Agreement Between Self-Report and Medical Record Prevalence of 16 Chronic Conditions in the Alaska EARTH Study

Cardiovascular Disease, Depressive Symptoms, and Heart Failure in Mexican American Aged 75 Years and Older During 12 Years of Follow Up

Objective

To examine the relationship of cardiovascular disease (CVD) and high depressive symptoms (HDS) with heart failure (HF) among Mexican American older adults without HF at baseline over 12-years of follow-up.

Methods

A 12-year prospective cohort study of 1,018 Mexicans Americans aged 75 and older from the Hispanic Established Population for the Epidemiologic Study of the Elderly (2004-2016). Measures included socio-demographics, CVD (heart attack or stroke), HDS, smoking status, body mass index, cognitive function, and HF. Participant were grouped into: CVD and HDS (n=11), CVD only (n=122), HDS only (n=44), and no CVD or HDS (n=841). Odds ratio (OR) and 95% Confidence Interval (CI) of HF over time were estimated using the Generalized Estimating Equation.

Results

Participants with CVD and HDS and those with HDS only had greater odds (OR=4.70, 95%CI=1.98-11.2 and OR=3.26, 95%CI=1.82-5.84, respectively) of HF over time, after controlling for all covariates. No significant association was found between CVD only and HF (OR=1.25, 95%CI=0.90-1.76).

Conclusion

Mexican American older adults with HDS only or both HDS and CVD were at high risk of HF. Appropriate management of CVD and depressive symptoms may reduce the onset of HF among this population.

Liver disease, heart failure, and 13-year mortality among Mexican American older adults: Nativity differences

PURPOSE

To examine nativity differences of co-occurring liver disease (LD) and heart failure (HF) on 13-year mortality among Mexican American older adults.

METHODS

Prospective cohort study of 1601 Mexican Americans aged ≥ 75 years from the Hispanic Established Population for the Epidemiologic Study of the Elderly (2004/05-2016). Participants were grouped into four groups: no LD and no HF (n = 1138), LD only (n = 53), HF only (n = 382), and both LD and HF (n = 28). We used Cox proportional hazards regression model to estimate the hazard ratio (HR) and 95% confidence interval (CI) of death over time.

RESULTS

The HR of death, as a function of HF only, was 1.32 (95% CI=1.07-1.62) among US-born and 1.36 (95% CI=1.04-1.78) among foreign-born participants, vs. those with no LD and no HF. Among foreign-born participants, the HR of death as a function of LD and HF was 3.39 (95% CI=1.65-6.93) vs. those without either. LD alone was not associated with mortality in either group. Among US-born, co-occurring LD and HF was not associated with mortality.

CONCLUSIONS

Foreign-born participants with both LD and HF were at higher risk of mortality over 13 years of follow up.

Evaluating health claim assessment skills of parents with preschool children: A cross-sectional study using Informed Health Choices Claim Evaluation Tool

Background

Health literacy is a global problem and is particularly relevant when making health care decisions about small children. We analysed how parents of preschool children assess health claims and explored the predictors of their assessment skill.

Methods

We conducted a survey with questions from the Claim Evaluation Tools (CET) database, part of the Informed Health Choices (IHC) project, in ten paediatric primary care practices of the Split-Dalmatia County Health Center, Split, Croatia, from 1 February to 31 March 2023. Eligible participants were parents accompanying preschool-aged children for check-ups. We also collected data on parents' and children's demographic and health characteristics (including the presence of any chronic illness in the child), visits to paediatric emergency service, hospitalisations, vaccination status, the presence of chronic illness of parents or relatives, and whether parents had to made treatment decisions for themselves and/or their family member.

Results

Overall, 402 parents of preschool children (median age 35 years (interquartile range (IQR) = 31.0-38.3)) had a median IHC CET test score of 10.0 (IQR = 8.0-11.0) out of 12 questions. The multiple regression analysis showed that female gender, higher level of education, being employed, and having a history of a visit to paediatric emergency service were significant predictors of the test score, explaining 21.9% of the variance.

