METHODS: Urine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure.
RESULTS: From the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 μg/L) and Uganda (7.6 to 0.8 μg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies.
CONCLUSIONS: Our results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.
METHODS: The total lifetime cost per TDT patient (TC1) is the sum of lifetime healthcare cost (TC2) and lifetime patient and family healthcare expenditure (TC3). TC2 was simulated using the Markov model, taking into account all costs subsidized by the government, and TC3 was estimated through a cross-sectional health survey approach. A survey was performed using a two-stage sampling method in 13 thalassaemia centres covering all regions in Malaysia.
RESULTS: A TDT patient is expected to incur TC2 of USD 561,208. ICT was the main driver of cost and accounted for 56.9% of the total cost followed by blood transfusion cost at 13.1%. TC3 was estimated to be USD 45,458. Therefore, the estimated TC1 of a TDT patient was USD 606,665. Sensitivity analyses showed that if all patients were prescribed oral ICT deferasirox for their lifetime, the total healthcare cost would increase by approximately 65%. Frequency of visits to health facilities for blood transfusion/routine monitoring and patients who were prescribed desferrioxamine were observed to be factors affecting patient and family monthly expenses.
CONCLUSION: The lifetime cost per TDT patient was USD 606,665, and this result may be useful for national health allocation planning. An estimation of the economic burden will provide additional information to decision makers on implementing prevention interventions to reduce the number of new births and medical service reimbursement.