Does health literacy mediate the relationship between socioeconomic status and health related outcomes in the Belgian adult population?

BACKGROUND: Health literacy (HL) has been put forward as a potential mediator through which socioeconomic status (SES) affects health. This study explores whether HL mediates the relation between SES and a selection of health or health-related outcomes. METHODS: Data from the participants of the Belgian health interview survey 2018 aged 18 years or older were individually linked with data from the Belgian compulsory health insurance (n = 8080). HL was assessed with the HLS-EU-Q6. Mediation analyses were performed with health behaviour (physical activity, diet, alcohol and tobacco consumption), health status (perceived health status, mental health status), use of medicine (purchase of antibiotics), and use of preventive care (preventive dental care, influenza vaccination, breast cancer screening) as dependent outcome variables, educational attainment and income as independent variables of interest, age and sex as potential confounders and HL as mediating variable. RESULTS: The study showed that unhealthy behaviours (except alcohol consumption), poorer health status, higher use of medicine and lower use of preventive care (except flu vaccination) were associated with low SES (i.e., low education and low income) and with insufficient HL. HL partially mediated the relationship between education and health behaviour, perceived health status and mental health status, accounting for 3.8-16.0% of the total effect. HL also constituted a pathway by which income influences health behaviour, perceived health status, mental health status and preventive dental care, with the mediation effects accounting for 2.1-10.8% of the total effect. CONCLUSIONS: Although the influence of HL in the pathway is limited, our findings suggest that strategies for improving various health-related outcomes among low SES groups should include initiatives to enhance HL in these population groups. Further research is needed to confirm our results and to better explore the mediating effects of HL.

QALY losses for chronic diseases and its social distribution in the general population: results from the Belgian Health Interview Survey.

BACKGROUND: The burden of chronic diseases is rapidly rising, both in terms of morbidity and mortality. This burden is disproportionally carried by socially disadvantaged population subgroups. Quality-adjusted life years (QALYs) measure the impact of disease on mortality and morbidity into a single index. This study aims to estimate the burden of chronic diseases in terms of QALY losses and to model its social distribution for the general population. METHODS: The Belgian Health Interview Survey 2013 and 2018 provided data on self-reported chronic conditions for a nationally representative sample. The annual QALY loss per 100,000 individuals was calculated for each condition, incorporating disease prevalence and health-related quality of life (HRQoL) data (EQ-5D-5L). Socioeconomic inequalities, based on respondents' socioeconomic status (SES), were assessed by estimating population attributable fractions (PAF). RESULTS: For both years, the largest QALY losses were observed in dorsopathies, arthropathies, hypertension/high cholesterol, and genitourinary problems. QALY losses were larger in women and in older individuals. Individuals with high SES had consistently lower QALY loss when facing a chronic disease compared to those with low SES. In both years, a higher PAF was found in individuals with hip fracture and stroke. In 2013, the health inequality gap amounts to 33,731 QALYs and further expanded to 42,273 QALYs in 2018. CONCLUSION: Given that chronic diseases will rise in the next decades, addressing its burden is necessary, particularly among the most vulnerable (i.e. older persons, women, low SES). Interventions in these target groups should get priority in order to reduce the burden of chronic diseases.

Unit Response and Costs in Web Versus Face-To-Face Data Collection: Comparison of Two Cross-sectional Health Surveys.

