Do welfare regimes matter for oral health? A multilevel analysis of European countries

While the role of political factors on population health has recently received increasing attention, relatively little is known in that respect for oral health. We aimed to assess the influence of welfare state regimes on the variation in adult oral health between European countries, building on the existing literature by using a multilevel approach. Our analysis also explored how the oral health of people with different socioeconomic position was influenced by living in five different welfare state regimes. We analysed data from the Eurobarometer survey 2009. The main outcome was no functional dentition, defined as having fewer than 20 natural teeth. Age, gender, marital status, education and occupational social class were the individual-level explanatory variables, while welfare regimes, GDP per capita and GDP annual growth were the country-level variables. Multilevel logistic regression models were fitted with individuals nested within countries. Results revealed that country-level characteristics accounted for 8.1% of the variation in oral health. Adults in all welfare regimes were more likely to have poorer oral health than their counterparts in the Scandinavian regime, with those in Eastern countries being 6.94 (95% CI: 3.62–12.67) times as likely to lack a functional dentition as adults in Scandinavian countries. The variation at country-level reduced significantly when welfare regimes were introduced into the model (from 0.57 to 0.16; 72% reduction), indicating that welfare regime explained much of the variation in the outcome among European countries. Finally, adults with less education and lower occupational level were more likely to have no functional dentition, especially in the Eastern and Bismarckian welfare regimes.     

Does reporting behaviour bias the measurement of social inequalities in self-rated health in Indonesia? An anchoring vignette analysis

Purpose

Studies on self-rated health outcomes are fraught with problems when individuals’ reporting behaviour is systematically biased by demographic, socio-economic, or cultural factors. Analysing the data drawn from the Indonesia Family Life Survey 2007, this paper aims to investigate the extent of differential health reporting behaviour by demographic and socio-economic status among Indonesians aged 40 and older (\(N = 3735\)).

Methods

Interpersonal heterogeneity in reporting style is identified by asking respondents to rate a number of vignettes that describe varying levels of health status in targeted health domains (mobility, pain, cognition, sleep, depression, and breathing) using the same ordinal response scale that is applied to the self-report health question. A compound hierarchical ordered probit model is fitted to obtain health differences by demographic and socio-economic status. The obtained regression coefficients are then compared to the standard ordered probit model.

Results

We find that Indonesians with more education tend to rate a given health status in each domain more negatively than their less-educated counterparts. Allowing for such differential reporting behaviour results in relatively stronger positive education effects.

Conclusion

There is a need to correct for differential reporting behaviour using vignettes when analysing self-rated health measures in older adults in Indonesia. Unless such an adjustment is made, the salutary effect of education will be underestimated.

     

Does social participation improve self-rated health in the older population? A quasi-experimental intervention study

Social participation has been linked to healthy aging and the maintenance of functional independence in older individuals. However, causality remains tenuous because of the strong possibility of reverse causation (healthy individuals selectively participate in social activities). We describe a quasi-experimental intervention in one municipality of Japan designed to boost social participation as a way of preventing long-term disability in senior citizens through the creation of ‘salons’ (or community centers). In this quasi-experimental intervention study, we compared 158 participants with 1391 non-participants in salon programs, and examined the effect of participation in the salon programs on self-rated health. We conducted surveys of community residents both before (in 2006) and after (in 2008) the opening of the salons. Even with a pre/post survey design, our study could be subject to reverse causation and confounding bias. We therefore utilized an instrumental variable estimation strategy, using the inverse of the distance between each resident's dwelling and the nearest salon as the instrument. After controlling for self-rated health, age, sex, equivalized income in 2006, and reverse causation, we observed significant correlations between participation in the salon programs and self-rated health in 2008. Our analyses suggest that participation in the newly-opened community salon was associated with a significant improvement in self-rated health over time. The odds ratio of participation in the salon programs for reporting excellent or good self-rated health in 2008 was 2.52 (95% CI 2.27–2.79). Our study provides novel empirical support for the notion that investing in community infrastructure to boost the social participation of communities may help promote healthy aging.     

The impact of neighborhood social capital on life satisfaction and self-rated health: A possible pathway for health promotion?

