Toward a Better Understanding of Listeriosis Risk among Older Adults in the United States: Characterizing Dietary Patterns and the Sociodemographic and Economic Attributes of Consumers with These Patterns

ABSTRACT Older adults are at higher risk of invasive listeriosis compared with the general population. Some foods are more likely than others to be contaminated with or to contain high levels of Listeria monocytogenes. The objectives of this study were to (i) determine dietary consumption patterns among older adults in the United States; (ii) evaluate sociodemographic and economic characteristics of older adults associated with each pattern; (iii) determine intake of foods associated with larger relative risk of listeriosis within these patterns; and (iv) rank these patterns based on risk. Data related to older adults (age 60 and older) participating in the cross-sectional National Health and Nutrition Examination Surveys (NHANES) 2009 to 2010, 2011 to 2012, and 2013 to 2014 (n = 4,967) were included in these analyses. Cluster analysis was used to define dietary patterns based on 24-h dietary recalls from day 1 and day 2. Mean intake of foods associated with higher risk of listeriosis was examined within each pattern, and analysis of variance with Dunnett's method of adjustment was used to evaluate significant differences in mean intake of foods. Patterns were ranked based on relative risk of listeriosis, using outbreak illness attribution data. Five distinct dietary patterns were identified. Patterns ranked at highest relative risk of listeriosis, based on U.S. outbreak illness attribution data, were characterized by relatively higher intakes of fruits, vegetables, and cheeses (∼13% respondents) or cereal, milk, and yogurt (∼14% respondents). Individuals consuming these dietary patterns differed in sex, race, food security, self-rated diet quality, and self-rated health. Cluster analysis, despite methodological limitations, provides new information on consumption, sociodemographic, and economic characteristics of subgroups within susceptible populations, which may be used to target educational messages. HIGHLIGHTS

‘This sickness is not hospital sickness’: a qualitative study of the evil eye as a source of neonatal illness in Ghana

Previous research has described the evil eye as a source of illness for pregnant women and their newborns. This study sought to explore the perceptions of the evil eye among mothers whose newborns had experienced a life-threatening complication across three regions of Ghana. As part of a larger, quantitative study, trained research assistants identified pregnant and newly delivered women (and their newborns) who had survived a life-threatening complication at three tertiary care hospitals in southern Ghana to participate in open-ended, qualitative interviews about their experiences in March–August 2015. All interviews were audio-recorded and transcribed verbatim into English and analysis using the constant comparative method of theme generation. A total of 37 mothers were interviewed, 20 about neonatal illnesses and 17 about maternal illnesses. Six of the 20 mothers interviewed about their newborn’s illnesses spoke at length about the evil eye being a potential cause of newborn illness. The evil eye was described in a variety of terms, but commonalities included a person looking at a pregnant woman, her newborn baby, the baby’s clothes and even the mother’s food, causing harm, even unintentionally. Prevention required mothers covering themselves while pregnant and keeping the baby away from others until it was old enough to ward off the evil eye. Treatment required traditional medicine, yet some indicated that allopathic medicine could help. The evil eye appears to serve a social control mechanism, encouraging pregnant women to dress modestly, stay indoors as much as possible and behave appropriately. The evil eye is a pervasive, universally understood phenomenon across three regions of Ghana, even amongst a hospitalized population receiving allopathic health care for life-threatening complications of childbirth. Understanding the role of the evil eye in newborn illness attribution is important for clinicians, researchers and programmatic staff to effectively address barriers to care seeking.

