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We describe COVID-19 cases among nonphysician healthcare personnel (HCP) by work location. The proportion of HCP with coronavirus disease 2019 (COVID-19) was highest in the emergency department and lowest among those working remotely. COVID-19 and non–COVID-19 units had similar proportions of HCP with COVID-19 (13%). Cases decreased across all work locations following COVID-19 vaccination.
Background: Whether working on COVID-19 designated units put healthcare workers (HCWs) at higher risk of acquiring COVID-19 is not fully understood. We report trends of COVID-19 incidence among nonphysician HCWs and the association between the risk of acquiring COVID-19 and work location in the hospital. Methods: The University of Iowa Hospitals & Clinics (UIHC) is an 811-bed, academic medical center serving as a referral center for Iowa. We retrospectively collected COVID-19–associated data for nonphysician HCWs from Employee Health Clinic between June 1st 2020 and July 31th 2021. The data we abstracted included age, sex, job title, working location, history of COVID-19, and date of positive COVID-19 test if they had a history of COVID-19. We excluded HCWs who did not have a designated working location and those who worked on multiple units during the same shift (eg, medicine resident, hospitalist, etc) to assess the association between COVID-19 infections and working location. Job titles were divided into the following 5 categories: (1) nurse, (2) medical assistant (MA), (3) technician, (4) clerk, and (5) others (eg patient access, billing office, etc). Working locations were divided into the following 6 categories: (1) emergency department (ED), (2) COVID-19 unit, (3) non–COVID-19 unit, (4) Clinic, (5) perioperative units, and (6) remote work. Results: We identified 6,971 HCWs with work locations recorded. During the study period, 758 HCWs (10.8%) reported being diagnosed with COVID-19. Of these 758 COVID-19 cases, 658 (86.8%) were diagnosed before vaccines became available. The location with the highest COVID-19 incidence was the ED (17%), followed by both COVID-19 and non–COVID-19 units (12.7%), clinics (11.0%), perioperative units (9.4%) and remote work stations (6.6%, p Conclusions: Strict and special infection control strategies may be needed for HCWs in the ED, especially where vaccine uptake is low. The administrative control of HCWs working remotely may be associated with a lower incidence of COVID-19. Given that the difference in COVID-19 incidence among HCWs by location was lower and comparable after the availability of COVID-19 vaccines, facilities should make COVID-19 vaccination mandatory as a condition of employment for all HCWs, especially in areas where the COVID-19 incidence is high.
Background: The IDSA has a clinical definition for catheter-related bloodstream infection (CRBSI) that requires ≥1 set of blood cultures from the catheter and ≥1 set from a peripheral vein. However, because blood cultures obtained from a central line may represent contamination rather than true infection, many institutions discourage blood cultures from central lines. We describe blood culture ordering practices in patients with a central line. Methods: The University of Iowa Hospitals & Clinics is an academic medical center with 860 hospital beds. We retrospectively collected data for blood cultures obtained from adult patients (aged ≥18 years) in the emergency department or an inpatient unit during 2020. We focused on the first blood cultures obtained during each admission because they are usually obtained before antibiotic initiation and are the most important opportunity to diagnose bacteremia. We classified blood-culture orders as follows: CRBSI workup, non-CRBSI sepsis workup, or incomplete workup. We defined CRBSI workup as ≥1 blood culture from a central line and ≥1 peripheral blood culture (IDSA guidelines). We defined non-CRBSI sepsis workup as ≥2 peripheral blood cultures without cultures from a central line because providers might have suspected secondary bacteremia rather than CRBSI. We defined incomplete workup as any order that did not meet the CRBSI or non-CRBSI sepsis workup. This occurred when only 1 peripheral culture was obtained or when ≥1 central-line culture was obtained without peripheral cultures. Results: We included 1,150 patient admissions with 4,071 blood cultures. In total, 349 patient admissions with blood culture orders (30.4%) met CRBSI workup. 62.8% were deemed non-CRBSI sepsis workup, and 6.9% were deemed an incomplete workup. Stratified by location, ICUs had the highest percentage of orders with incomplete workups (8.8%), followed by wards (7.2%) and the emergency department (5.1%). In total, 204 patient admissions had ≥1 positive blood culture (17.7%). The most frequently isolated organisms were Staphylococcus epidermidis (n = 33, 16.2%), Staphylococcus aureus (n = 16, 7.8%), and Escherichia coli (n = 15, 7.4%) Conclusions: Analysis of blood culture data allowed us to identify units at our institute that were underperforming in terms of ordering the necessary blood cultures to diagnose CRBSI. Being familiar with CRBSI guidelines as well as decreasing inappropriate ordering will help lead to early and proper diagnosis of CRBSI which can reduce its morbidity, mortality, and cost.
