Social Network Typology and Serious Psychological Distress: Findings from the National Survey of American Life

Gender differences in social networks and physical and mental health: are social relationships more health protective in women than in men?

Background

Individuals' relationships are characterized by multidimensional aspects and the unique make-up of different features is more or less supportive of physical and mental health. The current study derived social network types based on an extended set of indicators reflecting the structure, function, and quality of relationships, then examined their associations with diverse physical and mental health outcomes separately for men and women.

Methods

Using samples of 620 South Korean adults (Mage = 53.52), Latent Profile Analysis (LPA) was used to uncover distinct social network types, and multiple regression analyses were conducted to examine the link between network types and health outcomes.

Results

LPA analysis derived four network types: diversified, family-(un)supported, friend- based, and restricted. The prevalence and configuration of network types differed between men and women: the family-unsupported type was more prevalent in women than in men whereas the restricted type was more prevalent in men than in women. An individual's network type membership was significantly associated with one's physical and mental health and the positive effects of an optimal network type and the negative effects of a non-optimal network type on mental health were much greater for women than they were for men.

Discussion

The findings suggest that women benefit more from supportive networks but that they are also more vulnerable to a lack of supportive (or the presence of conflict-filled) relationships, and highlight that having diversified and greater quality relationships, and avoiding conflicts are critical for women to have enhanced health.

Social network typologies moderate the association of loneliness with depressive symptomatology in middle-aged and older adults

Background

Depression remains among the most prevalent mental disorders, and it severely affects daily functioning and quality of life. There has been extensive research reporting on the impact of social relationships on depression, but much of this research has only considered isolated aspects of relationships. This study derived social network types based on the multiple components of social relationships, and then investigated their effects on depressive symptoms.

Methods

Using samples of 620 adults (M_age = 53.52), Latent Profile Analysis (LPA) was conducted to uncover network types based on the structural (network size, contact frequency, marital status, and social engagement), functional (levels of support and conflict), and qualitative (satisfaction with relationships) aspects of social relationships. Multiple regressions were used to test if distinct network types directly impact on depressive symptoms and whether network types moderate the association of loneliness (perceived social isolation) with depressive symptoms.

Results

LPA identified four distinct network types (diverse, family-focused, friend-focused, and restricted) and there were significant differences in depressive symptoms among four network types. Analysis using the BCH method showed that individuals in the restricted network type had the highest depressive symptoms, followed in order by individuals in the friend-focused, family-focused, and diverse network types. Regression results further indicated that an individual's network network type membership was significantly associated with depressive symptoms, and being in the diverse and family-focused network types alleviated the negative effect of loneliness on depressive symptoms.

Conclusion

The results suggest that both quantitative and qualitative aspects of social relationships are important in buffering against the adverse effect of loneliness on depressive symptoms. These findings underscore the utility of taking a multi-dimensional approach to uncover heterogeneity in the social networks of adults and their implications on depression.

Sociodemographic Factors and Neighborhood/Environmental Conditions Associated with Social Isolation Among Black Older Adults

Objectives: To investigate sociodemographic factors and neighborhood/environmental conditions associated with social isolation (SI) among Black older adults. Methods: We utilized data from the 2014 and 2016 Leave-Behind Questionnaire from the Health and Retirement Study (HRS LBQ) among those who self-identified as Black (N = 2.323). Outcome variables for our study included SI from adult children, other family members, friends, disengagement from social participation and religious services, being unmarried, and living alone. These indicators were also combined into an overall SI index. Critical predictors included gender, age, household income, education, employment status, neighborhood cohesion, neighborhood disorder, urbanicity, and region of residence. Results: Sociodemographic factors of gender, education and household income were significantly associated with SI indicators. Additionally, some neighborhood/environmental conditions were associated with SI indicators. Discussion: SI was found to be patterned by sociodemographic factors. These results can be used to develop effective interventions to mitigate SI among Black older adults.

Multidimensional Social Network Types and Their Correlates in Older Americans

Background and Objectives

Social support networks of older adults have been linked to their health and well-being; however, findings regarding the effects of specific network characteristics have been mixed. Additionally, due to demographic shifts increasing numbers of older adults live outside of traditional family structures. Previous studies have not systematically examined the resulting complexity and heterogeneity of older adults’ social networks. Our objectives were to examine this complexity and heterogeneity by developing a multidimensional typology of social networks that simultaneously considers multiple structural and functional network characteristics, and to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort.

Research Design and Methods

Participants included 5,192 adults aged 57–85 years in the National Social Life, Health, and Aging Project at rounds 1 (2005–2006) and 3 (2015–2016). Data were collected on social relationships including network size, diversity, frequency of contact, and perceived support and strain in relationships. We used latent class analysis to derive the network typology and multinomial logistic regression to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort.

Results

Older adults were classified into 5 distinct social network types: (i) large, with strain; (ii) large, without strain; (iii) small, diverse, low contact; (iv) small, restricted, high contact; and (v) medium size and support. Membership in these network types varied by age, gender, marital status, race/ethnicity, education, mental health, and birth cohort.

Discussion and Implications

Network typologies can elucidate the varied interpersonal environments of older adults and identify individuals who lack social connectedness on multiple network dimensions and are therefore at a higher risk of social isolation.