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.     

Neighborhood Incarceration Rate and Asthma Prevalence in New York City: A Multilevel Approach

Objectives. We examined the association between neighborhood incarceration rate and asthma prevalence and morbidity among New York City adults.Methods. We used multilevel modeling techniques and data from the New York City Community Health Survey (2004) to analyze the association between neighborhood incarceration rate and asthma prevalence, adjusting for individual-level sociodemographic, behavioral, and environmental characteristics. We examined interactions between neighborhood incarceration rate, respondent incarceration history, and race/ethnicity.Results. The mean neighborhood rate of incarceration was 5.4% (range = 2.1%–12.8%). Neighborhood incarceration rate was associated with individual-level asthma prevalence (odds ratio [OR] = 1.06; 95% confidence interval [CI] = 1.03, 1.10) in unadjusted models but not after adjustment for sociodemographic characteristics (OR = 1.01; 95% CI = 0.98, 1.04). This association did not differ according to respondent race/ethnicity.Conclusions. Among New York City adults, the association between neighborhood incarceration rate and asthma prevalence is explained by the sociodemographic composition of neighborhoods and disparities in asthma prevalence at the individual level. Public health practitioners should further engage with criminal justice professionals and correctional health care providers to target asthma outreach efforts toward both correctional facilities and neighborhoods with high rates of incarceration.In the United States, asthma disproportionately affects non-White individuals living in urban areas and living in poverty.1 Because low socioeconomic status (SES) and racial/ethnic minority group status are closely intertwined with residence in an inner-city environment, characteristics of these inner-city neighborhoods have received much attention in the effort to explain patterns of asthma prevalence and morbidity.2,3 Epidemiological studies have highlighted the influence of poor housing, which may increase exposure to indoor allergens such as rat droppings4; greater likelihood of tobacco smoke exposure5; and overcrowding, which may predispose people to viral respiratory illness.2Because features of the physical environment do not completely explain observed patterns in asthma prevalence, features of the social environment have emerged as important asthma risk factors.6 Observational studies have demonstrated the association between asthma, psychological stress, and exposure to violent neighborhoods.7–9 For example, exposure to violence may influence an individual’s impulse control and risk-taking behavior, resulting in the adoption of coping behaviors, such as smoking, a known trigger for asthma.8–10 Psychological stress may be further compounded by the presence of overburdened or absent social supports and a perceived lack of control over one’s self or environment.6,11 Neighborhood-level constructs such as social capital and social cohesion have been linked to important health outcomes and may have an impact on asthma prevalence.12A natural but overlooked extension of this work is the potential impact of the criminal justice system on communities. Incarceration has a disproportionate impact on poor communities of color and has been linked to increased rates of asthma at the level of the individual.13–15 In addition to the effects on the individuals directly involved with the criminal justice system, neighborhood incarceration rates may play a role in shaping the social environment and thereby affect asthma prevalence. Exposure to high rates of neighborhood violence and crime often accompany exposure to incarceration. Recidivism and the risks of community reentry may further exacerbate this exposure.16 Incarceration has been shown to lead to long-term psychological stress for those affected17,18 and holds significant consequences for their families, creating further stress by removing social supports and weakening families.19 Individuals released from prison face legal barriers to employment, housing, public entitlements, and educational opportunities and various restrictions on political and social rights,20,21 further diminishing the social capital of their communities.Therefore, we sought to examine the association between neighborhood-level incarceration rates and several individual-level asthma outcomes. We hypothesized that increased neighborhood incarceration rates would be associated with increased asthma prevalence. Additionally, we proposed that increased neighborhood incarceration rates would be associated with increased asthma morbidity. We specifically examined factors potentially correlated with both neighborhood incarceration rate and asthma prevalence, such as SES, smoking, and poor housing conditions.     

Mother-Perceived Social Capital and Children’s Oral Health and Use of Dental Care in the United States

Objectives. We examined the association between mother-perceived neighborhood social capital and oral health status and dental care use in US children.Methods. We analyzed data for 67 388 children whose mothers participated in the 2007 National Survey of Children’s Health. We measured mothers’ perceived social capital with a 4-item social capital index (SCI) that captures reciprocal help, support, and trust in the neighborhood. Dependent variables were mother-perceived ratings of their child’s oral health, unmet dental care needs, and lack of a previous-year preventive dental visit. We performed bivariate and multivariable logistic regression analyses for each outcome.Results. After we controlled for potential confounders, children of mothers with high (SCI = 5–7) and lower levels (SCI ≥ 8) of social capital were 15% (P = .05) and about 40% (P ≤ .02), respectively, more likely to forgo preventive dental visits than were children of mothers with the highest social capital (SCI = 4). Mothers with the lowest SCI were 79% more likely to report unmet dental care needs for their children than were mothers with highest SCI (P = .01).Conclusions. A better understanding of social capital’s effects on children’s oral health risks may help address oral health disparities.It is well established that children living in families with low income and low educational attainment have poorer oral health and access to dental care than children with more affluent and educated families.1,2 Previous research has rigorously described oral health disparities by sociodemographic characteristics of individuals over the years, but only more recently have investigations begun to study the influence of larger contextual, environmental, and societal factors on the population’s oral health.3–6As part of this broader interest in the social determinants of health, the social connections that people have within their communities are receiving growing interest in public health research. This interest is rooted, in part, in the potential for people’s social connections to reduce health inequities through the mobilization of resources in society to better facilitate access to horizontally and vertically available social capital. Furthermore, social capital in the neighborhood may be particularly important for children’s well-being because the neighborhood is usually a central context for children’s psychosocial development. Children learn many of their social skills and values from within their neighborhood social networks.7 Especially in the absence of different kinds of support for children within the family,8 adult intervention on behalf of children in the neighborhood could serve as an important buffer against stressors and social risk factors embedded in the context of children’s lives.Although there is no consensus definition or a standardized approach to measuring social capital, it usually is thought of as consisting of some aspect of social structure and actions of individuals embedded in that structure.7 In social cohesion theory, social capital is conceptualized as the collective resources, such as trust, norms, and reciprocity, available to members of social groups, usually defined by geographic locales.9,10 This “social cohesion” school of social capital has been criticized for overlooking some aspects of social capital such as differences in residents’ abilities to access social capital and its potential negative effects on health.9,11 Nevertheless, greater social capital, measured by various features of social organizations in the community, has been linked to lower mortality and morbidity as well as self-reported better health outcomes.12 The hypothesized mechanisms are that social capital can influence health through (1) the diffusion of knowledge about health promotion, (2) maintenance of healthy behavioral norms or prevention of deviant health-related behaviors through informal social control, (3) promotion of access to local services and amenities, and (4) psychosocial processes that provide effective support, build self-esteem, and foster mutual respect.13It has been reported in the dental literature that a greater number of churches in neighborhood clusters was associated with the reduced severity of dental caries among low-income African American preschool children residing in Detroit, Michigan.3 Bramlett et al. previously examined various child-, family-, and neighborhood-level factors available in the 2003 National Survey of Children’s Health (NSCH) along with state-level factors from a variety of surveillance and census databases to test a multilevel conceptual model of determinants of young children’s oral health.5 Factors related to neighborhood cohesiveness and physical safety were correlated with parent-rated oral health status in children aged 1 through 5 years.5 Lower neighborhood social capital and community empowerment opportunities were also linked to higher rates of dental injuries14 and more dental caries among Brazilian adolescents.15Hypothesized sociobehavioral mechanisms linking social capital to health, empirical evidence on the association of social capital and general health, and initial evidence on the association of social capital–related variables and oral health strongly support further study of its potential impact on children’s oral health. It is evident from the literature that maternal oral health status, knowledge, and self-efficacy have a significant influence on children’s oral health behaviors and outcomes.16–19 In addition, gender may affect one’s perception of neighborhood social capital, patterns, and levels of social engagement and community participation.20,21 Little is known, however, about how social capital is perceived by female caregivers of children and how it might influence their behaviors and their children’s oral health. The purposes of this study were, therefore, to (1) describe the distribution of perceived social capital, using population-based data of self-reported neighborhood social cohesion among US mothers of children younger than 18 years, and (2) determine the association between neighborhood social capital and children’s oral health status and use of dental care.     