We analyzed blood-culture practices to characterize the utilization of the Infectious Diseases Society of America (IDSA) recommendations related to catheter-related bloodstream infection (CRBSI) blood cultures. Most patients with a central line had only peripheral blood cultures. Increasing the utilization of CRBSI guidelines may improve clinical care, but may also affect other quality metrics.
Irregular hospital discharge is highly prevalent among people admitted to hospital for mental health reasons. No study has examined the relationship between irregular discharge, post-discharge mortality and treatment setting (i.e. mortality after patients are discharged from acute in-patient or residential mental health settings).
To understand the relationship between irregular discharge and mortality among patients discharged from acute in-patient and residential settings.
A retrospective study was conducted in members of the US veteran population discharged from acute in-patient or residential settings of the US Department of Veterans Affairs between 2003 and 2018. Multivariate Cox proportional hazards were used to evaluate associations between irregular discharge and suicide, external-cause (as defined by ICD-10 Codes: V01-Y98) and all-cause mortality in the first 30-, 90- and 180-days post-discharge.
There were over 1.5 million mental health discharges between 2003 and 2018. Patients with an irregular discharge were at increased risk for suicide, external-cause and all-cause mortality in the first 180 days after discharge. In the first 30 days after discharge, patients with irregular discharge had more than three times greater suicide risk than patients with regular discharge (adjusted hazard ratio (HR) = 3.41, 95% CI 2.21–5.25). Suicide risk was higher among patients with irregular discharge in the first 30 days after acute in-patient discharge (adjusted HR = 1.55, 95% CI 1.11–2.16). In both settings, the mortality risk associated with irregular discharge attenuated but remained elevated within 90 and 180 days.
Irregular discharge after an acute in-patient or residential stay poses a large risk for mortality soon after discharge. Clinicians must identify effective interventions to mitigate harms associated with irregular discharge in these settings.
Background: COVID-19 in hospitalized patients may be the result of community acquisition or in-hospital transmission. Molecular epidemiology can help confirm hospital COVID-19 transmission and outbreaks. We describe large COVID-19 clusters identified in our hospital and apply molecular epidemiology to confirm outbreaks. Methods: The University of Iowa Hospitals and Clinics is an 811-bed academic medical center. We identified large clusters involving patients with hospital onset COVID-19 detected during March–October 2020. Large clusters included ≥10 individuals (patients, visitors, or HCWs) with a laboratory confirmed COVID-19 diagnosis (RT-PCR) and an epidemiologic link. Epidemiologic links were defined as hospitalization, work, or visiting in the same unit during the incubation or infectious period for the index case. Hospital onset was defined as a COVID-19 diagnosis ≥14 days from admission date. Admission screening has been conducted since May 2020 and serial testing (every 5 days) since July 2020. Nasopharyngeal swab specimens were retrieved for viral whole-genome sequencing (WGS). Cluster patients with a pairwise difference in ≤5 mutations were considered part of an outbreak. WGS was performed using Oxford Nanopore Technology and protocols from the ARTIC network. Results: We identified 2 large clusters involving patients with hospital-onset COVID-19. Cluster 1: 2 hospital-onset cases were identified in a medical-surgical unit in June 2020. Source and contact tracing revealed 4 additional patients, 1 visitor, and 13 employees with COVID-19. Median age for patients was 62 (range, 38–79), and all were male. In total, 17 samples (6 patients, 1 visitor, and 10 HCWs) were available for WGS. Cluster 2: A hospital-onset case was identified via serial testing in a non–COVID-19 intensive care unit in September 2020. Source investigation, contact tracing, and serial testing revealed 3 additional patients, and 8 HCWs. One HCW also had a community exposure. Patient median age was 60 years (range, 48–68) and all were male. In total, 11 samples (4 patients and 7 HCWs) were sequenced. Using WGS, cluster 1 was confirmed to be an outbreak: WGS showed 0–5 mutations in between samples. Cluster 2 was also an outbreak: WGS showed less diversity (0–3 mutations) and ruled out the HCW with a community exposure (20 mutations of difference). Conclusion: Whole-genome sequencing confirmed the outbreaks identified using classic epidemiologic methods. Serial testing allowed for early outbreak detection. Early outbreak detection and implementation of control measures may decrease outbreak size and genetic diversity.
