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The 1970s and 1980s saw the appearance of many papers on the topics of synergy, antagonism, and similar concepts of causal interactions and interdependence of effects, with a special emphasis on distinguishing these concepts from that of statistical interaction – the need for a product term in a model. As an example, Miettinen defined "synergism" as "the existence of instances in which both risk factors are needed for the effect", whereas "antagonism" is where "at least one [factor] can block the solo effect of the other". In response, Greenland and Poole constructed a systematic analysis of 16 possible individual response patterns in a deterministic causal model for two binary exposure variables, and showed how these patterns can be mapped onto nine types of sufficient causes, which in turn can be simplified into four intuitive categories. Although these and other papers recognized that epidemiology cannot directly study biological mechanisms underlying interaction, they showed how it can usefully study causal and preventive interdependence – which, despite its mechanistic agnosticism, has important implications for clinical decision making as well as for public health. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) is a respiratory disease affecting many people and able to be transmitted through direct and perhaps indirect contact. Direct contact transmission, mediated by aerosols or droplets, is widely demonstrated, whereas indirect transmission is only supported by collateral evidence such as virus persistence on inanimate surfaces and data from other similar viruses. The present systematic review aims to estimate SARS-CoV-2 prevalence on inanimate surfaces, identifying risk levels according to surface characteristics. Data were obtained from studies in published papers collected from two databases (PubMed and Embase) with the last search on 1 September 2020. Included studies had to be papers in English, had to deal with coronavirus and had to consider inanimate surfaces in real settings. Studies were coded according to our assessment of the risk that the investigated surfaces could be contaminated by SARS-CoV-2. A meta-analysis and a metaregression were carried out to quantify virus RNA prevalence and to identify important factors driving differences among studies. Thirty-nine out of forty retrieved paper reported studies carried out in healthcare settings on the prevalence of virus RNA, five studies carry out also analyses through cell culture and six tested the viability of isolated viruses. Overall prevalences of SARS-CoV-2 RNA on high-, medium- and low-risk surfaces were 0.22 (CI95 [0.152–0.296]), 0.04 (CI95 [0.007–0.090]), and 0.00 (CI95 [0.00–0.019]), respectively. The duration surfaces were exposed to virus sources (patients) was the main factor explaining differences in prevalence. [ABSTRACT FROM AUTHOR]

An investigation in a randomized population-based Swedish study with 564 participants aged 18-80 years showed that mean physical activity levels obtained using short message service (SMS) by means of cell phones (n = 171) were equal to corresponding levels obtained when sending identical questions by web (n = 182) or paper (n = 211). The response rates were similar for the SMS, web and paper groups. [ABSTRACT FROM AUTHOR]

Editor's Note: This Essay is the last paper of Olli Miettinen. I discussed it with him until about a week before his death on November 24, 2021. The article had gone through many iterations, as was the case with all his contributions to the European Journal of Epidemiology over the years. As Miettinen writes, it can be viewed as his academic mini-bio. Albert Hofman., (© 2022. The Author(s).)

Abstract  The successful and systematic collection of demographic and lifestyle data is central in the process of any epidemiological study. The traditionally used methods such as face-to-face and telephone interviews as well as paper-questionnaires are increasingly failing to produce good qualitative results within financially feasible limits. Tools that are better suited for the present dynamic populations are needed and the Internet presents a powerful alternative for the collection of data with several intrinsic features still unexplored. [ABSTRACT FROM AUTHOR]

The Rotterdam Study is a population-based cohort study, started in 1990 in the district of Ommoord in the city of Rotterdam, the Netherlands, with the aim to describe the prevalence and incidence, unravel the etiology, and identify targets for prediction, prevention or intervention of multifactorial diseases in mid-life and elderly. The study currently includes 17,931 participants (overall response rate 65%), aged 40 years and over, who are examined in-person every 3 to 5 years in a dedicated research facility, and who are followed-up continuously through automated linkage with health care providers, both regionally and nationally. Research within the Rotterdam Study is carried out along two axes. First, research lines are oriented around diseases and clinical conditions, which are reflective of medical specializations. Second, cross-cutting research lines transverse these clinical demarcations allowing for inter- and multidisciplinary research. These research lines generally reflect subdomains within epidemiology. This paper describes recent methodological updates and main findings from each of these research lines. Also, future perspective for coming years highlighted. [ABSTRACT FROM AUTHOR]

