scholarly journals Sensitivity analysis for an unmeasured confounder: a review of two independent methods

2010 ◽  
Vol 13 (2) ◽  
pp. 188-198 ◽  
Author(s):  
Ronir Raggio Luiz ◽  
Maria Deolinda Borges Cabral
Keyword(s):  
Sensitivity Analysis ◽  
Causal Inference ◽  
Observational Studies ◽  
Experimental Studies ◽  
Epidemiological Studies ◽  
Strong Constraint ◽  
Unmeasured Confounder ◽  
Direct Sensitivity ◽  
Hidden Biases ◽  
The Impact

One of the main purposes of epidemiological studies is to estimate causal effects. Causal inference should be addressed by observational and experimental studies. A strong constraint for the interpretation of observational studies is the possible presence of unobserved confounders (hidden biases). An approach for assessing the possible effects of unobserved confounders may be drawn up through the use of a sensitivity analysis that determines how strong the effects of an unmeasured confounder should be to explain an apparent association, and which should be the characteristics of this confounder to exhibit such an effect. The purpose of this paper is to review and integrate two independent sensitivity analysis methods. The two methods are presented to assess the impact of an unmeasured confounder variable: one developed by Greenland under an epidemiological perspective, and the other developed from a statistical standpoint by Rosenbaum. By combining (or merging) epidemiological and statistical issues, this integration became a more complete and direct sensitivity analysis, encouraging its required diffusion and additional applications. As observational studies are more subject to biases and confounding than experimental settings, the consideration of epidemiological and statistical aspects in sensitivity analysis strengthens the causal inference.

scholarly journals A Systematic Review of Research Investigating the Combined Ecological Impact of Anthropogenic Noise and Artificial Light at Night

2021 ◽  
Vol 9 ◽  
Author(s):  
Wouter Halfwerk ◽  
Paul Jerem
Keyword(s):  
Systematic Review ◽  
Observational Studies ◽  
Ecological Impact ◽  
Experimental Studies ◽  
Ecological Impacts ◽  
Anthropogenic Noise ◽  
Light Pollution ◽  
Artificial Light ◽  
Light At Night ◽  
The Impact

Levels of anthropogenic noise and artificial light at night (ALAN) are rapidly rising on a global scale. Both sensory pollutants are well known to affect animal behavior and physiology, which can lead to substantial ecological impacts. Most studies on noise or light pollution to date have focused on single stressor impacts, studying both pollutants in isolation despite their high spatial and temporal co-occurrence. However, few studies have addressed their combined impact, known as multisensory pollution, with the specific aim to assess whether the interaction between noise and light pollution leads to predictable, additive effects, or less predictable, synergistic or antagonistic effects. We carried out a systematic review of research investigating multisensory pollution and found 28 studies that simultaneously assessed the impact of anthropogenic noise and ALAN on animal function (e.g., behavior, morphology or life-history), physiology (e.g., stress, oxidative, or immune status), or population demography (e.g., abundance or species richness). Only fifteen of these studies specifically tested for possible interactive effects when both sensory pollutants were combined. Four out of eight experimental studies revealed a significant interaction effect, in contrast to only three out seven observational studies. We discuss the benefits and limitations of experimental vs. observational studies addressing multisensory pollution and call for more specific testing of the diverse ways in which noise and light pollution can interact to affect wildlife.

Road Safety and Mobile Phone Behaviors

2015 ◽  
pp. 1356-1365
Author(s):  
Junaid Ahmad Bhatti
Keyword(s):  
Mobile Phone ◽  
Road Safety ◽  
Motor Vehicle ◽  
Experimental Studies ◽  
Epidemiological Studies ◽  
Mobile Phone Use ◽  
Vehicle Collision ◽  
Safety Risks ◽  
Lane Position ◽  
The Impact

Mobile phone use while driving is one of the major road safety risks. In surveys from different settings, the rate of mobile phone use while driving ranged from 1 to 11%. Literature from observational and experimental studies show that driving capacities such as reacting to traffic hazards, maintaining a central lane position, maintaining a safe distance and speed are negatively affected when using a mobile phone while driving. Several epidemiological studies suggest that motor vehicle collision risks increase by two to nine times when using a mobile phone (handheld or hands-free) compared to not using the phone while driving. Considering these findings, almost three-quarters of the countries have adopted legislation banning the use of handheld mobile phone devices while driving. These interventions, however, are insufficient to deal with the use of hands-free mobile phones while driving and texting which are challenging to ascertain and prevent. Currently, “in-vehicle” and collision avoidance technologies are being evaluated to further reduce the impact of these road menaces in our society.