Conclusions

Parents of preschool children have a very good ability for critical assessment of health-related statements in a complex health care system and an environment of generally unsatisfactory health literacy. Further studies should explore how parents understand health claims in different geographical, socio-economic and cultural setting, and explore educational interventions to increase critical thinking abilities and informed decision-making, especially among fathers, unemployed parents and those with lower levels of education.

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.

Agreement Between Self-Reported Information and Health Register Data on Chronic Diseases in the Oldest Old

Purpose

To study the agreement on disease prevalence between survey data and national health register data among people aged over 90.

Patients and Methods

The survey data were from the Vitality 90+ Study conducted among 1637 community dwellers and persons in long-term care aged 90 and over in Tampere, Finland. The survey was linked with two national health registers, including hospital discharge data and prescription information. The prevalence of 10 age-related chronic diseases was calculated for each data source and the agreement between the survey and the registers was estimated using Cohen's kappa statistics and positive and negative percent agreement.

Results

The prevalence of most diseases was higher in the survey than in the registers. The level of agreement was highest when the survey was compared with information combined from both registers. Agreement was almost perfect for Parkinson's disease (ĸ=0.81) and substantial for diabetes (ĸ=0.75) and dementia (ĸ=0.66). For heart disease, hypertension, stroke, cancer, osteoarthritis, depression, and hip fracture, the agreement ranged from fair to moderate.

Conclusion

Self-reported information on chronic diseases shows acceptable agreement with health register data to warrant the use of survey methods in population-based health studies among the oldest old. It is important to acknowledge the gaps in health registers when validating self-reported information against register data.

Linking population-based cohorts with cancer registries in LMIC: a case study and lessons learnt in India

OBJECTIVES

In resource-constrained settings, cancer epidemiology research typically relies on self-reported diagnoses. To test a more systematic alternative approach, we assessed the feasibility of linking a cohort with a cancer registry.

SETTING

Data linkage was performed between a population-based cohort in Chennai, India, with a local population-based cancer registry.

PARTICIPANTS

Data set of Centre for Cardiometabolic Risk Reduction in South-Asia (CARRS) cohort participants (N=11 772) from Chennai was linked with the cancer registry data set for the period 1982-2015 (N=140 986).

METHODS AND OUTCOME MEASURES

Match*Pro, a probabilistic record linkage software, was used for computerised linkages followed by manual review of high scoring records. The variables used for linkage included participant name, gender, age, address, Postal Index Number and father's and spouse's name. Registry records between 2010 and 2015 and between 1982 and 2015, respectively, represented incident and all (both incident and prevalent) cases. The extent of agreement between self-reports and registry-based ascertainment was expressed as the proportion of cases found in both data sets among cases identified independently in each source.

RESULTS

There were 52 self-reported cancer cases among 11 772 cohort participants, but 5 cases were misreported. Of the remaining 47 eligible self-reported cases (incident and prevalent), 37 (79%) were confirmed by registry linkage. Among 29 self-reported incident cancers, 25 (86%) were found in the registry. Registry linkage also identified 24 previously not reported cancers; 12 of those were incident cases. The likelihood of linkage was higher in more recent years (2014-2015).

CONCLUSIONS

Although linkage variables in this study had limited discriminatory power in the absence of a unique identifier, an appreciable proportion of self-reported cases were confirmed in the registry via linkages. More importantly, the linkages also identified many previously unreported cases. These findings offer new insights that can inform future cancer surveillance and research in low-income and middle-income countries.

What is the impact of multimorbidity on out-of-pocket healthcare expenditure among community-dwelling older adults in Ireland? A cross-sectional study

OBJECTIVES

Individuals with multimorbidity use more health services and take more medicines. This can lead to high out-of-pocket (OOP) healthcare expenditure. This study, therefore, aimed to assess the association between multimorbidity (two or more chronic conditions) and OOP healthcare expenditure in a nationally representative sample of adults aged 50 years or over.

DESIGN

Cross-sectional analysis of data collected in 2016 from wave 4 of The Irish Longitudinal Study on Ageing.SettingIreland.ParticipantsCommunity-dwelling adults aged 50 years and over.MethodA generalised linear model with log-link and gamma distributed errors was fitted to assess the association between multimorbidity and OOP healthcare expenditure (including general practitioner, emergency department, outpatients, specialist consultations, hospital admissions, home care and prescription drugs).