Background: Hospital semiprivate rooms may lead to coronavirus disease 2019 (COVID-19) patient exposures. We investigated the risk of COVID-19 patient-to-patient exposure in semiprivate rooms and the subsequent risk of acquiring COVID-19. Methods: The University of Iowa Hospitals & Clinics is an 811-bed tertiary care center. Overall, 16% of patient days are spent in semiprivate rooms. Most patients do not wear masks while in semiprivate rooms. Active COVID-19 surveillance included admission and every 5 days nasopharyngeal SARS-CoV-2 polymerase chain reaction (PCR) testing. We identified inpatients with COVID-19 who were in semiprivate rooms during their infectious periods during July–December 2020. Testing was repeated 24 hours after the first positive test. Cycle threshold (Ct) values of the two tests (average Ct <30), SARS-CoV-2 serology results, clinical assessment, and COVID-19 history were used to determine patient infectiousness. Roommates were considered exposed if in the same semiprivate room with an infectious patient. Exposed patients were notified, quarantined (private room), and follow-up testing was arranged (median seven days). Conversion was defined as having a negative test followed by a subsequent positive within 14 days after exposure. We calculated the risk of exposure: number of infectious patients in semiprivate rooms/number of semiprivate patient-days (hospitalization days in semiprivate rooms). Results: There were 16,427 semiprivate patient days during July–December 2020. We identified 43 COVID-19 inpatients who roommates during their infectious periods. Most infectious patients (77%) were male; the median age was 67 years; and 22 (51%) were symptomatic. Most were detected during active surveillance: admission testing (51%) and serial testing (28%). There were 57 exposed roommates. The risk of exposure was 3 of 1,000 semiprivate patient days. In total, 16 roommates (28%) did not complete follow-up testing. Of 41 exposed patients with follow-up data, 8 (20%) converted following their exposure. Median time to conversion was 5 days. The risk of exposure and subsequent conversion was 0.7 of 1,000 semiprivate patient days. Median Ct value of the source patient was 20 for those who converted and 23 for those who did not convert. Median exposure time was 45 hours (range, 3–73) for those who converted and 12 hours (range, 1–75) for those who did not convert. Conclusions: The overall risk of exposure in semiprivate rooms was low. The conversion rate was comparable to that reported for household exposures. Lower Ct values and lengthier exposures may be associated with conversion. Active COVID-19 surveillance helps early detection and decreases exposure time.
Background: Hospitalized patients may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), even if they are admitted for other reasons. Because SARS-CoV-2 may remain positive by reverse-transcriptase polymerase chain reaction (RT-PCR) for months after infection, patients with a positive result may not necessarily be infectious. We aimed to determine the frequency of SARS-CoV-2 infections in patients admitted for reasons unrelated to coronavirus disease 2019 (COVID-19). Methods: The University of Iowa Hospitals and Clinics is an 811-bed tertiary-care center. We use a nasopharyngeal SARS-CoV-2 RT-PCR to screen admitted patients without signs or symptoms compatible with COVID-19. Patients with positive tests undergo a repeat test to assess cycle threshold (Ct) value kinetics. We reviewed records for patients with positive RT-PCR screening admitted during July–October 2020. We used a combination of history, serologies, and RT-PCR Ct values to assess and qualify likelihood of infectiousness: (1) likely infectious, if Ct values were <29, or (2) likely not infectious, if 1 or both samples had Cts <30 with or without a positive SARS-CoV-2 antinucleocapsid IgG/IgM test or history of a positive result in the past 90 days. Contact tracing was only conducted for patients likely to be infectious. We describe the isolation duration and contact tracing data. Results: In total, 6,447 patients were tested on hospital admission for any reason (persons under investigation or admitted for reasons other than COVID-19). Of these, 240 (4%) had positive results, but 65 (27%) of these were admitted for reasons other than COVID-19. In total, 55 patients had Ct values available and were included in this analysis. The median age was 56 years (range, 0–91), 28 (51%) were male, and 12 (5%) were children. The most frequent admission syndromes were neurological (36%), gastrointestinal (16%), and trauma (16%). Our assessment revealed 23 likely infections (42%; 14 definite, 9 possible) and 32 cases likely not infectious (58%). The mean Ct for patients who were likely infectious was 22; it was 34 for patients who were likely not infectious. Mean duration of in-hospital isolation was 6 days for those who were likely infectious and 2 days for those who were likely not infectious. We detected 8 individuals (1 healthcare worker and 7 patients) who were exposed to a likely infectious patient. Conclusions: SARS-CoV-2 infection in patients hospitalized for other reasons was infrequent. An assessment of the likelihood of infectiousness including history, RT-PCR Cts, and serology may help prioritize patients in need of isolation and contact investigations.
