TY - JOUR
T1 - Social network typologies and mortality risk among older people in China, India, and Latin America
T2 - A 10/66 Dementia Research Group population-based cohort study
AU - Santini, Ziggi Ivan
AU - Koyanagi, Ai
AU - Tyrovolas, Stefanos
AU - Haro, Josep M.
AU - Fiori, Katherine L.
AU - Uwakwa, Richard
AU - Thiyagarajan, Jotheeswaran A.
AU - Webber, Martin
AU - Prince, Martin
AU - Prina, A. Matthew
N1 - Funding Information:
The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007 – 2013 under REA grant agreement n° 316795.
Funding Information:
This is a secondary analysis of data collected by the 10/66 Dementia Research Group ( www.alz.co.uk/1066 ). The 10/66 DRG is led by Martin Prince and co-ordinated by Cleusa Ferri from Institute of Psychiatry, King's College London. The other principal investigators, responsible for research governance in each site are Juan Llibre Rodriguez (Cuba), Daisy Acosta (Dominican Republic), Mariella Guerra (Peru), Aquiles Salas (Venezuela), Ana Luisa Sosa (Mexico), KS Jacob (Vellore, India), Joseph D Williams (Chennai, India) and Yueqin Huang (China). The 10/66 Dementia Research Group's Research has been funded by the Wellcome Trust Health Consequences of Population Change Programme ( GR066133 – Prevalence phase in Cuba and Brazil; GR08002 – Incidence phase in Peru, Mexico, Argentina, Cuba, Dominican Republic, Venezuela and China), the World Health Organisation (India, Dominican Republic and China), the US Alzheimer's Association (IIRG – 04 – 1286 – Peru, Mexico and Argentina), and FONACIT / CDCH / UCV (Venezuela). The Rockefeller Foundation supported a dissemination meeting at their Bellagio Centre. Alzheimer's Disease International has provided support for networking and infrastructure.
Funding Information:
Stefanos Tyrovolas' work was funded through a scholarship from the Foundation for Education and European Culture (IPEP).
Funding Information:
Matthew Prina was supported by the MRC ( MR/K021907/1 ).
Funding Information:
Ai Koyanagi's work was supported by the Miguel Servet contract financed by the CP13/00150 project, integrated into the National R + D + I and funded by the ISCIII – General Branch Evaluation and Promotion of Health Research – and the European Regional Development Fund (ERDF) .
Publisher Copyright:
© 2015 The Authors.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - 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.
AB - 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.
KW - Ageing
KW - Developing countries
KW - Interpersonal relations
KW - Mortality
KW - Social networks
KW - Social support
KW - Survival rate
UR - http://www.scopus.com/inward/record.url?scp=84946558875&partnerID=8YFLogxK
U2 - 10.1016/j.socscimed.2015.10.061
DO - 10.1016/j.socscimed.2015.10.061
M3 - Journal article
C2 - 26575604
AN - SCOPUS:84946558875
SN - 0277-9536
VL - 147
SP - 134
EP - 143
JO - Social Science and Medicine
JF - Social Science and Medicine
ER -