Health Among Caregivers of Children With Health Problems: Findings From a Canadian Population-Based Study

Objectives. We used population-based data to evaluate whether caring for a child with health problems had implications for caregiver health after we controlled for relevant covariates.Methods. We used data on 9401 children and their caregivers from a population-based Canadian study. We performed analyses to compare 3633 healthy children with 2485 children with health problems. Caregiver health outcomes included chronic conditions, activity limitations, self-reported general health, depressive symptoms, social support, family functioning, and marital satisfaction. Covariates included family (single-parent status, number of children, income adequacy), caregiver (gender, age, education, smoking status, biological relationship to child), and child (age, gender) characteristics.Results. Logistic regression showed that caregivers of children with health problems had more than twice the odds of reporting chronic conditions, activity limitations, and elevated depressive symptoms, and had greater odds of reporting poorer general health than did caregivers of healthy children.Conclusions. Caregivers of children with health problems had substantially greater odds of health problems than did caregivers of healthy children. The findings are consistent with the movement toward family-centered services recognizing the link between caregivers'' health and health of the children for whom they care.Caring for a child with health problems can entail greater than average time demands,^1,2 medical costs,^3,4 employment constraints,^5,6 and childcare challenges.^6–8 These demands may affect the health of caregivers, a notion supported by a variety of small-scale observational studies that have shown increased levels of stress, distress, emotional problems, and depression among caregivers of children with health problems.^1,2,5,9–12Whether these problems are caused by the additional demands of caring for children with health problems or by confounding variables is difficult to answer definitively. The literature reports the identification of a variety of factors purported to be associated with caregiver health, including contextual factors such as socioeconomic status^13–17; child factors such as level of disability,^{1,11,13,18–21} presence of behavior problems,^22–25 and overall child adjustment²⁶; and caregiver-related characteristics such as coping strategies^11,22,27 and support from friends and family.^15,17,28,29 In general, this work has been based on small clinic-based samples^9,30 or specific child populations (e.g., cerebral palsy,^5,25 attention-deficit/hyperactivity disorder^31,32), and typically has been hampered by limited generalizability and a lack of careful, multivariate analysis. Furthermore, most studies have focused on caregivers'' psychological health,^1,2,5,9–12 although physical health effects may also exist among caregivers.^5,19,25,33One of the few studies to involve large-scale, population-based data compared the health of 468 caregivers of children with cerebral palsy to the health of a population-based sample of Canadian parents.⁵ The study showed that caregivers of children with cerebral palsy had poorer health on a variety of physical and psychological health measures. Furthermore, the data were consistent with a stress process model,^5,25 which proposes that additional stresses associated with caring for a child with cerebral palsy directly contribute to poorer caregiver health. However, these findings were based on a specific subpopulation of caregivers and univariate comparisons that could not control for potentially important confounders such as variation in caregiver education, income, and other demographic factors.We used population-based data to test the hypothesis that the health of caregivers of children with health problems would be significantly poorer than that of caregivers of healthy children, even after we controlled for relevant covariates. Our approach of using large-scale, population-based data representing a broad spectrum of childhood health problems³⁴ makes 4 key contributions to the current literature. First, our use of population-based data rather than small-scale, clinic-based studies yielded results that are potentially generalizable to a wide group of caregivers caring for children with health problems. Second, our examination of children with and without health problems allowed us to examine caregiver health effects across a wide variety of caregiving situations. Third, consideration of physical health outcomes (in addition to more regularly studied psychological outcomes) increased our knowledge of the breadth of caregiver health issues. Finally, controlling for relevant covariates allowed us to rule out a number of alternative explanations for caregiver health effects.     

Connecting Discovery and Delivery: The Need For More Evidence on Effective Smoking Cessation Strategies for People Living With HIV/AIDS

Smoking prevalence among the 1.1 million Americans living with HIV/AIDS is 2 to 3 times higher than the 19.8% rate among the general population. Since 1990, scientists have worked toward the discovery of health risks related to smoking in people living with HIV/AIDS; however, few studies have evaluated the delivery of smoking cessation interventions for this population. Increasing linkages between discovery science and delivery science may facilitate a faster transition to delivery of smoking cessation interventions for people living with HIV/AIDS.Health research often focuses on the discovery of risk factors associated with disease and death.¹ Although discovery of health risks is necessary to protect health, the delivery of interventions to improve health is equally important.^1–5 Information regarding how science moves from discovery to delivery points to substantial time lag and little cross-talk between discovery and delivery research.^1,6 This may be especially problematic in areas such as HIV/AIDS and smoking, where delay between discovery of smoking-related health outcomes in people living with HIV/AIDS and the delivery of interventions to reduce smoking among this population has serious consequences.Smoking prevalence in people living with HIV/AIDS is 2 to 3 times higher than is the 19.8% rate among the general population.^7–16 Discovery research has concluded that smokers with HIV/AIDS are more likely to be nonadherent to treatment, have a greater chance of being diagnosed with an AIDS-defining condition or dying, and report lower quality of life than do nonsmoking persons with HIV/AIDS.^13,17–21 Smokers living with HIV/AIDS have a higher risk of disease and opportunistic infection than do smokers who do not have HIV/AIDS.^9,22–34Delivery research indicates that population-specific smoking cessation interventions can be effective.^35–52 Although few studies have examined such strategies for persons living with HIV/AIDS,³⁵ a recent study found that 86% of smokers with HIV/AIDS would not benefit from standard cessation programs.⁵³ I used citation network analysis^54–56 to examine the characteristics of—and possible relationships between—discovery research relating health outcomes to smoking in persons living with HIV/AIDS and delivery research on interventions to reduce smoking among this population.     

Impact of individual-, environmental-, and policy-level factors on health care utilization among US farmworkers

Objectives. We examined individual-, environmental-, and policy-level correlates of US farmworker health care utilization, guided by the behavioral model for vulnerable populations and the ecological model.Methods. The 2006 and 2007 administrations of the National Agricultural Workers Survey (n = 2884) provided the primary data. Geographic information systems, the 2005 Uniform Data System, and rurality and border proximity indices provided environmental variables. To identify factors associated with health care use, we performed logistic regression using weighted hierarchical linear modeling.Results. Approximately half (55.3%) of farmworkers utilized US health care in the previous 2 years. Several factors were independently associated with use at the individual level (gender, immigration and migrant status, English proficiency, transportation access, health status, and non-US health care utilization), the environmental level (proximity to US–Mexico border), and the policy level (insurance status and workplace payment structure). County Federally Qualified Health Center resources were not independently associated.Conclusions. We identified farmworkers at greatest risk for poor access. We made recommendations for change to farmworker health care access at all 3 levels of influence, emphasizing Federally Qualified Health Center service delivery.US farmworkers face significant disease burden¹ and excessive mortality rates for some diseases (e.g., certain cancers and tuberculosis) and injuries.² Disparities in health outcomes likely stem from occupational exposures and socioeconomic and political vulnerabilities. US farmworkers are typically Hispanic with limited education, income, and English proficiency.³ Approximately half are unauthorized to work in the United States.³ Despite marked disease burden, health care utilization appears to be low.^1,4–9 For example, only approximately half of California farmworkers received medical care in the previous year.⁶ This rate parallels that of health care utilization for US Hispanics, of whom approximately half made an ambulatory care visit in the previous year, compared with 75.7% of non-Hispanic Whites.¹⁰ Disparities in dental care have a comparable pattern.^6,8,11,12 However, utilization of preventive health services is lower for farmworkers^5,7,13,14 than it is for both US Hispanics and non-Hispanic Whites.^15,16Farmworkers face numerous barriers to health care^1,4,17: lack of insurance and knowledge of how to use or obtain it,^6,18 cost,^{5,6,12,13,18–20} lack of transportation,^{6,12,13,19–21} not knowing how to access care,^6,18,20,21 few services in the area or limited hours,^12,20,21 difficulty leaving work,¹⁹ lack of time,^5,13,19 language differences,^6,8,18–20 and fear of the medical system,¹³ losing employment,⁶ and immigration officials.²¹ Few studies have examined correlates of health care use among farmworkers. Those that have are outdated or limited in representativeness.^5,7,14,22,23 Thus, we systematically examined correlates of US health care use in a nationally representative sample of farmworkers, using recently collected data. The sampling strategy and application of postsampling weights enhance generalizability. We selected correlates on the basis of previous literature and the behavioral model for vulnerable populations.²⁴ The behavioral model posits that predisposing, enabling, and need characteristics influence health care use.²⁵ The ecological model, which specifies several levels of influence on behavior (e.g., policy, environmental, intrapersonal),²⁶ provided the overall theoretical framework. To our knowledge, we are the first to extensively examine multilevel correlates of farmworker health care use. We sought to identify farmworkers at greatest risk for low health care use and to suggest areas for intervention at all 3 levels of influence so that farmworker service provision can be improved.     