The nine Bradford Hill (BH) viewpoints (sometimes referred to as criteria) are commonly used to assess causality within epidemiology. However, causal thinking has since developed, with three of the most prominent approaches implicitly or explicitly building on the potential outcomes framework: directed acyclic graphs (DAGs), sufficient-component cause models (SCC models, also referred to as 'causal pies') and the grading of recommendations, assessment, development and evaluation (GRADE) methodology. This paper explores how these approaches relate to BH's viewpoints and considers implications for improving causal assessment. We mapped the three approaches above against each BH viewpoint. We found overlap across the approaches and BH viewpoints, underscoring BH viewpoints' enduring importance. Mapping the approaches helped elucidate the theoretical underpinning of each viewpoint and articulate the conditions when the viewpoint would be relevant. Our comparisons identified commonality on four viewpoints: strength of association (including analysis of plausible confounding); temporality; plausibility (encoded by DAGs or SCC models to articulate mediation and interaction, respectively); and experiments (including implications of study design on exchangeability). Consistency may be more usefully operationalised by considering an effect size's transportability to a different population or unexplained inconsistency in effect sizes (statistical heterogeneity). Because specificity rarely occurs, falsification exposures or outcomes (i.e., negative controls) may be more useful. The presence of a dose-response relationship may be less than widely perceived as it can easily arise from confounding. We found limited utility for coherence and analogy. This study highlights a need for greater clarity on BH viewpoints to improve causal assessment. [ABSTRACT FROM AUTHOR]

Measures of causal effects play a central role in epidemiology. A wide range of measures exist, which are designed to give relevant answers to substantive epidemiological research questions. However, due to mathematical convenience and software limitations most studies only report odds ratios for binary outcomes and hazard ratios for time-to-event outcomes. In this paper we show how logistic regression models and Cox proportional hazards regression models can be used to estimate a wide range of causal effect measures, with the R-package stdReg. For illustration we focus on the attributable fraction, the number needed to treat and the relative excess risk due to interaction. We use two publicly available data sets, so that the reader can easily replicate and elaborate on the analyses. The first dataset includes information on 487 births among 188 women, and the second dataset includes information on 2982 women diagnosed with primary breast cancer. [ABSTRACT FROM AUTHOR]

Dementia is the major predictor of death in old age. The aim of this paper was to determine whether 8-year mortality among 85-year olds with and without dementia, and if the contribution of dementia to mortality relative to other common diseases has changed. We used two population-based cohorts of 85-year-olds (N = 1065), born in 1901–02 and 1923–24, which were examined with identical methods in 1986–87 and 2008–2010 and followed for 8-year mortality according to data from the Swedish Tax Agency. Dementia was diagnosed according to DSM-III-R. Other diseases were diagnosed based on self-reports, close informant interviews, somatic examinations, and the Swedish National In-patient Register. Compared to cohort 1901–02, cohort 1923–24 had a lower 8-year mortality both among those with (HR 0.7; 95% CI 0.5–0.99) and without dementia (HR 0.7; 95% CI 0.5–0.9). Dementia was associated with increased mortality in both cohorts (cohort 1901–02, HR 2.6; 95% CI 2.0–3.2, cohort 1923–24, HR 2.8; 95% CI 2.3–3.5), and remained the major predictor of death, with a population attributable risk of 31.7% in 1986–87 and 27.7% in 2008–10. Dementia remained the most important predictor of death in both cohorts. The relative risk for mortality with dementia did not change between cohorts, despite a decreased mortality rate in the population. [ABSTRACT FROM AUTHOR]