Neighborhood social capital has repeatedly been linked to favorable health-outcomes and life satisfaction. However, it has been questioned whether it’s impact on health has been over-rated. We aim to investigate relationships between neighborhood social capital and self-rated health (SRH) and life satisfaction (LS) respectively, both directly and indirectly mediated via Sense of Coherence and self-esteem. Based on a cross-sectional population-survey (N=865) in a medium size Norwegian municipality, we specified a structural equation model (SEM) including the above-listed variables, while controlling for gender, age, education, income, and employment status. The applied model explains more variance in LS (46%) than in SRH (23%). Social capital has a stronger impact on life satisfaction than on health. The indirect pathway via SOC had the highest impact on life satisfaction, but no significant relationship to SRH. Self-rated health was more tightly linked to personal background variables. Enhancing social capital in the neighborhood might be a beneficial strategy to promote life satisfaction, as well as strengthening sense of coherence even in healthy communities     

Does social cohesion modify the association between area income deprivation and mental health? A multilevel analysis

BACKGROUND: Despite the increasing belief that the places where people live influence their health, there is surprisingly little consistent evidence for their associations with mental health. We investigated the joint effect of community and individual-level socio-economic deprivation and social cohesion on individual mental health status. METHODS: Multilevel analysis of population survey data on 10,653 adults aged 18-74 years nested within the 325 census enumeration districts in Caerphilly county borough, Wales, UK. The outcome measure was the Mental Health Inventory (MHI-5) subscale of the SF-36 instrument. A social cohesion subscale was derived from a factor analysis of responses to the Neighbourhood Cohesion scale and was modelled at individual and area level. Area income deprivation was measured by the percentage of low income households. RESULTS: Poor mental health was significantly associated with area-level income deprivation and low social cohesion after adjusting for individual risk factors. High social cohesion significantly modified the association between income deprivation and mental health: the difference between the predicted mean area mental health scores at the 10th and 90th centiles of the low income distribution was 3.7 in the low cohesion group and 0.9 in the high cohesion group (difference of the difference in means = 2.8, 95% CI: 0.2, 5.4). CONCLUSIONS: Income deprivation and social cohesion measured at community level are potentially important joint determinants of mental health. Further research on the impact of the social environment on mental health should investigate causal pathways in a longitudinal study.     

Does place matter for cancer survival in Norway? A multilevel analysis of the importance of hospital affiliation and municipality socio-economic resources

Multilevel discrete-time hazard models for cancer mortality in cancer patients were estimated from register and census data to find out whether hospital affiliation and municipality socio-economic resources had an impact on cancer survival in Norway in the 1990s. Affiliation to a small local hospital was a disadvantage in only one health region. There were also other differences between health regions. Most notably, those who lived in Oslo and Southern Norway had a relatively poor survival, given the size of the nearest hospital. In addition to confirming the better prognosis for patients who themselves had high education, it was found that survival improved with increasing average education. This was primarily a result of earlier diagnosis. The impact of the economic situation was less clear. While a high average income was unrelated to mortality, as opposed to the beneficial impact of high individual income, a high unemployment rate, picking up also effects of individual unemployment, had an adverse effect.     

Does the state you live in make a difference? Multilevel analysis of self-rated health in the US

This paper investigates the different sources of variation between US states in self-rated health using multilevel statistical procedures. The different sources that are considered are based on individual- and state-level factors. Data for the analysis comes from the 1993-94 Behavioral Risk Factor Surveillance System and the 1986-90 General Social Surveys. Results show that individual-level factors (such as low income, being black, smoking) are strongly associated with self-rated poor health. Significant variation, however, remain between states after allowing for individual characteristics. Crucially, between-state variation in self-rated health is different for different income groups. State-level contextual effects are found for per-capita median-income and 'social capital'. While not strong, there seems to be a differential impact of state income-inequality on high-income groups, such that the affluent report better health from living in high inequality states. The paper substantiates the need to connect individual health to their macro socioeconomic context. Importantly, it is argued that without adopting an explicitly multilevel approach, the debate on linkages between individual health and income-inequality/social capital cannot be adequately addressed.     