Background: Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 RNA can be detected by real-time reverse-transcription polymerase chain reaction (RT-PCR) for several weeks after infection. Discerning persistent RT-PCR positivity versus reinfection is challenging and the frequency of COVID-19 reinfections is unknown. We aimed to determine the frequency of clinically suspected reinfection in our center and confirm reinfection using viral whole-genome sequencing (WGS). Methods: The University of Iowa Hospitals and Clinics (UIHC) is an 811-bed academic medical center. Patients with respiratory complaints undergo COVID-19 RT-PCR using nasopharyngeal swabs. The RT-PCR (TaqPath COVID-19 Combo kit) uses 3 targets (ORF1ab, S gene, and N gene). We identified patients with previous laboratory-confirmed COVID-19 who sought care for new respiratory complaints and underwent a repeated SARS-CoV-2 test at least 45 days from their first positive test. We then identified patients with median RT-PCR cycle threshold (Ct) values. Results: During the study period, 13,603 patients had a SARS-CoV-2– positive RT-PCR. Of these, 296 (2.2%) had a clinical visit for new onset of symptoms and a repeated RT-PCR assay >45 days from the first test. Moreover, 29 patients (9.8%) had a positive RT-PCR assay in the repeated testing. Ct values were available for samples from 25 patients; 7 (28%) had Ct values. Conclusions: In patients with a recent history of COVID-19 infection, repeated testing for respiratory symptoms was infrequent. Some had a SARS-CoV-2–positive RT-PCR assay on repeated testing, but only 1 in 4 had Ct values suggestive of a reinfection. We confirmed 1 case of reinfection using WGS.
The incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure in shared patient rooms was low at our institution: 1.8 per 1,000 shared-room patient days. However, the secondary attack rate (21.6%) was comparable to that reported in household exposures. Lengthier exposures were associated with SARS-CoV-2 conversion. Hospitals should implement measures to decrease shared-room exposures.
Patients admitted to the hospital may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), and hospitals have implemented SARS-CoV-2 admission screening. However, because SARS-CoV-2 reverse-transcription polymerase chain reaction (RT-PCR) assays may remain positive for months after infection, positive results may represent active or past infection. We determined the prevalence and infectiousness of patients who were admitted for reasons unrelated to COVID-19 but tested positive for SARS-CoV-2 on admission screening.
We conducted an observational study at the University of Iowa Hospitals & Clinics from July 7 to October 25, 2020. All patients admitted without suspicion of COVID-19 were included, and medical records of those with a positive admission screening test were reviewed. Infectiousness was determined using patient history, PCR cycle threshold (Ct) value, and serology.
In total, 5,913 patients were screened and admitted for reasons unrelated to COVID-19. Of these, 101 had positive admission RT-PCR results; 36 of these patients were excluded because they had respiratory signs/symptoms on admission on chart review. Also, 65 patients (1.1%) did not have respiratory symptoms. Finally, 55 patients had Ct values available and were included in this analysis. The median age of the final cohort was 56 years and 51% were male. Our assessment revealed that 23 patients (42%) were likely infectious. The median duration of in-hospital isolation was 5 days for those likely infectious and 2 days for those deemed noninfectious.
SARS-CoV-2 was infrequent among patients admitted for reasons unrelated to COVID-19. An assessment of the likelihood of infectiousness using clinical history, RT-PCR Ct values, and serology may help in making the determination to discontinue isolation and conserve resources.
Agriculture accounts for around 70 % of global freshwater withdrawals. As such, the food system has been identified as a critical intervention point to address water scarcity. Various studies have identified dietary patterns that contribute less to water scarcity. However, it is unclear what level of reduction is necessary to be considered sustainable. The pursuit of unnecessarily aggressive reductions could limit dietary diversity. Our objective was to assess the sustainability of water use supporting Australian dietary habits and the adequacy of current dietary guidelines.
