American Journal of Preventive Medicine (AM J PREV MED)

Publisher: American College of Preventive Medicine; Association of Teachers of Preventive Medicine, Elsevier Masson

Journal description

The American Journal of Preventive Medicine is the official journal of the American College of Preventive Medicine and the Association of Teachers of Preventive Medicine. It publishes articles in the areas of prevention research, teaching, practice and policy. Original research is published on interventions aimed at the prevention of chronic and acute disease and the promotion of individual and community health. Of particular emphasis are papers that address the primary and secondary prevention of important clinical, behavioral and public health issues such as injury and violence, infectious disease, women's health, smoking, sedentary behaviors and physical activity, nutrition, diabetes, obesity, and alcohol and drug abuse. Papers also address educational initiatives aimed at improving the ability of health professionals to provide effective clinical prevention and public health services. Papers on health services research pertinent to prevention and public health are also published. The journal also publishes official policy statements from the two co-sponsoring organizations, review articles, media reviews, and editorials. Finally, the journal periodically publishes supplements and special theme issues devoted to areas of current interest to the prevention community. For information on the American College of Preventive Medicine (ACPM) and the Association of Teachers of Preventive Medicine (ATPM), visit their web sites at the following URLs: http://www.acpm.org and http://www.atpm.org/.

Current impact factor: 4.28

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 4.281
2012 Impact Factor 3.945
2011 Impact Factor 4.044
2010 Impact Factor 4.11
2009 Impact Factor 4.235
2008 Impact Factor 3.766
2007 Impact Factor 3.489
2006 Impact Factor 3.497
2005 Impact Factor 3.167
2004 Impact Factor 3.188
2003 Impact Factor 3.256
2002 Impact Factor 2.63
2001 Impact Factor 2.064
2000 Impact Factor 2.192
1999 Impact Factor 1.442
1998 Impact Factor 1.199
1997 Impact Factor 0.995
1996 Impact Factor 0.829
1995 Impact Factor 0.856
1994 Impact Factor 0.617
1993 Impact Factor 0.549
1992 Impact Factor 0.646

Impact factor over time

Impact factor
Year

Additional details

5-year impact 5.25
Cited half-life 6.00
Immediacy index 2.25
Eigenfactor 0.04
Article influence 1.94
Website American Journal of Preventive Medicine website
Other titles American journal of preventive medicine
ISSN 0749-3797
OCLC 11120856
Material type Periodical, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Elsevier Masson

