Public health monitoring of hypertension, diabetes and elevated cholesterol: comparison of different data sources

Consistency between self-reported disease diagnosis and clinical assessment and under-reporting for chronic conditions: data from a community-based study in Xi'an, China

Aims

The current study aims to investigate the consistency between the surveyees' self-reported disease diagnosis and clinical assessment of eight major chronic conditions using community-based survey data collected in Xi'an, China in 2017. With a focus on under-reporting patients, we aim to explore its magnitude and associated factors, to provide an important basis for disease surveillance, health assessment and resource allocation, and public health decision-making and services.

Methods

Questionnaires were administered to collect self-reported chronic condition prevalence among the study participants, while physical examinations and laboratory tests were conducted for clinical assessment. For each of the eight chronic conditions, the sensitivity, specificity, under-reporting, over-reporting, and agreement were calculated. Log-binomial regression analysis was employed to identify potential factors that may influence the consistency of chronic condition reporting.

Results

A total of 2,272 participants were included in the analysis. Four out of the eight chronic conditions displayed under-reporting exceeding 50%. The highest under-reporting was observed for goiter [85.93, 95% confidence interval (CI): 85.25-86.62%], hyperuricemia (83.94, 95% CI: 83.22-84.66%), and thyroid nodules (72.89, 95% CI: 72.02-73.76%). Log-binomial regression analysis indicated that senior age and high BMI were potential factors associated with the under-reporting of chronic condition status in the study population.

Conclusion

The self-reported disease diagnosis by respondents and clinical assessment data exhibit significant inconsistency for all eight chronic conditions. Large proportions of patients with multiple chronic conditions were under-reported in Xi'an, China. Combining relevant potential factors, targeted health screenings for high-risk populations might be an effective method for identifying under-reporting patients.

National Health Examination Surveys: an essential piece of the health planning puzzle

National health examination surveys (HESs) have been developed to provide important information that cannot be obtained from other sources. A HES combines information obtained by asking participants questions with biophysical measurements taken by trained field staff. They are observational studies with the highest external validity and make specific contributions to both population (public health) and individual health. Few countries have a track record of a regular wide-ranging HES, but these are the basis of many reports and scientific papers. Despite this, little evidence about HES usefulness and impact or the factors that influence HES effectiveness have been disseminated. This paper presents examples of HES contributions to society in both Europe and the Americas. We sought information by emailing a wide list of people involved in running or using national HESs across Europe and the Americas. We asked for examples of where examination data from their HES had been used in national or regional policymaking. We found multiple examples of HES data being used for agenda-setting, including by highlighting nutritional needs and identifying underdiagnosis and poor management of certain conditions. We also found many ways in which HES have been used to monitor the impact of policies and define population norms. HES data have also been used in policy formation and implementation. HES data are influential and powerful. There is need for global support, financing and networking to transfer capacities and innovation in both fieldwork and laboratory technology.

Using random-forest multiple imputation to address bias of self-reported anthropometric measures, hypertension and hypercholesterolemia in the Belgian health interview survey

BACKGROUND

In many countries, the prevalence of non-communicable diseases risk factors is commonly assessed through self-reported information from health interview surveys. It has been shown, however, that self-reported instead of objective data lead to an underestimation of the prevalence of obesity, hypertension and hypercholesterolemia. This study aimed to assess the agreement between self-reported and measured height, weight, hypertension and hypercholesterolemia and to identify an adequate approach for valid measurement error correction.

METHODS

Nine thousand four hundred thirty-nine participants of the 2018 Belgian health interview survey (BHIS) older than 18 years, of which 1184 participated in the 2018 Belgian health examination survey (BELHES), were included in the analysis. Regression calibration was compared with multiple imputation by chained equations based on parametric and non-parametric techniques.

RESULTS

This study confirmed the underestimation of risk factor prevalence based on self-reported data. With both regression calibration and multiple imputation, adjusted estimation of these variables in the BHIS allowed to generate national prevalence estimates that were closer to their BELHES clinical counterparts. For overweight, obesity and hypertension, all methods provided smaller standard errors than those obtained with clinical data. However, for hypercholesterolemia, for which the regression model's accuracy was poor, multiple imputation was the only approach which provided smaller standard errors than those based on clinical data.

CONCLUSIONS

The random-forest multiple imputation proves to be the method of choice to correct the bias related to self-reported data in the BHIS. This method is particularly useful to enable improved secondary analysis of self-reported data by using information included in the BELHES. Whenever feasible, combined information from HIS and objective measurements should be used in risk factor monitoring.

