Social Network Type and Healthy Lifestyle Among Persons With Type 2 Diabetes.

Little is known about the heterogeneity and dynamics in older adults’ social networks and their bidirectional relationship with health in Asian societies. We investigate (1) social network types, (2) how network types predict health, and (3) whether health influences network types over time among older Singaporeans. We use data from Transitions in Health, Employment, Social engagement and Inter-Generational transfers in Singapore Study (THE SIGNS Study), a national longitudinal survey, collected in 2016-2017 (wave 1) and 2019 (wave 2). Latent class analysis is applied to identify distinct social network types and how they affect self-rated health after two years. Latent transition analysis is then employed to examine the pattern of change in network types between waves, and the relationship between baseline self-rated health and transition in network types. We identify six social network types: diverse, diverse but less socially engaged, immediate family, extended family, living alone yet diverse, and restricted (proportion at baseline: 7.2 %, 38.2 %, 14.1 %, 27.1 %, 7.0 %, and 6.4 %, respectively). Older adults in the ‘living alone yet diverse’ network type are less likely to report poor self-rated health after two years than those in the restricted and extended family network types. Additionally, we find that good health is related to more diversified network types—‘diverse’ and ‘diverse but less socially engaged’—at baseline, and network types are relatively stable over two years. These findings contribute to the literature by capturing complexities in the reciprocal relationship between social network types and health in later life.

Social Networks and Their Relationship to Mental Health Service Use and Expenditures Among Medicaid Beneficiaries

Subclinical left ventricular (LV) dysfunction is prevalent in type 2 diabetes (T2DM). As obesity has been proposed as one causal factor in the disease process, this could bias the reported prevalences. We wanted to characterize echocardiographic LV dysfunction in obese T2DM subjects as compared to non-diabetic obese controls. One hundred patients with T2DM without clinical signs of heart failure (29% females, mean ± SD age 58.4 ± 10.5 years, body mass index (BMI) 30.1 ± 5.5 kg/m(2), blood pressure (BP) 141 ± 18/83 ± 9 mmHg) and 100 non-diabetic controls (29% females) matched for age (58.6 ± 10.5 years), BMI (29.8 ± 4.0 kg/m(2) and systolic BP (140 ± 14 mmHg) underwent echocardiography and color tissue Doppler imaging (TDI). Diastolic function was evaluated with conventional Doppler recordings and early (e') and late (a') myocardial velocities. The ratio between early transmitral filling (E) and the corresponding myocardial tissue velocity (e') served as an index of LV filling pressure. T2DM patients had more concentric hypertrophy with a relative wall thickness of 0.42 ± 0.07 vs controls 0.38 ± 0.07, P < 0.001. The T2DM group had signs of diastolic dysfunction with lower E/A ratio (0.91 ± 0.27 vs. 1.12 ± 0.38, P < 0.001), deceleration time (195 ± 49 vs 242 ± 72 ms, P < 0.001), e' (5.7 ± 2.0 vs. 6.6 ± 1.8 cm/s, P = 0.001), and a' (6.5 ± 2.0 vs. 7.6 ± 1.5 cm/s, P < 0.001) compared to the controls, and higher E/e' (13.3 ± 4.7 vs. 11.1 ± 3.5, P < 0.001). Thus, there were indications of pseudo normalization and increased filling pressure in the T2DM group, whereas the controls had evidence for relaxation abnormalities without elevated filling pressure. Compared to a non-diabetic obese group, more advanced subclinical impairment of diastolic function was seen in T2DM.

Social networks are crucial to personal health, particularly among caregivers of individuals with dementia; however, different types of social networks among caregivers of those with dementia and how these differences are associated with caregiver burden and positive appraisal, remain underexamined. This study aims to depict dementia caregivers' social network types, related factors, and impact on caregiving experiences. A questionnaire-based survey was conducted with a total of 237 family caregivers of individuals with dementia nested additional semistructured interviews conducted with 14 caregivers in Chongqing, China. A quantitative study was designed to collect data on personal and situational information, social networks, caregiver burden, and positive aspects of caregiving. Qualitative data were collected via semistructured interviews. Latent class analysis and multivariate regression analyses were applied to quantitative data, and inductive content analysis to qualitative data. The 3 social network types-family-limited (n = 39, 16.46%), family-dominant (n = 99, 41.77%), and diverse network (n = 99, 41.77%)-differed in age and sex of caregivers and individuals with dementia, stage of dementia, and caregiving intensity. Caregivers in family-dominant networks had a lower caregiver burden (β= -0.299, p = .003) and greater positive aspects of caregiving (β= 0.228, p = .021) than those in family-limited networks. Three themes-accessibility, reciprocity, and reliance-emerged as facilitators and barriers when asking for support. Caregivers frequently cited the perception of economic, practical, and emotional support, yet reported a lack of adequate formal support from healthcare providers. Family caregivers of individuals with dementia have different social network types that vary considerably among sociocultural contexts and perceive various types of support from social networks. Solid family networks and diverse social networks are contributors to long-term dementia care.

