Population-averaged Model Research Articles

Understanding the influence of surgical parameters on craniofacial surgery outcomes: a computational study.

Sagittal craniosynostosis (SC) is a congenital condition whereby the newborn skull develops abnormally owing to the premature ossification of the sagittal suture. Spring-assisted cranioplasty (SAC) is a minimally invasive surgical technique to treat SC, where metallic distractors are used to reshape the newborn's head. Although safe and effective, SAC outcomes remain uncertain owing to the limited understanding of skull-distractor interaction and the limited information provided by the analysis of single surgical cases. In this work, an SC population-averaged skull model was created and used to simulate spring insertion by means of the finite-element analysis using a previously developed modelling framework. Surgical parameters were varied to assess the effect of osteotomy and spring positioning, as well as distractor combinations, on the final skull dimensions. Simulation trends were compared with retrospective measurements from clinical imaging (X-ray and three-dimensional photogrammetry scans). It was found that the on-table post-implantation head shape change is more sensitive to spring stiffness than to the other surgical parameters. However, the overall end-of-treatment head shape is more sensitive to spring positioning and osteotomy size parameters. The results of this work suggest that SAC surgical planning should be performed in view of long-term results, rather than immediate on-table reshaping outcomes.

RECEIPT OF GENDER-AFFIRMING SURGERY AMONG MEDICARE BENEFICIARIES

Abstract While transgender and gender diverse (TGD) people may never seek treatment related to their gender identity, many require access to gender-affirming treatments, including surgery. Starting in 2014, Medicare began covering gender-affirming surgery (GAS) on a case-by-case basis. In this study, we use national Medicare data to compare receipt of GAS by beneficiary characteristics. We classified TGD beneficiaries using an algorithm that combines diagnosis and procedure codes. Our study compared characteristics for all TGD identified beneficiaries and those who received GAS using a population-averaged logistic model using a generalized estimating equation (GEE) adjusting for dual status, age group, race/ethnicity, original reason for entitlement, and CMS region. Our sample accounted for 49,945 observations for 11,162 individuals, with a total of 290 identified records of GAS. In our adjusted analysis, we found that TGD beneficiaries in certain parts of the country had lower odds of GAS compared to their counterparts. Compared to CMS Region 1 (which includes Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont), those living in Region 3 (Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia), Region 4 (Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, and Tennessee), and Region 6 (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas) had a significantly lower odds of receiving GAS. Access to gender-affirming care may be influenced by CMS regional contractors, as well as state-by-state variation in Medicaid coverage for gender-affirming care. Further research is needed to explain why beneficiaries may have lower access to GAS to inform policy recommendations.

Audit committee characteristics, external audit quality, board diversity and firm performance: evidence from SAARC nation

Purpose The purpose of this study is to investigate the association between three corporate governance (CG) idiosyncrasies, namely audit committee characteristics, external audit quality (AQ), board diversity and firm performance (FP) in the South Asian Association for Regional Cooperation (SAARC) nations.Design/methodology/approach The study used a sample of 200 listed nonfinancial firms in the SAARC nations from 2012 to 2021. The System Generalized Method of Moment model was applied to the data consisting of 2000 firm-year observations. The Generalized Estimating Equation population-averaged model was also employed for added robustness. The study employed Tobin's Q as the measure of FP.Findings The findings revealed that amongst the CG variables tested, external AQ exhibited a significantly positive relationship with Tobin's Q. Significant negative influences on FP have been demonstrated by the variables of audit committee meeting and board's independence. Furthermore, gender diversity, CEO duality, audit committee strength and independence failed to record any significant association.Originality/value This study is one of the first to investigate the association between CG idiosyncrasies and FP in the SAARC nations. The study findings have important implications for policymakers and regulators in the region.