All-Cause and External Mortality in Released Prisoners: Systematic Review and Meta-Analysis

Objectives. We systematically reviewed studies of mortality following release from prison and examined possible demographic and methodological factors associated with variation in mortality rates.Methods. We searched 5 computer-based literature indexes to conduct a systematic review of studies that reported all-cause, drug-related, suicide, and homicide deaths of released prisoners. We extracted and meta-analyzed crude death rates and standardized mortality ratios by age, gender, and race/ethnicity, where reported.Results. Eighteen cohorts met review criteria reporting 26 163 deaths with substantial heterogeneity in rates. The all-cause crude death rates ranged from 720 to 2054 per 100 000 person-years. Male all-cause standardized mortality ratios ranged from 1.0 to 9.4 and female standardized mortality ratios from 2.6 to 41.3. There were higher standardized mortality ratios in White, female, and younger prisoners.Conclusions. Released prisoners are at increased risk for death following release from prison, particularly in the early period. Aftercare planning for released prisoners could potentially have a large public health impact, and further work is needed to determine whether certain groups should be targeted as part of strategies to reduce mortality.The global prison population in 2008 was estimated at 9.8 million with a median rate of imprisonment of 145 prisoners per 100 000 persons, most of whom are aged between 18 and 44 years.1 More than 2.3 million of these prisoners reside in the United States, which has the highest rate of imprisonment of 756 per 100 000 population. Natural cause mortality inside prison has been reported to be lower than that of the general population in France,2 Russia,3 England and Wales,4 and the United States.5 However, it is well-established that prisoner suicide rates are elevated compared with age-matched general populations.6 For example, the suicide rate of male prisoners in England and Wales between 1973 and 2003 was found to be 5 times higher than that of the general population,7 and in US jails, it has been reported to be 8 times higher.8 The odds of chronic medical conditions are increased by up to 4 times in US prisons.9 As prison populations are drawn from socioeconomically deprived backgrounds with reduced access to health care and health-seeking behavior when living in the community,10 prison provides an opportunity to provide public health interventions including health education and improving engagement with health services following release.11 For example, targeted health interventions such as medication review12 and HIV health education13,14 have been proposed.The health of prisoners following release from prison is less understood. At the end of 2009 in the United States, 819 308 prisoners were on parole or release following a prison term,15 and in England and Wales 20 895 offenders were released from prison in the first quarter of 2011.16 Despite these high absolute numbers, research has demonstrated that most sampled US jails did not plan for release of prisoners with mental illness, cardiovascular disease, or HIV/AIDS even though they considered it important.17 Mortality from suicide and drug-related causes has been reported to be particularly high in the immediate postrelease period,18,19 and, thus, public health interventions to target this period for those with a history of substance misuse have been outlined.20 The current review aims to synthesize evidence on mortality rates following release from prison and examine possible demographic and methodological factors associated with variation in these rates.     

Interventions to increase physical activity among healthy adults: meta-analysis of outcomes

Objectives. We conducted a meta-analysis summarizing the effects of interventions designed to increase physical activity among healthy adults.Methods. Our comprehensive searches located 358 reports eligible for inclusion. We used random-effects analyses to synthesize data, and we used meta-analytic analogues of regression and analysis of variance to examine potential moderator variables. We also explored moderator variable robustness and publication bias.Results. We computed meta-analytic results from studies comprising 99 011 participants. The overall mean effect size for comparisons of treatment groups versus control groups was 0.19 (higher mean for treatment participants than for control participants). This effect size is consistent with a mean difference of 496 ambulatory steps per day between treatment and control participants. Exploratory moderator analyses suggested that the characteristics of the most effective interventions were behavioral interventions instead of cognitive interventions, face-to-face delivery versus mediated interventions (e.g., via telephone or mail), and targeting individuals instead of communities. Participant characteristics were unrelated to physical activity effect sizes. Substantial between-studies heterogeneity remained beyond individual moderators.Conclusions. Interventions designed to increase physical activity were modestly effective. Interventions to increase activity should emphasize behavioral strategies over cognitive strategies.Adequate physical activity is linked with important health outcomes, including reductions in cardiovascular disease,¹ type 2 diabetes,^2,3 some cancers,^4,5 falls,⁶ osteoporotic fractures,⁷ and depression,⁸ and improvements in physical function,^9–11 weight management,^12–15 cognitive function,^16,17 and quality of life.¹⁸ Despite this compelling evidence for the benefits of physical activity, healthy adults commonly get an inadequate amount of physical activity.¹⁹Extensive primary research has tested interventions to increase physical activity. Although many meta-analyses have addressed health outcomes of physical activity, few have examined physical activity behavior outcomes. The seminal 1996 meta-analysis of interventions to increase physical activity behavior reported a moderate effect size across 127 studies of healthy and chronically ill adults and children.²⁰ Their moderator analyses documented larger effect sizes when interventions used behavior modification, had face-to-face delivery versus mediated delivery (e.g., telephone), focused on healthy people, measured active leisure versus structured exercise, measured low-intensity activity, encouraged unsupervised physical activity versus supervised physical activity, targeted participants of diverse ages, and targeted groups versus individuals.A recent comprehensive meta-analysis of work site programs for healthy adults documented a d effect size (standardized mean difference) of 0.21 but did not conduct moderator analyses to determine the intervention characteristics linked with the largest physical activity increases.²¹ Other meta-analyses have integrated across chronically ill adults²² or focused on small, specific interventions or populations, such as primary care–based referrals to physical activity programs,²³ older adults,²⁴ computer-based interventions,²⁵ or environmental interventions.²⁶ Many meta-analyses have been plagued by small samples that hinder moderator analyses.^27,28 For example, only 19 studies were included in the most recent Cochrane review that aggregated randomized, controlled trials with follow-up data gathered at least 6 months after interventions to increase physical activity among sedentary adults.²⁷Because of the importance of physical activity and the proliferation of studies testing interventions to increase physical activity, we sought to move this area of science forward by conducting a comprehensive meta-analysis to estimate the overall effect of interventions and, more importantly, to conduct moderator analyses to identify intervention characteristics associated with the best outcomes. We addressed 2 questions: (1) What overall effects do interventions designed to increase physical activity have on physical activity behavior after completion of interventions? (2) Do interventions’ effects on physical activity behavior vary depending on intervention, methodology, or sample characteristics?     