Time Trends and Sex Differences in the Association between Diabetes and Chronic Neck Pain, Chronic Low Back Pain, and Migraine. Analysis of Population-Based National Surveys in Spain (2014-2020)

(1) Background: To assess the time trend in the prevalence of chronic neck pain (CNP), chronic low back pain (CLBP), and migraine or frequent headache (MFH) among people with diabetes in Spain from 2014 to 2020, this study identified sex differences and compared the prevalence of these pain sites between people with diabetes and age−sex-matched non-diabetic subjects. (2) Methods: The study design included a cross-sectional and a case−control study. The data were obtained from the European Health Interview Surveys for Spain conducted in 2014 and 2020. The presence of diabetes, CNP, CLBP, and MFH was self-reported. Study covariates included sociodemographic characteristics, comorbidities, lifestyles, and pain-related variables. (3) Results: Among people with diabetes, the prevalence of CNP, CLBP, and MFH did not improve from 2014 to 2020. Women with diabetes had a significantly higher prevalence of all the pain sites analyzed than men with diabetes. After matching by sex and age, the prevalence of CNP (26.0% vs. 21.1%; p < 0.001), CLBP (31.2% vs. 25.0%; p < 0.001), and MFH (7.7% vs. 6.5%; p = 0.028) was higher for people with diabetes than for those without diabetes. Self-reported mental disease was independently associated with reporting the three pain sites analyzed in people with diabetes. (4) Conclusions: The prevalence of CNP, CLBP, and MFH has remained stable over time. Remarkable sex differences were found, with a higher prevalence among women than men with diabetes. Diabetes was associated with reporting in all the pain sites analyzed. Self-reported mental disease was associated with reporting CNP, CLBP, and MFH.

Effectiveness of using e-government platform "Absher" as a tool for noncommunicable diseases survey in Saudi Arabia 2019-2020: A cross-sectional study

Background

E-government platforms provide an opportunity to use a novel data source for population health surveillance (also known as e-health). Absher is a Saudi e-government platform with 23 million authenticated users, including residents and citizens in Saudi Arabia. All Absher users were invited to participate in a web-based survey to estimate the prevalence of noncommunicable diseases and their risk factors in Saudi Arabia.

Objective

To assess the potential of using an e-government platform (Absher) to administer web-based health surveys.

Methods

A cross-sectional, web-based health survey was administered to Absher users between April 2019 and March 2020. The survey instrument included eight items and took <5 min to complete. The respondents' data were compared to Saudi Arabia's 2016 census. Descriptive summary statistics of the prevalence of major noncommuncable diseases are presented and compared to population-based prevalence data from Saudi Arabia's World Health Survey (WHS) 2019. All analysis was conducted using Stata 13.0.

Results

Overall, the Absher health survey had a 24.6% response rate, with most respondents being male (84%), Saudi (67%), and between 30 and 44 years of age (49%). Overall, the prevalence of noncommunicable diseases and risk factors among respondents was high for overweight (35%) and obesity (30%) and low for asthma (6%). The prevalence of diabetes, dyslipidemia, and hypertension was between 15 and 17% on average, and 26.5% were smokers. In comparison to population-based World Health Survey estimates, the Absher survey overestimated obesity, diabetes, dyslipidemia, hypertension, and smoking rates, and underestimated overweight, whereas asthma prevalence was similar for Absher and the WHS.

Conclusions

With improvements in the study design, the use of e-government platforms can provide a useful and potentially low-cost data source for public health research.

Prevalence of dyslipidemia and hypercholesterolemia awareness: results from the Lookup 7+ online project

Background

Cardiovascular disease still represents the leading cause of death worldwide. Management of risk factors remains crucial; despite this, hypercholesterolemia, which is one of the most important modifiable cardiovascular risk factor, is still high prevalent in general population. The aim of this study is to determine the prevalence of dyslipidemia and hypercholesterolemia awareness in a very large population.

Methods

More than 65 000 users completed the online, self-administered survey. It was structured like a ‘journey’ where each stage corresponded to a cardiovascular risk factor: blood pressure, body mass index, cholesterol, diet, physical exercise, smoke and blood sugar. At the end, the user received a final evaluation of his health status.

Results

The mean age was 52.5 years (SD 13.9, range 18–98), with 35 402 (53.7%) men. About 56% of all participants believed to have normal cholesterol values, when only 40% of them really showed values <200 mg/dl. Only about 30% of all participants self-predicted to have abnormal cholesterol values whereas we found high cholesterol levels in about 60% of people.