Impact of energy depletion, human development, and income distribution on natural resource sustainability

Constant exploitation of natural resources has resulted from the industrialization and urbanization of society. One of the possible causes of the COVID-19 pandemic is an ecological disturbance caused by excessive resource exploitation. Countries worldwide have taken precautionary measures to limit the spread of this disease because of its highly infectious nature: lockdowns, quarantines, curfews, etc. This paper explores the impacts of energy depletion and the human development index on natural resources, considering the roles of CO2 emissions and economic growth in China from 1971 to 2019. We apply advanced economic modeling using the Phillips-Ouliaris test for integration, Gaussian identity mixed-effects Generalized Linear Model, and Robust GEE population-averaged model for long-run estimates. Results explain that CO2 emissions and economic growth devalue natural resources, while the human development index and energy depletion increase them. Depletion of natural resources occurs due to overexploitation and overuse of natural resources, as well as unsustainable planning and waste. In the case of natural resources that man uses to make other resources, such as dams, roads, sports complexes, etc., these are considered human-made resources. It is, therefore, essential to develop human resources as a part of the natural resource development process. Research limitations and future directions are discussed.

A comparison of perinatal outcomes following fresh blastocyst or cleavage stage embryo transfer in singletons and twins and between singleton siblings.

Are perinatal outcomes following fresh blastocyst versus fresh cleavage stage embryo transfer (ET) different in singletons, twins, and between singleton siblings? Singleton babies conceived following fresh blastocyst, versus cleavage stage, ET are less likely to be small for gestational age (SGA) or to have a congenital anomaly (a result confirmed by comparing singleton siblings), while singletons born following fresh blastocyst ET were at a higher risk of being large for gestational age (LGA) than their sibling born following fresh cleavage stage ET. Blastocyst stage transfer is now the preferred strategy in most IVF units. Previous studies have suggested that babies conceived through blastocyst transfer are at increased risk of preterm birth and LGA. A national population-based retrospective cohort study was performed using linked Human Fertilisation and Embryology Authority (HFEA) data on 130 516 IVF and ICSI livebirths occurring from 103 062 women between 2000 and 2017. We included women who had at least one singleton livebirth resulting from IVF/ICSI fresh embryo treatment, using their own eggs and partner's sperm. A linked HFEA dataset was analysed using a multilevel framework, which accommodated repeated IVF cycles resulting in livebirths in the same woman. A population-averaged robust Poisson model was used for binary outcomes and a multinomial logistic regression model was used for categorical outcomes. Unadjusted and adjusted risk ratios (aRRs) (95% CI) were calculated. There were 130 516 livebirths in 103 062 women, including 86 630 singletons, 43 886 twin births, and 5384 pairs of singleton siblings. In comparison with fresh cleavage stage ET, fresh blastocyst stage transfer in singletons was associated with a lower risk of low birthweight (aRR = 0.92; 95% CI 0.86, 0.99), lower risk of being SGA (0.83; 0.78, 0.89), and lower risk of congenital anomaly (0.79; 0.71, 0.89). This analysis did not show an increase in risk associated with preterm birth (1.00; 0.94, 1.06), high birthweight (0.99; 0.93, 1.06), LGA (0.99; 0.93, 1.05), and the chance of healthy singleton baby (1.00; 1.00, 1.02). Twins resulting from fresh blastocyst stage ET were at slightly higher risk of preterm birth (1.05; 1.02, 1.10) compared with twins conceived following fresh cleavage stage ET. There was insufficient evidence for an association with the other perinatal outcomes. Singleton siblings born following fresh blastocyst stage ET were at a higher risk of being LGA (1.57; 1.01, 2.46) and at lower risk of having a congenital anomaly (0.52; 0.28, 0.97) compared to their singleton siblings born following cleavage stage ET. There was some evidence of excess risk of preterm birth (1.42; 0.97, 2.23) associated with blastocyst stage transfer. However, we could not confirm an association between blastocyst stage ET and low birthweight (1.35; 0.81, 2.27), high birthweight (1.19; 0.80, 1.77), and the chance of being a healthy baby (0.97; 0.86, 1.09). This was an observational study where we were unable to adjust for some key confounders, such as maternal smoking status and BMI, which may change from one pregnancy to another and are not recorded in the HFEA dataset. In the largest study of its kind, our analysis of singleton siblings, corrected for unmeasured, non-time varying maternal factors, confirms the previously reported association between blastocyst transfer and LGA babies, and shows a reduced risk of congenital anomaly following blastocyst transfer. Our sibling analysis did not confirm a decreased risk of low birthweight following blastocyst transfer. Overall, absolute risks are low and there is insufficient evidence to challenge the practice of extended culture of embryos. This project is financed by an NHS Grampian Endowment Research Grant, project number 17/052. One of the authors, S.B., was the Editor in Chief of HROpen until 31 December 2022 and would have been in that role when the paper was first submitted. As an invited speaker, S.B. has received travel expenses, accommodation and honoraria from Merck, Organon, and Ferring. A.M. has received travel expenses, accommodation, and honoraria from Merck Serono, Cook Medical, Pharmasure, Gedeon Richter, and Ferring. D.J.M. is currently a HROpen Associate Editor. N/A.