The use of primary care electronic health records for research is abundant. The benefits gained from utilising such records lies in their size, longitudinal data collection and data quality. However, the use of such data to undertake high quality epidemiological studies, can lead to significant challenges particularly in dealing with misclassification, variation in coding and the significant effort required to pre-process the data in a meaningful format for statistical analysis. In this paper, we describe a methodology to aid with the extraction and processing of such databases, delivered by a novel software programme; the "Data extraction for epidemiological research" (DExtER). The basis of DExtER relies on principles of extract, transform and load processes. The tool initially provides the ability for the healthcare dataset to be extracted, then transformed in a format whereby data is normalised, converted and reformatted. DExtER has a user interface designed to obtain data extracts specific to each research question and observational study design. There are facilities to input the requirements for; eligible study period, definition of exposed and unexposed groups, outcome measures and important baseline covariates. To date the tool has been utilised and validated in a multitude of settings. There have been over 35 peer-reviewed publications using the tool, and DExtER has been implemented as a validated public health surveillance tool for obtaining accurate statistics on epidemiology of key morbidities. Future direction of this work will be the application of the framework to linked as well as international datasets and the development of standardised methods for conducting electronic pre-processing and extraction from datasets for research purposes. [ABSTRACT FROM AUTHOR]

Sweden has a long tradition of recording cause of death data. The Swedish cause of death register is a high quality virtually complete register of all deaths in Sweden since 1952. Although originally created for official statistics, it is a highly important data source for medical research since it can be linked to many other national registers, which contain data on social and health factors in the Swedish population. For the appropriate use of this register, it is fundamental to understand its origins and composition. In this paper we describe the origins and composition of the Swedish cause of death register, set out the key strengths and weaknesses of the register, and present the main causes of death across age groups and over time in Sweden. This paper provides a guide and reference to individuals and organisations interested in data from the Swedish cause of death register. [ABSTRACT FROM AUTHOR]

A broad review is given of the general principles underlying study design with emphasis on applications in medical and epidemiological contexts. The main theme of the paper is that, while the distinction between interventionist studies, that is experiments, and purely observational ones is important, there are many common threads. A wide range of specific applications are used in outline to illustrate the discussion. [ABSTRACT FROM AUTHOR]

The scientific debate following the initial formulation of the "bad luck" hypothesis in cancer development highlighted how measures based on analysis of variance are inappropriately used for risk communication. The notion of "explained" variance is not only used to quantify randomness, but also to quantify genetic and environmental contribution to disease in heritability coefficients. In this paper, we demonstrate why such quantifications are generally as problematic as bad luck estimates. We stress the differences in calculation and interpretation between the heritability coefficient and the population attributable fraction, the estimated fraction of all disease events that would not occur if an intervention could successfully prevent the excess genetic risk. We recommend using the population attributable fraction when communicating results regarding the genetic contribution to disease, as this measure is both more relevant from a public health perspective and easier to understand. [ABSTRACT FROM AUTHOR]

Understanding of causal pathways in epidemiology involves the concepts of direct and indirect effects. Recently, causal mediation analysis has been formalized to quantify these direct and indirect effects in the presence of exposure-mediator interaction and even allows for four-way decomposition of the total effect: controlled direct effect, reference interaction, mediated interaction, pure indirect effect. Whereas the other three effects can be intuitively conceptualized, mediated interaction is often considered a nuisance in statistical analysis. In this paper, we focus on mediated interaction and contrast it against pure mediation. We also propose a clinical and biological interpretation of mediated interaction using three hypothetical examples. With these examples we aim to make researchers aware that mediated interaction can actually provide important clinical and biological information. [ABSTRACT FROM AUTHOR]

Cognitive lifestyle measures such as education, occupation, and social engagement are commonly associated with late-life cognitive ability although their associations with cognitive decline tend to be mixed. However, longitudinal analyses of cognition rarely account for death and dropout, measurement error of the cognitive phenotype, and differing trajectories for different population sub-groups. This paper applies a joint latent class mixed model (and a multi-state model in a sensitivity analysis) that accounts for these issues to a large (n = 3,653), population-based cohort, Paquid, to model the relationship between cognitive lifestyle and cognitive decline. Cognition was assessed over a 20-year period using the Mini-Mental State Examination. Three cognitive lifestyle variables were assessed: education, mid-life occupation, and late-life social engagement. The analysis identified four latent sub-populations with class-specific longitudinal cognitive decline and mortality risk. Irrespective of the cognitive trajectory, increased social engagement was associated with a decreased mortality risk. High education was associated with the most favourable cognitive trajectory, and after adjusting for cognitive decline, with an increased mortality risk. Mid-life occupational complexity was also associated with more favourable trajectories but not with mortality risk. To realistically examine the link between cognitive lifestyle and cognitive decline, complex statistical models are required. This paper applies and compares in a sensitivity analysis two such models, and shows education to be linked to a compression of cognitive morbidity irrespective of cognitive trajectory. Furthermore, a potentially modifiable variable, late-life social engagement is associated with a decreased mortality risk in all of the population sub-groups. [ABSTRACT FROM AUTHOR]

