Let’s Get Physical: Sexual Orientation Disparities in Physical Activity,Sports Involvement,and Obesity Among a Population-Based Sample of Adolescents

Objectives. We examined sexual orientation disparities in physical activity, sports involvement, and obesity among a population-based adolescent sample.Methods. We analyzed data from the 2012 Dane County Youth Assessment for 13 933 students in grades 9 through 12 in 22 Wisconsin high schools. We conducted logistic regressions to examine sexual orientation disparities in physical activity, sports involvement, and body mass index among male and female adolescents.Results. When we accounted for several covariates, compared with heterosexual females, sexual minority females were less likely to participate in team sports (adjusted odds ratio [AOR] = 0.44; 95% confidence interval [CI] = 0.37, 0.53) and more likely to be overweight (AOR = 1.28; 95% CI = 1.02, 1.62) or obese (AOR = 1.88; 95% CI = 1.43, 2.48). Sexual minority males were less likely than heterosexual males to be physically active (AOR = 0.62; 95% CI = 0.46, 0.83) or to participate in team sports (AOR = 0.26; 95% CI = 0.20, 0.32), but the 2 groups did not differ in their risk of obesity.Conclusions. Sexual orientation health disparities in physical activity and obesity are evident during adolescence. Culturally affirming research, interventions, and policies are needed for sexual minority youths.Obesity is an increasing and serious health problem among adolescents.1,2 This is of major concern because obesity has many health and social consequences and it affects adolescents’ overall well-being.3,4 Obesity among adolescents also has a high likelihood of continuing into adulthood.5 Recent population-based and longitudinal research has demonstrated that there are disparities in obesity between sexual minority and heterosexual adolescents.6–8 Research has also documented sexual orientation disparities in physical activity and sports involvement in adolescence.9,10 Despite this increased attention, the overall empirical base remains limited, and findings also suggest some gender nuances that need further exploration. More population-based research is needed to investigate these disparities, consistent with federal health priorities.7,11There are sexual orientation–based disparities in physical activity and sports involvement among adolescents; however, there are mixed findings for females. One study reported that sexual minority females are less likely than heterosexual females to participate in moderate to vigorous physical activity and team sports,9 whereas another study found no such differences in physical activity.10 Findings are more consistent for sexual minority male adolescents, who are less likely than heterosexual males to engage in moderate to vigorous physical activity, to engage in recommended levels of physical activity, and to participate in team sports.9,10 More research is needed because of the paucity of studies and mixed results. This is especially important given that adolescents’ physical activity has been shown to relieve stress and protect against many mental and physical health conditions, including obesity,12,13 for which sexual minority adolescents are at greater risk.Research on sexual orientation disparities in obesity suggests that there are some gender nuances. Many studies have found that sexual minority female adolescents have higher risk of obesity than heterosexual females (e.g., higher body mass index [BMI], defined as weight in kilograms divided by the square of height in meters).6,8,10,14 These sexual orientation disparities in obesity among adolescent females parallel those among sexual minority adult women.15,16Findings of elevated obesity risk among sexual minority male adolescents are mixed. Some studies show that sexual minority males, specifically bisexual males, have higher odds of obesity than heterosexuals,14 whereas other studies have documented no differences.10 By contrast, some studies have found that heterosexual males have increases in BMI during adolescence compared with sexual minority males.6,8 These mixed findings for sexual minority males might be attributed to physical maturation and developmental changes in adolescence that some of the cross-sectional studies could not examine.10,14 Specifically, one study found that sexual minority males had higher obesity risk than heterosexual males in early adolescence, but their risk of obesity became lower than for heterosexual males later in adolescence.6 The authors postulated that, compared with heterosexual males, sexual minority males reach puberty maturation earlier in adolescence but make less substantial weight gains later in adolescence.6Sexual orientation health disparities have been explained through the minority stress model: sexual minority youths experience unique stressors and stigma related to their sexual identity (e.g., homophobic bullying), which lead to poorer health.17 Sexual minority adolescents might therefore be less likely to be physically active or involved in team sports because of potential minority stressors that they often experience at school, especially bias and heightened discrimination experienced in the context of sports or in their communities.18–20 More recently, the negative effects of minority stress and stigma on physical health disparities have been documented,21,22 including their effects on obesity for sexual minority women.23 However, the minority stress model is not sufficient in explaining how sexual minority adolescent females, but not males, are at greater risk for obesity compared with their heterosexual peers.Another potential explanation of these obesity disparities is related to cultural norms and sexual minority females’ experiences of internalizing ideals for femininity and appearance8 and sexual minority males’ ideals for muscularity and body image.24 For instance, compared with heterosexual women, sexual minority women are more likely to be satisfied with their bodies and attracted to women with greater body mass,25,26 whereas sexual minority men are less likely to be satisfied with their bodies compared with heterosexual men and are more likely to be attracted to muscular men.25,27 Therefore, these 2 groups might engage (or not engage) in differing body weight management and dieting behaviors compared with their heterosexual peers; concomitantly, these behaviors might render differing risks for obesity.Sexual minority adolescents’ lack of physical activity and sports involvement might be influenced by traditional gender norms associated with athleticism and sports, which has implications for their athletic self-esteem and involvement. For adolescent males, team sports are a means to define masculinity28; however, adolescent males often engage in homophobic banter to prove their masculinity and heterosexuality and to enforce traditional gender norms.29,30 Sexual prejudice is pervasive in athletic settings,19,20 making sports contexts unwelcoming and unsafe for many sexual minority males. Traditional feminine gender norms and homophobia also affect sexual minority females’ involvement in sports.31 However, sexual minority adolescent females have unique gendered experiences in relation to sports. Because women’s athleticism can be a stereotype for being a lesbian,32 sexual minority females might avoid sports involvement. Expecting or experiencing exclusion in sports settings might also affect sexual minority adolescents’ athletic self-esteem, consequently preventing them from engaging in future sports or physical activity.9 In fact, athletic self-esteem has been found to contribute to sexual orientation disparities in sports involvement and physical activity.9Emerging evidence of sexual orientation disparities in physical activity, sports involvement, and obesity among adolescents, in addition to potential gender nuances in these disparities, points to the need for more population-based research in this area. We therefore examined sexual orientation disparities among a large adolescent population-based sample and tested for gender differences. While accounting for variables commonly associated with physical activity and obesity among adolescents,4,33 we hypothesized that sexual minority adolescents would be less likely to report physical activity and sports involvement than would their heterosexual peers. We also hypothesized that sexual minority females would be at higher risk for being overweight and obese than their heterosexual peers. Because of mixed findings in existing sexual orientation disparities research among adolescent males, we hypothesized that sexual minority males would be at equal risk for being overweight and obese than their heterosexual male peers.     

Images of a Healthy Worksite: A Group-Randomized Trial for Worksite Weight Gain Prevention With Employee Participation in Intervention Design

Objectives. We assessed the effects of a worksite multiple-component intervention addressing diet and physical activity on employees’ mean body mass index (BMI) and the percentage of employees who were overweight or obese.Methods. This group-randomized trial (n = 3799) was conducted at 10 worksites in the northeastern United States. Worksites were paired and allocated into intervention and control conditions. Within- and between-groups changes in mean BMIs and in the percentage of overweight or obese employees were examined in a volunteer sample.Results. Within-group mean BMIs decreased by 0.54 kilograms per meter squared (P = .02) and 0.12 kilograms per meter squared (P = .73) at the intervention and control worksites, respectively, resulting in a difference in differences (DID) decrease of 0.42 kilograms per meter squared (P = .33). The within-group percentage of overweight or obese employees decreased by 3.7% (P = .07) at the intervention worksites and increased by 4.9% (P = .1) at the control worksites, resulting in a DID decline of 8.6% (P = .02).Conclusions. Our findings support a worksite population strategy that might eventually reduce the prevalence of overweight and obesity by minimizing environmental exposures to calorically dense foods and increasing exposures to opportunities for energy expenditure within worksite settings.Sixty-eight percent of adults residing in the United States are overweight or obese,1 and these conditions affect more than 1.4 billion adults worldwide.2 Traditional obesity control strategies, which have focused on changing diet and physical activity (PA) behaviors, provide significant individual benefits3 but are considered insufficient to reduce population disease burdens,4,5 for which broad, population-based approaches are needed.6 In addition to individual biology and behaviors, the physical, social, and cultural environment appears to contribute to the upward trend in population estimates of overweight and obesity7,8 by facilitating high-energy, low-nutrient diets and reducing the need to be physically active to perform activities of daily life.9Worksites are feasible self-contained environments with established communication systems in which interventions manipulating the food and PA environment and the social marketing of lifestyle changes can be implemented. Given that 58.4% of the US population aged 16 years or older is employed,10 worksite interventions have the potential to reach large number of adults11 and can foster the participation of employees in project development and sustainability.12–14 Moreover, participatory worksite interventions address workers’ needs, priorities, and interests and allow strategies to be adapted to the realities of individual sites.13 There is also a business case for weight control programs. In comparison with their nonobese counterparts, overweight and obese employees have higher absenteeism rates, have more work limitations, and are less productive.15–18With these issues in mind, the National Heart, Lung, and Blood Institute developed the Obesity Prevention in the Worksite initiative, a population-based approach to promoting behavioral change through environmental interventions that address prevention and control of weight gain.19 Prior to this initiative, worksite trials were either limited scope interventions, targeting a few aspects of the food or PA environment,9,20–23 or broader scope efforts simultaneously targeting risk factors for cardiovascular disease and cancer (e.g., smoking, diet).24–28 In addition, few studies addressed environmental influences related to excessive weight gain.Here we report the results of Images of a Healthy Worksite, one of the studies that is part of the Obesity Prevention in the Worksite initiative; this comprehensive nutrition and PA intervention was designed to promote healthy lifestyles and to stop the shift to the right of the population body mass index (BMI) curve. In this study, worksites were designated to receive an environmental intervention, and employees participated in intervention design. We hypothesized that mean BMIs among employees at the intervention worksites and the percentages of employees who were overweight or obese would not increase over a 2-year period or would increase less than at control worksites.     

