BACKGROUND: Restricted social networks have been associated with higher mortality in several developed countries but there are no studies on this topic from developing countries. This gap exists despite potentially greater dependence on social networks for support and survival due to various barriers to health care and social protection schemes in this setting. Thus, this study aims to examine how social network type at baseline predicts all-cause mortality among older adults in six Latin American countries, China, and India.
METHODS: Population-based surveys were conducted of all individuals aged 65+ years in eight countries (Cuba, Dominican Republic, Peru, Venezuela, Mexico, Puerto Rico, China, and India). Data on mortality were obtained at follow-up (mean 3.8 years after cohort inception). Follow-up data for 13,891 individuals were analysed. Social network types were assessed using Wenger's Practitioner Assessment of Network Type (PANT). Cox proportional hazard models were constructed to estimate the impact of social network type on mortality risk in each country, adjusting for socio-demographics, receipt of pension, disability, medical conditions, and depression. Meta-analysis was performed to obtain pooled estimates.
RESULTS: The prevalence of private network type was 64.4% in urban China and 1.6% in rural China, while the prevalence of locally integrated type was 6.6% in urban China and 86.8% in rural China. The adjusted pooled estimates across (a) all countries and (b) Latin America showed that, compared to the locally integrated social network type, the locally self-contained [(b) HR = 1.24, 95% CI 1.01-1.51], family dependent [(a) HR = 1.13, 95% CI 1.01-1.26; (b) HR = 1.13, 95% CI 1.001-1.28], and private [(a) HR = 1.36, 95% CI 1.06-1.73; (b) HR = 1.45, 95% CI 1.20-1.75] social network types were significantly associated with higher mortality risk.
CONCLUSION: Survival time is significantly reduced in individuals embedded in restricted social networks (i.e. locally self-contained, family dependent, and private network types). Social care interventions may be enhanced by addressing the needs of those most at risk of neglect and deteriorating health. Health policy makers in developing countries may use this information to plan efficient use of limited resources by targeting those embedded in restricted social networks.