Health status, neighborhood socioeconomic context, and premature mortality in the United States: The National Institutes of Health-AARP Diet and Health Study

Objectives. We examined whether the risk of premature mortality associated with living in socioeconomically deprived neighborhoods varies according to the health status of individuals.Methods. Community-dwelling adults (n = 566 402; age = 50–71 years) in 6 US states and 2 metropolitan areas participated in the ongoing prospective National Institutes of Health–AARP Diet and Health Study, which began in 1995. We used baseline data for 565 679 participants on health behaviors, self-rated health status, and medical history, collected by mailed questionnaires. Participants were linked to 2000 census data for an index of census tract socioeconomic deprivation. The main outcome was all-cause mortality ascertained through 2006.Results. In adjusted survival analyses of persons in good-to-excellent health at baseline, risk of mortality increased with increasing levels of census tract socioeconomic deprivation. Neighborhood socioeconomic mortality disparities among persons in fair-to-poor health were not statistically significant after adjustment for demographic characteristics, educational achievement, lifestyle, and medical conditions.Conclusions. Neighborhood socioeconomic inequalities lead to large disparities in risk of premature mortality among healthy US adults but not among those in poor health.Research dating back to at least the 1920s has shown that the United States has experienced persistent and widening socioeconomic disparities in premature mortality over time.^1–5 However, it has been unclear whether socioeconomic inequalities affect the longevity of persons in good and poor health equally. Socioeconomic status (SES) and health status are interrelated,^6–8 and both are strong independent predictors of mortality.⁹ Low SES is associated with greater risk of ill health and premature death,^{1–5,8,10–13} partly attributable to disproportionately high prevalence of unhealthful lifestyle practices^10,14,15 and physical and mental health conditions.^13,16 Correspondingly, risk of premature mortality is higher in poor than in more affluent areas.^16,17 Although the association between neighborhood poverty and mortality is independent of individual-level SES,^17,18 aggregation of low-SES populations in poor areas may contribute to variations in health outcomes across neighborhoods. Conversely, economic hardships resulting from ill health may lead persons in poor physical or mental health to move to poor neighborhoods.¹⁹ This interrelatedness may create spurious associations between neighborhood poverty and mortality.Although previous studies have found that the risk of premature death associated with poor health status varies according to individuals'' SES,^20,21 no published studies have examined whether the relative risks for premature mortality associated with living in neighborhoods with higher levels of socioeconomic deprivation vary by health status of individuals. Clarifying these relationships will inform social and public health policies and programs that aim to mitigate the health consequences of neighborhood poverty.^22,23We used data from a large prospective study to examine whether the risk of premature mortality associated with neighborhood socioeconomic context differs according to health status at baseline and remains after adjustment for person-level risk factors for mortality, such as SES, lifestyle practices, and chronic medical illnesses.     

Social gradients in oral health in older adults: findings from the English longitudinal survey of aging

Objectives. We examined prospective associations between socioeconomic position (SEP) markers and oral health outcomes in a national sample of older adults in England.Methods. Data were from the English Longitudinal Survey of Aging, a national cohort study of community-dwelling people aged 50 years and older. SEP markers (education, occupation, household income, household wealth, subjective social status, and childhood SEP) and sociodemographic confounders (age, gender, and marital status) were from wave 1. We collected 3 self-reported oral health outcomes at wave 3: having natural teeth (dentate vs edentate), self-rated oral health, and oral impacts on daily life. Using multivariate logistic regression models, we estimated associations between each SEP indicator and each oral health outcome, adjusted for confounders.Results. Irrespective of SEP marker, there were inverse graded associations between SEP and edentulousness, with proportionately more edentate participants at each lower SEP level. Lower SEP was also associated with worse self-rated oral health and oral impacts among dentate, but not among edentate, participants.Conclusions. There are consistent and clear social gradients in the oral health of older adults in England, with disparities evident throughout the SEP hierarchy.The inverse linear relationship between socioeconomic position (SEP) and health is well established.^1–4 The uneven distribution of health across socioeconomic strata has been observed in both industrialized and less developed countries and for most common diseases and causes of death.^1,5–8 In most cases, the association between SEP and health is characterized by a linear graded pattern, with people in each lower SEP category having successively worse levels of health and dying earlier than those that are better off, a characteristic known as the social gradient in health.⁹Although there is clear and consistent evidence about the existence of the social gradient in working-age adults,^10,11 studies in older adults are less consistent, with some showing attenuation of the gradient^12,13 and others reporting that it persisted^14,15 or even increased¹⁶ in magnitude.Oral health is particularly important at older ages with tooth loss shown to be independently associated with disability and mortality.^17–20 Oral health status in older people is also an important determinant of nutritional status.²¹Socioeconomic disparities in oral health have been consistently demonstrated for various indicators, mostly clinical and disease related^22–31 but also subjective measures of oral health and quality of life.^30,32–38 Some of these studies have explicitly assessed the existence of an oral health gradient,^{23,25–31,34–37} but almost all were carried out on adolescents and adults, with very few focusing on older people.^33,36 These few relevant studies are cross-sectional and inconclusive and have used a limited number of SEP indicators (typically, education and occupational class), thereby hindering any comprehensive analysis on the relationship between SEP and oral health.We addressed the gap in the literature about the existence of an oral health gradient at older ages by examining the prospective associations between a wide range of SEP indicators (education, occupation, household income, household wealth, subjective social status [SSS], and childhood SEP) and various oral health outcomes (presence of natural teeth, self-rated oral health, and oral impacts) in a national sample of older adults from the English Longitudinal Survey of Aging (ELSA). We explored whether there are any significant socioeconomic inequalities in oral health among older people in England and, if so, whether these take the form of a gradient.     

The association between perceived discrimination and obesity in a population-based multiracial and multiethnic adult sample

Objectives. We examined whether perceived chronic discrimination was related to excess body fat accumulation in a random, multiethnic, population-based sample of US adults.Methods. We used multivariate multinomial logistic regression and logistic regression analyses to examine the relationship between interpersonal experiences of perceived chronic discrimination and body mass index and high-risk waist circumference.Results. Consistent with other studies, our analyses showed that perceived unfair treatment was associated with increased abdominal obesity. Compared with Irish, Jewish, Polish, and Italian Whites who did not experience perceived chronic discrimination, Irish, Jewish, Polish, and Italian Whites who perceived chronic discrimination were 2 to 6 times more likely to have a high-risk waist circumference. No significant relationship between perceived discrimination and the obesity measures was found among the other Whites, Blacks, or Hispanics.Conclusions. These findings are not completely unsupported. White ethnic groups including Polish, Italians, Jews, and Irish have historically been discriminated against in the United States, and other recent research suggests that they experience higher levels of perceived discrimination than do other Whites and that these experiences adversely affect their health.It is estimated that 2 of every 3 adults in the United States are overweight or obese.^1,2 Obesity is a major risk factor for chronic health conditions, such as type 2 diabetes, coronary heart disease, hypertension, stroke, some forms of cancer, and osteoarthritis.³ Although it is widely accepted that high-fat diets and physical inactivity are preventable risk factors,⁴ obesity continues to increase.^1,2,5There is a growing interest in the relationship between psychosocial risk factors and excess body fat accumulation.^6–16 In particular, some evidence suggests that psychosocial stressors may play a role in disease progression in general and in excess body fat in particular.^7,8,17 The key factors underlying physiological reactions to psychosocial stress have not been completely elucidated, but McEwen and Seeman¹⁷ and others^7,18,19 posit that the continued adaptation of the physiological system to external challenges alters the normal physiological stress reaction pathways and that these changes are related to adverse health outcomes.^8,17,18,20 For example, in examining the association between psychosocial stress and excess body fat accumulation, Björntorp and others have suggested that psychosocial stress is linked to obesity, especially in the abdominal area.^7,8Perceived discrimination, as a psychosocial stressor, is now receiving increased attention in the empirical health literature.^21–24 Such studies suggest perceived discrimination is inversely related to poor mental and physical health outcomes and risk factors, including hypertension,^24,25 depressive symptoms,^26–28 smoking,^29–31 alcohol drinking,^32,33 low birthweight,^34,35 and cardiovascular outcomes.^36–38Internalized racism, the acceptance of negative stereotypes by the stigmatized group,³⁹ has also been recognized as a race-related psychosocial risk factor.⁴⁰ Recent studies have also suggested that race-related beliefs and experiences including perceived discrimination might be potentially related to excess body fat accumulation. Three of these studies^9,13,41 showed that internalized racism was associated with an increased likelihood of overweight or abdominal obesity among Black Caribbean women in Dominica⁴¹ and Barbados¹³ and adolescent girls in Barbados.⁹ These researchers posit that individuals with relatively high levels of internalized racism have adopted a defeatist mindset, which is believed to be related to the physiological pathway associated with excess body fat accumulation. However, Vines et al.¹⁶ found that perceived racism was associated with lower waist-to-hip ratios among Black women in the United States. Although the assessment of race-related risk factors varied across these studies, the findings suggest that the salience of race-related beliefs and experiences may be related to excess body fat accumulation.Collectively, the results of these studies are limited. First, because they examined the relationship between race-related beliefs and experiences and excess body fat only among women, we do not know if this relationship is generalizable to men.^13,16,41 Second, these studies only examined this relationship among Blacks, even though perceived unfair treatment because of race/ethnicity has been shown to be adversely related to the health of multiple racial/ethnic population groups in the United States^42–49 and internationally.^27,50–55 Third, none of the studies have examined the relationship between excess body fat accumulation and perceived nonracial/nonethnic experiences of interpersonal discrimination. Some evidence suggests that the generic perception of unfair treatment or bias is adversely related to health, regardless of whether it is attributed to race, ethnicity, or some other reason.^45,55,56 Fourth, none of these studies included other measures of stress. We do not know if the association between race-related risk factors and obesity is independent of other traditional indicators of stress.Using a multiethnic, population-based sample of adults, we examined the association of perceived discrimination and obesity independent of other known risk factors for obesity, including stressful major life events. Additionally, because reports of perceived racial/ethnic discrimination and non-racial/ethnic discrimination vary by racial/ethnic groups^24,45,46,57 and because Whites tend to have less excess body fat than do Blacks and Hispanics,^1,3 we examined the relationships between perceived discrimination and excess body fat accumulation among Hispanics, non-Hispanic Whites, and non-Hispanic Blacks.     

