Epidemiology and Treatment Outcomes of Tuberculosis with Chronic Hepatitis B Infection-California, 2016-2020.

BACKGROUND: Improved epidemiologic and treatment data for active tuberculosis (TB) with chronic hepatitis B virus (cHBV) infection might inform and encourage screening and vaccination programs focused on persons at risk of having both conditions. METHODS: We matched the California Department of Public Health TB registry during 2016-2020 to the cHBV registry using probabilistic matching algorithms. We used chi-square analysis to compare the characteristics of persons with TB and cHBV with those with TB only. We compared TB treatment outcomes between these groups using modified Poisson regression models. We calculated the time between reporting of TB and cHBV diagnoses for those with both conditions. RESULTS: We identified 8,435 persons with TB, including 316 (3.7%) with cHBV.- Among persons with TB and cHBV, 256 (81.0%) were non-U.S.-born Asian vs 4,186 (51.6%) with TB only (P <0.0001). End-stage renal disease (26 [8.2%] vs 322 [4.0%]; P <0.001) and HIV (21 [6.7%] vs 247 [3.0%]; P value = 0.02) were more frequent among those with TB and cHBV compared with those with TB only. Among those with both conditions, 35 (11.1%) had TB diagnosed >60 days before cHBV (median 363 days) and 220 (69.6%) had TB diagnosed >60 days after cHBV (median 3,411 days). CONCLUSION: Persons with TB and cHBV were found more frequently in certain groups compared with TB only, and infrequently had their conditions diagnosed together. This highlights an opportunity to improve screening and treatment of TB and cHBV in those at high risk for coinfection.

A Pediatric Case of Treatment-related Myelodysplastic Syndrome While on Therapy for Pre-B Acute Lymphoblastic Leukemia.

BACKGROUND: Treatment-related myelodysplastic syndrome (t-MDS) is a rare late effect of cancer therapy. After alkylating agents, this typically occurs years after completion of therapy. Treatment of t-MDS in pediatrics is an allogeneic stem cell transplant, however, the prognosis remains poor. OBSERVATIONS: This case demonstrates t-MDS developing in a patient receiving treatment for pre-B acute lymphoblastic leukemia. This patient was treated with a combination of hematopoietic stem cell transplant and hypomethylating agents. CONCLUSIONS: These agents should be considered for use in patients with t-MDS, before transplant to limit additional chemotherapy and as maintenance therapy post-transplant to reduce the risk of relapse.

Using the Generalized Synthetic Control Method to Estimate the Impact of Extreme Weather Events on Population Health.

BACKGROUND: Traditional epidemiologic approaches such as time-series or case-crossover designs are often used to estimate the effects of extreme weather events but can be limited by unmeasured confounding. Quasi-experimental methods are a family of methods that leverage natural experiments to adjust for unmeasured confounding indirectly. The recently developed generalized synthetic control method that exploits the timing of an exposure is well suited to estimate the impact of acute environmental events on health outcomes. To demonstrate how this method can be used to study extreme weather events, we examined the impact of the 20-26 October 2007 Southern California wildfire storm on respiratory hospitalizations. METHODS: We used generalized synthetic control to compare the average number of ZIP code-level respiratory hospitalizations during the wildfire storm between ZIP codes that were classified as exposed versus unexposed to wildfire smoke. We considered wildfire exposure eligibility for each ZIP code using fire perimeters and satellite-based smoke plume data. We retrieved respiratory hospitalization discharge data from the Office of Statewide Health Planning and Development. R code to implement the generalized synthetic control method is included for reproducibility. RESULTS: The analysis included 172 exposed and 578 unexposed ZIP codes. We estimated that the average effect of the wildfire storm among the exposed ZIP codes was an 18% (95% confidence interval: 10% to 29%) increase in respiratory hospitalizations. CONCLUSIONS: We illustrate the use of generalized synthetic control to leverage natural experiments to quantify the health impacts of extreme weather events when traditional approaches are unavailable or limited by assumptions.

Saharan Dust and Childhood Respiratory Symptoms in Benin.

