<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:prism="http://prismstandard.org/namespaces/1.2/basic/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns="http://purl.org/rss/1.0/"><channel rdf:about="http://www.ajpmonline.org/?rss=yes"><title>American Journal of Preventive Medicine</title><description>American Journal of Preventive Medicine RSS feed: Current Issue.    The  American Journal of Preventive Medicine  is the official journal of the  American 
College of Preventive Medicine  and the  Association for Prevention Teaching 
and Research . 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 for Prevention Teaching and Research (APTR), visit their web sites at the following URLs: 
http://www.acpm.org/ 
and 
http://www.aptrweb.org
   </description><link>http://www.ajpmonline.org/?rss=yes</link><dc:publisher>Elsevier Inc.</dc:publisher><dc:language>en</dc:language><dc:rights> © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved. </dc:rights><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:issn>0749-3797</prism:issn><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:publicationDate>June 2013</prism:publicationDate><prism:copyright> © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved. </prism:copyright><prism:rightsAgent>healthpermissions@elsevier.com</prism:rightsAgent><items><rdf:Seq><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001682/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001578/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS074937971300158X/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS074937971300161X/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001761/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001724/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001591/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001736/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001372/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001827/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001712/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS074937971300175X/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001840/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001864/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001839/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001748/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001815/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001566/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713002080/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713001852/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713002092/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713002626/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS074937971300247X/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713002481/abstract?rss=yes"/><rdf:li rdf:resource="http://www.ajpmonline.org/article/PIIS0749379713002493/abstract?rss=yes"/></rdf:Seq></items></channel><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001682/abstract?rss=yes"><title>A Cash-Back Rebate Program for Healthy Food Purchases in South Africa: Results from Scanner Data</title><link>http://www.ajpmonline.org/article/PIIS0749379713001682/abstract?rss=yes</link><description>Background: Improving diet quality is a key health promotion strategy. There is much interest in the role of prices and financial incentives to encourage healthy diet, but no data from large population interventions.Purpose: This study examines the effect of a price reduction for healthy food items on household grocery shopping behavior among members of South Africa's largest health plan.Methods: The HealthyFood program provides a cash-back rebate of up to 25% for healthy food purchases in over 400 designated supermarkets across all provinces in South Africa. Monthly household supermarket food purchase scanner data between 2009 and 2012 are linked to 170,000 households (60% eligible for the rebate) with Visa credit cards. Two approaches were used to control for selective participation using these panel data: a household fixed-effect model and a case–control differences-in-differences model.Results: Rebates of 10% and 25% for healthy foods are associated with an increase in the ratio of healthy to total food expenditure by 6.0% (95% CI=5.3, 6.8) and 9.3% (95% CI=8.5, 10.0); an increase in the ratio of fruit and vegetables to total food expenditure by 5.7% (95% CI=4.5, 6.9) and 8.5% (95% CI=7.3, 9.7); and a decrease in the ratio of less desirable to total food expenditure by 5.6% (95% CI=4.7, 6.5) and 7.2% (95% CI=6.3, 8.1).Conclusions: Participation in a rebate program for healthy foods led to increases in purchases of healthy foods and to decreases in purchases of less-desirable foods, with magnitudes similar to estimates from U.S. time-series data.</description><dc:title>A Cash-Back Rebate Program for Healthy Food Purchases in South Africa: Results from Scanner Data</dc:title><dc:creator>Roland Sturm, Ruopeng An, Darren Segal, Deepak Patel</dc:creator><dc:identifier>10.1016/j.amepre.2013.02.011</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>567</prism:startingPage><prism:endingPage>572</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001578/abstract?rss=yes"><title>School Soft Drink Availability and Consumption Among U.S. Secondary Students</title><link>http://www.ajpmonline.org/article/PIIS0749379713001578/abstract?rss=yes</link><description>Background: Consumption of sugar-sweetened beverages (SSBs) such as soft drinks has been associated with significantly increased energy intake and body weight. One strategy used to reduce soft drink consumption among adolescents has been reducing availability in schools; however, research is limited on associations between availability of soft drinks in school and student consumption.Purpose: This study examines associations between regular and diet soft drink availability in schools and student consumption using data from 329 secondary schools and 9284 students.Methods: Data were obtained from two sources: (1) nationally representative cross-sectional samples of students in Grades 8, 10, and 12 from U.S. public and private schools in 2010 and 2011 in the Monitoring the Future study and (2) administrators of the same schools in the Youth, Education, and Society study. Multilevel modeling conducted in 2012 examined associations between school availability and student consumption controlling for student sociodemographics and school characteristics.Results: In the total sample of more than 9000 students, regular and diet soft drink availability in school was not related to student consumption of these beverages in multivariate models. Yet, among African-American high school students, school regular and diet soft drink availability was significantly related to higher daily consumption (both before and after controlling for student and school factors).Conclusions: Although removal of soft drinks from schools may not result in significantly lower overall student consumption, such actions may result in significant decreases in soft drink consumption for specific student groups.