Rural-urban differences in sociodemographic,social network and lifestyle factors related to mortality of middle-aged Japanese men from the Komo-Ise cohort study

To examine rural-urban differences in the relationships of sociodemographic, social network, and lifestyle factors to mortality in middle-aged men, we used the data from a community based prospective cohort study, the Komo-Ise study. The subjects were all men aged 40-69 years living in Komochi Village, the rural group (n=2,295), or the downtown district of Isesaki City, the urban group (n=3,334), as of 1993. They completed a self-administered questionnaire in 1993 and were followed for all-cause deaths until 2000. The Cox proportional hazards model was used to compute relative risks (RRs) with 95% confidence intervals (CIs). Low educated men and men without a spouse in the rural group had an increased risk of mortality (RR=4.4; 95%CI: 1.1-18.2, RR=2.4; 95%CI: 1.2-4.5). Men who did not enjoy good fellowship with their neighbors in the rural group had a decreased risk of mortality (RR=0.58; 95%CI: 0.35-0.97). Mortality risks were significantly higher in urban men not participating in hobbies, club activities or community groups (RR=1.6; 95%CI: 1.1-2.4). These variables remained significant risk factors, even after controlling for all sociodemographic, social network, lifestyle, and health status variables. Educational level, marital status and relation to neighborhoods showed significant rural-urban differences.     

Mortality, lifestyle and socio-economic status

This paper uses the British Health and Lifestyle Survey (1984-1985) data and the longitudinal follow-up of May 2003 to investigate the determinants of premature mortality in Great Britain and the contribution of lifestyle choices to socio-economic inequality in mortality. A behavioural model, which relates premature mortality to a set of observable and unobservable factors, is considered. A maximum simulated likelihood (MSL) approach for a multivariate probit (MVP) is used to estimate a recursive system of equations for mortality, morbidity and lifestyles. Health inequality is explored using the Gini coefficient and a decomposition technique. The decomposition analysis for predicted mortality shows that, after allowing for endogeneity, lifestyles contribute strongly to inequality in mortality, reducing the direct role of socio-economic status. This contradicts the view, which is widely held in epidemiology, that lifestyles make a relatively minor contribution to observed socio-economic gradients in health.     

Relations between Internet use, socio-economic status (SES), social support and subjective health

This study aimed to explore relations between Internet use, socio-economic status (SES), social support and subjective health. Participants were from representative samples between 15 and 80 years of age from seven different European countries. Two different survey datasets were used: (i) eHealth trends (eHT; N = 7934) and (ii) the European social survey (ESS2; N = 11248). Internet users who had used the Internet for health purposes were compared with Internet users who had not used it for health purposes. Structural equation modelling was used to assess the relationships between SES, Internet use, social support and subjective health. Use of other media was compared to Internet use in relation to social support and subjective health. Internet use was found to be more closely related to social support and subjective health than use of other media. Internet use was also found to be a plausible mediator between SES and subjective health, especially through interacting with social support.     

Gender and age differences in lifestyle factors related to hypertension in middle-aged civil service employees

The aim of this study is to identify lifestyle factors related to hypertension in man and woman workers, and to investigate age and gender differences in the relationships of the factors. From 6,000 civil service employees (4,937 men and 1,063 women) aged 40-69 years, information on lifestyle-related factors such as stress, exercise habits, preference for salty taste, alcohol drinking and smoking habits, and body mass index, as well as age and family history of hypertension was obtained through self-administered questionnaires in 1997. Hypertension was defined as either a systolic blood pressure > or = 140 mmHg, a diastolic blood pressure > or = 90 mmHg, or undergoing treatment for hypertension, and was present by 37.0% in men and 19.6% in women. Only body mass index was a significant lifestyle-related risk factor common to both genders with an odds ratio and its 95% confidence interval in parentheses of 2.2 (2.0-2.5) for men and 3.2 (2.3-4.6) for women. Men and women who preferred salty taste showed multivariate adjusted odds ratios of 0.9 (0.8-1.1) and 1.5 (1.1-2.2) for hypertension, respectively. In the stratified subanalysis, women aged 50 years and over had a significant odds ratio of 2.7 (1.5-4.9), whereas women aged 40-49 years and men of all age classes failed to show significant relationships. Salt intake was suggested to be a key factor for hypertension particularly for women after menopause.     

