Effects of hypertension and use of antihypertensive drugs in pregnancy on the risks of childhood cancers in Taiwan.

BACKGROUND: Childhood cancers are associated with high mortality and morbidity, and some maternal prescription drug use during pregnancy has been implicated in cancer risk. There are few studies on the effects of hypertension, preeclampsia, and the use of antihypertensives in pregnancy on children's cancer risks. OBJECTIVE: This population-based cohort study analyzed the relationship between hypertension, preeclampsia, and antihypertensives taken during pregnancy and the risks of childhood cancers in the offspring. METHODS: Data on all children born in Taiwan between 2004 and 2015 (N = 2,294,292) were obtained from the Maternal and Child Health Database. This registry was linked with the National Health Insurance Database and Cancer Registry to get the records of maternal use of diuretics or other antihypertensives in pregnancy and records of children with cancer diagnosed before 13 years. We used Cox proportional hazard modeling to estimate the influence of maternal health conditions and antihypertensive drug exposure on the risks of developing childhood cancers. RESULTS: Offspring of mothers with hypertension (chronic or gestational) had a higher risk of acute lymphocytic lymphoma [hazard ratio (HR) = 1.87, 95% Confidence Interval (CI) 1.32 - 2.65] and non-Hodgkin's lymphoma (HR = 1.96, 95% CI 1.34 - 2.86). We estimated only a weak increased cancer risk in children whose mothers used diuretics (HR = 1.16, 95% CI 0.77 - 1.74) or used antihypertensives other than diuretics (HR = 1.15, 95% CI 0.86 - 1.54) before birth. CONCLUSIONS: In this cohort study, children whose mothers had chronic and gestational hypertension had an increased risk of developing childhood cancer.

A prediction model for classifying maternal pregnancy smoking using California state birth certificate information.

BACKGROUND: Systematically recorded smoking data are not always available in vital statistics records, and even when available it can underestimate true smoking rates. OBJECTIVE: To develop a prediction model for maternal tobacco smoking in late pregnancy based on birth certificate information using a combination of self- or provider-reported smoking and biomarkers (smoking metabolites) in neonatal blood spots as the alloyed gold standard. METHODS: We designed a case-control study where childhood cancer cases were identified from the California Cancer Registry and controls were from the California birth rolls between 1983 and 2011 who were cancer-free by the age of six. In this analysis, we included 894 control participants and performed high-resolution metabolomics analyses in their neonatal dried blood spots, where we extracted cotinine [mass-to-charge ratio (m/z) = 177.1023] and hydroxycotinine (m/z = 193.0973). Potential predictors of smoking were selected from California birth certificates. Logistic regression with stepwise backward selection was used to build a prediction model. Model performance was evaluated in a training sample, a bootstrapped sample, and an external validation sample. RESULTS: Out of seven predictor variables entered into the logistic model, five were selected by the stepwise procedure: maternal race/ethnicity, maternal education, child's birth year, parity, and child's birth weight. We calculated an overall discrimination accuracy of 0.72 and an area under the receiver operating characteristic curve (AUC) of 0.81 (95% confidence interval [CI] 0.77, 0.84) in the training set. Similar accuracies were achieved in the internal (AUC 0.81, 95% CI 0.77, 0.84) and external (AUC 0.69, 95% CI 0.64, 0.74) validation sets. CONCLUSIONS: This easy-to-apply model may benefit future birth registry-based studies when there is missing maternal smoking information; however, some smoking status misclassification remains a concern when only variables from the birth certificate are used to predict maternal smoking.

Multiple forms of perceived job discrimination and hypertension risk among employed women: Findings from the Sister Study.

