The European Journal of Public Health Advance Access originally published online on August 3, 2006
The European Journal of Public Health 2007 17(2):199-205; doi:10.1093/eurpub/ckl113
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Health services research |
Comparison of routine care self-reported and biometrical data on hypertension and diabetes: results of the Utrecht Health Project
Esther A. Molenaar1,2, Erik J.C. Van Ameijden1,2, Diederick E. Grobbee1 and Mattijs E. Numans1
1 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht Utrecht, The Netherlands
2 Municipal Health Service Utrecht, Utrecht The Netherlands
Correspondence: Esther A Molenaar, MSc, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Stratenum 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands, tel.: +31 30 2538644, fax: +31 30 2539028, e-mail: E.A.molenaar{at}umcutrecht.nl
Received January 9, 2006, accepted June 2, 2006
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Abstract |
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Background: Information on the prevalence of diseases is commonly gathered by questionnaires. Although the method is relatively inexpensive and efficient as opposed to physical examinations, the validity of the information collected is often questioned. The objective of this study was to assess the value of biometrical data complementary to self-reported questionnaire information for estimating the prevalence of hypertension and diabetes in the population at large and to examine factors that affect the accuracy of self-reporting. Methods: Baseline data of 4950 adult participants of the Utrecht Health Project, a community-based prospective cohort study, were used to calculate sensitivity and specificity of self-reported hypertension and diabetes with the results of blood pressure measurements and blood glucose levels, corrected for current medication use, as the reference standard. Multivariate logistic regression analysis was performed to determine which participants' characteristics independently predicted the accuracy of self-reports. Results: Overall sensitivity was 34.5% for self-reported data on hypertension and 58.9% for diabetes, while overall specificity was high for both conditions (96.4 and 99.4%, respectively). The agreement between self-reported and biometrical data was higher for diabetes than for hypertension and varied per subgroup. Conclusions: The use of self-reported data to estimate the prevalence of hypertension and diabetes may lead to underestimated prevalence estimates and biased associations with risk factors due to differential misclassification. Adding biometrical measurements to self-reported questionnaire information will assure the validity of the data. The magnitude of the additional value of biometrical data depends on the condition studied and the characteristics of the population under investigation.
Keywords: accuracy, data collection, diabetes, hypertension
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Introduction |
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In public health surveys information on the prevalence of diseases in the population at large is commonly gathered by questionnaires.1 Although the method is relatively inexpensive and efficient opposed to physical examinations and anthropometrics, the validity of the information collected is often questioned as it may be threatened by random and systematic errors.2,3 The accuracy of self-reported data on medical history depends amongst others on the subjects' knowledge and understanding of the relevant information, ability to recall it, and willingness to report it.4 Furthermore, diseases may not (yet) have been diagnosed.5 The rate of incorrect reporting and therefore misclassification can be significant and can vary by disease, population and by the severity of the disease.5–10
Hypertension and diabetes are two major chronic conditions that contribute considerably to the global burden of disease.11,12 Accurate information about the prevalence of these conditions is essential for health care planners, policy makers and health professionals. Several studies have tried to assess the accuracy of self-reported questionnaire information on hypertension and/or diabetes but the majority of these studies was based on relatively small samples and/or restricted to certain subgroups, notably the elderly.1–5,7–9,13–19 Limited information is available on the accuracy of self-reported data in large community-based samples.3
The present study utilised baseline data of a comprehensive cohort study that starts with an extended intake procedure in primary care. The value of biometrical data, as extracted from the extended intake procedure, was assessed complementary to self-reported questionnaire information for estimating the prevalence of hypertension and diabetes. This approach allowed for an evaluation of the accuracy of reported data in a large community-wide population taken from primary care practices. In addition, factors were examined that affect sensitivity and specificity of self-reported disease information in subgroups to identify possible differential misclassification.