Dietary intake data were obtained from the National Nutrition and Physical Activity component of the Australian Health Survey. For each individual daily diet, the water scarcity footprint was quantified, following ISO14046:2014, as well as a diet quality score. Water scarcity footprint results were compared with the planetary boundary for freshwater use downscaled to the level of an individual diet.
9341 adults participating in the Australian Health Survey.
Dietary water scarcity footprints averaged 432·6 L-eq (95 % CI 432·5, 432·8), less than the 695 litres/person per d available to support the current global population of 7·8 billion, and the 603 litres/person per d available for a future population of 9 billion. Diets based on the Australian Dietary Guidelines required 521 L-eq/d, or 379 L-eq/d with lower water scarcity footprint food choices.
Diets based on the Australian Dietary Guidelines were found to be within the freshwater planetary boundary. What is needed in Australia is greater compliance with dietary guidelines.
The EVOSHEEP project combines archaeozoology, geometric morphometrics and genetics to study archaeological sheep assemblages dating from the sixth to the first millennia BC in eastern Africa, the Levant, the Anatolian South Caucasus, the Iranian Plateau and Mesopotamia. The project aims to understand changes in the physical appearance and phenotypic characteristics of sheep and how these related to the appearance of new breeds and the demand for secondary products to supply the textile industry.
The Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) is commonly used to assist with post-concussion return-to-play decisions for athletes. Additional investigation is needed to determine whether embedded indicators used to determine the validity of scores are influenced by the presence of neurodevelopmental disorders (NDs).
This study examined standard and novel ImPACT validity indicators in a large sample of high school athletes (n = 33,772) with or without self-reported ND.
Overall, 7.1% of athletes’ baselines were judged invalid based on standard ImPACT validity criteria. When analyzed by group (healthy, ND), there were significantly more invalid ImPACT baselines for athletes with an ND diagnosis or special education history (between 9.7% and 54.3% for standard and novel embedded validity criteria) when compared to athletes without NDs. ND history was a significant predictor of invalid baseline performance above and beyond other demographic characteristics (i.e., age, sex, and sport), although it accounted for only a small percentage of variance. Multivariate base rates are presented stratified for age, sex, and ND.
These data provide evidence of higher than normal rates of invalid baselines in athletes who report ND (based on both the standard and novel embedded validity indicators). Although ND accounted for a small percentage of variance in the prediction of invalid performance, negative consequences (e.g., extended time out of sports) of incorrect decision-making should be considered for those with neurodevelopmental conditions. Also, reasons for the overall increase noted here, such as decreased motivation, “sandbagging”, or disability-related cognitive deficit, require additional investigation.
The seroprevalence of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) IgG antibody was evaluated among employees of a Veterans Affairs healthcare system to assess potential risk factors for transmission and infection.
All employees were invited to participate in a questionnaire and serological survey to detect antibodies to SARS-CoV-2 as part of a facility-wide quality improvement and infection prevention initiative regardless of clinical or nonclinical duties. The initiative was conducted from June 8 to July 8, 2020.
Of the 2,900 employees, 51% participated in the study, revealing a positive SARS-CoV-2 seroprevalence of 4.9% (72 of 1,476; 95% CI, 3.8%–6.1%). There were no statistically significant differences in the presence of antibody based on gender, age, frontline worker status, job title, performance of aerosol-generating procedures, or exposure to known patients with coronavirus infectious disease 2019 (COVID-19) within the hospital. Employees who reported exposure to a known COVID-19 case outside work had a significantly higher seroprevalence at 14.8% (23 of 155) compared to those who did not 3.7% (48 of 1,296; OR, 4.53; 95% CI, 2.67–7.68; P < .0001). Notably, 29% of seropositive employees reported no history of symptoms for SARS-CoV-2 infection.
The seroprevalence of SARS-CoV-2 among employees was not significantly different among those who provided direct patient care and those who did not, suggesting that facility-wide infection control measures were effective. Employees who reported direct personal contact with COVID-19–positive persons outside work were more likely to have SARS-CoV-2 antibodies. Employee exposure to SARS-CoV-2 outside work may introduce infection into hospitals.
The Cognitive Abilities Screening Instrument (CASI) is a screening test of global cognitive function used in research and clinical settings. However, the CASI was developed using face validity and has not been investigated via empirical tests such as factor analyses. Thus, we aimed to develop and test a parsimonious conceptualization of the CASI rooted in cognitive aging literature reflective of crystallized and fluid abilities.