The Relationship Between Neighborhood Socioeconomic Characteristics and Physical Inactivity Among Adolescents Living in Boston,Massachusetts

Objectives. We sought to determine whether the socioeconomic environment was associated with no participation in physical activity among adolescents in Boston, Massachusetts.Methods. We used cross-sectional data from 1878 urban adolescents living in 38 neighborhoods who participated in the 2008 Boston Youth Survey, a biennial survey of high school students (aged 14–19 years). We used multilevel multiple regression models to determine the association between neighborhood-level exposures of economic deprivation, social fragmentation, social cohesion, danger and disorder, and students’ reports of no participation in physical activity in the previous week.Results. High social fragmentation within the residential neighborhood was associated with an increased likelihood of being inactive (odds ratio = 1.53; 95% confidence interval = 1.14, 2.05). No other neighborhood exposures were associated with physical inactivity.Conclusions. Social fragmentation might be an important correlate of physical inactivity among youths living in urban settings. Interventions might be needed to assist youths living in unstable neighborhoods to be physically active.Physical activity is important to the growth and development of children and adolescents.1,2 Physical activity is associated with a decreased risk for overweight and obesity, type 2 diabetes, and other chronic morbidities.1–3 Recent recommendations for physical activity among children and adolescents aged 6 to 17 years include at least 1 hour a day of moderate to vigorous physical activity.3 However, research indicates that only 8% of American adolescents meet these recommendations.4 In 2011, in the United States, 13.8% of students had not participated in at least 60 minutes of physical activity that increased their heart rate and made them breathe hard some of the time on any day during the 7 days before the survey.5 A better understanding of factors that may influence physical inactivity is warranted.Although individual and familial characteristics are known to be determinants,6–12 growing evidence suggests that physical activity is associated with the socioeconomic environment.13–17 The residential neighborhood, where children spend large portions of their time, may influence their health behaviors.Socioeconomic features of the neighborhood have been shown to be associated with adolescent physical activity. Area-level economic deprivation, which is a collective measure of average socioeconomic position of populations living within a particular area,13,17,18 is one such neighborhood characteristic that may influence health behavior. Economic deprivation may be an indication of the distribution of environmental resources and exposures at the area level. Previous work has shown economic deprivation as a significant predictor of physical activity levels.13,17Social fragmentation, a dimension of the socioeconomic environment that is conceptually distinct from economic deprivation, is linked to the concept of anomie, which Emile Durkheim defined as a state of normlessness,19 or the breakdown of social bonds between individuals and their communities, with fragmentation of social identity and rejection of self-regulatory values.19 Instead of being a proxy for poverty, social fragmentation is an indication of rapid population turnover, single-person households, and rented tenancy, which are thought to be related to greater residential instability. Researchers have used census variables, such as the proportion of residents renting, to define specific social conditions. It is hypothesized that social fragmentation leads inhabitants to feel disconnected with their neighbors and their community. This might influence parents to disallow their youths to participate in forms of physical activity such as active transportation to school or work. In a previous study, we found an association between social fragmentation and walking for exercise among mothers of children who are at risk for obesity.20Other area-level characteristics that have been shown to be associated with physical activity behavior include social cohesion,14 disorder,15 and neighborhood safety.15,21 Social cohesion has been defined as the connectedness and solidarity among individuals and groups in society.22 Neighborhood disorder is composed of both social and physical disorder.23 Social disorder involves the presence of threatening individuals or groups, and physical disorder is defined by the deterioration of urban landscapes.23 Neighborhood safety has been measured objectively (e.g., crime rates24–26) and by respondents’ perception of their neighborhoods.15,27–31In the present study, we tested potential pathways through which neighborhood socioeconomics could influence youths’ physical inactivity. First, we examined the potential mediation of the association between each of the neighborhood socioeconomic characteristics and physical inactivity via perceptions of neighborhood safety. For example, a neighborhood that is characterized by high social fragmentation, low social cohesion, high crime rates, high poverty, and high physical disorder might elicit feelings of fear and perceptions of lack of safety. As a result, parents may be less likely to allow their children to use active modes of transportation or play outside. This is supported by numerous studies showing that youths who perceive their neighborhoods to be unsafe are more likely to be physically inactive.15,32,33 A second possible pathway is represented by neighborhood differences in the level of individual-level social cohesion; i.e., communities with high levels of social fragmentation or high economic deprivation are also characterized by lower levels of cohesion between residents. In turn, an erosion of social cohesion is associated with physical inactivity because residents lack the effective means for the transmission of norms that encourage exercise among youths,34,35 or they lack the collective efficacy to maintain the local physical infrastructure for physical activity (e.g., parks and playgrounds).36The additive role of independent area-level socioeconomic factors has not been fully investigated. Also, the mechanisms in which socioenvironmental characteristics influence physical activity need to be better understood. Therefore, the objective of this investigation was to determine the association between neighborhood economic deprivation, social fragmentation, safety, and social disorder on physical inactivity among a sample of public high-school students in Boston, Massachusetts. We also investigated perception of neighborhood safety and student-reported social cohesion as mediators between socioeconomic characteristics and physical activity.     

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.     

Influences of Physical and Social Neighborhood Environments on Children's Physical Activity and Obesity

Objectives. We investigated the association between physical and social neighborhood environments and fifth-grade students’ physical activity and obesity.Methods. We collected data on 650 children and their primary caregivers during phase 1 of Healthy Passages, a multisite, community-based, cross-sectional study of health risk behaviors and health outcomes in children. We conducted independent systematic neighborhood observations to measure neighborhood physical characteristics, and we analyzed survey data on social processes. We modeled children''s physical activity and obesity status with structural equation models that included latent variables for the physical and social environments.Results. After we controlled for children''s sociodemographic factors, we found that a favorable social environment was positively associated with several measures of physical activity and that physical activity was negatively associated with obesity in these children. Physical environment was not significantly associated with physical activity.Conclusions. Our findings suggest that neighborhood social factors as well as the physical environment should be considered in the development of health policy and interventions to reduce childhood obesity.The prevalence of childhood obesity in the United States has gone up dramatically in recent decades: overweight prevalence has increased from 6.5% in 1976 to 1980 to 18.8% in 2003 to 2004 among children aged 6 to 11 years.¹ Childhood obesity is worrisome not only because it can cause immediate morbidity, but also because the physical inactivity and poor dietary habits associated with obesity in childhood can persist into adulthood.²Several factors at both the individual and contextual levels might contribute to childhood obesity. At the individual level, considerable differences exist in childhood obesity and physical activity levels by socioeconomic status, race/ethnicity, and gender.^3–5 For example, Mexican American boys and Black girls are more likely than are other children to be overweight.⁶ Adolescent activity levels and correlates of physical activity also vary by gender^7,8 and race/ethnicity.⁹At the contextual level, the effects of parenting, the home environment, and developmental and psychological factors on diet, obesity, and physical activity have received significant attention.^10–14 Recently, the importance of the broader social and physical environment on obesity has been recognized.^15–17Researchers have investigated the direct and indirect effects of neighborhood environments on physical activity among adults,^18,19 but few studies have focused on youths.^17,20 In addition, most of this research has focused on the influence of neighborhood physical environment on physical activity. The influence of neighborhood social environment has received less attention. Research has linked only a few aspects of the social environment, specifically neighborhood safety and cohesion, to physical activity and obesity.For our theoretical framework, we drew on the Social Determinants of Health and Environmental Health Promotion model,^21,22 which describes how fundamental, intermediate, and proximate socioeconomic processes interacting with the built environment determine population health. We focused on specific relationships between intermediate factors (the physical environment), proximate factors (the social environment as perceived by residents and physical activity), and health (obesity). The social environment, which includes social integration and stressors such as safety, was included as a proximate factor even though it is a community-level factor because it is measured as perceived at the personal level. We were unable to include fundamental factors, such as economic inequalities and residential segregation. Figure 1 depicts the relationships we studied.Open in a separate windowFIGURE 1Theoretical model for childhood obesity.Note. BMI = body mass index. Arrows indicate direction of influence.^aData obtained from Systemic Social Observations.^bData obtained from questionnaire.^cData obtained from measurements.A large amount of literature on the physical environment, physical activity, and obesity addresses several aspects of the neighborhood physical environment. Studies that used ecological models²³ showed that several aspects of the physical environment had an effect on obesity in adults.²⁴ For example, residents of a mixed-land-use neighborhood (i.e., both residential and commercial) or a high-density neighborhood were likely to be more active because of opportunities to walk to stores and other destinations. However, the empirical evidence on land use and density and adult obesity is mixed.^25–31 Little is known about the influence of land use and density on children''s physical activity. One of the few studies on this subject did not find a positive relationship between residential density and children''s physical activity.³² One study found that children living in areas with high population density were more likely to walk or bike to school.³³Traffic and physical disorder (graffiti and litter) in the physical environment are likely to discourage physical activity by increasing perceived danger on the street and public places and reducing a sense of neighborhood social cohesion that might attract outdoor or group activity. Among children, research showed that less traffic and the presence of sidewalks in good condition were associated with more walking or biking to school and other destinations.^8,34,35 Although physical disorder has been associated with less physical activity and more obesity among adults,³⁶ one study found no such association in children.³⁷The neighborhood social environment may be at least as important to physical activity as the physical environment, but its role has not been adequately studied. Previous research on neighborhood social environments focused primarily on safety. Inadequate neighborhood safety is likely to curb outdoor activities and has repeatedly been correlated with low physical activity levels among schoolchildren.^37–40 In qualitative research on barriers to physical activity, middle-school students reported safety concerns as a major barrier.^41,42 However, Sallis et al. found no links between parents’ perceptions of neighborhood safety and physical activity in fourth- and fifth-grade students,⁴³ and another study found a negative association between girls’ physical activity and parents’ perceptions of park safety.⁴⁴Social cohesion has been shown to influence health at the neighborhood level.⁴⁵ Neighborhood social cohesion might also influence young people''s physical activity levels through several potential pathways. Increased social contact and social exchange among members of a community may lead to the adoption of more-healthful behaviors and a culture favoring fitness. The availability of a network of parents who know each other and who are willing to watch out for neighborhood children (collective socialization of children) could facilitate enforcement of healthful norms, including support for physical activity, as well as increase awareness of programs for youths. Neighborhood collective efficacy, a measure of willingness of neighbors to come together for the common good, facilitates collective action, including improving availability and access to recreational resources for children.⁴⁶Some studies have found that neighborhood cohesion influences physical activity. Social capital at the county level was positively associated with physical activity levels,⁴⁷ and neighborhood social cohesion was associated with increased levels of physical activity among older adults.⁴⁸ Collective efficacy was associated with lower body mass index (BMI; weight in kilograms divided by height in meters squared) among adults and adolescents.⁴⁹ Molnar et al. found that lower social disorder was associated with more recreational activity among children and adolescents.³⁷We investigated the association between physical and social neighborhood environment and fifth-grade students’ physical activity and obesity through multiple measures of neighborhood physical characteristics and social processes. We measured neighborhood physical factors with independent systematic neighborhood observations and social processes with survey data.We hypothesized that, after we controlled for children''s sociodemographic characteristics (Figure 1), the physical environment (measured by more traffic, more physical disorder, low residential density, and primarily residential neighborhood) would be negatively associated and the social environment (measured by safety and social cohesion) would be positively associated with children''s physical activity levels and that these levels would correlate with childhood obesity.     

