American Journal of Epidemiology (AM J EPIDEMIOL)

Publisher: Johns Hopkins University. School of Hygiene and Public Health; Society for Epidemiologic Research (U.S.), Oxford University Press (OUP)

Journal description

The American Journal of Epidemiology is the premiere epidemiological journal devoted to the publication of empirical research findings methodological developments in the field of epidemiological research and opinion pieces. It is aimed at both fellow epidemiologists and those who use epidemiological data including public health workers and clinicians.

Current impact factor: 5.23

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 5.23
2013 Impact Factor 4.975
2012 Impact Factor 4.78
2011 Impact Factor 5.216
2010 Impact Factor 5.745
2009 Impact Factor 5.589
2008 Impact Factor 5.454
2007 Impact Factor 5.285
2006 Impact Factor 5.241
2005 Impact Factor 5.068
2004 Impact Factor 4.933
2003 Impact Factor 4.486
2002 Impact Factor 4.189
2001 Impact Factor 3.948
2000 Impact Factor 3.87
1999 Impact Factor 3.978
1998 Impact Factor 3.699
1997 Impact Factor 3.773
1996 Impact Factor 4.112
1995 Impact Factor 3.712
1994 Impact Factor 3.482
1993 Impact Factor 3.081
1992 Impact Factor 3.135

Impact factor over time

Impact factor

Additional details

5-year impact 5.63
Cited half-life >10.0
Immediacy index 1.40
Eigenfactor 0.06
Article influence 2.38
Website American Journal of Epidemiology website
Other titles American journal of epidemiology
ISSN 0002-9262
OCLC 1480139
Material type Periodical, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Oxford University Press (OUP)

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 12 months embargo
  • Conditions
    • Pre-print can only be posted prior to acceptance
    • Pre-print must be accompanied by set statement (see link)
    • Pre-print must not be replaced with post-print, instead a link to published version with amended set statement should be made
    • Pre-print on author's personal website, employer website, free public server or pre-prints in subject area
    • Post-print in Institutional repositories or Central repositories
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany archived copy (see policy)
    • Eligible authors may deposit in OpenDepot
    • The publisher will deposit in PubMed Central on behalf of NIH authors
    • Publisher last contacted on 19/02/2015
    • This policy is an exception to the default policies of 'Oxford University Press (OUP)'
  • Classification