The Effect of a “Maintain,Don’t Gain” Approach to Weight Management on Depression Among Black Women: Results From a Randomized Controlled Trial

Objectives. We evaluated the effect of a weight gain prevention intervention (Shape Program) on depression among socioeconomically disadvantaged overweight and obese Black women.Methods. Between 2009 and 2012, we conducted a randomized trial comparing a 12-month electronic health–based weight gain prevention intervention to usual primary care at 5 central North Carolina community health centers. We assessed depression with the Patient Health Questionnaire (PHQ-8). We analyzed change in depression score from baseline to 12- and 18-month follow-up across groups with mixed models. We used generalized estimating equation models to analyze group differences in the proportion above the clinical threshold for depression (PHQ-8 score ≥ 10).Results. At baseline, 20% of participants reported depression. Twelve-month change in depression scores was larger for intervention participants (mean difference = −1.85; 95% confidence interval = −3.08, −0.61; P = .004). There was a significant reduction in the proportion of intervention participants with depression at 12 months with no change in the usual-care group (11% vs 19%; P = .035). All effects persisted after we controlled for weight change and medication use. We saw similar findings at 18 months.Conclusions. The Shape Program, which includes no mention of mood, improved depression among socioeconomically disadvantaged Black women.Depression is one of the most common and disabling, yet treatable, mental health conditions in the United States.1,2 Women are twice as likely as men to be affected,3 and more than 1 in 7 (14.9%) Black women will experience major depression in their lifetime.4 Observational evidence suggests that, although the prevalence of major depression is lower among Blacks than Whites, its severity is greater for Blacks.5 This is likely a result of racial disparities in access to depression treatment.6 Indeed, compared with their White counterparts, Black adults with depression are less likely to receive treatment for depression (39.7% vs 54.0%).6 Of those who do seek treatment, Blacks are less likely than Whites to receive care that corresponds to clinical practice guidelines.6,7 These racial disparities are magnified by socioeconomic disadvantage.8 Depression is 3 times more common for those with incomes below the federal poverty level, compared with those with higher incomes.9 As a consequence, the challenge remains how to effectively treat socioeconomically disadvantaged Black women with depression.Obesity is also disproportionately prevalent among Black women relative to other racial/ethnic groups.10 The high burden of obesity among Black women not only indicates a higher prevalence of obesity-related chronic diseases (e.g., diabetes, heart disease),11 but it may also have an impact on psychosocial outcomes such as depression.12 As such, interventions focusing on behavioral weight control may present a useful opportunity to address both obesity and depression.Behavioral weight loss interventions typically include frequent contact with a weight loss counselor; self-monitoring of diet, exercise, and weight; and lessons that cover various topics such as problem solving, relapse prevention, and stress management. Indeed, across numerous studies, behavioral weight loss interventions have been shown to promote reductions in depression.13,14 Such findings are generally believed to be related to weight loss15 and mediated by improvements in body satisfaction; that is, for many, weight loss might enhance body satisfaction and, thus, improve depression outcomes.16,17 However, this finding has most frequently been demonstrated in predominantly socioeconomically advantaged White women, who tend to exhibit strong relations between body size and mood.16,18 In contrast, Black women have greater social acceptance of overweight, less body weight dissatisfaction, and higher body weight ideals compared with White women.19–22 Thus, it is unclear whether Black women would experience a similar reduction in depression as a result of obesity treatment.Although weight loss is indicated for those with obesity, promoting clinically meaningful weight change among Black women has been a major challenge.23 Across various studies, Black women achieve less weight loss relative to White women.24–26 The reason for this racial disparity in weight loss outcomes is unclear, but may be influenced in part by differences in sociocultural norms related to weight, diet, and physical activity.27 As a result, interventions that focus on preventing weight gain may be a useful alternative treatment approach among overweight and obese Black women.27We recently conducted a study titled the Shape Program, a 12-month randomized controlled trial with follow-up at 18 months, evaluating an electronic health weight gain prevention intervention among Black women compared with usual care in the primary care setting.27 The Shape intervention was found to be effective in staving off weight gain at 12 and 18 months.28 It is unclear whether a weight gain prevention approach, as was tested in Shape, would be helpful for treating depression among Black women. As such, we sought to examine the potential spillover benefits produced by this “maintain, don’t gain” approach on depression, compared with usual care.     

Posttraumatic Stress Disorder and Incident Heart Failure Among a Community-Based Sample of US Veterans

Objectives. We investigated the association between posttraumatic stress disorder (PTSD) and incident heart failure in a community-based sample of veterans.Methods. We examined Veterans Affairs Pacific Islands Health Care System outpatient medical records for 8248 veterans between 2005 and 2012. We used multivariable Cox regression to estimate hazard ratios and 95% confidence intervals for the development of heart failure by PTSD status.Results. Over a mean follow-up of 7.2 years, veterans with PTSD were at increased risk for developing heart failure (hazard ratio [HR] = 1.47; 95% confidence interval [CI] = 1.13, 1.92) compared with veterans without PTSD after adjustment for age, gender, diabetes, hyperlipidemia, hypertension, body mass index, combat service, and military service period. Additional predictors for heart failure included age (HR = 1.05; 95% CI = 1.03, 1.07), diabetes (HR = 2.54; 95% CI = 2.02, 3.20), hypertension (HR = 1.87; 95% CI = 1.42, 2.46), overweight (HR = 1.72; 95% CI = 1.25, 2.36), obesity (HR = 3.43; 95% CI = 2.50, 4.70), and combat service (HR = 4.99; 95% CI = 1.29, 19.38).Conclusions. Ours is the first large-scale longitudinal study to report an association between PTSD and incident heart failure in an outpatient sample of US veterans. Prevention and treatment efforts for heart failure and its associated risk factors should be expanded among US veterans with PTSD.Posttraumatic stress disorder (PTSD) is a psychiatric illness that affects approximately 7.7 million Americans aged older than 18 years.1 PTSD typically results after the experience of severe trauma, and veterans are at elevated risk for the disorder. The National Vietnam Veterans Readjustment Study reported the prevalence of PTSD among veterans who served in Vietnam as 15.2% among men and 8.1% among women.2 In fiscal year 2009, nearly 446 045 Veterans Administration (VA) patients had a primary diagnosis of PTSD, a threefold increase since 1999.3 PTSD is of growing clinical concern as evidence continues to link psychiatric illnesses to conditions such as arthritis,4 liver disease,5 digestive disease,6 and cancer.6 When the postwar health status of Vietnam veterans was examined, those with PTSD had higher rates of diseases of the circulatory, nervous, digestive, musculoskeletal, and respiratory systems.7The evidence linking PTSD to coronary heart disease (CHD) is substantial.8–10 Veterans with PTSD are significantly more likely to have abnormal electrocardiograph results, myocardial infarctions, and atrioventricular conduction deficits than are veterans without PTSD.11 In a study of 605 male veterans of World War II and the Korean War, CHD was more common among veterans with PTSD than among those without PTSD.12 Worldwide, adults exposed to the disaster at Chernobyl experienced increased rates of CHD up to 10 years after the event,13 and studies of stressors resulting from the civil war in Lebanon found elevated CHD mortality.14,15Although the exact biological mechanism by which PTSD contributes to CHD remains unclear, several hypotheses have been suggested, including autonomic nervous system dysfunction,16 inflammation,17 hypercoagulability,18 cardiac hyperreactivity,19 altered neurochemistry,20 and co-occurring metabolic syndrome.16 One of the hallmark symptoms of PTSD is hyperarousal,21 and the neurobiological changes brought on from sustained sympathetic nervous system activation affect the release of neurotransmitters and endocrine function.22 These changes have negative effects on the cardiovascular system, including increased blood pressure, heart rate, and cardiac output.22,23Most extant literature to date examining cardiovascular sequelae has shown a positive association between PTSD and coronary artery disease.8–10 Coronary artery disease is well documented as one of the most significant risk factors for future development of heart failure.24 Despite burgeoning evidence for the role of PTSD in the development of coronary artery disease, there are few studies specifically exploring the relationship between PTSD and heart failure. Limited data suggest that PTSD imparts roughly a threefold increase in the odds of developing heart failure in both the general population5 and in a sample of the elderly.25 These investigations, however, have been limited by cross-sectional study design, a small proportion of participants with PTSD, and reliance on self-reported measures for both PTSD and heart failure.5,25 Heart failure is a uniquely large public health issue, as nearly 5 million patients in the United States are affected and there are approximately 500 000 new cases each year.26 Identifying predictors of heart failure can aid in early detection efforts while simultaneously increasing understanding of the mechanism behind development of heart failure.To mitigate the limitations of previous investigations, we undertook a large-scale prospective study to further elucidate the role of prevalent PTSD and development of incident heart failure among veterans, while controlling for service-related and clinical covariates. Many studies investigating heart failure have relied on inpatient records; we leveraged outpatient records to more accurately reflect the community burden of disease.     

