 Physical Activity Guidelines for Americans. Using official early and normal retirement ages as instruments for retirement, our causal IV analyses suggest significant positive effects of retirement on meeting the Guidelines. These effects are robust with regard to the treatment of unobserved individual-specific heterogeneity, the measurement of guideline compliance, the definition of retirement and respondents' health insurance status. We also show that the effects of retirement on physical activity are larger for persons with higher levels of education and wealth.
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Ejercicio Físico , Jubilación , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Encuestas y Cuestionarios , Estados UnidosRESUMEN
This study quantitatively estimates the effects of corruption on five major health indicators by using recent cross-country panel data covering 119 countries for the period of 2005-2011. The corruption indicators provided by the World Bank and Transparency International are used, and both the two-way fixed effect and the two-stage least squares approaches are employed for our estimation. The estimation results show that, in general, corruption is negatively associated with a country's health outcomes. A lower level of corruption or a better control of corruption in a country can lead to longer life expectancy, a lower infant mortality rate and a lower under-five mortality rate for citizens. However, our estimation finds no significant association between corruption and individual diseases including human immunodeficiency virus prevalence and tuberculosis incidence. The findings suggest that corruption reduction itself is an effective method to promote health. Copyright © 2015 John Wiley & Sons, Ltd.
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Fraude/estadística & datos numéricos , Estado de Salud , Mortalidad del Niño , Preescolar , Salud Global/estadística & datos numéricos , Infecciones por VIH/epidemiología , Humanos , Lactante , Mortalidad Infantil , Esperanza de Vida , Tuberculosis Pulmonar/epidemiologíaRESUMEN
The ability to make strong causal inferences, based on data derived from outside of the laboratory, is largely restricted to data arising from well-designed randomized control trials. Nonetheless, a number of methods have been developed to improve our ability to make valid causal inferences from data arising from observational studies. In this paper, I review concepts of causation as a background to counterfactual causal ideas; the latter ideas are central to much of current causal theory. Confounding greatly constrains causal inferences in all observational studies. Confounding is a biased measure of effect that results when one or more variables, that are both antecedent to the exposure and associated with the outcome, are differentially distributed between the exposed and non-exposed groups. Historically, the most common approach to control confounding has been multivariable modeling; however, the limitations of this approach are discussed. My suggestions for improving causal inferences include asking better questions (relates to counterfactual ideas and "thought" trials); improving study design through the use of forward projection; and using propensity scores to identify potential confounders and enhance exchangeability, prior to seeing the outcome data. If time-dependent confounders are present (as they are in many longitudinal studies), more-advanced methods such as marginal structural models need to be implemented. Tutorials and examples are cited where possible.