RESULTS

Overall, 3453 (58.5%) participants had multimorbidity. Among those with any OOP healthcare expenditure, individuals with multimorbidity spent more on average per annum (€806.8 for two conditions, €885.8 for three or more conditions), than individuals with no conditions (€580.3). Pharmacy-dispensed medicine expenditure was the largest component of expenditure. People with multimorbidity on average spent more of their equivalised household income on healthcare (7.1% for two conditions, 9.7% for three or more conditions), than people with no conditions (5.0%). A strong positive association was found between number of conditions and OOP healthcare expenditure (p<0.001) and between having private health insurance and OOP healthcare expenditure (p<0.001). A strong negative association was found between eligibility for free primary/hospital care and heavily subsidised medicines and OOP healthcare expenditure (p<0.001).

CONCLUSIONS

This study suggests that having multimorbidity in Ireland increases OOP healthcare expenditure, which is problematic for those with more conditions who have lower incomes. This highlights the need for this financial burden to be considered when designing healthcare/funding systems to address multimorbidity, so that access to essential healthcare can be maximised for those with greatest need.

Mortality risk in older Japanese people based on self-reported dyslipidemia treatment and socioeconomic status: The JAGES cohort study

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Older people under self-reported dyslipidemia treatment had some distinction.

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They had higher income and education levels than those without treatment.

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Their self-reported treatment status was negatively associated with mortality risk.

Few studies consider socioeconomic status when assessing mortality risk in dyslipidemia cases. This study used cohort data from the 2010 Japan Gerontological Evaluation Study (JAGES), which contains data on older Japanese people, to associate socioeconomic status with mortality risk in patients treated for dyslipidemia. In this 6-year longitudinal study, we examined 47,275 older Japanese people aged ≥ 65 years who could independently perform activities of daily living. Patients’ background characteristics were classified based on their dyslipidemia treatment status and were assessed using the chi-squared test. The mortality risk was assessed using the Cox proportional hazards model, wherein the objective and explanatory variables were total mortality and self-report of dyslipidemia treatment, respectively. The participants were stratified by sex and age into younger (aged 65–74 years) and older (aged ≥ 75 years) groups of men and women. The results were adjusted, with health condition, health behavior, and socioeconomic status as confounding factors. The adjusted hazard ratios of 5514 people who died during the follow-up who had self-reported dyslipidemia treatment were 0.49 [95% confidence interval (CI) 0.35–0.69] for younger men; 0.57 (95% CI 0.42–0.76) for older men; 0.52 (95% CI 0.34–0.80) for younger women; and 0.47 (95% CI 0.33–0.67) for older women. Older people undergoing treatment for dyslipidemia had factors beneficial for health, such as good socioeconomic status. Despite considering these factors, individuals undergoing dyslipidemia treatment had a negative association with mortality risk.

Agreement Between Self-Reported Information and Administrative Data on Comorbidities, Imaging and Treatment in Denmark - A Validation Study of 38,745 Patients with Knee or Hip Osteoarthritis

Purpose

To validate self-reported information obtained from patients with knee or hip osteoarthritis (OA) in primary care against administrative data from the three national Danish registries.

Patients and Methods

We compared the baseline and 12-month follow-up data from 38,745 patients with knee or hip OA participating in the Good Life with osteoArthritis in Denmark (GLA:D^®) program with registry-based data on joint surgeries, pain medication dispensing, radiographs, and hospital diagnoses. Agreement was calculated using Cohen's Kappa (k) and percentage agreement, both with 95% CI.

Results

There was a moderate agreement between self-report and registry-based data for previous knee surgery (k=0.58, 84.99%) and a substantial agreement for previous hip surgery (k=0.73, 97.05%). Agreement varied from 0.05 to 0.95 and 84.99% to 99.94% for different types of surgeries with lowest agreement for collateral ligament surgery (k=0.05, 99.82%) and highest agreement for joint replacement (k=0.95, 99.54% for knee; k=0.95, 99.48% for hip). There was a moderate agreement (k=0.41, 81.59%) for knee and a slight agreement (k=0.20, 64.79%) for hip radiographs. Agreement varied from 0.01 to 0.53 and 65.39% to 99.90% for pain medication with lowest agreement for topical NSAID (k=0.01, 95.00%) and highest agreement for opioids (k=0.53, 92.56%). For comorbidities, agreement varied from 0.14 to 0.90 and 78.07% to 98.91%, with lowest agreement for anemia or other blood disease (k=0.14, 97.63%) and highest agreement for diabetes (k=0.90, 98.73%).

