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

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.

Quantification of gastric emptying with magnetic resonance imaging in healthy volunteers: A systematic review

BACKGROUND

Several magnetic resonance imaging (MRI) protocols have been used to assess gastric emptying (GE) with MRI. This systematic review summarizes the current literature on the topic. The aim was to provide an overview of the available imaging protocols and underline the items that appear most agreed upon and those that deserve further investigation.

METHODS

According to PRISMA guidelines, two independent reviewers conducted a systematic literature search with a pre-specified strategy in different databases. Peer-reviewed articles that utilized MRI techniques to assess GE in healthy volunteers (HVs) were included. The quality and the outcomes of the studies were reported and analyzed.

KEY RESULTS

The literature search yielded 30 studies (531 HVs, weighted mean age 27.4, weighted mean body mass index 23.0 kg/m² ), T2-weighted sequences, balanced turbo field echo, and balanced gradient echo were evenly utilized, with volunteers in the supine position (74% of the studies). After overnight fasting, both liquid (56%) and mixed (44%) meals were equally utilized. Segmentation of the volumes was predominantly performed manually (63%) with a reported mean T50 ranging from 7 to 330 min.

CONCLUSIONS & INFERENCES

As observed in this systematic review, MRI is a flexible tool for assessing GE. Different protocols were analyzed, showing an equal capacity to assess the GE. However, many items in these protocols still require further investigation to obtain a common standard and increase this assessment quality.

Blood Pressure and Self-Management in Black Women with Hypertension: Protocol Revisions to the BRAINS Study due to the COVID-19 Pandemic (Preprint)

BACKGROUND

The COVID-19 pandemic and the halt to in-person research activities beginning in March 2020 brought new challenges to protocol development and implementation. Due to the pandemic, we had to revise our protocol for the Brain Relationships Among Information, Neuroprocessing, and Self-Management (BRAINS) study, which was designed to examine health information behavior, brain activity, diabetes status, and self-management behavior among Black women with hypertension.

OBJECTIVE

This report outlines 7 steps describing how our research team (1) revised the BRAINS study protocol, (2) implemented a remote method of data collection, and (3) mitigated the challenges we faced.

METHODS

Prior to March 2020, Black women with hypertension were invited to participate in the BRAINS study to undergo a functional magnetic resonance imaging scan, complete surveys, have their blood pressure measured, and have their blood drawn. After these measures were collected, participants would receive phone calls from a dietician to complete two 24-hour dietary recalls using the Nutrition Data System for Research. Our revised protocol relied on a web-based, interactive approach. Participants received a study kit that included an Omron automatic home blood pressure monitor and a hemoglobin A_1c kit from the DTIL laboratory. In a Zoom meeting with each participant, our team played an introductory video, administered surveys (via Qualtrics), and guided participants through measuring their blood pressure and performing a finger stick to collect a blood sample for hemoglobin A_1c testing. We examined cognitive function using the TestMyBrain Digital Neuropsychology Toolkit, as we were unable to access the functional magnetic resonance imaging laboratory to assess brain activity. The 7 steps in revising our protocol were as follows: conceptualizing the move from in-person to remote study activities (step 1); contacting the funders (step 2); submitting changes for Institutional Review Board approval (step 3); preparing to implement the revised protocol (step 4); implementing the study changes (step 5); mitigating challenges (step 6); and evaluating protocol implementation (step 7).

RESULTS

Approximately 1700 individuals responded to web-based advertisements about the BRAINS study. A total of 131 individuals completed our eligibility screener. We conducted our first Zoom appointment in July 2020 and our last Zoom appointment in September 2020. Using our revised strategies, a total of 99 participants completed all study measures within a 3-month period.

CONCLUSIONS

In this report, we discuss successes and challenges in revising our protocol and reaching our population of interest remotely, safely, and effectively. The information we have outlined can help researchers create similar protocols to reach and conduct research remotely with diverse populations, such as individuals who are unable to participate in studies in person.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/43849.

Comparing self-reported and measured hypertension and hypercholesterolaemia at standard and more stringent diagnostic thresholds: the cross-sectional 2010-2015 Busselton Healthy Ageing study

Background

Population health behaviour and risk factor surveys most often rely on self-report but there is a lack of studies assessing the validity of self-report using Australian data. This study investigates the sensitivity, specificity and agreement of self-reported hypertension and hypercholesterolaemia with objective measures at standard and more stringent diagnostic thresholds; and factors associated with sensitivity and specificity of self-report at different thresholds.

Methods

This study was a secondary analysis of a representative community-based cross-sectional sample of 5,092 adults, aged 45–69 years, residing in Busselton, Western Australia, surveyed in 2010–2015. Participants completed a self-administered questionnaire. Blood pressure and serum cholesterol levels were measured.

Results

At currently accepted diagnostic thresholds, sensitivities of self-reported hypertension and hypercholesterolaemia were 58.5% and 39.6%, respectively and specificities were >90% for both. Agreement using Cohen’s kappa coefficient was 0.562 and 0.223, respectively. At two higher diagnostic thresholds, sensitivities of self-reported hypertension and hypercholesterolaemia improved by an absolute 14–23% and 15–25%, respectively and specificities remained >85%. Agreement was substantial for hypertension (kappa = 0.682–0.717) and moderate for hypercholesterolaemia (kappa = 0.458–0.533). Variables that were independently associated with higher sensitivity and lower specificity of self-report were largely consistent across thresholds and included increasing age, body mass index, worse self-rated health, diabetes and family history of hypertension.