Does socioeconomic status affect the association of social relationships and health? A moderator analysis

Background  

Social relations have repeatedly been found to be an important determinant of health. However, it is unclear whether the association between social relations and health is consistent throughout different status groups. It is likely that health effects of social relations vary in different status groups, as stated in the hypothesis of differential vulnerability. In this analysis we explore whether socioeconomic status (SES) moderates the association between social relations and health.     

Does the association between self-rated health and mortality vary by social class?

Self-rated health (SRH) predicts future mortality. Individuals in different social classes with similar physical health status may have different reference levels and criteria against which they judge their health, therefore the SRH–mortality relationship may vary according to social class. We examine the relationship between SRH and mortality by occupational social class in a prospective study of 22,457 men and women aged 39–79 years, without prevalent disease, living in the general community in Norfolk, United Kingdom, recruited using general practice age–sex registers in 1993–1997 and followed up for an average of 10 years. As expected, SRH was related to subsequent mortality. The age and sex adjusted hazard ratio for mortality for those with poor compared to those with excellent SRH was 4.35 (95% confidence interval 3.38–5.59, P < 0.001). The prevalence of poor or moderate SRH was higher in manual than in non-manual classes. However, SRH was similarly related to mortality in manual and non-manual classes: when non-manual classes are compared with manual classes for each category of SRH, the 95% confidence intervals for the mortality hazard ratios overlap. There was no evidence of an interaction between social class and SRH in either men or women. Thus in this population, SRH appears to predict mortality in a similar manner in non-manual and manual classes.     

Is social capital the key to inequalities in health?

There has been vigorous debate between the "social capital" and "neomaterialist" interpretations of the epidemiological evidence regarding socioeconomic determinants of health. We argue that levels of income inequality, social capital, and health in a community may all be consequences of more macrolevel social and economic processes that influence health across the life course. We discuss the many reasons for the prominence of social capital theory, and the potential drawbacks to making social capital a major focus of social policy. Intervening in communities to increase their levels of social capital may be ineffective, create resentment, and overload community resources, and to take such an approach may be to "blame the victim" at the community level while ignoring the health effects of macrolevel social and economic policies.     

The European health divide: a matter of financial or social capital?

The 'European east--west health divide' has been documented both for mortality and for self-rated health. The reason for this divide, however, remains to be explained. The aim of this study is, firstly, to investigate whether in 1995-97 differences in self-rated health persisted between countries in central and eastern Europe, the former Soviet Union, and western Europe. A further aim is to try to explain these differences with reference to people's financial status and social capital. This study found substantial differences in self-rated health between countries in western Europe, in central and eastern Europe, and in the former Soviet Union (where self-rated health seems to be poorest in general). There were also substantial differences between areas in terms of economic and social capital, with western Europe doing better in all the analysed circumstances. In economic terms people in the former Soviet Union seemed to be more dissatisfied than those living in central and eastern Europe. When one looks at differences in social capital between the two post-communist areas the picture is more mixed. Economic satisfaction was demonstrated to have a strong and significant effect on people's self-rated health, with a higher satisfaction reducing the odds of 'poor' health. When this factor was controlled for the area, differences in self-rated health were reduced dramatically, for both men and women. Organisational activity (men only), trust in people, and confidence in the legal system also reduced the odds of 'less than good health', but were not as important in explaining the health differences between areas. One can conclude that economic factors as well as some aspects of social capital play a role for area differences in self-rated health. Of these it would appear that economic factors are the more important.     

Does the multidimensional nature of Super Profiles help district health authorities understand the way social capital affects health?

BACKGROUND: Social capital describes the notion that the social processes in an area can lead to benefits in health. As Super Profiles describe the social character of an area and they are easy for health authorities to use, they could provide a simple method for local assessment of how social organization affects health. METHODS: We calculated the expected mean birthweight for the enumeration districts of Birmingham based upon marital status, registration details of the child, year of birth, the mother's country of birth, fetal sex and deprivation as judged by the Townsend score using data from 138,696 live-born singleton births for the years 1986-1996 inclusive. We classified enumeration districts into Target Markets, derived from Super Profiles. For each Target Market, we calculated the observed mean birthweight and the difference and 95 per cent confidence interval between the observed and expected birthweights. We used information in Super Profiles to speculate about the social processes that led to some Target Markets having mean birthweights that were significantly different from those expected. RESULTS: Fifteen of the 40 Target Markets had significant differences between predicted and observed mean birthweight, but these differences were less than 50 g. There were no common characteristics of Target Markets that were consistently advantageous for birthweight and none that were disadvantageous. CONCLUSION: The information in the Super Profiles does not illuminate the way that social processes affect health, and the variation in mean birthweight between areas explained by social processes as measured by Super Profiles is small.     