Diet-Beverage Consumption and Caloric Intake Among US Adults,Overall and by Body Weight

Objectives. We examined national patterns in adult diet-beverage consumption and caloric intake by body-weight status.Methods. We analyzed 24-hour dietary recall with National Health and Nutrition Examination Survey 1999–2010 data (adults aged ≥ 20 years; n = 23 965).Results. Overall, 11% of healthy-weight, 19% of overweight, and 22% of obese adults drink diet beverages. Total caloric intake was higher among adults consuming sugar-sweetened beverages (SSBs) compared with diet beverages (2351 kcal/day vs 2203 kcal/day; P = .005). However, the difference was only significant for healthy-weight adults (2302 kcal/day vs 2095 kcal/day; P < .001). Among overweight and obese adults, calories from solid-food consumption were higher among adults consuming diet beverages compared with SSBs (overweight: 1965 kcal/day vs 1874 kcal/day; P = .03; obese: 2058 kcal/day vs 1897 kcal/day; P < .001). The net increase in daily solid-food consumption associated with diet-beverage consumption was 88 kilocalories for overweight and 194 kilocalories for obese adults.Conclusions. Overweight and obese adults drink more diet beverages than healthy-weight adults and consume significantly more solid-food calories and a comparable total calories than overweight and obese adults who drink SSBs. Heavier US adults who drink diet beverages will need to reduce solid-food calorie consumption to lose weight.The trends and patterns of sugar-sweetened beverage (SSB) consumption have been well described in the literature,1,2 but less is known about consumption of diet beverages (artificially sweetened no-calorie drinks) among US adults. Available evidence focuses on broad temporal trends or changes among demographic groups suggesting that consumption of diet beverages has increased dramatically from about 3% of adults in 19653 to about 20% of adults today,4 and that diet-beverage drinkers are typically characterized as young to middle-age adults (aged 20–59 years), female, non-Hispanic White, and higher income.4To our knowledge, no studies to date have focused on national patterns in diet-beverage consumption and caloric intake by body-weight status. Understanding diet-beverage consumption by body weight is important as consuming these zero- or no-calorie drinks is a common weight-management strategy. Switching from SSBs to diet drinks has indeed been shown to be associated with weight loss because of differences in caloric content between the drinks.5 However, the evidence base is far from conclusive. Some studies, mostly cross-sectional in design, have shown that diet-beverage drinkers tend to be overweight,5,6 that they typically do not consume fewer calories on the days they consume diet beverages,7 and that high consumers (households purchasing more than 20 12-packs of diet soda annually) generally purchase more snack foods at the grocery store and more overall calories than consumers purchasing SSBs.8 The evidence from long-term studies is similarly mixed; some show the reduction in caloric intake promotes weight loss or maintenance, others show no effect, and some show weight gain.9 Evidence also suggests that diet drinkers have the same caloric intake and body mass index (BMI; defined as weight in kilograms divided by the square of height in meters) as SSB drinkers10,11 and that consumption of diet drinks can be associated with significant weight gain.12The primary purpose of this study was to describe patterns in diet-beverage consumption and caloric intake (total, beverage, and solid-food calories) among US adults overall and among body-weight categories. In addition, we examined variations in dietary habits (i.e., snacking and calories per meal occasion) among adults consuming diet beverages. This analysis does not attempt to estimate the impact of diet-beverage intake on obesity incidence because of our reliance on cross-sectional data.     

Social Branding to Decrease Smoking Among Young Adults in Bars

Objectives. We evaluated a Social Branding antitobacco intervention for “hipster” young adults that was implemented between 2008 and 2011 in San Diego, California.Methods. We conducted repeated cross-sectional surveys of random samples of young adults going to bars at baseline and over a 3-year follow-up. We used multinomial logistic regression to evaluate changes in daily smoking, nondaily smoking, and binge drinking, controlling for demographic characteristics, alcohol use, advertising receptivity, trend sensitivity, and tobacco-related attitudes.Results. During the intervention, current (past 30 day) smoking decreased from 57% (baseline) to 48% (at follow-up 3; P = .002), and daily smoking decreased from 22% to 15% (P < .001). There were significant interactions between hipster affiliation and alcohol use on smoking. Among hipster binge drinkers, the odds of daily smoking (odds ratio [OR] = 0.44; 95% confidence interval [CI] = 0.30, 0.63) and nondaily smoking (OR = 0.57; 95% CI = 0.42, 0.77) decreased significantly at follow-up 3. Binge drinking also decreased significantly at follow-up 3 (OR = 0.64; 95% CI = 0.53, 0.78).Conclusions. Social Branding campaigns are a promising strategy to decrease smoking in young adult bar patrons.Tobacco companies1 and public health authorities2–5 recognize young adulthood as a critical time when experimenters either quit or transition to regular tobacco use. Young adults are also aspirational role models for youths.1,6,7 Tobacco companies devote considerable resources to reaching young adults to encourage tobacco use,1,8–11 and young adults have a high prevalence of smoking.12 In California in 2011, young adults had the highest smoking prevalence of any age group, and the Department of Health estimated that 32% of California smokers started smoking between the ages of 18 and 26 years.13 Although they are more likely to intend to quit and successfully quit than older adults,14–17 young adults are less likely to receive assistance with smoking cessation.18,19 Although there are few proven interventions to discourage young adult smoking,20 cessation before age 30 years avoids virtually all of the long-term adverse health effects of smoking.21Tobacco companies have a long history of using bars and nightclubs to reach young adults and to encourage smoking.1,6,9–11,22–24 Bar attendance and exposure to tobacco bar marketing is strongly associated with smoking.25 The 1998 Master Settlement Agreement and Food and Drug Administration regulations that limit tobacco advertising to youths, explicitly permit tobacco marketing in “adult only” venues, including bars and nightclubs.26,27Aggressive tobacco marketing may actually be more intensive in smoke-free bars: a 2010 study of college students attending bars found that students in the community with a smoke-free bar law were more likely to be approached by tobacco marketers, offered free gifts, and to take free gifts for themselves than in communities without a smoke-free bar law.28 Bars and nightclubs also attract young adults who are more likely to exhibit personality traits such as sensation seeking,29 increasing their risk30 independently of receptivity to tobacco advertising; tobacco promotional messages resonate with these personality traits.8,31 Tobacco marketing campaigns are tailored to specific segments of the population defined by psychographics (e.g., values, attitudes, shared interests, such as tastes in music and fashion, and friend groups) and demographic criteria, and they aim to create positive smoker images, identities, and social norms for smoking.1,8 Tobacco marketing campaigns also focus on young adult trendsetters to leverage peer influence to promote smoking.6,10In contrast to the tobacco companies’ efforts, most young adult health interventions take place in colleges or health centers rather than social environments.32–39 Bars and nightclub venues represent an opportunity to reach those at highest risk for long-term smoking morbidity and mortality.40 We evaluated the effectiveness of an intervention to decrease cigarette smoking by countering tobacco industry marketing strategies targeting young adults attending bars and nightclubs in the San Diego, California, “hipster” scene. Because tobacco and alcohol use are strongly linked,41,42 we also examined the effects of the intervention on alcohol use and among binge drinkers. We found a significant decrease in smoking in the community where the intervention took place, including significant decreases among nondaily smokers and binge drinkers, as well as a significant decrease in binge drinking.     

Loose Cigarette Purchasing and Nondaily Smoking Among Young Adult Bar Patrons in New York City