Conclusion

As the most common types of pain medication used by patients with OA can be bought over-the-counter and as most OA patients are treated in primary care, which is often not covered by national registries, self-report of pain medication use and comorbidities is preferred but cannot be sufficiently validated against registry-based data. Future studies collecting self-reported information on joint surgery and pain medication from patients with OA should use a less detailed categorization to improve accuracy.

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

Background

Health administrative data were increasingly used for chronic diseases (CDs) surveillance purposes. This cross sectional study explored the agreement between Belgian compulsory health insurance (BCHI) data and Belgian health interview survey (BHIS) data for asserting CDs.

Methods

Individual BHIS 2013 data were linked with BCHI data using the unique national register number. The study population included all participants of the BHIS 2013 aged 15 years and older. Linkage was possible for 93% of BHIS-participants, resulting in a study sample of 8474 individuals. For seven CDs disease status was available both through self-reported information from the BHIS and algorithms based on ATC-codes of disease-specific medication, developed on demand of the National Institute for Health and Disability Insurance (NIHDI). CD prevalence rates from both data sources were compared. Agreement was measured using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) assuming BHIS data as gold standard. Kappa statistic was also calculated. Participants’ sociodemographic and health status characteristics associated with agreement were tested using logistic regression for each CD.

Results

Prevalence from BCHI data was significantly higher for CVDs but significantly lower for COPD and asthma. No significant difference was found between the two data sources for the remaining CDs. Sensitivity was 83% for CVDs, 78% for diabetes and ranged from 27 to 67% for the other CDs. Specificity was excellent for all CDs (above 98%) except for CVDs. The highest PPV was found for Parkinson’s disease (83%) and ranged from 41 to 75% for the remaining CDs. Irrespective of the CDs, the NPV was excellent. Kappa statistic was good for diabetes, CVDs, Parkinson’s disease and thyroid disorders, moderate for epilepsy and fair for COPD and asthma. Agreement between BHIS and BCHI data is affected by individual sociodemographic characteristics and health status, although these effects varied across CDs.

Conclusions

NHIDI’s CDs case definitions are an acceptable alternative to identify cases of diabetes, CVDs, Parkinson’s disease and thyroid disorders but yield in a significant underestimated number of patients suffering from asthma and COPD. Further research is needed to refine the definitions of CDs from administrative data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-020-00500-4.

Sarcopenic obesity and 10-year cardiovascular disease risk scores in cancer survivors and non-cancer participants using a nationwide survey

OBJECTIVE

To evaluate the associations of combinations of sarcopenia and adiposity phenotypes with 10-year cardiovascular disease (CVD) risk scores in cancer survivors and non-cancer participants.

METHODS

In 19,019 individuals including 1023 cancer survivors free of CVD who were aged ≥30 years from the Korea National Health and Nutrition Examination Survey, combination groups of sarcopenia, obesity and abdominal obesity based on handgrip strength, BMI and waist circumference, respectively, were generated and 10-year CVD risk scores based on Framingham risk model were determined.

RESULTS AND CONCLUSION

After adjusting for socio-demographic factors, health behaviours, dietary intake of nutrients and time since cancer diagnosis and current cancer therapy (in cancer survivors), cancer survivors with sarcopenic non-obesity, non-sarcopenic abdominal obesity or sarcopenic abdominal obesity had, respectively, 84%, 85% and 3.61-fold higher odds for ≥10% CVD risk scores compared with cancer survivors without those phenotypes. In non-cancer participants, sarcopenia, obesity, abdominal obesity and combinations of those phenotypes had higher odds from 1.37 (in those with obesity) to 4.24 (in those with sarcopenic abdominal obesity) for ≥10% CVD risk scores compared with reference phenotypes. In conclusion, cancer survivors and non-cancer participants with sarcopenia, obesity, abdominal obesity or combination of those phenotypes had increased 10-year CVD risk scores.