In 2007, supplementation with the trace element selenium in a trial was unexpectedly found to be associated with an excess risk of type 2 diabetes. Given the concerns raised by these findings and the large number of recent studies on this topic, we reviewed the available literature with respect to this possible association. In this paper, we assessed the results of both experimental and nonexperimental epidemiologic studies linking selenium with type 2 diabetes incidence. Through a systematic literature search, we retrieved 50 potentially eligible nonexperimental studies and 5 randomized controlled trials published through June 11, 2018. To elucidate the possible dose-response relation, we selected for further analysis those studies that included multiple exposure levels and serum or plasma levels. We computed a pooled summary risk ratio (RR) of diabetes according to selenium exposure in these studies. We also computed a RR for diabetes incidence following supplementation with 200 µg/day of selenium compared with placebo in trials. In the nonexperimental studies, we found a direct relation between selenium exposure and risk of diabetes, with a clear and roughly linear trend in subjects with higher plasma or serum selenium levels, with RR at 140 µg/L of selenium exposure compared with a referent category of < 45 µg/L equal to 3.6 [95% confidence interval (CI) 1.4-9.4]. A dose-response meta-analysis focusing on studies with direct assessment of dietary selenium intake showed a similar trend. In experimental studies, selenium supplementation increased the risk of diabetes by 11% (RR 1.11, 95% CI 1.01-1.22) compared with the placebo-allocated participants, with a higher RR in women than in men. Overall, results from both nonexperimental and experimental studies indicate that selenium may increase the risk of type 2 diabetes across a wide range of exposure levels. The relative increase in risk is small but of possible public health importance because of the high incidence of diabetes and the ubiquity of selenium exposure. [ABSTRACT FROM AUTHOR]

Childhood cancer survivors face risks from a variety of late effects, including cardiac events, second cancers, and late mortality. The aim of the pan-European PanCare Childhood and Adolescent Cancer Survivor Care and Follow-Up Studies (PanCareSurFup) Consortium was to collect data on incidence and risk factors for these late effects among childhood cancer survivors in Europe. This paper describes the methodology of the data collection for the overall PanCareSurFup cohort and the outcome-related cohorts. In PanCareSurFup 13 data providers from 12 countries delivered data to the data centre in Mainz. Data providers used a single variable list that covered all three outcomes. After validity and plausibility checks data was provided to the outcome-specific working groups. In total, we collected data on 115,596 patients diagnosed with cancer from 1940 to 2011, of whom 83,333 had survived 5 years or more. Due to the eligibility criteria and other requirements different numbers of survivors were eligible for the analysis of each of the outcomes. Thus, 1014 patients with at least one cardiac event were identified from a cohort of 39,152 5-year survivors; for second cancers 3995 survivors developed at least one second cancer from a cohort of 71,494 individuals, and from the late mortality cohort of 79,441 who had survived at least 5 years, 9247 died subsequently. Through the close cooperation of many European countries and the establishment of one central data collection and harmonising centre, the project succeeded in generating the largest cohort of children with cancer to date. [ABSTRACT FROM AUTHOR]

Paediatric population neuroimaging is an emerging field that falls at the intersection between developmental neuroscience and epidemiology. A key feature of population neuroimaging studies involves large-scale recruitment that is representative of the general population. One successful approach for population neuroimaging is to embed neuroimaging studies within large epidemiological cohorts. The Generation R Study is a large, prospective population-based birth-cohort in which nearly 10,000 pregnant mothers were recruited between 2002 and 2006 with repeated measurements in the children and their parents over time. Magnetic resonance imaging was included in 2009 with the scanning of 1070 6-to-9-year-old children. The second neuroimaging wave was initiated in April 2013 with a total of 4245 visiting the MRI suite and 4087 9-to-11-year-old children being scanned. The sequences included high-resolution structural MRI, 35-direction diffusion weighted imaging, and a 6 min and 2 s resting-state functional MRI scan. The goal of this paper is to provide an overview of the imaging protocol and the overlap between the neuroimaging data and metadata. We conclude by providing a brief overview of results from our first wave of neuroimaging, which highlights a diverse array of questions that can be addressed by merging the fields of developmental neuroscience and epidemiology. [ABSTRACT FROM AUTHOR]

