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      Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research

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          Abstract

          Population health interventions are essential to reduce health inequalities and tackle other public health priorities, but they are not always amenable to experimental manipulation. Natural experiment (NE) approaches are attracting growing interest as a way of providing evidence in such circumstances. One key challenge in evaluating NEs is selective exposure to the intervention. Studies should be based on a clear theoretical understanding of the processes that determine exposure. Even if the observed effects are large and rapidly follow implementation, confidence in attributing these effects to the intervention can be improved by carefully considering alternative explanations. Causal inference can be strengthened by including additional design features alongside the principal method of effect estimation. NE studies often rely on existing (including routinely collected) data. Investment in such data sources and the infrastructure for linking exposure and outcome data is essential if the potential for such studies to inform decision making is to be realized.

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          Most cited references46

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          Comparative Politics and the Synthetic Control Method

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            Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches.

            A central problem in public health studies is how to make inferences about the causal effects of treatments or agents. In this article we review an approach to making such inferences via potential outcomes. In this approach, the causal effect is defined as a comparison of results from two or more alternative treatments, with only one of the results actually observed. We discuss the application of this approach to a number of data collection designs and associated problems commonly encountered in clinical research and epidemiology. Topics considered include the fundamental role of the assignment mechanism, in particular the importance of randomization as an unconfounded method of assignment; randomization-based and model-based methods of statistical inference for causal effects; methods for handling noncompliance and missing data; and methods for limiting bias in the analysis of observational data, including propensity score matching and sensitivity analysis.
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              The impact of pesticide regulations on suicide in Sri Lanka.

              Between 1950 and 1995 suicide rates in Sri Lanka increased 8-fold to a peak of 47 per 100,000 in 1995. By 2005, rates had halved. We investigated whether Sri Lanka's regulatory controls on the import and sale of pesticides that are particularly toxic to humans were responsible for these changes in the incidence of suicide. Ecological analysis using graphical and descriptive approaches to identify time trends in suicide and risk factors for suicide in Sri Lanka, 1975-2005. Restrictions on the import and sales of WHO Class I toxicity pesticides in 1995 and endosulfan in 1998, coincided with reductions in suicide in both men and women of all ages. 19,769 fewer suicides occurred in 1996-2005 as compared with 1986-95. Secular trends in unemployment, alcohol misuse, divorce, pesticide use and the years associated with Sri Lanka's Civil war did not appear to be associated with these declines. These data indicate that in countries where pesticides are commonly used in acts of self-poisoning, import controls on the most toxic pesticides may have a favourable impact on suicide. In Asia, there are an estimated 300,000 deaths from pesticide self-poisoning annually. National and international policies restricting the sale of pesticides that are most toxic to humans may have a major impact on suicides in the region.
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                Author and article information

                Journal
                8006431
                1309
                Annu Rev Public Health
                Annu Rev Public Health
                Annual review of public health
                0163-7525
                1545-2093
                26 June 2018
                11 January 2017
                20 March 2017
                26 April 2019
                : 38
                : 39-56
                Affiliations
                MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow G2 3QB, United Kingdom
                Article
                EMS78383
                10.1146/annurev-publhealth-031816-044327
                6485604
                28125392
                d29867ba-c5ff-4402-aba9-48ceaf5bb458

                This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 (CC-BY-SA) International License, which permits unrestricted use, distribution, and reproduction in any medium and any derivative work is made available under the same, similar, or a compatible license. See credit lines of images or other third-party material in this article for license information.

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                population health interventions,evaluation methods,causal inference

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