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.

Journal Impact: 1.80*

*This value is calculated using ResearchGate data and is based on average citation counts from work published in this journal. The data used in the calculation may not be exhaustive.

Journal impact history

2016 Journal impact Available summer 2017
2015 Journal impact 1.80
2014 Journal impact 0.20
2013 Journal impact 0.22
2012 Journal impact 0.16
2011 Journal impact 0.05
2010 Journal impact 0.05
2009 Journal impact 3.24
2008 Journal impact 4.23
2007 Journal impact 3.64
2006 Journal impact 3.02
2005 Journal impact 2.81
2004 Journal impact 2.64
2003 Journal impact 2.38
2002 Journal impact 2.14
2001 Journal impact 1.87
2000 Journal impact 1.72

Journal impact over time

Journal impact

Additional details

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

This journal may support self-archiving.
Learn more

Publications in this journal

  • Stephanie Donauer · Mekibib Altaye · Yingying Xu · [...] · Kimberly Yolton
    [Show abstract] [Hide abstract] ABSTRACT: Prenatal exposure to organophosphate pesticides, which is ubiquitous, may be detrimental to neurological development. We examined 327 mother/infant pairs in Cincinnati, Ohio, between 2003 and 2006 to determine associations between prenatal exposure to organophosphate pesticides and neurodevelopment. Twice during pregnancy urinary concentrations of 6 common dialkylphosphates, nonspecific metabolites of organophosphate pesticides, were measured. Aggregate concentrations of diethylphosphates, dimethylphosphates, and total dialkylphosphates were calculated. Bayley Scales of Infant Development, Second Edition-Mental and Psychomotor Developmental indices were administered at ages 1, 2, and 3 years, the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition, at age 4, and the Wechsler Preschool and Primary Scale of Intelligence, Third Edition, at age 5. Mothers with higher urinary total dialkylphosphate concentrations reported higher levels of socioeconomic status and increased fresh fruit and vegetable intake. We found no associations between prenatal exposure to organophosphate pesticides and cognition at 1–5 years of age. In our cohort, exposure to organophosphate pesticides during pregnancy was not associated with cognition during early childhood. It is possible that a higher socioeconomic status and healthier diet may protect the fetus from potential adverse associations with gestational organophosphate pesticide exposure, or that dietary exposure to the metabolites is innocuous and not an ideal measure of exposure to the parent compound.
    Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: To shed light on the etiology of metabolic syndrome development, it is important to understand whether its 5 component disorders follow certain onset sequences. To explore disease progression of the syndrome, we studied the ages at onset of 5 cardiometabolic diseases: abdominal obesity, diabetes, hypertension, hypertriglyceridemia, and hypo-α-lipoproteinemia. In analyzing longitudinal data from the Cardiovascular Disease Risk Factors Two-Township Study (1989–2002) in Taiwan, we adjusted for nonsusceptibility, utilizing the logistic-accelerated failure time location-scale mixture regression models for left-truncated and interval-censored data to simultaneously estimate the associations of township and sex with the susceptibility probability and the age-at-onset distribution of susceptible individuals for each disease. We then validated the onset sequences of 5 cardiometabolic diseases by comparing the overall probability density curves across township-sex strata. Visualization of these curves indicates that women tended to have onsets of abdominal obesity and hypo-α-lipoproteinemia in young adulthood, hypertension and hypertriglyceridemia in middle age, and diabetes later; men tended to have onsets of abdominal obesity, hypo-α-lipoproteinemia, and hypertriglyceridemia in young adulthood, hypertension in middle age, and diabetes later. Different onset patterns of abdominal obesity, hypo-α-lipoproteinemia, and male hypertension were identified between townships. Our proposed method provides a novel strategy for investigating both pathogenesis and preventive measures of complex syndromes.
    Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Pairs of spouses share common lifestyle factors. In a cross-sectional analysis, we investigated whether spouses of diabetic individuals had a higher prevalence of diabetes and cardiometabolic disorders in a community-based population of Chinese adults aged 40 years or older between 2011 and 2012. A total of 34,805 pairs of spouses were identified. All participants underwent a standard oral glucose tolerance test and provided detailed clinical, sociodemographic, and lifestyle information. Diabetes and multiple cardiometabolic disorders were defined according to standard criteria. Compared with participants whose spouses did not have diabetes, participants whose spouses had diabetes had higher odds of having diabetes (for men, odds ratio (OR) = 1.33, 95% confidence interval (CI): 1.22, 1.45; for women, OR = 1.35, 95% CI: 1.24, 1.47), obesity (for men, OR = 1.34, 95% CI: 1.13, 1.59; for women, OR = 1.19, 95% CI: 1.05, 1.35), metabolic syndrome (for men, OR = 1.31, 95% CI: 1.21, 1.42; for women, OR = 1.12, 95% CI: 1.04, 1.20), and cardiovascular disease (for men, OR = 1.18, 95% CI: 1.03, 1.34; for women, OR = 1.18, 95% CI: 1.03, 1.35). The associations were independent of age, body mass index, education, family history of diabetes, cigarette smoking, alcohol drinking, physical activity, and diet. Spousal diabetes was simple and valuable information for identifying individuals at risk for diabetes and cardiometabolic disorders.
    Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Debate continues on how to measure and weight diseases in multimorbidity. We quantified the association of a broad range of chronic diseases with physical health–related qualify of life and used these weights to develop and validate a multimorbidity weighted index (MWI). Community-dwelling adults in 3 national, prospective studies—the Nurses' Health Study (n = 121,701), Nurses' Health Study II (n = 116,686), and Health Professionals Follow-up Study (n = 51,529)—reported physician-diagnosed diseases and completed the Short Form 36 physical functioning (PF) scale over multiple survey cycles between 1992 and 2008. Mixed models were used to obtain regression coefficients for the impact of 98 morbid conditions on PF. The MWI was formed by weighting conditions by these coefficients and was validated through bootstrapping. The final sample included 612,592 observations from 216,890 participants (PF mean score = 46.5 (standard deviation, 11)). The association between diseases and PF varied severalfold (median, −1.4; range, −10.6 to 0.8). End-stage organ diseases were associated with the greatest reduction in PF. The mean MWI score was 4.8 (median, 3.7; range, 0–53), and the mean number of comorbid conditions was 3.3 (median, 2.8; range, 0–34). This validated MWI weights diseases by severity using PF, a patient-centered outcome. These results suggest that simple disease count is unlikely to capture the full impact of multimorbidity on health-related quality of life, and that the MWI is feasible and readily implemented.
    Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: The exposome has been defined as the totality of exposures individuals experience over the course of their lives and how those exposures affect health. Three domains of the exposome have been identified: internal, specific external, and general external. Internal factors are those that are unique to the individual, and specific external factors include occupational exposures and lifestyle factors. The general external domain includes sociodemographic factors such as educational level and financial status. Eliciting information on the exposome is daunting and not feasible at present; the undertaking may never be fully realized. A variety of tools have been identified to measure the exposome. Biomarker measurements will be one of the major tools in exposomic studies. However, exposure data can also be obtained from other sources such as sensors, geographic information systems, and conventional tools such as survey instruments. Proof-of-concept studies are being conducted that show the promise of exposomic investigation and the integration of different kinds of data. The inherent value of exposomic data in epidemiologic studies is that they can provide greater understanding of the relationships among a broad range of chemical and other risk factors and health conditions and ultimately lead to more effective and efficient disease prevention and control.
    Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: We investigated the association between socioeconomic status and ovarian cancer in African-American women. We used a population-based case-control study design that included case patients with incident ovarian cancer (n = 513) and age- and area-matched control participants (n = 721) from 10 states who were recruited into the African American Cancer Epidemiology Study from December 2010 through December 2014. Questionnaires were administered via telephone, and study participants responded to questions about several characteristics, including years of education, family annual income, and risk factors for ovarian cancer. After adjustment for established ovarian cancer risk factors, women with a college degree or more education had an odds ratio of 0.71 (95% confidence interval (CI): 0.51, 0.99) when compared with those with a high school diploma or less (P for trend = 0.02); women with family annual incomes of $75,000 or more had an odds ratio of 0.74 (95% CI: 0.47, 1.16) when compared with those with incomes less than $10,000 (P for trend = 0.055). When these variables were dichotomized, compared with women with a high school diploma or less, women with more education had an adjusted odds ratio of 0.72 (95% CI: 0.55, 0.93), and compared with women with an income less than $25,000, women with higher incomes had an adjusted odds ratio of 0.86 (95% CI: 0.66, 1.12). These findings suggest that ovarian cancer risk may be inversely associated with socioeconomic status among African-American women and highlight the need for additional evidence to more thoroughly characterize the association between socioeconomic status and ovarian cancer.