Reaiming RE-AIM: Using the Model to Plan, Implement, and Evaluate the Effects of Environmental Change Approaches to Enhancing Population Health

The RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework, which provides a practical means of evaluating health interventions, has primarily been used in studies focused on changing individual behaviors. Given the importance of the built environment in promoting health, using RE-AIM to evaluate environmental approaches is logical. We discussed the benefits and challenges of applying RE-AIM to evaluate built environment strategies and recommended modest adaptations to the model. We then applied the revised model to 2 prototypical built environment strategies aimed at promoting healthful eating and active living. We offered recommendations for using RE-AIM to plan and implement strategies that maximize reach and sustainability, and provided summary measures that public health professionals, communities, and researchers can use in evaluating built environment interventions.The RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework¹ was developed to enhance the impact of health promotion interventions by evaluating the dimensions considered most relevant to real-world implementation, such as the capacity to reach underserved populations and to be adopted within diverse settings.^2,3 Briefly, the reach dimension of the framework refers to the percentage and characteristics of individuals receiving the intervention; effectiveness refers to the impact of the intervention, including anticipated as well as unanticipated outcomes; adoption concerns the percentage and representativeness of settings that adopt the intervention; implementation refers to the consistency and cost of delivering the intervention; and maintenance refers to long-term sustainability at both the setting and individual levels (see http://www.re-aim.org for more information about the framework.).^1,4,5The RE-AIM model was intended to guide planning and evaluation of evidence-based interventions^6,7 that address the different levels of the socioecological model, such as those that target individual health behavior change by increasing intrapersonal, organizational, and community resource support.⁸ It has been used to evaluate programmatic and policy⁹ interventions addressing a wide range of health conditions (e.g., diabetes, obesity, and hypertension)^10–12 and health behaviors (e.g., physical activity, dietary behaviors, and smoking).^13–15Despite RE-AIM''s efficacy as a public health planning and evaluation framework, it has not been formally applied to interventions targeting the social or built (i.e., manmade features of the environment that provide the settings for human activity)^16,17 environment. As public health continues to expand its focus beyond surveillance and epidemiology to address root factors affecting community health, we need models that help frame the planning and implementation of multilevel health interventions and guide comprehensive evaluations of the processes, effects, and outcomes¹⁸ associated with such interventions. Holistic evaluations of changes in public spaces (e.g., changes in transportation and land use) are critical given the complexity of such changes and their strong potential to positively affect social capital and cohesion or to exacerbate social and health inequities.Here we focus on applying RE-AIM to built environment interventions, although many of the issues and recommendations are also applicable to social environment interventions, and intended or unintended social consequences of interventions are included within the RE-AIM model. Our specific goals are to provide a rationale for using RE-AIM to plan and evaluate built environment changes that promote health behavior, discuss definitions and measures of the dimensions of RE-AIM and propose adaptations to them, illustrate applications of the dimensions through examples of built environment changes, and establish practical RE-AIM summary measures for built environment interventions.     

Intergenerational relationships between the smoking patterns of a population-representative sample of US mothers and the smoking trajectories of their children

Objectives. We assessed intergenerational transmission of smoking in mother-child dyads.Methods. We identified classes of youth smoking trajectories using mixture latent trajectory analyses with data from the Children and Young Adults of the National Longitudinal Survey of Youth (n = 6349). We regressed class membership on prenatal and postnatal exposure to maternal smoking, including social and behavioral variables, to control for selection.Results. Youth smoking trajectories entailed early-onset persistent smoking, early-onset experimental discontinued smoking, late-onset persistent smoking, and nonsmoking. The likelihood of early onset versus late onset and early onset versus nonsmoking were significantly higher among youths exposed prenatally and postnatally versus either postnatally alone or unexposed. Controlling for selection, the increased likelihood of early onset versus nonsmoking remained significant for each exposure group versus unexposed, as did early onset versus late onset and late onset versus nonsmoking for youths exposed prenatally and postnatally versus unexposed. Experimental smoking was notable among youths whose mothers smoked but quit before the child''s birth.Conclusions. Both physiological and social role-modeling mechanisms of intergenerational transmission are evident. Prioritization of tobacco control for pregnant women, mothers, and youths remains a critical, interrelated objective.Women who smoke during pregnancy are more likely to have offspring who become adolescent smokers.^1–7 Studies link mother''s smoking during pregnancy with youths'' earlier smoking initiation,^3,7–9 greater persistence in regular smoking,^3,7 and stronger nicotine dependency.^6,8,10,11Hypothesized physiological pathways for mother-to-child transmission of smoking are reviewed elsewhere^12–14 and may include inherited susceptibility to addiction alone or in combination with in utero neurodevelopmental exposure and scarring that activates nicotine susceptibility. Furthermore, because few women who smoke during pregnancy quit after delivery^15,16 higher rates of smoking among offspring may reflect role modeling of maternal smoking behavior. Notably, parental smoking is hypothesized to demonstrate pro-smoking norms and solidify pro-smoking attitudes.^17,18Studies considering both smoking during pregnancy and subsequent maternal smoking outcomes have sought to distinguish between these proposed social and physiological transmission pathways.^{1–4,6,7,9,19} Similarly, studies controlling for family sociodemographic factors^{1,2,4,5,7,8,10,11,19,20} or maternal propensity for health or risk taking^1,2,9,10 have sought to further distinguish direct physiological or social transmission from selection. Studies considering children''s cognitive and behavioral outcomes have shown that selection by maternal social and behavioral precursors to smoking during pregnancy strongly biases findings on smoking during pregnancy^21,22; however, it remains unclear whether this is also the case for youth smoking. Some studies^2,3,5,6,19 have observed that smoking during pregnancy operates independently of subsequent maternal smoking. A few have found that smoking during pregnancy is only independently associated in select analyses (e.g., for initiation but not frequency or number of cigarettes^6,9 or only among females^7,20). Several have found that smoking during pregnancy does not operate independently of subsequent maternal smoking behavior,^1,4 and the remaining studies do not address postnatal maternal smoking.^8,9,11We explored whether these inconsistencies in findings supporting social or physiological mechanisms for intergenerational transmission can be accounted for by more comprehensively examining maternal and child smoking behavior. Previous work has established the advantages of statistical models for youth smoking trajectories that capture initiation, experimentation, cessation, or continued use.^23–28 Studies focusing on parental smoking concurrent with youth smoking suggest that postnatal exposures may differentially predispose youths for specific smoking trajectories.^24,26–28 Only 3 known studies have considered whether smoking during pregnancy influences youth smoking progression, and these have shown greater likelihood of early regular use^3,11 and telescoping to dependence.⁸ However, limitations of sample selectivity and measurement and modeling of maternal and youth smoking outcomes restrict the generalizability and scope of these findings.²⁹ To specifically address these limitations and more comprehensively assess hypothesized intergenerational transmission pathways, we used US population–representative data, latent variable techniques, and a rich set of data on maternal and youth smoking and social and behavioral selection factors. We characterized trajectories of youth smoking from adolescence through young adulthood and considered exposure to various maternal smoking patterns from prebirth to the child''s early adolescence.     