Does the predictive power of self-rated health for subsequent mortality risk vary by socioeconomic status in the US?

BACKGROUND: The purpose of this study is to test whether the predictive power of an individual's self-rated health (SRH) on subsequent mortality risk differs by socioeconomic status (SES) in the United States. METHODS: We use the National Health Interview Survey 1986-94 linked to Multiple Cause of Death Files 1986-97 (NHIS-MCD). Analyses are based on non-Hispanic Black and White adults 25 and older (n = 358,388). Cox proportional hazard models are used to estimate the effect of SRH on mortality risk during follow-up. Interactions of SRH and level of education and SRH and level of income are used to assess differences in the predictive power of SRH for subsequent mortality risk. RESULTS: The effect of SRH on subsequent mortality risk differs by level of education and level of income. Lower health ratings are more strongly associated with mortality for adults with higher education and/or higher income relative to their lower SES counterparts. CONCLUSIONS: Our findings suggest that individuals with different education or income levels may evaluate their health differently with respect to the traditional five-point SRH scale, and hence their subjective health ratings may not be directly comparable. These results have important implications for research that tries to quantify and explain socioeconomic inequalities in health based on self-rated health.     

Does social support mediate or moderate socioeconomic differences in self-rated health among adolescents?

Objective

Social support is assumed to be a protective social determinant of health. The aim of this cross-sectional study was to explore whether social support from the father, mother and friends mediates or moderates the association between socioeconomic position and self-rated health among adolescents.

Methods

The sample consisted of 1,863 secondary school students from the Kosice region in Slovakia (mean age 16.85; 53.3% females, response rate 98.9%). We assessed the mediation and moderation effects of social support from the mother, father and friends on the relation between socioeconomic position and self-rated health, performing binary logistic regression models. Socioeconomic position was measured by parents?? education, the family affluence scale and financial strain.

Results

Social support from the father mediated the association between family affluence and self-rated health among both males and females and the association between financial strain and self-rated health among males only. No moderating effect of social support on socioeconomic differences in self-rated health was found.

Conclusion

Father involvement seems to have the potential to mediate socioeconomic differences in health during adolescence.     

Whose health is affected by income inequality? A multilevel interaction analysis of contemporaneous and lagged effects of state income inequality on individual self-rated health in the United States

The empirical relationship between income inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state income inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state income inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state income inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state income inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17-1.45) in a conditional model that included individual age, sex, race, marital status, education, income, and health insurance coverage as well as state median income. With few exceptions, we did not find strong statistical support for differential effects of state income inequality across different population groups. For instance, the relationship between state income inequality and poor health was steeper for whites compared to blacks (OR=1.34; 95% CI: 1.20-1.48) and for individuals with incomes greater than $75,000 compared to less affluent individuals (OR=1.65; 95% CI: 1.26-2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state income inequality on individual self-rated poor health. To the extent that contemporaneous state income inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state income inequality on health. At the same time, the contemporaneous main effect of state income inequality remained statistically significant even when conditioned for past levels of income inequality and median income of states.     