</description><dc:title>School Soft Drink Availability and Consumption Among U.S. Secondary Students</dc:title><dc:creator>Yvonne M. Terry-McElrath, Patrick M. O’Malley, Lloyd D. Johnston</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.026</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>573</prism:startingPage><prism:endingPage>582</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS074937971300158X/abstract?rss=yes"><title>Vending and School Store Snack and Beverage Trends: Minnesota Secondary Schools, 2002–2010</title><link>http://www.ajpmonline.org/article/PIIS074937971300158X/abstract?rss=yes</link><description>Background: The Child Nutrition and WIC Reauthorization Act of 2004 (hereafter called the 2004 Reauthorization Act) was federal legislation that required school districts participating in the federally funded school meal program to develop and implement policies addressing nutrition guidelines for all foods and beverages available on school campuses by the onset of the 2006/2007 school year.Purpose: Vending machine and school store (VMSS) availability and low-nutrient, energy-dense snacks and beverages in VMSS were assessed in a statewide sample of Minnesota secondary schools before and after the 2004 Reauthorization Act was implemented in 2006/2007.Methods: The CDC School Health Profiles principal survey was collected from a representative sample of middle (n=170) and high (n=392) schools biennially from 2002 to 2010. Trends were estimated using general linear models with a logit link and linear spline modeling. Analyses were conducted in 2012.Results: Among high schools, VMSS (p=0.001) and sugar-sweetened beverages (p=0.004), high-fat salty snacks (p=0.001), and candy (p=0.001) in VMSS decreased from 2002 to 2008. In 2008, a change in slope direction from negative to positive occurred for all food practices and an increase in VMSS (p=0.014) and sugar-sweetened beverages (p=0.033) was seen. Among middle schools, VMSS (p=0.027), sugar-sweetened beverages (p=0.001), high-fat salty snacks (p=0.001), and candy (p=0.029) decreased from 2002 to 2010.Conclusions: This study supports a link between policy and sustainable decreases in some food practices but not others and a differential effect that favors middle schools over high schools. Policy-setting is a dynamic process requiring ongoing surveillance to identify shifting trends.</description><dc:title>Vending and School Store Snack and Beverage Trends: Minnesota Secondary Schools, 2002–2010</dc:title><dc:creator>Martha Y. Kubik, Cynthia Davey, Marilyn S. Nanney, Richard F. MacLehose, Toben F. Nelson, Brandon Coombes</dc:creator><dc:identifier>10.1016/j.amepre.2013.02.009</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>583</prism:startingPage><prism:endingPage>588</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS074937971300161X/abstract?rss=yes"><title>Nutritional Quality at Eight U.S. Fast-Food Chains: 14-Year Trends</title><link>http://www.ajpmonline.org/article/PIIS074937971300161X/abstract?rss=yes</link><description>Background: Frequent consumption of fast-food menu items that are high in fat, sugar, and sodium contribute to poor dietary quality, increasing individuals’ risk for diet-related chronic diseases.Purpose: To assess 14-year trends in the nutritional quality of menu offerings at eight fast-food restaurant chains in the U.S.Methods: Data on menu items and food and nutrient composition were obtained in 2011 from archival versions of the University of Minnesota Nutrition Coordinating Center Food and Nutrient Database for eight fast-food restaurant chains. In this database, ingredient and nutrition information for all foods sold by the fast-food restaurants were updated biannually between 1997/1998 and 2009/2010. Healthy Eating Index (HEI)-2005 scores were calculated for each restaurant menu as a measure of the extent to which menu offerings were consistent with Dietary Guidelines for Americans and compared over time.Results: Of a possible index total of 100 (healthiest), the HEI-2005 score across all eight fast-food restaurants was 45 in 1997/1998 and 48 in 2009/2010. Individually, restaurant scores in 1997/1998 ranged from 37 to 56 and in 2009/2010 ranged from 38 to 56. The greatest improvements in nutritional quality were seen in the increase of meat/beans, decrease in saturated fat, and decrease in the proportion of calories from solid fats and added sugars. The HEI-2005 score improved in six restaurants and decreased in two.Conclusions: The nutritional quality of menu offerings at fast-food restaurant chains included in this study increased over time, but further improvements are needed. Fast-food restaurants have an opportunity to contribute to a healthy diet for Americans by improving the nutritional quality of their menus.</description><dc:title>Nutritional Quality at Eight U.S. Fast-Food Chains: 14-Year Trends</dc:title><dc:creator>Mary O. Hearst, Lisa J. Harnack, Katherine W. Bauer, Alicia A. Earnest, Simone A. French, J. Michael Oakes</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.028</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>589</prism:startingPage><prism:endingPage>594</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001761/abstract?rss=yes"><title>Menu Labeling Regulations and Calories Purchased at Chain Restaurants</title><link>http://www.ajpmonline.org/article/PIIS0749379713001761/abstract?rss=yes</link><description>Background: The federal menu labeling law will require chain restaurants to post caloric information on menus, but the impact of labeling is uncertain.Purpose: The goal of the current study was to examine the effect of menu labeling on calories purchased, and secondarily, to assess self-reported awareness and use of labels.Design: Single-community