Conclusions

Self-reported hypertension and hypercholesterolaemia often misclassify individuals’ objective status and underestimate objective prevalences, at standard diagnostic thresholds, which has implications for surveillance studies that rely on self-reported data. Self-reports of hypertension, however, may be reasonable indicators of those with blood pressures ≥160/100 mmHg or those taking anti-hypertensive medications. Self-reported hypercholesterolaemia data should be used with caution at all thresholds.

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 self-reports and biomedical measurements on hypertension and diabetes among older adults in China

Background

Researchers interested in the effects of health on various life outcomes often use self-reported health and disease as an indicator of true, underlying health status. However, the validity of reporting is questionable as it relies on the awareness, recall bias and social desirability. Accordingly, biomedical test is generally regarded as a more precise indication of the disease.

Methods

Using data from the third wave of China Health and Retirement Longitudinal Study (CHARLS), we selected individuals aged 40–85 years old who participated in both health interview survey and biomedical test. Sensitivity, specificity, false negative reporting and false positive reporting were used as measurements of (dis) agreement or (in) validity, and binary and multinomial logistic regression were used to estimate under-report or over-report of hypertension and diabetes.

Results

Self-reported hypertension and diabetes showed low sensitivity (73.24 and 49.21%, respectively) but high specificity (93.61 and 98.05%, respectively). False positive reporting of hypertension and diabetes were 3.97 and 1.67%, while false negative reports were extremely high at 10.14 and 7.38%. Educational attainment, hukou, age and gender affected both group-specific error and overall error with some differences in their magnitude and directions.

Conclusion

Self-reported conditions underestimate the disease burden of hypertension and diabetes in China. Adding objective measurements into social survey could improve data accuracy and allow better understanding of socioeconomic inequalities in health. Furthermore, there is an urgent need to provide basic health education and physical examination to citizens, and promote the use of healthcare to lower the incidence and unawareness of disease in China.

Accuracy of Self-Reported Hypertension, Diabetes, and Hyperlipidemia among Adults of Liwan, Guangzhou, China

Background:

We aimed to determine the accuracy of self-reported diabetes, hypertension, and hyperlipidemia in Chinese adults and examine factors that affect the accuracy of self-reports.

Methods:

This representative cross-sectional survey was conducted in Liwan District, Guangzhou City, Southeast China. Self-reported data were collected using a structured questionnaire. Biometrical data were recorded, including blood lipid, blood glucose and arterial blood pressure levels. Sensitivity, specificity, and κ values of self-reports were used as measurements of accuracy or agreements. The Robust Poisson-GEE was applied to determine the association of participants’ characteristics with the accuracy of self-reports.

Results:

Self-reported and biometrical data of 1278 residents aged 18 yr and older (693 women and 585 men) were used to calculate three measures of agreement. The agreement between self-reports and biomedical measurements was substantial for both hypertension and diabetes (κ=0.77 and 0.76), but only slight for hyperlipidemia (κ=0.06). Similarly, the sensitivity was higher for hypertension and diabetes (72.3% and 71.2%) than for hyperlipidemia (6.8%), while the specificity was high overall (≥98%). The factors associated with an accurate self-reported diagnosis in respondents with disease included having undergone blood pressure measurement (for hypertension) or blood glucose measurement (for diabetes) in the past 6 month, having attended health knowledge lectures in the past year and having social health insurances (for hypertension), and having undergone physical discomfort in the past 2 weeks (for hypertension and diabetes).

Conclusion:

The accuracy of self-reported hypertension and diabetes was high, whereas that of self-reported hyperlipidemia was lower among the population.

Self-reported Age of Hypertension Onset and Hypertension-Mediated Organ Damage in Middle-Aged Individuals

Background

Objectively defined early onset hypertension, based on repeated blood pressure measurements, is a strong risk factor for cardiovascular disease (CVD). We aimed to assess if also self-reported hypertension onset age is associated with hypertension-mediated organ damage (HMOD). Additionally, we evaluated the agreement between self-reported and objectively defined hypertension onset age.

Methods

We studied 2,649 participants (50 ± 4 years at the time of outcome assessment, 57% women) of the Coronary Artery Risk Development in Young Adults (CARDIA) study who underwent measurements for echocardiographic left ventricular hypertrophy (LVH), left ventricular diastolic dysfunction (LVDD), coronary calcification, and albuminuria. We divided the participants into groups according to self-reported hypertension onset age (<35 years, 35–44 years, ≥45 years, and no hypertension). We used multivariable-adjusted logistic regression models to assess the relation between self-reported hypertension onset age with the presence of HMOD, with those who did not report hypertension as the referent group.

Results

Compared with individuals without self-reported hypertension, self-reported hypertension onset at <35 years was associated with LVH (odds ratio (OR), 2.38; 95% confidence interval (CI), 1.51–3.76), LVDD (OR, 2.32; 95% CI, 1.28–4.18, coronary calcification (OR, 2.87; 95% CI, 1.50–5.47), and albuminuria (OR, 1.62; 95% CI, 0.81–3.26). Self-reported hypertension onset at ≥45 years was only associated with LVDD (OR, 1.81; 95% CI, 1.06–3.08). The agreement between self-reported and objectively defined hypertension onset age groups was 78–79%.

Conclusions

Our findings suggest that self-reported hypertension onset age, a pragmatically feasible assessment in clinical practice, is a reasonable method for assessing risk of HMOD and CVD.