Objectives. We examined loose cigarette (loosie) purchasing behavior among young adult (aged 18–26 years) smokers at bars in New York City and factors associated with purchase and use.Methods. Between June and December 2013, we conducted cross-sectional surveys (n = 1916) in randomly selected bars and nightclubs. Using multivariable logistic regression models, we examined associations of loose cigarette purchasing and use with smoking frequency, price, social norms, cessation behaviors, and demographics.Results. Forty-five percent (n = 621) of nondaily smokers and 57% (n = 133) of daily smokers had ever purchased a loosie; 15% of nondaily smokers and 4% of daily smokers reported that their last cigarette was a loosie. Nondaily smokers who never smoked daily were more likely than were daily smokers to have last smoked a loosie (odds ratio = 7.27; 95% confidence interval = 2.35, 22.48). Quitting behaviors and perceived approval of smoking were associated with ever purchasing and recently smoking loosies.Conclusions. Loosie purchase and use is common among young adults, especially nondaily smokers. Smoking patterns and attitudes should be considered to reduce loose cigarette purchasing among young adults in New York City.Widespread adoption of clean indoor air laws and cigarette tax increases denormalize smoking behavior1 and decrease smoking rates.2,3 Although increasing taxes is one of the most effective means of smoking prevention and reduction,3 the increased price of cigarettes can also lead to tax-avoidant behaviors, such as buying untaxed packs smuggled from states with lower cigarette taxes and purchasing loose cigarettes, or “loosies.”4–6 In New York City (NYC), where a cigarette pack costs about $11.50, it has become common for smokers to purchase discounted packs and individual cigarettes from street peddlers and friends.7,8Much of the research exploring loosie purchasing in the United States has focused on underage or low-income minority populations, often in urban areas.7,9,10 One study found that in early 1993, 70% of stores in central Harlem sold loosies to minors.7 Another study conducted with a 2005–2006 convenience sample in inner-city Baltimore found that 77% of African American smokers aged 18 to 24 years had purchased loosies in the past month.11 Similarly, loosie purchasing in Mexico was more common among younger smokers with lower incomes.12Availability and visibility of loosies can promote smoking and encourage relapse.13 We defined nondaily smokers as those who smoked on 1 to 29 of the past 30 days.14,15 Shiffman et al. found that nondaily smokers were more likely than daily smokers to report that social and environmental stimuli motivated their smoking behavior.16 More specifically, cues such as taste, smell, social goading to smoke, and specific situations (e.g., smoking after meals) are more likely to be reported as motivators to smoke by nondaily smokers than by daily smokers.16 Because social–environmental cues have substantial impact on nondaily smokers’ motivation to smoke, it is likely that the cue of seeing loosies in one’s environment also motivates nondaily smokers to smoke.16Previous research substantiates this claim, with 1 study showing that people who regularly saw loosies available for purchase were more likely to be current smokers.17 Therefore, the widespread availability of loosies may have a greater impact on nondaily smokers. Nondaily smokers make up a third of US smokers,18,19 and nondaily smoking is increasingly common among young adults.20 Many young adults who smoke on only some days do not self-identify as smokers,21 and nondaily smoking is frequently paired with alcohol consumption.22–24 Nondaily and light smoking carry a lower, but substantial, risk for lung cancer and a similar risk as does daily smoking for cardiovascular disease.25–27 Occasional smokers also have higher smoking-related morbidity and mortality than do people who have never smoked.26,28–30Nondaily smoking can be a long-term behavior pattern31,32 or a transition to or from daily smoking.31 Nondaily smokers include different subgroups that may have very different smoking patterns or motivations to quit.33,34 Nondaily smokers who previously smoked daily have been defined in previous research as converted nondaily smokers. Nondaily smokers who have never smoked daily are defined as native nondaily smokers.18,19 Important differences exist between these subgroups of smokers: converted nondaily smokers are more likely to quit smoking than are native nondaily smokers and daily smokers,18,19 although most converted and native nondaily smokers were unable to remain abstinent for more than 90 days.19Loosie purchasing and use may play an important role in promoting continued tobacco use among nondaily smokers. The 2010 NYC Community Health Survey35 found that more than one third (34%) of young adult nondaily smokers (aged 18–26 years) reported that their last cigarette smoked was a loosie, compared with 14% of young adult daily smokers. Another study of NYC adults demonstrated that nondaily smokers were more likely to purchase loose cigarettes than were light and heavy smokers.36 To the best of our knowledge, little is known about the factors associated with loosie purchasing among nondaily smokers in the United States.We sought to better understand the factors associated with loosie purchasing among NYC young adults, specifically to determine (1) loosie purchase and use rates among converted nondaily, native nondaily, and daily smokers; (2) whether loosie purchase or use are associated with perceived social norms of smoking behavior; and (3) whether loosie purchasing is associated with smoking cessation intention or behavior.     

Clustering of Midlife Lifestyle Behaviors and Subsequent Cognitive Function: A Longitudinal Study

Objectives. We examined the association between individual and clustered lifestyle behaviors in middle age and later in cognitive functioning.Methods. Middle-aged participants (n = 2430) in the Supplémentation en Vitamines et Minéraux Antioxydant study self-reported their low physical activity, sedentary behavior, alcohol use, smoking, low fruit and vegetable consumption, and low fish consumption. We assessed cognition 13 years later via 6 neuropsychological tests. After standardization, we summed the scores for a composite cognitive measure. We estimated executive functioning and verbal memory scores using principal component analysis. We estimated the mean differences (95% confidence intervals [CIs]) in cognitive performance by the number of unhealthy behaviors using analysis of covariance. We identified latent unhealthy behavior factor via structural equation modeling.Results. Global cognitive function and verbal memory were linearly, negatively associated with the number of unhealthy behaviors: adjusted mean differences = −0.36 (95% CI = −0.69, −0.03) and −0.46 (95% CI = −0.80, −0.11), respectively, per unit increase in the number of unhealthy behaviors. The latent unhealthy behavior factor with low fruit and vegetable consumption and low physical activity as main contributors was associated with reduced verbal memory (RMSEA = 0.02; CFI = 0.96; P = .004). No association was found with executive functioning.Conclusions. Comprehensive public health strategies promoting healthy lifestyles might help deter cognitive aging.Noncommunicable diseases with notable lifestyle components are the leading causes of death worldwide.1,2 There is also growing evidence of the critical role of different midlife health and risk behaviors in cognitive aging.3–7 Because lifestyles are inherently modifiable and no treatment of cognitive decline is available, such findings argue for the paramount importance of prevention.8,9Current data support a deleterious effect of alcohol abstinence or abuse (compared with moderate alcohol consumption),10 smoking,7 low fruit and vegetable intake,11 low fish intake,12 and low physical activity (PA) levels13 on cognitive aging. However, it has been widely documented that lifestyle factors are strongly correlated with each other, forming a cluster of healthy or unhealthy behaviors.14 Traditionally, such interrelations have been accounted for by statistical adjustment; however, it is of major public health interest to consider the cumulative and combined effect of the various lifestyle behaviors on health by using multidimensional strategies.14Research that examines the combined effect of lifestyle factors on mortality is plentiful, and data have been colligated in a recent meta-analysis.15 These authors reported a 66% reduction in mortality risk by comparing adherence to 4 or more healthy lifestyle behaviors versus engagement in any number of unhealthy behaviors.The combined effect of lifestyle factors has also been explored in relation to cardiovascular diseases,16–18 cancer,18–22 diabetes,18,23 memory complaints,24 and dementia25–27; however, very few studies have reported findings regarding cognition.28,29 Despite heterogeneity in the definition of a healthy lifestyle, study design, and residual confounding, available, but scarce, data support a critical, protective role of healthy lifestyles in cognitive health through their beneficial properties via oxidative, inflammatory, vascular, and other neuroprotective pathways.30–33Our objectives in this study were to examine the association between individual and clustered lifestyle behaviors and later cognitive functioning. We employed traditional and innovative techniques (structural equation modeling) in our epidemiological pursuit.     

Body Mass Index Categories and Mortality Risk in US Adults: The Effect of Overweight and Obesity on Advancing Death

Objectives. We examined the association of body mass index with all-cause and cardiovascular disease (CVD)–specific mortality risks among US adults and calculated the rate advancement period by which death is advanced among the exposed groups.Methods. We used data from the Third National Health and Nutrition Examination Survey (1988–1994) linked to the National Death Index mortality file with follow-up to 2006 (n = 16 868). We used Cox proportional hazards regression to estimate the rate of dying and rate advancement period for all-cause and CVD-specific mortality for overweight and obese adults relative to their normal-weight counterparts.Results. Compared with normal-weight adults, obese adults had at least 20% significantly higher rate of dying of all-cause or CVD. These rates advanced death by 3.7 years (grades II and III obesity) for all-cause mortality and between 1.6 (grade I obesity) and 5.0 years (grade III obesity) for CVD-specific mortality. The burden of obesity was greatest among adults aged 45 to 64 years for all-cause and CVD-specific mortality and among women for all-cause mortality.Conclusions. These findings highlight the impact of the obesity epidemic on mortality risk and premature deaths among US adults.Obesity has been increasing in the US population over the past 5 decades, and so has its impact on morbidity1–3 and mortality.4–9 For instance, obesity has been associated with all-cause mortality in the United States and elsewhere.10–13 In fact, evidence from a recent review of 97 articles (including 37 in the United States) suggests that obesity (body mass index [BMI; defined as weight in kilograms divided by the square of height in meters] ≥ 30.0) is associated with higher all-cause mortality risk.14 When obesity was further classified into grades I (BMI 30.0 to < 35), II (BMI 35.0 to < 40.0), and III (BMI ≥ 40.0), the high risk of mortality was observed for grades II and III only. By contrast, overweight was associated with a protective effect against all-cause mortality.14 Moreover, studies examining obesity and CVD-specific mortality have also found a significant increase in mortality risk among US obese adults.9,15,16Among studies examining the association between obesity and mortality in the United States, few have focused on a nationally representative sample such as the National Health and Nutrition Examination Survey (NHANES) with objective measures of weight and height,8,9,17 and none has examined the effect of overweight and obesity on advancing the risk of death among adults. Thus, we used data from the NHANES III for the years 1988 through 1994 linked to the National Death Index (NDI) mortality file with follow-up to year 2006 to examine the association of BMI categories with all-cause and CVD-specific mortality risk among US adults aged 18 years and older. We also calculated the rate advancement period (RAP)18 or the average time by which the rate of death is advanced among overweight and obese adults compared with their normal-weight counterparts. In addition, we examined whether these associations and RAPs differed by age, gender, and race/ethnicity.     

