Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-2 (of 2 Records) |
Query Trace: Strassle PD[original query] |
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Sex and age distributions of persons in foodborne disease outbreaks and associations with food categories
Strassle PD , Gu W , Bruce BB , Gould LH . Epidemiol Infect 2019 147 e200 Sex and age differences in food preferences may be reflected in the demographics of outbreaks. Outbreaks from 1998-2015 with a single confirmed implicated food source in the Centers for Disease Control and Prevention Foodborne Disease Outbreak Surveillance System were analysed using logistic regression to assess associations between a food category, sex and age. Males were more likely to be involved in outbreaks attributed to beef, pork, game, dairy and shellfish; females were more likely to be involved in grains-beans, nuts-seeds, fruits, sprouts and vegetable row crops outbreaks. Children <5-years-old were more likely than other age groups to be involved in dairy outbreaks, children 5-19-years-old were most likely to be involved in beef and game outbreaks, adults 20-49-years-old were most likely to be involved in fish, shellfish and sprout outbreaks and adults 50-years-old were most likely to be involved in turkey outbreaks. Age and sex are associated with specific food categories in outbreaks. This information may be useful in helping to identify sources of foodborne disease outbreaks. |
What we don't know can hurt us: nonresponse bias assessment in birth defects research
Strassle PD , Cassell CH , Shapira SK , Tinker SC , Meyer RE , Grosse SD . Birth Defects Res A Clin Mol Teratol 2015 103 (7) 603-9 BACKGROUND: Nonresponse bias assessment is an important and underutilized tool in survey research to assess potential bias due to incomplete participation. This study illustrates a nonresponse bias sensitivity assessment using a survey on perceived barriers to care for children with orofacial clefts in North Carolina. METHODS: Children born in North Carolina between 2001 and 2004 with an orofacial cleft were eligible for inclusion. Vital statistics data, including maternal and child characteristics, were available on all eligible subjects. Missing 'responses' from nonparticipants were imputed using assumptions based on the distribution of responses, survey method (mail or phone), and participant maternal demographics. RESULTS: Overall, 245 of 475 subjects (51.6%) responded to either a mail or phone survey. Cost as a barrier to care was reported by 25.0% of participants. When stratified by survey type, 28.3% of mail respondents and 17.2% of phone respondents reported cost as a barrier. Under various assumptions, the bias-adjusted estimated prevalence of cost as barrier to care ranged from 16.1% to 30.0%. Maternal age, education, race, and marital status at time of birth were not associated with subjects reporting cost as a barrier. CONCLUSION: As survey response rates continue to decline, the importance of assessing the potential impact of nonresponse bias has become more critical. Birth defects research is particularly conducive to nonresponse bias analysis, especially when birth defect registries and birth certificate records are used. Future birth defect studies which use population-based surveillance data and have incomplete participation could benefit from this type of nonresponse bias assessment. |
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