Neighborhood Blight,Stress, and Health: A Walking Trial of Urban Greening and Ambulatory Heart Rate

We measured dynamic stress responses using ambulatory heart rate monitoring as participants in Philadelphia, Pennsylvania walked past vacant lots before and after a greening remediation treatment of randomly selected lots. Being in view of a greened vacant lot decreased heart rate significantly more than did being in view of a nongreened vacant lot or not in view of any vacant lot. Remediating neighborhood blight may reduce stress and improve health.Vacant lots are abandoned parcels of urban land that signal blight, with overgrown vegetation, trash dumping, and other illegal activities. Exposure to these lots is associated with negative health outcomes.1–7 Although complex social and economic factors broadly explain the relationship between neighborhood blight and health, limited experimentation with biological outcomes has been conducted in real-world settings.8The body’s stress response is a reasonable biological pathway for understanding the impact of neighborhood blight on health.9,10 Although this response is protective in acute situations, permanent downstream inflammatory changes and dysregulation of cardiovascular, neurological, and endocrine systems accumulate over a lifetime for persons repeatedly exposed to stressors in their neighborhood surroundings.11–16 Basic structural improvements to blighted neighborhood environments, such as “greening” vacant lots, offers a promising and sustainable, yet underused, solution to such stressors.5,17We examined the microspatial impact of neighborhood physical conditions during short neighborhood walks by experimentally testing a specific condition (the remediation of blighted vacant land) to a dynamic biological marker (heart rate).18–21 Using georeferenced heart rate monitoring in an experimental study of an individual’s native environment is a unique approach to field studies of neighborhood blight on acute stress.22     

Neighborhood Ethnic Composition,Spatial Assimilation,and Change in Body Mass Index Over Time Among Hispanic and Chinese Immigrants: Multi-Ethnic Study of Atherosclerosis

Objectives. We investigated relations between changes in neighborhood ethnic composition and changes in body mass index (BMI) and waist circumference among Chinese and Hispanic immigrants in the United States.Methods. We used Multi-Ethnic Study of Atherosclerosis data over a median 9-year follow-up (2000–2002 to 2010–2012) among Chinese (n = 642) and Hispanic (n = 784) immigrants aged 45 to 84 years at baseline. We incorporated information about residential moves and used econometric fixed-effects models to control for confounding by time-invariant characteristics. We characterized neighborhood racial/ethnic composition with census tract–level percentage Asian for Chinese participants and percentage Hispanic for Hispanic participants (neighborhood coethnic concentration).Results. In covariate-adjusted longitudinal fixed-effects models, results suggested associations between decreasing neighborhood coethnic concentration and increasing weight, although results were imprecise: within-person BMI increases associated with an interquartile range decrease in coethnic concentration were 0.15 kilograms per meters squared (95% confidence interval [CI] = 0.00, 0.30) among Chinese and 0.17 kilograms per meters squared (95% CI = –0.17, 0.51) among Hispanic participants. Results did not differ between those who did and did not move during follow-up.Conclusions. Residential neighborhoods may help shape chronic disease risk among immigrants.More than 40 million immigrants reside in the United States, 81% of whom emigrated from Latin America or Asia.1 Not only is the US foreign-born population increasing, but also is the proportion of immigrants who have resided in the United States for a long period of time. An estimated 39% of immigrants had resided in the United States for 20 years or more as of 2010, and this proportion is projected to surpass 50% by 2030.2 This demographic shift has important ramifications for population health and the health service burden because, among immigrants, both cardiovascular disease (CVD) risk and weight, a key CVD risk factor, tend to increase with longer length of stay in the United States, above and beyond the influence of age.3–7Although explanations for immigrant health patterns often focus on how individual-level health behaviors change across time to align with those of the receiving US culture,5 broader factors may also be important. For example, the neighborhoods in which immigrants reside may contribute to weight changes associated with tenure in the United States. Recent immigrants tend to initially settle in immigrant enclaves, neighborhoods with large numbers of other immigrants of the same country of origin or ethnicity (high coethnic concentration). However, over time, many immigrants move out of immigrant enclaves to neighborhoods with lower proportions of other coethnics or immigrants.8 Classical sociological spatial assimilation theory posits that this process of residential spatial assimilation serves as one important dimension of assimilation into the dominant US culture.8–10 Although the theory does not explicitly state how health would be affected, it implies changes in exposures to neighborhood-level social and physical characteristics that could influence health.Weight-related physical and social resources in neighborhoods with large immigrant populations may differ from those with fewer immigrants.9,11–13 For example, businesses in immigrant enclaves often provide services or products specific to their ethnic market, including food stores.9,12 Empirical findings on whether the food environment in immigrant enclaves is healthier than in other neighborhoods are inconsistent. Higher neighborhood proportions of Hispanic and Asian residents have been associated with higher numbers of convenience stores and fast-food restaurants—sources of unhealthy foods—but also with higher numbers of nonchain supermarkets and grocery stores, which may contribute to a healthier and more culturally appropriate food environment.14–16 Chinese and Hispanic participants living in immigrant enclaves have reported better availability of healthy food than participants living in other neighborhoods.13 Other aspects of the built environment that are relevant to weight, such as how conducive to walking it is, may also vary by neighborhood ethnic composition.13 Aside from physical resources, the presence of other immigrants in a neighborhood may provide psychosocial benefits by buffering residents against discrimination or by providing access to larger social networks,11,17 but the empirical evidence is again inconsistent.13 These neighborhood differences may in turn affect behavioral and psychosocial determinants of weight.18–23 For example, higher immigrant and ethnic concentration has been associated with differences in diet and physical activity,13,24–27 as well as with better mental health and less perceived discrimination,17,28–35 all of which could have an impact on weight.Few studies have examined associations between neighborhood ethnic composition and weight among immigrants.36–41 Results have varied depending on the immigrant group examined or the composition measure used (e.g., percentage foreign-born, percentage Hispanic).36–39 Moreover, the majority of previous evidence is cross-sectional and cannot investigate patterns of residential mobility, including spatial assimilation, that may affect weight over time.42 Longitudinal studies are therefore crucial for understanding how neighborhood context may affect weight over time in immigrants.3 Despite substantial theoretical and empirical sociological research dedicated to characterizing residential patterns among immigrants, there is little research in either sociology or public health that explicitly examines the implications of these patterns for health.We used longitudinal econometric fixed-effects models to investigate whether changes in neighborhood ethnic composition were related to changes in body mass index (BMI; defined as weight in kilograms divided by the square of height in meters) and waist circumference (WC) over a median follow-up of 9 years among a cohort of Chinese and Hispanic immigrants in the United States. Because fixed-effects models rely only on intraindividual variability, and therefore tightly control for all time-invariant individual-level characteristics, this approach can reduce the likelihood that observed results are confounded.43 We hypothesized that decreases in neighborhood coethnic concentration would be related to increases in BMI and WC in our sample. We also hypothesized that immigrants who spatially assimilated during follow-up (i.e., who moved to a neighborhood with lower coethnic concentration, as opposed to staying in the same residence with their neighborhood changing around them) would experience greater increases in BMI and WC. Our second hypothesis was driven by the idea that, consistent with classical spatial assimilation theory, spatial assimilation may denote a greater likelihood of adopting less healthy behaviors associated with the dominant US culture.     

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.     