BACKGROUND: Hypertension has been linked to socially patterned stressors, including discrimination. Few studies have quantified the risk of hypertension associated with exposure to perceived job discrimination. METHODS: We used prospective cohort data from the Sister Study (enrollment from 2003-2009) to estimate self-reported incident hypertension associated with perceived job discrimination based on race, gender, age, sexual orientation, or health status. Job discrimination in the prior 5 years was assessed in 2008-2012, and incident doctor-diagnosed hypertension was ascertained in previously hypertension-free participants. RESULTS: Among the 16,770 eligible participants aged 37-78 years at the start of follow-up, 10.5% reported job discrimination in the past 5 years, and 19.2% (n = 3226) reported incident hypertension during a median follow-up of 9.7 years (interquartile range 8.2-11.0 years). Self-reported poor health or inclusion in minoritized groups based on race/ethnicity or sexual orientation were more frequent among those reporting job discrimination. In a Cox proportional hazards model adjusting for covariates, report of at least one type of job discrimination (compared to none) was associated with a 14% (hazard ratio = 1.14 [95% confidence: 1.02-1.27]) higher hypertension risk. Results from sensitivity analyses reinforced the findings. CONCLUSIONS: Results suggest that interventions addressing job discrimination could have workplace equity and health benefits.

Associations of U.S. state-level COVID-19 policies intensity with cannabis sharing behaviors in 2020.

BACKGROUND: Cannabis use before the COVID-19 pandemic for many involved sharing prepared cannabis for inhalation, practices that were less prevalent during the pandemic. State-level COVID-19 containment policies may have influenced this decrease. This study examined the extent to which the intensity of state-level COVID-19 policies were associated with individual-level cannabis sharing. Findings have the potential to guide harm reduction policies for future respiratory pandemics and seasonal respiratory virus waves. METHODS: This study used cross-sectional individual-level data from the COVID-19 Cannabis Study, an anonymous U.S.-based web survey on cannabis use disseminated during the early phase of the pandemic (Full sample N = 1,883). We combined individual-level data with state-level policy data from Kaiser Family Foundation's State COVID-19 Data and Policy Actions for three time-points from June to August 2020 that overlapped with the survey period. Cannabis sharing was dichotomized as any versus no sharing. We adapted a previously published coding framework to score the intensity of COVID-19 policies implemented in each U.S. state and averaged the policy score across the time period. We then used Poisson regression models to quantify the associations of the average state-level COVID-19 policy score with cannabis sharing during the pandemic. RESULTS: Participants (n = 925) reporting using inhalation as a mode for cannabis use were included in this analysis. Most respondents were male (64.1%), non-Hispanic White (54.3%), with a mean age of 33.7 years (SD 8.8). A large proportion (74.9%) reported sharing cannabis during the pandemic. Those who shared cannabis more commonly lived in states with a lower average policy score (16.7, IQR 12.3-21.5) compared to those who did not share (18.6, IQR 15.3-25.3). In adjusted models, the prevalence ratio of any cannabis sharing per every 5-unit increase in the average COVID-19 policy score was 0.97 (95% CI 0.93, 1.01). CONCLUSIONS: Fewer individuals shared cannabis in states with more intense COVID-19 containment policies compared to those in states with less intense policies. Individuals who use cannabis may be willing to make changes to their behavior and may further benefit from specific and directed public health messaging to avoid sharing during respiratory infection outbreaks.

Complexity in Epidemiology and Public Health. Addressing Complex Health Problems Through a Mix of Epidemiologic Methods and Data.

