This systematic literature review explores the applications of social network platforms for disaster health care management and resiliency and investigates their potential to enhance decision-making and policy formulation for public health authorities during such events.

A comprehensive search across academic databases yielded 90 relevant studies. Utilizing qualitative and thematic analysis, the study identified the primary applications of social network data analytics during disasters, organizing them into 5 key themes: communication, information extraction, disaster Management, Situational Awareness, and Location Identification.

The findings highlight the potential of social networks as an additional tool to enhance decision-making and policymaking for public health authorities in disaster settings, providing a foundation for further research and innovative approaches in this field.

However, analyzing social network data has significant challenges due to the massive volume of information generated and the prevalence of misinformation. Moreover, it is important to point out that social network users do not represent individuals without access to technology, such as some elderly populations. Therefore, relying solely on social network data analytics is insufficient for effective disaster health care management. To ensure efficient disaster management and control, it is necessary to explore alternative sources of information and consider a comprehensive approach.

Individuals with diminished social connections are at higher risk of mental disorders, dementia, circulatory conditions and musculoskeletal conditions. However, evidence is limited by a disease-specific focus and no systematic examination of sex differences or the role of pre-existing mental disorders.

We conducted a cohort study using data on social disconnectedness (loneliness, social isolation, low social support and a composite measure) from the 2013 and 2017 Danish National Health Survey linked with register data on 11 broad categories of medical conditions through 2021. Poisson regression was applied to estimate incidence rate ratios (IRRs), incidence rate differences (IRDs), and explore sex differences and interaction with pre-existing mental disorders.

Among 162,497 survey participants, 7.6%, 3.5% and 14.8% were classified as lonely, socially isolated and with low social support, respectively. Individuals who were lonely and with low social support had a higher incidence rate in all 11 categories of medical conditions (interquartile range [IQR] of IRRs, respectively 1.26–1.49 and 1.10–1.14), whereas this was the case in nine categories among individuals who were socially isolated (IQR of IRRs, 1.01–1.31). Applying the composite measure, the highest IRR was 2.63 for a mental disorder (95% confidence interval [CI], 2.38–2.91), corresponding to an IRD of 54 (95% CI, 47–61) cases per 10,000 person-years. We found sex and age differences in some relative and absolute estimates, but no substantial deviations from additive interaction with pre-existing mental disorders.

This study advances our knowledge of the risk of medical conditions faced by individuals who are socially disconnected. In addition to the existing evidence, we found higher incidence rates for a broad range of medical condition categories. Contrary to previous evidence, our findings suggest that loneliness is a stronger determinant for subsequent medical conditions than social isolation and low social support.

A preregistered analysis plan and statistical code are available at Open Science Framework (https://osf.io/pycrq).

Social isolation has been implicated in the development of cognitive impairment, but research on this association remains limited among racial-ethnic minoritized populations. Our study examined the interplay between social isolation, race–ethnicity and dementia.

We analyzed 11 years (2011–2021) of National Health and Aging Trends Study (NHATS) data, a prospective nationally representative cohort of U.S. Medicare beneficiaries aged 65 years and older. Dementia status was determined using a validated NHATS algorithm. We constructed a longitudinal score using a validated social isolation variable for our sample of 6,155 community-dwelling respondents. Cox regression determined how the interaction between social isolation and race–ethnicity was associated with incident dementia risk.

Average longitudinal frequency of social isolation was higher among older Black (27.6%), Hispanic (26.6%) and Asian (21.0%) respondents than non-Hispanic White (19.1%) adults during the 11-year period (t = −7.35, p < .001). While a higher frequency of social isolation was significantly associated with an increased (approximately 47%) dementia risk after adjusting for sociodemographic covariates (adjusted hazard ratio [aHR] = 1.47, 95% CI [1.15, 1.88], p < .01), this association was not significant after adjusting for health covariates (aHR = 1.21, 95% CI [0.96, 1.54], p = .11). Race–ethnicity was not a significant moderator in the association between social isolation and dementia.

Older adults from racial-ethnic minoritized populations experienced a higher longitudinal frequency of social isolation. However, race–ethnicity did not moderate the positive association observed between social isolation and dementia. Future research is needed to investigate the underlying mechanisms contributing to racial-ethnic disparities in social isolation and to develop targeted interventions to mitigate the associated dementia risk.

Social networks are critical social health factors for older adults. This study examined the association between social networks and dietary variety among community-dwelling older adults.

A cross-sectional study, using the dietary variety score (DVS) developed for older Japanese people to assess dietary variety and the Lubben Social Network Scale (LSNS-6) to assess social networks.

N City, H Prefecture, Japan.

Community-dwelling older adults aged ≥ 65 years (n 1229).

The LSNS-6 score in the low DVS group was lower than that in the middle and high DVS groups (12·2 ± 5·6 v. 13·4 ± 5·4 and 14·4 ± 5·7, P < 0·001). The population of social isolation (LSNS-6, < 12) in the low DVS group was higher than that in the middle and high DVS groups (43·5 % v. 35·8 % and 31·0 %, P = 0·005). Multivariate linear regression analysis showed that the LSNS-6 score was positively correlated with DVS (standardised coefficient, 0·092; P = 0·002). Social isolation was also significantly associated with a low DVS in the multivariate-adjusted logistic analysis model (OR, 1·30; 95 % CI 1·00, 1·68; P = 0·048). Stratified analysis results revealed the LSNS-6 and DVS were significantly associated in participants with the following characteristics: younger age (< 75 years), women and those living with someone.

Social networks were associated with dietary variety; social isolation was related to poor dietary variety among community-dwelling older adults. An association between social networks and dietary variety was observed among young-old older adults, women and those living with someone.

Identifying the correlates of mental health resilience (MHR)—defined as the discrepancy between one’s reported current mental health and one’s predicted mental health based on their physical performance—may lead to strategies to alleviate the burden of poor mental health in aging adults. Socioeconomic factors, such as income and education, may promote MHR via modifiable factors, such as physical activity and social networks.

A cross-sectional study was conducted. Multivariable generalized additive models characterized the associations between socioeconomic and modifiable factors with MHR.

Data were taken from the population-based Canadian Longitudinal Study on Aging (CLSA), which collected data at various data collection sites across Canada.

Approximately 31,000 women and men between the ages of 45 and 85 years from the comprehensive cohort of the CLSA.

Depressive symptoms were assessed by the Center for Epidemiological Studies Depression Scale. Physical performance was measured objectively using a composite of grip strength, sit-to-stand, and balance performance. Socioeconomic and modifiable factors were measured by self-report questionnaires.

Household income, and to a lesser extent, education were associated with greater MHR. Individuals reporting more physical activity and larger social networks had greater MHR. Physical activity accounted for 6% (95% CI: 4 to 11%) and social network accounted for 16% (95% CI: 11 to 23%) of the association between household income and MHR.

The burden of poor mental health in aging adults may be alleviated through targeted interventions involving physical activity and social connectedness for individuals with lower socioeconomic resources.