Background and aim: In epidemiological questionnaire studies results can be influenced by non-responder bias. However, in respiratory epidemiology this has been analysed in very few recently published papers. The aim of our paper is to assess if the results found in our previous postal questionnaire study in an adult population in Northern Finland were biased by non-response. Methods: A random sample of 385 persons from the 1284 non-responders in a previous postal questionnaire study was examined. The same questionnaire as in the original study was again mailed to these persons, and those still not answering were contacted by phone. Results: Totally 183 complete answers (48%) were collected. Lack of interest (56%) and forgetting to mail the response letter (22%) were the most common reasons to non-response. Typical non-responders were young men and current smokers who less frequently reported respiratory symptoms in exercise and asthma than the responders in the original study. Answers collected by phone gave for some questions higher prevalence rates than postal answers. Conclusion: Firstly, in this population the response rate (83.6%) in the original study was high enough to provide reliable results for respiratory symptoms and diseases, only the prevalence of current smoking was biased by non-response. Secondly, the methods used for collecting responses in a non-response study may influence the results. [ABSTRACT FROM AUTHOR]

Epidemiology has been remarkably successful in the past in identifying the important agents of disease, the impact of the environment, both physical and social, and interrelationship with host susceptibility (genomics). Many of the advances in improving the health of individuals and populations have been the result of epidemiology studies that have identified the specific 'agents' of disease and application of public health and preventive medicine. In recent years, large longitudinal studies have dominated epidemiology research, especially long incubation period chronic diseases. The initial hypotheses in these studies have been expanded by vertical extension studies using newer technologies to measure independent variables, vertical pseudopods, and additional studies of other diseases, horizontal pseudopods, of the original longitudinal study. Host susceptibility, i.e. genomics, has also become a prominent component of these longitudinal studies. The critical question addressed in this paper is whether these 'pseudopod' epidemiology approaches have enhanced public health or generated a large number of studies of little impact. [ABSTRACT FROM AUTHOR]

Attention-deficit/hyperactivity (ADHD) symptoms have been associated with the decision to become self-employed. Although these symptoms are generally regarded as disadvantageous, there may also be a bright side. To our knowledge, however, there has been no systematic, epidemiological evidence to support this claim. This paper examines the association between ADHD symptoms and self-employment in a population-based sample from the STAGE cohort of the Swedish Twin Registry (N = 7208). For replication, we used a sample of Dutch students who participated in the Global University Entrepreneurial Spirit Students' Survey (N = 13,112). In the Swedish sample, we found a positive association with self-employment for both general ADHD symptoms [odds ratio (OR) 1.13; 95 % confidence intervals (CI) 1.04-1.23] and hyperactivity symptoms [OR 1.19; 95 % CI 1.08-1.32], whereas no association was found for attention-deficit symptoms [OR 0.99; 95 % CI 0.89-1.10]. The positive association between hyperactivity and self-employment was replicated in the Dutch student sample [OR 1.09; 95 % CI 1.03-1.15]. Our results show that certain aspects of ADHD, in particular hyperactivity, can have a bright side, as they are positively associated with self-employment. [ABSTRACT FROM AUTHOR]

Polyneuropathy is a disabling condition of the peripheral nerves, characterized by symmetrical distal numbness and paresthesia, often accompanied with pain and weakness. Although the disease is often encountered in neurological clinics and is well known by physicians, incidence and prevalence rates are not well known. We searched EMBASE, Medline, Web-of-science, Cochrane, PubMed Publisher, and Google Scholar, for population-based studies investigating the prevalence of polyneuropathy and its risk factors. Out of 5119 papers, we identified 29 eligible studies, consisting of 11 door-to-door survey studies, 7 case-control studies and 11 cohort/database studies. Prevalence of polyneuropathy across these studies varies substantially. This can partly be explained by differences in assessment protocols and study populations. The overall prevalence of polyneuropathy in the general population seems around 1 % and rises to up to 7 % in the elderly. Polyneuropathy seemed more common in Western countries than in developing countries and there are indications that females are more often affected than males. Risk factor profiles differ across countries. In developing countries communicable diseases, like leprosy, are more common causes of neuropathy, whereas in Western countries especially diabetes, alcohol overconsumption, cytostatic drugs and cardiovascular disease are more commonly associated with polyneuropathy. In all studies a substantial proportion of polyneuropathy cases (20-30 %) remains idiopathic. Most of these studies have been performed over 15 years ago. More recent evidence suggests that the prevalence of polyneuropathy in the general population has increased over the years. Future research is necessary to confirm this increase in prevalence and to identify new and potentially modifiable risk factors. [ABSTRACT FROM AUTHOR]