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Methods |
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Study population
The present study used baseline data from the Utrecht Health Project (UHP). Details of the study have been published previously.20 In summary, the UHP is a prospective cohort study conducted in a newly developed residential area in the Netherlands (i.e. Leidsche Rijn). All new residents of the area are invited by their new primary care general practitioner to participate in the UHP. At baseline an individual health profile (IHP) is made by means of an extended intake procedure for the new general practitioner. This procedure includes information from the following three sources: (i) data on past medical history and use of medication obtained from the previous general practitioner and the pharmacist; (ii) answers to a self-administered postal health questionnaire; and (iii) results from a physical examination by research nurses, laboratory tests, and diagnostic tests. The health questionnaire is completed before the physical examination takes place.
The Medical Ethics Commission of the University Medical Center Utrecht in The Netherlands has approved the UHP. The UHP started to recruit participants in 2001 and since then response has been steadily increasing. By January 2005 13 128 inhabitants were invited, of whom 6755 gave informed consent (response 51.4%). Baseline data were complete for 6304 (48%) participants, of whom 4950 were aged 
18 years.
The present analysis was based on the information of the first 4950 adult participants of the UHP.
Data
The self-reported information on hypertension was based on the question ‘Have you had a high blood pressure during the past 12 months, that has (ever) been diagnosed by a general practitioner or specialist?’ The self-reported information on diabetes was based on the question ‘Have you had diabetes during the past 12 months, that has (ever) been diagnosed by a general practitioner or specialist?’
Blood pressure was measured twice on a single occasion as part of the IHP. The average of the two blood pressure readings was used to determine blood pressure levels. In agreement with current guidelines of the Dutch College of General Practitioners, hypertension was defined as a systolic blood pressure 140 mmHg (if age <60 years) or 160 mmHg (if age 60 years) and/or a diastolic blood pressure 90 mmHg (all ages) and current use of antihypertensive drug for the indication of hypertension.21
In addition glucose levels were determined as part of the IHP. In agreement with current diabetes guidelines of the Dutch College of General Practitioners, diabetes was defined as fasting venous glucose levels >6.9 mmol/l or fasting capillary glucose levels >6.0 mmol/l or non-fasting venous glucose levels >11.0 mmol/l and current use of antidiabetic drug.22
When pharmaceutical data were incomplete, self-reported information on current use of antihypertensive drugs for the indication of hypertension or current use of antidiabetic drug was checked and used. An overview of the methods used to classify whether participants were having hypertension and/or diabetes is given in table 1. Biometrical measurements corrected for current medication use are further referred to as biometrical measurements/data.
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Self-reported data in the questionnaire provided for the majority of the information on the participant characteristics. According to Dutch standards, ethnicity was based on the country of birth of the participant and both parents. Educational level was used as measure of social economic status (SES) since it is considered the most stable indicator of SES throughout adulthood.23 The variable referred to the highest education level completed, with the respondent choosing one of the eight categories in the questionnaire. History of cardiovascular disease (CVD) was based on the question ‘Have you had serious heart complaints or a stroke for the past 12 months, that has (ever) been diagnosed by a general practitioner or specialist?’ Participants having both hypertension and diabetes, based on the biometrical data, were defined as having a combination of the conditions. Height and weight were measured as part of the IHP to the nearest 0.1 cm and 0.5 kg. Overweight was defined as a body mass index
25 kg per m2. The presence of depressive symptoms was assessed by means of the score on the SCL-90.24 A score 25 was considered high and used as indicator for the presence of depressive symptoms.25 Utilisation of health care was a summary measure of contact with the general practitioner or visit to a specialist the past 2 months or hospitalisation the past 12 months. Contact with the general practitioner also included telephone calls with the general practitioner or the assistant and could refer to the former or current general practitioner.
Data analysis
Age was classified in five categories: 18–29, 30–39, 40–49, 50–59, and 60+. Ethnicity was dichotomised as Dutch and non-Dutch. Socioeconomic status was grouped into three standard hierarchic levels: low (no formal education, lower secondary education or intermediate secondary education), middle (higher secondary education), and high (higher vocational or university education).
