Quantifying the Causal Effect of Individual Mobility on Health Status in Urban Space

2021 ◽  
Vol 5 (4) ◽  
pp. 1-30
Author(s):  
Yunke Zhang ◽  
Fengli Xu ◽  
Tong Xia ◽  
Yong Li
Keyword(s):  
Health Status ◽  
Urban Space ◽  
Prediction Models ◽  
Healthy Lifestyle ◽  
Causal Effect ◽  
Human Mobility ◽  
Causal Effects ◽  
Environment Impact ◽  
Individual Mobility ◽  
Mobility Behaviour

How does individual mobility in the urban environment impact their health status? Previous works have explored the correlation between human mobility behaviour and individual health, yet the study on the underlying causal effect is woefully inadequate. However, the correlation analysis can sometimes be bewildering because of the confounding effects. For example, older people visit park more often but have worse health status than younger people. The common associations with age will lead to a counter-intuitive negative correlation between park visits and health status. Obtaining causal effects from confounded observations remains a challenge. In this paper, we construct a causal framework based on propensity score matching on multi-level treatment to eliminate the bias brought by confounding effects and estimate the total treatment effects of mobility behaviours on health status. We demonstrate that the matching procedure approximates a de-confounded randomized experiment where confounding variables are balanced substantially. The analysis on the directions of estimated causal effects reveals that fewer neighbouring tobacco shops and frequent visits to sports facilities are related with higher risk in health status, which differs from their correlation directions. Physical mobility behaviours and environment features have more significant estimated effects on health status than contextual mobility behaviours. Moreover, we embed our causal analysis framework in health prediction models to filter out features with superficial correlation but insignificant effects that might lead to over-fitting. This strategy achieves better model robustness with more features filtered out than L1-regularization. Our findings shed light on individual healthy lifestyle and mobility-related health policymaking.

scholarly journals Understanding the nature of association between anxiety phenotypes and anorexia nervosa: a triangulation approach

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
E. Caitlin Lloyd ◽  
Hannah M. Sallis ◽  
Bas Verplanken ◽  
Anne M. Haase ◽  
Marcus R. Munafò
Keyword(s):  
Anorexia Nervosa ◽  
Longitudinal Study ◽  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Causal Effect ◽  
Causal Effects ◽  
Observational Research ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Depressed Affect

Abstract Background Evidence from observational studies suggests an association between anxiety disorders and anorexia nervosa (AN), but causal inference is complicated by the potential for confounding in these studies. We triangulate evidence across a longitudinal study and a Mendelian randomization (MR) study, to evaluate whether there is support for anxiety disorder phenotypes exerting a causal effect on AN risk. Methods Study One assessed longitudinal associations of childhood worry and anxiety disorders with lifetime AN in the Avon Longitudinal Study of Parents and Children cohort. Study Two used two-sample MR to evaluate: causal effects of worry, and genetic liability to anxiety disorders, on AN risk; causal effects of genetic liability to AN on anxiety outcomes; and the causal influence of worry on anxiety disorder development. The independence of effects of worry, relative to depressed affect, on AN and anxiety disorder outcomes, was explored using multivariable MR. Analyses were completed using summary statistics from recent genome-wide association studies. Results Study One did not support an association between worry and subsequent AN, but there was strong evidence for anxiety disorders predicting increased risk of AN. Study Two outcomes supported worry causally increasing AN risk, but did not support a causal effect of anxiety disorders on AN development, or of AN on anxiety disorders/worry. Findings also indicated that worry causally influences anxiety disorder development. Multivariable analysis estimates suggested the influence of worry on both AN and anxiety disorders was independent of depressed affect. Conclusions Overall our results provide mixed evidence regarding the causal role of anxiety exposures in AN aetiology. The inconsistency between outcomes of Studies One and Two may be explained by limitations surrounding worry assessment in Study One, confounding of the anxiety disorder and AN association in observational research, and low power in MR analyses probing causal effects of genetic liability to anxiety disorders. The evidence for worry acting as a causal risk factor for anxiety disorders and AN supports targeting worry for prevention of both outcomes. Further research should clarify how a tendency to worry translates into AN risk, and whether anxiety disorder pathology exerts any causal effect on AN.

scholarly journals The Pice Effects of Competition from Parallel Imports and Therapeutic Alternatives: Using Dynamic Models to Estimate the Causal Effect on the Extensive and Intensive Margins