Background: Population aging is a social and economic concern for China. It is essential to understand types of social support networks available to elderly people living in China.Objectives: The aim of this research was to identify network types among Chinese older adults and to examine the differential relationship of the network types, health outcomes and health-related behaviors.Methods: Secondary analysis of data compiled by the Chinese Longitudinal Healthy Longevity Survey (n = 9749) was extracted. Network types were derived through latent class analysis with Mplus 6.12 software. Statistical analysis included descriptive statistics, one-way ANOVA, multiple logistic regression and path analysis.Results: Four types of social networks were identified, these included private (16%), non-couple-focused (15%), couple-focused (47%) and diverse (22%). Compared with elders belonging to other networks, elders in diverse network possessed the healthiest status and the highest health-related behaviors score. Health-related behaviors played a role in mediating social network types to health outcomes was identified. Findings were aligned to the conceptual model pathway proposed by Berkman (2000).Conclusion: The findings demonstrate that types of social networks for elders are significantly correlated to health-related behaviors and health outcomes. Detail and understanding of the correlations are useful to inform healthcare practice and policy and to assist the development of appropriate interpersonal interventions.

Using a Randomised Controlled Trial to Test the Effectiveness of a Family-Oriented, Theoretically Based, Diabetes Self-Management Education Program to Improve Glycaemia, Self-Management and Self-Efficacy of Individuals with Type 2 Diabetes Mellitus Living in Rural Thailand

Social Network Service is a one of the service where people may communicate with one another; and may also exchange messages even of any type of audio or video communication. Social Network Service as name suggests a type of network. Such type of web application plays a dominant role in internet technology. In such type of online community, people may share their common interest. Facebook LinkedIn, orkut and many more are the Social Network Service and it is good medium of making link with people having unique or common interest and goals. But the problem of privacy protection is a big issue in today's world. As social networking sites allows anonymous users to share information of other stuffs. Due to which cybercrime is also increasing to a rapid extent. In this article we preprocessed the web log data of Social Network Services and assemble that data on the basis of image file format like jpg, jpeg, gif, png, bmp etc. and also propose a framework for victim's identification.Keywords: Preprocessing, Web Log Data, Social Network Service, Data Mining, Cyber Crime1 IntroductionNow days we can see social networking services are growing day by day, First of all the term of social network is a social structure made of individuals (or organizations) called nodes, which are tied (connected) by one or more specific types of interdependency, such as friendship, kinship, financial exchange, dislike or relationships of beliefs, knowledge or prestige [8].Social networking is the grouping of individuals into specific groups, like small rural communities or a neighbourhood subdivision, if you will [3]. Generally some social services focus on the privacy issue too. Due to which one person could not see the friend link of other one. There are various types of social network are available. Personal networks-These kinds of network allow creating profiles online and linked with other person, with a focus on social linkage such as friendship. For example, Orkut, LinkedIn, Facebook, MySpace are stage for communicating with contacts [9][4][13]. These kinds' networks involve users exchanging information with people. Statuses update networks-These types of social networks are developed to allow small status update to person in order to communicate with other persons. For example, Twitter, these types of network people may exchange messages or thoughts day by day. Location networks-These networks are developed to show one's real-time location, either as public information or as an update viewable to authorized contacts. Content sharing networks-These networks are designed as platforms for sharing content, such as music, photographs and videos. For example YouTube and Flicker. Shared interest networks-Some social networks are built around a common interest or geared to a specific group of people. These networks incorporate features from other types of social networks but are slanted toward a subset of individuals, such as those with similar hobbies, educational backgrounds, political affiliations, ethnic backgrounds, religious views, sexual orientations or other defining interests. For example LinkedIn [16].Figure 1 shows that the social relationships among different users. In social networking services any person can interacts another person we have shown the person using dot in the give Fig. and maintained its relationships through lines. In this network any number of users (u1, u2, u3 ...) can communicate each other.But their exists some services that do not suffer from such kind of issues like LinkedIn Facebook, orkut etc. 'Mutual friend' is that feature existing on such services which provides a way of connecting through other person.Mutual friends are the persons who are Social Networking Service (SNS) friends with both you and the person whose timeline you are viewing. Or we can say mutual friends are the common friends of a person. Suppose u1 is friend of u10 and u14 then u1 is mutual friend of u10, u14. According to Fig. …