pre–post–post cross-sectional study. Data were collected in 2008–2010 and analyzed in 2011–2012.Setting/participants: 50 sites from 10 chain restaurants in King County, Washington, selected through stratified, two-stage cluster random sampling. A total of 7325 customers participated. Eligibility criteria were: being an English speaker, aged≥14 years, and having an itemized receipt. The study population was 59% male, 76% white non-Hispanic, and 53% aged&lt;40 years.Intervention: A regulation requiring chain restaurants to post calorie information on menus or menu boards was implemented.Main outcome measures: Mean number of calories purchased.Results: No significant changes occurred between baseline and 4–6 months postregulation. Mean calories per purchase decreased from 908.5 to 870.4 at 18 months post-implementation (38 kcal, 95% CI=−76.9, 0.8, p=0.06) in food chains and from 154.3 to 132.1 (22 kcal, 95% CI=−35.8, −8.5, p=0.002) in coffee chains. Calories decreased in taco and coffee chains, but not in burger and sandwich establishments. They decreased more among women than men in coffee chains. Awareness of labels increased from 18.8% to 61.7% in food chains and from 4.4% to 30.0% in coffee chains (both p&lt;0.001). Among customers seeing calorie information, the proportion using it (about one third) did not change substantially over time. After implementation, food chain customers using information purchased on average fewer calories compared to those seeing but not using (difference=143.2 kcal, p&lt;0.001) and those not seeing (difference=135.5 kcal, p&lt;0.001) such information.Conclusions: Mean calories per purchase decreased 18 months after implementation of menu labeling in some restaurant chains and among women but not men.</description><dc:title>Menu Labeling Regulations and Calories Purchased at Chain Restaurants</dc:title><dc:creator>James W. Krieger, Nadine L. Chan, Brian E. Saelens, Myduc L. Ta, David Solet, David W. Fleming</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.031</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>595</prism:startingPage><prism:endingPage>604</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001724/abstract?rss=yes"><title>5-Year Changes in Afterschool Physical Activity and Sedentary Behavior</title><link>http://www.ajpmonline.org/article/PIIS0749379713001724/abstract?rss=yes</link><description>Background: The afterschool period holds promise for the promotion of physical activity, yet little is known about the importance of this period as children age.Purpose: To examine changes in physical activity of children aged 5–6 years and 10–12 years and their sedentary time in the afterschool period over 3 and 5 years, and to determine the contribution of this period to daily physical activity and sedentary behavior over time.Methods: Data from two longitudinal studies conducted in Melbourne, Australia, were used. Accelerometer data were provided for 2053 children at baseline (Children Living in Active Neighbourhoods Study [CLAN]: 2001; Health, Eating and Play Study [HEAPS]: 2002/2003); 756 at 3-year follow-up (time point 2 [T2]); and 622 at 5-year follow-up (T3). Light (LPA), moderate (MPA) and vigorous (VPA) physical activity were determined using age-adjusted cut-points. Sedentary time was defined as≤100counts/minute. Multilevel analyses, conducted in April 2012, assessed change in physical activity and sedentary time and the contributions of the afterschool period to overall levels.Results: Afterschool MPA and VPA decreased among both cohorts, particularly in the younger cohort, who performed less than half of their baseline levels at T3 (MPA: T1=24minutes; T3=11minutes; VPA: T1=12minutes; T3=4minutes). LPA also declined in the older cohort. Afterschool sedentary time increased among the younger (T1=42minutes; T3=64minutes) and older cohorts (T1=57minutes; T3=84minutes). The contribution of the afterschool period to overall MPA and VPA increased in the older cohort from 23% to 33% over 5 years. In the younger cohort, the contribution of the afterschool period to daily MPA and VPA decreased by 3% over 5 years.Conclusions: The importance of the afterschool period for children’s physical activity increases with age, particularly as children enter adolescence.</description><dc:title>5-Year Changes in Afterschool Physical Activity and Sedentary Behavior</dc:title><dc:creator>Lauren Arundell, Nicola D. Ridgers, Jenny Veitch, Jo Salmon, Trina Hinkley, Anna Timperio</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.029</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>605</prism:startingPage><prism:endingPage>611</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001591/abstract?rss=yes"><title>Sexual Orientation Disparities in Cardiovascular Biomarkers Among Young Adults</title><link>http://www.ajpmonline.org/article/PIIS0749379713001591/abstract?rss=yes</link><description>Background: Emerging evidence from general population studies suggests that lesbian, gay, and bisexual (LGB) adults are more likely to experience adverse cardiovascular outcomes relative to heterosexuals. No studies have examined whether sexual orientation disparities exist in biomarkers of early cardiovascular disease risk.Purpose: To determine whether sexual orientation disparities in biomarkers of early cardiovascular risk are present among young adults.Methods: Data come from Wave IV (2008–2009) of the National Longitudinal Study for Adolescent Health (N=12,451), a prospective nationally representative study of U.S. adolescents followed into young adulthood (mean age=28.9 years). A total of 520 respondents identified as lesbian, gay, or bisexual. Biomarkers included C-reactive protein, glycosylated hemoglobin, systolic and diastolic blood pressure, and pulse rate. Analyses were conducted in 2012.Results: In gender-stratified models adjusted for demographics (age, race/ethnicity); SES (income, education); health behaviors (smoking, regular physical activity, alcohol consumption); and BMI, gay and bisexual men had significant elevations in C-reactive protein, diastolic blood pressure, and pulse rate, compared to heterosexual men. Despite having more risk factors for cardiovascular disease, including smoking, heavy alcohol consumption, and higher BMI, lesbians and bisexual women had lower levels of C-reactive protein than heterosexual women in fully adjusted models.Conclusions: Evidence was found for sexual orientation disparities in biomarkers of cardiovascular risk among young adults, particularly in gay and bisexual men. These findings, if confirmed in other studies, suggest that disruptions in core physiologic processes that ultimately confer risk for cardiovascular disease may occur early in the life course for sexual-minority men.