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PubMed1997

Mutations in the COL5A1 gene are causal in the Ehlers-Danlos syndromes I and II.

The Ehlers-Danlos syndrome (EDS) is a heterogeneous connective-tissue disorder of which at least nine subtypes are recognized. Considerable clinical overlap exists between the EDS I and II subtypes, suggesting that both are allelic disorders. Recent evidence based on linkage and transgenic mice studies suggest that collagen V is causally involved in human EDS. Collagen V forms heterotypic fibrils with collagen I in many tissues and plays an important role in collagen I fibrillogenesis. We have identified a mutation in COL5A1, the gene encoding the pro(alpha)1(V) collagen chain, segregating with EDS I in a four-generation family. The mutation causes the substitution of the most 5' cysteine residue by a serine within a highly conserved sequence of the pro(alpha)1(V) C-propeptide domain and causes reduction of collagen V by preventing incorporation of the mutant pro(alpha)1(V) chains in the collagen V trimers. In addition, we have detected splicing defects in the COL5A1 gene in a patient with EDS I and in a family with EDS II. These findings confirm the causal role of collagen V in at least a subgroup of EDS I, prove that EDS I and II are allelic conditions, and represent a, so far, unique example of a human collagen disorder caused by substitution of a highly conserved cysteine residue in the C-propeptide domain of a fibrillar collagen.

Adolescent↗

PubMed1994

Incorporating trend data to aid in the causal interpretation of individual-level correlations among variables: examples focusing on the recent decline in marijuana use.

Given the close correspondence of several trends beginning in 1979, it is tempting to conclude that increases in perceived risk and disapproval led to the decline in actual use of marijuana. In this chapter, two alternative interpretations are considered, reflecting different hypotheses about individual-level causal processes: (1) changes in use led to the changes in attitudes, or (2) changes in some other factor(s) (e.g., increased "conventionality") caused both changes in use and changes in attitudes. This chapter documents a series of analyses designed to untangle such issues by incorporating trend data along with individual-level, cross-sectional relationships. One analysis strategy shows that controlling attitudes could "account for" the time trend in marijuana use, whereas the reverse is not true. The second analysis strategy examines how time trends in marijuana use are affected by multivariate controls for attitudes, as well as other individual characteristics, and shows that only the attitude measures can "explain" the time trend in marijuana use. Although these analyses are viewed as helping to explain the recent secular trend downward in marijuana use, as well as the still more recent decline in cocaine use, their most important contribution to prevention intervention research may be that they support a very basic generalization about individual-level causal processes: individual attitudes about specific drugs affect individuals use of those drugs.

Adolescent↗

PubMed1997

[Air pollution and health--causal criteria in environmental epidemiology].

The evidence for the adverse health effects of today's "normal" air pollution relies heavily on epidemiologic studies. Given the major impact of these effects on environmental, economic and social policy, the causality of epidemiologic findings becomes a central issue. The scientific process of establishing causality based on the air pollution epidemiology literature is reviewed. It consists of two steps: first, the quality and validity of each epidemiologic study must be rigorously assessed (design, selection, confounding); second, the overall evidence across all valid studies must be appraised. Of major importance are the consistency of results between replicate studies and the coherence of effects across a variety of different pathophysiologically or logically interrelated epidemiologic health outcomes, such as respiratory symptoms, exacerbations of respiratory diseases, use of health care, sick absenteeism, or, among the most sensitive subjects, mortality. Demonstration of a dose-response association is crucial and has been shown in many studies. Valid studies may use varied indicators of the air pollution mixtures, such as particulate matter, NO2, SO2, or others. However, epidemiology is incapable of investigating the biologic pathophysiologic mechanisms, which require experimental studies. Such studies may increase the biologic plausibility of epidemiologic findings. Given the common sources of many of the air pollution indicators used in epidemiology, a knowledge of pathophysiologic mechanisms is not a prerequisite for public health action aimed at improving air quality in cities.

Air Pollution↗

PubMedDate not supplied

[Emotions, stress, smoking, alcohol consumption and cancer--the correlational and causal connections].

Correlative and causal relationships are discussed between emotions, stress, smoking, drinking, and cancer. The following conclusions have been drawn. Emotions control the physiological stress reactions: the negative emotions initiate and maintain stress, and positive emotions stop it. A dissatisfied need provokes the development of the state of emotional stress. There are two types of emotional stress states: the active stress which is directed to "overcoming" and the passive state of "waiting till the stress is over". Individuals differ in emotionality, stress reactivity, and inclination to the active and passive emotional stress. The passive emotional stress increases the probability of cancer. This effect is caused by the development of the hormonal and neurotransmitter state, which provokes immunosuppression, DNA damage, and stimulation of hemopoiesis. Smoking and drinking are the ways of modifying the psychoemotional state. These habits as well as development of cancer are the effects of the same cause--stress. Thus, cases of correlation between smoking and drinking do not reflect the causal relationships. Only intensive smoking and drinking which lead to tissue damage can increase the incidence of cancer.