Revisiting the Role of the Urban Environment in Substance Use: The Case of Analgesic Overdose Fatalities

Objectives. We examined whether neighborhood social characteristics (income distribution and family fragmentation) and physical characteristics (clean sidewalks and dilapidated housing) were associated with the risk of fatalities caused by analgesic overdose.Methods. In a case-control study, we compared 447 unintentional analgesic opioid overdose fatalities (cases) with 3436 unintentional nonoverdose fatalities and 2530 heroin overdose fatalities (controls) occurring in 59 New York City neighborhoods between 2000 and 2006.Results. Analgesic overdose fatalities were less likely than nonoverdose unintentional fatalities to have occurred in higher-income neighborhoods (odds ratio [OR] = 0.82; 95% confidence interval [CI] = 0.70, 0.96) and more likely to have occurred in fragmented neighborhoods (OR = 1.35; 95% CI = 1.05, 1.72). They were more likely than heroin overdose fatalities to have occurred in higher-income (OR = 1.31; 95% CI = 1.12, 1.54) and less fragmented (OR = 0.71; 95% CI = 0.55, 0.92) neighborhoods.Conclusions. Analgesic overdose fatalities exhibit spatial patterns that are distinct from those of heroin and nonoverdose unintentional fatalities. Whereas analgesic fatalities typically occur in lower-income, more fragmented neighborhoods than nonoverdose fatalities, they tend to occur in higher-income, less unequal, and less fragmented neighborhoods than heroin fatalities.Rates of fatal overdoses caused by analgesic opioids have increased dramatically in the United States, particularly over the past 5 years.1–3 The prevalence of nonmedical analgesic drug abuse is second only to that of marijuana abuse, and currently the number of fatal overdoses attributed to opioid analgesics, such as oxycodone, hydrocodone, and codeine, is greater than the number attributed to heroin and cocaine combined.4Urban areas have long been associated with elevated risks of substance abuse and subsequent mortality from unintentional drug poisoning. From 1997 to 2002, the number of overdose deaths involving opioid analgesics increased 97% in urban areas during a time when the rate of overdose from all drugs increased 27%.5 From a public health burden standpoint, understanding the determinants of analgesic overdose mortality in large urban areas is critical to help stem the tide of mortality from analgesics, as all available data suggest that analgesic overdose mortality in these areas will continue to increase in the coming years.6Extant epidemiological research in the area has predominantly been concerned with the role of individual characteristics in explaining the prevalence of analgesic overdose throughout the United States.5,7–12 Analgesic opiate overdose decedents have been reported to be primarily White, male, and adult (ranging in age from 25 to 54 years) and to exhibit a high prevalence of concurrent psychotherapeutic drug use.5,7–10 However, several organizing frameworks in the field (principally rooted in ecosocial theory) suggest that environments operate jointly with individual factors to influence the risk of substance use.13–15In addition to individual characteristics such as psychiatric morbidity, genetic vulnerability, gender, and age,16–20 these frameworks suggest that interconnected components of influence shape drug use. These components include social policies and regulations that affect the allocation of social and health resources21–26; social and physical features of the neighborhood environment that structure the availability of drugs, influence norms around use, and generate sources of stress that contribute to drug use13,14,27–37; and interpersonal characteristics, such as social support and social networks, that mediate the relationship between the neighborhood environment and drug use.28,31,38–42 Despite this conceptual orientation, few studies have attempted to provide an understanding of the contextual factors that may explain the geographic distribution of analgesic overdose in an urban environment.Of particular interest in the urban context are the features of neighborhoods that can shape drug overdose. Established conceptual frameworks suggest 2 such features: primary determinants of infrastructure, employment, education, and health care resources, including residential segregation, income distribution, and neighborhood deprivation, and secondary determinants that are consequences of these fundamental conditions and may mediate their impact on drug use, including the quality of the built environment, social norms around drug use, and family fragmentation.15 Drawing on this framework, we examined 3 features of the neighborhood environment that have been previously linked with drug overdose: income distribution, quality of the built environment, and family fragmentation.35,37,43,44First, neighborhood income distribution has been consistently linked to drug abuse or overdose fatalities.27,35,44,45 For example, research has shown that in New York City neighborhoods with more unequal income distributions, drug overdoses are more likely than other causes to lead to unintentional deaths.35,44 The erosion of social capital and greater mistrust of authority found in more unequal neighborhoods may lead to a greater reluctance to seek medical help in cases of overdose.46 Furthermore, underinvestment in health and social resources could contribute to longer response times on the part of paramedics and limited access to substance abuse treatment. It is plausible that these same processes may drive a higher risk for analgesic opiate overdose in more unequal neighborhoods.Second, studies have shown a positive association between poor quality of the built environment (dilapidated buildings, vandalism of public property, and littering) and risk of drug overdose.43,44,46 Deterioration of the built environment has been linked with higher levels of distress.47 In turn, people with higher levels of distress may be more vulnerable to drug abuse and overdose than people low in distress.48,49 Moreover, reduced social capital reflected in a vandalized and littered built environment may discourage neighborhood residents from interacting with each other and from developing relationships that would enable to them to intervene to prevent the development of drug distribution networks in the neighborhood.50Third, family fragmentation (e.g., a high prevalence of divorced, separated, or single-parent families) represents a social mechanism through which neighborhoods may influence analgesic overdose. Disruption of the neighborhood social fabric may manifest in personal forms of disorganization within adult relationships.51,52 Studies of crime have shown that family disruption influences the collective ability of local residents to promote adult and youth conformity to local norms and laws.53–55 A high prevalence of fragmented families in a neighborhood reduces the neighborhood’s ability to monitor young people and respond to delinquency and crime.56 Such disorganization may have direct consequences in terms of access to and consumption of analgesics, given that the formation of drug-selling and drug-consuming networks may be more likely in neighborhoods where residents do not monitor delinquent activity consistently.57Furthermore, disrupted families may be less likely to exert informal control over the abuse of analgesics by other family members.57 Given that consumption of analgesics occurs most frequently at home,58 the absence of a family support and control net is particularly problematic.This study had 2 aims. First, we examined the roles that the 3 features of the neighborhood social and physical environment just described—income distribution, the quality of the built environment, and family fragmentation—play in the risk of unintentional death from analgesic overdose in New York City. Second, we examined whether analgesic opiate overdoses in New York City are driven by distinct neighborhood factors than heroin overdose, the historically most prevalent form of illicit opiate overdose in urban areas.59,60     

Neighborhood Characteristics and Change in Depressive Symptoms Among Older Residents of New York City

Objectives. We investigated the relationship between the depressive symptoms of older adults over time and the characteristics of the neighborhoods in which they live.Methods. We surveyed a random sample of 1325 New York City residents aged 50 years or older in 2005 and conducted 808 follow-up interviews in 2007. We assessed the compositional characteristics of the respondents'' neighborhoods at a census-tract level and determined the relationships between these characteristics and changes in respondents'' depressive symptoms.Results. In multivariable models that adjusted for individual-level covariates including income, a range of neighborhood characteristics predicted worsening depressive symptoms. Factor analysis suggested that these characteristics operated in 3 clusters: neighborhood socioeconomic influences, residential stability, and racial/ethnic composition, with positive neighborhood socioeconomic influences being significantly protective against worsening symptoms. Life stressors, personality trait neuroticism, African American race, and daily baseline contact with social networks were also associated with worsening symptoms.Conclusions. An older adult''s neighborhood of residence is an important determinant of his or her mental health. Those making efforts to improve mental health among the elderly need to consider the role of residential context in improving or impairing mental health.Depression is an important cause of morbidity in the general community.¹ The prevalence of depression is high among elderly persons, and longitudinal studies have found modest increases in depressive symptoms with age.^2–4 The incidence of depression peaks in early adult life, but there appears to be a secondary peak in incidence among people in their 50s, suggesting that the transition to older age may present specific risks for depression.⁵ Depression is associated with significant disability among older adults and may place their functional independence at risk.⁶ At least 1 longitudinal study has also suggested that older African Americans may be at increased risk of symptoms of depression compared with older White adults.⁷Although a number of individual-level factors are known to increase the risk of depression,^8–10 it has long been thought that the physical and social environments in which people live may also influence their mental health.^11–13 The environment may play a particularly important role in the mental health of older adults, who, compared with younger adults, are more likely to spend time in their neighborhood of residence, more likely to suffer from disabilities that may be exacerbated by their environments,¹⁴ and are more vulnerable to threats to their safety.^15–17A number of theories have been proposed to explain this association between neighborhood characteristics and depression. Researchers have drawn on systemic theory to propose that neighborhoods characterized by higher levels of poverty and residential instability have lower levels of social cohesion and lower levels of control over deviant social networks.^18,19 The concomitant lack of social order may contribute to low levels of trust, which would impede collaborative efforts to control crime and reduce neighborhood disorder.²⁰ High levels of crime may generate higher levels of fear and stress, as could the deteriorating building conditions and high levels of physical disorder associated with disadvantaged neighborhoods.^20,21 In contexts of social isolation and limited social organization, residents may not benefit from the social networks necessary to buffer them from the stressors they face on a daily basis.²²These theories about the influence of the neighborhood context on collective and individual sources of stress agree with the “differential vulnerability” hypothesis and with social stress theory, both of which posit that environments can influence health by increasing the likelihood of personal stress events such as unemployment or traumatic events, or by providing resources to cope with such stressors.^23–26 Studies using multilevel analytic methods that can account for both individual-level and neighborhood-level effects suggest that neighborhood-level characteristics such as affluence, disadvantage, inequality, and residential stability have a significant impact on physical health, even after accounting for individual-level factors.^27–30 However, research into their possible influence on mental health has been more limited.Cross-sectional studies using multilevel approaches have suggested that symptoms of depression are more prevalent in residents of disadvantaged neighborhoods^31–33 and that this association may be stronger in neighborhoods having less residential turnover^34,35 or higher population density.³⁶ Similar associations have been observed among older adults, for whom living in a neighborhood that is poor or has few elderly people has been associated with higher levels of depressive symptoms, after accounting for individual vulnerabilities.³⁷ The presence of stress-buffering support systems has been associated with lower levels of depression in cross-sectional research, whereas low levels of social support in neighborhoods with high social isolation were related to higher depression levels.^38,39 However, other research has failed to replicate these findings.⁴⁰ Furthermore, the cross-sectional nature of this research means that even positive studies cannot exclude the possibility that the observed relationships simply reflect a tendency for depressed individuals to become disadvantaged or to live in disadvantaged neighborhoods.Longitudinal research can better explore the causal mechanisms behind these relationships, but there have been few prospective studies in this field. A study of individuals who were screened for an HIV prevention intervention found that perceptions of neighborhood characteristics predicted change in depressive symptoms 9 months later.⁴¹ The Alameda County Study found that living in a high-poverty area was associated with worse health status and more symptoms of depression; however, this association was lost when all individual-level covariates were included in multivariable analysis.⁴² In previous research conducted by members of our own team, we identified a significant association between incident depression and neighborhoods classified as low socioeconomic status, even after adjusting for individual income, adverse life events, and educational status.⁴³ This kind of prospective research, although suggestive, has often been weakened by reliance on perceived neighborhood characteristics, limitations of the measures used, or absence of information on possible confounders.To overcome these limitations, we examined the relationship between characteristics of the neighborhood of residence of older adults and symptoms of depression using longitudinal data from the New York City Neighborhood and Mental Health in the Elderly Study (NYCNAMES). We hypothesized that neighborhood socioeconomic status may either exacerbate or ameliorate the stressors confronting participants, thereby influencing levels of depression symptoms over the study period, even after accounting for key individual-level factors. We used information from the 2000 US Census to characterize neighborhoods, and we aggregated these characteristics into dimensions that might shed light on the mechanisms underlying observed relationships.     