Validity of self-reported cancer: Comparison between self-report versus cancer registry records in the Geelong Osteoporosis Study

BACKGROUND

Determining the validity of self-reported data is important. The aim of this study was to assess the validity of self-reported cancer and investigate factors associated with accurate reporting in men and women.

METHODS

Study participants (n = 1727) from the Geelong Osteoporosis Study, located in south-eastern Australia, were utilised. Self-reported cancer data were compared to Victorian Cancer Registry records. Age, socioeconomic status (SES), education and time between cancer diagnosis and study appointment were investigated as factors associated with accuracy of self-report.

RESULTS

There were 142 participants who self-reported a cancer and 135 with a VCR record. Comparing self-report to any registry record, sensitivity was 63.7 %, specificity 96.5 %, PPV 60.6 %, NPV 96.9 %, and overall agreement ĸ0.588. Comparing exact-match records, sensitivity was 58.8 %, specificity 95.5 %, PPV 49.3 %, NPV 96.9 % and overall agreement ĸ0.499. In logistic regression models, post-secondary education was independently associated with accuracy of any (OR 1.72, 95 % CI 1.10-2.70) and exact-match (OR 1.59, 95 % CI 1.05-2.42) self-report, compared to cancer registry record. For any cancer, being aged >70 years was inversely associated with accuracy (OR 0.24, 95 % CI 0.15-0.38). Likewise, for matched cancer reporting, those aged 60-70 years (OR 0.51, 95 %CI 0.30-0.88) and >70 years (OR 0.23, 95 % CI 0.15-0.35) were less accurate. No other significant associations were detected.

CONCLUSION

Results suggest moderate agreement between self-report and registry data for any cancer among men and women. However, when comparing self-report to registry data for exact-match cancer type, level of overall agreement deteriorated. Self-report cancer data may be acceptable for determining a history of cancer, although, is less accurate in identifying history of specific cancer types documented in registry-based data.

How effective are population health surveys for estimating prevalence of chronic conditions compared to anonymised clinical data?

INTRODUCTION

Population health surveys are used to record person-reported outcome measures for chronic health conditions and provide a useful source of data when evaluating potential disease burdens. The reliability of survey-based prevalence estimates for chronic diseases is unclear nonetheless. This study applied methodological triangulation via a data linkage method to validate prevalence of selected chronic conditions (angina, myocardial infarction, heart failure, and asthma).

METHODS

Linked healthcare records were used for a combined cohort of 11,323 adults from the 2013 and 2014 sweeps of the Welsh Health Survey (WHS). The approach utilised consented survey data linked to primary and secondary care electronic health record (EHR) data back to 2002 within the Secure Anonymised Information Linkage (SAIL) Databank.

RESULTS

This descriptive study demonstrates validation of survey and clinical data using data linkage for selected chronic cardiovascular conditions and asthma with varied success. The results indicate that identifying cases for separate cardiovascular conditions was limited without specific medication codes for each condition, but more straightforward for asthma, where there was an extensive list of medications available. For asthma there was better agreement between prevalence estimates based on survey and clinical data as a result.

CONCLUSION

Whilst the results provide external validity for the WHS as an instrument for estimating the burden of chronic disease, they also indicate that a data linkage appproach can be used to produce comparable prevalence estimates using clinical data if a defined condition-specific set of clinical codes are available.

Is there an agreement between self-reported medical diagnosis in the CARTaGENE cohort and the Québec administrative health databases?

BACKGROUND

Population health studies often use existing databases that are not necessarily constituted for research purposes. The question arises as to whether different data sources such as in administrative health data (AHD) and self-report questionnaires are equivalent and lead to similar information.

OBJECTIVES

The main objective of this study was to assess the level of agreement between self-reported medical conditions and medical diagnosis captured in AHD. A secondary objective was to identify predictors of agreement among medical conditions between the two data sources. Therefore, the purposes of the study were to explore the extent to which these two methods of commonly used public health data collection provide concordant records and identify the main predictors of statistical variations.