Public health and the underlying disease processes are complex, often involving the interaction of biologic, social, psychologic, economic, and other processes that may be nonlinear and adaptive and have other features of complex systems. There is therefore a need to push the boundaries of public health beyond single-factor data analysis and expand the capacity of research methodology to tackle real-world complexities. This article sets out a way to operationalize complex systems thinking in public health, with a particular focus on how epidemiologic methods and data can contribute towards this end. Our proposed framework comprises three core dimensions-patterns, mechanisms, and dynamics-along which complex systems may be conceptualized. These dimensions cover seven key features of complex systems-emergence, interactions, nonlinearity, interference, feedback loops, adaptation, and evolution. We relate this framework to examples of methods and data traditionally used in epidemiology. We conclude that systematic production of knowledge on complex health issues may benefit from: formulation of research questions and programs in terms of the core dimensions we identify, as a comprehensive way to capture crucial features of complex systems; integration of traditional epidemiologic methods with systems methodology such as computational simulation modeling; interdisciplinary work; and continued investment in a wide range of data types. We believe that the proposed framework can support the systematic production of knowledge on complex health problems, with the use of epidemiology and other disciplines. This will help us understand emergent health phenomena, identify vulnerable population groups, and detect leverage points for promoting public health.

Maternal anemia and the risk of childhood cancer: A population-based cohort study in Taiwan.

BACKGROUND: Childhood cancer may be related to maternal health in pregnancy. Maternal anemia is a common condition in pregnancy, especially in low-income countries, but the association between maternal anemia and childhood cancer has not been widely studied. OBJECTIVE: To examine the potential relation between maternal anemia during pregnancy and childhood cancers in a population-based cohort study in Taiwan. METHODS: We examined the relationship between maternal anemia and childhood cancer in Taiwan (N = 2160 cancer cases, 2,076,877 noncases). Cases were taken from the National Cancer Registry, and noncases were selected from birth records. Using national health registries, we obtained maternal anemia diagnoses. We estimated the risks for childhood cancers using Cox proportional hazard analysis. RESULTS: There was an increased risk of cancers in children born to mothers with nutritional anemia (hazard ratio (HR): 1.32, 95% CI 0.99, 1.76). Iron deficiency anemia (HR: 1.30, 95% CI 0.97-1.75) carried an increased risk, while non-nutritional anemias were not associated with childhood cancer risk. CONCLUSION: Our results provide additional support for screening for anemia during pregnancy. Adequate nutrition and vitamin supplementation may help to prevent some childhood cancer.

Maternal vitamin D levels and male reproductive health: a population-based follow-up study.

Maternal vitamin D levels during pregnancy may be important for reproductive health in male offspring by regulating cell proliferation and differentiation during development. We conducted a follow-up study of 827 young men from the Fetal Programming of Semen Quality (FEPOS) cohort, nested in the Danish National Birth Cohort to investigate if maternal vitamin D levels were associated with measures of reproductive health in adult sons. These included semen characteristics, testes volume, and reproductive hormone levels and were analysed according to maternal vitamin D (25(OH)D3) levels during pregnancy. In addition, an instrumental variable analysis using seasonality in sun exposure as an instrument for maternal vitamin D levels was conducted. We found that sons of mothers with vitamin D levels < 25 nmol/L had 11% (95% CI - 19 to - 2) lower testes volume and a 1.4 (95% CI 1.0 to 1.9) times higher risk of having low testes volume (< 15 mL), in addition to 20% (95% CI - 40 to 9) lower total sperm count and a 1.6 (95% CI 0.9 to 2.9) times higher risk of having a low total sperm count (< 39 million) compared with sons of mothers with vitamin D levels > 75 nmol/L. Continuous models, spline plots and an instrumental variable analysis supported these findings. Low maternal vitamin D levels were associated with lower testes volume and lower total sperm count with indications of dose-dependency. Maternal vitamin D level above 75 nmol/L during pregnancy may be beneficial for testes function in adult sons.

Puff, Puff, Don't Pass: harm reduction for cannabis use during a viral respiratory pandemic.