BACKGROUND: Potential is seen in web data collection for population health surveys due to its combined cost-effectiveness, implementation ease, and increased internet penetration. Nonetheless, web modes may lead to lower and more selective unit response than traditional modes, and this may increase bias in the measured indicators. OBJECTIVE: This research assesses the unit response and costs of a web study versus face-to-face (F2F) study. METHODS: Alongside the Belgian Health Interview Survey by F2F edition 2018 (BHISF2F; net sample used: 3316), a web survey (Belgian Health Interview Survey by Web [BHISWEB]; net sample used: 1010) was organized. Sociodemographic data on invited individuals was obtained from the national register and census linkages. Unit response rates considering the different sampling probabilities of both surveys were calculated. Logistic regression analyses examined the association between mode system and sociodemographic characteristics for unit nonresponse. The costs per completed web questionnaire were compared with the costs for a completed F2F questionnaire. RESULTS: The unit response rate is lower in BHISWEB (18.0%) versus BHISF2F (43.1%). A lower response rate was observed for the web survey among all sociodemographic groups, but the difference was higher among people aged 65 years and older (15.4% vs 45.1%), lower educated people (10.9% vs 38.0%), people with a non-Belgian European nationality (11.4% vs 40.7%), people with a non-European nationality (7.2% vs 38.0%), people living alone (12.6% vs 40.5%), and people living in the Brussels-Capital (12.2% vs 41.8%) region. The sociodemographic characteristics associated with nonresponse are not the same in the 2 studies. Having another European (OR 1.60, 95% CI 1.20-2.13) or non-European nationality (OR 2.57, 95% CI 1.79-3.70) compared to a Belgian nationality and living in the Brussels-Capital (OR 1.72, 95% CI 1.41-2.10) or Walloon (OR 1.47, 95% CI 1.15-1.87) regions compared to the Flemish region are associated with a higher nonresponse only in the BHISWEB study. In BHISF2F, younger people (OR 1.31, 95% CI 1.11-1.54) are more likely to be nonrespondents than older people, and this was not the case in BHISWEB. In both studies, lower educated people have a higher probability of being nonrespondent, but this effect is more pronounced in BHISWEB (low vs high education level: Web, OR 2.71, 95% CI 2.21-3.39 and F2F OR 1.70, 95% CI 1.48-1.95). The BHISWEB study had a considerable advantage; the cost per completed questionnaire was almost 3 times lower (€41 [US $48]) compared with F2F data collection (€111 [US $131]). CONCLUSIONS: The F2F unit response rate was generally higher, yet for certain groups the difference between web and F2F was more limited. Web data collection has a considerable cost advantage. It is therefore worth experimenting with adaptive mixed-mode designs to optimize financial resources without increasing selection bias (eg, only inviting sociodemographic groups who are keener to participate online for web surveys while continuing to focus on increasing F2F response rates for other groups).

Belgian population norms for the EQ-5D-5L, 2018.

PURPOSE: Health-related quality of life outcomes are increasingly used to monitor population health and health inequalities and to assess the (cost-) effectiveness of health interventions. The EQ-5D-5L has been included in the Belgian Health Interview Survey, providing a new source of population-based self-perceived health status information. This study aims to estimate Belgian population norms for the EQ-5D-5L by sex, age, and region and to analyze its association with educational attainment. METHODS: The BHIS 2018 provided EQ-5D-5L data for a nationally representative sample of the Belgian population. The dimension scores and index values were analyzed using logistic and linear regressions, respectively, accounting for the survey design. RESULTS: More than half of respondents reported problems of pain/discomfort, while over a quarter reported problems of anxiety/depression. The average index value was 0.84. Women reported more problems on all dimensions, but particularly on anxiety/depression and pain/discomfort, resulting in significantly lower index values. Problems with mobility, self-care, and usual activities showed a sharp increase after the age of 80 years. Consequently, index values decreased significantly by age. Lower education was associated with a higher prevalence of problems for all dimensions except anxiety/depression and with a significantly lower index value. CONCLUSION: This paper presents the first nationally representative Belgian population norms using the EQ-5D-5L. Inclusion of the EQ-5D in future surveys will allow monitoring over time of self-reported health, disease burden, and health inequalities.

Mixing mixed-mode designs in a national health interview survey: a pilot study to assess the impact on the self-administered questionnaire non-response.