Meaningful Signals or Cheap Talk - Do Gender Targets Affect Employees’ Perceptions of Equality?

We investigate whether gender targets set by firms are associated with employees’ perceptions of equality. To conduct our quantitative empirical study, we deploy a unique dataset of 38,460 employee reviews recorded from 2016 to 2020 for 68 German firms that reported gender targets for their executive boards. We carry out statistical analyses constructing a GEE population-averaged model. Our results suggest that gender targets are only associated with higher levels of perceived equality among employees if ambitions exceed a ratio of 1:7 and are followed by a female appointment. Meanwhile, we find that irrespective of target setting, female executive board representation is positively associated with employees’ equality perceptions. We contribute to research on gender policy by providing a first quantitative study on equality perceptions following gender target setting.

Exploring Overweight Risk Trajectories During Childhood and Their Associations With Elevated Blood Pressure at Late Adolescence: a Retrospective Cohort Study.

Overweight during childhood is significantly associated with higher risk of high blood pressure (HBP) in later life. However, recognition of critical intervention period is limited. We aimed to analyze the changes in overweight risk during school-age and its relationship with HBP. Seventeen thousand eight hundred sixteen school-aged children (53.9% boys) with a mean follow-up time of 8.2 years were involved. Children's overweight was defined as body mass index Z score ≥1 and was fitted with a group-based trajectory model. The 4 trajectories were labeled as constant low, high decreasing, low rising, and constant high according to the change of overweight risk during follow-up. Population-averaged logit model and log-binomial regression models were used to analyze HBP risk. Cox proportional hazard model was used to analyze the HBP incidence among distinct groups. Children with higher overweight risk generally had higher HBP risk during follow-up. However, the HBP risk in low rising group was low at baseline and increased to 3.14 (95% CI, 2.54-3.88; P<0.001) for boys and 3.23 (95% CI, 2.08-5.01; P=0.004) for girls at end point, which were comparable to the relative risk in the constant high group (4.60 [95% CI, 4.02-5.27] for boys and 5.28 [95% CI, 3.94-7.07] for girls). Findings of this study provide insights on patterns of overweight risks during childhood. Children with transition from normal to overweight during teen years would be high-risk in HBP incidence.

Area level deprivation and monthly COVID-19 cases: The impact of government policy in England

This paper aims to understand the relationship between area level deprivation and monthly COVID-19 cases in England in response to government policy throughout 2020. The response variable is monthly reported COVID-19 cases at the Middle Super Output Area (MSOA) level by Public Health England, with Index of Multiple Deprivation (IMD), ethnicity (percentage of the population across 5 ethnicity categories) and the percentage of the population older than 70 years old and time as predictors. A GEE population-averaged panel-data model was employed to model trends in monthly COVID-19 cases with the population of each MSOA included as the exposure variable. Area level deprivation is significantly associated with COVID-19 cases from March 2020; however, this relationship is reversed in December 2020. Follow up analysis found that this reversal was maintained when controlling for the novel COVID-19 variant outbreak in the South East of England. This analysis indicates that changes in the role of deprivation and monthly reported COVID-19 over time cases may be linked to two government policies: (1) the premature easing of national restrictions in July 2020 when cases were still high in the most deprived areas in England and (2) the introduction of a regional tiered system in October predominantly in the North of England. The analysis adds to the evidence showing that deprivation is a key driver of COVID-19 outcomes and highlights the unintended negative impact of government policy.

Early-life disease environment and adult height in historical populations.