Suicidal Behavior Among Female Sex Workers in Goa, India: The Silent Epidemic

Objectives. We sought to study suicidal behavior prevalence and its association with social and gender disadvantage, sex work, and health factors among female sex workers in Goa, India.Methods. Using respondent-driven sampling, we recruited 326 sex workers in Goa for an interviewer-administered questionnaire regarding self-harming behaviors, sociodemographics, sex work, gender disadvantage, and health. Participants were tested for sexually transmitted infections. We used multivariate analysis to define suicide attempt determinants.Results. Nineteen percent of sex workers in the sample reported attempted suicide in the past 3 months. Attempts were independently associated with intimate partner violence (adjusted odds ratio [AOR] = 2.70; 95% confidence interval [CI] = 1.38, 5.28), violence from others (AOR = 2.26; 95% CI = 1.15, 4.45), entrapment (AOR = 2.76; 95% CI = 1.11, 6.83), regular customers (AOR = 3.20; 95% CI = 1.61, 6.35), and worsening mental health (AOR = 1.05; 95% CI = 1.01, 1.11). Lower suicide attempt likelihood was associated with Kannad ethnicity, HIV prevention services, and having a child.Conclusions. Suicidal behaviors among sex workers were common and associated with gender disadvantage and poor mental health. India''s widespread HIV-prevention programs for sex workers provide an opportunity for community-based interventions against gender-based violence and for mental health services delivery.Suicide is a public health priority in India. Rates of suicide in India are 5 times higher than in the developed world,^1,2 with particularly high rates of suicide among young women.^3–5 Verbal autopsy surveillance from southern India suggests that suicide accounts for 50% to 75% of all deaths among young women, with average suicide rates of 158 per 100 000.²Common mental disorders such as depressive and anxiety disorders, and social disadvantage such as gender-based violence and poverty, are major risk factors for suicide among women.^1,3,6–8 Although research from high-income countries shows that common mental disorders are a major contributor to the risk of suicidal behavior, their role is less clear in low- and middle-income countries in which social disadvantage has been found to be at least as important.^1,3,6–8 Gender disadvantage is increasingly seen as an important contributing factor to the high rates of suicide seen among women in Asia.^1,3,6,7 Gender-based violence is a common manifestation of gender disadvantage and has been linked with common mental disorders and suicide in population-based studies of women and young adults in Goa, India.^4,5,9 Lack of autonomy, early sexual debut, limited sexual choices, poor reproductive health, and social isolation are other manifestations of gender disadvantage.Sex work in India is common. An estimated 0.6% to 0.7% of the female adult urban population are engaged in commercial sexual transactions.¹⁰ Studies from developed nations have found a high prevalence of self-harming behaviors in people engaged in transactional sexual activity.¹¹ There is also growing evidence suggesting that HIV-positive individuals from traditionally stigmatized groups report higher rates of violence exposure and suicidal ideation.^12,13 Female sex workers in India are a traditionally stigmatized group, with high prevalence of HIV¹⁰ and levels of stigma and violence that relate to the context of their work.¹⁴ Yet, despite substantial investigation of their reproductive and sexual health needs, there is virtually no information on suicide and its determinants among female sex workers from low- and middle-income countries.¹⁵As demonstrated in the hierarchical conceptual framework outlined in Figure 1,^4,5,9 we hypothesized that gender disadvantage, sex work, and health factors together with factors indicative of social disadvantage are distal determinants of female sex workers'' vulnerability to suicidal behaviors,^4,5,9,15 the effects of which would be mediated though poor mental health.³ We studied the burden of suicidal behaviors in a cross-sectional sample of female sex workers in Goa, India. We explored the association of sociodemographic factors, type of sex work, sexual health, and gender disadvantage, with and without measures of poor mental health, on suicide attempts in the past 3 months.Open in a separate windowFIGURE 1A conceptual framework for social risk factors for suicide among female sex workers in India.Note. STI = sexually transmitted infection.     

The Case for Improving the Health of Ex-Prisoners

The global prison population exceeds 10 million and continues to grow; more than 30 million people are released from custody annually. These individuals are disproportionately poor, disenfranchised, and chronically ill.There are compelling, evidence-based arguments for improving health outcomes for ex-prisoners on human rights, public health, criminal justice, and economic grounds. These arguments stand in stark contrast to current policy and practice in most settings.There is also a dearth of evidence to guide clinicians and policymakers on how best to care for this large and growing population during and after their transition from custody to community. Well-designed longitudinal studies, clinical trials, and burden of disease studies are pivotal to closing this evidence gap.The world prison population is more than 10.75 million and is growing at a rate in excess of population growth.1 Although in the United States there is a distinction between prisoners (felony offenders incarcerated in state and federal prisons) and jail detainees (mostly misdemeanor offenders), this distinction is not made in most countries. Here we use the term prisoner to refer to both prisoners and jail detainees. Because of the rapid turnover of custodial populations, it has been estimated that globally, more than 30 million people move through prisons each year.2 Incarceration rates vary markedly within and between countries, and are heavily influenced by public policy decisions, such as the criminalization of drug users3 and the de-institutionalization of the mentally ill.4 The United States has the highest incarceration rate in the world (743 per 100 000 population) and accounts for more than one fifth of the world’s prisoners, with approximately 2.2 million people in custody on any one day.1 Of these, 1.5 million are held in state and federal prisons, and spend on average three years in custody before returning to the community; more than 700 000 are held in local jails, where the average stay is less than seven days. Given the large incarcerated population and rapid turnover of jail detainees, in excess of 11 million persons pass through US correctional facilities each year—more than in any other country.5–7Prisoners globally are characterized by complex and multifaceted health problems.8 Although imprisonment confers its own unique health risks,9,10 health usually improves in custody, where stable accommodation and regular meals are provided at little or no cost, illicit drugs are less readily available, and high-intensity health services are routinely provided.11,12 Unfortunately, these health gains are often rapidly lost after return to the community, where many ex-prisoners experience poor health-related outcomes, including poorly controlled disease,13 elevated rates of life-threatening drug overdose,14,15 preventable hospitalization,16,17 and mortality.18,19 Key to improving these outcomes is increased access to health care for ex-prisoners,20 but this has proven difficult to achieve. Despite recent encouraging research findings,21 the greater challenge has been translating promising pilot programs into policy, at scale and in a sustainable way. Here we make the case for improving the health of ex-prisoners, in the hope that this will provide a platform for evidence-based advocacy to improve the health of this profoundly marginalized, challenging, and underserved population.     