BACKGROUND: Many population health surveys consist of a mixed-mode design that includes a face-to-face (F2F) interview followed by a paper-and-pencil (P&P) self-administered questionnaire (SAQ) for the sensitive topics. In order to alleviate the burden of a supplementary P&P questioning after the interview, a mixed-mode SAQ design including a web and P&P option was tested for the Belgian health interview survey. METHODS: A pilot study (n = 266, age 15+) was organized using a mixed-mode SAQ design following the F2F interview. Respondents were invited to complete a web SAQ either immediately after the interview or at a later time. The P&P option was offered in case respondents refused or had previously declared having no computer access, no internet connection or no recent usage of computers. The unit response rate for the web SAQ and the overall unit response rate for the SAQ independent of the mode were evaluated. A logistic regression analysis was conducted to explore the association of socio-demographic characteristics and interviewer effects with the completed SAQ mode. Furthermore, a logistic regression analysis assessed the differential user-friendliness of the SAQ modes. Finally, a logistic multilevel model was used to evaluate the item non-response in the two SAQ modes while controlling for respondents' characteristics. RESULTS: Of the eligible F2F respondents in this study, 76% (107/140) agreed to complete the web SAQ. Yet among those, only 78.5% (84/107) actually did. At the end, the overall (web and P&P) SAQ unit response rate reached 73.5%. In this study older people were less likely to complete the web SAQ. Indications for an interviewer effect were observed as regard the number of web respondents, P&P respondents and respondents who refused to complete the SAQ. The web SAQ scored better in terms of user-friendliness and presented higher item response than the P&P SAQ. CONCLUSIONS: The web SAQ performed better regarding user-friendliness and item response than the P&P SAQ but the overall SAQ unit response rate was low. Therefore, future research is recommended to further assess which type of SAQ design implemented after a F2F interview is the most beneficial to obtain high unit and item response rates.

Determinants of unit nonresponse in multi-mode data collection: A multilevel analysis.

BACKGROUND: Multi-mode data collection is widely used in surveys. Since several modes of data collection are successively applied in such design (e.g. self-administered questionnaire after face-to-face interview), partial nonresponse occurs if participants fail to complete all stages of the data collection. Although such nonresponse might seriously impact estimates, it remains currently unexplored. This study investigates the determinants of nonresponse to a self-administered questionnaire after having participated in a face-to-face interview. METHODS: Data from the Belgian Health Interview Survey 2013 were used to identify determinants of nonresponse to self-administered questionnaire (n = 1,464) among those who had completed the face-to-face interview (n = 8,133). The association between partial nonresponse and potential determinants was explored through multilevel logistic regression models, encompassing a random interviewer effect. RESULTS: Significant interviewer effects were found. Almost half (46.6%) of the variability in nonresponse was attributable to the interviewers, even in the analyses controlling for the area as potential confounder. Partial nonresponse was higher among youngsters, non-Belgian participants, people with a lower educational levels and those belonging to a lower income household, residents of Brussels and Wallonia, and people with poor perceived health. Higher odds of nonresponse were found for interviews done in the last quarters of the survey-year. Regarding interviewer characteristics, only the total number of interviews carried out throughout the survey was significantly associated with nonresponse to the self-administered questionnaire. CONCLUSIONS: The results indicate that interviewers play a crucial role in nonresponse to the self-administered questionnaire. Participant characteristics, interview circumstances and interviewer characteristics only partly explain the interviewer variability. Future research should examine further interviewer characteristics that impact nonresponse. The current study emphasises the importance of training and motivating interviewers to reduce nonresponse in multi-mode data collection.

Using mortality follow-up of surveys to estimate social inequalities in healthy life years.