2021 ◽  
Author(s):  
David Granlund
Keyword(s):  
Dynamic Models ◽  
Causal Effect ◽  
The Other ◽  
Causal Effects ◽  
Parallel Imports ◽  
Extensive And Intensive Margins ◽  
Price Effects ◽  
Short And Long Term ◽  
Therapeutic Alternatives

AbstractThis paper studies responses to competition with the use of dynamic models that distinguish between short- and long-term price effects. The dynamic models also allow lagged numbers of competitors to become valid and strong instruments for the current numbers, which enables studying the causal effects using flexible specifications. A first parallel trader is found to decrease prices of exchangeable products by 7% in the long term. On the other hand, prices do not respond to the first competitor that sells therapeutic alternatives; but competition from four or more competitors that sell on-patent therapeutic alternatives decreases prices by about 10% in the long term.

Causal Returns to Education

2006 ◽  
Vol 226 (1) ◽  
Author(s):  
Anton L. Flossmann ◽  
Winfried Pohlmeier
Keyword(s):  
Educational Attainment ◽  
Educational Policy ◽  
Empirical Evidence ◽  
Returns To Education ◽  
Causal Effect ◽  
Causal Effects ◽  
Continuous Treatment ◽  
Treatment Variable ◽  
Secondary Schooling ◽  
Upper Secondary

SummaryThis paper surveys the empirical evidence on causal effects of education on earnings for Germany and compares alternative studies in the light of their underlying identifying assumptions. We work out the different assumptions taken by various studies, which lead to rather different interpretations of the estimated causal effect. In particular, we are interested in the question to what extend causal return estimates are informative regarding educational policy advice. Despite the substantial methodological differences, we have to conclude that the empirical findings for Germany are quite robust and do not deviate substantially from each other. This also holds for the few studies which rely on ignorability conditions, regardless of whether they use educational attainment as a continuous treatment variable or as a discrete treatment indicator. Own estimates based on the matching approach indicate that the selection into upper secondary schooling is suboptimal

Health Insurance and Health Status: Exploring the Causal Effect from a Policy Intervention

2015 ◽  
Vol 25 (11) ◽  
pp. 1389-1402 ◽  
Author(s):  
Jay Pan ◽  
Xiaoyan Lei ◽  
Gordon G. Liu
Keyword(s):  
Health Insurance ◽  
Health Status ◽  
Causal Effect ◽  
Policy Intervention

Causal inference via string diagram surgery

2021 ◽  
pp. 1-22
Author(s):  
Bart Jacobs ◽  
Aleks Kissinger ◽  
Fabio Zanasi
Keyword(s):  
Causal Inference ◽  
Probabilistic Reasoning ◽  
Causal Effect ◽  
Sufficient Conditions ◽  
Causal Effects ◽  
Stochastic Matrices ◽  
Counterfactual Reasoning ◽  
Special Cases ◽  
String Diagram ◽  
Set Up

Abstract Extracting causal relationships from observed correlations is a growing area in probabilistic reasoning, originating with the seminal work of Pearl and others from the early 1990s. This paper develops a new, categorically oriented view based on a clear distinction between syntax (string diagrams) and semantics (stochastic matrices), connected via interpretations as structure-preserving functors. A key notion in the identification of causal effects is that of an intervention, whereby a variable is forcefully set to a particular value independent of any prior propensities. We represent the effect of such an intervention as an endo-functor which performs ‘string diagram surgery’ within the syntactic category of string diagrams. This diagram surgery in turn yields a new, interventional distribution via the interpretation functor. While in general there is no way to compute interventional distributions purely from observed data, we show that this is possible in certain special cases using a calculational tool called comb disintegration. We demonstrate the use of this technique on two well-known toy examples: one where we predict the causal effect of smoking on cancer in the presence of a confounding common cause and where we show that this technique provides simple sufficient conditions for computing interventions which apply to a wide variety of situations considered in the causal inference literature; the other one is an illustration of counterfactual reasoning where the same interventional techniques are used, but now in a ‘twinned’ set-up, with two version of the world – one factual and one counterfactual – joined together via exogenous variables that capture the uncertainties at hand.

scholarly journals Novel bounds for causal effects based on sensitivity parameters on the risk difference scale