Reinforcement of smoking and drinking: tobacco marketing strategies linked with alcohol in the United States

Objectives. We investigated tobacco companies’ knowledge about concurrent use of tobacco and alcohol, their marketing strategies linking cigarettes with alcohol, and the benefits tobacco companies sought from these marketing activities.Methods. We performed systematic searches on previously secret tobacco industry documents, and we summarized the themes and contexts of relevant search results.Results. Tobacco company research confirmed the association between tobacco use and alcohol use. Tobacco companies explored promotional strategies linking cigarettes and alcohol, such as jointly sponsoring special events with alcohol companies to lower the cost of sponsorships, increase consumer appeal, reinforce brand identity, and generate increased cigarette sales. They also pursued promotions that tied cigarette sales to alcohol purchases, and cigarette promotional events frequently featured alcohol discounts or encouraged alcohol use.Conclusions. Tobacco companies’ numerous marketing strategies linking cigarettes with alcohol may have reinforced the use of both substances. Because using tobacco and alcohol together makes it harder to quit smoking, policies prohibiting tobacco sales and promotion in establishments where alcohol is served and sold might mitigate this effect. Smoking cessation programs should address the effect that alcohol consumption has on tobacco use.Smoking remains the leading preventable cause of premature mortality in the United States, accounting for more than 440 000 deaths annually.¹ Alcohol consumption is the third-leading cause of mortality in the nation.² Each year, approximately 79 000 deaths are attributable to excessive alcohol use.³ The concurrent use of cigarettes and alcohol further increases risks for certain cancers, such as cancer of the mouth, throat, and esophagus.^4,5 In addition, the use of both tobacco and alcohol makes it more difficult to quit either substance.⁶Smoking and drinking are strongly associated behaviors.^7–13 Smokers are more likely to drink alcohol,¹¹ drink more frequently,^8,11 consume a higher quantity of alcohol,^8,11,14 and demonstrate binge drinking (5 or more drinks per episode) than are nonsmokers.^9,11,12 Alcohol drinkers, especially binge drinkers, are also more likely to smoke^7,8,10 and are more likely to smoke half a pack of cigarettes or more per day.¹⁰The association between tobacco use and alcohol use becomes stronger with the heavier use of either substance.^8,15,16 Alcohol consumption increases the desire to smoke,^17,18 and nicotine consumption increases alcohol consumption.¹⁹ Experimental studies have demonstrated that nicotine and alcohol enhance each other''s rewarding effects.^16,18 Alcohol increases the positive subjective effects of smoking,^8,15,16,20 and smoking while using alcohol is more reinforcing than is smoking without concurrent alcohol use.⁸ Smokers smoke more cigarettes while drinking alcohol,^8,15,18 especially during binge-drinking episodes.^8,15 This behavior has also been observed among nondaily smokers^8,15 and light smokers.¹⁷The concurrent use of alcohol and tobacco is common among young adults,^8,10,12,21 including nondaily smokers,^19,22–24 nondependent smokers,⁸ and novice smokers.¹³ Young adult smokers have reported that alcohol increases their enjoyment of and desire for cigarettes^8,25 and that tobacco enhances the effect of alcohol: it “brings on the buzz” or “gave you a double buzz.”^13,23,26 Young adult nondaily smokers described the pairing of alcohol and cigarettes as resembling “milk and cookies” or “peanut butter with jelly.”²⁴ Young adults have also been the focus of aggressive tobacco promotional efforts in places where alcohol is consumed, such as bars and nightclubs.^27,28Consumer products often fall into cohesive groups (sometimes referred to as “Diderot unities”) that may reinforce certain patterns of consumption,²⁹ and these groupings may be influenced by marketing activities. In the case of tobacco and alcohol, these product links may have been further enhanced by cooperation between tobacco and alcohol companies (e.g., cosponsorship) or corporate ownership of both tobacco and alcohol companies (e.g., Philip Morris''s past ownership of Miller Brewing Company).We used tobacco industry documents to explore tobacco companies’ knowledge regarding linked tobacco and alcohol use and the companies’ marketing strategies that linked cigarettes with alcohol. We were interested in 3 basic issues: (1) what tobacco companies knew about the association between drinking and smoking, especially about smokers’ drinking behaviors, (2) how tobacco and alcohol companies developed cross promotions featuring cigarettes and alcohol, and (3) how tobacco companies linked cigarettes with alcohol in their marketing activities and the benefits they expected to gain from those activities.     

Demonstrating the Importance and Feasibility of Including Sexual Orientation in Public Health Surveys: Health Disparities in the Pacific Northwest

Objectives. We identified health disparities for a statewide population of lesbian, gay, and bisexual (LGB) men and women compared with their heterosexual counterparts.Methods. We used data from the 2003–2006 Washington State Behavioral Risk Factor Surveillance System to examine associations between sexual orientation and chronic health conditions, health risk behaviors, access to care, and preventive services.Results. Lesbian and bisexual women were more likely than were heterosexual women to have poor physical and mental health, asthma, and diabetes (bisexuals only), to be overweight, to smoke, and to drink excess alcohol. They were also less likely to have access to care and to use preventive services. Gay and bisexual men were more likely than were heterosexual men to have poor mental health, poor health-limited activities, and to smoke. Bisexuals of both genders had the greatest number and magnitude of disparities compared with heterosexuals.Conclusions. Important health disparities exist for LGB adults. Sexual orientation can be effectively included as a standard demographic variable in public health surveillance systems to provide data that support planning interventions and progress toward improving LGB health.A limited number of studies have described chronic disease health risks among lesbian, gay, and bisexual (LGB) adults. Few of these studies have been population based, and those were often conducted in limited geographic areas or did not include a heterosexual comparison group. Most have relied on convenience samples or other targeted study designs and studied only specific health issues such as smoking or HIV risk factors.The patchwork of available studies indicates that LGB adults have important health disparities. Compared with heterosexual women, lesbian and bisexual women have been shown to have poorer overall health and mental health^1–3; higher rates of smoking,^4–11 alcohol consumption,^8,11–13 asthma,^3,13 and obesity²; and less access to health care,¹² including routine preventive screenings such as Papanicolaou (Pap) tests or mammograms,^14–16 although they were more likely to have had HIV tests.¹⁵ Gay and bisexual men have reported higher rates of smoking^4–6,9 and alcohol use⁸ and poorer general health and mental health^1,3 compared with heterosexual men. An LGB companion document to the Healthy People 2010 initiative identified 29 specific objectives that prioritized sexual minorities, but data by sexual orientation were not available in public health surveillance systems to track most of those objectives.¹⁷ In a recent review of sexual and gender minority health issues, Mayer et al.¹⁸ called for more inclusion of sexual minority identifiers in national data sets as a necessary next step in elimination of health disparities.In 2003, Washington began to include a question about sexual orientation in its Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is a telephone-based survey of adults that is sponsored by the Centers for Disease Control and Prevention (CDC) and implemented throughout the United States.¹⁹For previous analyses, we combined data from 2 states (Washington and Oregon) collecting LGB information in BRFSS since 2003 into a single data set to gain sufficient numbers to describe LGB smoking behaviors.⁶ After 4 years of data collection, we now have enough LGB respondents from Washington alone to examine a variety of indicators. The purpose of this study was to describe a variety of health indicators for a statewide population of LGB men and women compared with their heterosexual counterparts. By demonstrating the feasibility and relevance of collecting information on sexual orientation in the BRFSS, we provide justification for public health surveillance systems to progress beyond “don''t ask, don''t tell” policies.     