Mineral dust is one of the largest natural constituents of coarse particulate matter (PM10). Most of these dust emissions originate from northern Africa, and several hundred tera-grams of dust are emitted annually from this region. Previous evidence has linked dust PM10 to adverse respiratory outcomes in children. However, most of these studies have been from high-income countries (HICs) or examined dust from other regions of the world, mainly Asia. Evidence from low-to-middle-income countries (LMICs) in Africa is scarce. Respiratory infections are one of the leading causes of under-five mortality across the globe. However, there is a poignant disparity in studies examining these outcomes in children in the region where most dust is emitted. This study linked remotely sensed satellite data to a nationally representative survey to examine acute exposure to dust in children living in Benin using a time-stratified case-crossover analysis. We identified acute effects of exposure to dust and increased risk of cough in children under five. The effect of increased risk is strongest within two weeks of exposure and dissipates by four weeks. Children living in rural areas and households with lower income had a greater risk of adverse respiratory outcomes when exposed to dust. We could elucidate the specific period and conditions of increased risk for respiratory problems in children living in Benin.

Precipitation variability and risk of infectious disease in children under 5 years for 32 countries: a global analysis using Demographic and Health Survey data.

BACKGROUND: Precipitation variability is a potentially important driver of infectious diseases that are leading causes of child morbidity and mortality worldwide. Disentangling the links between precipitation variability and disease risk is crucial in a changing climate. We aimed to investigate the links between precipitation variability and reported symptoms of infectious disease (cough, fever, and diarrhoea) in children younger than 5 years. METHODS: We used nationally representative survey data collected between 2014 and 2019 from Demographic and Health Survey (DHS) surveys for 32 low-income to middle-income countries in combination with high-resolution precipitation data (via the Climate Hazards Group InfraRed Precipitation with Station dataset). We only included DHS data for which interview dates and GPS coordinates (latitude and longitude) of household clusters were available. We used a regression modelling approach to assess the relationship between different precipitation variability measures and infectious disease symptoms (cough, fever, and diarrhoea), and explored the effect modification of different climate zones and disease susceptibility factors. FINDINGS: Our global analysis showed that anomalously wet conditions increase the risk of cough, fever, and diarrhoea symptoms in humid, subtropical regions. These health risks also increased in tropical savanna regions as a result of anomalously dry conditions. Our analysis of susceptibility factors suggests that unimproved sanitation and unsafe drinking water sources are exacerbating these effects, particularly for rural populations and in drought-prone areas in tropical savanna. INTERPRETATION: Weather shifts can affect the survival and transmission of pathogens that are particularly harmful to young children. As our findings show, the health burden of climate-sensitive infectious diseases can be substantial and is likely to fall on populations that are already among the most disadvantaged, including households living in remote rural areas and those lacking access to safe water and sanitation infrastructure. FUNDING: University of California, San Diego FY19 Center Launch programme.

Extreme heat, preterm birth, and stillbirth: A global analysis across 14 lower-middle income countries.

Stillbirths and complications from preterm birth are two of the leading causes of neonatal deaths across the globe. Lower- to middle-income countries (LMICs) are experiencing some of the highest rates of these adverse birth outcomes. Research has suggested that environmental determinants, such as extreme heat, can increase the risk of preterm birth and stillbirth. Under climate change, extreme heat events have become more severe and frequent and are occurring in differential seasonal patterns. Little is known about how extreme heat affects the risk of preterm birth and stillbirth in LMICs. Thus, it is imperative to examine how exposure to extreme heat affects adverse birth outcomes in regions with some of the highest rates of preterm and stillbirths. Most of the evidence linking extreme heat and adverse birth outcomes has been generated from high-income countries (HICs) notably because measuring temperature in LMICs has proven challenging due to the scarcity of ground monitors. The paucity of health data has been an additional obstacle to study this relationship in LMICs. In this study, globally gridded meteorological data was linked with spatially and temporally resolved Demographic and Health Surveys (DHS) data on adverse birth outcomes. A global analysis of 14 LMICs was conducted per a pooled time-stratified case-crossover design with distributed-lag nonlinear models to ascertain the relationship between acute exposure to extreme heat and PTB and stillbirths. We notably found that experiencing higher maximum temperatures and smaller diurnal temperature range during the last week before birth increased the risk of preterm birth and stillbirth. This study is the first global assessment of extreme heat events and adverse birth outcomes and builds the evidence base for LMICs.

Green mobility and obesity risk: A longitudinal analysis in California.