Neighborhood Context and Infant Birthweight Among Recent Immigrant Mothers: A Multilevel Analysis

Objectives. We compared the influence of the residential environment and maternal country of origin on birthweight and low birthweight of infants born to recent immigrants to urban Ontario.Methods. We linked delivery records (1993–2000) to an immigration database (1993–1995) and small-area census data (1996). The data were analyzed with cross-classified random-effects models and standard multilevel methods. Higher-level predictors included 4 independent measures of neighborhood context constructed by factor analysis and maternal world regions of origin.Results. Births (N = 22 189) were distributed across 1396 census tracts and 155 countries of origin. The associations between neighborhood indices and birthweight disappeared after we controlled for the maternal country of origin in a cross-classified multilevel model. Significant associations between world regions and birthweight and low birthweight persisted after we controlled for neighborhood context and individual characteristics.Conclusions. The residential environment has little, if any, influence on birthweight among recent immigrants to Ontario. Country of origin appears to be a much more important factor in low birthweight among children of recent immigrants than current neighborhood. Findings of neighborhood influences among recent immigrants should be interpreted with caution.Socioeconomic disparities in birth outcomes are well documented,^1–3 even in countries with universal access to health care,^4,5 such as Canada. An increasing body of literature, including several multilevel studies, suggests that context affects birth outcomes, particularly neighborhood influences in predominantly urban areas.^6–16 Little is known, however, about neighborhood influences among immigrants.^15,17–19There are theoretical and practical reasons to explore this issue. It has been suggested that exposure to neighborhoods may take some time to affect human health.²⁰ Even if neighborhood influences are detected among the offspring of recent immigrant women exposed to neighborhoods during their entire pregnancy, a life-course perspective suggests that early life experiences and premigration exposures may still affect birth outcomes of migrants in the new country.^19,21 The maternal country of origin thus constitutes another relevant context to be considered when analyzing differences in birthweight among recent immigrants, because substantial differences in birthweight have been reported by geographical region and nativity status.^22–24 It is important to clarify the role of the pre- and postmigration exposures, because the proportion of live births to immigrant women has been showing an upward trend during recent decades in several industrialized countries.^24–27We compared the influence of the residential environment at the time of delivery with that of the maternal country of origin on birthweight and the proportion of low birthweights among infants born to women who recently immigrated to Canada and settled in Ontario census metropolitan areas from 1993 to 1995. We hypothesized that the maternal country of origin would have a greater effect on birthweight than would the residential environment in which immigrants currently resided in urban Ontario.     

Association of Perceived Neighborhood Safety on Body Mass Index

Objectives. We sought to determine whether there is an association between perceived neighborhood safety and body mass index (BMI), accounting for endogeneity.Methods. A random sample of 2255 adults from the Los Angeles Family and Neighborhood Survey 2000–2001 was analyzed using instrumental variables. The main outcome was BMI using self-reported height and weight, and the main independent variable was residents’ report of their neighborhood safety.Results. In adjusted analyses, individuals who perceived their neighborhoods as unsafe had a BMI that was 2.81 kg/m² (95% confidence interval [CI] = 0.11, 5.52) higher than did those who perceived their neighborhoods as safe.Conclusions. Our results suggest that clinical and public health interventions aimed at reducing rates of obesity may be enhanced by strategies to modify the physical and social environment that incorporate residents’ perceptions of their communities.Obesity is a major public health problem^1–5 that contributes to poor quality of life; increased incidence of diabetes, cardiovascular disease, and other chronic conditions; and higher mortality rates.⁵ During the last decade, population-based strategies to reduce obesity have emphasized modification of physical and social environments, which may be particularly important in disadvantaged communities. Low neighborhood socioeconomic status (SES),⁶ a higher proportion of Black and Latino residents,^7–10 barriers in the built environment (e.g., fewer places to walk),^11,12 lack of access to supermarkets or fresh fruits and vegetables,^6,13,14 and a higher density of fast food restaurants¹⁵ are all characteristics of residential environments associated with obesity. Research also suggests that low levels of collective efficacy (a perception of mutual trust and willingness to help each other)¹⁶ are associated with adolescent obesity. However, the mechanisms through which neighborhood social, economic, and physical characteristics lead to weight gain and obesity are not well characterized.Perceived neighborhood safety is a mechanism through which neighborhood characteristics may influence obesity. Residence in a neighborhood perceived as unsafe may contribute to obesity in a number of ways, including increased secretion of stress hormones,^17–19 lower rates of walking or other outdoor physical activity,^20–28 and higher rates of stress-related eating.^29–32 Perceived safety may reflect the physical, social, and resource characteristics of neighborhoods. For example, residents may perceive a neighborhood to be unsafe if supermarkets and retailers that sell fresh fruits and vegetables are unwilling to locate in their neighborhoods, or if fast food restaurants and stores that sell low-cost, calorie-dense foods tend to locate in their neighborhoods.^33–35 Yet, the limited literature on relations between perceived safety and body weight is mixed. One study found that mothers with young children, residing in large cities, and perceiving their neighborhoods as unsafe were more likely to be obese,³⁶ and another study found no association between perceived safety and obesity.³⁷ Similarly, in the larger body of literature on neighborhood safety and physical activity, some studies found an association of perceived neighborhood safety with physical activity levels,^20–26 although other analyses showed no such relationship,^38–42 suggesting a more complex etiology.We hypothesized that 1 reason for the inconsistent findings in these previous analyses—all of which were cross-sectional—is endogeneity bias, that is, the possibility that the findings from these studies may have been influenced by either reverse causality^36,43 or unmeasured neighborhood or individual characteristics influencing both perceived neighborhood safety and obesity. For example, reverse causality may occur if larger individuals, believing nobody would attack them because of their size, feel safer, or if larger individuals, being less agile and less physically fit and believing they cannot protect themselves, feel less safe. To address the possibility of endogeneity from reverse causality or unmeasured neighborhood or individual characteristics, we studied the association between perceived neighborhood safety and obesity in a population-based, geographically sampled cohort of residents in Los Angeles County, California. We used 2-stage least squares regression, a special case of an instrumental variables analysis that is a method developed to produce statistically consistent estimates when the covariate of interest is potentially endogenous. To our knowledge, no studies to date have used instrumental variables analysis to assess the relationship between neighborhood safety and obesity.     