Longitudinal Associations Between Poverty and Obesity From Birth Through Adolescence

Objectives. We examined the relationship between timing of poverty and risk of first-incidence obesity from ages 3 to 15.5 years.Methods. We used the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (1991–2007) to study 1150 children with repeated measures of income, weight, and height from birth to 15.5 years in 10 US cities. Our dependent variable was the first incidence of obesity (body mass index ≥ 95th percentile). We measured poverty (income-to-needs ratio < 2) prior to age 2 years and a lagged, time-varying measure of poverty between ages 2 and 12 years. We estimated discrete-time hazard models of the relative risk of first transition to obesity.Results. Poverty prior to age 2 years was associated with risk of obesity by age 15.5 years in fully adjusted models. These associations did not vary by gender.Conclusions. Our findings suggest that there are enduring associations between early life poverty and adolescent obesity. This stage in the life course may serve as a critical period for both poverty and obesity prevention.There are significant socioeconomic disparities in rates of childhood and adolescent obesity, defined as a body mass index (BMI) at or above the 95th percentile, adjusted for age and gender.1–3 Children of low socioeconomic status (SES) are 1.6 times more likely to be obese than high-SES children4 and have steeper rates of increase in obesity.5,6 Despite evidence that the prevalence of obesity has recently stabilized among children overall, it continues to increase among low-SES children.2,5 The positive relationship between low SES and obesity is especially worrisome because of relatively high rates of childhood poverty that have only increased in the recent economic downturn.7 One in 5 US children (16.4 million) now live in families with incomes below the federal poverty level.8To better understand the relationship between poverty and obesity, longitudinal studies of childhood poverty and its associations with obesity throughout childhood are needed. To develop effective policies preventing the incidence of child obesity, studies must also determine critical periods in childhood during which poverty may exert greater influence on the incidence of obesity.9,10 Most studies demonstrating a link between SES and obesity, however, have used a cross-sectional study design.1,5,6,11–16 Fewer studies address the issue of timing of childhood poverty (or other SES measures) and obesity incidence (or changes in BMI) later in life.17–20 Moreover, these few studies omit key information on weight history17,19 and SES prior to middle childhood (younger than 7 years)18,19 or are based on non-US populations,21 which precludes the study of early life associations between poverty and obesity, and limits generalizability to the United States.We used a comprehensive, community-based data set of US children followed from birth to about 15 years of age and for whom multiple measures of children’s SES, height, and weight were collected. Our objective was to examine critical periods in the relationship between poverty and the risk of the first incidence of obesity across the early life course.     

Life-Course Accumulation of Neighborhood Disadvantage and Allostatic Load: Empirical Integration of Three Social Determinants of Health Frameworks

Objectives. We examined if the accumulation of neighborhood disadvantages from adolescence to mid-adulthood were related to allostatic load, a measure of cumulative biological risk, in mid-adulthood, and explored whether this association was similar in women and men.Methods. Data were from the participants in the Northern Swedish Cohort (analytical n = 818) at ages 16, 21, 30, and 43 years in 1981, 1986, 1995, and 2008. Personal living conditions were self-reported at each wave. At age 43 years, 12 biological markers were measured to operationalize allostatic load. Registered data for all residents in the cohort participants’ neighborhoods at each wave were used to construct a cumulative measure of neighborhood disadvantage. Associations were examined in ordinary least-squares regression models.Results. We found that cumulative neighborhood disadvantage between ages 16 and 43 years was related to higher allostatic load at age 43 years after adjusting for personal living conditions in the total sample (B = 0.11; P = .004) and in men (B = 0.16; P = .004), but not in women (B = 0.07; P = .248).Conclusions. Our findings suggested that neighborhood disadvantage acted cumulatively over the life course on biological wear and tear, and exemplified the gains of integrating social determinants of health frameworks.Different frameworks relevant to social determinants of health have been introduced, developed, and applied to research during the last 2 decades. We specifically aimed to empirically integrate the allostatic load,1 neighborhoods and health,2 and life-course epidemiology3 frameworks by examining whether the life-course accumulation of neighborhood disadvantage was related to allostatic load in mid-adulthood.The allostatic load model4,5 was developed within the stress physiology field and was introduced as a general framework for the cumulative “wear and tear” the body eventually experiences across multiple interrelated physiological systems because of repeated stressor exposures during the life course. Allostatic load (or cumulative biological risk) has been proposed as a biological link that explains socioeconomic disparities in morbidity and mortality6,7; empirical studies have demonstrated that allostatic load is patterned by social determinants (e.g., ethnicity, education, and income)8–11 and prospectively predicts mortality as well as cognitive and physical decline.12–14Studying the importance of the area of residence—defined, for example, by parishes, wards, or neighborhoods—for health represents a more contextual perspective on social determinants of health. For example, socioeconomic status aggregated at the neighborhood level is related to cardiovascular health beyond individual-level socioeconomic conditions.2,15 Such effects have been attributed to several possible pathways, including (1) indirect-cognitive paths, where the effects are mediated by conscious responses such as health-damaging behaviors, and (2) direct-contextual paths, which include differential chronic stressor exposure and the potential development of allostatic load.16 Cross-sectional studies in recent years have demonstrated that various neighborhood characteristics, such as socioeconomic disadvantages,17 poverty,11 lack of affluence,18 and perceived neighborhood conditions,19 are related to allostatic load. However, most studies within the field use cross-sectional or short-term prospective designs20,21; conceptual and empirical elaborations of how social context affects health in the long term are lacking.21However, such a long-term temporal perspective emphasizes life-course epidemiology, which focuses on how and when exposures over the life course affect adult health outcomes, a question that is guided by conceptual life-course models.3 The cumulative risk model, which posits that the most important aspect for health effects is the accumulation of exposures across the life course, is the model with the most consistent empirical support (e.g., socioeconomic disadvantages and cardiovascular outcomes).22Although the few recent register-based studies on area effects on health over the life course found only a small proportion of variance in adult morbidity and mortality to be attributable to the area of residence at specific life-course periods,23 mortality risk clustered at the area of residence seemed to accumulate over the life course, corresponding to a cumulative risk life-course model.24 The cumulative risk model is also the model that most closely corresponds to the allostatic load framework, which emphasizes the gradual accumulation of physiological dysregulation over the life course.6 Empirical studies demonstrated that the life-course accumulation of individual socioeconomic disadvantages and of adversity from childhood or adolescence to mid-adulthood were related to allostatic load.25–27In summary, despite the unique contributions of research on the social determinants of health offered by allostatic load, neighborhoods and health, and the life-course epidemiology frameworks, empirical efforts to integrate them are at an early stage. To advance this task, the cumulative risk life-course model appears to be a promising focal point.The present 27-year prospective cohort study specifically aimed to examine whether socioeconomic disadvantages of the residence neighborhood at 4 time points during the life course were cumulatively related to allostatic load in mid-adulthood, when taking the life-course accumulation of disadvantageous personal living conditions into account. Previous research hypothesized that women were more embedded in their communities, and because of this, could be more exposed to neighborhoods stressors and health effects.28 Therefore, our secondary aim explored this cumulative effect on allostatic load separately in women and men.     

Gender as a Moderator in the Association of Body Weight to Smoking and Mental Health

Objectives. I sought to examine gender''s role as a moderator in the association of relative body weight to smoking and mental health.Methods. Data came from the 2004–2005 Minnesota Survey on Adult Substance Use, a statewide telephone survey (N = 16 289). Current smoking and mental health problems were examined in relation to relative body weight across genders, with control for covariates.Results. Relative to their healthy-weight counterparts, overweight or obese men were less likely to smoke, whereas overweight women were more likely to smoke. Mental health problems were not related to relative body weight among men. However, overweight or obese women were more likely than were their healthy-weight counterparts to have a negative self-assessment of mental health, and obese women were more likely to have a mental health problem. In addition, underweight women had increased odds of being a smoker and having mental health problems.Conclusions. The results indicate that gender has a moderating role in the association between body weight and both smoking and mental health. Gender-specific analysis rather than adjustment for the impact of gender in analyses is a promising avenue for future research.The prevalence of overweight and obesity in the United States has increased sharply since the mid-1970s for both adults and children. Data from the National Health and Nutrition Examination Surveys (NHANES) show that, among adults aged 20 to 74 years, the prevalence of obesity increased from 15.0% in the 1976–1980 survey to 32.9% in the 2003–2004 survey.¹ Between 1980 and 2002, overweight prevalence tripled for children and adolescents aged 6 to 19 years. Many experts have referred to an “obesity epidemic,” and a recent survey commissioned by the Trust for America''s Health found that 85% of the general public thinks that obesity in the United States has reached “epidemic proportions.”²As a stigmatized condition, obesity is among the easiest to recognize and the most difficult to treat of medical conditions.^3–5 Obese individuals face social exclusion and discrimination in many areas of their lives in addition to the physical health issues that are related to obesity. Escalating rates of obesity, accompanied by the prevalence of extreme dieting and the use of smoking or other unhealthy means of weight control, have raised concern among both public health experts and the general public.^6–9Being overweight or obese increases the risk of many physical health conditions, including hypertension, type 2 diabetes, coronary heart disease, and some cancers. However, the association between obesity and other behavioral health issues such as smoking and mental disorders is not as conclusive; some studies found no direct relationship, whereas others found a significant relationship or even an inverse relationship between obesity and depression or other behavioral health problems.^10–13 Similarly, research on the association between smoking and body weight has yielded inconsistent results, with many studies reporting an inverse relationship between smoking and body weight, and others showing smokers to be heavier than nonsmokers in many Western populations.^14–18Various theses have been proposed to explain these inconsistent findings. Friedman and Brownell¹⁹ have noted that the inconsistencies might be attributed to methodological and sampling limitations. Mustillo et al.¹² have suggested that they might be caused by failure to consider the developmental trajectories of obesity—that is, to distinguish between the transiently obese, the chronically obese, and those whose obesity is confined to childhood or adolescence. Other scholars have suggested that the inconsistencies were caused by effect modifications by various factors, including demographic and socioeconomic characteristics.^20,21Body image and weight concerns have been found to be more important for females than for males, and numerous studies have found that dieting behaviors and weight concerns are related to current smoking and prospectively related to smoking initiation among young girls, but not boys.^7,16,22,23 Although the relationship between smoking and body weight per se has not been established, literature reviews^16,22 show a rather consistent association between concern about one''s weight and current smoking or smoking initiation among adolescent girls and an association between greater weight concern and higher rates of smoking relapse or reduced likelihood of quitting among women.Several studies have found a difference by gender in the relationship between obesity and depressive mood.^24,25 For example, in their NHANES study, Onyike et al.²⁶ found that obesity was associated with past-month depression in women but not in men. Additional support for gender''s function as a possible moderator comes from a study on genetic variants of the obesity gene: Comings et al.²⁷ found that genetic factors were more likely to be involved in obesity among females than males and were causally involved not only in obesity but in its associated behavioral disorders, such as anxiety and depression.Following the framework of effect modifications, I examined gender''s role in the association of body weight to smoking and mental health. I hypothesized that (1) overweight or obese women were more likely to smoke than their healthy-weight counterparts, (2) overweight or obese women were more likely to have mental health problems than their healthy-weight counterparts, and (3) the association between body weight and both smoking and mental health would be stronger among women than among men.     