Conclusions

Dyslipidemia is very prevalent and half of the people with high cholesterol is not aware of having high values.

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.

Combining self-reported and objectively measured survey data to improve hypertension prevalence estimates: Portuguese experience

BACKGROUND

Accurate data on hypertension is essential to inform decision-making. Hypertension prevalence may be underestimated by population-based surveys due to misclassification of health status by participants. Therefore, adjustment for misclassification bias is required when relying on self-reports. This study aims to quantify misclassification bias in self-reported hypertension prevalence and prevalence ratios in the Portuguese component of the European Health Interview Survey (INS2014), and illustrate application of multiple imputation (MIME) for bias correction using measured high blood pressure data from the first Portuguese health examination survey (INSEF).

METHODS

We assumed that objectively measured hypertension status was missing for INS2014 participants (n = 13,937) and imputed it using INSEF (n = 4910) as auxiliary data. Self-reported, objectively measured and MIME-corrected hypertension prevalence and prevalence ratios (PR) by sex, age group and education were estimated. Bias in self-reported and MIME-corrected estimates were computed using objectively measured INSEF data as a gold-standard.

RESULTS

Self-reported INS2014 data underestimated hypertension prevalence in all population subgroups, with misclassification bias ranging from 5.2 to 18.6 percentage points (pp). After MIME-correction, prevalence estimates increased and became closer to objectively measured ones, with bias reduction to 0 pp - 5.7 pp. Compared to objectively measured INSEF, self-reported INS2014 data considerably underestimated prevalence ratio by sex (PR = 0.8, 95CI = [0.7, 0.9] vs. PR = 1.2, 95CI = [1.1, 1.4]). MIME successfully corrected direction of association with sex in bivariate (PR = 1.1, 95CI = [1.0, 1.3]) and multivariate analyses (PR = 1.2, 95CI = [1.0, 1.3]). Misclassification bias in hypertension prevalence ratios by education and age group were less pronounced and did not require correction in multivariate analyses.

CONCLUSIONS

Our results highlight the importance of misclassification bias analysis in self-reported hypertension. Multiple imputation is a feasible approach to adjust for misclassification bias in prevalence estimates and exposure-outcomes associations in survey data.

Comparison of data sources on alcohol problems: An exploratory exercise using surveys vs. national healthcare registers

Aims:

Both survey and healthcare register data struggle as data sources to capture the phenomenon of alcohol problems. We study a large group of people for whom survey data and two types of register data are available, and examine the overlaps of similar or related measures in the different data sources to learn about potential weaknesses in each. We also examine how register-based data on the prevalence of alcohol problems change depending on which register data are used.

Design:

We use data from the Regional Health and Wellbeing Study (ATH) of the adult Finnish population collected in 2013 and 2014 (n = 69,441), individually linked with data on two national healthcare registers (Care Register for Health Care; Register of Primary Health Care visits) for the survey year and previous year.

Results:

The prevalence of substance-abuse-related healthcare was almost two-fold if data on outpatient primary care visits were included in addition to hospitalisations. Forty-six per cent of the survey respondents self-reporting substance-abuse-related healthcare service use were identified in the registers, and 22% of all respondents with such service use according to registers reported this in the survey. Records of substance-abuse-related healthcare service use, controlled for self-reported alcohol use and self-reported substance-abuse-related service use, were found more often for men, the middle-aged, people with basic education only, and the non-employed.

Conclusions:

The results are suggestive of underreporting in both data sources. There is an evident need to develop recording practices in the healthcare registers regarding substance use disorders.

From monitoring to action: utilising health survey data in national policy development and implementation in Finland

Background

Health interview and examination surveys provide valuable information for policy, practice and research purposes. Appropriate use of high-quality, representative and timely population data can indirectly help the citizens to live healthier and longer lives. The aim of this study was to review how health survey data have supported health policy making, health research and everyday health care in Finland.

Methods

Data were collected by focused interviews with ten Finnish senior experts from the Ministry of Social Affairs and Health, political parties, National Institute for Health and Welfare, universities, and health associations.

Results

Most interviewees agreed that health surveys have positively affected the health of the population over the past 50 years - through health strategies, care guidelines, legislation, research, prevention programs, risk calculators, and healthier products on the market. There is also a need for further development: the latest research results should be provided in a nutshell for politicians, and effective tools should be developed more for health care professionals’ use. The coverage of health information on children, adolescents, oldest old, disabled persons, migrants and ethnic minorities should be improved.