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: The prevalence of hypertension is increasing among younger women, and new strategies are needed to identify high-risk women who should be targets for early intervention. Several mechanisms underlying hypertension might also contribute to premenstrual syndrome (PMS), but whether women with PMS have a higher risk of subsequently developing hypertension has not been assessed. We prospectively evaluated this possibility in a substudy of the Nurses' Health Study II. Participants were 1,257 women with clinically significant PMS (1991-2005) and 2,463 age-matched comparison women with few menstrual symptoms. Participants were followed for incident hypertension until 2011. Over 6-20 years, hypertension was reported by 342 women with PMS and 541 women without. After adjustment for age, smoking, body mass index, and other risk factors for hypertension, women with PMS had a hazard ratio for hypertension of 1.4 (95% confidence interval: 1.2, 1.6) compared with women without PMS. Risk was highest for hypertension that occurred before 40 years of age (hazard ratio = 3.3; 95% confidence interval: 1.7, 6.5; P for interaction = 0.0002). The risk associated with PMS was not modified by use of oral contraceptives or antidepressants but was attenuated among women with high intakes of thiamine and riboflavin (P < 0.05). These results suggest that PMS might be associated with future development of hypertension and that this risk may be modifiable.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv159
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    ABSTRACT: High-sensitivity C-reactive protein (hs-CRP) has been associated with coronary heart disease (CHD) in numerous but not all observational studies, and whether low levels of low-density lipoprotein cholesterol (LDL-C) alter this association is unknown. In the Multi-Ethnic Study of Atherosclerosis (2000-2012), we prospectively assessed the association of hs-CRP concentrations with incident CHD in participants who did not receive lipid-lowering therapy, as well as in those with LDL-C concentrations less than 130 mg/dL (n = 3,106) and those with LDL-C concentrations of 130 mg/dL or greater (n = 1,716) at baseline (2000-2002). Cox proportional hazard analyses were used to assess the associations after adjustment for socioeconomic status, traditional risk factors, body mass index, diabetes, aspirin use, kidney function, and coronary artery calcium score. Loge hs-CRP was associated with incident CHD in participants with LDL-C concentrations of 130 mg/dL or higher (hazard ratio (HR) = 1.29, 95% confidence interval (CI): 1.05, 1.60) but not in those with LDL-C concentrations less than 130 mg/dL (HR = 0.88, 95% CI: 0.74, 1.05; P for interaction = 0.003). As a whole, loge hs-CRP was not associated with incident CHD in participants who had not received lipid-lowering therapy at baseline (HR = 1.05, 95% CI: 0.92, 1.20) and who had mean LDL-C concentrations less than 130 mg/dL. These findings suggest that LDL-C concentrations might be a moderator of the contribution of hs-CRP to CHD.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv144
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    ABSTRACT: The impact of risk factors on the amount of time taken to reach an endpoint is a common parameter of interest. Hazard ratios are often estimated using a discrete-time approximation, which works well when the by-interval event rate is low. However, if the intervals are made more frequent than the observation times, missing values will arise. We investigated common analytical approaches, including available-case (AC) analysis, last observation carried forward (LOCF), and multiple imputation (MI), in a setting where time-dependent covariates also act as mediators. We generated complete data to obtain monthly information for all individuals, and from the complete data, we selected "observed" data by assuming that follow-up visits occurred every 6 months. MI proved superior to LOCF and AC analyses when only data on confounding variables were missing; AC analysis also performed well when data for additional variables were missing completely at random. We applied the 3 approaches to data from the Canadian HIV-Hepatitis C Co-infection Cohort Study (2003-2014) to estimate the association of alcohol abuse with liver fibrosis. The AC and LOCF estimates were larger but less precise than those obtained from the analysis that employed MI.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv152
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    ABSTRACT: Benzene is an established cause of adult leukemia, but whether it is associated with childhood leukemia remains unclear. We conducted a meta-analysis in which we reviewed the epidemiologic literature on this topic and explored causal inference, bias, and heterogeneity. The exposure metrics that we evaluated included occupational and household use of benzenes and solvents, traffic density, and traffic-related air pollution. For studies of occupational and household product exposure published from 1987 to 2014, the summary relative risk for childhood leukemia was 1.96 (95% confidence interval (CI): 1.53, 2.52; n = 20). In these studies, the summary relative risk was higher for acute myeloid leukemia (summary relative risk (sRR) = 2.34, 95% CI: 1.72, 3.18; n = 6) than for acute lymphoblastic leukemia (sRR = 1.57; 95% CI: 1.21, 2.05; n = 14). The summary relative risk was higher for maternal versus paternal exposure, in studies that assessed benzene versus all solvents, and in studies of gestational exposure. In studies of traffic density or traffic-related air pollution published from 1999 to 2014, the summary relative risk was 1.48 (95% CI: 1.10, 1.99; n = 12); it was higher for acute myeloid leukemia (sRR = 2.07; 95% CI: 1.34, 3.20) than for acute lymphoblastic leukemia (sRR = 1.49; 95% CI: 1.07, 2.08) and in studies that involved detailed models of traffic pollution (sRR = 1.70; 95% CI: 1.16, 2.49). Overall, we identified evidence of associations between childhood leukemia and several different potential metrics of benzene exposure.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv120
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    ABSTRACT: Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a "correct" way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv133
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    ABSTRACT: One method by which to identify fundamental biological processes that may contribute to age-related disease and disability, instead of disease-specific processes, is to construct endophenotypes comprising linear combinations of physiological measures. Applying factor analyses methods to phenotypic data (2006-2009) on 28 traits representing 5 domains (cognitive, cardiovascular, metabolic, physical, and pulmonary) from 4,472 US and Danish individuals in 574 pedigrees from the Long Life Family Study (United States and Denmark), we constructed endophenotypes and assessed their relationship with mortality. The most dominant endophenotype primarily reflected the physical activity and pulmonary domains, was heritable, was significantly associated with mortality, and attenuated the association of age with mortality by 24.1%. Using data (1997-1998) on 1,794 Health, Aging and Body Composition Study participants from Memphis, Tennessee, and Pittsburgh, Pennsylvania, we obtained strikingly similar endophenotypes and relationships to mortality. We also reproduced the endophenotype constructs, especially the dominant physical activity and pulmonary endophenotype, within demographic subpopulations of these 2 cohorts. Thus, this endophenotype construct may represent an underlying phenotype related to aging. Additional genetic studies of this endophenotype may help identify genetic variants or networks that contribute to the aging process.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv143