Adaptation, Physiological↗

PubMed1997

Causal probabilistic network and power spectral estimation used in sleep stage classification.

A new method for sleep-stage classification using a causal probabilistic network as automatic classifier has been implemented and validated. The system uses features from the primary sleep signals from the brain (EEG) and the eyes (AOG) as input. From the EEG, features are derived containing spectral information which is used to classify power in the classical spectral bands, sleep spindles and K-complexes. From AOG, information on rapid eye movements is derived. Features are extracted every 2 seconds. The CPN-based sleep classifier was implemented using the HUGIN system, an application tool to handle causal probabilistic networks. The results obtained using different training approaches show agreements ranging from 68.7 to 70.7% between the system and the two experts when a pooled agreement is computed over the six subjects. As a comparison, the interrater agreement between the two experts was found to be 71.4%, measured also over the six subjects.

Adult↗

PubMed1999

Causal diagrams for epidemiologic research.

Causal diagrams have a long history of informal use and, more recently, have undergone formal development for applications in expert systems and robotics. We provide an introduction to these developments and their use in epidemiologic research. Causal diagrams can provide a starting point for identifying variables that must be measured and controlled to obtain unconfounded effect estimates. They also provide a method for critical evaluation of traditional epidemiologic criteria for confounding. In particular, they reveal certain heretofore unnoticed shortcomings of those criteria when used in considering multiple potential confounders. We show how to modify the traditional criteria to correct those shortcomings.

Epidemiologic Methods↗

PubMed2003

Adverse childhood experiences and self-reported liver disease: new insights into the causal pathway.

OBJECTIVE: To examine the relationship of adverse childhood experiences (ACEs), including abuse, neglect, and forms of household dysfunction, to the risk of liver disease by assessing the role of risk behaviors, such as substance abuse and high-risk sexual activity, as mediators of the ACEs-liver disease relationship. METHODS: Retrospective cohort study data were collected from 17 337 adult health plan members through a survey. Logistic regression adjusted for age, sex, race, and education was used to estimate the strength of the ACEs-liver disease relationship and the impact of the mediators in this relationship. RESULTS: Each of 10 ACEs increased the risk of liver disease 1.2 to 1.6 times (P<.001). The number of ACEs (ACE score) had a graded relationship to liver disease (P<.001). Compared with persons with no ACEs, the adjusted odds ratio of ever having liver disease among persons with 6 or more ACEs was 2.6 (P<.001). The ACE score also had a strong graded relationship to risk behaviors for liver disease. The strength of the ACEs-liver disease association was reduced 38% to 50% by adjustment for these risk behaviors, suggesting they are mediators of this relationship. CONCLUSIONS: The ACE score showed a graded relationship to the risk of liver disease that appears to be mediated substantially by behaviors that increase the risk of viral and alcohol-induced liver disease. Understanding the effect of ACEs on the risk of liver disease and development of these behaviors provides insight into causal pathways, which may prove useful in the prevention of liver disease.

Alcohol Drinking↗

PubMed1999

A threshold causal model for clinical trials with departures from intended treatment.

Randomized clinical trials often are planned to study a specific intervention. However, the collection of data on treatment actually received often reveals variable levels of treatment exposure (or 'dose') across subjects, due to non-compliance or other reasons. This paper presents a new method, using such 'dose' data as well as control group responses, to assess a causal dose-response relationship. The specific model utilizes a threshold function and incorporates a random effect term to allow for heterogeneous treatment responses among subjects. Further modelling of the random effects allows for reduction of error variance and control for potential confounders. The threshold dose is estimated using a residual variance criterion based on a transformed model. Estimates of standard errors and confidence intervals are obtained using a bootstrap procedure. The method is applied to data from an AIDS clinical trial. A simulation study demonstrates the adequacy of the threshold estimates for particular sample sizes and error variances. The limitations of this essentially exploratory method, as well as some possible extensions, are discussed. Published in 1999 by John Wiley & Sons, Ltd. This article is a US Government Work and is in the public domain in the United States.

CD4 Lymphocyte Count↗

PubMed2006

Insights into different results from different causal contrasts in the presence of effect-measure modification.

