Social Media Means
Photo: Kamaji Ogino
In general, women tend to have more close relationships than men, although men usually have larger social networks [46]. Therefore, the different types of social support and networks may operate in different ways and with different impacts on health between genders.
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Read More »The demographic and socioeconomic variables were age, gender, employment status (working/not working), and years of schooling (classified into four groups: no formal education/1–4 years/5–8 years/9 years or more). Income from pension or paid work was classified into four groups, where 1 represents the minimum wage (response options: 0.0–1.0/1.1–3.0/3.1–5.0/5.1 and above) [38]. Information about kinship between participants was not collected. However, since they were systematically drawn from different vaccination posts, they were assumed to be unrelated and not residents of the same household. Health-related behaviours referred to engaging in physical activity 5 or more times per week for at least 30 min (response options: Yes/No) [39] and smoking status (response options: current smoker/former smoker/non-smoker). Whilst universality, comprehensive care and equity are the core principles of the national health care system in Brazil (SUS), profound inequalities in access persist and elderly people with health insurance are more likely to receive care [40]. Use of health services was assessed whether the participant had health insurance (Yes/No) and type of health services used when receiving treatment (Public/Private). Participants’ functional status was assessed by their capacity to perform tasks in scales assessing basic and instrumental activities of daily living (ADL and IADL). ADL refers to ability to bathe, dress, use the toilet, transferring, continence, and eating. IADL gauges performance in unassisted meal preparation, housekeeping, laundering, medication management, and use of the telephone. Non-domestic activities considered in IADL are unassisted shopping for food, clothing, and medicine, and attending medical appointments and social and religious events without help. All the ADL and IADL items were scored for each activity the participant could perform independently [41]. Participants were categorized as independent (ADL and IADL = 0), partially dependent (ADL = 0 and IADL ≥ 1), and dependent (ADL ≥ 1). Somatic health problems (joint disease, such as arthritis, arthrosis, or rheumatism; depression; hypertension; and diabetes) were measured by the following question: ‘Have you ever been diagnosed with […] by a physician or health care professional?’ (Yes/No). Participants were categorised by the number of health problems reported (0, 1, 2–4, and ≥5).
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Read More »The outcome variable was dichotomised into ‘good SRH’ (very good and good) and ‘poor SRH’ (regular, poor, and very poor) [7]. SRH status, perceived social support, social network, and other covariates were compared against gender by using Pearson’s chi-square test. Proportions and 95% confidence intervals (95% CIs) of perceived social support, social network, and covariates were estimated for ‘good SRH’ and ‘poor SRH’ groups and stratified by gender. Comparisons of the independent variables between SRH groups were also conducted through Pearson’s chi-square test. All independent variables that had a p value below 0.20 in the bivariate analysis were selected for multivariate analysis. The variable ‘With whom do you live?’, used to measure perceived social support, was excluded in the multivariate analysis because of this criterion. Multivariate logistic regression using nested models tested the association of perceived social support and social networks with SRH while adjusting for covariates. The analysis was conducted separately for each gender. Odds ratios (ORs) and 95% CIs were estimated. Stepwise forward selection of variables in different blocks was performed according to the theoretical framework (Figure 1). This approach is recommended when testing the effect of a postulated risk factor on an outcome derived from a conceptual framework while describing the hierarchical relationships between risk factors [42]. Independent variables were organised into six blocks: (1) perceived social support and social network, (2) age group, (3) socioeconomic characteristics, (4) health-related behaviours, (5) use of health care services, (6) functional status measures and somatic health problems. The significance of additional variables was tested at each stage and non-significant variables (p > 0.05) were excluded to reduce discrepancy between the data and the model and to obtain an model with relatively few parameters [43]. Age group and education (years of schooling) were maintained in all models as important predictors of SRH. Variance inflation factor analysis did not indicate multicollinearity between perceived social support, size of social network, and covariates. Sample weights were used to adjust for sampling complexity. Weighted data were obtained by using a complex sample plan and were submitted to the complex samples analysis in SPSS version 17 for Windows (SPSS Inc., Chicago, IL).
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