METHODS

Data were extracted from CARTaGENE, a population-based cohort in Québec, Canada, which was linked to the provincial health insurance records of the same individuals, namely the MED-ÉCHO database from the Régie de l'assurance maladie du Québec (RAMQ) and the fee-for-service billing records provided by the physician, for the time period 1998-2012. Agreement statistics (kappa coefficient) along with sensitivity, specificity and predictive positive value were calculated for 19 chronic conditions and 12 types of cancers. Logistic regressions were used to identify predictors of concordance between self-report and AHD from significant covariates (sex, age groups, education, region, income, heavy utilization of health care system and Charlson comorbidity index).

RESULTS

Agreement between self-reported data and AHD across diseases ranged from kappa of 0.09 for chronic renal failure to 0.86 for type 2 diabetes. Sensitivity of self-reported data was higher than 50% for 14 out of the 31 medical conditions studied, especially for myocardial infarction (88.62%), breast cancer (86.28%), and diabetes (85.06%). Specificity was generally high with a minimum value of 89.70%. Lower concordance between data sources was observed for higher frequency of health care utilization and higher comorbidity scores.

CONCLUSION

Overall, there was moderate agreement between the two data sources but important variations were found depending on the type of disease. This suggests that CARTaGENE's participants were generally able to correctly identify the kind of diseases they suffer from, with some exceptions. These results may help researchers choose adequate data sources according to specific study objectives. These results also suggest that Québec's AHD seem to underestimate the prevalence of some chronic conditions, which might result in inaccurate estimates of morbidity with consequences for public health surveillance.

How does parent/self-reporting of common respiratory conditions compare with medical records among Aboriginal and Torres Strait Islander (Indigenous) children and young adults?

AIM

Self-reporting and/or data from medical records are frequently used in studies to ascertain health history. Data on the discrepancies between these information sources is lacking for Indigenous Australians. This study reports such data for selected respiratory and atopic conditions common among Indigenous Australians.

METHODS

Data were extracted from the Indigenous respiratory reference value study, a multicentre cross-sectional study of Indigenous children and young adults (3-25 years) between June 2015 and November 2017. Only those living in rural/remote regions were included. Self-reported history was collected from parents (if participants <18 years) or participants. Medical records were manually reviewed. Participants with incomplete data (missing self-reported and/or medical record information) were excluded. Agreement between sources was examined using Cohen's kappa.

RESULTS

Of 1097 participants, 889 (97.1% <18 years) had sufficient self-reported and medical record histories for comparison. Asthma was self-reported by 15.7% of participants and was reported in medical records for 10.3% (κ = 0.53, 95% confidence interval (CI) 0.45-0.61). For bronchiectasis, the reported rates were 1.5 and 0.7% (κ = 0.52, 95% CI 0.25-0.80), pneumonia 1.1 and 5.8% (κ = 0.15, 95% CI 0.02-0.27), allergic rhinitis 6.6 and 0.6% (κ = 0.05, 95% CI -0.03, 0.13) and eczema 5.8 and 6.2% (κ = 0.30, 95% CI 0.18-0.42).

CONCLUSIONS

Within our cohort, agreement was moderate for asthma and bronchiectasis, fair for eczema and poor for pneumonia and allergic rhinitis. These results highlight the challenges associated with how best to obtain an accurate health history within Australian Indigenous rural/remote communities. Generalisability of findings and contributions of poor health knowledge and/or poor medical record documentation need further exploration.

Agreement between self-reported and central cancer registry-recorded prevalence of cancer in the Alaska EARTH study

Reliance on self-reported health status information as a measure of population health can be challenging due to errors associated with participant recall. We sought to determine agreement between self-reported and registry-recorded site-specific cancer diagnoses in a cohort of Alaska Native people. We linked cancer history information from the Alaska Education and Research Towards Health (EARTH) cohort and the Alaska Native Tumor Registry (ANTR), and calculated validity measures (sensitivity, specificity, positive predictive value, negative predictive value, kappa). Multiple logistic regression models were used to assess independent associations of demographic variables with incorrect reporting. We found that among Alaska EARTH participants, 140 self-reported a history of cancer, and 99 matched the ANTR. Sensitivity ranged from 79% (colorectal cancer) to 100% (prostate cancer); specificity was over 98% for all-sites examined. Kappa was higher among prostate and female breast cancers (κ=0.86) than colorectal cancers (κ=0.63). Women (odds ratio [OR] (95% confidence interval [CI]): 2.8 (1.49-5.31)) and participants who were older than 50 years (OR (95% CI): 2.8 (1.53-4.12)) were more likely to report incorrectly. These data showed good agreement between self-reported and registry-recorded cancer history. This may be attributed to the high quality of care within the Alaska Tribal Health System, which strongly values patient-provider relationships and the provision of culturally appropriate care.