</description><dc:title>Sexual Orientation Disparities in Cardiovascular Biomarkers Among Young Adults</dc:title><dc:creator>Mark L. Hatzenbuehler, Katie A. McLaughlin, Natalie Slopen</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.027</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>612</prism:startingPage><prism:endingPage>621</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001736/abstract?rss=yes"><title>Problem Behavior and Urban, Low-Income Youth: A Randomized Controlled Trial of Positive Action in Chicago</title><link>http://www.ajpmonline.org/article/PIIS0749379713001736/abstract?rss=yes</link><description>Background: Youth problem behaviors remain a public health issue. Youth in low-income, urban areas are particularly at risk for engaging in aggressive, violent, and disruptive behaviors.Purpose: To evaluate the effects of a school-based social–emotional learning and health promotion program on problem behaviors and related attitudes among low-income, urban youth.Design: A matched-pair, cluster RCT.Setting/participants: Participants were drawn from 14 Chicago Public Schools over a 6-year period of program delivery with outcomes assessed for a cohort of youth followed from Grades 3 to 8. Data were collected from Fall 2004 to Spring 2010, and analyzed in Spring 2012.Intervention: The Positive Action program includes a scoped and sequenced K–12 classroom curriculum with six components: self-concept, social and emotional positive actions for managing oneself responsibly, and positive actions directed toward physical and mental health, honesty, getting along with others, and continually improving oneself. The program also includes teacher, counselor, family, and community training as well as activities directed toward schoolwide climate development.Main outcome measures: Youth reported on their normative beliefs in support of aggression and on their bullying, disruptive, and violent behaviors; parents rated youths’ bullying behaviors and conduct problems; schoolwide data on disciplinary referrals and suspensions were obtained from school records.Results: Multilevel growth-curve modeling analyses conducted on completion of the trial indicated that Positive Action mitigated increases over time in (1) youth reports of normative beliefs supporting aggressive behaviors and of engaging in disruptive behavior and bullying (girls only) and (2) parent reports of youth bullying behaviors (boys only). At study end-point, students in Positive Action schools also reported a lower rate of violence-related behavior than students in control schools. Schoolwide findings indicated positive program effects on both disciplinary referrals and suspensions. Program effect sizes ranged from −0.26 to −0.68.Conclusions: These results extend evidence of the effectiveness of the Positive Action program to low-income, minority, urban school settings, and to middle school–aged youth.Trial registration: This study is registered at ClinicalTrials.gov NCT01025674.</description><dc:title>Problem Behavior and Urban, Low-Income Youth: A Randomized Controlled Trial of Positive Action in Chicago</dc:title><dc:creator>Kendra M. Lewis, Marc B. Schure, Niloofar Bavarian, David L. DuBois, Joseph Day, Peter Ji, Naida Silverthorn, Alan Acock, Samuel Vuchinich, Brian R. Flay</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.030</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Research Articles</prism:section><prism:startingPage>622</prism:startingPage><prism:endingPage>630</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001372/abstract?rss=yes"><title>Cost Savings Associated with Prohibiting Smoking in U.S. Subsidized Housing</title><link>http://www.ajpmonline.org/article/PIIS0749379713001372/abstract?rss=yes</link><description>Background: Tobacco smoking in multiunit housing can lead to secondhand-smoke (SHS) exposure among nonsmokers, increased maintenance costs for units where smoking is permitted, and fire risks. During 2009–2010, approximately 7.1 million individuals lived in subsidized housing in the U.S., a large proportion of which were children, elderly, or disabled.Purpose: This study calculated the annual economic costs to society that could be averted by prohibiting smoking in all U.S. subsidized housing.Methods: Estimated annual cost savings associated with SHS-related health care, renovation of units that permit smoking, and smoking-attributable fires in U.S. subsidized housing were calculated using residency estimates from the U.S. Department of Housing and Urban Development and previously reported national and state cost estimates for these indicators. When state estimates were used, a price deflator was applied to account for differential costs of living or pricing across states. Estimates were calculated overall and by cost type for all U.S. subsidized housing, as well as for public housing only. Data were obtained and analyzed between January and March 2011.Results: Prohibiting smoking in all U.S. subsidized housing would yield cost savings of approximately $521 million per year, including $341 million in SHS-related healthcare expenditures, $108 million in renovation expenses, and $72 million in smoking-attributable fire losses. Prohibiting smoking in U.S. public housing alone would yield cost savings of approximately $154 million per year.Conclusions: Efforts to prohibit smoking in all U.S. subsidized housing would protect health and generate substantial cost savings to society.