The studies on the risk of tuberculosis (TB) in patients with type 1 diabetes mellitus (T1DM) alone are limited. We examined this relationship using a population-based retrospective cohort study. From claims data of the National Health Insurance system of Taiwan, we identified 5195 patients with T1DM newly diagnosed from 2002 to 2011 and 20,780 randomly selected controls without T1DM, frequency matched by age, sex, and year of diagnosis. Both cohorts were followed up until the end of 2011 to evaluate the risk of TB. The overall incidence of TB was 4.07-fold higher in the T1DM cohort than in the control cohort (1.18 vs 0.29 per 1000 person-years, P < 0.001). Compared with the controls, the Cox model estimated adjusted hazard ratios (HRs) of TB in patients with T1DM were greater in men than in women (4.62 vs 3.59) and in adults than in children (4.06 vs 3.37), but not significant. The adjusted HR was much greater for those with comorbidities than those without comorbidities (14.6 vs 1.62, P < 0.001). Compared with the controls, the patients with T1DM were also more likely to develop TB with multiple emergency room visits (adjusted HR: 116.1, 95% confidence interval [CI] = 43.8–307.4) or hospitalizations (adjusted HR: 86.5, 95% CI = 33.7–222.4). Patients with T1DM are at elevated risks of developing TB with much higher HRs for those with comorbidities, within the first year of diagnosis, and with frequent emergency cares or hospitalizations.

Voluntary vaccination reflects how individuals weigh the risk of infection and the cost of vaccination against the spread of vaccine-preventable diseases, such as smallpox and measles. In a homogeneously mixing population, the infection risk of an individual depends largely on the proportion of vaccinated individuals due to the effects of herd immunity. While in a structured population, the infection risk can also be affected by the structure of individuals’ social network. In this paper, we focus on studying individuals’ self-organizing behaviors under the circumstance of voluntary vaccination in different types of social networks. Specifically, we assume that each individual together with his/her neighbors forms a local well-mixed environment, where individuals meet equally often as long as they have a common neighbor. We carry out simulations on four types of locally-mixed social networks to investigate the network effects on voluntary vaccination. Furthermore, we also evaluate individuals’ vaccinating decisions through interacting with their “neighbors of neighbors”. The results and findings of this paper provide a new perspective for vaccination policy-making by taking into consideration human responses in complex social networks.

The purpose of this study was to identify the social network types of elders and to identify differences among latent classes by social network. The data of 312 elders used in this study were collected from health, welfare, and other facilities and from elders living in the community. The interviews were conducted from July 16 to September 30, 2007 using a standard, structured questionnaire. Descriptive statistics, one way ANOVA with the SPSS 15.0 program and latent class analysis using Maximum Likelihood Latent Structure Analysis (MLLSA) program were used to analyze the data. Using latent class analysis, social network types among older adults were identified as diverse for 58.0% of the sample, as family for 34.0%, and as isolated for 8.0%. The health status of respondents differed significantly by network type. Elders in diverse networks had significantly higher health status and elders in isolated networks had significantly lower physical health status on average than those in all other networks. The results of this study suggest that these network types have important practical implications for health status of elders. Social service programs should focus on different groups based on social network type and promote social support and social integration.

This study was designed to identify social network types among lesbian, gay, bisexual, and transgender (LGBT) older adults and examine the relationship between social network type and mental health. We analyzed the 2014 survey data of LGBT adults aged 50 and older (N = 2,450) from Aging with Pride: National Health, Aging, and Sexuality/Gender Study. Latent profile analyses were conducted to identify clusters of social network ties based on 11 indicators. Multiple regression analysis was performed to examine the association between social network types and mental health. We found five social network types. Ordered from greatest to least access to family, friend, and other non-family network ties, they were diverse, diverse/no children, immediate family-focused, friend-centered/restricted, and fully restricted. The friend-centered/restricted (33%) and diverse/no children network types (31%) were the most prevalent. Among individuals with the friend-centered/restricted type, access to social networks was limited to friends, and across both types children were not present. The least prevalent type was the fully restricted network type (6%). Social network type was significantly associated with mental health, after controlling for background characteristics and total social network size; those with the fully restricted type showed the poorest mental health. Unique social network types (diverse/no children and friend-centered/restricted) emerge among LGBT older adults. Moreover, individuals with fully restricted social networks are at particular risk due to heightened health needs and limited social resources. This study highlights the importance of understanding heterogeneous social relations and developing tailored interventions to promote social connectedness and mental health in LGBT older adults.