Insulin and cognitive function in humans: experimental data and therapeutic considerations

2005 ◽  
Vol 33 (5) ◽  
pp. 1037-1040 ◽  
Author(s):  
M.W.J. Strachan
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Function ◽  
Memory Function ◽  
Experimental Studies ◽  
Epidemiological Studies ◽  
Therapeutic Benefit ◽  
Systemic Absorption ◽  
Intravenous Insulin ◽  
People With Dementia ◽  
The Impact

Data from experimental studies in animals and from epidemiological studies in humans suggest a link between insulin and cognitive performance. Do these results translate into clinical and therapeutic benefit for people with cognitive impairment? Insulin injected peripherally can readily cross the blood–brain barrier. Intravenous insulin can improve aspects of cognitive function in healthy adults and in individuals with Alzheimer's dementia. Moreover, intravenous insulin increases concentrations of a long form of β-amyloid protein, Aβ42. One potential confounding factor with these data, however, is the need for co-administration of glucose with the insulin to maintain euglycaemia as glucose itself can facilitate memory function. Administration of insulin via the intranasal route is scientifically (and therapeutically) more attractive because the insulin goes directly to the cerebrospinal fluid, with minimal systemic absorption; this obviates the need for a glucose infusion. Intranasal insulin may improve some aspects of memory in healthy individuals, but has yet to be studied in people with cognitive impairment. TZDs (thiazolidinediones) reduce peripheral insulin concentrations by enhancing insulin sensitivity. In adults with Type II (non-insulin-dependent) diabetes, TZD therapy improves memory function, but so does sulphonylurea therapy (which elevates peripheral insulin concentrations). Improved memory is linked to lower blood glucose concentrations, rather than altered insulin levels. However, major trials are currently under way examining the impact of TZDs in people with dementia.

scholarly journals Use of sensitivity analysis to assess the effects on anti-hepatitis A virus antibodies of access to household water supply

2007 ◽  
Vol 136 (3) ◽  
pp. 334-340 ◽  
Author(s):  
M. D. B. CABRAL ◽  
R. R. LUIZ
Keyword(s):  
Sensitivity Analysis ◽  
Water Supply ◽  
Hepatitis A ◽  
Hepatitis A Virus ◽  
Confounding Variable ◽  
Unmeasured Confounder ◽  
External Adjustment ◽  
Household Water ◽  
The Impact ◽  
Positive Results

SUMMARYThe objective of this study was to assess the impact of a possible unmeasured confounding variable in a previously published association between the effects of household water supply and positive results for hepatitis A serology. This was estimated using a path of integration between two methods of sensitivity analysis, called Rosenbaum's method and Greenland's external adjustment. The association between household water supply and positive results for hepatitis A (outcome) serology was insensitive to confounding unless the odds ratio for the association between the confounder and the outcome was ⩾4. The integration of the two sensitivity analysis methods presented proved useful when assessing the effects of a potential unmeasured confounder.

scholarly journals Volatile organic compounds and risk of asthma and allergy: a systematic review

2015 ◽  
Vol 24 (135) ◽  
pp. 92-101 ◽  
Author(s):  
Ulugbek B. Nurmatov ◽  
Nara Tagiyeva ◽  
Sean Semple ◽  
Graham Devereux ◽  
Aziz Sheikh
Keyword(s):  
Systematic Review ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Experimental Studies ◽  
Evidence Base ◽  
Epidemiological Studies ◽  
Poor Quality ◽  
Volatile Organic ◽  
Asthma And Allergy ◽  
The Impact

Volatile organic compounds (VOCs) are ubiquitous domestic pollutants. Their role in asthma/allergy development and exacerbations is uncertain. This systematic review investigated whether domestic VOC exposure increases the risk of developing and/or exacerbating asthma and allergic disorders.We systematically searched 11 databases and three trial repositories, and contacted an international panel of experts to identify published and unpublished experimental and epidemiological studies.8455 potentially relevant studies were identified; 852 papers were removed after de-duplication, leaving 7603 unique papers that were screened. Of these, 278 were reviewed in detail and 53 satisfied the inclusion criteria. Critical appraisal of the included studies indicated an overall lack of high-quality evidence and substantial risk of bias in this body of knowledge. Aromatics (i.e. benzenes, toluenes and xylenes) and formaldehyde were the main VOC classes studied, both in relation to the development and exacerbations of asthma and allergy. Approximately equal numbers of studies reported that exposure increased risks and that exposure was not associated with any detrimental effects.The available evidence implicating domestic VOC exposure in the risk of developing and/or exacerbating asthma and allergy is of poor quality and inconsistent. Prospective, preferably experimental studies, investigating the impact of reducing/eliminating exposure to VOC, are now needed in order to generate a more definitive evidence base to inform policy and clinical deliberations in relation to the management of the now substantial sections of the population who are either at risk of developing asthma/allergy or living with established disease.