</description><dc:title>Cost Savings Associated with Prohibiting Smoking in U.S. Subsidized Housing</dc:title><dc:creator>Brian A. King, Richard M. Peck, Stephen D. Babb</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.024</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Brief Reports</prism:section><prism:startingPage>631</prism:startingPage><prism:endingPage>634</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001827/abstract?rss=yes"><title>Neighborhood Walkability: Field Validation of Geographic Information System Measures</title><link>http://www.ajpmonline.org/article/PIIS0749379713001827/abstract?rss=yes</link><description>Background: Given the health benefits of walking, there is interest in understanding how physical environments favor walking. Although GIS-derived measures of land-use mix, street connectivity, and residential density are commonly combined into indices to assess how conducive neighborhoods are to walking, field validation of these measures is limited.Purpose: To assess the relationship between audit- and GIS-derived measures of overall neighborhood walkability and between objective (audit- and GIS-derived) and participant-reported measures of walkability.Methods: Walkability assessments were conducted in 2009. Street-level audits were conducted using a modified version of the Pedestrian Environmental Data Scan. GIS analyses were used to derive land-use mix, street connectivity, and residential density. Participant perceptions were assessed using a self-administered questionnaire. Audit, GIS, and participant-reported indices of walkability were calculated. Spearman correlation coefficients were used to assess the relationships between measures. All analyses were conducted in 2012.Results: The correlation between audit- and GIS-derived measures of overall walkability was high (R=0.7 [95% CI=0.6, 0.8]); the correlations between objective (audit and GIS-derived) and participant-reported measures were low (R=0.2 [95% CI=0.06, 0.3]; R=0.2 [95% CI=0.04, 0.3], respectively). For comparable audit and participant-reported items, correlations were higher for items that appeared more objective (e.g., sidewalk presence, R=0.4 [95% CI=0.3, 0.5], versus safety, R=0.1 [95% CI=0.003, 0.3]).Conclusions: The GIS-derived measure of walkability correlated well with the in-field audit, suggesting that it is reasonable to use GIS-derived measures in place of more labor-intensive audits. Interestingly, neither audit- nor GIS-derived measures correlated well with participants’ perceptions of walkability.</description><dc:title>Neighborhood Walkability: Field Validation of Geographic Information System Measures</dc:title><dc:creator>Samantha Hajna, Kaberi Dasgupta, Max Halparin, Nancy A. Ross</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.033</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Brief Reports</prism:section><prism:startingPage>e51</prism:startingPage><prism:endingPage>e55</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001712/abstract?rss=yes"><title>Interventions to Prevent Post-Traumatic Stress Disorder: A Systematic Review</title><link>http://www.ajpmonline.org/article/PIIS0749379713001712/abstract?rss=yes</link><description>Context: Traumatic events are prevalent worldwide; trauma victims seek help in numerous clinical and emergency settings. Using effective interventions to prevent post-traumatic stress disorder (PTSD) is increasingly important. This review assessed the efficacy, comparative effectiveness, and harms of psychological, pharmacologic, and emerging interventions to prevent PTSD.Evidence acquisition: The following sources were searched for research on interventions to be included in the review: MEDLINE; Cochrane Library; CINAHL; EMBASE; PILOTS (Published International Literature on Traumatic Stress); International Pharmaceutical Abstracts; PsycINFO; Web of Science; reference lists of published literature; and unpublished literature (January 1, 1980 to July 30, 2012). Two reviewers independently selected studies, extracted data or checked accuracy, assessed study risk of bias, and graded strength of evidence. All data synthesis occurred between January and September 2012.Evidence synthesis: Nineteen studies covered various populations, traumas, and interventions. In meta-analyses of three trials (from the same team) for people with acute stress disorder, brief trauma-focused cognitive behavioral therapy was more effective than supportive counseling in reducing the severity of PTSD symptoms (moderate-strength); these two interventions had similar results for incidence of PTSD (low-strength); depression severity (low-strength); and anxiety severity (moderate-strength). PTSD symptom severity after injury decreased more with collaborative care than usual care (single study; low-strength). Debriefing did not reduce incidence or severity of PTSD or psychological symptoms in civilian traumas (low-strength). Evidence about relevant outcomes was unavailable for many interventions or was insufficient owing to methodologic shortcomings.Conclusions: Evidence is very limited regarding best practices to treat trauma-exposed individuals. Brief cognitive behavioral therapy may reduce PTSD symptom severity in people with acute stress disorder; collaborative care may help decrease symptom severity post-injury.</description><dc:title>Interventions to Prevent Post-Traumatic Stress Disorder: A Systematic Review</dc:title><dc:creator>Catherine A. Forneris, Gerald Gartlehner, Kimberly A. Brownley, Bradley N. Gaynes, Jeffrey Sonis, Emmanuel Coker-Schwimmer, Daniel E. Jonas, Amy Greenblatt, Tania M. Wilkins, Carol L. Woodell, Kathleen N. Lohr</dc:creator><dc:identifier>10.1016/j.amepre.2013.02.013</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Review and Special Articles</prism:section><prism:startingPage>635</prism:startingPage><prism:endingPage>650</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS074937971300175X/abstract?rss=yes"><title>Tracking Physical Activity and Sedentary Behavior in Childhood: A Systematic Review</title><link>http://www.ajpmonline.org/article/PIIS074937971300175X/abstract?rss=yes</link><description>Context: To date, no reviews have investigated the evidence of tracking of physical activity and sedentary behavior specifically during early childhood (aged 0–5.9 years) or from early childhood to middle childhood (aged 6–12 years). It is important to review the evidence of tracking of these behaviors to determine their stability during the foundational early years of life.Evidence acquisition: A literature search of studies was conducted in seven electronic databases (January 1980 to April 2012). Studies were compared on methodologic quality and evidence of tracking of physical activity or sedentary behavior. Tracking was defined as the stability (or relative ranking within a cohort) of behaviors, such as physical activity and sedentary behavior, over time.Evidence synthesis: Eleven studies met the inclusion criteria. All studies reporting physical activity outcomes had high methodologic quality; 71% of studies reporting sedentary behavior outcomes