To assess the difference in prevalence estimates by data collection method, the prevalence of hypertension and diabetes was calculated based on self-reported information as well as on results from biometrical measurements. To assess the accuracy of the self-reported data, sensitivity and specificity were calculated with the results of the biometrical measurements as the reference standard for a diagnosis of hypertension or diabetes. Sensitivity was defined as the percentage of participants with a diagnosis, based on the biometrical data, who reported to have the condition in the questionnaire. Specificity was defined as the percentage of participants without a diagnosis, who reported not to have the condition in the questionnaire.
Sensitivity and specificity estimates were calculated across different subgroups. Pearson chi-squared tests were used to assess differences in sensitivity and specificity between subgroups. If one of the cells had a count <5, Fisher's exact tests were employed.
To determine which participant characteristics independently predicted the accuracy of self-reports, multivariate logistic regression analysis with backwards-variable selection was performed with above-mentioned variables as independent factors, considering the dichotomous variable of correct self-reporting as the dependent variable. The analyses were done separately for the participants with a diagnosis and those without a diagnosis, to study sensitivity and specificity respectively. Participants with missing or unknown data on a particular variable were excluded from that analysis only. All analyses were performed with the SPSS package (version 12.0).
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Results |
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General characteristics
More than half (55.1%) of the participants were female, the majority aged 30–39 years with a mean age of 39.3 ± 12.5 years. The vast majority was of Dutch origin, rather well educated and had no history of CVD or a combination of hypertension and diabetes. Half of the participants were overweight and in nearly a fifth of the participants depressive symptoms were present. Sixty-three percent of the study population had recently been in contact with health care (table 2).
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Prevalence
The prevalence of hypertension and diabetes based on the biometrical data was 22.9 [ 95% confidence interval (95% CI), 21.7–24.1) and 3.6% (95% CI, 3.0–4.1), respectively. Self-reported data underestimated the prevalence of hypertension >2-fold. The prevalence of diabetes based on the self-reported data lead to an underestimation of 40% compared with the reference standard (table 3).
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Sensitivity
Almost two-third of the participants with confirmed hypertension misclassified themselves as not having hypertension and only a third reported correctly on their condition [overall sensitivity, 34.5%; 95% CI, 31.7–37.4; table 3]. The degree of accurate reporting differed between subgroups (table 4). It was almost four times more likely for participants who had recently used health care to report hypertension accurately compared with those who had not [odds ratio (OR) = 3.85; 95% CI, 2.70–5.47]. The likelihood of correct reporting increased as age increased (OR = 1.42; 95% CI, 1.28–1.57) and females were almost twice more likely to accurately report hypertension when present than men (OR = 1.96; 95% CI, 1.45–2.66). In addition, participants with a history of CVD (OR = 2.57; 95% CI, 1.08–6.13) overweight (OR = 1.45; 95% CI, 1.05–2.01), or depressive symptoms (OR = 1.57; 95% CI, 1.09–2.27) were more likely to correctly classify themselves as having a diagnosis of hypertension than those without. Among the participants with depressive symptoms, men were more likely to accurately report hypertension than women.
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The overall sensitivity for self-reported diabetes was higher than for hypertension. More than half of the participants with diabetes, according to the biometrical measurement, reported the condition correctly (overall sensitivity 58.9%; 95% CI, 51.1–66.8; table 3). The degree of accurate reporting differed between subgroups (table 4). There were not enough diabetic participants (N = 151) to allow multivariate analyses but crude analyses showed that, as for hypertension, accurate reporting was more common among recent health care users (ORcrude= 3.98; 95% CI, 1.44–11.05). On the other hand, females were twice less likely to report diabetes when present (ORcrude= 0.48; 95% CI 0.25–0.92).