Dietary Patterns of Older Adults in the United States and Their Risk of Listeriosis: Characterizing Sociodemographic and Economic Attributes of Consumers by Dietary Patterns (P18-047-19)

Objectives 1) Determine dietary consumption patterns, among older adults in the United States; 2) Evaluate sociodemographic and economic characteristics associated with each pattern; 3) Determine intake of foods associated with larger relative risk of listeriosis within these patterns; and 4) Rank these patterns based on risk. Methods The study included older adults, age 60 and older, from What We Eat in America, National Health and Nutrition Examination Surveys 2009–2010, 2011–2012 and 2013–2014 (n = 4967). Cluster analysis based on day 1 24-hour dietary recalls was used to define dietary patterns. ANOVA with Dunnett's method of adjustment used to evaluate significant differences in mean intake of foods associated with higher risk of listeriosis within each pattern. Patterns were ranked based on relative risk of listeriosis using outbreak illness attribution and risk assessment data. Results Five distinct dietary patterns were identified -Vegetables, Fruits & Oils; Mixed Dishes; RTE (Ready-To-Eat) Cereal, Milk & Yogurt; Meat & Potatoes; and Cured Meats & Cheese. The patterns ranked at highest relative risk of listeriosis, based on 2013 outbreak illness attribution data, were (1) the Vegetables, Fruits & Oils, characterized by relatively higher intakes of fruits, vegetables, and vegetable oils (∼22% respondents), (2) the RTE (Ready-To-Eat) Cereal, Milk & Yogurt, with relatively higher intakes of cereal, milk, and yogurt (16% respondents); and, based on 2003 risk assessment data, (3) the Cured Meats & Cheese with relatively higher intakes of breads, cheese, and cured meats (∼9.6% respondents). Individuals consuming these dietary patterns differed in sex, race/ethnicity, food security, self-rated diet quality, and self-rated health. Conclusions Cluster analysis, despite methodological limitations, provides new information on consumption, sociodemographic, and economic characteristics of subgroups within susceptible populations that can be used to target educational messages. Funding Sources Agricultural Research Service, US Department of Agriculture; Food and Drug Administration.

Time valuation of historical outbreak attribution data

SUMMARYHuman illness attribution is recognized as an important metric for prioritizing and informing food-safety decisions and for monitoring progress towards long-term food-safety goals. Inferences regarding the proportion of illnesses attributed to a specific commodity class are often based on analyses of datasets describing the number of outbreaks in a given year or combination of years. In many countries, the total number of pathogen-related outbreaks reported nationwide for an implicated food source is often fewer than 50 instances in a given year and the number of years for which data are available can be fewer than 10. Therefore, a high degree of uncertainty is associated with the estimated fraction of pathogen-related outbreaks attributed to a general food commodity. Although it is possible to make inferences using only data from the most recent year, this type of estimation strategy ignores the data collected in previous years. Thus, a strong argument exists for an estimator that could ‘borrow strength’ from data collected in the previous years by combining the current data with the data from previous years. While many estimators exist for combining multiple years of data, most either require more data than is currently available or lack an objective and biologically plausible theoretical basis. This study introduces an estimation strategy that progressively reduces the influence of data collected in past years in accordance with the degree of departure from a Poisson process. The methodology is applied to the estimation of the attribution fraction forSalmonellaandEscherichia coliO157:H7 for common food commodities and the estimates are compared against two alternative estimators.

Causal Attribution and Illness Perception: A Cross-Sectional Study in Mexican Patients with Psychosis

Health psychology researchers have begun to focus greater attention on people’s beliefs about health/illness since these beliefs can clearly affect behavior. This cross-sectional study aimed at (1) identifying the most common factors psychotic patients attribute their illness to and (2) assessing the association between causal attribution and illness perception (cognitive, emotional, and comprehensibility dimensions). Sixty-two patients (56.5% females) who had been treated for psychosis at a public psychiatric hospital in Mexico answered the Angermeyer and Klusmann Illness Attribution Scale and the Brief Illness Perception Questionnaire. Results showed that most patients attributed psychosis onset to social factors and that attribution to their personality might have an overwhelmingly negative effect on their lives. Acknowledging psychotic patient attributional beliefs and considering them in clinical practice could improve treatment efficacy and overall recovery success. This is particularly important in psychosis, since symptoms are often severe and/or persistent and require long-term treatment.