had high methodologic quality. Of the tracking coefficients for physical activity, 4% were large, 60% were moderate, and 36% were small. Of the tracking coefficients for sedentary behavior, 33% were large, 50% were moderate, and 17% were small. Overall, there was evidence of moderate tracking of physical activity during early childhood, and from early childhood to middle childhood, and of moderate-to-large tracking of sedentary behavior during early childhood and from early childhood to middle childhood.Conclusions: This review highlights the importance of establishing recommended levels of physical activity and sedentary behavior during the early years of life. Based on this review, the following recommendations are made: (1) early childhood should be targeted as a critical time to promote healthy lifestyle behaviors through methodologically sound prevention studies; and (2) future tracking studies should assess a broad range of sedentary behaviors using objective measures.</description><dc:title>Tracking Physical Activity and Sedentary Behavior in Childhood: A Systematic Review</dc:title><dc:creator>Rachel A. Jones, Trina Hinkley, Anthony D. Okely, Jo Salmon</dc:creator><dc:identifier>10.1016/j.amepre.2013.03.001</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Review and Special Articles</prism:section><prism:startingPage>651</prism:startingPage><prism:endingPage>658</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001840/abstract?rss=yes"><title>Equity-Specific Effects of 26 Dutch Obesity-Related Lifestyle Interventions</title><link>http://www.ajpmonline.org/article/PIIS0749379713001840/abstract?rss=yes</link><description>Context: Reducing health inequalities is a policy priority in many developed countries. Little is known about effective strategies to reduce inequalities in obesity and its underlying behaviors. The goal of the study was to investigate differential effectiveness of interventions aimed at obesity prevention, the promotion of physical activity or a healthy diet by SES.Evidence acquisition: Subgroup analyses in 2010 and 2011 of 26 Dutch studies funded by The Netherlands Organization for Health Research and Development after 1990 (n=17) or identified by expert contact (n=9). Methodologic quality and differential effects were synthesized in harvest plots, subdivided by setting, age group, intensity, and time to follow-up.Evidence synthesis: Seven lifestyle interventions were rated more effective and four less effective in groups with high SES; for 15 studies no differential effects could be demonstrated. One study in the healthcare setting showed comparable effects in both socioeconomic groups. The only mass media campaign provided modest evidence for higher effectiveness among those with high SES. Individually tailored and workplace interventions were either more effective in higher-SES groups (n=4) or no differential effects were demonstrated (n=9). School-based studies (n=7) showed mixed results. Two of six community studies provided evidence for better effectiveness in lower-SES groups; none were more effective in higher-SES groups. One high-intensity community-based study provided best evidence for higher effectiveness in low-SES groups.Conclusions: Although for the majority of interventions aimed at obesity prevention, the promotion of physical activity, or a healthy diet, no differential effectiveness could be demonstrated, interventions may widen as well as reduce socioeconomic inequalities in these outcomes. Equity-specific subgroup analyses contribute to needed knowledge about what may work to reduce socioeconomic inequalities in obesity and underlying health behaviors.</description><dc:title>Equity-Specific Effects of 26 Dutch Obesity-Related Lifestyle Interventions</dc:title><dc:creator>Tessa Magnée, Alex Burdorf, Johannes Brug, Stef P.M. Kremers, Anke Oenema, Patricia van Assema, Nicole P.M. Ezendam, Lenneke van Genugten, Ingrid J. Hendriksen, Marijke Hopman-Rock, Wilma Jansen, Johan de Jong, Paul L. Kocken, Willemieke Kroeze, Lydia Kwak, Lilian Lechner, Jascha de Nooijer, Mireille N. van Poppel, Suzan J.W. Robroek, Hanneke Schreurs, Esther M. van Sluijs, Ingrid J.M. Steenhuis, Maartje M. van Stralen, Nannah I. Tak, Saskia J. te Velde, Willemijn M. Vermeer, Birgitte Wammes, Marieke F. van Wier, Frank J. van Lenthe</dc:creator><dc:identifier>10.1016/j.amepre.2012.11.041</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Review and Special Articles</prism:section><prism:startingPage>e57</prism:startingPage><prism:endingPage>e66</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001864/abstract?rss=yes"><title>Financial Incentives for Healthy Behavior: Ethical Safeguards for Behavioral Economics</title><link>http://www.ajpmonline.org/article/PIIS0749379713001864/abstract?rss=yes</link><description>Abstract: Economic incentives to promote healthy behavior are becoming increasingly common and have been suggested as an approach to decreasing healthcare costs. Ethical concerns about programs with such incentives are that they may contribute to inequities, be coercive, interfere with therapeutic relationships, undermine personal responsibility for health, and decrease social solidarity. Additionally, they may be a source of stigma or discrimination, promote dependence, and be unfair for those already engaged in targeted health behaviors or those who cannot fulfill the incentivized behaviors. Incentive programs need to incorporate appropriate safeguards to monitor these risks and support fairness in offering economic incentives to promote healthy behavior.