Environmental Factors Associated With Social Participation of Older Adults Living in Metropolitan,Urban, and Rural Areas: The NuAge Study

Objectives. We compared the social participation of older adults living in metropolitan, urban, and rural areas, and identified associated environmental factors.Methods. From 2004 to 2006, we conducted a cross-sectional study using an age-, gender-, and area-stratified random sample of 1198 adults (aged 67–82 years). We collected data via interviewer-administered questionnaires and derived from Canadian censuses.Results. Social participation did not differ across living areas (P = .09), but after controlling for potential confounding variables, we identified associated area-specific environmental variables. In metropolitan areas, higher social participation was associated with greater proximity to neighborhood resources, having a driver’s license, transit use, and better quality social network (R² = 0.18). In urban areas, higher social participation was associated with greater proximity to neighborhood resources and having a driver’s license (R² = 0.11). Finally, in rural areas, higher social participation was associated with greater accessibility to key resources, having a driver’s license, children living in the neighborhood, and more years lived in the current dwelling (R² = 0.18).Conclusions. To enhance social participation of older adults, public health interventions need to address different environmental factors according to living areas.Social participation, which is defined as the involvement of the person in activities that provide interactions with others in the community,1 is a key element of successful2 and healthy3,4 aging that ensures survival and development of people in society throughout their existence.5 As a modifiable target of health interventions, social participation is conceptualized by the Human Development Model and Disability Creation Process to be the result of bidirectional interaction between personal and environmental factors.5 Some personal factors,6 including age, gender, and health, are recognized as being related to social participation.2 Environmental factors (i.e., aspects that are extrinsic to individuals and generate a reaction from them)7 relate to the immediate social and physical environment to which individuals, especially older adults, are exposed. Environmental factors may act as facilitators or barriers to the accomplishment of social and community activities.5 Environmental factors are also important because interventions targeting the environment may have a greater impact on an individual’s social participation than those targeting individual factors.8To date, some theoretical and empirical evidence supports associations between specific environmental factors and social participation.9 For example, the Human Development Model and Disability Creation Process showed that support, attitude, services, systems, policies, and accessibility of the physical environment can be associated with social participation.5 Another study demonstrated that user-friendliness of the physical environment and access to transport facilities promote older adults’ social participation in both urban and rural areas.10 Favorable characteristics, such as proximity to resources and services, including access to food shopping, health services, banking, and social or sports clubs, are also important factors.11,12 Moreover, independently of individual demographic and socioeconomic characteristics, older adults living in affluent areas are less likely to have lower social participation.13 Support from the social environment14 and resource accessibility in the physical environment11 may be seen as imperatives to help individuals with disabilities living in the community.15 The presence of local resources may have an impact on the likelihood of initiating and maintaining social links with community members.16 However, little is known about which environmental factors are associated with social participation of older adults according to living area. Living in metropolitan, urban, or rural areas can have an impact on many personal factors, such as health and well-being, as well as on several environmental factors (e.g., neighborhood socioeconomic status or access to services and transportation). For example, access to public transport for people living in rural areas may be limited, which can be a challenge.17 To our knowledge, only 1 study18 compared social participation of older people living in metropolitan, urban, and rural areas. Despite area differences in income, access to public transportation, services and resources, automobile use, satisfaction with social support, and sense of security, no significant difference was found in social participation and its associated factors.18 In our study, which involved 350 older adults, we operationalized social participation by the level of difficulty and assistance required in targeted daily activities and social roles. Because having a better understanding of older adults’ social participation according to their living environment could improve the development of public health services, further studies operationalizing social participation by the frequency of involvement in social activities and considering other environmental factors are needed. We aimed to compare social participation of older adults living in metropolitan, urban and rural areas, and identified associated environmental factors.     

Prevalence of HCV Infection Among Clients in Community-Based Health Settings in Hawaii, 2002–2010: Assessing Risk Factors

Objectives. We sought to determine the prevalence of HCV infection and identify risk factors associated with HCV infection among at-risk clients presenting to community-based health settings in Hawaii.Methods. Clients from 23 community-based sites were administered risk factor questionnaires and screened for HCV antibodies from December 2002 through May 2010. We performed univariate and multivariate logistic regression analyses.Results. Of 3306 participants included in the analysis, 390 (11.8%) tested antibody positive for HCV. Highest HCV antibody prevalence (17.0%) was in persons 45 to 64 years old compared with all other age groups. Significant independent risk factors were current or prior injection drug use (P < .001), blood transfusion prior to July 1992 (P = .002), and having an HCV-infected sex partner (P = .03). Stratification by gender revealed sexual exposure to be significant for males (P = .001).Conclusions. Despite Hawaii’s ethnic diversity, high hepatocellular carcinoma incidence, and a statewide syringe exchange program in place since the early 1990s, our HCV prevalence and risk factor findings are remarkably consistent with those reported from the mainland United States. Hence, effective interventions identified from US mainland population studies should be generalizable to Hawaii.Hepatitis C is the most prevalent chronic blood-borne viral infection in the United States, with an estimated 1.3% of the population chronically infected.1 Chronic HCV infection is often asymptomatic; approximately 75% of infected persons may be unaware that they are infected.2 Transmission is mainly through direct blood-to-blood contact, and the most common risk factor in the United States is the sharing of injection drug use equipment.1,2 Complications from HCV infection include cirrhosis, hepatocellular carcinoma (HCC), and end-stage liver disease; more than one third of liver transplants in the United States can be attributed to HCV.3 There is currently no vaccine,4 and until recently, standard therapy with pegylated interferon and ribavirin achieved a sustained virologic response in only 40% to 50% of patients.5,6In May 2011, the US Food and Drug Administration approved 2 new HCV-specific protease inhibitors for the treatment of chronic genotype 1 HCV infections: boceprevir7,8 and telaprevir.9,10 In combination with standard therapy, these drugs have achieved significantly higher rates of sustained virologic response: up to 67% to 75%.7,10 Achieving sustained virologic response is key to reducing mortality, HCC, and other comorbidities.11,12 With such a large percentage of HCV-infected individuals unaware of their status and new successful treatments available, there is now increased rationale for health providers to screen their clients for chronic HCV infection.The population of Hawaii differs from that of the mainland United States on a number of key factors related to HCV and HCC. Hawaii has the highest incidence of HCC nationally.13 Asian/Pacific Islanders have the highest incidence of HCC in the United States,13 and 57% of the Hawaii’s population is Asian, either alone or in combination with other ethnic groups.14 The high HCC incidence among Asian/Pacific Islanders is attributed in large part to chronic hepatitis B virus (HBV) infection,13,15 and the identification and treatment of persons with chronic HBV or HCV infection is an important public health priority in Hawaii. In addition, Hawaii implemented a statewide syringe exchange program in the early 1990s, the first state to do so.16 The risk factor demonstrating the strongest association with HCV infection in the United States is injection drug use,1,17 and syringe exchange programs have demonstrated efficacy in reducing HCV infection among injection drug users.18,19To our knowledge, only 3 HCV prevalence studies have been conducted in Hawaii; however, each focused on a specific well-defined subgroup population: patients with HCC,20 HIV-infected persons enrolled in a state drug assistance plan,21 and adults from a homeless shelter.22The Adult Viral Hepatitis Prevention Program of the Hawaii State Department of Health, which offers risk-based HCV antibody testing based on reported national risk factors,1,23 has been collecting data on persons undergoing screening since 2002. We investigated the prevalence of HCV antibody positivity among at-risk clients of community-based health programs in Hawaii and identified demographic characteristics and independent risk factors associated with HCV infection.     