Follow-up Study Methods for a Longitudinal Cohort of Alaska Native and American Indian People Living within Urban South Central Alaska: The EARTH Study

Longitudinal data are needed to investigate chronic disease causation and improve prevention efforts for Alaska Native and American Indian (ANAI) people. This paper describes the methods used to conduct follow-up data collection of a longitudinal cohort that enrolled ANAI adults between 2004 and 2006 in south central Alaska. The follow-up study re-examined ANAI participants in a large, urban centre in south central Alaska between 2015 and 2017. Computerized surveys were used to collect self-reported health, lifestyle, physical activity, and diet data. Clinical measurements included blood pressure, fasting blood glucose and lipid panel, urine albumin/creatinine, height, weight, and waist and hip circumference. Participants were provided individual results at the conclusion of their visit. A total of 1320 south central Alaska study participants completed the baseline visit. Study staff attempted to contact all living cohort members for inclusion in the follow-up study. More than 11,000 attempted contacts were made. Of the 637 available for participation, 388 completed the follow-up visit. The proportion of women increased from baseline to follow-up examinations (67 vs. 72%, p < 0.01). Self-reported health status of being married or living as married (46% vs. 39%, p < 0.01), and those reporting being employed or self-employed (55% vs. 47%, p < 0.01) were higher at follow-up when compared to baseline. Almost all participants at follow-up (97%) agreed to long-term storage of biological specimens for future study. Despite demographic differences between the follow-up and baseline cohorts, longitudinal data collected will provide novel insight on chronic disease development and prevention for ANAI people as well as other populations.

Cancer incidence and associations with known risk and protective factors: the Alaska EARTH study

PURPOSE

Cancer is the leading cause of mortality among Alaska Native (AN) people. The Alaska Education and Research Towards Health (EARTH) cohort was established to examine risk and protective factors for chronic diseases, including cancer, among AN people. Here, we describe the cancer experience of the Alaska EARTH cohort in relation to statewide- and region-specific tumor registry data, and assess associations with key cancer risk factors.

METHODS

AN participants were recruited into the Alaska EARTH cohort during 2004-2006. Data collected included patient demographic, anthropometric, medical and family history, and lifestyle information. This study linked the Alaska EARTH data with cancer diagnoses recorded by the Alaska Native Tumor Registry (ANTR) through 12/31/15. We compared EARTH incidence to ANTR statewide incidence. We examined independent associations of smoking status, diet, BMI, and physical activity with incident all-site cancers using multivariable-adjusted Cox proportional hazards models.

RESULTS

Between study enrollment and 2015, 171 of 3,712 (4.7%) Alaska EARTH study participants were diagnosed with cancer. The leading cancers among Alaska EARTH participants were female breast, lung, and colorectal cancer, which reflected those observed among AN people statewide. Incidence (95% CI) of cancer (all sites) among Alaska EARTH participants was 629.7 (510.9-748.6) per 100,000 person-years; this was comparable to statewide rates [680.5 (660.0-701.5) per 100,000 population]. We observed lower risk of all-sites cancer incidence among never smokers.

CONCLUSIONS

Cancer incidence in the Alaska EARTH cohort was similar to incidence observed statewide. Risk and protective factors for leading cancers among AN people mirror those observed among other populations.

Agreement between self-reports, proxy-reports and the National Patient Register regarding diagnoses of cardiovascular disorders and diabetes mellitus in a population-based sample of 80-year-olds

Background

cognitive impairment is common among older adults, necessitating the use of collateral sources in epidemiological studies involving this age group. The objective of this study was to evaluate agreement between self- and proxy-reports of cardiovascular disorders and diabetes mellitus in a population-based sample of 80-year-olds. Further, both self- and proxy-reports were compared with hospital register data.

