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Measuring the prevalence of chronic diseases using population surveys by pooling self-reported symptoms, diagnosis and treatments: results from the World Health Survey of 2003 for South Asia

  • Original Article
  • Published:
International Journal of Public Health

Abstract

Objectives

Measuring disease prevalence poses challenges in countries where information systems are poorly developed. Population surveys soliciting information on self-reported diagnosis also have limited capacity since they are influenced by informational and recall biases. Our aim is to propose a method to assess the prevalence of chronic disease by combining information on self-reported diagnosis, self-reported treatment and highly suggestive symptoms.

Methods

An expanded measure of prevalence was developed using data from the World Health Survey for Bangladesh, India and Sri Lanka. Algorithms were constructed for six chronic diseases.

Results

The expanded measures of chronic disease increase the prevalence estimates. Prevalence varies across socio-demographic characteristics, such as age, education, socioeconomic status (SES), and country. Finally, the association, as also risk factor, between chronic disease status and poor self-rated health descriptions increases significantly when one takes into account highly suggestive symptoms of diseases.

Conclusions

Our expanded measure of chronic disease could form a basis for surveillance of chronic diseases in countries where health information systems have been poorly developed. It represents an interesting trade-off between the bias associated with usual surveillance data and costs.

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Acknowledgments

This study was funded by the Canadian Institute of Health Research (CIHR). The authors would like to acknowledge the support of Sarah Descôteaux in editing the manuscript and Ritika Palit for assistance in computing statistical analyses. We are grateful to Vanessa Beal for the linguistic revision of the manuscript. Jean-Frederic Levesque is a Junior 1 level career award recipient from the Fonds Recherche Québec-Santé. Subrata Mukherjee is a HOPE scholarship recipient by the Canadian Institutes for Health Research. The authors thank the anonymous reviewers and the editor for their insightful comments.

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There is no competing interest to declare.

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Correspondence to J.-F. Levesque.

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J.-F. Levesque is lead author, S. Mukherjee is joint lead author and S. Mishra is senior author.

Appendix 1 – Detailed descriptions of diagnosis algorithms

Appendix 1 – Detailed descriptions of diagnosis algorithms

Arthritis: We focused on chronic inflammatory to identify the less probable and highly probable cases. To have a less probable disease, individuals must have reported pain, aching, stiffness or swelling in or around the joint for more than a month and this pain must not be related to any injury. At the highly probable level, individuals must have confirmed that the pain they have in the morning or after a long rest without movement lasts for more than 30 min.

Angina: For angina, diagnosis categories were based on a prior assessment of the individual risk of cardiovascular disease. The risk assessment was made using an adapted version of the Framingham office-based charts. Since no biomarkers were identified, the cardio vascular disease (CVD) risk score was calculated using gender, body mass index (BMI) and smoking and diabetes status only. The final score was then categorized as low, moderate and high risk of CVD. There is an important limit for the risk assessment for Bangladesh because of a large number of missing observations for height and weight in that country; the BMI calculations were done using the age- and gender-based median values of the other two countries. As a result, the risk of CVD for Bangladesh is probably underestimated.

Following the assessment of CVD risk, the symptom-based diagnosis categories were generated. To fall into the less probable category, individuals had to have a low or a moderate risk of CVD, and report having pain and discomfort in the chest when walking uphill, in a hurry, or pain when walking at ordinary pace on level ground. They also had to report that, for this pain, they needed to stop/stand still or slow down or take pain-relieving medicines. For the highly probable category, the same categorization of symptoms applied, but this time combined with a high risk of CVD.

Asthma: In the case of asthma, the main challenge resides in distinguishing the cases from individuals suffering from chronic obstructive pulmonary disease (COPD). Even if asthma is targeted, COPD is common in developing countries, shares similar symptoms with asthma and can also be treated with the same drugs.

To be categorized as less probable, individuals must have reported attacks of wheezing or whistling breathing. This symptom is necessary for asthma. Then, to be categorized as highly probable, individuals must have reported in addition to the first symptom, any combination of attacks of wheezing after exercising, feeling of tightness in the chest, waking up with a feeling of tightness in the chest or at any other time, or attacks of shortness of breath without obvious causes.

Depression: For depression, in the same logic as for arthritis, a focus on major depressive episode was selected to generate the symptom-based diagnosis. First, all individuals must have reported to be sad for several days, empty, depressed or lose interest in things they usually enjoy. This period of sadness must have lasted for more than 2 weeks and for nearly every day. This is the central and necessary symptom for depression. Then, individuals were categorized as less probable if, on top of the central symptom, they reported one positive answer for (1) tired for several days or with an energy decrease, (2) a loss of appetite, or (3) a slowing down in thinking. For highly probable category, these three additional symptoms applied but with two or more positive answers.

Schizophrenia and other psychoses: The WHS covered schizophrenia and also included in the general category under “other psychoses”. Questions in this general category are labeled under mental disorders and symptoms included are not highly specific to schizophrenia. First, to be categorized as less probable, individuals have to report one positive answer from the following four: (1) they are feeling that something strange and unexplainable is going on, (2) that people are too interested in them and that there is a plot to harm them, (3) that their thoughts are being directly interfered with, controlled by another person or taken over by strange forces, and (4) that they are seeing visions or hearing voices that others could not see or hear. Second, to be categorized as highly probable, the same symptoms applied but in different and stricter grouping. They had to have at least one positive answer from the first two (1) or (2) and one positive answer from the remaining two (3) or (4).

As mentioned above, symptoms for mental disorders are very specific and accordingly, diagnosis categories had to be constructed with care. Other studies on psychosis have demonstrated that there is a good proportion of individuals who will report any one symptoms associated with psychosis, but if interviewed a second time by a professional, the diagnosis cannot be established (Arch Gen Psychiatry. 1996;53:102–103). As a result, the prevalence of schizophrenia itself is probably overestimated and includes other psychiatric disorders as well.

Diabetes: Diabetes is the only disease for which there are only two categories: no diseases and confirmed cases. Due to the nature of this disease, with a long pre-symptomatic period, it was not possible to survey the associated symptoms. Hence, to fall into the confirmed case category, individuals must have reported ever being diagnosed (high blood sugar), being treated, following a program or taking medicines for diabetes.

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Levesque, JF., Mukherjee, S., Grimard, D. et al. Measuring the prevalence of chronic diseases using population surveys by pooling self-reported symptoms, diagnosis and treatments: results from the World Health Survey of 2003 for South Asia. Int J Public Health 58, 435–447 (2013). https://doi.org/10.1007/s00038-013-0446-5

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