BACKGROUND: The estimation of healthy life years (HLY) by socio-economic status (SES) requires two types of data: the prevalence of activity limitation by SES generally extracted from surveys and mortality rates by SES generally derived from a linkage between the SES information in population databases (census, register) and mortality records. In some situations, no population-wide databases are available to produce mortality rates by SES, and therefore some alternatives must be explored. This paper assesses the validity of calculating HLY by SES using mortality rates derived from a linkage between surveys and mortality records. METHODS: TWO SURVEYS WERE CHOSEN TO EXPLORE THE VALIDITY OF THE PROPOSED APPROACH: The Belgian Health Interview Survey (HIS) and the Belgian Survey on Income and Living Conditions (SILC). The mortality follow-up of these surveys were used to calculate HLY by educational level at age 25. These HLY were compared with HLY estimates calculated using the mortality follow-up of the 2001 census. The validity of this approach was evaluated against two criteria. First, the HLY calculated using the census and those calculated using the surveys must not be significantly different. Second, survey-based HLY must show significant social inequalities since such inequalities have been consistently reported with census-based HLY. RESULTS: Both criteria were met. First, for each educational category, no statistically significant difference was found when comparing census-based and survey-based HLY estimates. For instance, men in the lowest educational category have shown a HLY of 34 years according to the HIS, and while this figure was 35.5 years according to the census, this difference was not statistically significant. Second, the survey-based HLY have shown a significant social gradient. For instance, men in the highest educational category are expected to live 9.5 more HLY than their counterparts in the lowest educational category based on the HIS estimates, compared with 7.3 HLY based on the census estimates. CONCLUSIONS: This article suggests that using the mortality follow-up of a nationally representative cross-sectional survey is a valid approach to monitor social inequalities in HLY in the absence of population-wide data.

Using multiple measures of inequalities to study the time trends in social inequalities in smoking.

BACKGROUND: The time trends in social inequalities in smoking have been examined in a number of international publications; however, these studies have rarely used multiple measures of health inequalities simultaneously. Also the analytical approach used often did not account, as recommended, for the changes in the relative distribution of social groups and the changes in the absolute level of the health outcome within social groups. METHODS: Data from four successive waves of the Belgian Health Interview Survey (1997, 2001, 2004, 2008) were used to study the time trends in educational inequalities in daily smoking for those aged between 15 and 74 years. We estimated two measures of relative inequalities: the OR and the relative index of inequality; and two measures of absolute inequalities: the population attributable fraction and the slope index of inequality. Three of these measures (relative index of inequality, population attributable fraction, slope index of inequality) account for the change in the relative size of the social groups over time. RESULTS: The four measures of inequality were consistent in showing significant inequalities among educational groups. The time trends, however, were less consistent. Measures of trends in relative inequalities witnessed a small linear increase. However, no substantial over time change was observed with the measures of absolute inequalities. CONCLUSION: The time trends in social inequalities in smoking varied according to the measure of inequality used. This study confirms the importance of using multiple measures of inequalities to understand and monitor social inequalities in smoking.

Socio-economic differences in participation of households in a Belgian national health survey.

BACKGROUND: Socio-economic inequalities in health survey participation can jeopardize the extrapolation of the survey findings to the total population. Earlier research, based on aggregated data, showed that in Belgium less-educated people with poor health were less likely to participate in a health survey. In this article, the association by socio-economic status and household non-response in a health survey is examined. METHODS: A linkage between the Belgian Health Survey 2001 with Census 2001 enabled us to evaluate the participation by socio-economic status. RESULTS: We observed that the socio-economic position was a determinant of health survey participation: participation rate was significantly lower in households with a lower socio-economic profile. CONCLUSION: Socio-economic inequalities in participation can introduce a bias in the health survey findings. Strategies targeting improvement of the participation of lower socio-economic groups need to be considered.

Contribution of mortality and disability to the secular trend in health inequality at the turn of century in Belgium.

BACKGROUND: There is evidence that health inequalities by socio-economic status have persisted. We examined whether educational differences in Disability-Free Life Expectancy (DFLE) and Disability Life Expectancy (DLE) at age 25 has narrowed or widened between the 1990s and 2000s in Belgium. The contribution of mortality and disability prevalence to the secular trend is investigated. METHODS: We used disability data from the 1997 and 2004 Belgian Health Interviews Surveys and mortality data from the 3-years follow-up of the 1991 and 2001 census population to assess education-related disparities in DFLE and DLE and to partition these differences into additive contributions of mortality and disability. RESULTS: Compared to the highest educated population, differences in the prevalence of disability accounted for at least 66% of the inequality in DFLE. In the latest period, the differences in DFLE compared to men with tertiary education was 4.8, 6.6, 9.7 and 18.6 years for men with, respectively higher secondary, lower secondary, primary and no education. Among females, inequalities in DFLE were, respectively 5.8, 5.1, 10.8 and 18.2 years. There was no evidence that the educational differences in DFLE narrowed since the 1990s. Compared to people with the highest educational attainment, the inequalities in DFLE increased over time for all educational groups except for men with primary education. CONCLUSION: The social divide in health increased over time: people with the highest education continued to live even longer, they continued to live even longer without disability and to live less years with disability.