Isolation, social support, life events and health status

Research on the influence of social networks and social support on health status, conducted in English-speaking countries over the past decade, is not yet widespread in France. A review of the literature reveals that this social support has undeniable effects on mental health, and less obvious effects on physical health; it also stresses the major conceptual and methodological problems encountered in socio-epidemiological approaches. It would appear necessary to construct an overall model integrating life events, coping abilities and individual psychological factors; Social support is considered as a function of social networks, fulfilling roles of emotional support, material help, information provider, egostrengthener and social normalizer. Its mechanisms for dealing with stress, especially the buffer-role hypothesis, are also discussed.     

Perceived stress,internal resources,and social support as determinants of mental health among young adults

BACKGROUND: Mental health is a central determinant of quality of life. While psychiatric morbidity of populations has been studied extensively, the role of perceived stress, social support, and internal resources as determinant of health is still poorly understood. METHODS: We surveyed 2000 randomly selected university students. Perceived stress was measured by the Brief Encounter Psychosocial Instrument, social support by the Duke-UNC Functional Social Support Questionnaire, internal resources (mastery and self-esteem) by a brief version of the Pearlin coping questionnaire. Linear regression models were used to explore the relationships between these variables and mental health, based on the SF-12 health survey. RESULTS: After two reminders, 1257 students answered the questionnaire. In bivariate analysis, mental health was negatively associated with stress and positively associated with internal resources and social support (all p-values < 0.001). In multiple regression analysis, internal resources were positively associated with mental health, and buffered the negative impact of stress on mental health. Internal resources and stress mediated the positive impact of social support on mental health. CONCLUSIONS: Our data confirm that perceived stress is an important risk factor for low mental health and suggest that mastery and self-esteem are important protective factors of mental health among young adults.     

The relationship of lifestyle factors, personal character, and mental health status of employees of a major Japanese electrical manufacturer

Summary  To examine the relationship lifestyle factors, personal character, mental health status, and job strain a self-administered questionnaire survey was conducted among employees of a leading electrical manufacturing company in Japan. A total of 2,327 workers (Male=1,668, Female=659) responded to the survey. We analyzed the relationships of health practices based on such factors as: Free child (FC) from the Egogram, the Working-life satisfaction, and the General Health Questionnaire-28 through Path-analysis techniques. The following results were obtained: The mental health status was significantly affected by such factors as health practices, Working-life satisfaction, personal character (FC), life satisfaction, and age. Health practices and personal character (FC) showed a direct relationship to the mental health status and an indirect relationship to the Working-life satisfaction and life satisfaction. The variances accounting for mental health status were 41.8% in male workers and 43.8% in female workers. Path-analysis data suggested that mental health status was affected about 40% by lifestyle, personal character, Working-life satisfaction, and life satisfaction. It was suggested that there might be important factors affecting mental health status but which are unknown to us by as much as 60% in the present day. These findings suggested the necessity of further investigation of the relationship among lifestyle factors, mental health status, and job strain among employees of a reputable company in the present day.     

Physical and social environmental factors related to co-occurrence of unhealthy lifestyle behaviors

Previous work identifying determinants of co-occurrence of behavioral risk factors have focused on their association with individuals' characteristics with scant attention paid to their relationship to contextual factors. Data came from 21,007 individuals ≥15 years of age who participated in the cross-sectional 2011–2012 Spanish National Health Survey. Two indicators were defined by tobacco consumption, alcohol intake, diet, physical activity, and body mass index. The first indicator, based on dichotomized measures, ranges from 0 to 5. The second one (unhealthy lifestyle index), ranges from 0 to 15, with 0 denoting the healthiest score. Among the determinants, we examined social support, five perceived characteristics of the neighborhood, and the socioeconomic deprivation index of the census tract of residence. Data were analyzed using multilevel linear and logistic regression models adjusted for the main sociodemographic characteristics. Using the dichotomized indicator, the probability of having 3–5 risk factors versus <3 factors was associated with low social support (Odds Ratio [OR] 1.50; 95% Confidence Interval [CI]: 1.25–1.80). Issues surrounding neighborhood cleanliness (OR = 1.18; 95%CI: 1.04–1.33), air pollution (OR = 1.38; 95%CI: 1.16–1.64), and street crime (OR = 1.21; 95%CI: 1.03–1.42) were associated with determinants of co-occurrence. Risk factors co-occurrence increased as deprivation level increased: the OR for the highest deprivation quintile versus the lowest was 1.30 (95%CI: 1.14–1.48). Similar results were observed when using the unhealthy lifestyle index. Poorer physical and social environments are related to greater co-occurrence of risk factors for chronic diseases. Health promotion interventions targeting the prevention of risk factors should consider the contextual characteristics of the neighborhood environment.     