ABSTRACTThis study investigates the changes in social network types among older adults in South Korea, and it examines whether, and to what extent, these changes influence their health and psychological wellbeing. Data were obtained from the Korean Longitudinal Study of Ageing. The sample was restricted to respondents over 65 years of age who participated in both the 2006 and 2008 surveys (N = 3,501). The social network types for both years were derived by Latent Class Analysis. Changes in network types over time were then identified. A series of multivariate regression analyses were conducted to examine the effects of social network changes on self-rated health, depressive symptoms and life satisfaction. Restricted, Family, Friend and Diverse network types were derived in each wave of the study. Although the direction of social network changes was not always towards the Restricted type, the Restricted network was the most prevalent and stable type among older Koreans. Older adults who remained in or transitioned to restricted types of social networks were more likely to have poor self-rated health, higher levels of depressive symptoms and lower levels of life satisfaction. This study adds to the limited body of literature on longitudinal network typology, and it expands the knowledge of social network types among older adults in diverse social and cultural contexts.

Considering beneficial effects of leisure activities in later life on well-being and health, we investigated which type of social network among older adults is associated with starting their participation in leisure activities. We used data from a longitudinal Japan Gerontological Evaluation Study (JAGES) conducted in Japan every three years from 2010 to 2016. We extracted types of social networks of older adults who did not participate in leisure activities in 2013 and responded to items related to social networks (n = 3436) relying on latent class analysis to examine changes in leisure activity participation over a three-year period within each latent class while controlling for participants’ activity in 2010. As a result, we identified five latent classes of social networks: the Neighborhood network, the Restricted network, which is characterized by limited social contacts, the Colleagues network, the Same-Interest network, and the Diverse network, from the most to the least prevalent. We found that members of the Neighborhood (Cohen’s d = 0.161) and Same-Interest networks (d = 0.660) were significantly more likely to, and members of the Diverse (d = 0.124) and Colleague networks (d = 0.060) were not significantly more likely to start leisure activities than those in the Restricted network. Furthermore, we found that lower age, better mental health, and higher education level were positively associated with starting participation in leisure activities in some latent classes. Horticulture or gardening was most likely to be chosen across all latent classes. Supporting the formation of social networks facilitating leisure activities, and recommending activities that were likely to be selected could be one solution for getting and keeping older adults active.

The purpose was to examine the relationship between different types of social networks and memory over 15 years of followup in a large cohort of older Australians who were cognitively intact at study baseline. Our specific aims were to investigate whether social networks were associated with memory, determine if different types of social networks had different relationships with memory, and examine if changes in memory over time differed according to types of social networks. We used five waves of data from the Australian Longitudinal Study of Ageing, and followed 706 participants with an average age of 78.6 years (SD 5.7) at baseline. The relationships between five types of social networks and changes in memory were assessed. The results suggested a gradient of effect; participants in the upper tertile of friends or overall social networks had better memory scores than those in the mid tertile, who in turn had better memory scores than participants in the lower tertile. There was evidence of a linear, but not quadratic, effect of time on memory, and an interaction between friends' social networks and time was apparent. Findings are discussed with respect to mechanisms that might explain the observed relationships between social networks and memory.

The purpose of the study was to identify the different types of social support networks (SSNs) among community-dwelling people aged 75+ years in selected areas of Poland, and to evaluate any associations between the network type and demographic and health variables of the population studied. The two most prevalent SSN types identified using the Practitioner Assessment of Network Type were “family dependent” (35.8%) and “locally integrated” (32.2%). “Local self-contained” (6.4%), “wider community focused” (2.8%) and “private restricted” (5.6%) SSNs were observed less frequently. In 17.2% of cases, it was not possible to identify the type of network unequivocally. Older people with a locally integrated SSN, in contrast to the family dependent type, were generally younger, living alone, and less likely to be homebound, rate their health as poor, suffer from depression or dementia, and had lower levels of functional disability. Locally integrated SSNs are recognized in the literature as being the most robust in terms of facilitating well-being and providing sufficient support to help maintain the older person in the community. This may reflect the higher levels of independence of older people able to sustain these support networks, which are then transformed into family-dependent types as their health deteriorates, but confirmation of this would require prospective studies. An improved understanding of the prevalence of different types of social networks among older people in Poland would help to guide a systematic approach to recognizing unmet needs in this population and provide crucial information in the planning of formal services.