PURPOSE: Both propensity score (PS) matching and inverse probability of treatment weighting (IPTW) allow causal contrasts, albeit different ones. In the presence of effect-measure modification, different analytic approaches produce different summary estimates. METHODS: We present a spreadsheet example that assumes a dichotomous exposure, covariate, and outcome. The covariate can be a confounder or not and a modifier of the relative risk (RR) or not. Based on expected cell counts, we calculate RR estimates using five summary estimators: Mantel-Haenszel (MH), maximum likelihood (ML), the standardized mortality ratio (SMR), PS matching, and a common implementation of IPTW. RESULTS: Without effect-measure modification, all approaches produce identical results. In the presence of effect-measure modification and regardless of the presence of confounding, results from the SMR and PS are identical, but IPTW can produce strikingly different results (e.g., RR = 0.83 vs. RR = 1.50). In such settings, MH and ML do not estimate a population parameter and results for those measures fall between PS and IPTW. CONCLUSIONS: Discrepancies between PS and IPTW reflect different weighting of stratum-specific effect estimates. SMR and PS matching assign weights according to the distribution of the effect-measure modifier in the exposed subpopulation, whereas IPTW assigns weights according to the distribution of the entire study population. In pharmacoepidemiology, contraindications to treatment that also modify the effect might be prevalent in the population, but would be rare among the exposed. In such settings, estimating the effect of exposure in the exposed rather than the whole population is preferable.

Bias↗

PubMed1996

Causal attribution as a search for underlying mechanisms: an explanation of the conjunction fallacy and the discounting principle.

We propose that causal attribution involves searching for underlying mechanism information (i.e., the processes underlying the relationship between the cause and the effect). This processing account can explain both the conjunction effect (i.e., conjunctive explanations being rated more probable than their components) and the discounting effect (i.e., the effect of one cause being discounted when another cause is already known to be true). When two explanations cohere with respect to a single mechanism, they would be judged to be more likely than a single explanation which partly supports that mechanism. When the two explanations imply two separate mechanisms, one would be discounted. In Experiment 1, both effects occurred with mechanism-based explanations but not with covariation-based explanations in which the cause-effect relationship was phrased in terms of statistical covariations without referring to mechanisms. In Experiments 2 and 3, the amount of the discounting and conjunction effects varied depending on the relationships between specific mechanisms in the two given explanations. We discuss why the current results pose difficulties for previous attribution models.

Causality↗

PubMed2002

Developmental and content effects in reasoning with causal conditionals.

Two predictions derived from Markovits and Barrouillet's (2001) developmental model of conditional reasoning were tested in a study in which 72 twelve-year-olds, 80 fifteen-year-olds, and 104 adults received a paper-and-pencil test of conditional reasoning with causal premises ("if cause P then effect Q"). First, we predicted that conditional premises would induce more correct uncertainty responses to the Affirmation of the consequent and Denial of the antecedent forms when the antecedent term is weakly associated to the consequent than when the two are strongly associated and that this effect would decrease with age. Second, uncertainty responding to the Denial of the antecedent form ("P is not true") should be easier when the formulation of the minor premise invites retrieval of alternate antecedents ("if something other than P is true"). The results were consistent with the hypotheses and indicate the importance of retrieval processes in understanding developmental patterns in conditional reasoning with familiar premises.

Adolescent↗

PubMed1997

Is there a causal relationship between alcohol use and violence? A synthesis of evidence.

This chapter reviews the evidence bearing on the question of whether those individuals who consume alcohol have an increased probability of subsequent violent behavior. Four bodies of relevant research are examined: experimental studies with animals, experimental studies with humans, individual-level correlational studies, and macro-level correlational studies. All these research approaches provide some evidence of an association between alcohol consumption and violent behavior, but no firm conclusion can be drawn about whether alcohol plays a causal role in such behavior. Various limitations, deficiencies, and ambiguities of available research that contribute to this state of affairs are discussed.

Alcohol Drinking↗

PubMed1999

Environmental tobacco smoke and ischaemic heart disease: a case study in applying causal criteria.

BACKGROUND: Whether ischaemic heart disease (IHD) is caused by exposure to environmental tobacco smoke (ETS), commonly known as "passive smoking", has been debated from both epidemiological and biological perspectives. METHODS AND RESULTS: In this paper we use Bradford Hill criteria to synthesize results from the biological and epidemiological literature in a formal assessment of the strength of support for such a relationship. Although we find that these criteria, designed for clinical trials, do not give an ideal framework for assessment of epidemiological and biological studies, nevertheless they do provide systematic guidance for this assessment. For the general population, of the nine tests proposed by Hill we find that one (biological plausibility) seems to be supported, though not unarguably; three (strength, consistency. specificity) appear to fail by accepted standards; and the remaining five have insufficient data for a clear evaluation (biological gradient, experimental evidence, temporality, coherence, analogy). Overall, this provides at best weak support for a causal association between ETS and IHD across the general community. Conversely, there appears to be more support, especially in the biology studies, for an association between ETS and IHD for those with preexisting disease, although epidemiological studies are limited in this area. CONCLUSIONS: One of the outcomes of this review is the identification of areas of focus for future epidemiological and biological research. First, we find that stronger associations may be found in the particular subpopulation with pre-existing IHD. In this case, more convincing biological plausibility and experimental evidence indicate a need for relevant epidemiological studies, although individual responses are very variable. Second, we identify the need for further, more detailed evaluations of the nature of vessel wall thickenings occurring in experimental models of ETS exposure. Third, we propose long-term animal studies of initiation of IHD, including direct assessment of effects on the accumulation of lipid in vessel walls, at appropriate ETS exposure levels.