    Article · Aug 2016 · American Journal of Epidemiology
  • Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Social epidemiologists often seek to determine the mechanisms that underlie health disparities. This work is typically based on mediation procedures that may not be justified with exposures of common interest in social epidemiology. In this analysis, we explored the consequences of using standard approaches, referred to as the difference and generalized product methods, when mediator-outcome confounders are associated with the exposure. We compared these with inverse probability-weighted marginal structural models, the structural transformation method, doubly robust g-estimation of a structural nested model, and doubly robust targeted minimum loss-based estimation. We used data on 900,726 births from 2003 to 2007 in the Penn Moms study, conducted in Pennsylvania, to assess the extent to which breastfeeding prior to hospital discharge explained the racial disparity in infant mortality. Overall, for every 1,000 births, 3.36 more infant deaths occurred among non-Hispanic black women relative to all other women (95% confidence interval: 2.78, 3.93). Using the difference and generalized product methods to assess the disparity that would remain if everyone breastfed prior to discharge suggested a complete elimination of the disparity (risk difference = −0.87 per 1,000 births; 95% confidence interval: −1.39, −0.35). In contrast, doubly robust methods suggested a reduction in the disparity to 2.45 (95% confidence interval: 2.20, 2.71) more infant deaths per 1,000 births among non-Hispanic black women. Standard approaches for mediation analysis in health disparities research can yield misleading results.
    Article · Aug 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Traditional epidemiologic approaches allow us to compare counterfactual outcomes under 2 exposure distributions, usually 100% exposed and 100% unexposed. However, to estimate the population health effect of a proposed intervention, one may wish to compare factual outcomes under the observed exposure distribution to counterfactual outcomes under the exposure distribution produced by an intervention. Here, we used inverse probability weights to compare the 5-year mortality risk under observed antiretroviral therapy treatment plans to the 5-year mortality risk that would had been observed under an intervention in which all patients initiated therapy immediately upon entry into care among patients positive for human immunodeficiency virus in the US Centers for AIDS Research Network of Integrated Clinical Systems multisite cohort study between 1998 and 2013. Therapy-naïve patients (n = 14,700) were followed from entry into care until death, loss to follow-up, or censoring at 5 years or on December 31, 2013. The 5-year cumulative incidence of mortality was 11.65% under observed treatment plans and 10.10% under the intervention, yielding a risk difference of -1.57% (95% confidence interval: -3.08, -0.06). Comparing outcomes under the intervention with outcomes under observed treatment plans provides meaningful information about the potential consequences of new US guidelines to treat all patients with human immunodeficiency virus regardless of CD4 cell count under actual clinical conditions.
    Article · Jul 2016 · American Journal of Epidemiology
  • Tiange Wang · Yu Xu · Min Xu · [...] · Weiqing Wang
    [Show abstract] [Hide abstract] ABSTRACT: Prolactin plays an important role in maintaining a normal glucose homeostasis during pregnancy and beyond. Studies investigating the association between prolactin and type 2 diabetes beyond pregnancy are rare and none is prospective. We aimed to examine whether prolactin associates with type 2 diabetes prospectively in a Chinese population. In 2009, 2,377 participants aged 40 years or older were enrolled from Shanghai, China. Among 1,596 diabetes-free participants at baseline, 1,510 completed the follow-up investigation in 2013. Participants who had a fasting plasma glucose ≥126 mg/dL and/or a 2-hour plasma glucose ≥200 mg/dL during a 75-g oral glucose tolerance test had a definite diagnosis of type 2 diabetes or received antidiabetic therapies during follow-up were classified as having type 2 diabetes. During a mean follow-up of 3.7 years, 189 new cases of type 2 diabetes were documented. After multivariate adjustment, women in the highest quartile of prolactin showed the lowest risk for diabetes compared with those in the lowest quartile (hazard ratio = 0.48, 95% confidence interval: 0.26, 0.90). However, such significant associations were not observed in men. Prolactin may be a mediator in the pathogenesis of type 2 diabetes in women; however, more studies are needed to elucidate the underlying sex-specific mechanism.