Methods

data were obtained from the Gothenburg H70 Birth Cohort Studies in Sweden. The study had a cross-sectional design and information was collected through semi-structured interviews in 2009–2012 from participants born in 1930 (N = 419) and their proxy informants. The National Patient Register provided diagnoses registered during hospital stays. Agreement was measured with Kappa values (K).

Results

agreement between self- and proxy-reports was substantial for diabetes mellitus (K = 0.79), atrial fibrillation (K = 0.61), myocardial infarction (K = 0.75), angina pectoris (K = 0.73) and hypertension (K = 0.62), and fair for intermittent claudication (K = 0.38) and heart failure (K = 0.40). Compared to the National Patient Register, a large proportion of those with a hospital discharge diagnosis were also self- and proxy-reported.

Conclusions

proxy informants can be an important source of information, at least for well-defined conditions such as myocardial infarction, angina pectoris and diabetes mellitus.

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

Background

Three data sources are generally used in monitoring health on the population level. Health interview surveys (HISs) are based on participants' self-report. Health examination surveys (HESs) yield more objective data, and also persons who are unaware of their elevated risks can be detected. Medical records (MRs) and other administrative registers also provide objective data, but their availability, coverage and quality vary between countries. We summarized studies comparing self-reported data with (i) measured data from HESs or (ii) MRs. We aimed to describe differences in feasibility and comparability of different data sources for monitoring (i) elevated blood pressure or hypertension (ii) elevated blood glucose or diabetes and (iii) elevated total cholesterol.

Methods

We conducted a literature search to identify studies, which validated self-reported measures against objective measures. We found 30 studies published since the year 2000 fulfilling our inclusion criteria (targeted to adults and comparing prevalence among the same persons).

Results

Hypertension and elevated total cholesterol were prone to be under-estimated in HISs. The under-estimate was more pronounced, when the HIS data were compared with HES data, and lower when compared with MRs. For diabetes, the HISs and the objective methods resulted in fairly similar prevalence rates.

Conclusion

The three data sources measure different manifestations of the risk factors and cannot be expected to yield similar prevalence rates. Using HIS data only may lead to under-estimation of elevated risk factor levels or disease prevalence. Whenever possible, information from the three data sources should be evaluated and combined.

Measurement Error and Misclassification in Electronic Medical Records: Methods to Mitigate Bias

PURPOSE OF REVIEW

We sought to: 1) examine common sources of measurement error in research using data from electronic medical records (EMR), 2) discuss methods to assess the extent and type of measurement error, and 3) describe recent developments in methods to address this source of bias.

RECENT FINDINGS

We identified eight sources of measurement error frequently encountered in EMR studies, the most prominent being that EMR data usually reflect only the health services and medications delivered within the specific health facility/system contributing to the EMR data. Methods for assessing measurement error in EMR data usually require gold standard or validation data, which may be possible using data linkage. Recent methodological developments to address the impact of measurement error in EMR analyses were particularly rich in the multiple imputation literature.

SUMMARY

Presently, sources of measurement error impacting EMR studies are still being elucidated, as are methods for assessing and addressing them. Given the magnitude of measurement error that has been reported, investigators are urged to carefully evaluate and rigorously address this potential source of bias in studies based in EMR data.

Individual Data Linkage of Survey Data with Claims Data in Germany-An Overview Based on a Cohort Study

Research based on health insurance data has a long tradition in Germany. By contrast, data linkage of survey data with such claims data is a relatively new field of research with high potential. Data linkage opens up new opportunities for analyses in the field of health services research and public health. Germany has comprehensive rules and regulations of data protection that have to be followed. Therefore, a written informed consent is needed for individual data linkage. Additionally, the health system is characterized by heterogeneity of health insurance. The lidA-living at work-study is a cohort study on work, age and health, which linked survey data with claims data of a large number of statutory health insurance data. All health insurance funds were contacted, of whom a written consent was given. This paper will give an overview of individual data linkage of survey data with German claims data on the example of the lidA-study results. The challenges and limitations of data linkage will be presented. Despite heterogeneity, such kind of studies is possible with a negligibly small influence of bias. The experience we gain in lidA will be shown and provide important insights for other studies focusing on data linkage.