Racial/Ethnic and Socioeconomic Differences in Short-Term Breast Cancer Survival Among Women in an Integrated Health System

Objectives. We examined the combined influence of race/ethnicity and neighborhood socioeconomic status (SES) on short-term survival among women with uniform access to health care and treatment.Methods. Using electronic medical records data from Kaiser Permanente Northern California linked to data from the California Cancer Registry, we included 6262 women newly diagnosed with invasive breast cancer. We analyzed survival using multivariable Cox proportional hazards regression with follow-up through 2010.Results. After consideration of tumor stage, subtype, comorbidity, and type of treatment received, non-Hispanic White women living in low-SES neighborhoods (hazard ratio [HR] = 1.28; 95% confidence interval [CI] = 1.07, 1.52) and African Americans regardless of neighborhood SES (high SES: HR = 1.44; 95% CI = 1.01, 2.07; low SES: HR = 1.88; 95% CI = 1.42, 2.50) had worse overall survival than did non-Hispanic White women living in high-SES neighborhoods. Results were similar for breast cancer–specific survival, except that African Americans and non-Hispanic Whites living in high-SES neighborhoods had similar survival.Conclusions. Strategies to address the underlying factors that may influence treatment intensity and adherence, such as comorbidities and logistical barriers, should be targeted at low-SES non-Hispanic White and all African American patients.Breast cancer is the most common cancer among women in the United States, and it is the second leading cause of cancer death.1 Despite significant improvements in breast cancer survival from 1992 to 2009,1,2 racial/ethnic and socioeconomic survival disparities have persisted.3,4 African American women have consistently been found to have worse survival after breast cancer,3,5–11 Hispanic women have worse or similar survival,3,9,11,12 and Asian women as an aggregated group have better or similar survival3,9,11,12 than do non-Hispanic White women. Underlying factors thought to contribute to these racial/ethnic disparities include differences in stage at diagnosis,8,12,13 distributions of breast cancer subtypes,14–16 comorbidities,12,13,17 access to and utilization of quality care,13,18 and treatment.12,13Numerous studies also have found poorer survival after breast cancer diagnosis among women residing in neighborhoods of lower socioeconomic status (SES).6,9,19,20 Research has shown that inadequate use of cancer screening services, and consequent late stage diagnosis and decreased survival, contribute to the SES disparities.21,22 Similar to racial/ethnic disparities, SES disparities have been attributed to inadequate treatment and follow-up care and comorbidities.18 Previous population-based studies have continued to observe racial/ethnic survival disparities after adjusting for neighborhood SES, but these studies have not considered the combined influence of neighborhood SES and race/ethnicity.3,9,11,12,23 These disparities may remain because information on individual-level SES, health insurance coverage, comorbidities, quality of care, and detailed treatment regimens have typically not been available.3,8,9,11,13 Even among studies using national Surveillance Epidemiology and End Results–Medicare linked data, in which more detailed information on treatment and comorbidities are available among some patients aged 65 years and older, survival disparities have remained.12,23,24 However, not all data on medical conditions and health care services are captured in Medicare claims, including data on Medicare beneficiaries enrolled in HMOs (health maintenance organizations).25,26Using electronic medical records data from Kaiser Permanente Northern California (KPNC) linked to data from the population-based California Cancer Registry (CCR), we recently reported that chemotherapy use followed practice guidelines but varied by race/ethnicity and neighborhood SES in this integrated health system.27 Therefore, to overcome the limitations of previous studies and address simultaneously the multiple social28 and clinical factors affecting survival after breast cancer diagnosis, we used the linked KPNC–CCR database to determine whether racial/ethnic and socioeconomic differences in short-term overall and breast cancer–specific survival persist in women in a membership-based health system. Our study is the first, to our knowledge, to consider the combined influence of neighborhood SES and race/ethnicity and numerous prognostic factors, including breast cancer subtypes and comorbidities, thought to underlie these long-standing survival disparities among women with uniform access to health care and treatment.     

Association Between Neighborhood Disadvantage and Hypertension Prevalence,Awareness, Treatment,and Control in Older Adults: Results From the University of Alabama at Birmingham Study of Aging

Objectives. We evaluated the effect of neighborhood disadvantage (ND) on older adults’ prevalence, awareness, treatment, and control of hypertension.Methods. Data were from the University of Alabama at Birmingham Study of Aging, an observational study of 1000 community-dwelling Black and White Alabamians aged 65 years and older, in 1999 to 2001. We assessed hypertension prevalence, awareness, treatment, and control with blood pressure measurements and self-report data. We assessed ND with US Census data corresponding with participants’ census tracts, created tertiles of ND, and fit models with generalized estimating equations via a logit link function with a binomial distribution. Adjusted models included variables assessing personal advantage and disadvantage, place-based factors, sociodemographics, comorbidities, and health behaviors.Results. Living in mid-ND (adjusted odds ratio [AOR] = 1.6; 95% confidence interval [CI] = 1.2, 2.1) and high-ND tertiles (AOR = 1.8; 95% CI = 1.3, 2.3) was associated with higher hypertension prevalence, and living in high-ND tertiles was associated with lower odds of controlled hypertension (AOR = 0.6; 95% CI = 0.4, 0.6). In adjusted models, ND was not associated with hypertension awareness or treatment.Conclusions. These findings show that neighborhood environmental factors matter for hypertension outcomes and suggest the importance of ND for hypertension management in older adults.The characteristics of the geographic spaces or neighborhoods where people live influence their health throughout the life course.1–9 The mechanisms whereby neighborhood characteristics affect individuals’ health include psychosocial and material resources in those geographic spaces. Specifically, neighborhoods have the potential to be a source of social capital, providing support to persons in need; to have physical capital, offering parks and recreation resources for physical activity; and to have human capital, generating economic output. Any of these resources can contribute to the overall well-being of individuals living there.10 Alternatively, stress caused by high crime, low social support, limited economic resources, or a lack of material resources such as health services6 may ultimately negatively affect the health of individuals living in a neighborhood. Furthermore, limited community-based assistance programs, as well as limited access to healthful foods or adequate shopping opportunities and recreational facilities11 in disadvantaged neighborhoods may also have adverse effects on health. The daily stress of living in such disadvantaged neighborhoods may place a high burden on individuals’ physiological systems, a burden which is sometimes called allostatic load.12,13These risks and benefits of neighborhood contexts may accrue over a long period of time and may affect people either right away or for many years in the future14 and lead to conditions such as hypertension. In fact, neighborhood-level psychosocial and material deprivations are particularly problematic for individuals’ cardiovascular health and for management of cardiovascular risk factors. In 2004, Diez Roux et al.15 demonstrated an association between negative environments and both cardiovascular and noncardiovascular mortality. Other researchers have found similar effects, including Mujahid et al.16 who showed that walkability, access to healthy food, greater safety, and greater social cohesion were associated with a lower likelihood of hypertension.Although these findings are useful for gaining insights into the general population, work is needed to assess the effects of neighborhood characteristics on specific, unique subpopulations. To that end, there has been a growing interest in the effects of neighborhood context on older adults because of their potentially greater sensitivity (than the general population) to the effects of their neighborhood contexts on health.8,17–22 This is particularly important, as Lawton and Simon purported in the environmental docility hypothesis,23 because, as persons age and become more ill, losing control of their ability to perform activities of daily living, they may become more sensitive to characteristics of their environments, including the neighborhoods where they live. Specifically, then, older adults’ inability to navigate through disadvantaged neighborhoods may put them at higher risk for hypertension because of more concentrated exposure to psychosocial stressors. In addition, deprivation of health services including access to physicians and pharmacies in disadvantaged neighborhoods may cause adverse outcomes. Finally, older adults’ negative perception of their neighborhood environment may have a negative impact on their likelihood of being mobile and active, even when, in reality, theirs is not an unsafe or disadvantaged neighborhood.Although there is a burgeoning literature on the relationship between neighborhood characteristics and cardiovascular outcomes and a growing interest in neighborhood effects on older adults, no work known to these authors has examined neighborhood effects on hypertension specifically among older adults. Therefore, we aimed to assess if an association exists between neighborhood disadvantage (ND), measured by a validated ND index (NDI),24 and hypertension prevalence, awareness, treatment, and control in a cohort of community-dwelling older adults.     