scholarly journals Assess the Application of the E-Value in the Unmeasured Confounder Evaluation of Observational Pharmaceutical Studies

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lihong Huang ◽  
Jianbing Ma ◽  
Xiaochun Qiu ◽  
Tao Suo
Keyword(s):  
Public Health ◽  
Sensitivity Analysis ◽  
Lower Bound ◽  
Confidence Interval ◽  
Effect Size ◽  
Observational Studies ◽  
Relative Effect ◽  
Analysis Tool ◽  
Unmeasured Confounder ◽  
Unmeasured Confounders

Public health is very important in big cities, and data analysis on public health studies is always a demanding issue that determines the study effectiveness. E-value was proposed as a standard sensitivity analysis tool to assess unmeasured confounders in observational studies, but its value is doubted. To evaluate the usefulness of E-value, in this paper, we collected 368 observational studies on drug effectiveness evaluation published from 1998 to September 2019 (out of 3426 searched studies) and evaluated the features of E-value. We selected the effects of primary outcomes or the largest effects in terms of hazard ratio, risk ratio, or odds ratio. Effects were transformed into estimated effect sizes following a standard E-value computation. In all 368 studies, the disease with the highest percentage was infections and infestations, at 21.7% (80/368). Our results showed that the median relative effect size was 1.89 (Q1-Q3: 1.41–2.95), and the corresponding median E-value was 3.19 with 95% confidence interval lower bound 1.77. Smaller studies yielded larger E-values for the effect size estimate and the relationship was considerably attenuated when considering the E-value for the lower bound of 95% confidence interval on the effect size. Notably, E-values have a monotonic, almost linear relationship with effect estimates. We found that E-value may cause misimpressions on the unmeasured confounder, and the same E-value does not reflect the varying nature of the unmeasured confounders in different studies, and there lacks a guidance on how E-value can be deemed as small or large, all of which limits the capability of E-value as a standard sensitivity analysis tool in real applications.

scholarly journals A note on a sensitivity analysis for unmeasured confounding, and the related E-value

2020 ◽  
Vol 8 (1) ◽  
pp. 229-248
Author(s):  
Arvid Sjölander
Keyword(s):  
Sensitivity Analysis ◽  
Observational Studies ◽  
Real Data ◽  
Feasible Region ◽  
Maximal Strength ◽  
Unmeasured Confounding ◽  
Unmeasured Confounder ◽  
Two Parameters ◽  
Strength Of Association

Abstract Unmeasured confounding is one of the most important threats to the validity of observational studies. In this paper we scrutinize a recently proposed sensitivity analysis for unmeasured confounding. The analysis requires specification of two parameters, loosely defined as the maximal strength of association that an unmeasured confounder may have with the exposure and with the outcome, respectively. The E-value is defined as the strength of association that the confounder must have with the exposure and the outcome, to fully explain away an observed exposure-outcome association. We derive the feasible region of the sensitivity analysis parameters, and we show that the bounds produced by the sensitivity analysis are not always sharp. We finally establish a region in which the bounds are guaranteed to be sharp, and we discuss the implications of this sharp region for the interpretation of the E-value. We illustrate the theory with a real data example and a simulation.

scholarly journals On the use of the E-value for sensitivity analysis in epidemiologic studies

2021 ◽  
Vol 37 (6) ◽  
Author(s):  
Conceição Christina Rigo Vale ◽  
Nubia Karla de Oliveira Almeida ◽  
Renan Moritz Varnier Rodrigues de Almeida
Keyword(s):  
Sensitivity Analysis ◽  
Prenatal Care ◽  
Low Birthweight ◽  
Epidemiological Studies ◽  
Epidemiologic Studies ◽  
Sensitivity Index ◽  
Analysis Tool ◽  
Causal Inferences ◽  
Unmeasured Confounder ◽  
Increased Risk