Specificity
The overall specificity for self-reported hypertension was high. Of those with normal blood pressure measurements, 96.4% (95% CI, 95.7–97.0) classified themselves correctly whereas 3.7% erroneously indicated that they were having hypertension (table 3). Women (OR = 0.61; 95% CI, 0.40–0.92), elderly persons (OR = 0.69; 95% CI, 0.61–0.79), participants with a history of CVD (OR = 0.13; 95% CI, 0.06–0.27), and recent health care users (OR = 0.39; 95% CI, 0.23–0.65) were less likely to correctly report the absence of hypertension (table 4).
Self-reported diabetes had a higher specificity than hypertension. Of all participants without diabetes 99.4% (95% CI, 99.2–99.7) accurately reported absence of the disease (table 3). A history of CVD (OR = 0.06; 95% CI, 0.02–0.16) and depressive symptoms (OR = 0.26; 95% CI, 0.11–0.63) were found to be independent predictors for accurate reporting (table 4).
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Discussion |
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The present analysis of self-reported and biometrical data on hypertension and diabetes obtained in a large community-based cohort taken from primary practices shows a sensitivity of 34.5% for self-reported data on hypertension and a sensitivity of 58.9% for diabetes. Specificity was high for both conditions. Thus, few participants without the condition erroneously report hypertension or diabetes in a questionnaire, but 65% of the cases of hypertension and
40% of the cases of diabetes will be missed. The agreement between self-reported and biometrical data was higher for diabetes than for hypertension and varied across subgroups. Gender, age, recent utilisation of health care and a history of CVD were found to be the strongest independent predictors of the accuracy of self-reported data on hypertension and diabetes. There are certain limitations to be addressed to appreciate the findings in this study. First, due to the limited availability of pharmaceutical data, information on current medication use was based on pharmaceutical as well as self-reported data to minimise under-ascertainment of medication use. Although Klungel et al.26 reported a close agreement for data on current prescription medication use between both information sources, recall sensitivity was higher for questions about medication used for a specific indication than for open-ended questions as applied in the current study. Incomplete information on medication use may therefore account for misclassification of participants whose biometrical data were normalised due to medication use (the supposedly false positives). In our judgement, this potential bias will be small and not influence our main conclusions
Second, the reliance on two measurements taken during a single physical examination instead on multiple measurements over longer time intervals may have lead to biased estimates of the prevalence of disease.15 In the case of blood pressure measurements presence of white coat hypertension (WCH) could induce an overestimation of the prevalence of hypertension and a concomitant underestimate of the sensitivity of the self-report.4 In addition, general practitioners may use higher cut-off values for the diagnosis of hypertension, classifying patients with hypertension according to the guidelines as not having hypertension.5,15 When hypertension was defined as a systolic blood pressure of 160 mmHg, and/or a diastolic blood pressure of 95 mmHg for all age categories, the sensitivity of self-reported hypertension in this study increased from 34.5 to 54.7% whereas the specificity decreased slightly from 96.4 to 95.1%. This shows the strong influence of the criteria for hypertension on the sensitivity of self-reported data.
The study was done in a rather homogeneous (78.6% Dutch, 80.1% middle or high educated) population. Although the sample reflects the demographic composition of the inhabitants of the residential area studied, generalisation to other, more heterogeneous, populations is uncertain.
Finally, due to a limited number of diabetic participants there was limited power to study the influence of participants' characteristics on the sensitivity of the self-reported data on diabetes.