Previous work reports an inverse association between neighborhood greenness and obesity. Limitations of this work, which relies largely on cross-sectional data, include that studies often lack control for unmeasured genetic and sociodemographic factors that may confound associations, and cannot disentangle temporal order between neighborhood greenness and obesity. We move beyond a cross-sectional approach and leverage a longitudinal sibling-linked dataset with health, residential, and demographic information on women with two births in California between 2007 and 2015 (N = 552,929). We used a sibling comparison design to control for unmeasured stable characteristics of women and tested whether a positive change in neighborhood greenness (i.e., "upward green mobility") precedes a reduction in obesity risk. Models also adjusted for baseline obesity risk and time-varying individual- and neighborhood-level socioeconomic factors. As hypothesized, we find that upward green mobility varies inversely with the odds of obesity. Results indicate that small decreases in neighborhood greenness may also show protective associations with obesity risk. Our findings, if replicated, suggest that changing levels (particularly increases) of greenness in the residential environment may combat the rise of obesity.

Modeling the Impact of Population Intervention Strategies on Reducing Health Disparities: Water, Sanitation, and Hygiene Interventions and Childhood Diarrheal Disease in Peru.

Access to safe water and basic sanitation and hygiene facilities (WASH) are important for childhood health globally. However, inequalities in WASH access persist, and local governments need to better understand the potential impact of scaling up WASH services on childhood health. Using 2011 Peru Demographic and Health Survey data as a case study, we applied a modified substitution estimator approach to assess the impact of scaling up access (20-100%) to WASH on diarrhea prevalence among children < 5 years. The modified substitution estimator approach can help identify population subgroups or areas where WASH interventions and sustained implementation could be most beneficial and reduce existing disparities. Using findings from a recent meta-analysis and computing bootstrapped estimates and 95% CIs, we examined inequalities in the effect of WASH on self-reported diarrhea by urbanicity, maternal education level, household wealth, and district of residence. Increasing access (100% change) to improved water sources, sanitation, and hygiene facilities reduced population-level prevalence of childhood diarrhea by 8.2% (95% CI: 4.1, 12.3), 5.5% (95% CI: 0.7, 9.8), and 5.2% (95% CI: 2.2, 8.1), respectively. In stratified analyses, increased access to improved water sources and hygiene facilities was associated with decreased prevalence of diarrhea, with the largest reduction in rural areas and households with lower maternal education and lower wealth. Our findings suggest targeted WASH implementation in Peru is needed in rural areas and among lower socioeconomic-status households. In addition, even low levels of change in overall WASH access may decrease diarrhea prevalence.

Defining heat waves and extreme heat events using sub-regional meteorological data to maximize benefits of early warning systems to population health.

BACKGROUND: Extreme heat events have been consistently associated with an increased risk of hospitalization for various hospital diagnoses. Classifying heat events is particularly relevant for identifying the criteria to activate early warning systems. Heat event classifications may also differ due to heterogeneity in climates among different geographic regions, which may occur at a small scale. Using local meteorological data, we identified heat waves and extreme heat events that were associated with the highest burden of excess hospitalizations within the County of San Diego and quantified discrepancies using county-level meteorological criteria. METHODS: Eighteen event classifications were created using various combinations of temperature metric, percentile, and duration for both county-level and climate zone level meteorological data within San Diego County. Propensity score matching and Poisson regressions were utilized to ascertain the association between heat wave exposure and risk of hospitalization for heat-related illness and dehydration for the 1999-2013 period. We estimated both relative and absolute risks for each heat event classification in order to identify optimal definitions of heat waves and extreme heat events for the whole city and in each climate zone to target health impacts. RESULTS: Heat-related illness differs vastly by level (county or zone-specific), definition, and risk measure. We found the county-level definitions to be systematically biased when compared to climate zone definitions with the largest discrepancy of 56 attributable hospitalizations. The relative and attributable risks were often minimally correlated, which exemplified that relative risks alone are not adequate to optimize heat waves definitions. CONCLUSIONS: Definitions based on county-level defined thresholds do not provide an accurate picture of the observed health effects and will fail to maximize the potential effectiveness of heat warning systems. Absolute rather than relative risks are a more appropriate measure to define the set of criteria to activate early warnings systems and thus maximize public health benefits.

Does the air pollution model influence the evidence of socio-economic disparities in exposure and susceptibility?

