Abstract
OBJECTIVES: To explore the impact of various measurements of long-term health conditions (LTCs) on the resulting prevalence estimates using data from a nationally representative dataset. METHODS: Children and young people in the Millennium Cohort Study were followed at ages 3, 5, 7, 11, and 14 years (N = 15,631). We estimated the weighted prevalence of LTCs at each time point and examined the degree to which estimates agreed with alternate health indicators (special educational needs and disability [SEND], specific chronic conditions, and common chronicity criteria) using descriptive analyses, Cohen's kappa statistic, and percentage agreement. RESULTS: The estimated weighted prevalence of LTCs peaked at 5 years old (20%). Despite high percentage agreement, we observed at best moderate chance-corrected agreement between the type of LTC and reasons for SEND (kappas from 0.02 to 0.56, percentage agreement from 97% to 99%) or specified chronic conditions (kappas from 0.002 to 0.02, percentage agreement from 73% to 97%). Applying chronicity criteria decreased the estimated weighted prevalence of LTCs (3%). CONCLUSION: How long-term conditions are defined drastically alters the estimated weighted prevalence of LTCs. Improved clarity and consistency in the definition and measurement of LTCs is urgently needed to underpin policy and commissioning of services.