Nutrition and the incidence of diseases during early life are considered environmental factors that determine people's height when they become adults. While there is extensive literature focusing on the relationship between physical growth, general mortality and infant mortality rates, few studies analyse the impact of certain disease groups on the final height of historical populations. Using regional mortality rates by causes of death, the main objective of this study is to determine the onset of the disease environment during early life for populations born in Spain between 1916 and 1930, and its relationship with the stature reached at 21 years of age. A population-averaged model is performed on epidemic-infectious, gastrointestinal, and congenital diseases during the gestation period and first year of life. The disease burden in early life had a statistically significant negative effect on adult stature. These results support the premise that an improvement in the disease environment could lead to a greater number of short children surviving and therefore a decrease in the average height.

GEECORR: A SAS macro for regression models of correlated binary responses and within-cluster correlation using generalized estimating equations

Background and objectives: Generalized estimating equations (GEE) provide population-averaged model inference for longitudinal and clustered outcomes via a generalized linear model for the effect of explanatory variables on the marginal mean, while intra-cluster correlations are ordinarily treated as nuisance parameters. Software to richly parameterize and conduct inference for complex correlation structures in the marginal modeling framework is scarce.Methods: A SAS macro, GEECORR, has been developed for the analysis of clustered binary data based on GEE to include additional estimating equations for modeling pairwise correlation between binary variates as a function of covariates.Results: We illustrate the macro in a surveillance study with repeated measures, a longitudinal study, and a study with biological clustering.Conclusions: This article provides an overview of the GEE method consisting of a pair of estimating equations, describes the features and capabilities of the GEECORR macro including regression diagnostics and finite-sample bias-corrected covariance estimators, and demonstrates the macro usage for three studies.

Prospective associations between physical activity and BMI with irregular periods and heavy menstrual bleeding in a large cohort of Australian women.

Are physical activity (PA) and body mass index (BMI) associated with irregular periods and heavy menstrual bleeding (HMB) in Australian women? Overweight and obese women have higher odds of both irregular periods and HMB than underweight/normal-weight women, but high levels of PA reduce the odds of HMB. Most studies on relationships between PA and menstrual problems have focused on female athletes, but there have been few population-based studies. Prospective cohort study, 10618 participants in the Australian Longitudinal Study of Women's Health (ALSWH) who completed mailed surveys in 1996, with follow-ups in 2000, 2003, 2006, 2009, 2012, and 2015. Participants were aged 22 to 27 in 2000. They were asked to report their PA levels and the frequency of irregular periods and HMB in each survey. BMI was calculated at every survey from self-reported weight and height. Generalised estimating equation population-averaged model analyses were conducted to calculate odds ratios (OR) and 95% confidence intervals (95% CIs). At age 22 to 27 years, the prevalence of irregular periods was 19.4%. This remained stable over 15 years. There were no associations between PA and irregular periods. Overweight and obese women had higher odds of irregular periods [overweight: OR 1.08, (95% CI 1.00-1.17); obese: OR 1.29, (95%CI 1.18-1.41)] than women who were underweight/normal weight.The prevalence of HMB at age 22-27 years was 15.9%; this doubled over 15 years. Women who were highly active had 10% lower odds of HMB than women who reported no PA [OR 0.90, (95%CI 0.82-0.98)]. Overweight and obese women had higher odds of HMB [overweight: OR 1.15, (95%CI 1.07-1.23); obese: OR 1.37, (95%CI 1.26-1.49)] than women who were underweight/normal weight. Among obese women, high levels of PA were associated with 19% [OR 0.81, (95%CI 0.68-0.97)] reduction in the odds of HMB. Data collected in the ALSWH are self-reported, which may be subject to recall bias. Reverse causation, due to menstrual problems impacting PA, is possible although sensitivity analyses suggest this is unlikely to have affected the results. Other conditions, e.g., polycystic ovary syndrome, for which no or incomplete data were available, could have affected the results. Intervention studies are needed to assess the effect of increasing PA in women with HMB, but these preliminary findings suggest that promoting PA could be an affordable and feasible strategy for reducing HMB in young adult women. The ALSWH is funded by the Australian Government. Funding for these analyses was provided by a University of Queensland (UQ) International Postgraduate Research Scholarship and a UQ International Development Fellowship. The authors declare no conflicts of interest. N/A.