Neighborhood socioeconomic status and cognitive function in women

Objectives. We examined whether neighborhood socioeconomic status (NSES) is associated with cognitive functioning in older US women and whether this relationship is explained by associations between NSES and vascular, health behavior, and psychosocial factors.Methods. We assessed women aged 65 to 81 years (n = 7479) who were free of dementia and took part in the Women''s Health Initiative Memory Study. Linear mixed models examined the cross-sectional association between an NSES index and cognitive functioning scores. A base model adjusted for age, race/ethnicity, education, income, marital status, and hysterectomy. Three groups of potential confounders were examined in separate models: vascular, health behavior, and psychosocial factors.Results. Living in a neighborhood with a 1-unit higher NSES value was associated with a level of cognitive functioning that was 0.022 standard deviations higher (P = .02). The association was attenuated but still marginally significant (P < .1) after adjustment for confounders and, according to interaction tests, stronger among younger and non-White women.Conclusions. The socioeconomic status of a woman''s neighborhood may influence her cognitive functioning. This relationship is only partially explained by vascular, health behavior, or psychosocial factors. Future research is needed on the longitudinal relationships between NSES, cognitive impairment, and cognitive decline.A growing body of research suggests that the characteristics of neighborhoods in which individuals live may influence their risk of poor self-rated health, cardiovascular disease, and mortality above and beyond individual-level characteristics.^1–15 The proposed mechanisms by which lower quality neighborhoods may affect physical health include increased exposure to chronic stressors and pollutants in the environment; increased access to alcohol and cigarette outlets; barriers to physical activity; reduced social support, networks, and cohesion; and reduced access to high-quality health and social services. Three recent studies have linked lower neighborhood socioeconomic status (NSES) to lower cognitive function in UK adults older than 52 years,¹⁶ US adults older than 70 years living in urban areas,¹⁷ and Mexican Americans older than 65 years living in 5 southwestern states.¹⁸ However, the mechanisms underlying this relationship are not well understood.Extensive epidemiological research has linked NSES to vascular-related conditions,^4,19–22 poor health behaviors,^23–25 and greater psychosocial stress.^26–30 Incidentally, these factors also have well-established linkages with brain health such that individuals who have vascular-related conditions,^31,32 who engage in low levels of physical activity, whose tobacco and alcohol consumption is excessive,^33–35 and who have pronounced symptoms of depression or low social support^36–38 are at increased risk for poor cognitive function. No studies to date have addressed whether these conditions may explain the relationship between NSES and cognitive function.Previous studies indicate that neighborhood environments may influence poor cognitive function above and beyond individual-level demographic characteristics such as age, race/ethnicity, educational attainment, and income.^16,17,39,40 Certain demographic subgroups may be especially vulnerable to the effects of NSES on cognitive function. For example, poor neighborhood environments may have stronger effects on older adults than on younger adults because older adults spend more time in their neighborhoods⁴¹; may have less access to social, financial, or health services; and have accumulated more exposures to stressors or pollutants. Non-White older adults who live in lower socioeconomic status (SES) neighborhoods may face discrimination or other stressors that may confer greater vulnerability to NSES effects on cognitive function.Wight et al.¹⁷ examined individual- and neighborhood-level educational interactions among US adults. However, no US study to date has addressed whether other individual-level demographic factors may buffer or exacerbate the negative effects on cognitive function of living in a lower SES neighborhood using an index consisting of important measures of SES beyond education alone.We examined whether an NSES index was related to cognitive function in a large, geographically and demographically diverse cohort of older US women with rich data on a sensitive measure of global cognitive function and a comprehensive set of clinical, behavioral, and psychosocial confounders. In addition, we assessed whether the relationship between NSES and cognitive function was explained by risk and protective factors for poor cognitive function that have also been linked with NSES and whether certain subgroups were more vulnerable to lower NSES.     

A Systematic Review of Neighborhood Disparities in Point-of-Sale Tobacco Marketing

We systematically reviewed evidence of disparities in tobacco marketing at tobacco retailers by sociodemographic neighborhood characteristics. We identified 43 relevant articles from 893 results of a systematic search in 10 databases updated May 28, 2014. We found 148 associations of marketing (price, placement, promotion, or product availability) with a neighborhood demographic of interest (socioeconomic disadvantage, race, ethnicity, and urbanicity).Neighborhoods with lower income have more tobacco marketing. There is more menthol marketing targeting urban neighborhoods and neighborhoods with more Black residents. Smokeless tobacco products are targeted more toward rural neighborhoods and neighborhoods with more White residents. Differences in store type partially explain these disparities.There are more inducements to start and continue smoking in lower-income neighborhoods and in neighborhoods with more Black residents. Retailer marketing may contribute to disparities in tobacco use. Clinicians should be aware of the pervasiveness of these environmental cues.Tobacco products and their marketing materials are ubiquitous in US retailers from pharmacies to corner stores.1 A similar presence is found across the globe, except in countries that ban point-of-sale (POS) tobacco marketing (e.g., Australia, Canada, Thailand2). In the United States, the POS has become the main communications channel for tobacco marketing3,4 and is reported as a source of exposure to tobacco marketing by more than 75% of US youths.5 Burgeoning evidence6,7 suggests that marketing at the POS is associated with youths’ brand preference,8 smoking initiation,9 impulse purchases,10,11 and compromised quit attempts.12,13The marketing of tobacco products is not uniform; it is clear from industry documents that the tobacco industry has calibrated its marketing to target specific demographic groups defined by race,14 ethnicity,15 income,16 mental health status,17 gender,18,19 and sexual orientation.20 Framed as an issue of social and environmental justice,14 research has documented historical racial, ethnic, and socioeconomic disparities in the presence of tobacco billboards,21–25 racial disparities in total tobacco marketing volume,24 and targeting of menthol cigarettes to communities with more Black residents.25,26 Targeted marketing of a consumer product that kills up to half27 of its users when used as directed exacerbates inequities in morbidity and mortality. Smoking is estimated to be responsible for close to half of the difference in mortality between men in the lowest and highest socioeconomic groups.28 However, evidence of marketing disparities is scattered across multiple disciplines and marketing outcomes, such as product availability, advertising quantity, presence of promotional discounts, and price. A synthesis of this literature would provide valuable information for intervention on tobacco marketing in the retail environment and inform etiological research on health disparities.To address this gap in the literature, we systematically reviewed observational studies that examined the presence and quantity of POS tobacco marketing to determine the extent to which marketing disparities exist by neighborhood demographic characteristic (i.e., socioeconomic disadvantage, race, ethnicity, and urbanicity).     

Effects of a Brief Case Management Intervention Linking People With HIV to Oral Health Care: Project SMILE

Objectives. Although people with HIV experience significant oral health problems, many consistently identify oral health as an unmet health care need. We conducted a randomized controlled trial to evaluate the impact of a dental case management intervention on dental care use.Methods. We evaluated the intervention according to self-reported dental care use at 6-, 12-, and 18-month follow-ups. Multivariable logistic models with generalized estimating equations were used to assess the effects of the intervention over time.Results. The odds of having a dental care visit were about twice as high in the intervention group as in the standard care group at 6 months (adjusted odds ratio [OR] = 2.52; 95% confidence interval [CI] = 1.58, 4.08) and 12 months (adjusted OR = 1.98; 95% CI = 1.17, 3.35), but the odds were comparable in the 2 groups by 18 months (adjusted OR = 1.07; 95% CI = 0.62, 1.86). Factors significantly associated with having a dental care visit included frequent physician visits and dental care referrals.Conclusions. We demonstrated that a dental case management intervention targeting people with HIV was efficacious but not sustainable over time. Barriers not addressed in the intervention must be considered to sustain its use over time.In the era of antiretroviral therapy, people with HIV are living longer and the treatment of associated medical and oral manifestations of the disease has shifted to a chronic disease model.1 Previous studies have shown that a person living with HIV/AIDS is more likely than a person without the disease to experience oral health problems.2–5 Furthermore, the oral health problems of individuals with HIV can be more severe and difficult to treat than those of the general population and may also contribute to the onset of opportunistic infections.5The oral health complications associated with HIV are well documented,2–6 and oral manifestations are increasingly being recognized as markers for monitoring treatment efficacy and predicting treatment failure.7 Oral manifestations, including Kaposi’s sarcoma, necrotizing ulcerative periodontitis, oral hairy leukoplakia, and candidiasis, may be present in up to 50% of people with HIV and 80% of people diagnosed with AIDS,5,6 and may predict low CD4 counts.8 In addition, individuals living with HIV/AIDS may experience difficulty in maintaining adequate salivary flow, which affects chewing, swallowing, and the ability to take medication.4 Chronic use of highly active antiretroviral therapy can also contribute to diminished salivary flow as well as an increased risk of oral candidiasis and oral hairy leukoplakia.9Throughout the 1990s, a series of study findings highlighted the unmet needs for dental care among people with HIV infection.10–14 This gap in oral health care services was corroborated by findings from the oral health component of the HIV Cost and Services Utilization Study,15 which demonstrated that unmet dental needs were twice as common as unmet medical needs among HIV-positive adults16,17 and led to a national call to action to improve access to oral health care.18 That study also showed that approximately half of people living with HIV had dental insurance, and those without dental insurance had greater unmet needs for dental services.17,19,20Recently published findings suggest that an unmet need still persists. One example is an initiative, funded by the Health Resources and Services Administration, that included 2469 people living with HIV who had not received dental care during the preceding year. Nearly half of these individuals (48%) reported an unmet dental need since their HIV diagnosis, 52% had not seen a dentist in more than 2 years, and 63% rated the health of their teeth and gums as fair or poor.21,22 An earlier investigation involving baseline data from the study presented here showed that oral health problems and symptoms were very prevalent among our study population, with 63% of participants having experienced an oral health impact very often or fairly often in the preceding 4 weeks.23Barriers to dental care use among individuals living with HIV include fear of dental care, HIV-specific stigma, fear of disclosing their HIV status to health care providers, perceived cost barriers, and poor adherence to medical guidance.20,22,24–31 Compounding patient access barriers, dental care providers may be reluctant to treat patients with HIV owing to fears of HIV transmission and associated stigma.32–36Previous research conducted in Florida revealed that more than one third of people with HIV do not discuss oral health with their primary care providers.37 Although clinical guidelines recommend that HIV care providers examine the oral cavity during initial and interim physical examinations of people living with HIV, this still may not be a regular clinical practice.37 To address underuse of oral health care services among individuals with HIV, we evaluated the efficacy of an intervention that linked individuals to dental care. The sample comprised a population of HIV-positive individuals in south Florida who had received HIV primary care but had not received oral health services in the preceding 12 months.     

