Validity of self-reported data to assess the prevalence of overweight, hypertension and cholesterol

Background

Accurate data on the risk factors of non-communicable diseases is essential to build evidence-based prevention programs. In Belgium, this is assessed through self-reported (SR) data from the Belgian health interview surveys (BHIS) in a wide population sample or through objective measures from small-scale surveys (such as the Belgian health examination survey [BHES]). It has been shown, however, that relying on SR data leads to a prevalence underestimation. The objective of this study is to assess the agreement between SR and measured overweight, hypertension and high cholesterol and to provide information to do a valid correction for measurement error.

Methods

The BHIS/BHES 2018 database was used (n = 1184). Kappa coefficient was used to assess the agreement between SR and measured hypertension (systolic BP > 140 mmHg, diastolic BP > 90 mmHg, or reported use of medication for hypertension) and ICC was used to assess the agreement between SR and measured BMI. SR high cholesterol was compared to a measured total serum cholesterol >190 mg/dl.

Results

Risk factor prevalence based on SR data is severely underestimated. The agreement between SR and measured data is high for BMI (ICC: 0.92), moderate for hypertension (Kappa: 0.49) and poor for cholesterol (Kappa: 0.05). Using SR data, 45% of the people with a measured hypertension and 22% of the people with a measured high cholesterol are detected. With regressions based on the SR risk factor, age, sex and education, the measured BMI and hypertension can be predicted with a good accuracy (BMI: R2: 87%, HBP: AUC: 86%). A lower accuracy is observed for the cholesterol model (AUC: 65%). Using predicted values instead of SR data yields higher estimates of people suffering from overweight (+8% relative increase), obesity (+12%), hypertension (+24%) and cholesterol (+36%).

Conclusions

Using SR data yields to an underestimation of the prevalence of obesity, hypertension and high cholesterol in Belgium

Key messages

Relying on SR data to assess the prevalence of overweight, hypertension and high cholesterol requires a correction for measurement error. Using the predicted values from regression models based on the SR risk factor, age, sex and education, yields higher estimates of people suffering from overweight, hypertension and cholesterol.

Impact of overweight on the burden of non-communicable diseases in Belgium: the WaIST project

Issue

Excess weight status is one of the main metabolic risk factors for non-communicable diseases. According to the Belgian health interview survey of 2018, 49.3% of the adult population suffered from overweight. Despite the great national burden, and apart from isolated actions, there is not anymore a comprehensive nutritional and physical activity health plan in Belgium. Consequentially, Belgium requires action-oriented research to support the implementation of evidence-based policies for the prevention of excessive weight gain.

Description of the Problem

The WaIST project aims to assess the contribution of excess weight status to the societal impact of non-communicable diseases, disability and multi-morbidity, and to model and compare the potential impact of internationally recommended health policies. The project also aims to support knowledge translation and policy transfer through a close interaction with national decision makers and stakeholders.

Results

The disease burden of diabetes, cardiovascular diseases, cancer and musculoskeletal disorders will be estimated in terms of disability-adjusted life years (DALYs) and healthcare expenses from a societal perspective. For this purpose, survey, registry, health insurance, and hospital discharge data will be used. Subsequently, health interventions tackling overweight will be selected considering scientific evidence and stakeholder priorities. Health impact assessments will then be conducted projecting the future impact of the interventions on health outcomes and costs related to excess weight status.

Lessons

The use of national data for the computation of the burden of disease provides better estimates for DALYs and costs compared to European or global study results. Moreover, the results of the project will allow to explore the impact of health intervention specific for the Belgian case.

Key messages

Considering the burden associated with overweight-related diseases, preventing obesity is important from a public health and financial perspective. Integrating these results into evidence-based policies could provide governments and partners with a key tool for effective health interventions.

Core Standards of the EUBIROD Project. Defining a European Diabetes Data Dictionary for Clinical Audit and Healthcare Delivery

BACKGROUND

A set of core diabetes indicators were identified in a clinical review of current evidence for the EUBIROD project. In order to allow accurate comparisons of diabetes indicators, a standardised currency for data storage and aggregation was required. We aimed to define a robust European data dictionary with appropriate clinical definitions that can be used to analyse diabetes outcomes and provide the foundation for data collection from existing electronic health records for diabetes.

METHODS

Existing clinical datasets used by 15 partner institutions across Europe were collated and common data items analysed for consistency in terms of recording, data definition and units of measurement. Where necessary, data mappings and algorithms were specified in order to allow partners to meet the standard definitions. A series of descriptive elements were created to document metadata for each data item, including recording, consistency, completeness and quality.

RESULTS

While datasets varied in terms of consistency, it was possible to create a common standard that could be used by all. The minimum dataset defined 53 data items that were classified according to their feasibility and validity. Mappings and standardised definitions were used to create an electronic directory for diabetes care, providing the foundation for the EUBIROD data analysis repository, also used to implement the diabetes registry and model of care for Cyprus.

CONCLUSIONS

The development of data dictionaries and standards can be used to improve the quality and comparability of health information. A data dictionary has been developed to be compatible with other existing data sources for diabetes, within and beyond Europe.

Information sources used in decision making: considerations for simulation development

Simulation tasks, together with think aloud techniques are often used to research the cognitive processes individuals go through when making a decision or solving a problem. They have been utilised to a certain degree within nursing. A study was carried out to try and identify the sources of information nurses in acute medical and surgical wards used to make assessment judgements. A sample of 114 nurses were interviewed, and their responses analysed using content analysis. Four main sources of information were identified, with verbal interaction being the source of information most frequently mentioned by the subjects. The content of material presented in simulations is normally tested using techniques such as expert panels. However, this paper suggests that of equal importance may be the form of presentation or source of that information. It is suggested that in order to increase the validity of information obtained from simulation tasks, the form of presentation of information to the subject should also be considered.