BACKGROUND: Prior to the COVID-19 pandemic, cannabis use social practices often involved sharing prepared cannabis (joints/blunts/cigarettes) and cannabis-related paraphernalia. Previous studies have demonstrated that sharing paraphernalia for cannabis, tobacco, and crack cocaine is a risk factor for respiratory viral and bacterial infections. Although COVID-19 is a respiratory viral infection that spreads through droplets and airborne transmission, it is unclear if many individuals adopted harm reduction practices around sharing cannabis. This study: quantifies the prevalence of sharing prepared non-medical cannabis and cannabis-related paraphernalia reported before and during the pandemic; assesses changes in sharing of non-medical cannabis from before to during the pandemic; assess the association between frequency of non-medical cannabis use and sharing of cannabis during the pandemic; and describes how respondents obtained their cannabis and the reasons for changing their cannabis use during the pandemic to explain differences in sharing patterns. METHODS: This cross-sectional study used data collected from an anonymous, US-based web survey on cannabis-related behaviors from August to September 2020 (n = 1833). Participants were included if they reported using a mode of inhalation for non-medical cannabis consumption. We calculated proportional changes in sharing cannabis before/during the COVID-19 pandemic. Associations between frequency of cannabis use and cannabis sharing during the COVID-19 pandemic were assessed using logistic regression analysis. RESULTS: Overall, 1,112 participants reported non-medical cannabis use; 925 (83.2%) reported a mode of cannabis inhalation. More respondents reported no sharing during (24.9%) than before the pandemic (12.4%; p < 0.01); less respondents shared most of the time (19.5% before; 11.2% during; p < 0.01) and always during the pandemic (5.2% before; 3.1% during; p < 0.01). After adjusting for covariates, the odds of any sharing during the pandemic for those who reported ≥ weekly cannabis use was 0.53 (95% CI 0.38, 0.75) compared to those who reported ≤ monthly. CONCLUSIONS: Sharing of prepared cannabis and cannabis-related paraphernalia decreased during the COVID-19 pandemic compared to before the pandemic. This finding suggests potential risk mitigation strategies taken by participants for COVID-19 prevention either directly through behavior change or indirectly through adherence to COVID-19 prevention recommendations. Harm reduction messaging around sharing of cannabis during surges of COVID-19 or other respiratory infections may provide benefit in reducing infection among those who use cannabis, especially as cannabis use in the USA continues to increase.

SARS-CoV-2 Infection During Pregnancy and Associated Perinatal Health Outcomes: A National US Cohort Study.

BACKGROUND: Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been associated with increased risk of adverse perinatal health outcomes, few large-scale, community-based epidemiological studies have been conducted. METHODS: We conducted a national cohort study using deidentified administrative claims data for 78 283 pregnancies with estimated conception before 30 April 2020 and pregnancy end after 11 March 2020. We identified SARS-CoV-2 infections using diagnostic and laboratory testing data, and compared the risk of pregnancy outcomes using Cox proportional hazard models treating coronavirus disease 2019 (COVID-19) as a time-varying exposure and adjusting for baseline covariates. RESULTS: Of the pregnancies, 2655 (3.4%) had a documented SARS-CoV-2 infection. COVID-19 during pregnancy was not associated with risk of miscarriage, antepartum hemorrhage, or stillbirth, but was associated with 2-3 fold higher risk of induced abortion (adjusted hazard ratio [aHR], 2.60; 95% confidence interval [CI], 1.17-5.78), cesarean delivery (aHR, 1.99; 95% CI, 1.71-2.31), clinician-initiated preterm birth (aHR, 2.88; 95% CI, 1.93-4.30), spontaneous preterm birth (aHR, 1.79; 95% CI, 1.37-2.34), and fetal growth restriction (aHR, 2.04; 95% CI, 1.72-2.43). CONCLUSIONS: Prenatal SARS-CoV-2 infection was associated with increased risk of adverse pregnancy outcomes. Prevention could have fetal health benefits.

Causal and Associational Language in Observational Health Research: A Systematic Evaluation.