Abstract: This study illustrates the use of a recently developed sensitivity index, the E-value, helpful in strengthening causal inferences in observational epidemiological studies. The E-value aims to determine the minimum required strength of association between an unmeasured confounder and an exposure/outcome to explain the observed association as non-causal. Such parameter is defined as E - v a l u e = R R + R R R R - 1, where RR is the risk ratio between the exposure and the outcome. Our work illustrates the E-value using observational data from a recently published study on the relationship between indicators of prenatal care adequacy and the outcome low birthweight. The E-value ranged between 1.45 and 5.63 according to the category and prenatal care index evaluated, showing the highest value for the “no prenatal care” category of the GINDEX index and the minimum value for “intermediate prenatal care” of the APNCU index. For “inappropriate prenatal care” (all indexes), the E-value ranged between 2.76 (GINDEX) and 4.99 (APNCU). These findings indicate that only strong confounder/low birthweight associations (more than 400% increased risk) would be able to fully explain the prenatal care vs. low birthweight association observed. The E-value is a useful, intuitive sensitivity analysis tool that may help strengthening causal inferences in epidemiological observational studies.

scholarly journals The impact of outdoor air pollution on COVID-19: a review of evidence from in vitro, animal, and human studies

2021 ◽  
Vol 30 (159) ◽  
pp. 200242
Author(s):  
Thomas Bourdrel ◽  
Isabella Annesi-Maesano ◽  
Barrak Alahmad ◽  
Cara N. Maesano ◽  
Marie-Abèle Bind
Keyword(s):  
Air Pollution ◽  
Uv Radiation ◽  
Air Pollutants ◽  
Experimental Studies ◽  
Population Level ◽  
Epidemiological Studies ◽  
Human Studies ◽  
The Impact

Studies have pointed out that air pollution may be a contributing factor to the coronavirus disease 2019 (COVID-19) pandemic. However, the specific links between air pollution and severe acute respiratory syndrome-coronavirus-2 infection remain unclear. Here we provide evidence from in vitro, animal and human studies from the existing literature. Epidemiological investigations have related various air pollutants to COVID-19 morbidity and mortality at the population level, however, those studies suffer from several limitations. Air pollution may be linked to an increase in COVID-19 severity and lethality through its impact on chronic diseases, such as cardiopulmonary diseases and diabetes. Experimental studies have shown that exposure to air pollution leads to a decreased immune response, thus facilitating viral penetration and replication. Viruses may persist in air through complex interactions with particles and gases depending on: 1) chemical composition; 2) electric charges of particles; and 3) meteorological conditions such as relative humidity, ultraviolet (UV) radiation and temperature. In addition, by reducing UV radiation, air pollutants may promote viral persistence in air and reduce vitamin D synthesis. Further epidemiological studies are needed to better estimate the impact of air pollution on COVID-19. In vitro and in vivo studies are also strongly needed, in particular to more precisely explore the particle–virus interaction in air.

Challenges in Measuring the Impact of Interruption on Patient Safety and Workflow Outcomes

2011 ◽  
Vol 50 (05) ◽  
pp. 447-453 ◽  
Author(s):  
S. Y. W. Li ◽  
A. G. Dunn ◽  
E. Coeira ◽  
F. Magrabi
Keyword(s):  
Patient Safety ◽  
Observational Studies ◽  
Computational Models ◽  
Experimental Studies ◽  
Primary Task ◽  
Electronic Prescribing ◽  
Time On Task ◽  
Specific Effects ◽  
Multiple Variables ◽  
The Impact

SummaryObjective: To examine the problem of studying interruption in healthcare.Methods: Review of the interruption literature from psychology, human-computer interaction; experimental studies of electronic prescribing and error behaviour; observational studies in emergency and intensive care.Results: Primary task and interruption variables which contribute to the outcomes of an interruption include the type of task (primary and interrupting task); point of interruption; duration of interruption; similarity of interruptive task to primary task; modality of interruption; environmental cues; and interruption handling strategy. Effects of interruption on task performance can be examined by measuring errors, the time on task, interruption lag and resumption lag.Conclusions: Interruptions are a complex phenomenon where multiple variables including the characteristics of primary tasks, the interruptions themselves, and the environment may influence patient safety and work-flow outcomes. Observational studies present significant challenges for recording many of the process variables that influence the effects of interruptions. Controlled experiments provide an opportunity to examine the specific effects of variables on errors and efficiency. Computational models can be used to identify the situations in which interruptions to clinical tasks could be disruptive and to investigate the aggregate effects of interruptions.

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