Trends in social inequalities in obesity: Belgium, 1997 to 2004.

OBJECTIVES: Studies examining the time trend in social inequalities in obesity have yielded diverse results. The aim of this study is to investigate whether social inequalities in obesity have increased overtime in Belgium. METHODS: We used data from three national cross-sectional health interview surveys (1997 n=7953, 2001 n=8887, and 2004 n=9709) to estimate age-standardized obesity prevalence and a series of summary measures reflecting health inequalities in men and women aged 18 years and older. RESULTS: For males, a clear socioeconomic gradient was observed between obesity and education. This gradient witnessed a large increase between the years 1997 and 2004. For instance, the relative index of inequality increased from 1.92 (95% CI: 1.16-3.18) to 3.71 (95% CI: 2.49-5.54). Social inequalities in female obesity indicate a different pattern. Our results revealed a very steep socioeconomic gradient for female obesity, but overtime, no significant change was observed. The relative index of inequality for female obesity was 4.04 (95% CI: 2.47-6.63) in 1997 and 4.03 (95% CI: 2.75-5.90) in 2004. CONCLUSIONS: Using three comparable nation-wide population-based surveys, our study has shown that in Belgium from 1997 to 2004, the socioeconomic gradient in obesity has increased for males and persisted for females.

Does income inequality modify the association between air pollution and health?

BACKGROUND: It has been hypothesized that socioeconomic status may act as an effect modifier of the association between air pollution and health. In this study, we investigated whether income inequality may modify the association between fine particulate pollution and self-reported health. METHODS: We combined several different sources of data. Demographic and socio-economic data, at the individual level, were drawn from the 2001 US Behavioral Risk Factor Surveillance System (BRFSS). County-level particulate pollution data for the year 2001 were provided by the US Environmental Protection Agency. State-level income inequality was measured by the Gini index using US census data from the year 2000. We used a hierarchical logistic regression to model the association between general self-reported health and fine particulate pollution accounting for income inequality as an effect modifier and controlling for the usual confounders. RESULTS: We found that when income inequality is low (10th percentile of the Gini distribution), the odds of reporting fair or poor health for a 10microg/m3 increase in particulate pollution is 1.34 (95% confidence interval 1.21-1.48). The analogous odds ratio for higher income inequality (60th percentile of the Gini distribution) is 1.11 (95% confidence interval 1.06-1.16). CONCLUSIONS: Income inequality was found to be an effect modifier of the association between general self-reported health and particulate pollution. However, these findings challenged our hypothesis that people living in higher income inequality areas are more vulnerable to the impact of air pollution. We discuss the factors driving these results.

Health inequalities and place: a theoretical conception of neighbourhood.

In the past 10 years, interest in studying the relationship between area of residence and health has grown. During this period empirical relations between place and health have been observed at a variety of spatial scales, from census tracts to administrative units in metropolitan areas to whole regions, and for a variety of health outcomes. Despite the richness of the data, there are relatively few publications offering theoretical explanations for these observations, and a sound conception of place itself is still lacking. Using place as a relational space linked to where people live, work and play, this paper conceptualises the nature of neighbourhoods as they contribute to the local production of health inequalities in everyday life. In reference to Giddens' structuration theory, we propose that neighbourhoods essentially involve the availability of, and access to, health-relevant resources in a geographically defined area. Taking inspiration from the work of Godbout on informal reciprocity, we further propose that such availability and access are regulated according to four different sets of rules: proximity, prices, rights, and informal reciprocity. Our theoretical framework suggests that these rules give rise to five domains, the physical, economic, institutional, local sociability, and community organisation domains which cut across neighbourhood environments through which residents may acquire resources that shape their lifecourse trajectory in health and social functioning.