  • American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv288
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    ABSTRACT: Differences in internal dose of nicotine and tobacco-derived carcinogens among ethnic/racial groups have been observed. In this study, we explicitly examined the relationships between genetic ancestries (genome-wide average) and 19 tobacco-derived biomarkers in smokers from 3 admixed groups in the Multiethnic Cohort Study (1993-present), namely, African ancestry in African Americans (n = 362), Amerindian ancestry in Latinos (n = 437), and Asian and Native Hawaiian ancestries in Native Hawaiians (n = 300). After multiple comparison adjustment, both African and Asian ancestries were significantly related to a greater level of free cotinine; African ancestry was also significantly related to lower cotinine glucuronidation (P's < 0.00156). The predicted decrease in cotinine glucuronidation was 8.6% (P = 4.5 × 10(-6)) per a 20% increase in African ancestry. Follow-up admixture mapping revealed that African ancestry in a 12-Mb region on chromosome 4q was related to lower cotinine glucuronidation (P's < 2.7 × 10(-7), smallest P = 1.5 × 10(-9)), although this is the same region reported in our previous genome-wide association study. Our results implicate a genetic ancestral component in the observed ethnic/racial variation in nicotine metabolism. Further studies are needed to identify the underlying genetic variation that could potentially be ethnic/racial specific.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv138
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    ABSTRACT: Findings on the association between television (TV) viewing and all-cause mortality in epidemiologic studies have been inconsistent. Therefore, we conducted a meta-analysis of data from prospective cohort studies to quantify this association. Relevant articles were identified by searching MEDLINE (PubMed; National Library of Medicine, Bethesda, Maryland) and EMBASE (Elsevier B.V., Amsterdam, the Netherlands) from inception to March 1, 2015, and reviewing the reference lists of retrieved articles. Study-specific results were pooled using a random-effects model. Of 2,578 citations identified by the search strategy, 10 cohort studies (61,494 deaths among 647,475 individuals) met the inclusion criteria. The summary relative risk of all-cause mortality for the highest category of TV viewing time versus the lowest was 1.33 (95% confidence interval: 1.20, 1.47), with heterogeneity among studies (I(2) = 66.7%, Pheterogeneity = 0.001). In dose-response meta-analysis, TV viewing time was statistically significantly associated with all-cause mortality risk in a J-shaped fashion (Pnonlinearity = 0.001). These results indicate that prolonged TV viewing time might increase the risk of all-cause mortality. Given the high prevalence of excessive TV viewing, public health recommendations or interventions aimed at decreasing the amount of TV viewing time in modern societies are warranted.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv164

  • American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv277
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    ABSTRACT: Mass vaccination campaigns with the oral poliovirus vaccine targeting children aged <5 years are a critical component of the global poliomyelitis eradication effort. Monitoring the coverage of these campaigns is essential to allow corrective action, but current approaches are limited by their cross-sectional nature, nonrandom sampling, reporting biases, and accessibility issues. We describe a new Bayesian framework using data augmentation and Markov chain Monte Carlo methods to estimate variation in vaccination coverage from children's vaccination histories investigated during surveillance for acute flaccid paralysis. We tested the method using simulated data with at least 200 cases and were able to detect undervaccinated groups if they exceeded 10% of all children and temporal changes in coverage of ±10% with greater than 90% sensitivity. Application of the method to data from Pakistan for 2010-2011 identified undervaccinated groups within the Balochistan/Federally Administered Tribal Areas and Khyber Pakhtunkhwa regions, as well as temporal changes in coverage. The sizes of these groups are consistent with the multiple challenges faced by the program in these regions as a result of conflict and insecurity. Application of this new method to routinely collected data can be a useful tool for identifying poorly performing areas and assisting in eradication efforts.
    American Journal of Epidemiology 11/2015; 182(11). DOI:10.1093/aje/kwv199