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • On authors personal or authors institutions server
    • Published source must be acknowledged
    • Must link to journal home page
    • Publisher's version/PDF cannot be used
    • Articles in some journals can be made Open Access on payment of additional charge
    • 'Elsevier Masson' is an imprint of 'Elsevier'
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Introduction: Diverse combinations of built environment (BE) features for physical activity (PA) are understudied. This study explored whether patterns of GIS-derived BE features explained objective and self-reported PA, sedentary behavior, and BMI. Methods: Neighborhood Quality of Life Study participants (N1⁄42,199, aged 20–65 years, 48.2% female, 26% ethnic minority) were sampled in 2001–2005 from Seattle / King County WA and Baltimore MD / Washington DC regions. Their addresses were geocoded to compute net residential density, land use mix, retail floor area ratio, intersection density, public transit, and public park and private recreation facility densities using a 1-km network buffer. Latent profile analyses (LPAs) were estimated from these variables. Multilevel regression models compared profiles on accelerometer- measured moderate to vigorous PA (MVPA) and self-reported PA, adjusting for covariates and clustering. Analyses were conducted in 2013–2014. Results: Seattle region LPAs yielded four profiles, including low walkability/transit/recreation (L-L-L); mean walkability/transit/recreation (M-M-M); moderately high walkability/transit/ recreation (MH-MH-MH); and high walkability/transit/recreation (H-HH). All measures were higher in the HHH than the LLL profile (difference of 17.1 minutes/day for MVPA, 146.5 minutes/week for walking for transportation, 58.2 minutes/week for leisure-time PA, and 2.2 BMI points; all po0.05). Baltimore region LPAs yielded four profiles, including L-L-L; M-M-M; high land use mix, transit, and recreation (HLU-HT-HRA); and high intersection density, high retail floor area ratio (HID-HRFAR). HLU-HT-HRA and L-L-L differed by 12.3 MVPA minutes/day; HID-HRFAR and L-L-L differed by 157.4 minutes/week for walking for trans- portation (all ps<0.05). Conclusions: Patterns of environmental features explain greater differences in adults’ PA than the four-component walkability index.
    American Journal of Preventive Medicine 07/2015; DOI:10.1016/j.amepre.2015.05.024
  • American Journal of Preventive Medicine 05/2015; DOI:10.1016/j.amepre.2015.02.016
  • [Show abstract] [Hide abstract]
    ABSTRACT: Context Evidence on the strength of the association between low SES and chronic kidney disease (CKD; measured by low estimated glomerular filtration rate [eGFR], high albuminuria, low eGFR/high albuminuria, and renal failure) is scattered and sometimes conflicting. Therefore, a systematic review and meta-analysis was performed to summarize the strength of the associations between SES and CKD and identify study-level characteristics related to this association. Evidence acquisition Studies published through January 2013 in MEDLINE and Embase were searched. From 35 studies that met the inclusion criteria, association estimates were pooled per CKD measure in the meta-analysis (performed between 2013 and 2014). Meta-regression analysis was used to identify study-level characteristics related to the strength of the SES–CKD association. Evidence synthesis Low SES was associated with low eGFR (OR=1.41, 95% CI=1.21, 1.62), high albuminuria (OR=1.52, 95% CI=1.22, 1.82), low eGFR/high albuminuria (OR=1.38, 95% CI=1.03, 1.74), and renal failure (OR=1.55, 95% CI=1.40, 1.71). Differences in SES measures across studies were not related to the strength of associations between low SES and any of the CKD measures (low GFR, p=0.63; high albuminuria, p=0.29; low eGFR/high albuminuria, p=0.54; renal failure, p=0.31). Variations in the strength of associations were related to the level of covariate adjustment for low eGFR (p<0.001) and high albuminuria (p<0.001). Conclusions Socioeconomic disparities in CKD were fairly strong, irrespective of how SES was measured. Variations in the strength of the associations were related to the level of covariate adjustment, particularly for low eGFR and high albuminuria.
    American Journal of Preventive Medicine 05/2015; 48(5):580-592. DOI:10.1016/j.amepre.2014.11.004.
  • American Journal of Preventive Medicine 04/2015; 48(4). DOI:10.1016/j.amepre.2014.10.023
  • American Journal of Preventive Medicine 04/2015; DOI:10.1016/j.amepre.2015.02.022
  • American Journal of Preventive Medicine 03/2015; 48(5). DOI:10.1016/j.amepre.2014.12.003
  • American Journal of Preventive Medicine 03/2015; 48(3):e5. DOI:10.1016/j.amepre.2014.11.011
  • American Journal of Preventive Medicine 03/2015; 48(3):e4. DOI:10.1016/j.amepre.2014.11.012
  • American Journal of Preventive Medicine 03/2015; 48(3):e1. DOI:10.1016/j.amepre.2014.11.001
  • American Journal of Preventive Medicine 02/2015; 48(2). DOI:10.1016/j.amepre.2014.10.021
  • American Journal of Preventive Medicine 02/2015; 48(5). DOI:10.1016/j.amepre.2014.11.006
  • [Show abstract] [Hide abstract]
    ABSTRACT: A computer-assisted tobacco decision support tool increased dental practitioners' (dentists and dental hygienists) advice to quit smoking and referral to a quitline during a group randomized trial. The purpose of this study is to document the extent to which use persisted after the trial. Electronic dental record (EDR) data from 2010 to 2013 were analyzed in 2014 for use of computer-assisted tobacco intervention tool advice scripts and referral to a quitline during four periods: during the trial and post-trial when only intervention clinic dental practitioners had access to the tool, and during full deployment, both before and after an EDR modification. Intervention clinic dental practitioners (18.5 dentist full-time equivalents [FTEs] and 27.8 dental hygienist FTEs practicing in seven clinics) referred 19.0% of 1,368 smokers to a quitline during the trial and referred 15.4% of 4,011 smokers post-trial. After full tool deployment but pre-EDR change, these dental practitioners referred 15.6% of 2,214 intervention clinic smokers, whereas 18.3 dentist FTEs and 29.7 dental hygienist FTEs practicing in eight clinics referred 8.5% of 2,113 smokers. Post-EDR change, dental practitioners referred 12.2% of 2,214 intervention clinic smokers and 8.1% of 2,399 control clinic smokers to a quitline. In the last three quarters of observation, clinic script use ranged from 15.4% to 65.8% and referral to a quitline ranged from 2.0% to 18.7% of visits. Although EDR design affected rates of referral, dental practitioners persisted in using a computer-assisted tobacco intervention tool to refer smokers to a quitline. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
    American Journal of Preventive Medicine 02/2015; 48(6). DOI:10.1016/j.amepre.2014.12.017
  • [Show abstract] [Hide abstract]
    ABSTRACT: Obesity incurs a substantial economic burden to healthcare systems. Little is known about the combined medical costs attributable to obesity among individuals with physical disabilities (PDs). To estimate the annual healthcare utilization and expenditure associated with overweight and obesity among adults with and without PDs. Weighted multivariate generalized linear models were used to estimate healthcare costs and utilization among adults with and without PDs, across standard BMI categories, using the 2002-2011 Medical Expenditure Panel Survey. The analyses, performed in 2013-2014, included a population representative sample of 215,107 individuals, aged ≥18 years. Overall, 36,349 adults reported moderate or significant PDs. The primary outcomes were total healthcare costs, physician office visits, and hospitalization. After adjusting for sociodemographic variables, self-rated mental and physical health, physical activity, and year, adults with PDs incurred more than 1.96 times the adjusted total healthcare costs ($4,298, 95% CI=$3,980, $4,617) than adults without PDs. Obese individuals spent significantly more than those at normal weight ($726, p<0.001). Obese individuals with PDs spent 1.13 times more than normal-weight individuals with PDs ($1,107, p<0.001) and >2.2 times more than normal-weight individuals without PDs ($5,197, p<0.001). PDs plus obesity represents $23.9 billion/year, or roughly 50% of the total costs attributable to obesity in the U.S. Across BMI categories, there was significantly greater healthcare utilization and cost among adults with PDs, independent of age, race, education, and SES. Health policies need to identify behavioral interventions that address both healthy weight achievement/maintenance and functional independence among all adults. Published by Elsevier Inc.
    American Journal of Preventive Medicine 02/2015; 48(4). DOI:10.1016/j.amepre.2014.11.007