2021 ◽  
Vol 9 (1) ◽  
pp. 190-210
Author(s):  
Arvid Sjölander ◽  
Ola Hössjer
Keyword(s):  
Risk Ratio ◽  
Simulation Study ◽  
Observational Studies ◽  
Causal Effect ◽  
Real Data ◽  
Risk Difference ◽  
Causal Effects ◽  
Ratio Scale ◽  
Unmeasured Confounding ◽  
Range Of Values

Abstract Unmeasured confounding is an important threat to the validity of observational studies. A common way to deal with unmeasured confounding is to compute bounds for the causal effect of interest, that is, a range of values that is guaranteed to include the true effect, given the observed data. Recently, bounds have been proposed that are based on sensitivity parameters, which quantify the degree of unmeasured confounding on the risk ratio scale. These bounds can be used to compute an E-value, that is, the degree of confounding required to explain away an observed association, on the risk ratio scale. We complement and extend this previous work by deriving analogous bounds, based on sensitivity parameters on the risk difference scale. We show that our bounds can also be used to compute an E-value, on the risk difference scale. We compare our novel bounds with previous bounds through a real data example and a simulation study.

scholarly journals Causal Effect Between Total Cholesterol and HDL Cholesterol as Risk Factors for Chronic Kidney Disease: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Liu Miao ◽  
Yan Min ◽  
Chuan-Meng Zhu ◽  
Jian-Hong Chen ◽  
Bin Qi ◽  
...  
Keyword(s):  
Total Cholesterol ◽  
Serum Lipid ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Hdl Cholesterol ◽  
Causal Effects ◽  
Lipid Levels ◽  
Serum Lipid Levels ◽  
Genome Wide ◽  
Mr Study

Abstract Background/Aims: While observational studies show an association between serum lipid levels and cardiovascular disease (CVD), intervention studies that examine the preventive effects of serum lipid levels on the development of CKD are lacking. Methods: To estimate the role of serum lipid levels in the etiology of CKD, we conducted a two-sample Mendelian randomization (MR) study on serum lipid levels. Single nucleotide polymorphisms (SNPs), which were significantly associated genome-wide with plasma serum lipid levels from the GLGC and CKDGen consortium genome-wide association study (GWAS), including total cholesterol (TC, n = 187365), triglyceride (TG, n = 177861), HDL cholesterol (HDL-C, n = 187167), LDL cholesterol (LDL-C, n = 173082), apolipoprotein A1 (ApoA1, n = 20687), apolipoprotein B (ApoB, n = 20690) and CKD (n = 117165), were used as instrumental variables. None of the lipid-related SNPs was associated with CKD (all P > 0.05). Results: MR analysis genetically predicted the causal effect between TC/HDL-C and CKD. The odds ratio (OR) and 95% confidence interval (CI) of TC within CKD was 0.756 (0.579 to 0.933) (P = 0.002), and HDL-C was 0.85 (0.687 to 1.012) (P = 0.049). No causal effects between TG, LDL-C- ApoA1, ApoB and CKD were observed. Sensitivity analyses confirmed that TC and HDL-C were significantly associated with CKD. Conclusions: The findings from this MR study indicate causal effects between TC, HDL-C and CKD. Decreased TC and elevated HDL-C may reduce the incidence of CKD but need to be further confirmed by using a genetic and environmental approach.

scholarly journals Assessment of the health of medical students

2020 ◽  
Vol 64 (3) ◽  
pp. 132-138
Author(s):  
Anastasiya A. Khablova ◽  
Galina N. Bondar’ ◽  
Pavel F. Kiku ◽  
Natal’ya S. Tumanova ◽  
Valentina N. Rasskazova ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Status ◽  
Medical Students ◽  
Healthy Lifestyle ◽  
Well Being ◽  
Component Composition ◽  
The Body ◽  
Spiritual Well Being ◽  
Academic Workload ◽  
The Individual

Human health, in addition to social and spiritual well-being, is determined by its physical condition, which reflects the functional capabilities of the body, features of physical development and ensures working capacity in any activity, including academic workload, which is extremely important for students in higher educational institutions. The purpose of the study is to assess the health status of students at the School of Biomedicine of the Far Eastern Federal University. Material and methods. The health status of 184 medical students (147 young women and 37 young men) was assessed using a sociological survey (questionnaire) and a study of the component composition of the body using bioimpedancemetry. Results. The low physical activity, detected in 68% of students and bad habits (smoking tobacco) have been established to negatively affect students’ health. Among smokers, 75% of students live in dormitories on the university campus. According to the results of bioimpedancemetry, significant deviations from the age norm were noted in terms of body mass index (BMI) (50% of cases) and fat mass (FM) (71% of cases). Significant gender differences in the individual components of the body were not identified. Discussion. The most aggressive factors that significantly affect the health of students are unbalanced nutrition, lack of compliance with the regime of study and rest, lack of sleep and stay in the fresh air, lack of physical activity, lack of motivation for a healthy lifestyle. Significant deviations in BMI and FM, identified by bioimpedancemetry, indicate the risks of developing arterial hypertension, metabolic syndrome, and nutritional status disorders. Medical students need to give recommendations for increasing motor activity and changing diet. Conclusion. The results of the study can be used in the future to determine the functional state of students and develop preventive measures to preserve the health of medical students.