    Article · Jul 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Vaccines are increasingly targeted toward women of reproductive age, and vaccines to prevent influenza and pertussis are recommended during pregnancy. Prelicensure clinical trials typically have not included pregnant women, and when they are included, trials cannot detect rare events. Thus, postmarketing vaccine safety assessments are necessary. However, analysis of observational data requires detailed assessment of potential biases. Using data from 8 Vaccine Safety Datalink sites in the United States, we analyzed the association of monovalent H1N1 influenza vaccine (MIV) during pregnancy with preterm birth (<37 weeks) and small-for-gestational-age birth (birth weight < 10th percentile). The cohort included 46,549 pregnancies during 2009–2010 (40% of participants received the MIV). We found potential biases in the vaccine–birth outcome association that might occur due to variable access to vaccines, the time-dependent nature of exposure to vaccination within pregnancy (immortal time bias), and confounding from baseline differences between vaccinated and unvaccinated women. We found a strong protective effect of vaccination on preterm birth (relative risk = 0.79, 95% confidence interval: 0.74, 0.85) when we ignored potential biases and no effect when accounted for them (relative risk = 0.91; 95% confidence interval: 0.83, 1.0). In contrast, we found no important biases in the association of MIV with small-for-gestational-age birth. Investigators conducting studies to evaluate birth outcomes after maternal vaccination should use statistical approaches to minimize potential biases.
    Article · Jul 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Immunization of pregnant women against influenza has the potential to reduce adverse fetal outcomes by reducing prenatal exposure to influenza illness. However, as touched on by Fell et al. (Am J Epidemiol. 2016;184(3):163–175) and Vazquez-Benitez et al. (Am J Epidemiol. 2016;184(3):176–186) in this issue of the Journal, observational studies in which the causal effect of maternal influenza illness and influenza immunization on fetal health are evaluated are prone to bias because of the complex temporal nature of influenza illness seasonality, influenza immunization schedules, and gestation itself. Immortal time bias is introduced by an “anytime-in-pregnancy” exposure definition because the shortened pregnancy duration associated with many adverse fetal outcomes limits the opportunity to become exposed, whereas including follow-up time during which pregnancies are no longer at risk of an adverse outcome (e.g., gestational time after 37 weeks in studies of preterm birth) can lead to overestimation of any true benefits of immunization (or harms from influenza illness). We present a framework to avoid time-related biases in the study of influenza illness and immunization in pregnancy and advise that investigations of fetal benefit from maternal influenza immunization should only be undertaken when information is available on the calendar time of influenza virus circulation and the gestational age at which maternal influenza immunization occurred.
    Article · Jul 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Individual-level epidemiologic studies of pregnancy outcomes after maternal influenza are limited in number and quality and have produced inconsistent results. We used a time-series design to investigate whether fluctuation in influenza virus circulation was associated with short-term variation in population-level rates of preterm birth, stillbirth, and perinatal death in Ontario between 2003 and 2012. Using Poisson regression, we assessed the association between weekly levels of circulating influenza virus and counts of outcomes offset by the number of at-risk gestations during 3 gestational exposure windows. The rate of preterm birth was not associated with circulating influenza level in the week preceding birth (adjusted rate ratio = 1.01, 95% confidence interval: 1.00, 1.02) or in any other exposure window. These findings were robust to alternate specifications of the model and adjustment for potential confounding. Stillbirth and perinatal death rates were similarly not associated with gestational exposure to influenza circulation during late pregnancy. We could not assess mortality outcomes relative to early gestational exposure because of missing dates of conception for many stillbirths. In this time-series study, population-level influenza circulation was not associated with short-term variation in rates of preterm birth, stillbirth, or perinatal death.