Conclusions

Sound health policy and its successful implementation require extensive national cooperation and new communication strategies between policy makers, researchers, health care professionals, health service providers - and citizens. The future health information system in Finland should better cover all population groups. To obtain more comprehensive health information, the possibilities for register linkages should be secured and register data should be further evaluated and developed to serve health monitoring purposes.

Food consumption and glycemic testing of adults and elderly diabetic patients from Public Health: A systematic review of assessment methods

AIMS

To map and discuss the different methods used to assess food consumption and glycemic testing of adults and elderly diabetic patients from Public Health.

MATERIALS AND METHODS

A total of 710 records were identified by searching databases integrated by the Virtual Health Library website, between September and October 2017. The Newcastle Ottawa scale was used for study quality assessment. A total of 8 studies met inclusion criteria for analysis. Study characteristics were extracted and synthesized to generate comparisons.

RESULTS

Food consumption was evaluated by Food Frequency Questionnaire, 24-hour Dietary Recall, Eating Attitudes Test (EAT-26), Questionnaire On Eating and Weight Patterns (QEWP-R), and questioning the salt intake. Glucose testing methods included Postprandial Glucose, Glycated Hemoglobin (HbA1C), fasting glucose, and self-reported diabetes.

CONCLUSIONS

Most methods that access food consumption use single questionnaires, which are easy to administer and yield easily interpreted results. For glycemic testing, the majority used are conventional methods.

Differential self-report error by socioeconomic status in hypertension and hypercholesterolemia: INSEF 2015 study

BACKGROUND

This study aimed to compare self-reported and examination-based prevalence of hypertension and hypercholesterolemia in Portugal in 2015 and to identify factors associated with the measurement error in self-reports.

METHODS

We used data from the Portuguese National Health Examination Survey (n = 4911), that combines personal interview, blood collection and, physical examination. Sensitivity and specificity of self-reported hypertension and hypercholesterolemia were calculated. Poisson regression was used to estimate prevalence ratios (PRs) of underreport of hypertension and hypercholesterolemia according to sex, age, socioeconomic status (education and income) and general practitioner (GP) consultation in the past year.

RESULTS

Sensitivity of self-reports was 69.8% for hypertension and 38.2% for hypercholesterolemia. Underreport of hypertension was associated with male gender (PR = 1.54), lack of GP consultation (PR = 1.70) and being 25-44 years old (PR = 2.45) or 45-54 years old (PR = 2.37). Underreport of hypercholesterolemia was associated with lack of GP consultation (PR = 1.15), younger age (PR = 1.83 for 25-44 age group and PR = 1.52 for 45-54 age group), secondary (PR = 1.30) and higher (PR = 1.27) education.

CONCLUSION

Self-reported data underestimate prevalence of hypertension and hypercholesterolemia. Magnitude of measurement error in self-reports varies by health conditions and population characteristics. Adding objective measurements to self-reported questionnaires improve data accuracy allowing better understanding of socioeconomic inequalities in health.

Prescribing pattern of antihypertensive drugs in two European cohorts: a population-based database study

Background: Antihypertensive drugs play a crucial role in reducing cardiovascular morbidity and mortality. Variability in prescribing patterns constitutes a major challenge for current healthcare systems. This study aimed to compare patterns of use of antihypertensives in general practice in two southern European populations. Methods: Observational study. Data on antihypertensive drugs consumption in primary care setting (2016) were obtained from pharmacy refill records in Campania (Italy) and Aragon (Spain). Prescribing rates and the number of defined daily doses [DDD/1,000 inhabitants/day (DID)] were calculated, and the Drug Utilization 90% (DU90%) approach used to reveal differences in prescribing patterns in both regions. Results: Antihypertensive prescribing rates in Campania and Aragon were 250.8 (95%CI: 250.2-251.3) and 201.7 (95%CI: 200.9-202.5) users/1,000 inhabitants/year. Overall consumption was of 310.1 and 256.8 DID, respectively. Spanish users, especially women and the elderly, consumed a greater volume of diuretics. Conversely, other therapeutic subgroups were more consumed in Campania. However, the most prescribed subgroups accounted for comparable proportions of the total consumption in each region. Conclusions: Both prescribing rates and intensity of antihypertensive use were higher in Campania. Pharmacy refill records in cross-country comparisons allow to know the factors influencing variability in prescribing habits with a view to improving prescribing quality.