Longitudinal Predictors of Human Papillomavirus Vaccination Among a National Sample of Adolescent Males

Objectives. We conducted a longitudinal study to examine human papillomavirus (HPV) vaccine uptake among male adolescents and to identify vaccination predictors.Methods. In fall 2010 and 2011, a national sample of parents with sons aged 11 to 17 years (n = 327) and their sons (n = 228) completed online surveys. We used logistic regression to identify predictors of HPV vaccination that occurred between baseline and follow-up.Results. Only 2% of sons had received any doses of HPV vaccine at baseline, with an increase to 8% by follow-up. About 55% of parents who had ever received a doctor’s recommendation to get their sons HPV vaccine did vaccinate between baseline and follow-up, compared with only 1% of parents without a recommendation. Fathers (odds ratio = 0.29; 95% confidence interval = 0.09, 0.80) and non-Hispanic White parents (odds ratio = 0.29; 95% confidence interval = 0.11, 0.76) were less likely to have vaccinated sons. Willingness to get sons HPV vaccine decreased from baseline to follow-up among parents (P < .001) and sons (P = .003).Conclusions. Vaccination against HPV remained low in our study and willingness to vaccinate may be decreasing. Physician recommendation and education about HPV vaccine for males may be key strategies for improving vaccination.Quadrivalent human papillomavirus (HPV) vaccine against types 6, 11, 16, and 18 is approved to protect against genital warts (caused mostly by HPV types 6 and 111) and anal cancer (caused mostly by HPV types 16 and 182) in males.3 About 4% of men in the United States report a previous diagnosis of genital warts,4 and about 2250 new cases of anal cancer occur annually among males in the United States.5 Given the high levels of HPV concordance among sexual partners,6 vaccinating males may also have indirect health benefits for their partners.7 United States guidelines began including HPV vaccine for males in October 2009.8 The Advisory Committee on Immunization Practices first provided a permissive recommendation, recommending the 3-dose quadrivalent vaccine series for males aged 9 to 26 years but not making it part of their routine vaccination schedule.8 In October 2011, the Advisory Committee on Immunization Practices updated its stance on HPV vaccine for males and recommended routine vaccination of boys aged 11 to 12 years with catch-up vaccination for males aged 13 to 21 years.9 The updated recommendation continues to allow HPV vaccine to be given to males aged as young as 9 years and up to 26 years.9Although numerous studies have examined HPV vaccine uptake among females,10 data on HPV vaccine uptake among males are sparse. Despite mostly encouraging early levels of parental acceptability of the vaccine for males,11–13 initial estimates found that only about 2% of male adolescents in the United States had received any doses of HPV vaccine by the end of 2010.14,15 Recent data suggest that this increased to about 8% by the end of 2011.16 We are not aware of any studies that have examined predictors of vaccine uptake among males.Our study addresses several important gaps in the existing literature. We provide the first longitudinal examination of HPV vaccination among males and identify predictors of vaccine uptake. In doing so, we used data from both parents and their adolescent sons because many adolescents are involved in vaccination decisions.17 We also examined longitudinal changes in vaccine acceptability among parents and sons and parents’ reasons for not getting their sons HPV vaccine, because these data may provide valuable insight about future HPV vaccine uptake among males.     

Impact of Rurality,Broiler Operations,and Community Socioeconomic Factors on the Risk of Campylobacteriosis in Maryland

Objectives. We evaluated the combined impact of community-level environmental and socioeconomic factors on the risk of campylobacteriosis.Methods. We obtained Campylobacter case data (2002–2010; n = 3694) from the Maryland Foodborne Diseases Active Surveillance Network. We obtained community-level socioeconomic and environmental data from the 2000 US Census and the 2007 US Census of Agriculture. We linked data by zip code. We derived incidence rate ratios by Poisson regressions. We mapped a subset of zip code–level characteristics.Results. In zip codes that were 100% rural, incidence rate ratios (IRRs) of campylobacteriosis were 6 times (IRR = 6.18; 95% confidence interval [CI] = 3.19, 11.97) greater than those in urban zip codes. In zip codes with broiler chicken operations, incidence rates were 1.45 times greater than those in zip codes without broilers (IRR = 1.45; 95% CI = 1.34, 1.58). We also observed higher rates in zip codes whose populations were predominantly White and had high median incomes.Conclusions. The community and environment in which one lives may significantly influence the risk of campylobacteriosis.Campylobacter is a leading cause of bacterial gastroenteritis in much of the developed and developing world.1,2 In addition to the diarrhea and vomiting associated with gastroenteritis, infection with Campylobacter can lead to more serious sequelae, such as Guillain-Barré syndrome, a demyelinating autoimmune disorder that can sometimes lead to death.3 Scallan et al.4 estimated that Campylobacter causes approximately 845 000 domestically acquired illnesses in the United States each year, along with 8463 hospitalizations and 76 deaths. Although the majority of these illnesses are estimated to be foodborne,4 attributing specific infections to specific sources has been challenging.Commonly reported risk factors for Campylobacter outbreaks include exposure to undercooked poultry,5 unpasteurized milk,6,7 and contaminated water.8 Eating in restaurants,9 not observing proper food preparation practices,10 and traveling abroad9,11 have also been associated with both outbreaks and sporadic (nonoutbreak) cases of campylobacteriosis. Additional risk factors for sporadic infections include contact with pets,5,12 contact with farm animals and livestock,13,14 and contact with animal feces.15 Significant associations of living in rural areas with risk of campylobacteriosis also have been identified in Europe and Canada.16–18 Moreover, a specific feature of rural environments—animal density—has been identified as a significant predictor of Campylobacter incidence in Canada and New Zealand.16,17Several sociodemographic risk factors for campylobacteriosis have also been identified, the 2 most consistent being gender (males) and age (< 5 years).8,16–19 Previous studies have also evaluated socioeconomic factors associated with the incidence of Campylobacter infection, and the findings suggest that these infections may occur more frequently among individuals characterized by higher socioeconomic status.16,20 Moreover, Samuel et al.21 reported that the incidence of campylobacteriosis among African Americans was lower than that among other ethnic groups across multiple sites in the United States, although hospitalization rates for this group were higher. These findings, however, may be influenced by differentials in illness reporting among varying races and ethnic groups.Nonetheless, these previous reports have largely resulted from population-based case–control studies focused on individual-level data. To our knowledge, no US study has examined the combined effect of community-level environmental and socioeconomic risk factors on the risk of campylobacteriosis. Such an analysis can be useful in (1) identifying (and possibly predicting) “hot spot” communities that bear high burdens of this illness, and (2) addressing significant research gaps concerning potential health disparities in the risk of infectious diseases.22 We linked Maryland Foodborne Diseases Active Surveillance (FoodNet) data to US Census data and US Department of Agriculture Census of Agriculture data at the zip code level to evaluate associations between community-level environmental and socioeconomic risk factors and the incidence of Campylobacter infections in Maryland.     

Neighborhood Social Capital,Neighborhood Attachment,and Dental Care Use for Los Angeles Family and Neighborhood Survey Adults

Objectives. We tested the hypothesis that neighborhood-level social capital and individual-level neighborhood attachment are positively associated with adult dental care use.Methods. We analyzed data from the 2000–2001 Los Angeles Family and Neighborhood Survey that were linked to US Census Bureau data from 2000 (n = 1800 adults aged 18–64 years across 65 neighborhoods). We used 2-level hierarchical logistic regression models to estimate the odds of dental use associated with each of 4 forms of social capital and neighborhood attachment.Results. After adjusting for confounders, the odds of dental use were significantly associated with only 1 form of social capital: social support (adjusted odds ratio [AOR] = 0.85; 95% confidence interval [CI] = 0.72, 0.99). Individual-level neighborhood attachment was positively associated with dental care use (AOR = 1.05; 95% CI = 1.01, 1.10).Conclusions. Contrary to our hypothesis, adults in neighborhoods with higher levels of social capital, particularly social support, were significantly less likely to use dental care. Future research should identify the oral health–related attitudes, beliefs, norms, and practices in neighborhoods and other behavioral and cultural factors that moderate and mediate the relationship between social capital and dental care use.Oral health is an indicator of general health and social justice.1,2 Common dental diseases such as tooth decay and gum disease are linked to chronic health conditions, including cardiovascular disease, stroke, diabetes, obesity, and kidney disease.3–7 When left untreated, dental diseases can lead to difficulties chewing food, pain, systemic infections, hospitalization, and, in rare cases, death. Less visible are the social consequences of poor oral health, such as lost work hours,8 functional limitations,9,10 and poor quality of life.11A comprehensive strategy for optimal oral health involves exposure to topical fluorides (e.g., in optimally fluoridated water, toothpaste), limited fermentable carbohydrate intake, tobacco use prevention, and regular dental visits.12 Professional dental care is particularly important because dentists have opportunities to assess a patient’s risk level for oral health problems, provide diagnostic and preventive care as well as needed restorative care, deliver patient-centered anticipatory guidance, and screen for systemic health conditions.13–16 However, not all individuals in the United States have equal access to dental care.17Most dental utilization studies focus on children younger than 18 years and seniors aged 65 years and older, even though data from the National Health and Nutrition Examination Survey indicate a decline in dental care use for US adults aged 18 to 64 years.18 Between 1988 and 1994 and 1999 and 2004, there were significant drops in the proportions of adults who had an annual dental visit for those aged 20 to 34 years (from 63.5% to 54.6%) and those aged 35 to 49 years (from 69.0% to 62.5%).18 The factors related to these declines are unknown.The 2008 World Health Organization report Closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health calls for policies and interventions targeting the social determinants of health to reduce and eliminate health disparities.19 Social determinants of health are the structural and environmental conditions that shape human welfare and well-being,20 with health inequalities attributed to unequal distribution of and access to power, money, and resources.21 Although social factors contribute to disparities in dental care use,22 relevant studies focus mostly on individual-level determinants.23–37 There has been less emphasis on the area-level social determinants of adult dental care use.Social capital is an important health determinant38–41 and is defined as the material, affective, and informational resources inherent in social networks. Most health research has focused on social capital in neighborhoods. Neighborhood-based social capital can be operationalized into 4 forms: (1) social support (provisions that help residents cope with everyday challenges), (2) social leverage (sharing information on health- and non–health-related issues), (3) informal social control (maintenance of safety and norms), and (4) neighborhood organization participation (organized efforts that address community quality of life and personal well-being).42 Social capital has direct and interactive associations with a range of positive and negative health-related outcomes.43,44 In some cases, these resources may not help individuals pursue a desirable health outcome or may inhibit an individual’s efforts through negative influences in the community.45Although investigators have examined social capital and access to health care services,46 fewer oral health–related studies have focused on social capital. In 2 multilevel studies of elderly persons in Japan, number of teeth was positively associated with higher levels of neighborhood friendship networks47 and a higher prevalence of neighborhood peer group activities.48 Neighborhood social capital also moderated the relationship between income inequality and self-reported oral health but not the number of teeth present among the Japanese elderly.49 A study of Japanese students aged 18 to 19 years found that poor self-reported oral health was associated with lower levels of neighborhood trust and with higher levels of neighborhood informal social control.50 Among Brazilians aged 14 to 15 years, a 5-dimension measure showed that social capital (social trust, social control, empowerment, neighborhood security, and political efficacy) was inversely associated with odds of dental injury.51Although social capital was not the primary focus, there are 2 relevant US publications. The first reported positive associations between neighborhood social capital and self-reported oral health for children younger than 18 years.52 In the second, neighborhood social capital was identified as a potential source of oral health disparities between Black children and White children aged 3 to 17 years (measured as having a dental problem and poor self-reported oral health) but not for disparities in preventive dental care use.53 Collectively, these studies suggest that neighborhood social capital is an important determinant of oral health.54–56 However, they have 2 main limitations: (1) none of the operationalizations of social capital considered the extent of neighborhood social ties, the resources linked to these ties, or unequal access to resources42; and (2) none focused on dental care use for adults aged 18 to 64 years, a US population subgroup that has exhibited declines in dental care use.18We addressed previous limitations by adopting a multilevel conceptual model of social capital42,43,45 to examine how neighborhood social capital is associated with dental care use for US adults (Figure 1). We operationalized neighborhood-level social capital as the 4 forms identified earlier (social support, social leverage, informal social control, and neighborhood organization participation). Individual-level neighborhood attachment is the extent to which an individual knows and socializes with neighbors42–44; this moderates the effects of social capital.57 On the basis of this model, we tested 3 hypotheses: (1) higher levels of each form of neighborhood social capital are associated with greater odds of dental use, (2) neighborhood attachment is associated with greater odds of dental care use, and (3) there are interactions between social capital and neighborhood attachment. This study represents an important first step in understanding the social determinants of an important oral health behavior. Our long-term goal is to develop and test neighborhood-based interventions and policies aimed at improving the oral health of individuals at greatest risk for disparities in dental care use.Open in a separate windowFIGURE 1—Conceptual model and proposed study hypotheses tested using data from the Los Angeles Family and Neighborhood Survey, 2000–2001.Note. H1 = hypothesis 1 (there is a direct relationship between the 4 social capital forms and adult dental care use); H2 = hypothesis 2 (there is a direct relationship between neighborhood attachment and adult dental care use); H3 = hypothesis 3 (in modeling adult dental care use, there is an interaction between the four forms of social capital and neighborhood attachment).     