We estimated the degree to which language used in the high-profile medical/public health/epidemiology literature implied causality using language linking exposures to outcomes and action recommendations; examined disconnects between language and recommendations; identified the most common linking phrases; and estimated how strongly linking phrases imply causality. We searched for and screened 1,170 articles from 18 high-profile journals (65 per journal) published from 2010-2019. Based on written framing and systematic guidance, 3 reviewers rated the degree of causality implied in abstracts and full text for exposure/outcome linking language and action recommendations. Reviewers rated the causal implication of exposure/outcome linking language as none (no causal implication) in 13.8%, weak in 34.2%, moderate in 33.2%, and strong in 18.7% of abstracts. The implied causality of action recommendations was higher than the implied causality of linking sentences for 44.5% or commensurate for 40.3% of articles. The most common linking word in abstracts was "associate" (45.7%). Reviewers' ratings of linking word roots were highly heterogeneous; over half of reviewers rated "association" as having at least some causal implication. This research undercuts the assumption that avoiding "causal" words leads to clarity of interpretation in medical research.

Maternal diabetes and childhood cancer risks in offspring: two population-based studies.

BACKGROUND: The effect of maternal diabetes on childhood cancer has not been widely studied. METHODS: We examined this in two population-based studies in Denmark (N = 6420 cancer cases, 160,484 controls) and Taiwan (N = 2160 cancer cases, 2,076,877 non-cases) using logistic regression and Cox proportional hazard regression adjusted for birth year, child's sex, maternal age and birth order. RESULTS: Gestational diabetes in Denmark [odds ratio (OR) = 0.98, 95% confidence interval (CI): 0.71-1.35] or type II and gestational diabetes in Taiwan (type II: hazard ratio (HR) = 0.81, 95% CI: 0.63-1.05; gestational diabetes: HR = 1.06, 95% CI: 0.92-1.22) were not associated with cancer (all types combined). In Denmark, maternal type I diabetes was associated with the risk of glioma (OR = 2.33, 95% CI: 1.04-5.22), while in Taiwan, the risks of glioma (HR = 1.59, 95% CI: 1.01-2.50) were elevated among children whose mothers had gestational diabetes. There was a twofold increased risk for hepatoblastoma with maternal type II diabetes (HR = 2.02, 95% CI: 1.02-4.00). CONCLUSIONS: Our results suggest that maternal diabetes is an important risk factor for certain types of childhood cancers, emphasising the need for effective interventions targeting maternal diabetes to prevent serious health effects in offspring.

Causal Effect of Chronic Pain on Mortality Through Opioid Prescriptions: Application of the Front-Door Formula.

BACKGROUND: Chronic pain is the leading cause of disability worldwide and is strongly associated with the epidemic of opioid overdosing events. However, the causal links between chronic pain, opioid prescriptions, and mortality remain unclear. METHODS: This study included 13,884 US adults aged ≥20 years who provided data on chronic pain in the National Health and Nutrition Examination Survey 1999-2004 with linkage to mortality databases through 2015. We employed the generalized form of the front-door formula within the structural causal model framework to investigate the causal effect of chronic pain on all-cause mortality mediated by opioid prescriptions. RESULTS: We identified a total of 718 participants at 3 years of follow-up and 1260 participants at 5 years as having died from all causes. Opioid prescriptions increased the risk of all-cause mortality with an estimated odds ratio (OR) (95% confidence interval) = 1.5 (1.1, 1.9) at 3 years and 1.3 (1.1, 1.6) at 5 years. The front-door formula revealed that chronic pain increased the risk of all-cause mortality through opioid prescriptions; OR = 1.06 (1.01, 1.11) at 3 years and 1.03 (1.01, 1.06) at 5 years. Our bias analysis showed that our findings based on the front-door formula were likely robust to plausible sources of bias from uncontrolled exposure-mediator or mediator-outcome confounding. CONCLUSIONS: Chronic pain increased the risk of all-cause mortality through opioid prescriptions. Our findings highlight the importance of careful guideline-based chronic pain management to prevent death from possibly inappropriate opioid prescriptions driven by chronic pain.

Comparative Effectiveness of Dialysis Modality on Laboratory Parameters of Mineral Metabolism.