</description><dc:title>Financial Incentives for Healthy Behavior: Ethical Safeguards for Behavioral Economics</dc:title><dc:creator>Karsten Lunze, Michael K. Paasche-Orlow</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.035</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Review and Special Articles</prism:section><prism:startingPage>659</prism:startingPage><prism:endingPage>665</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001839/abstract?rss=yes"><title>Prevention Screening and Counseling: Strategy for Integration Into Medical Education and Practice</title><link>http://www.ajpmonline.org/article/PIIS0749379713001839/abstract?rss=yes</link><description>Abstract: Providing optimal preventive services across the life span is integral to improving the nation’s health. However, teaching future health professionals evidence-based prevention screening and counseling has notable limitations. Applying the U.S. Preventive Services Task Force (Task Force) preventive services recommendations is necessary but not sufficient to teach comprehensive and practical preventive services delivery. Certain important health topics have not yet been investigated by the Task Force; other Task Force health topics have insufficient evidence or nonspecific recommendations. The purpose of the current paper is to provide a strategy and develop a tool to educate future healthcare professionals in recommendations for prevention screening and counseling.Age-specific preventive history charts for children and adults were created using a total of 60 recommendations from the following sources (with number of recommendations shown): the Task Force (n=37); four primary care professional organizations (n=15); and a representative panel of experts (n=8). Using a systematic approach that incorporates other accredited organizations and inclusion criteria (as described) yielded a practical tool that is applicable in both educational and clinical settings.</description><dc:title>Prevention Screening and Counseling: Strategy for Integration Into Medical Education and Practice</dc:title><dc:creator>Sarah M. Mian, Suzanne Lazorick, Kristina L. Simeonsson, Hayley F. Afanador, Chelsea L. Stowe, Lloyd F. Novick</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.034</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Topics in Education</prism:section><prism:startingPage>666</prism:startingPage><prism:endingPage>671</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001748/abstract?rss=yes"><title>Strategies to Reduce Indoor Tanning: Current Research Gaps and Future Opportunities for Prevention</title><link>http://www.ajpmonline.org/article/PIIS0749379713001748/abstract?rss=yes</link><description>Abstract: Exposure to ultraviolet radiation from indoor tanning device use is associated with an increased risk of skin cancer, including risk of malignant melanoma, and is an urgent public health problem. By reducing indoor tanning, future cases of skin cancer could be prevented, along with the associated morbidity, mortality, and healthcare costs. On August 20, 2012, the CDC hosted a meeting to discuss the current body of evidence on strategies to reduce indoor tanning as well as research gaps. Using the Action Model to Achieve Healthy People 2020 Overarching Goals as a framework, the current paper provides highlights on the topics that were discussed, including (1) the state of the evidence on strategies to reduce indoor tanning; (2) the tools necessary to effectively assess, monitor, and evaluate the short- and long-term impact of interventions designed to reduce indoor tanning; and (3) strategies to align efforts at the national, state, and local levels through transdisciplinary collaboration and coordination across multiple sectors. Although many challenges and barriers exist, a coordinated, multilevel, transdisciplinary approach has the potential to reduce indoor tanning and prevent future cases of skin cancer.</description><dc:title>Strategies to Reduce Indoor Tanning: Current Research Gaps and Future Opportunities for Prevention</dc:title><dc:creator>Dawn M. Holman, Kathleen A. Fox, Jeffrey D. Glenn, Gery P. Guy, Meg Watson, Katie Baker, Vilma Cokkinides, Mark Gottlieb, DeAnn Lazovich, Frank M. Perna, Blake P. Sampson, Andrew B. Seidenberg, Craig Sinclair, Alan C. Geller</dc:creator><dc:identifier>10.1016/j.amepre.2013.02.014</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Theme: Strategies to Prevent Skin Cancer</prism:section><prism:startingPage>672</prism:startingPage><prism:endingPage>681</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001815/abstract?rss=yes"><title>Preventing Skin Cancer Through Reduction of Indoor Tanning: Current Evidence</title><link>http://www.ajpmonline.org/article/PIIS0749379713001815/abstract?rss=yes</link><description>Abstract: Exposure to ultraviolet radiation from indoor tanning devices (tanning beds, booths, and sun lamps) or from the sun contributes to the risk of skin cancer, including melanoma, which is the type of skin cancer responsible for most deaths. Indoor tanning is common among certain groups, especially among older adolescents and young adults, adolescent girls and young women, and non-Hispanic whites. Increased understanding of the health risks associated with indoor tanning has led to many efforts to reduce use. Most environmental and systems efforts in the U.S. (e.g., age limits or requiring parental consent/accompaniment) have occurred at the state level. At the national level, the U.S. Food and Drug Administration and the Federal Trade Commission regulate indoor tanning devices and advertising, respectively.The current paper provides a brief review of (1) the evidence on indoor tanning as a risk factor for skin cancer; (2) factors that may influence use of indoor tanning devices at the population level; and (3) various environmental and systems options available for consideration when developing strategies to reduce indoor tanning. This information provides the context and background for the companion paper in this issue of the American Journal of Preventive Medicine, which summarizes highlights from an informal expert meeting convened by the CDC in August 2012 to identify opportunities to prevent skin cancer by reducing use of indoor tanning devices.</description><dc:title>Preventing Skin Cancer Through Reduction of Indoor Tanning: Current Evidence</dc:title><dc:creator>Meg Watson, Dawn M. Holman, Kathleen A. Fox, Gery P. Guy, Andrew B. Seidenberg, Blake P. Sampson, Craig Sinclair, DeAnn Lazovich</dc:creator><dc:identifier>10.1016/j.amepre.2013.02.015</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Theme: Strategies to Prevent Skin Cancer</prism:section><prism:startingPage>682</prism:startingPage><prism:endingPage>689</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001566/abstract?rss=yes"><title>The Role of Physicians in Promoting Healthier Built Environments</title><link>http://www.ajpmonline.org/article/PIIS0749379713001566/abstract?rss=yes</link><description>The normal physician treats the problem; the good physician treats the person; the best physician treats the community.