Does variation in general practitioner (GP) practice matter for the length of sick leave? A multilevel analysis based on Norwegian GP-patient data

In Norway, as in many countries, the national insurance system is under economic stress from demographic change impacting on the pensions versus contributions balance, and an increasing number of disability and sickness benefit claimants. The general practitioner (GP) is responsible for assessing work capacity and issuing certificates for sick leave based on an evaluation of the patient. Although many studies have analyzed certified sickness absence and predictive factors, no studies assess its variation between patients, GPs or geographical areas within a multilevel framework. Using a rich Norwegian matched patient-GP data set and employing a multilevel random intercept model, the study attempts to disentangle patient, GP and municipality-level variation in the certified sickness absence length for Norwegian workers in 2003. We find that most observed patient and GP characteristics are significantly associated with the length of sick leave (LSL) and medical diagnosis is an important observed factor explaining certified sickness durations. However, 98% of the unexplained variation in the LSL is attributed to patient factors rather than influenced by variation in GP practice or differences in municipality-level characteristics. Our findings indicate that GPs practice variation does not matter much for the patients' LSL. Our results are compatible with a high degree of patient involvement in current general practice. Based on this understanding one may infer that GPs play an advocate role for their patients in Norway, where the patients' own wishes are important when decisions are made.     

Do social policies and political context matter for health in the United Kingdom?

This U.K. case study combines lessons from historical assessments with new empirical analyses of trends over the last decade to inform an appraisal of the impact of social actions on health. The empirical analyses examine life expectancy in the 354 local government councils in England by first identifying those that have better or worse health than expected fromtheir socioeconomic profile, and then selecting paired sets of "overachievers" and "underachievers" for more in-depth analysis. The findings taken as a whole provide evidence that social policies and political context do indeed matter for health. The historical material from the first industrial revolution, in particular, provides some of the most compelling evidence for this proposition. The empirical analyses over the last decade found a very powerful inverse association: the more deprived the local council, the lower the life expectancy of the population within that locality. However, even for the same level of deprivation and socioeconomic characteristics, some councils were doing much better than others in terms of health: for example, more than three years difference in life expectancy for carefully matched "urban fringe" councils. The article then examines the councils' political makeup and hence their likely policy perspective.     

Changing places? A comparative analysis of area-based health trends in Scotland through the 1980s and 1990s

OBJECTIVES: Have places in Scotland with the worst/best levels of health and the worst/best experience of health determinants changed since the early 1980s? Twenty-year trends and local-level changes in a selection of health-related indicators were examined to answer this question. STUDY DESIGN AND METHODS: Routine data for seven health-related indicators, principally derived from Scottish government 'social justice milestones', were collated and analysed at postcode-sector level across four 5-year periods covering the 1980s and 1990s. Analysis was carried out by decile, deprivation quintile, individual postcode sector and for selected 'regeneration areas'. RESULTS: There was little change in the ranking of areas with the worst and best health in Scotland over the 20-year period. The worst and best initial deciles remained in those positions throughout, while analysis by deprivation showed that the most disadvantaged areas had become relatively worse over the period. The regeneration areas, with one exception, showed little long-term improvement across the indicators. However, a number of postcode sectors across Scotland did buck this overall trend. CONCLUSIONS: This study confirmed the enduring nature of health differences between areas in Scotland, and provided further evidence of widening health inequalities between affluent and deprived areas. The positive experiences of a small number of areas may warrant further investigation since they may hold important lessons for area-based health improvement. The research highlights the potential of this type of analysis to monitor and evaluate area-based initiatives.     

Individual and neighbourhood determinants of social participation and social capital: a multilevel analysis of the city of Malmö, Sweden

The aim of this study was to analyse the impact of neighbourhood on individual social capital (measured as social participation). The study population consisted of 14,390 individuals aged 45-73 that participated in the Malm? diet and cancer study in 1992-1994, residing in 90 neighbourhoods of Malm?, Sweden (population 250,000). A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second level, was performed. The study analysed the effect (intra-area correlation and cross-level modification) of the neighbourhood on individual social capital after adjustment for compositional factors (e.g. age, sex, educational level, occupational status, disability pension, living alone, sick leave, unemployment) and, finally, one contextual migration factor. The prevalence of low social participation varied from 23.0% to 39.7% in the first and third neighbourhood quartiles, respectively. Neighbourhood factors accounted for 6.3% of the total variance in social participation, and this effect was reduced but not eliminated when adjusting for all studied variables (-73%), especially the occupational composition of the neighbourhoods (-58%). The contextual migration variable further reduced the variance in social participation at the neighbourhood level to some extent. Our study supports Putnam's notion that social capital, which is suggested to be an important factor for population health and possibly for health equity, is an aspect that is partly contextual in its nature.