How do income inequality and fiscal consolidation impact on banking crises? A post-Keynesian view

This is the first paper in estimating a population-averaged panel logit probability model to test the importance of the interaction between deficit in the public budgeting and income inequality in banking crises, for 36 developed countries from 1961-2011. New empirical evidence is shown on whether rising inequality is linked with financial crises, corroborating theoretical expectations of post-Keynesian authors. Policy measures are provided and tested empirically: whilst in general terms higher levels of income inequality could be associated with financial crises; countries with high levels of income inequality could reduce the likelihood of a crisis better in a context of fiscal consolidation. One reason could be that governments could use this public surplus for reducing income inequality, which helps to reduce defaults and banking crises. These results could be useful for academics, and policy-makers.

The Impact of Continuity of Care on Cervical Cancer Screening: How Visit Pattern Affects Guideline Concordance.

Cervical cancer can be prevented and highly curable if detected early. Current guidelines recommend women to receive cervical cancer screening starting at age 21. Our study aims to investigate how improving continuity of care (COC) may influence guideline concordance of cervical cancer screening. Using the eligibility and claims data, we created a person-month panel data set for women who were enrolled in Oregon Medicaid for at least 80% of the period from 2008 to 2015. We then selected our study cohort following the cervical cancer screening guidelines. Our dependent variable is whether a woman received cervical cancer screening concordant with guidelines in a given month, when she did not receive Pap test in the past 36months and did not receive co-testing of HPV test plus Pap test in the past 60months. We used both population-averaged logit model and conditional fixed-effect logit model to estimate the association between the guideline concordance and the COC index, after controlling for high risk, pregnancy, age, race, and ethnicity. A total of 466,526 person-month observations were included in our main models. A 0.1 unit increase of the COC score was significantly associated with a decrease in the odds of receiving guideline-concordant cervical cancer screening (population-averaged logit model: OR = 0.988, p < .001; conditional fixed-effect logit model: OR = 0.966, p < .001). Our findings remain robust to a series of sensitivity analyses. A better COC may not be necessarily beneficial to improving cervical cancer prevention. Educations for both physicians and patients should be supplemented to assure quality of preventive care.

Characteristics of older adults predict concern about stopping medications

ObjectiveTo predict the association between demographic, psychological, and medication-specific characteristics and the level of concern about stopping medications among older adults. DesignCross-sectional study in which participants read 6 vignettes in which a primary care provider broached the idea of stopping a medication. Medications differed in risk, regulatory status, and indication for discontinuation. Setting and participantsNational Web-based survey distributed to adults aged 65 years or older by Dynata in January 2019. Outcome measuresParticipants reported their concern about stopping each medication (7-point scale, not at all to extremely), their preferences for more versus less care (Medical Maximizer-Minimizer Scale, MMS), medication attitudes (Beliefs about Medicines Questionnaire, BMQ), demographic characteristics, and health literacy. We used a generalized estimating equations population-averaged model to examine characteristics associated with concern about stopping medications among all the vignettes and linear regressions to explore levels of concern for individual vignettes. Regressions included the MMS, BMQ, health literacy, and demographics. ResultsA total of 942 individuals started the survey, and 823 were included in our analysis. Approximately one-half of participants (range: glyburide, 49.5% to aspirin, 56.0%) reported substantial concern (≥ 4 on a 1–7 scale) about stopping each medication. Characteristics that significantly increased concern about stopping medications included female gender, identifying as black or African American, higher MMS score, and higher BMQ specific score. Higher MMS score predicted increased concern about stopping medications for each of the 6 medications. ConclusionCharacteristics of older adults (e.g., medical maximizing-minimizing preferences), as opposed to medication-specific characteristics, predict concern about stopping medications.

Disentangling the behavioural variability of confined cell migration

Cell-to-cell variability is inherent to numerous biological processes, including cell migration. Quantifying and characterizing the variability of migrating cells is challenging, as it requires monitoring many cells for long time windows under identical conditions. Here, we observe the migration of single human breast cancer cells (MDA-MB-231) in confining two-state micropatterns. To describe the stochastic dynamics of this confined migration, we employ a dynamical systems approach. We identify statistics to measure the behavioural variance of the migration, which significantly exceeds that predicted by a population-averaged stochastic model. This additional variance can be explained by the combination of an ‘ageing’ process and population heterogeneity. To quantify population heterogeneity, we decompose the cells into subpopulations of slow and fast cells, revealing the presence of distinct classes of dynamical systems describing the migration, ranging from bistable to limit cycle behaviour. Our findings highlight the breadth of migration behaviours present in cell populations.

