Comparing health insurance data and health interview survey data for ascertaining chronic disease prevalence in Belgium

Impact of short-term exposure to air pollution on natural mortality and vulnerable populations: a multi-city case-crossover analysis in Belgium

BACKGROUND

The adverse effect of air pollution on mortality is well documented worldwide but the identification of more vulnerable populations at higher risk of death is still limited. The aim of this study was to evaluate the association between natural mortality (overall and cause-specific) and short-term exposure to five air pollutants (PM2.5, PM10, NO2, O3 and black carbon) and identify potential vulnerable populations in Belgium.

METHODS

We used a time-stratified case-crossover design with conditional logistic regressions to assess the relationship between mortality and air pollution in the nine largest Belgian agglomerations. Then, we performed a random-effect meta-analysis of the pooled results and described the global air pollution-mortality association. We carried out stratified analyses by individual characteristics (sex, age, employment, hospitalization days and chronic preexisting health conditions), living environment (levels of population density, built-up areas) and season of death to identify effect modifiers of the association.

RESULTS

The study included 304,754 natural deaths registered between 2010 and 2015. We found percentage increases for overall natural mortality associated with 10 μg/m3 increases of air pollution levels of 0.6% (95% CI: 0.2%, 1.0%) for PM2.5, 0.4% (0.1%, 0.8%) for PM10, 0.5% (-0.2%, 1.1%) for O3, 1.0% (0.3%, 1.7%) for NO2 and 7.1% (-0.1%, 14.8%) for black carbon. There was also evidence for increases of cardiovascular and respiratory mortality. We did not find effect modification by individual characteristics (sex, age, employment, hospitalization days). However, this study suggested differences in risk of death for people with preexisting conditions (thrombosis, cardiovascular diseases, asthma, diabetes and thyroid affections), season of death (May-September vs October-April) and levels of built-up area in the neighborhood (for NO2).

CONCLUSIONS

This work provided evidence for the adverse health effects of air pollution and contributed to the identification of specific population groups. These findings can help to better define public-health interventions and prevention strategies.

Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium

In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.

Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report

BACKGROUND

Studies have suggested that agreement between administrative health data and self-report for asthma status ranges from fair to good, but few studies benefited from administrative health data over a long period. We aimed to (1) evaluate agreement between asthma status ascertained in administrative health data covering a period of 30 years and from self-report, and (2) identify determinants of agreement between the two sources.

METHODS

We used administrative health data (1983-2012) from the Quebec Birth Cohort on Immunity and Health, which included 81,496 individuals born in the province of Quebec, Canada, in 1974. Additional information, including self-reported asthma, was collected by telephone interview with 1643 participants in 2012. By design, half of them had childhood asthma based on health services utilization. Results were weighted according to the inverse of the sampling probabilities. Five algorithms were applied to administrative health data (having ≥ 2 physician claims over a 1-, 2-, 3-, 5-, or 30-year interval or ≥ 1 hospitalization), to enable comparisons with previous studies. We estimated the proportion of overall agreement and Kappa, between asthma status derived from algorithms and self-reports. We used logistic regression to identify factors associated with agreement.

RESULTS

Applying the five algorithms, the prevalence of asthma ranged from 49 to 55% among the 1643 participants. At interview (mean age = 37 years), 49% and 47% of participants respectively reported ever having asthma and asthma diagnosed by a physician. Proportions of agreement between administrative health data and self-report ranged from 88 to 91%, with Kappas ranging from 0.57 (95% CI: 0.52-0.63) to 0.67 (95% CI: 0.62-0.72); the highest values were obtained with the [≥ 2 physician claims over a 30-year interval or ≥ 1 hospitalization] algorithm. Having sought health services for allergic diseases other than asthma was related to lower agreement (Odds ratio = 0.41; 95% CI: 0.25-0.65 comparing ≥ 1 health services to none).

CONCLUSIONS

These findings indicate good agreement between asthma status defined from administrative health data and self-report. Agreement was higher than previously observed, which may be due to the 30-year lookback window in administrative data. Our findings support using both administrative health data and self-report in population-based epidemiological studies.

Comparing self-reported health interview survey and pharmacy billing data in determining the prevalence of diabetes, hypertension, and hypercholesterolemia in Belgium

BACKGROUND

Administrative and health surveys are used in monitoring key health indicators in a population. This study investigated the agreement between self-reported disease status from the Belgian Health Interview Survey (BHIS) and pharmaceutical insurance claims extracted from the Belgian Compulsory Health Insurance (BCHI) in ascertaining the prevalence of diabetes, hypertension, and hypercholesterolemia.

