Local Network Interaction as a Mechanism for Wealth Inequality.

Given limited institutional resources, low-income populations often rely on social networks to improve their socioeconomic outcomes. However, it remains in question whether small-scale social interactions could affect large-scale economic inequalities in under-resourced contexts. Here, we leverage population-level data from one of the poorest South African settings to construct a large-scale, geographically defined, inter-household social network. Using a multilevel network model, we show that having social ties in close geographic proximity is associated with stable household asset conditions, while geographically distant ties correlate to changes in asset allocation. Notably, we find that localised network interactions are associated with an increase in wealth inequality at the regional level, demonstrating how macro-level inequality may arise from micro-level social processes. Our findings highlight the importance of understanding complex social connections underpinning inter-household resource dynamics, and raise the potential of large-scale social assistance programs to reduce disparities in resource-ownership by accounting for local social constraints.

Understanding Household Dynamics From the Ground Up: A Longitudinal Study From a Rural South African Setting.

Investigations into household structure in low- and middle-income countries (LMICs) provide important insight into how families manage domestic life in response to resource allocation and caregiving needs during periods of rapid sociopolitical and health-related challenges. Recent evidence on household structure in many LMICs contrasts with long-standing viewpoints of worldwide convergence to a Western nuclearized household model. Here, we adopt a household-centered theoretical and methodological framework to investigate longitudinal patterns and dynamics of household structure in a rural South African setting during a period of high AIDS-related mortality and socioeconomic change. Data come from the Agincourt Health and Socio-Demographic Surveillance System (2003-2015). Using latent transition models, we derived six distinct household types by examining conditional interdependency between household heads' characteristics, members' age composition, and migration status. More than half of households were characterized by their complex and multigenerational profiles, with considerable within-typology variation in household size and dependency structure. Transition analyses showed stability of household types under female headship, while higher proportions of nuclearized household types dissolved over time. Household dissolution was closely linked to prior mortality experiences-particularly, following death of a male head. Our findings highlight the need to better conceptualize and contextualize household changes across populations and over time.

The double-edged role of accessed status on health and well-being among middle- and older-age adults in rural South Africa: The HAALSI study.

Background: Social capital theory conceptualizes accessed status (the socioeconomic status of social contacts) as interpersonal resources that generate positive health returns, while social cost theory suggests that accessed status can harm health due to the sociopsychological costs of generating and maintaining these relationships. Evidence for both hypotheses has been observed in higher-income countries, but not in more resource-constrained settings.We therefore investigated whether the dual functions of accessed status on health may be patterned by its interaction with network structure and functions among an older population in rural South Africa. Method: We used baseline survey data from the HAALSI study ("Health and Aging in Africa: a Longitudinal Study of an INDEPTH Community in South Africa") among 4,379 adults aged 40 and older. We examined the direct effect of accessed status (measured as network members' literacy), as well as its interaction with network size and instrumental support, on life satisfaction and self-rated health. Results: In models without interactions, accessed status was positively associated with life satisfaction but not self-rated health. Higher accessed status was positively associated with both outcomes for those with fewer personal contacts. Interaction effects were further patterned by gender, being most health-protective for women with a smaller network and most health-damaging for men with a larger network. Conclusions: Supporting social capital theory, we find that having higher accessed status is associated with better health and well-being for older adults in a setting with limited formal support resources. However, the explanatory power of both theories appears to depending on other key factors, such as gender and network size, highlighting the importance of contextualizing theories in practice.

Clusters of HIV Risk and Protective Sexual Behaviors in Agincourt, Rural South Africa: Findings from the Ha Nakekela Population-Based Study of Ages 15 and Older.

Understanding how sexual behaviors cluster in distinct population subgroups along the life course is critical for effective targeting and tailoring of HIV prevention messaging and intervention activities. We examined interrelatedness of sexual behaviors and variation between men and women across a wide age range in a rural South African setting with a high HIV burden. Data come from the Ha Nakekela population-based survey of people aged 15-85-plus drawn from the Agincourt Health and Socio-Demographic Surveillance System. We used latent class analysis of six sexual behavior indicators to identify distinct subgroup sexual behavior clusters. We then examined associations between class membership and sociodemographic and other behavioral risk factors and assessed the accuracy of a reduced set of sexual behavior indicators to classify individuals into latent classes. We identified three sexual behavior classes: (1) single with consistent protective behaviors; (2) risky behaviors; and (3) in union with lack of protective behaviors. Patterns of sexual behaviors varied by gender. Class membership was also associated with age, HIV status, nationality, and alcohol use. With only two sexual behavior indicators (union status and multiple sexual partners), individuals were accurately assigned to their most likely predicted class. There were distinct multidimensional sexual behavior clusters in population subgroups that varied by sex, age, and HIV status. In this population, only two brief questions were needed to classify individuals into risk classes. Replication in other situations is needed to confirm these findings.