Air Pollution, Indoor↗

PubMed2003

Causality in epidemiology.

Epidemiology represents an interesting and unique example of cross-fertilization between social and natural sciences. Epidemiology has evolved from a monocausal to a multicausal concept of the "web of causation", thus mimicking a similar and much earlier shift in the social sciences. However, in comparison with the social sciences epidemiology is both more sensitive to underlying biological models (which condition the interpretation of population findings), and more prone to a simplification of the causal pathways. Paradoxically, epidemiology has developed more sophisticated theoretical models for bias and confounding than the social sciences did, but for the practical purpose of identifying single preventable risk factors. Epidemiology makes use more often of study designs that simulate experimentation, than of surveys in the general population.

Bias↗

PubMed2003

Issues of causality in the history of occupational epidemiology.

Occupational epidemiology has its roots in classical medicine. However, it became a quantitative discipline only in the 20th century, through the pioneering work of individuals such as Case, Lloyd, and Selikoff and organizations such as the Division of Occupational Health of the U.S. Public Health Service. Studies of chemical dye workers, bituminous coal miners, smelting workers, and uranium miners have been especially important sources of innovations in methodology and in development of logical reasoning leading to acceptance of causal relationships of occupational exposures that lead to respiratory diseases and cancer. The cooperation of labor unions, such as those of steel and asbestos workers, has often been a crucial factor in providing essential data.

Causality↗

PubMed2003

[Occupational disease 2108. Degenerative changes of the cervical spine as a causality criterion in the assessment of discogenic diseases according to BeKV 2108].

With the second amendment to the Ordinance on Occupational Diseases (BeKV) of 18 December 1992, discogenic diseases of the spine are included in the disease register of occupational diseases for the first time. If occupations that impose stress on the spine have been practised for many years, the possibility exists of recognizing degenerative diseases as an occupational disease. In assessment practice, the radiological data on the spine exposed to stress is compared with that of regions which are remote from the stress (cervical/thoracic spine). This pattern of the distribution of degenerative disease is then used as the basis for determining a causal relationship between the occupation causing the stress and disease of the axial skeleton. The pattern of degeneration of the cervical spine was investigated in two groups, one with ( n =153) and one without ( n =333) occupations that impose stress on the lumbar spine. A cumulative score of degenerative changes was elaborated and presented as a new classification. No differences were found between the groups with regard to either the frequency of occurrence, segmental distribution or severity of disease. In both groups, degenerative changes correlated with age. The prevailing assessment practice is discussed on the basis of these data.

Adult↗

PubMed2005

[The causal relationship between dissociation and trauma. A critical review].

This article discusses the accepted view that trauma causes dissociation. We critically evaluate studies that explored this relationship and discuss their shortcomings. In addition, individual differences related to dissociative experiences are discussed. In doing so, we focus on their potential to create pseudo-correlations between dissociative symptoms and self-reports of childhood trauma. After concluding that the causal link between trauma and dissociation is far from self-evident or empirically substantiated, we suggest some avenues for further research.

Adult↗

PubMed2006

The relationship between health care expenditure and health outcomes. Evidence and caveats for a causal link.

The relationship between health care expenditure and health outcomes is of interest to policy makers in the light of steady increases in health care spending for most industrialised countries. However, establishing causal relationships is complex because, firstly, health care expenditure is only one of many quantitative and qualitative factors that contribute to health outcomes, and, secondly, measurement of health status is an imperfect process. This study reviews key findings and methodological approaches in this field and reports the results of our own empirical study of countries of the European Union. Our analysis examines life expectancy and infant mortality as the 'output' of the health care system, and various life-style, environmental and occupational factors as 'inputs'. Econometric analyses using a fixed effects model are conducted on a panel data set for the former 15 members of the European Union over the period 1980-1995. The findings show that increases in health care expenditure are significantly associated with large improvements in infant mortality but only marginally in relation to life expectancy. The findings are generally consistent with those of several previous studies. Caveats and improvements for future research are presented.

Causality↗