With regard to the validity of self-reported data, previous studies have also demonstrated that self-reported questionnaires are insensitive instruments that often underestimate the real prevalence rate of hypertension and diabetes.14,19 However, the sensitivity in this study (34.5% for self-reported hypertension and 58.9% for diabetes) was poor compared to the estimates in other studies that used biometrical data as reference. In these studies the sensitivity for hypertension ranged from the lowest value of 43% to the highest value of 82% and for diabetes it ranged from 66.7 to 85.2%.4,6,15,16,18,19,27–29 When medical records were used as reference data even higher sensitivities were found.2,7,8,14 This can partly be explained by the fact that undiagnosed subjects will remain hidden when this methodology is used. In addition, most validation studies on older populations showed higher estimates, which can be explained by more accurate reporting by elderly who have the condition, as in the present study, and the more severe stage of the conditions in this subpopulation. As expected, the specificity in this study was markedly high for both conditions (96.4% for hypertension and 99.4% for diabetes), which is consistent with the findings of previous studies that used biometrical data as reference. In the literature, specificity for hypertension ranged from 80 to 95.3% and from 95.2 to 99% for diabetes.4,15–17,19,28,29
Overall, we found self-reported data on hypertension and diabetes were more specific than sensitive. Therefore an underestimation of prevalence estimates and an attenuation of associations with risk factors can be expected. For example, given the sensitivity and specificity estimates obtained in this study and the assumption of non-differential misclassification, a true relative risk (RR) of 2.0 will result in an observed RR of 1.46 for hypertension and 1.94 for diabetes.
Our study supports the view that self-reporting of diabetes has a better validity than that of hypertension.15,16,19 It has been postulated that conditions with more clear diagnostic criteria, like diabetes, are more likely to be reported accurately than conditions, like hypertension, that have less unambiguous criteria and are less disabling during daily life.5 However, as these silent conditions may be major risk factors for chronic diseases, it is important for the general practitioner to assess the condition in an early stage and make sure the subject receives appropriate treatment and is aware of the condition.
Our findings show that certain subgroups are more likely to accurately self-report hypertension. Recent health care users, older participants, females, and those with a history of CVD, overweight or depressive symptoms were more likely to correctly self-report their hypertensive state. Previous studies have also found higher sensitivity of self-reported hypertension among the first four mentioned subgroups.4,8,14,15,18,27–29 Possible explanations may be the increased exposure to monitoring programs and a higher health consciousness among these subgroups.4 The few studies that investigated the influence of depressive symptoms showed variable results.13,19 This could partly be due to the use of different criteria for the presence of depression.
The observed misclassification between subgroups in this study indicates differential misclassification which may have serious consequences from an etiological point of view, namely biased associations with risk factors. For example, the RR for hypertension associated with overweight will be overestimated given the higher sensitivity of self-reported hypertension among overweight participants in this study. The observed differential misclassification may also have possible consequences for the overall sensitivity and specificity estimates generated by present study, due to overrepresentation of some subgroups. However, as some of the overrepresented subgroups seem to increase the likelihood of accurate reporting on hypertension and diabetes (recent health care users), whereas others seem to decrease the accuracy (young of age, well educated), we expect the effect on the overall estimates to be small.
In conclusion, the results from the current study support the view that adding biometrical data to self-reported questionnaire information for monitoring the prevalence of diabetes and hypertension does markedly improve the accuracy of detecting populations at risk due to hypertension or diabetes. As the accuracy of self-reporting varied between condition and subgroups (implying systematic errors), the magnitude of the additional value would depend on the condition studied and the characteristics of the population under investigation. Conditions that have more pronounced symptoms that affect the daily life of the individual and are better defined may be more likely to be reported correctly. However, in general, when self-reports are the sole source of information used this will lead to an underestimation of the prevalence rates of hypertension and diabetes and biased associations with risk factors due to differential misclassification. Therefore it is recommended to include biometrical measurements in order to assure the validity of the data and to reduce misclassification at the individual level.
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Conflict of interest |
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There are no conflicts of interest to declare.
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Acknowledgments |
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We acknowledge the participating inhabitants of Leidsche Rijn, Utrecht, The Netherlands, and the general practitioners working in this area for providing research data from routine care. The Utrecht Health Project received grants from the Ministry of Health, Welfare, and Sports (VWS), the University of Utrecht, the Province of Utrecht, the Dutch Organisation of Care Research (ZON), the University Medical Center of Utrecht (UMC Utrecht) and the Dutch College of Healthcare Insurance Companies (CVZ).
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References |
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