Association of smoking with other lifestyle factors and mental health status of Japanese factory workers

A self-administered questionnaire survey was conducted among factory workers in Japan. The questionnaire included items concerning eight health practices recommended by Morimoto and the General Health Questionnaire-28. Data from 1598 male workers were analyzed. There were few differences in comprehensive health status due to smoking status, but smokers under the age of 30 years had worse lifestyle habits than nonsmokers with regard to favorable drinking and eating breakfast, and smokers between the ages 30 and 44 years had worse lifestyle habits with regard to favorable drinking and eating breakfast, and better habits regarding sleeping hours and working hours. Smokers under 30 showed worse mental health status than ex-smokers with regard to social dysfunction, though there was little difference between those aged from 30 to 44 and those 45 and older. The results suggested the importance of considering the difference in lifestyle and mental health status due to smoking status when providing advice for improving health habits.     

Healthy-equivalent income, a tool to analyze social inequalities in health

This paper argues that the analysis of social inequalities in health should be part of the general analysis of inequalities in living standards. An index of living standards is proposed, namely, healthy-equivalent income, which takes account of individual preferences about the relative importance of health among other dimensions. As it is shown, the criterion which evaluates social situations by looking at the distribution of healthy-equivalent incomes, giving priority to the worst-off in this distribution, is the only one that satisfies basic conditions of efficiency and equity. This approach is compared to related empirical approaches (cost-benefit analysis, health concentration curve). It is argued that the correlation between health and income (or socio-economic status) does deteriorate the distribution of healthy-equivalent incomes, but does not deserve the excessive amount of attention devoted to it in social epidemiology because it is only a component of inequalities in living standards. More specifically, improving the situation of the worst-off in terms of healthy-equivalent income should be adopted as the objective of health public policies, instead of reducing this correlation, which is not a defensible objective.     

Socio-economic status, health and lifestyle

The role of lifestyle in mediating the relationship between socio-economic characteristics and health has been discussed extensively in the epidemiological and economic literatures. Previous analyses have not considered a formal framework incorporating unobservable heterogeneity. In this paper, we develop a simple economic model in which health is determined (partially) by lifestyle, which depends on preferences, budget and time constraints and unobservable characteristics. We estimate a recursive empirical specification consisting of a health production function and reduced forms for the lifestyle equations using Maximum Simulated Likelihood (MSL) for a multivariate probit (MVP) model with discrete indicators of lifestyle choices and self-assessed health (SAH) on British panel data from the 1984 and 1991 Health and Lifestyle Survey (HALS). We find that sleeping well, exercising, and not smoking in 1984 have dramatic positive effects on the probability of reporting excellent or good SAH in 1991, and that these effects are much larger having accounted for endogeneity. The failure of epidemiological analyses to account for unobserved heterogeneity can explain their low estimates of the relevance of lifestyle in the socio-economic status-health relationship. Indicators for prudent alcohol consumption and eating breakfast in 1984 are not found to be statistically significant determinants of SAH in 1991.     

Gender,socio-economic status and metabolic syndrome in middle-aged and old adults

Background  

Studies that addressed social and economic determinants of cardiovascular diseases, consistently showed an increase prevalence of the individual features of metabolic syndrome in the lower socio-economic strata. Thus, this study aimed to evaluate the association between social class and metabolic syndrome in a sample of urban middle-aged and old Portuguese adults.     

Cigarette smoking,health status,socio-economic status and access to health care in diabetes mellitus: a cross-sectional survey

Background  

In diabetes mellitus, cigarette smoking is associated with increased risk of cardiovascular mortality and microvascular complications. We evaluated cigarette smoking in people with diabetes mellitus in a socio-economically deprived area.     

Socioeconomic status,social support,oral health beliefs,psychosocial factors,health behaviours and health-related quality of life in adolescents

Quality of Life Research - This study assessed the relationships between socioecononic status (SES), social support, oral health beliefs, psychosocial factors, health-related behaviours and...     

An intervention study to promote self-improvement of lifestyle in a Japanese community: a new health support program

Objective  

To assess the effectiveness of two health support programs developed to improve the lifestyle of community residents through exercise, nutrition-based health education, and group dynamics.     