Walking and Cycling to Health: A Comparative Analysis of City, State, and International Data

Objectives. We sought to determine the magnitude, direction, and statistical significance of the relationship between active travel and rates of physical activity, obesity, and diabetes.Methods. We examined aggregate cross-sectional health and travel data for 14 countries, all 50 US states, and 47 of the 50 largest US cities through graphical, correlation, and bivariate regression analysis on the country, state, and city levels.Results. At all 3 geographic levels, we found statistically significant negative relationships between active travel and self-reported obesity. At the state and city levels, we found statistically significant positive relationships between active travel and physical activity and statistically significant negative relationships between active travel and diabetes.Conclusions. Together with many other studies, our analysis provides evidence of the population-level health benefits of active travel. Policies on transport, land-use, and urban development should be designed to encourage walking and cycling for daily travel.Many nations throughout the world have experienced large increases in obesity rates over the past 30 years.^1,2 The World Health Organization estimates that more than 300 million adults are obese,³ putting them at increased risk for diseases such as diabetes, hypertension, cardiovascular disease, gout, gallstones, fatty liver, and some cancers.^4,5 Several studies have linked the increase in obesity rates to physical inactivity^6–8 and to widespread availability of inexpensive, calorie-dense foods and beverages.^1,9The importance of physical activity for public health is well established. A US Surgeon General''s report in 1996, Physical Activity and Health,¹⁰ summarized evidence from cross-sectional studies; prospective, longitudinal studies; and clinical investigations. The report concluded that physical inactivity contributes to increased risk of many chronic diseases and health conditions. Furthermore, the research suggested that even 30 minutes per day of moderate-intensity physical activity, if performed regularly, provides significant health benefits. Subsequent reports have supported these conclusions.^11–13The role of physical activity in prevention of weight gain is well documented.¹⁴ Strong evidence from cross-sectional studies has established an inverse relationship between physical activity and body mass index.^15,16 In addition, longitudinal studies have shown that exercisers gain less weight than do their sedentary counterparts.^6,8 Thus, the obesity epidemic may be explained partly by declining levels of physical activity.^1,17,18A growing body of evidence suggests that differences in the built environment for physical activity (e.g., infrastructure for walking and cycling, availability of public transit, street connectivity, housing density, and mixed land use) influence the likelihood that people will use active transport for their daily travel.^19,20 People who live in areas that are more conducive to walking and cycling are more likely to engage in these forms of active transport.^21–25 Walking and cycling can provide valuable daily physical activity.^26–30 Such activities increase rates of caloric expenditure,³¹ and they generally fall into the moderate-intensity range that provides health benefits.^32–35 Thus, travel behavior could have a major influence on health and longevity.^29,30,36,37Over the past decade, researchers have begun to identify linkages between active travel and public health.^38–40 Cross-sectional studies indicate that walking and cycling for transport are linked to better health. The degree of reliance on walking and cycling for daily travel differs greatly among countries.^39,41 European countries with high rates of walking and cycling have less obesity than do Australia and countries in North America that are highly car dependent.²⁶ In addition, walking and cycling for transport are directly related to improved health in older adults.⁴² The Coronary Artery Risk Development in Young Adults Study found that active commuting was positively associated with aerobic fitness among men and women and inversely associated with body mass index, obesity, triglyceride levels, resting blood pressure, and fasting insulin among men.^26,39,41,43Further evidence of the link between active commuting and health comes from prospective, longitudinal studies.⁴⁴ Matthews et al. examined more than 67 000 Chinese women in the Shanghai women''s health study and followed them for an average of 5.7 years.³⁷ Women who walked (P < .07) and cycled (P < .05) for transport had lower rates of all-cause mortality than did those who did not engage in such behaviors. Similarly, Andersen et al. observed that cycling to work decreased mortality rates by 40% among Danish men and women.³⁶ A recent analysis of a multifaceted cycling demonstration project in Odense, Denmark, reported a 20% increase in cycling levels from 1996 to 2002 and a 5-month increase in life expectancy for males.⁴⁵We analyzed recent evidence from a variety of data sources that supports the crucial relationship between active travel, physical activity, obesity, and diabetes. We used city- and state-level data from the United States and national aggregate data for 14 countries to determine the magnitude, direction, and statistical significance of each relationship.     

Life-Course Socioeconomic Position and Incidence of Diabetes Mellitus Among Blacks and Whites: The Alameda County Study, 1965�C1999

Objectives. We examined associations between several life-course socioeconomic position (SEP) measures (childhood SEP, education, income, occupation) and diabetes incidence from 1965 to 1999 in a sample of 5422 diabetes-free Black and White participants in the Alameda County Study.Methods. Race-specific Cox proportional hazard models estimated diabetes risk associated with each SEP measure. Demographic confounders (age, gender, marital status) and potential pathway components (physical inactivity, body composition, smoking, alcohol consumption, hypertension, depression, access to health care) were included as covariates.Results. Diabetes incidence was twice as high for Blacks as for Whites. Diabetes risk factors independently increased risk, but effect sizes were greater among Whites. Low childhood SEP elevated risk for both racial groups. Protective effects were suggested for low education and blue-collar occupation among Blacks, but these factors increased risk for Whites. Income was protective for Whites but not Blacks. Covariate adjustment had negligible effects on associations between each SEP measure and diabetes incidence for both racial groups.Conclusions. These findings suggest an important role for life-course SEP measures in determining risk of diabetes, regardless of race and after adjustment for factors that may confound or mediate these associations.Diabetes mellitus is a major cause of morbidity and mortality in the United States.^1,2 Type 2 diabetes disproportionately affects Hispanics, as well as non-Hispanic Black Americans, American Indians/Alaska Natives, and some Asian/Pacific Islander groups. In the United States, members of racial and ethnic minority groups are almost twice as likely to develop or have type 2 diabetes than are non-Hispanic Whites.^2–5 Significant racial and ethnic differences also exist in the rates of diabetes-related preventive services, quality of care, and disease outcomes.^6–10Researchers have attempted to determine why, relative to Whites, members of racial and ethnic minority groups are disproportionately affected by diabetes. For example, compared with White Americans, Black Americans are presumed to have stronger genetic^5,11 or physiological^11–13 susceptibility to diabetes, or greater frequency or intensity of known diabetes risk factors, such as obesity, physical inactivity, and hypertension.^14–17Black Americans also are more likely than are White Americans to occupy lower socioeconomic positions.¹⁸ Low socioeconomic position (SEP) across the life course is known to influence the prevalence^19–24 and incidence^3,19,25–30 of type 2 diabetes. The risk of diabetes also is greater for people who are obese,^3,17,31 physically inactive,^3,32 or have hypertension,^33,34 all of which are conditions more common among people with lower SEP.^16,35–37Several studies have focused on the extent to which socioeconomic factors, body composition (i.e., weight, height, body mass index, and waist circumference), and behaviors explain the excess risk of diabetes attributed to race.^4,12,19,30 For example, 2 separate studies, one with data from the Health and Retirement Study¹⁹ and the other with data from the Atherosclerosis Risk in Communities Study,³⁰ used race to predict diabetes incidence. Attempting to separate the direct and indirect effects of race on diabetes,³⁸ these studies assessed, via statistical adjustment, which socioeconomic measures and diabetes-related risk factors, when adjusted, could account for the excess risk among Black participants relative to White participants.^19,30 Adjustment for education lessened the effect of Black race on diabetes incidence in the Atherosclerosis Risk in Communities Study.³⁰ In the Health and Retirement Study, excess risk attributed to Black race was not explained by early-life socioeconomic disadvantage, but it was reduced after adjustment for education and later-life economic resources.¹⁹ The validity of this analytic approach has been challenged, however, because the socioeconomic measures used were assumed to have the same meaning across all racial/ethnic groups, a questionable assumption³⁸ in the United States, especially in 1965.We sought to explore the predictive effects of several life-course socioeconomic factors on the incidence of diabetes among both Black and White Americans. We examined demographic confounders (age, gender, marital status) and diabetes risk factors (obesity, large waist circumference, physical inactivity, high blood pressure, depression, access to health care) as possible mediators of the observed associations between SEP and incident diabetes (i.e., the development of new cases of diabetes over time).     