Health Literacy: A Pathway to Better Oral Health

Objectives. We examined whether health literacy was associated with self-rated oral health status and whether the relationship was mediated by patient–dentist communication and dental care patterns.Methods. We tested a path model with data collected from 2 waves of telephone surveys (baseline, 2009–2010; follow-up, 2011) of individuals residing in 36 rural census tracts in northern Florida (final sample size n = 1799).Results. Higher levels of health literacy were associated with better self-rated oral health status (B = 0.091; P < .001). In addition, higher levels of health literacy were associated with better patient–dentist communication, which in turn corresponded with patterns of regular dental care and better self-rated oral health (B = 0.003; P = .01).Conclusions. Our study showed that, beyond the often-reported effects of gender, race, education, financial status, and access to dental care, it is also important to consider the influence of health literacy and quality of patient–dentist communication on oral health status. Improved patient–dentist communication is needed as an initial step in improving the population’s oral health.Oral health status is inexorably linked with general health,1 as evidenced by the association between poor oral health and chronic diseases, such as diabetes,2 cardiovascular disease,3 and respiratory disease.4 Among US adults, the burden of oral disease falls heaviest on vulnerable population groups,5–7 particularly those living in rural areas.8 Although improving oral health is named as one of the top 5 health priorities in Rural Healthy People 2010,9 little progress has been made in establishing public health programs to address this priority area. To achieve the goal of improved oral health, it is essential to study the risk factors associated with the oral health status of individuals residing in rural areas and to understand the relationships among these risk factors.The association between low dental care utilization and poor oral health outcomes has been proposed as a partial explanation for urban–rural disparities in oral health status.10–13 The rate of dental care utilization is lower among US rural than general populations, and dental visits tend to be problem—rather than prevention—oriented.14–17 Low levels of financial security and a lack of dental providers in rural areas are cited as major reasons for the low utilization rates in rural populations.12,18,19 However, evidence that individuals with dental insurance benefits choose to forgo regular preventive dental care suggests the presence of additional determinants in dental care utilization.20Previous research showed that communication between dentists and their patients plays an important role in the use of dental services.21–24 Effective patient–dentist communication increases utilization of dental services by lessening dental anxiety and, as a result, increasing patient perceptions of provider competence.25 Conversely, deficient communication skills, on either side of the patient–provider equation, are likely to increase dental anxiety and overall dissatisfaction with care.Health literacy deficits can interfere with effective patient–dentist communication. Individuals with low health literacy skills often have difficulty describing dental problems to their dentist and understanding dental conditions described by the dentist.26 Rozier et al. surveyed about 2000 dentists in the United States regarding the use of the 5 domains of communication techniques: interpersonal communication, teach-back method, patient-friendly materials and aids, assistance, and patient-friendly practice.27 Findings revealed low routine use by dentists of each communication technique, including those thought to be most effective with patients who demonstrate low health literacy.The association between low health literacy and poor health outcomes is well established.28–30 However, in the context of oral health, the literature offers few studies identifying the relationship between health literacy and oral health outcomes. It has been suggested that those with low health literacy are at highest risk for oral diseases and problems31 and that low health literacy may be associated with barriers to accessing care and with oral health behaviors such as seeking preventive care.32 Furthermore, rural residents have lower health literacy skills than urban residents.33 However, how health literacy is related to oral health status among rural populations remains an unanswered question.Frequently acknowledged risk factors for poor oral health include gender (male), race (Black), educational attainment (low), financial status (low), and access to dental care (none). We controlled for these factors in an examination of the effects of health literacy, patient–dentist communication, and dental care patterns on self-rated oral health status. In addition, we tested mediational pathways between health literacy and self-rated oral health. We hypothesized that greater health literacy would be associated with better patient–dentist communication, and in turn, that better patient–dentist communication would be associated with an increased likelihood of seeking regular dental care, ultimately leading to better self-rated oral health.     

Determinants of Mental Health and Self-Rated Health: A Model of Socioeconomic Status,Neighborhood Safety,and Physical Activity

Objectives. We investigated the underlying mechanisms of the influence of socioeconomic status (SES) on mental health and self-rated health (SRH), and evaluated how these relationships might vary by race/ethnicity, age, and gender.Methods. We analyzed data of 44 921 adults who responded to the 2009 California Health Interview Survey. We used a path analysis to test effects of SES, neighborhood safety, and physical activity on mental health and SRH.Results. Low SES was associated with greater neighborhood safety concerns, which were negatively associated with physical activity, which was then negatively related to mental health and SRH. This model was similar across different racial/ethnic and gender groups, but mean levels in the constructs differed across groups.Conclusions. SES plays an important role in SRH and mental health, and this effect is further nuanced by race/ethnicity and gender. Identifying the psychological (neighborhood safety) and behavioral (physical activity) factors that influence mental health and SRH is critical for tailoring interventions and designing programs that can improve overall health.Social determinants of health have been a focus in disparities research because these factors can be changed through prevention, intervention, and policy.1,2 Recently, there have been concerted efforts around the world to examine how social and environmental factors affect an individual’s health status.3–6 In this study, we tested a model that examines how social determinants influence mental health and self-rated health (SRH).The relation between socioeconomic status (SES), or socioeconomic position, and health has been examined extensively.7–14 Regardless of how SES is measured, the predominant view is that an individual’s social and economic resources strongly influence one’s health.15–17 Decades of research have shown that lower SES is associated with poorer health behaviors,17 a variety of health-related problems including hypertension and diabetes,18,19 and greater morbidity and mortality.11,20,21 The number of studies of SES and mental health is also growing. Some of these studies indicate that major depression is higher in low-SES groups.22–27 SES is a complex phenomenon and has been measured in several ways.28–31 Some researchers have argued that it is one’s relative position in the hierarchy, or socioeconomic position, that is the critical factor. Others have suggested that education alone is the single best indicator of SES.14 In recent studies, SES is most commonly measured in terms of education and income.10In the current study, the choice of variables was influenced by ecological systems theory and Diez Roux’s pathways model, which describes how SES might contribute to health disparities via individual and contextual pathways, such as neighborhoods.32–37 Low-SES neighborhoods have fewer resources and services and reduced physical activity compared with high-SES neighborhoods.38,39 One reason for reduced physical activity might be that those who feel less safe in their neighborhoods feel uncomfortable engaging in outdoor physical activity.40–42 Thus, the link between neighborhood conditions and health may be partially explained by safety fears.24,43,44 It is clear that lack of physical activity could contribute to health problems, but research has also demonstrated the beneficial effects of physical activity on mental health.45,46 Taken together, these findings point to the potential influence of SES on health and mental health, potentially by affecting neighborhood safety and physical activity.Race/ethnicity and SES are deeply intertwined; thus, teasing apart these effects is important in ascertaining the true influence of SES. This study contributes to the existing literature by examining the relationship between SES on mental health and SRH in a single model. Previous studies have examined how SES might affect health, mostly using regression analyses to test the relation between SES and safety fears, or safety fears and physical activity, for example. Our model considers both psychological (fear) and behavioral processes (physical activity), and is grounded in the existing literature. Additionally, we address previous study limitations by assessing how relations among SES, neighborhood safety, physical activity, mental health, and SRH might vary by race/ethnicity, age, and gender, thus providing a more nuanced picture of how SES affects health.42,47 The use of a diverse and large sample in California provides valuable insights into understanding potential subgroup disparities. We used a structural equation modeling (SEM) framework because it allows us to focus on 2 equally important outcomes: SRH and mental health.As seen in Figure 1, we hypothesized that individuals lower in SES have greater fears about their safety. Greater concerns over one’s safety would inhibit physical activity, which in turn would lead to worse health outcomes. We compared this model across 4 subgroups: (1) non-White women, (2) non-White men, (3) White women, and (4) White men. Additionally, age was included as a predictor of mental health and SRH, and time lived at current residence as a predictor of safety fears.48Open in a separate windowFIGURE 1—Hypothesized multiple-group path model of the effects of socioeconomic status on self-rated health and mental health through neighborhood safety fears and physical activity.Note. The model was fit across 4 groups: non-White women, non-White men, White women, and White men. We tested age as a moderator on the relation between safety concerns and physical activity (relation not shown). Single-headed arrows indicate a hypothesized pathway between 2 variables (+ = positive association, – = negative association). Two-headed arrows on same variable represent variances. Two-headed arrows between 2 variables represent covariances.