INTRODUCTION: Chronic kidney disease-mineral and bone disorders (CKD-MBD) are prevalent in patients undergoing maintenance dialysis. Yet, there are limited and mixed evidence on the effects of different dialysis modalities involving longer treatment times or higher frequencies on CKD-MBD markers. METHODS: This cohort study used data from 132,523 incident dialysis patients treated with any of the following modalities: conventional thrice-weekly in-center hemodialysis, nocturnal in-center hemodialysis (NICHD), home hemodialysis (HHD), or peritoneal dialysis (PD) from 2007 to 2011. We used marginal structural models fitted with inverse probability weights to adjust for fixed and time-varying confounding and informative censoring. We estimated the average effects of treatments with different dialysis modalities on time-varying serum concentrations of CKD-MBD markers: albumin-corrected calcium, phosphate, parathyroid hormone (PTH), and alkaline phosphatase (ALP) using pooled linear regression. RESULTS: Most of the cohort were exclusively treated with conventional in-center hemodialysis, while few were ever treated with NICHD or HHD. At the baseline, PD patients had the lowest mean and median values of PTH, while NICHD patients had the highest median values. During follow-up, compared to hemodialysis patients, patients treated with NICHD had lower mean serum PTH (19.8 pg/mL [95% confidence interval: 2.8, 36.8] lower), whereas PD and HHD patients had higher mean PTH (39.7 pg/mL [31.6, 47.8] and 51.2 pg/mL [33.0, 69.3] higher, respectively). Compared to hemodialysis patients, phosphate levels were lower for patients treated with NICHD (0.44 mg/dL [0.37, 0.52] lower), PD (0.15 mg/dL [0.12, 0.19] lower), or HHD (0.33 mg/dL [0.27, 0.40] lower). There were no clinically meaningful associations between dialysis modalities and concentrations of calcium or ALP. CONCLUSION: In incident dialysis patients, compared to treatment with conventional in-center hemodialysis, treatments with other dialysis modalities with longer treatment times or higher frequency were associated with different patterns of serum phosphate and PTH. Given the recent growth in the use of dialysis modalities other than hemodialysis, the associations between the treatment and the CKD-MBD markers warrant additional study.

Conceptualizing, Contextualizing, and Operationalizing Race in Quantitative Health Sciences Research.

Differences in health outcomes across racial groups are among the most commonly reported findings in health disparities research. Often, these studies do not explicitly connect observed disparities to mechanisms of systemic racism that drive adverse health outcomes among racialized and other marginalized groups in the United States. Without this connection, investigators inadvertently support harmful narratives of biologic essentialism or cultural inferiority that pathologize racial identities and inhibit health equity. This paper outlines pitfalls in the conceptualization, contextualization, and operationalization of race in quantitative population health research and provides recommendations on how to appropriately engage in scientific inquiry aimed at understanding racial health inequities. Race should not be used as a measure of biologic difference, but rather as a proxy for exposure to systemic racism. Future studies should go beyond this proxy use and directly measure racism and its health impacts.VISUAL ABSTRACTAppeared as Annals "Online First" article.

Performance of diagnostic coding and laboratory testing results to measure COVID-19 during pregnancy and associations with pregnancy outcomes.

