Summary
Rural families continue to experience health inequalities in comparison to their urban and suburban counterparts.This study sought to identify the types and extent of stressors associated with health issues for rural, low-income families, as well as relevant resources and appraisal processes that can enhance or detract from adaptation.Twenty-five participants were recruited from rural counties in three states, Florida, Kentucky, and Washington. Participants werefemale caregivers of at least one child under the age of 13, and participated in semi-structured interviews. Qualitative analyses identified three major themes: 1) family health exacerbated by rural poverty, 2) assessment and utilization of resources, and 3) perceived hierarchy of needs and actions.The results of this study revealed how rural, low-income mothers cope with highly stressful environment economically and geographically to optimize their family health and can be used to inform the development of programming to support rural, low-income mothers.

Objectives

• To analyze health challenges faced by rural, low-income families within a framework of Family Stress Theory
• To document the health management strategies applied by low-income families to optimize their well-being
• To provide implications for health policies and programs targeting rural, low-income families

Subject Codes: health, health care, poverty
Population Codes: low income, rural, Hispanic/Latina/o/x
Method and Approach Codes: grounded theory, qualitative methodology, social justice

Summary
Obesity is a significant problem in the U.S., with Latinx youth facing increased risks. Past studies have used cumulative risk models (CRMs) to predict obesity, but they have focused primarily on risks and not on protective factors, and research has not focused on rural Latinx youth populations. Therefore, this study focused on data from 119 rural Midwestern Latinx 10-to-12-year-old youth.The CRM included 10 risk factors from three categories (physiological, family-level, parental-level), and protective routines (sleep duration) assessed through surveys and objective measurements. Total risks were associated with increased obesity prevalence. Protective routines moderated this process, lowering obesity prevalence for children with healthy routines even when facing increased risks. These findings support previous literature, and emphasize the importance of healthy, modifiable routines. Future research and interventions should promote beneficial, protective, modifiable routines that lower the prevalence of obesity in children, especially for youth who face increased risks.

Objectives

• Assess how well a cumulative risk model predicts different BMI outcomes in a sample of rural Midwestern Latinx youth.
• Examine the influence of protective routines on lowering the risk for child obesity.
• Examine the potential influence of protective routines as moderating factors in the relationship between cumulative risks and obesity outcomes.

Subject Codes: risk factors, protective factors, physical health
Population Codes: obesity, Hispanic/Latina/o/x, rural
Method and Approach Codes: structural equation modeling (SEM), regression: linear (simple, multiple, hierarchical), mediation/indirect effects models

Summary
Migrant, seasonal farmworkers in the United States often live communally in poor conditions that are linked with negative physical health outcomes. They are also likely to live below the poverty line and experience food insecurity, or limited access to sufficient food. Poor living conditions and high poverty rates are associated with higher rates of depression. Food insecurity is linked with lower psychological functioning and suicide. Those who are food insecure may undereat due to negative feelings, potentially further exacerbating depressive symptoms. Current research is mostly limited to children or families living together in the US. There is a gap in understanding food-related challenges for men on H-2A visas, living away from their families. We examine (1) the influence of Body Mass Index, food insecurity, and undereating behaviors on depression, (2) food insecurity on undereating behaviors, (3) the indirect effect of undereating behaviors on the relationship between food insecurity and depression.

Objectives

• To measure the association between food insecurity and depression among migrant farmworkers
• To examine if food insecurity influences undereating behaviors
• To understand how undereating may explain the link between food insecurity and depression

Subject Codes: food (in)security, depression, migration
Population Codes: Hispanic/Latina/o/x, low income, migrant
Method and Approach Codes: structural equation modeling (SEM), mediation/indirect effects models,

Summary
The rise in prevalence of obesity and chronic diseases among adults in India is a major public health concern. While this increase in obesity and chronic disease prevalence is thought to be driven by modernization, research on modernization and obesity among Indian adults is limited. Moreover, obesity disparities between urban and rural populations require more attention as individuals living in urban areas have higher rates of overweight and obesity compared to rural residents. Utilizing two waves of the India Human Development Survey (IHDS), we will examine the relationship between indicators of modernization, and risk factors for obesity and chronic disease among Indian adults. The long-term implications of this novel research are to reduce obesity and chronic disease disparities among rural and urban adults living in India.

Objectives

• To examine changes in the prevalence of obesity and chronic disease among Indian adults
• To identify individual, social, and lifestyle factors associated with obesity and chronic disease among Indian adults
• To describe the implications of these findings for research and practice.

Subject Codes: chronic illness, inequalities, public health
Population Codes: international (non-U.S.), obesity, Asian/Pacific Islander
Method and Approach Codes: secondary data analysis, quantitative methodology, regression: logistic (binary, ordinal, or multinomial)