METHODS

Linkage was made between the BHIS 2018 and the BCHI 2018, from which chronic condition was ascertained using the Anatomical Therapeutic Chemical (ATC) classification and defined daily dose. The data sources were compared using estimates of disease prevalence and various measures of agreement and validity. Multivariable logistic regression was performed for each chronic condition to identify the factors associated to the agreement between the two data sources.

RESULTS

The prevalence estimates computed from the BCHI and the self-reported disease definition in BHIS, respectively, are 5.8% and 5.9% diabetes cases, 24.6% and 17.6% hypertension cases, and 16.2% and 18.1% of hypercholesterolemia cases. The overall agreement and kappa coefficient between the BCHI and the self-reported disease status is highest for diabetes and is equivalent to 97.6% and 0.80, respectively. The disagreement between the two data sources in ascertaining diabetes is associated with multimorbidity and older age categories.

CONCLUSION

This study demonstrated the capability of pharmacy billing data in ascertaining and monitoring diabetes in the Belgian population. More studies are needed to assess the applicability of pharmacy claims in ascertaining other chronic conditions and to evaluate the performance of other administrative data such as hospital records containing diagnostic codes.

Association between temperature and natural mortality in Belgium: Effect modification by individual characteristics and residential environment

BACKGROUND

There is strong evidence of mortality being associated to extreme temperatures but the extent to which individual or residential factors modulate this temperature vulnerability is less clear.

METHODS

We conducted a multi-city study with a time-stratified case-crossover design and used conditional logistic regression to examine the association between extreme temperatures and overall natural and cause-specific mortality. City-specific estimates were pooled using a random-effect meta-analysis to describe the global association. Cold and heat effects were assessed by comparing the mortality risks corresponding to the 2.5th and 97.5th percentiles of the daily temperature, respectively, with the minimum mortality temperature. For cold, we cumulated the risk over lags of 0 to 28 days before death and 0 to 7 days for heat. We carried out stratified analyses and assessed effect modification by individual characteristics, preexisting chronic health conditions and residential environment (population density, built-up area and air pollutants: PM2.5, NO2, O3 and black carbon) to identify more vulnerable population subgroups.

RESULTS

Based on 307,859 deaths from natural causes, we found significant cold effect (OR = 1.42, 95%CI: 1.30-1.57) and heat effect (OR = 1.17, 95%CI: 1.12-1.21) for overall natural mortality and for respiratory causes in particular. There were significant effects modifications for some health conditions: people with asthma were at higher risk for cold, and people with psychoses for heat. In addition, people with long or frequent hospital admissions in the year preceding death were at lower risk. Despite large uncertainties, there was suggestion of effect modification by air pollutants: the effect of heat was higher on more polluted days of O3 and black carbon, and a higher cold effect was observed on more polluted days of PM2.5 and NO2 while for O3, the effect was lower.

CONCLUSIONS

These findings allow for targeted planning of public-health measures aiming to prevent the effects of extreme temperatures.

Cross-national comparisons of health indicators require standardized definitions and common data sources

Background

Health indicators are used to monitor the health status and determinants of health of the population and population sub-groups, identify existing or emerging health problems which would require prevention and health promotion activities, help to target health care resources in the most adequate way as well as for evaluation of the success of public health actions both at the national and international level. The quality and validity of the health indicator depends both on available data and used indicator definition. In this study we will evaluate existing knowledge about comparability of different data sources for definition of health indicators, compare how selected health indicators presented in different international databases possibly differ, and finally, present the results from a case study from Finland on comparability of health indicators derived from different data sources at national level.

Methods

For comparisons, four health indicators were selected that were commonly available in international databases and available for the Finnish case study. These were prevalence of obesity, hypertension, diabetes, and asthma in the adult populations. Our evaluation has three parts: 1) a scoping review of the latest literature, 2) comparison of the prevalences presented in different international databases, and 3) a case study using data from Finland.

Results

Literature shows that comparability of estimated outcomes for health indicators using different data sources such as self-reported questionnaire data from surveys, measured data from surveys or data from administrative health registers, varies between indicators. Also, the case study from Finland showed that diseases which require regular health care visits such as diabetes, comparability is high while for health outcomes which can remain asymptomatic for a long time such as hypertension, comparability is lower. In different international health related databases, country specific results differ due to variations in the used data sources but also due to differences in indicator definitions.

Conclusions

Reliable comparison of the health indicators over time and between regions within a country or across the countries requires common indicator definitions, similar data sources and standardized data collection methods.

Correction to: Comparing health insurance data and health interview survey data for ascertaining chronic disease prevalence in Belgium

An amendment to this paper has been published and can be accessed via the original article.