Adult prescription drug use and pediatric medication exposures and poisonings - PubMed (original) (raw)

Adult prescription drug use and pediatric medication exposures and poisonings

Lindsey C Burghardt et al. Pediatrics. 2013 Jul.

Abstract

Background and objectives: Nontherapeutic medication ingestions continue to be a major pediatric health problem, with recent increases in ingestions despite a number of public health interventions. It is unknown how changes in adult prescription drug use relate to pediatric medication poisonings. The objective of the study was to measure the association between changing adult prescription drug patterns and pediatric medication exposures and poisonings and identify high-risk classes of medications and pediatric age groups.

Methods: We measured monthly pediatric exposures and poisonings using the National Poison Data System and prescriptions written for adults using the National Ambulatory Medical Care Surveys for 2000 through 2009. Associations between adult prescriptions for oral hypoglycemics, antihyperlipidemics, β-blockers, and opioids and exposures and poisonings among children 0 to 5, 6 to 12, and 13 to 19 years were analyzed by using multiple time-series analysis. Emergency department visits, serious injuries, and hospitalizations stemming from these associations were described.

Results: Adult medication prescriptions were statistically significantly associated with exposures and poisonings in children of all ages, with the strongest association observed for opioids. Across medications, the greatest risk was among children 0 to 5 years old, followed by 13- to 19-year-olds. Rates of emergency department visits were highest for events related to hypoglycemics (60.1%) and β-blockers (59.7%), whereas serious injuries and hospitalizations occurred most frequently with opioids (26.8% and 35.2%, respectively) and hypoglycemics (19.5% and 49.4%, respectively).

Conclusions: Increasing adult drug prescriptions are strongly associated with rising pediatric exposures and poisonings, particularly for opioids and among children 0 to 5 years old. These associations have sizable impacts, including high rates of serious injury and health care use.

Keywords: drug therapy; epidemiology; poisoning; prescription drugs; prevention and control.

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Figures

FIGURE 1

FIGURE 1

Trends in pediatric exposures and poisonings related to oral hypoglycemics, antihyperlipidemics, β-blockers, and opioids and adult mentions of these medications. Exposures and poisonings increased statistically significantly for all age groups related to each of the drug classes (P < .001). Adult drug mentions increased statistically significantly for all drug classes (P < .001).

FIGURE 1

FIGURE 1

Trends in pediatric exposures and poisonings related to oral hypoglycemics, antihyperlipidemics, β-blockers, and opioids and adult mentions of these medications. Exposures and poisonings increased statistically significantly for all age groups related to each of the drug classes (P < .001). Adult drug mentions increased statistically significantly for all drug classes (P < .001).

FIGURE 2

FIGURE 2

Increases in pediatric exposures and poisonings associated with adult drug mentions of opioids, antihyperlipidemics, oral hypoglycemics, and β-blockers. Each bar indicates a month-specific mean predicted change in pediatric exposures and poisonings for a 1 percentage point increase in adult medication mentions. Lines show the corresponding confidence intervals estimated by using 1000 draws from the mean value’s variance-covariance matrix for the maximum likelihood estimate. Displayed numeric values represent the mean association averaging over 1 to 6 months.

FIGURE 2

FIGURE 2

Increases in pediatric exposures and poisonings associated with adult drug mentions of opioids, antihyperlipidemics, oral hypoglycemics, and β-blockers. Each bar indicates a month-specific mean predicted change in pediatric exposures and poisonings for a 1 percentage point increase in adult medication mentions. Lines show the corresponding confidence intervals estimated by using 1000 draws from the mean value’s variance-covariance matrix for the maximum likelihood estimate. Displayed numeric values represent the mean association averaging over 1 to 6 months.

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