BACKGROUND: Large-scale evaluation of COVID-19 is likely to rely on the quality of ICD coding. However, little is known about the validity of ICD-coded COVID-19 diagnoses. OBJECTIVES: To evaluate the performance of diagnostic codes in detecting COVID-19 during pregnancy. METHODS: We used data from a national cohort of 78,283 individuals with a pregnancy ending between 11 March 2020 and 31 January 2021 in the OptumLabs® Data Warehouse (OLDW). OLDW is a longitudinal, real-world data asset with de-identified administrative claims and electronic health record data. We identified all services with an ICD-10-CM diagnostic code of U07.1 and all laboratory claims records for COVID-19 diagnostic testing. We compared ICD-coded diagnoses to testing results to estimate positive and negative predictive values (PPV and NPV). To evaluate impact on risk estimation, we estimated risk of adverse pregnancy outcomes by source of exposure information. RESULTS: Of 78,283 pregnancies, 5644 had a laboratory test result for COVID-19. Testing was most common among older individuals, Hispanic individuals, those with higher socioeconomic status and those with a diagnosed medical condition or pregnancy complication; 52% of COVID-19 cases was identified through ICD-coded diagnosis alone, 19% from laboratory test results alone and 29% from both sources. Agreement between ICD-coded diagnosis and laboratory testing records was high 91% (95% confidence interval [CI] 90, 92). However, the PPV of ICD-code diagnosis was low (36%; 95% CI 33, 39). We observed up to a 50% difference in risk estimates of adverse pregnancy outcomes when exposure was based on laboratory testing results or diagnostic coding alone. CONCLUSIONS: More than one-in-five COVID-19 cases would be missed by using ICD-coded diagnoses alone to identify COVID-19 during pregnancy. Epidemiological studies exclusively relying on diagnostic coding or laboratory testing results are likely to be affected by exposure misclassification. Research and surveillance should draw upon multiple sources of COVID-19 diagnostic information.

Cohort Study and Bias Analysis of the Obesity Paradox Across Stages of Chronic Kidney Disease.

OBJECTIVE: In advanced chronic kidney disease (CKD), patients with obesity often have better outcomes than patients without obesity, often called the 'obesity paradox'. Yet, in CKD, the prevalence of inflammation increases as CKD progresses. Although a potential confounder, inflammation may be left unaccounted in obesity-mortality studies. We examined the associations of body mass index (BMI) with all-cause and cause-specific mortality across CKD stages, with consideration for uncontrolled confounding due to unmeasured inflammation. METHODS: We investigated 2,703,512 patients with BMI data between 2004 and 2006. We used Cox models to examine the associations of BMI with all-cause, cardiovascular, and cancer mortality, (ref: BMI 25-<30 kg/m2), adjusted for clinical characteristics and stratified by CKD stages. To address uncontrolled confounding, we performed bias analysis using a weighted probabilistic model of inflammation given the observed data applied to weighted Cox models. RESULTS: The cohort included 5% females and 14% African Americans. In adjusted analyses, the associations of the BMI with all-cause and cardiovascular mortality showed a reverse J-shape, where a higher BMI (>40 kg/m2) was associated with a higher risk. Conversely, a lower mortality risk was observed with a BMI 30-<35 kg/m2 across all CKD stages and for BMI >40 kg/m2 in CKD stage 4/5. Cancer mortality analyses showed an inverse relationship. Bias analysis for uncontrolled confounding suggested that independent of inflammation, the obesity paradox was present. CONCLUSION: We observed the presence of the obesity paradox in this study. This association was consistent in advanced CKD and in our bias analysis, suggesting that inflammation may not fully explain the observed BMI-mortality associations including in patients with CKD.

Behavioral Problems at Age 11 Years After Prenatal and Postnatal Exposure to Acetaminophen: Parent-Reported and Self-Reported Outcomes.

Several studies have reported associations between prenatal acetaminophen exposure and behavioral outcomes in young children. We aimed to evaluate the associations of prenatal and postnatal exposures to acetaminophen with behavioral problems in children at age 11 years, using behavioral measures reported by parents and children. We studied 40,934 mother-child pairs from the Danish National Birth Cohort enrolled during 1996-2002. Parent-reported and child-reported Strengths and Difficulties Questionnaire (SDQ) responses were collected during the 11-year follow-up. We estimated risk ratios for behavioral problems including total difficulties as well as internalizing or externalizing behaviors following prenatal (during pregnancy) or postnatal (within the first 18 months after birth) acetaminophen exposure. Parent-reported and child-reported SDQ scores were moderately correlated; higher for externalizing (r = 0.59) than internalizing (r = 0.49) behaviors. Prenatal acetaminophen exposure was associated with 10%-40% higher risks for total difficulties and internalizing and externalizing problems based on parent- or child-reported SDQ, with the association being stronger for greater cumulative weeks of acetaminophen use. Postnatal exposure was associated with 16%-19% higher risks for parent-reported internalizing behaviors, but the associations were weak or null for child-reported scores except for prosocial behavior. Our study corroborates published associations between prenatal exposures to acetaminophen and behavioral problems and extends the literature to early adolescence.

