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Predictors of Asthma in Young Children Does Reporting Source Affect Our Conclusions? Jane E. Miller Jane E. Miller, Ph.D. Institute for Health, Health.

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Presentation on theme: "Predictors of Asthma in Young Children Does Reporting Source Affect Our Conclusions? Jane E. Miller Jane E. Miller, Ph.D. Institute for Health, Health."— Presentation transcript:

1 Predictors of Asthma in Young Children Does Reporting Source Affect Our Conclusions? Jane E. Miller Jane E. Miller, Ph.D. Institute for Health, Health Care Policy and Aging Research Rutgers University, NJ, USA

2 About the author Jane E. Miller earned her Ph.D. in demography from the University of Pennsylvania in 1989. She joined the faculty of the Institute for Health, Health Care Policy and Aging Research and the School of Planning and Public Policy at Rutgers University after completing a post-doctoral fellowship at the Office of Population Research at Princeton University. Dr. Miller’s research interests concern maternal and child health and development. She recently completed a five-year project on “Poverty Dynamics and Child Well-Being in the United States” as a Faculty Scholar of the William T. Grant Foundation. She is currently involved in a study of retention in SCHIP - the federal State Children’s Health Insurance Program.

3 Learning objectives To learn about the two most common sources of child health data. To know the strengths and weaknesses of each health data source. To understand the reasons for varying estimates of disease prevalence and distribution based on data from different sources.

4 Performance objectives To be able to critique studies of child health based on maternal reports and medical records. To understand the implications of different data sources for estimates of disease prevalence and distribution.

5 Common sources of child health data Maternal reports are used to collect data on: –Child health. –Health behaviors. Medical records are used to collect data on: –Health care utilization. –Diagnoses. –Treatments.

6 Maternal reports Strengths: –Available for all children. –Mothers (parents) see their children daily and know them well. Weaknesses: –Mothers don’t have medical training. –Retrospective recall of child’s health over his/her lifetime.

7 Medical records Strengths: –Diagnoses by trained medical providers. –Recorded at time of visit. Weaknesses: –Only available for children who receive medical care. –Parents may not take mildly ill child to doctor.

8 Which source is “right”? Both maternal reports and medical records have their drawbacks. Neither source can be viewed as the “gold standard”.

9 Are the two sources consistent? Do mothers and medical providers concur about children’s chronic health conditions? –Do they identify the same cases? –Do they exclude the same non-cases? To compare properly, need a data set with both medical records & maternal reports for the same set of children.

10 Data used in study 1998 National Maternal and Infant Health Survey and 1991 Longitudinal Followup (NMIHS/LF). –Sample of birth certificates from 1988. –83% of baseline sample followed to 1991. –91% of parents granted consent to contact medical providers.

11 Data sources in NMIHS/LF Mother’s questionnaire –1991: “Have you ever been told your child has _____ (health condition)?” –14 chronic health conditions. E.g., Asthma. Chronic heart disease. Medical records. –Checklist of specific medical conditions. –Space to list ICD9 codes for all diagnoses made during each visit.

12 Concurrence on asthma 1, 098 cases of asthma were identified by one or both sources. –36% were mentioned by both the mother and a medical provider (agreement), –36% by mother only (disagreement), –27% by medical provider only (disagreement). Cohen’s kappa = 0.48 –Moderate agreement using standard criteria.

13 Epidemiologic implications of poor concurrence What are the implications of lack of concurrence between mothers’ reports and medical records? How does it affect: –Prevalence estimates? E.g., how common is asthma? –Distribution estimates? E.g., who has asthma?

14 Asthma prevalence estimates Vary widely depending on reporting source. –Mother’s reports: 10.0% –Medical records: 7.7% –Both sources: 4.1% –Either source: 13.6%

15 * * * # # # * Comparison of estimated effects of sociodemographic and health characteristics on risk of asthma

16 Different predictors of asthma Reporting sources agree on elevated asthma risk for: –Preterm infants. –Boys. –Black children. Maternal reports but not medical records also find: –Elevated asthma for: Poor children. Those whose mothers smoke. –Reduced asthma for: Breastfed children.

17 Summary of findings Different reporting sources on a consistent sample of children yielded –Poor concurrence between maternal reports and medical records on asthma. –Different estimates of prevalence. –Different estimates of distribution across socioeconomic and behavioral subgroups.

18 Drawbacks of maternal reports No prompts or definitions of terms on the survey. –Mother’s terminology may not match: Doctor’s. Questionnaire. Less knowledgeable about child health and development: –Misdiagnosis.

19 Drawbacks of medical records Children who do not visit a doctor or visit less often are less likely to be diagnosed, even if they have the health condition. –Low income families. –Uninsured families. –Others with barriers to health care. Language barriers. Cultural barriers.

20 Generalizability to other health conditions Inconsistencies between patient self-reports and medical records have also been found in: –Other studies of chronic child health conditions. –Studies of adult health. –Health during pregnancy. Health behaviors. Health events and health status during pregnancy.

21 Generalizability to other data sources Time point or interval of data collection –Lifetime prevalence: “Have you ever had ___?” –Current (recent) prevalence: “In the past 12 months, have you had ___?” Method of data collection –Health examinations will only pick up current symptoms. –Health interviews can capture past as well as present symptoms.

22 Consider the (data) source! Don’t be fooled by comparable estimates of prevalence from different sources. –The distributions could be substantially different. Consider strengths and weaknesses of data sources. –When interpreting results of your own analyses. –When reading others’ results. Primary data collectors: –Design your data collection to minimize problems.


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