Participatory Design of Mass Health Communication in Three Languages for Seniors and People With Disabilities on Medicaid

Objectives. We used participatory design methods to develop and test guidebooks about health care choices intended for 600 000 English-, Spanish-, and Chinese-speaking seniors and people with disabilities receiving Medicaid in California.Methods. Design and testing processes were conducted with consumers and professionals; they included 24 advisory group interviews, 36 usability tests, 18 focus groups (105 participants), 51 key informant interviews, guidebook readability and suitability testing, linguistic adaptation, and iterative revisions of 4 prototypes.Results. Participatory design processes identified preferences of intended audiences for guidebook content, linguistic adaptation, and format; guidebook readability was scored at the sixth- to eighth-grade level and suitability at 95%. These findings informed the design of a separate efficacy study that showed high guidebook usage and satisfaction, and better gains in knowledge, confidence, and intended behaviors among intervention participants than among control participants.Conclusions. Participatory design can be used effectively in mass communication to inform vulnerable audiences of health care choices. The techniques described can be adapted for a broad range of health communication interventions.Reaching vulnerable populations and communicating effectively with them is a critical public health challenge. The estimated 55.6 million Medicaid beneficiaries¹ are one of the most vulnerable US populations and face serious communication barriers related to limited literacy, language, culture, and disability.^2,3 Of this population, the most at-risk subgroups are the more than 13.5 million seniors and people with disabilities.¹ Their communication barriers are even greater: many have limited health literacy skills (difficulty accessing, understanding, and acting on health information), limited English proficiency,^2,4 or physical or cognitive conditions that impede access to information.With the rapid proliferation of “consumer choice models” in many states, millions of Medicaid beneficiaries are now required to make complex decisions about health plan options and effectively using health care.³ These decisions have important implications for the targeted beneficiaries regarding access to needed preventive, curative, and supportive services.^3,5–9 However, studies show that these populations have difficulty making such decisions—in part because of the poor quality of information they receive.^3–6,8,9 For example, in studies in which seniors on Medicaid used printed materials about health care choices, only 32% of those in Florida³ and 25% of those in California¹⁰ could understand the information. This is not surprising, as more than 250 studies indicate that printed materials related to health are written at reading levels greatly exceeding the average literacy skills of adults in the United States.¹¹Theoretical guidance from socio-ecological,¹² social cognitive,¹³ and transtheoretical models,¹⁴ as well as 40 years of empirical research, suggest that health communication is more effective when it is relevant to people''s personal and social contexts.^15–29 For this reason, interpersonal and tailored computer-mediated communication, which can be personalized, typically show better results than materials-based mass communication.^{18,22,24,25,30–32} However, Medicaid programs primarily communicate with seniors and people with disabilities through printed materials, given the need for low-cost mass distribution and this population''s limited access to both in-person advice and the Internet. Is there a way to reach these highly vulnerable groups effectively and affordably?Research from the past 20 years shows that using strategies to adapt printed mass communication resources more closely to the needs of population subgroups can improve outcomes.^15–29 These design principles include matching readability more closely to users'' literacy levels and using “clear communication” formatting criteria,^33–35 incorporating culturally relevant concepts and graphics,^{4,17,19,23,36–40} and adapting rather than literally translating material into other languages.^{4,19,23,39,41}Such design principles are invaluable, but they can only approximate how real audiences use and react to health communication. For this reason, increasing emphasis is being placed on “participatory” or “user-centered” design—a structured approach that employs varied formative research methods to involve intended consumer and professional audiences as codevelopers of communication.^{4,19,25,42–45}Guidelines from the US Department of Health and Human Services and its centers, including the Centers for Disease Control and Prevention and the National Cancer Institute, recommend participatory design as a primary strategy to develop health communication.^{33–35,43,46} For the past 20 years, our center (Health Research for Action, www.uchealthaction.org) has leveraged such guidance to create large-scale mass communication materials by and for diverse populations.Two decades of studies confirm that when users participate in designing and testing communication, outcomes are more successful, including those for vulnerable groups.^{4,25,28,42,44,47–51} However, limited research is available about the detailed, iterative methods and steps involved in developing user-centered, materials-based mass communication—especially about how to adapt it for specific situations.In California, the Department of Health Care Services (DHCS) was concerned that fewer than 25% of Medicaid beneficiaries who were seniors or people with disabilities made active choices about health plans. By default, many beneficiaries could have plans ill suited for their health care needs. In 2006, the DHCS commissioned our center to use participatory processes to develop and test a guidebook about choosing and navigating health plans, intended for approximately 600 000 statewide Medicaid beneficiaries who were seniors and people with disabilities, in multiple language versions. Our objectives were to determine the (1) importance of participatory design in improving mass communication for diverse and vulnerable audiences, (2) methods to engage consumers and professionals in communication design and testing, (3) processes and outcomes of a project to create a user-designed guidebook for Medicaid beneficiaries, and (4) implications for health communication researchers and practitioners.     

Correlates of incarceration among young methamphetamine users in Chiang Mai, Thailand

Objectives. We examined correlates of incarceration among young methamphetamine users in Chiang Mai, Thailand in 2005 to 2006.Methods. We conducted a cross-sectional study among 1189 young methamphetamine users. Participants were surveyed about their recent drug use, sexual behaviors, and incarceration. Biological samples were obtained to test for sexually transmitted and viral infections.Results. Twenty-two percent of participants reported ever having been incarcerated. In multivariate analysis, risk behaviors including frequent public drunkenness, starting to use illicit drugs at an early age, involvement in the drug economy, tattooing, injecting drugs, and unprotected sex were correlated with a history of incarceration. HIV, HCV, and herpes simplex virus type 2 (HSV-2) infection were also correlated with incarceration.Conclusions. Incarcerated methamphetamine users are engaging in behaviors and being exposed to environments that put them at increased risk of infection and harmful practices. Alternatives to incarceration need to be explored for youths.Over the past decade, methamphetamine use has increased exponentially and reached epidemic proportions, particularly in North America¹ and Southeast Asia.² The methamphetamine epidemic has been concentrated among adolescents and young adults and has significant public health implications² because methamphetamine use has been associated with high-risk behaviors including multiple sexual partners, contractual sex, polydrug use, and aggression.^3,4Thailand has experienced a steadily increasing methamphetamine epidemic since 1996.⁵ By 2003, an estimated 3 500 000 Thais had ever used methamphetamines.⁶ In 1996, Thailand criminalized methamphetamines, treating the trafficking, possession, and use of methamphetamines with the same severity as heroin-related offenses.⁷ In 2003 the government began a “war on drugs” in an attempt to control the epidemic.^8,9 In combination, these events led to a doubling in the number of incarcerated individuals between 1996 and 2004.^7,10 In 2005, 64% of Thai inmates were drug offenders,¹¹ and in 2006, 75% of drug-related arrests and charges were related to methamphetamines.¹² Treatment for methamphetamine use is limited. Institutional management of methamphetamine users includes the use of rehabilitation centers, military-style boot camps, compulsory drug treatment centers, and prisons.¹¹A history of incarceration has been associated with negative health outcomes, including sexually transmitted infections (STIs) and blood-borne viruses, particularly syphilis,¹³ herpes,¹⁴ HIV,^10,15,16 hepatitis b (HBV),^17,18 and HCV.^18–21 The prevalence of these pathogens has been found to be much higher in prisons than in the general population.^22–26 Although these infections may be a result of a high-risk lifestyle leading to incarceration, it is also clear that the prison system exposes individuals to environments and behaviors that increase their risk of acquiring these infections, such as tattooing,^{10,18,21,27–29} unprotected sex as a result of limited condom availability,²⁷ and using shared needles to inject drugs.^27,30,31With so many young methamphetamine users entering the judicial system, it is important to understand the characteristics of this group so that appropriate public health interventions can be designed. Young methamphetamine users need to be diverted away from the judicial system to decrease high-risk behaviors that may impact their own well-being and that of the community.As part of a randomized controlled trial to reduce the risks associated with methamphetamine use among youths in Chiang Mai, Thailand, we investigated behavioral and viral correlates of incarceration among a sample of 1189 young adults aged 18 to 25 years.