Optimal uses of pooled testing for COVID-19 incorporating imperfect test performance and pool dilution effect: An application to congregate settings in Los Angeles County.

INTRODUCTION: Pooled testing is a potentially efficient alternative strategy for COVID-19 testing in congregate settings. We evaluated the utility and cost-savings of pooled testing based on imperfect test performance and potential dilution effect due to pooling and created a practical calculator for online use. METHODS: We developed a 2-stage pooled testing model accounting for dilution. The model was applied to hypothetical scenarios of 100 specimens collected during a one-week time-horizon cycle for varying levels of COVID-19 prevalence and test sensitivity and specificity, and to 338 skilled nursing facilities (SNFs) in Los Angeles County (Los Angeles) (data collected and analyzed in 2020). RESULTS: Optimal pool sizes ranged from 1 to 12 in instances where there is a least one case in the batch of specimens. 40% of Los Angeles SNFs had more than one case triggering a response-testing strategy. The median number (minimum; maximum) of tests performed per facility were 56 (14; 356) for a pool size of 4, 64 (13; 429) for a pool size of 10, and 52 (11; 352) for an optimal pool size strategy among response-testing facilities. The median costs of tests in response-testing facilities were $8250 ($1100; $46,100), $6000 ($1340; $37,700), $6820 ($1260; $43,540), and $5960 ($1100; $37,380) when adopting individual testing, a pooled testing strategy using pool sizes of 4, 10, and optimal pool size, respectively. CONCLUSIONS: Pooled testing is an efficient strategy for congregate settings with a low prevalence of COVID-19. Dilution as a result of pooling can lead to erroneous false-negative results.

Use of Data to Understand the Social Determinants of Depression in Two Middle-Income Countries: the 3-D Commission.

Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression.This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y).Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government's outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators.

Data Sources for Understanding the Social Determinants of Health: Examples from Two Middle-Income Countries: the 3-D Commission.

The expansion in the scope, scale, and sources of data on the wider social determinants of health (SDH) in the last decades could bridge gaps in information available for decision-making. However, challenges remain in making data widely available, accessible, and useful towards improving population health. While traditional, government-supported data sources and comparable data are most often used to characterize social determinants, there are still capacity and management constraints on data availability and use. Conversely, privately held data may not be shared. This study reviews and discusses the nature, sources, and uses of data on SDH, with illustrations from two middle-income countries: Kenya and the Philippines. The review highlights opportunities presented by new data sources, including the use of big data technologies, to capture data on social determinants that can be useful to inform population health. We conducted a search between October 2010 and September 2020 for grey and scientific publications on social determinants using a search strategy in PubMed and a manual snowball search. We assessed data sources and the data environment in both Kenya and the Philippines. We found limited evidence of the use of new sources of data to study the wider SDH, as most of the studies available used traditional sources. There was also no evidence of qualitative big data being used. Kenya has more publications using new data sources, except on the labor determinant, than the Philippines. The Philippines has a more consistent distribution of the use of new data sources across the HEALTHY determinants than Kenya, where there is greater variation of the number of publications across determinants. The results suggest that both countries use limited SDH data from new data sources. This limited use could be due to a number of factors including the absence of standardized indicators of SDH, inadequate trust and acceptability of data collection methods, and limited infrastructure to pool, analyze, and translate data.