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Triangulation in aetiological epidemiology.

ABSTRACT: Triangulation is the practice of obtaining more reliable answers to research questions through integrating results from several different approaches, where each approach has different key sources of potential bias that are unrelated to each other. With respect to causal questions in aetiological epidemiology, if the results of different approaches all point to the same conclusion, this strengthens confidence in the finding. This is particularly the case when the key sources of bias of some of the approaches would predict that findings would point in opposite directions if they were due to such biases. Where there are inconsistencies, understanding the key sources of bias of each approach can help to identify what further research is required to address the causal question. The aim of this paper is to illustrate how triangulation might be used to improve causal inference in aetiological epidemiology. We propose a minimum set of criteria for use in triangulation in aetiological epidemiology, summarize the key sources of bias of several approaches and describe how these might be integrated within a triangulation framework. We emphasize the importance of being explicit about the expected direction of bias within each approach, whenever this is possible, and seeking to identify approaches that would be expected to bias the true causal effect in different directions. We also note the importance, when comparing results, of taking account of differences in the duration and timing of exposures. We provide three examples to illustrate these points.

SUBMITTER: Lawlor DA

PROVIDER: S-EPMC5841843 | biostudies-other | 2016 Dec

REPOSITORIES: biostudies-other

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Triangulation in aetiological epidemiology.

Lawlor Debbie A DA Tilling Kate K Davey Smith George G

International journal of epidemiology 20161201 6

Triangulation is the practice of obtaining more reliable answers to research questions through integrating results from several different approaches, where each approach has different key sources of potential bias that are unrelated to each other. With respect to causal questions in aetiological epidemiology, if the results of different approaches all point to the same conclusion, this strengthens confidence in the finding. This is particularly the case when the key sources of bias of some of th ...[more]

PMID: 28108528

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Project description:Genetic studies of human diseases have identified many variants associated with pathogenesis and severity. However, most studies have used only statistical association to assess putative relationships to disease, and ignored other factors for evaluation. For example, evolution is a factor that has shaped disease risk, changing allele frequencies as human populations migrated into and inhabited new environments. Since many common variants differ among populations in frequency, as does disease prevalence, we hypothesized that patterns of disease and population structure, taken together, will inform association studies. Thus, the population distributions of allelic risk variants should reflect the distributions of their associated diseases. Evolutionary Triangulation (ET) exploits this evolutionary differentiation by comparing population structure among three populations with variable patterns of disease prevalence. By selecting populations based on patterns where two have similar rates of disease that differ substantially from a third, we performed a proof of principle analysis for this method. We examined three disease phenotypes, lactase persistence, melanoma, and Type 2 diabetes mellitus. We show that for lactase persistence, a phenotype with a simple genetic architecture, ET identifies the key gene, lactase. For melanoma, ET identifies several genes associated with this disease and/or phenotypes related to it, such as skin color genes. ET was less obviously successful for Type 2 diabetes mellitus, perhaps because of the small effect sizes in known risk loci and recent environmental changes that have altered disease risk. Alternatively, ET may have revealed new genes involved in conferring disease risk for diabetes that did not meet nominal GWAS significance thresholds. We also compared ET to another method used to filter for phenotype associated genes, population branch statistic (PBS), and show that ET performs better in identifying genes known to associate with diseases appropriately distributed among populations. Our results indicate that ET can filter association results to improve our ability to discover disease loci.

Project description:BackgroundThere is a need for valid approaches to measure sexual interactions to assess the impact of behavioural interventions and to predict the impact of behaviour changes. Different methods of asking about sexual behaviour often yield conflicting answers and men often report higher levels of heterosexual activity than women. To better understand self-reported sexual behaviour data and how best to collect it, we analyzed data collected as part of a larger project (ST IMPACTS) on the social and behavioural impact of introducing community-level HIV self-testing (HIVST) with counseling (semi-supervised with pre- and generic post-test counseling provided on delivery or collection of test kits) in an urban Malawian setting.MethodsInformation on sexual behaviour was collected from HIV self-testers over a three-month period. Three different methods were used: retrospective face-to-face interviews (FTFI); audio computer assisted self-interviews (ACASI) and a prospective coital diary. Both retrospective instruments were used before and after the three-month study period. Frequency and cross-tabulation, as well as scatterplots, were used for exploratory analyses. Chi-square tests were used to test for differences in proportions. Spearman's correlation coefficient was used to explore associations between both continuous and ordinal variables and Wilcoxon's paired sample and Mann-Whitney test was used to test for differences in such variables or between variables.ResultsThere was reasonable agreement between the two retrospective methods although both yielded inconsistent answers e.g. with lower reported numbers of life-time sexual partners at the end than at the beginning of the study period. The diary method elicited higher reported levels of sex with multiple partners than both retrospective instruments which may be due to inadequate recall. Over the study period 37.4% of men and 19.7% of women reported multiple sexual partners using the diary. There was no clear relationship between reported sexual behaviour and HIV status (prevalence 9.6%).ConclusionsDiaries may therefore have higher validity for sensitive behaviour reporting and thus be the preferred method in similar African contexts in measuring sexual behaviours.

Dataset Information

Triangulation in aetiological epidemiology.

Publications

Triangulation in aetiological epidemiology.

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