scholarly journals Education, intelligence and Alzheimer’s disease: Evidence from a multivariable two-sample Mendelian randomization study

2018 ◽  
Author(s):  
Emma L Anderson ◽  
Laura D Howe ◽  
Kaitlin H Wade ◽  
Yoav Ben-Shlomo ◽  
W. David Hill ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Univariate Analysis ◽  
Causal Effects ◽  
Training Interventions ◽  
Bidirectional Relationship ◽  
Years Of Schooling

AbstractObjectivesTo examine whether educational attainment and intelligence have causal effects on risk of Alzheimer’s disease (AD), independently of each other.DesignTwo-sample univariable and multivariable Mendelian Randomization (MR) to estimate the causal effects of education on intelligence and vice versa, and the total and independent causal effects of both education and intelligence on risk of AD.Participants17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer’s Project (IGAP) consortiumMain outcome measureOdds ratio of AD per standardised deviation increase in years of schooling and intelligenceResultsThere was strong evidence of a causal, bidirectional relationship between intelligence and educational attainment, with the magnitude of effect being similar in both directions. Similar overall effects were observed for both educational attainment and intelligence on AD risk in the univariable MR analysis; with each SD increase in years of schooling and intelligence, odds of AD were, on average, 37% (95% CI: 23% to 49%) and 35% (95% CI: 25% to 43%) lower, respectively. There was little evidence from the multivariable MR analysis that educational attainment affected AD risk once intelligence was taken into account, but intelligence affected AD risk independently of educational attainment to a similar magnitude observed in the univariate analysis.ConclusionsThere is robust evidence for an independent, causal effect of intelligence in lowering AD risk, potentially supporting a role for cognitive training interventions to improve aspects of intelligence. However, given the observed causal effect of educational attainment on intelligence, there may also be support for policies aimed at increasing length of schooling to lower incidence of AD.

scholarly journals CONCEPTUAL DIRECTIONS IN ORGANIZATION OF MEDICAL ASSISTANCE FOR CHILDREN IN THE CONDITIONS OF EDUCATION

2020 ◽  
Vol 73 (6) ◽  
pp. 1124-1128
Author(s):  
Georgii M. Danylenko ◽  
Tetiana V. Peresypkina ◽  
Antonina I. Butenko ◽  
Anna M. Peresypkina ◽  
Halyna I. Holubnycha ◽  
...  
Keyword(s):  
Health Status ◽  
Conceptual Model ◽  
Social Determinants ◽  
School Health ◽  
Healthy Lifestyle ◽  
Legal Framework ◽  
Educational Institutions ◽  
Medical Support ◽  
Medical Sector ◽  
Effective System

The aim of this work is: to define the Conceptual model of medical provision of children in educational institutions in modern conditions. Materials and methods: analysis of data from a longitudinal study of children’s health; questionnaire of parents, teachers, heads of educational institutions on the volume of medical support for students; questioning students’ lifestyle and social determinants of health. Results: According to the study has determined the medical and social determinants which negative affect on health status of school age childrens; detected the most appropriate types of of school health services which based on the parents, medical and teachers opinion. The important also is monitoring of health status of children for develop of prevent measure for improove health status and forming of healthy lifestyle behavioral. Problematic issues to be addressed include: improving the legal framework on the competences and volumes of health care for pupils in educational institutions; material equipment; setting up a system for monitoring and analyzing the health status of students and educational groups, identifying health risk factors; establishing a continuous multimodal health-oriented system of student-oriented youth behavior. Conclusions: The health status of students and the level of health-oriented behavior, the reform of the medical sector require introduction of an effective system of medical support for students of organized groups, improving the system of preventive care for students, parents, which is presented in the Conceptual model.

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