摘要：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. 10 In 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. 48 Open in a separate window FIGURE 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.