    Article · Jul 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: The present investigation was designed to determine the prevalence and types of dual and poly-use of tobacco products in the US Air Force, as well as characteristics and factors associated with these types. We conducted a cross-sectional assessment of tobacco-product use among 13,873 Air Force trainees from 2013 to 2014. The assessment included prevalence of the use of 10 different tobacco products and demographic and environmental factors, such as risk perceptions of tobacco use, peer use, and tobacco-company influences. Latent class analysis was carried out to determine types of poly-tobacco users. Tobacco-product use was reported by 27.1% of participants, and of those, over half reported using more than 1 tobacco product. Latent class analysis indicated 5 classes of poly-tobacco use. Factors associated with poly-tobacco (vs. mono-tobacco) use included lower confidence to remain tobacco-free, low harm perceptions, and receiving tobacco products free at bars or social events. Rates of dual and poly-tobacco use are high among trainees, and while these groups are similar to mono users in some ways, there are a number of differences that need to be considered when developing targeted interventions to address use of multiple tobacco products.
    Article · Jul 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Little is known about how combining efficacious interventions for human immunodeficiency virus (HIV) prevention could lead to HIV elimination. We used an agent-based simulation model, the HIV calibrated dynamic model, to assess the potential for HIV elimination in South Africa. We examined several scenarios (from continuation of the current status quo to perfect achievement of targets) with differing combinations of male condom use, adult male circumcision, HIV testing, and early antiretroviral therapy (ART). We varied numerous parameters, including the proportion of adult males circumcised, the frequency of condom use during sex acts, acceptance of HIV testing, linkage to health care, criteria for ART initiation, ART viral suppression rates, and loss to follow-up. Maintaining current levels of combination prevention would lead to increasing HIV incidence and prevalence in South Africa, while the perfect combination scenario was projected to eliminate HIV on a 50-year time scale from 2013 to 2063. Perfecting testing and treatment, without changing condom use or circumcision rates, resulted in an 89% reduction in HIV incidence but not elimination. Universal adult male circumcision alone resulted in a 21% incidence reduction within 20 years. Substantial decreases in HIV incidence are possible from sufficient uptake of both primary prevention and ART, but with continuation of the status quo, HIV elimination in South Africa is unlikely within a 50-year time scale.
    Article · Jul 2016 · American Journal of Epidemiology
  • [Show abstract] [Hide abstract] ABSTRACT: Unbiased estimation of causal parameters from marginal structural models (MSMs) requires a fundamental assumption of no unmeasured confounding. Unfortunately, the time-varying covariates used to obtain inverse probability weights are often error-prone. Although substantial measurement error in important confounders is known to undermine control of confounders in conventional unweighted regression models, this issue has received comparatively limited attention in the MSM literature. Here we propose a novel application of the simulation-extrapolation (SIMEX) procedure to address measurement error in time-varying covariates, and we compare 2 approaches. The direct approach to SIMEX-based correction targets outcome model parameters, while the indirect approach corrects the weights estimated using the exposure model. We assess the performance of the proposed methods in simulations under different clinically plausible assumptions. The simulations demonstrate that measurement errors in time-dependent covariates may induce substantial bias in MSM estimators of causal effects of time-varying exposures, and that both proposed SIMEX approaches yield practically unbiased estimates in scenarios featuring low-to-moderate degrees of error. We illustrate the proposed approach in a simple analysis of the relationship between sustained virological response and liver fibrosis progression among persons infected with hepatitis C virus, while accounting for measurement error in γ-glutamyltransferase, using data collected in the Canadian Co-infection Cohort Study from 2003 to 2014.
    Article · Jul 2016 · American Journal of Epidemiology