  • American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv275
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    ABSTRACT: In an attempt to reproduce the results of an inconclusive 1927 report by the British Medical Research Council on the hereditary versus social origins of rheumatic fever, Read, Ciocco, and Taussig, from Johns Hopkins University, with the support of Frost, conducted a case-control study in 1935 and 1936. Their study, which appeared in the American Journal of Hygiene in 1938, was outstanding for its clear and tidy rational for separating hereditary from environmental causes. The authors compared the prevalence of rheumatic fever among the relatives of 33 children admitted for "incident" rheumatic fever and 33 control children admitted in a tuberculosis clinic for reasons other than rheumatic fever. Both rheumatic fever (cases) and tuberculosis (controls) were diseases of the poor. All family members of both cases and controls, including uncles, aunts, and grandparents, were eligible for interview and physical examination. The results were compatible with the presence of an "inherited predisposition" to rheumatic fever because the disease was more prevalent among the uncles, aunts, and grandparents of case patients than among those of control patients. Methodologically, the paper by Read, Ciocco, and Taussig is an important but almost completely forgotten milestone in the evolution of case-control studies and of genetic epidemiology.
    American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv221

  • American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv220

  • American Journal of Epidemiology 11/2015; DOI:10.1093/aje/kwv297

  • American Journal of Epidemiology 10/2015; DOI:10.1093/aje/kwv286

  • American Journal of Epidemiology 09/2015; DOI:10.1093/aje/kwv209
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    ABSTRACT: Married couples might be an appropriate target for obesity prevention interventions. In the present study, we aimed to evaluate whether an individual's risk of obesity is associated with spousal risk of obesity and whether an individual's change in body mass index (BMI; weight in kilograms divided by height in meters squared) is associated with spousal BMI change. We analyzed data from 3,889 spouse pairs in the Atherosclerosis Risk in Communities Study cohort who were sampled at ages 45-65 years from 1986 to 1989 and followed for up to 25 years. We estimated hazard ratios for incident obesity by whether spouses remained nonobese, became obese, remained obese, or became nonobese. We estimated the association of participants' BMI changes with concurrent spousal BMI changes using linear mixed models. Analyses were stratified by sex. At baseline, 22.6% of men and 24.7% of women were obese. Nonobese participants whose spouses became obese were more likely to become obese themselves (for men, hazard ratio = 1.78, 95% confidence interval: 1.30, 2.43; for women, hazard ratio = 1.89, 95% confidence interval: 1.39, 2.57). With each 1-unit increase in spousal BMI change, women's BMI change increased by 0.15 (95% confidence interval: 0.13, 0.18) and men's BMI change increased by 0.10 (95% confidence interval: 0.09, 0.12). Having a spouse become obese nearly doubles one's risk of becoming obese. Future research should consider exploring the efficacy of obesity prevention interventions in couples.
    American Journal of Epidemiology 09/2015; DOI:10.1093/aje/kwv112
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    ABSTRACT: A challenge for population health surveillance systems using telephone methodologies is to maintain representative estimates as response rates decrease. Raked weighting, rather than conventional poststratification methodologies, has been developed to improve representativeness of estimates produced from telephone-based surveillance systems by incorporating a wider range of sociodemographic variables using an iterative proportional fitting process. This study examines this alternative weighting methodology with the monthly South Australian population health surveillance system report of randomly selected people of all ages in 2013 (n = 7,193) using computer-assisted telephone interviewing. Poststratification weighting used age groups, sex, and area of residence. Raked weights included an additional 6 variables: dwelling status, number of people in household, country of birth, marital status, educational level, and highest employment status. Most prevalence estimates (e.g., diabetes and asthma) did not change when raked weights were applied. Estimates that changed by at least 2 percentage points (e.g., tobacco smoking and mental health conditions) were associated with socioeconomic circumstances, such as dwelling status, which were included in the raked-weighting methodology. Raking methodology has overcome, to some extent, nonresponse bias associated with the sampling methodology by incorporating lower socioeconomic groups and those who are routinely not participating in population surveys into the weighting formula. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail:
    American Journal of Epidemiology 08/2015; 182(6):kwv080. DOI:10.1093/aje/kwv080