Human Papillomavirus Vaccination Among Young Adult Gay and Bisexual Men in the United States

Objectives. We examined human papillomavirus (HPV) vaccination among gay and bisexual men, a population with high rates of HPV infection and HPV-related disease.Methods. A national sample of gay and bisexual men aged 18 to 26 years (n = 428) completed online surveys in fall 2013. We identified correlates of HPV vaccination using multivariate logistic regression.Results. Overall, 13% of participants had received any doses of the HPV vaccine. About 83% who had received a health care provider recommendation for vaccination were vaccinated, compared with only 5% without a recommendation (P < .001). Vaccination was lower among participants who perceived greater barriers to getting vaccinated (odds ratio [OR] = 0.46; 95% confidence interval [CI] = 0.27, 0.78). Vaccination was higher among participants with higher levels of worry about getting HPV-related disease (OR = 1.54; 95% CI =  1.05, 2.27) or perceived positive social norms of HPV vaccination (OR = 1.57; 95% CI =  1.02, 2.43).Conclusions. HPV vaccine coverage is low among gay and bisexual men in the United States. Future efforts should focus on increasing provider recommendation for vaccination and should target other modifiable factors.Oncogenic human papillomavirus (HPV) types (mainly types 16 and 18) cause an estimated 93% of anal cancers, 63% of oropharyngeal cancers, and 36% of penile cancers among men in the United States.1 Nononcogenic HPV types 6 and 11 cause almost all anogenital warts.2 Gay and bisexual men have high rates of HPV infection and HPV-related disease. A recent review suggests that more than 50% of HIV-negative gay and bisexual men have an anogenital HPV infection.3 About 7% of gay and bisexual men report a history of genital warts.4 Anal cancer is also of great concern, with incidence among HIV-negative gay and bisexual men estimated to be 35 cases per 100 000 population.5 The anal cancer incidence rate among all men in the United States is just 1.6 cases per 100 000 population.6US guidelines began including the quadrivalent HPV vaccine (against HPV types 6, 11, 16, and 18) for males in October 2009.7 The Advisory Committee on Immunization Practices (ACIP) first provided a permissive recommendation that allowed the HPV vaccine to be given to males aged 9 to 26 years but did not include the vaccine in their routine vaccination schedule.7 In October 2011, the ACIP began recommending routine vaccination for boys aged 11 to 12 years with catch-up vaccination for males aged 13 to 21 years.8 Importantly, the ACIP recommends HPV vaccination for men who have sex with men through age 26 years.8The HPV vaccine series consists of 3 doses, with the second dose administered 1 to 2 months after the first dose, and the third dose is administered 6 months after the first dose.7 The quadrivalent HPV vaccine is currently approved to protect males against genital warts and anal cancer.9 Despite recommendations, recent data suggest that fewer than 21% of males in the United States have received any doses of the HPV vaccine.10–14Although several HPV-related disparities exist among gay and bisexual men, little research has addressed HPV vaccination among this population. Past studies have shown that knowledge about HPV and the HPV vaccine tends to be modest among gay and bisexual men.15–19 Many gay and bisexual men have indicated their willingness to get the HPV vaccine, with estimates ranging from 36% to 86%.16,18–20 Data on actual HPV vaccine coverage are sparse; a past study found only 7% of 68 young adult gay and bisexual men had received any doses of the HPV vaccine.11 This study was, however, conducted before the ACIP recommendation for routine vaccination of males.We built on this past research by examining HPV vaccination among a national sample of young adult gay and bisexual men in the recommended age range for HPV vaccination (18–26 years). We identified correlates of vaccination and why young adult gay and bisexual men are not getting the HPV vaccine. These data will help inform future programs for increasing HPV vaccination among this high-risk population.     

Racial,Ethnic, and Socioeconomic Differences in the Incidence of Obesity Related to Childbirth

Objectives. We investigated the relationship between childbirth and 5-year incidence of obesity.Methods. We performed a prospective analysis of data on 2923 nonobese, nonpregnant women aged 14 to 22 years from the 1979 National Longitudinal Survey of Youth Cohort, which was followed from 1980 to 1990. We used multivariable logistic regression analyses to determine the adjusted relative risk of obesity for mothers 5 years after childbirth compared with women who did not have children.Results. The 5-year incidence of obesity was 11.3 per 100 parous women, compared with 4.5 per 100 nulliparous women (relative risk [RR] = 3.5; 95% confidence interval [CI] = 2.4, 4.9; P < .001). The 5-year incidence of obesity was 8.6 for primiparous women (RR = 2.8; 95% CI = 1.5, 5.0) and 12.2 for multiparous women (RR = 3.8; 95% CI = 2.6, 5.6). Among parous women, White women had the lowest obesity incidence (9.1 per 100 vs 15.1 per 100 for African Americans and 12.5 per 100 for Hispanics).Conclusions. Parous women have a higher incidence of obesity than do nulliparous women, and minority women have a higher incidence of parity-related obesity than do White women. Thus, efforts to reduce obesity should target postpartum women and minority women who give birth.Women in the United States are disproportionately overweight, particularly minority and socioeconomically disadvantaged women.^1,2 Approximately two thirds of adult women are overweight, and of this group, one third are obese.¹ Among racial/ethnic groups, African American and Hispanic women have the highest prevalences of obesity, at 50% and 40%, respectively.¹ Women who are socioeconomically disadvantaged have higher obesity rates than do women of higher socioeconomic standing.³ In addition, emerging evidence links perinatal factors such as parity (number of births) to obesity in later life,^4–9 although researchers investigating the relationship between parity and major weight gain or obesity have found mixed results.^7,10–17Several studies have reported that multiparous women (those who have had 2 or more live births) were more likely to be overweight than were nulliparous women (those who have never had a live birth).^10–13,15 Another study found that primiparous women (those who have had at least 1 live birth) were more likely to be overweight and to have major long-term weight gain than were multiparous and nulliparous women.¹⁷ Other studies have found little or no relationship between parity and weight gain or obesity.^7,12,14,16 The inconsistencies in these findings may stem from differences in definitions of the main outcomes, the use of cross-sectional study designs versus prospective designs, or the exclusion of prevalent cases of obesity at baseline. The majority of these studies focused on the outcomes of mean body mass index (BMI), mean weight gain, weight change, major weight gain, or prevalence of obesity, but not on the incidence of parity-related obesity. Additionally, these studies did not establish that births occurred before the outcome measured.^10,12,13,16 Nor have these studies investigated whether racial/ethnic or socioeconomic differences exist in the incidence of parity-related obesity. Thus, we used prospective data to determine the 5-year incidence of parity-related obesity among our sample and to investigate whether this incidence varied by race/ethnicity or socioeconomic status.