Secondary data analysis implementing confirmatory factor analyses where we tested the proposed two-factor solution, an alternate one-factor solution, and conducted a χ2 difference test to determine which model had a significantly better fit.
Data came from 3,491 men from the Kuakini Honolulu-Asia Aging Study.
The Cognitive Abilities Screening Instrument.
Findings demonstrated that both models fit the data; however, the two-factor model had a significantly better fit than the one-factor model. Criterion validity tests indicated that participant age was negatively associated with both factors and that education was positively associated with both factors. Further tests demonstrated that fluid abilities were significantly and negatively associated with a later-life dementia diagnosis.
We encourage investigators to use the two-factor model of the CASI as it could shed light on underlying cognitive processes, which may be more informative than using a global measure of cognition.
There is limited understanding of the cognitive profiles of Spanish-speaking children with Attention-Deficit/Hyperactivity Disorder (ADHD). The current study investigated the cognitive cluster profiles of Puerto Rican Spanish-speaking children with ADHD using the Wechsler Intelligence Scales for Children-Fourth Edition Spanish (WISC-IV Spanish) Index scores and examined the association between cognitive cluster profiles with other potentially relevant factors.
Hierarchical cluster analysis was used to identify WISC-IV clusters in a sample of 165 Puerto Rican children who had a primary diagnosis of ADHD. To examine the validity of the ADHD clusters, analysis of variances and chi-square analyses were conducted to compare the clusters across sociodemographics (e.g., age and education), type of ADHD diagnosis (ADHD subtype, Learning Disorder comorbidity), and academic achievement.
Clusters were differentiated by level and pattern of performance. A five-cluster solution was identified as optimal that included (C1) multiple cognitive deficits, (C2) processing speed deficits, (C3) generally average performance, (C4) perceptual reasoning strengths, and (C5) working memory deficits. Among the five clusters, the profile with multiple cognitive deficits was characterized by poorer performance on the four WISC-IV Spanish Indexes and was associated with adverse sociodemographic characteristics.
Results illustrate that there is substantial heterogeneity in cognitive abilities of Puerto Rican Spanish-speaking children with ADHD, and this heterogeneity is associated with a number of relevant outcomes.
The food system is responsible for around 70% of global freshwater use. Pathways toward responsible consumption and production of food are therefore critically needed to ensure the planetary boundary for freshwater use is not transgressed. There is also an uneven spatial distribution of freshwater resources and human water demands, meaning that water-scarcity is acute in some regions but a lesser concern in others. Quantifying the water-scarcity impacts associated with food consumption is therefore a complex challenge due to the diversity of individual eating patterns, the very large number of individual food products available, and the many different regions where food is grown or processed. To our knowledge, this is the first study to calculate water footprints for a large number of self-selected diets. Life cycle assessment was used to model the water-scarcity footprints of 9,341 individual Australian adult diets obtained through 24-hour recall as part of the most recent Australian Health Survey. Three water-scarcity indicators were used, including the AWARE model recently developed by a project group working under the auspices of the United Nations Environment Programme (UNEP) / Society of Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative (www.lifecycleinitiative.org). In addition, a diet quality score was calculated for each of these diets. Our objective was to identify pathways toward healthier diets with lower water-scarcity impacts. Dietary water-scarcity footprints averaged 362 L-eq person-1 day-1 and were highly variable (sd. 218 L-eq person-1 day-1), reflecting the diversity of eating habits in the general community. The largest water-scarcity impacts were related to the excessive consumption of discretionary foods (alcoholic beverages, processed meat products, dairy desserts, cream, butter, muesli bars, confectionery, chocolate, biscuits, cakes, waffles, fried potato and extruded snacks, etc.). The potential to reduce dietary water-scarcity impacts is large, although the opportunity to intervene through amended dietary guidelines is not straightforward due to the large variations in water-scarcity footprint intensity between individual foods within a food group, and the inability of consumers to identify lower water-scarcity footprint products without food labeling. Reductions in the water-scarcity footprint of Australian food consumption are likely best achieved through reductions in food waste, technological change to improve water-use efficiency in food production, as well as the implementation of product reformulation and procurement strategies in the food manufacturing sector to avoid higher water-scarcity footprint intensity ingredients.