The combined relations of gender,enculturation, and depressive symptoms with health risk behaviors in Mexican-Americans: a moderated mediation analysis

ABSTRACT

Objectives: The present study investigated the relationships of enculturation and depressive symptoms with health risk behavior engagement in Mexican-American college students and examined how these relationships differed by gender. Previous research has noted consistent gender differences in health risk behavior (e.g. alcohol use, substance use, and risky sexual behavior) among Latina/os, and emphasized the role of U.S. acculturation in this difference. Research examining the role of heritage cultural retention (i.e. enculturation), and including the added influence of mental health variables, such as depressive symptoms, is currently lacking. This study sought to address this gap.

Design: A large sample (N?=?677) of Mexican-American college students from four universities (located in New York, California, Florida, and Texas) completed an online questionnaire assessing health risk behaviors and corresponding variables.

Results: We found that males who endorsed more behavioral enculturation and depressive symptoms were more likely to engage in health risk behavior than all others in the sample. Contrary to previous literature, no relationship was found between behavioral enculturation and health risk behavior in females.

Conclusion: The current study found behavioral enculturation to be associated with depressive symptoms, and in turn with health risk behaviors among the males in our sample. Additional research will be needed to identify the mechanism underlying the relationship between enculturation and depressive symptoms as well as between depressive symptoms and risky behavior.     

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.