Imaging plays an essential role in research on neurological diseases in the elderly. The Rotterdam Scan Study was initiated as part of the ongoing Rotterdam Study with the aim to elucidate the causes of neurological disease by performing imaging of the brain in a prospective population-based setting. Initially, in 1995 and 1999, random subsamples of participants from the Rotterdam Study underwent neuroimaging, whereas from 2005 onwards MRI has been implemented into the core protocol of the Rotterdam Study. In this paper, we discuss the background and rationale of the Rotterdam Scan Study. Moreover, we describe the imaging protocol, image post-processing techniques, and the main findings to date. Finally, we provide recommendations for future research, which will also be topics of investigation in the Rotterdam Scan Study. [ABSTRACT FROM AUTHOR]

The impact of non-communicable diseases (NCDs) in populations extends beyond ill-health and mortality with large financial consequences. To systematically review and meta-analyze studies evaluating the impact of NCDs (including coronary heart disease, stroke, type 2 diabetes mellitus, cancer (lung, colon, cervical and breast), chronic obstructive pulmonary disease and chronic kidney disease) at the macro-economic level: healthcare spending and national income. Medical databases (Medline, Embase and Google Scholar) up to November 6th 2014. For further identification of suitable studies, we searched reference lists of included studies and contacted experts in the field. We included randomized controlled trials, systematic reviews, cohorts, case-control, cross-sectional, modeling and ecological studies carried out in adults assessing the economic consequences of NCDs on healthcare spending and national income without language restrictions. All abstracts and full text selection was done by two independent reviewers. Any disagreements were resolved through consensus or consultation of a third reviewer. Data were extracted by two independent reviewers using a pre-designed data collection form. Studies evaluating the impact of at least one of the selected NCDs on at least one of the following outcome measures: healthcare expenditure, national income, hospital spending, gross domestic product (GDP), gross national product, net national income, adjusted national income, total costs, direct costs, indirect costs, inpatient costs, outpatient costs, per capita healthcare spending, aggregate economic outcome, capital loss in production levels in a country, economic growth, GDP per capita (per capita income), percentage change in GDP, intensive growth, extensive growth, employment, direct governmental expenditure and non-governmental expenditure. From 4,364 references, 153 studies met our inclusion criteria. Most of the studies were focused on healthcare related costs of NCDs. 30 studies reported the economic impact of NCDs on healthcare budgets and 13 on national income. Healthcare expenditure for cardiovascular disease (12-16.5 %) was the highest; other NCDs ranged between 0.7 and 7.4 %. NCD-related health costs vary across the countries, regions, and according to type of NCD. Additionally, there is an increase in costs with increased severity and years lived with the disease. Low- and middle-income (LMI) countries were the focus of just 16 papers, which suggests an information shortage concerning the true economic burden of NCDs in these countries. NCDs pose a significant financial burden on healthcare budgets and nations' welfare, which is likely to increase over time. However further work is required to standardize more consistently the methods available to assess the economic impact of NCDs and to involve (hitherto under-addressed) LMI populations across the globe. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have been successful in identifying loci associated with a wide range of complex human traits and diseases. Up to now, the majority of GWAS have focused on European populations. However, the inclusion of other ethnic groups as well as admixed populations in GWAS studies is rapidly rising following the pressing need to extrapolate findings to non-European populations and to increase statistical power. In this paper, we describe the methodological steps surrounding genetic data generation, quality control, study design and analytical procedures needed to run GWAS in the multiethnic and highly admixed Generation R Study, a large prospective birth cohort in Rotterdam, the Netherlands. Furthermore, we highlight a number of practical considerations and alternatives pertinent to the quality control and analysis of admixed GWAS data. [ABSTRACT FROM AUTHOR]