Influence of social support on health among gender and socio-economic groups of adolescents

BACKGROUND: The influence of social support on health was explored among gender and socio-economic groups with the aim of contributing to the explanation of socio-economic health differences among Slovak adolescents. METHODS: The sample consisted of 2616 Slovak adolescents (52.4% male, 47.6% female, mean age 15 years). The data were assessed by a self-reported questionnaire including measures of social support, socio-economic status and health. RESULTS: There are significant gender differences in social support, which are unfavourable for males. On the other hand, there are significant gender differences in health, unfavourable for females. Low social support is significantly related to worse health. There are significant socio-economic differences in both health and social support, which are unfavourable for lower socio-economic groups. Three groups, females, adolescents from lower socio-economic groups, and also adolescents reporting low social support, less frequently consider their health as excellent or very good. Females suffer from more health complaints, report worse psychological health, vitality and mental health in comparison to males, to adolescents from higher socio-economic groups, and to adolescents reporting high social support. Males and adolescents from lower socio-economic groups more frequently reported low social support in comparison to females and adolescents from higher socio-economic groups. No significant differences in the influence of social support on health among gender and socio-economic groups of adolescents were confirmed. CONCLUSION: Social support is related to health and it is unequally distributed among gender and socio-economic groups. Social support had a positive impact on health, but this effect was independent of gender and socio-economic groups.     

Vitamin D status is associated with sociodemographic factors, lifestyle and metabolic health

Purpose

Low serum 25(OH)D concentration has been shown to predict the occurrence of several chronic diseases. It is, however, still unclear whether the associations are causal or due to confounding. The aim of this study was to investigate the associations between serum 25(OH)D concentration and sociodemographic, lifestyle and metabolic health-related factors.

Methods

The study population comprised 5,714 men and women, aged 30–79 years, from the Health 2000 Survey representing the Finnish population. Serum 25(OH)D concentration was determined by radioimmunoassay from serum samples frozen at ?70 °C. Sociodemographic, lifestyle and metabolic factors were determined by questionnaires, interviews and measurements. Linear regression was used to assess the associations between serum 25(OH)D and the factors studied.

Results

The mean serum 25(OH)D concentration was 45.3 nmol/l and it varied between categories of sociodemographic, lifestyle and metabolic health variables. Older age, being married or cohabiting and higher education were related to higher serum 25(OH)D concentration. Those with the healthiest lifestyle estimated by a lifestyle index based on body mass index, physical activity, smoking, alcohol consumption and diet had 15.8 nmol/l higher serum 25(OH)D concentration compared to those with the unhealthiest lifestyle. Of the indicators of metabolic health, only waist circumference and HDL cholesterol were significantly associated with 25(OH)D after adjustment for sociodemographic, lifestyle and other metabolic health factors.

Conclusion

This study suggests that serum 25(OH)D concentration is associated with a multitude of sociodemographic, lifestyle and metabolic health factors. Thus, it is possible that such factors confound associations observed between serum 25(OH)D concentration and chronic diseases.     

Obesity and cardio-metabolic risk factors in urban adults of Benin: Relationship with socio-economic status,urbanisation, and lifestyle patterns

Background  

There is a dearth of information on diet-related chronic diseases in West Africa. This cross-sectional study assessed the rate of obesity and other cardiovascular disease (CVD) risk factors in a random sample of 200 urban adults in Benin and explored the associations between these factors and socio-economic status (SES), urbanisation as well as lifestyle patterns.     

Leisure-time physical activity and related lifestyle characteristics among middle-aged Japanese. Japan Lifestyle Monitoring Study Group

The present study describes leisure-time physical activity status and related lifestyle factors in middle-aged Japanese. Data were obtained from 1,893 (905 men, 988 women) participants aged 40-69 years who had either been selected from a public registry or who had visited a healthcare facility. Subjects responded to a self-administered questionnaire and were interviewed using an assessment method for leisure-time and on-the-job physical activity within the last 12 months by trained interviewers. According to the leisure-time physical activity score, men and urban residents tended to engage in more leisure-time physical activity than did women and rural residents, respectively. Leisure-time physical activity tended to be inversely associated with on-the-job physical activity in all cases aside from women in urban regions, and also to be associated with higher levels of education in rural regions. Subjects engaging in more leisure-time physical activity had higher odds ratios of certain lifestyle factors, indicating a healthy lifestyle that included a variety of foods in their diet and a subjective sense of wellness in both men and women, in addition to non-smoking and drinking milk in men. These results suggested that leisure-time physical activity is influenced by socio-environmental factors, and that it is accompanied by other healthy behavior.