—Chinese proverb   Most physicians work in clinical settings, providing one-to-one care to their patients. However, physicians long have recognized that involvement with community-level concerns can be necessary and appropriate to help address broad health-related issues. Some of the most important health advances, such as smoking restrictions, seat belt requirements, bicycle helmets, and environmental lead reduction, have grown out of collaboration between health and community sectors. Physician advocacy has been a key part of these strategies.</description><dc:title>The Role of Physicians in Promoting Healthier Built Environments</dc:title><dc:creator>Andrew L. Dannenberg, Philip Wu, Howard Frumkin</dc:creator><dc:identifier>10.1016/j.amepre.2013.01.025</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Current Issues</prism:section><prism:startingPage>e67</prism:startingPage><prism:endingPage>e69</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713002080/abstract?rss=yes"><title>Nutritional Quality of Menu Offerings at Eight Fast-Food Chains in the U.S. A Commentary</title><link>http://www.ajpmonline.org/article/PIIS0749379713002080/abstract?rss=yes</link><description>In this issue of the American Journal of Preventive Medicine, Hearst and colleagues use the U.S. Department of Agriculture (USDA)’s Healthy Eating Index to provide a much-needed assessment of the nutritional quality of fast food and evaluate how it has changed over 14 years. Their results show that the nutritional quality of fast food has improved little over the last decade, rising a mere three points out of a 100-point scale. This tiny increase is disappointing, and a bit surprising, given the many pronouncements by companies that they have added healthier menu options, switched to healthier cooking fats, are reducing sodium, and are touting other changes in company press releases and advertising.</description><dc:title>Nutritional Quality of Menu Offerings at Eight Fast-Food Chains in the U.S. A Commentary</dc:title><dc:creator>Margo G. Wootan</dc:creator><dc:identifier>10.1016/j.amepre.2013.03.003</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Editorials and Commentary</prism:section><prism:startingPage>690</prism:startingPage><prism:endingPage>691</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713001852/abstract?rss=yes"><title>What's Impeding Post-Traumatic Stress Disorder Prevention?</title><link>http://www.ajpmonline.org/article/PIIS0749379713001852/abstract?rss=yes</link><description>Post-traumatic stress disorder (PTSD) is a mental disorder caused by serious, often life-threatening traumatic events. Previously considered almost exclusively in the context of war-related traumatic stressors—which have rightfully been in the forefront of public and medical attention in recent years, owing to the experiences of U.S. troops in the Iraq and Afghanistan conflicts—trauma is, in fact, more commonly experienced outside of military situations. Millions of individuals every year are exposed to life-threatening and life-altering events that put them at risk for mental disorders such as PTSD. These events include motor vehicle collisions, intimate partner violence and other physical or sexual assault, childhood maltreatment, natural disasters, and a myriad of other more rare (e.g., gun massacres) but no less unfortunate events.</description><dc:title>What's Impeding Post-Traumatic Stress Disorder Prevention?</dc:title><dc:creator>Murray B. Stein, Ariel J. Lang</dc:creator><dc:identifier>10.1016/j.amepre.2013.03.002</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Editorials and Commentary</prism:section><prism:startingPage>692</prism:startingPage><prism:endingPage>693</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713002092/abstract?rss=yes"><title>Corrections</title><link>http://www.ajpmonline.org/article/PIIS0749379713002092/abstract?rss=yes</link><description>Wilcox S, Parrott A, Baruth M, et al. The Faith, Activity, and Nutrition Program: A Randomized Controlled Trial in African-American Churches. Am J Prev Med 2013;44(2):122–31.   In , the gender categories were reversed. The corrected table is below.</description><dc:title>Corrections</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/j.amepre.2013.03.004</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Departments</prism:section><prism:startingPage>694</prism:startingPage><prism:endingPage>695</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713002626/abstract?rss=yes"><title>Author Index</title><link>http://www.ajpmonline.org/article/PIIS0749379713002626/abstract?rss=yes</link><description></description><dc:title>Author Index</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S0749-3797(13)00262-6</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Departments</prism:section><prism:startingPage>696</prism:startingPage><prism:endingPage>699</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS074937971300247X/abstract?rss=yes"><title>Masthead</title><link>http://www.ajpmonline.org/article/PIIS074937971300247X/abstract?rss=yes</link><description></description><dc:title>Masthead</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S0749-3797(13)00247-X</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A1</prism:startingPage><prism:endingPage>A2</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713002481/abstract?rss=yes"><title>CME page for AMEPRE_3774</title><link>http://www.ajpmonline.org/article/PIIS0749379713002481/abstract?rss=yes</link><description></description><dc:title>CME page for AMEPRE_3774</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S0749-3797(13)00248-1</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A3</prism:startingPage><prism:endingPage>A3</prism:endingPage></item><item rdf:about="http://www.ajpmonline.org/article/PIIS0749379713002493/abstract?rss=yes"><title>CME page for AMEPRE_3776</title><link>http://www.ajpmonline.org/article/PIIS0749379713002493/abstract?rss=yes</link><description></description><dc:title>CME page for AMEPRE_3776</dc:title><dc:creator></dc:creator><dc:identifier>10.1016/S0749-3797(13)00249-3</dc:identifier><dc:source>American Journal of Preventive Medicine 44, 6 (2013)</dc:source><dc:date>2013-06-01</dc:date><prism:publicationName>American Journal of Preventive Medicine</prism:publicationName><prism:publicationDate>2013-06-01</prism:publicationDate><prism:volume>44</prism:volume><prism:number>6</prism:number><prism:issueIdentifier>S0749-3797(13)X0005-4</prism:issueIdentifier><prism:section>Frontmatter</prism:section><prism:startingPage>A4</prism:startingPage><prism:endingPage>A4</prism:endingPage></item></rdf:RDF>