Studies assessing socio-economic disparities in air pollution exposure and susceptibility are usually based on a single air pollution model. A time stratified case-crossover study was designed to assess the impact of the type of model on differential exposure and on the differential susceptibility in the relationship between ozone exposure and daily mortality by socio-economic strata (SES) in Montreal. Non-accidental deaths along with deaths from cardiovascular and respiratory causes on the island of Montreal for the period 1991-2002 were included as cases. Daily ozone concentration estimates at partictaipants' residence were obtained from the five following air pollution models: Average value (AV), Nearest station model (NS), Inverse-distance weighting interpolation (IDW), Land-use regression model with back-extrapolation (LUR-BE) and Bayesian maximum entropy model combined with a land-use regression (BME-LUR). The prevalence of a low household income (< 20,000/year) was used as socio-economic variable, divided into two categories as a proxy for deprivation. Multivariable conditional logistic regressions were used considering 3-day average concentrations. Multiplicative and additive interactions (using Relative Excess Risk due to Interaction) as well as Cochran's tests were calculated and results were compared across the different air pollution models. Heterogeneity of susceptibility and exposure according to socio-economic status (SES) were found. Ratio of exposure across SES groups means ranged from 0.75 [0.74-0.76] to 1.01 [1.00-1.02], respectively for the LUR-BE and the BME-LUR models. Ratio of mortality odds ratios ranged from 1.01 [0.96-1.05] to 1.02 [0.97-1.08], respectively for the IDW and LUR-BE models. Cochran's test of heterogeneity between the air pollution models showed important heterogeneity regarding the differential exposure by SES, but the air pollution model was not found to influence heterogeneity regarding the differential susceptibility. The study showed air pollution models can influence the assessment of disparities in exposure according to SES in Montreal but not that of disparities in susceptibility.

Computed tomography detection of extracapsular spread of squamous cell carcinoma of the head and neck in metastatic cervical lymph nodes.

Background and purpose In patients with squamous cell carcinoma of the head and neck (HNSCC), extracapsular spread (ECS) of metastases in cervical lymph nodes affects prognosis and therapy. We assessed the accuracy of intravenous contrast-enhanced computed tomography (CT) and the utility of imaging criteria for preoperative detection of ECS in metastatic cervical lymph nodes in patients with HNSCC. Materials and methods Preoperative intravenous contrast-enhanced neck CT images of 93 patients with histopathological HNSCC metastatic nodes were retrospectively assessed by two neuroradiologists for ECS status and ECS imaging criteria. Radiological assessments were compared with histopathological assessments of neck dissection specimens, and interobserver agreement of ECS status and ECS imaging criteria were measured. Results Sensitivity, specificity, positive predictive value, and accuracy for overall ECS assessment were 57%, 81%, 82% and 67% for observer 1, and 66%, 76%, 80% and 70% for observer 2, respectively. Correlating three or more ECS imaging criteria with histopathological ECS increased specificity and positive predictive value, but decreased sensitivity and accuracy. Interobserver agreement for overall ECS assessment demonstrated a kappa of 0.59. Central necrosis had the highest kappa of 0.74. Conclusion CT has moderate specificity for ECS assessment in HNSCC metastatic cervical nodes. Identifying three or more ECS imaging criteria raises specificity and positive predictive value, therefore preoperative identification of multiple criteria may be clinically useful. Interobserver agreement is moderate for overall ECS assessment, substantial for central necrosis. Other ECS CT criteria had moderate agreement at best and therefore should not be used individually as criteria for detecting ECS by CT.

Quantifying published scholarly works of experiential education directors.

OBJECTIVE: To determine the amount and potential impact of scholarly works that directors of experiential education in US colleges and schools of pharmacy have published since 2001. METHODS: A search in Web of Science was used to identify publications and citations for the years 2001-2011 by experiential education directors as identified by the American Association of Colleges of Pharmacy (AACP) Roster of Faculty and Professional Staff in 2011. Publication productivity was analyzed by position title, faculty rank, and type of institution (public vs private, research vs nonresearch-intensive). Types of published works were characterized, related citations were identified, and a reported h-index was collected for each person who published during this period. RESULTS: Ninety-seven of 226 (43%) experiential education directors published 344 scholarly works which had received 1841 citations, for an average of 1 publication every 3 years and an average citation rate of 5.3 per publication. Directors at publicly funded and research-intensive institutions published slightly more than did their counterparts at private and nonresearch-intensive schools. Publications were concentrated in 6 journals with a weighted mean publication impact factor of 1.5. CONCLUSION: Many experiential education directors have published scholarly works even though their titles and ranks vary widely. While the quantity of such works may not be large, the impact is similar to that of other pharmacy practice faculty members. These results could be used to characterize the scholarly performance of experiential education directors in recent years as well as to establish a culture of scholarship in this emerging career track within pharmacy education.