The Effect of Left Ventricular Assist Devices (LVAD) on Pulmonary Hypertension: A Single Center Review

Purpose Recently published case series have demonstrated that long-term LVAD support may reverse pulmonary hypertension in end-stage heart failure. This study's purpose was to review our local experience through right-heart catheterization follow-up of LVAD patients. Methods Patients were identified through the local VAD coordinator and our perioperative surgical database. Pre- and peri-operative data were captured from our database while catheterization data were gathered from electronic records. Pulmonary hypertension was defined as having a pre-implant mean pulmonary artery (PA) pressure >25 mmHg. Hemodynamics were captured from 1 year prior to LVAD insertion to loss of follow-up or death. A population-averaged panel-data model using generalized estimating equation (GEE) was used to determine the effects of pre-operative variables on longitudinal pulmonary hemodynamics . Results From 2004 to 2018, 95 patients underwent LVAD implantation at our institution. Hemodynamics were available on 72 of these patients, of which 52 had pre-operative pulmonary hypertension. Average follow-up was 697±574 days. Mean PA pressures over time are represented in Figure 1. Most had normalization of their PA pressures following LVAD implantation and this process occurred within the first year in the majority of patients. Following GEE model fitting, no pre-operative variables appeared to affect post-operative PA pressures significantly, including whether the patient was diagnosed with pulmonary hypertension prior to LVAD implantation. Cardiac risk factors as well as pre-operative ejection fraction also did not appear to significantly affect changes in post-operative PA pressures. Conclusion In this single-center retrospective analysis, LVAD implantation appeared to lower pulmonary artery pressures in patients with end-stage heart failure. The development of pre-operative pulmonary hypertension and other cardiac risk factors did not appear to significantly affect this process.

Evaluating elbow osteoarthritis within the prehistoric Tiwanaku state using generalized estimating equations (GEE).

Studies of osteoarthritis (OA) in human skeletal remains can come with scalar problems. If OA measurement is noted as present or absent in one joint, like the elbow, results may not identify specific articular pathology data and the sample size may be insufficient to address research questions. If calculated on a per data point basis (i.e., each articular surface within a joint), results may prove too data heavy to comprehensively understand arthritic changes, or one individual with multiple positive scores may skew results and violate the data independence required for statistical tests. The objective of this article is to show that the statistical methodology Generalized Estimating Equations (GEE) can solve scalar issues in bioarchaeological studies. Using GEE, a population-averaged statistical model, 1,195 adults from the core and one colony of the prehistoric Tiwanaku state (AD 500-1,100) were evaluated bilaterally for OA on the seven articular surfaces of the elbow joint. GEE linked the articular surfaces within each individual specimen, permitting the largest possible unbiased dataset, and showed significant differences between core and colony Tiwanaku peoples in the overall elbow joint, while also pinpointing specific articular surfaces with OA. Data groupings by sex and age at death also demonstrated significant variation. A pattern of elbow rotation noted for core Tiwanaku people may indicate a specific pattern of movement. GEE is effective and should be encouraged in bioarchaeological studies as a way to address scalar issues and to retain all pathology information.

Abstract 17266: Right Atrial Volumes Changes in Tetralogy of Fallot

Introduction &amp; Hypothesis: There is limited information on right atrial (RA) function in the congenital heart defects. RA volume and function may give insight into the right ventricle (RV) diastolic function. We sought to assess RA function in tetralogy of Fallot (TOF) patients prior to and after complete surgical repair. Methods: Infants with TOF prior to complete repair were included for retrospective chart review and offline analysis of 2-dimensional echocardiograms (echo) before and after surgical repair. RA phasic volumes and stroke volumes were calculated. All volumes were indexed to body surface area. Results: There were 40 infants with TOF (45% females), of which 70% had pulmonary stenosis, 30% pulmonary atresia. Roughly 85% and 60% had 3, or more, echo available pre- and postoperatively. Table 1 (attached) shows the patient characteristics and phasic RA volumes. The indexed RA phasic volumes were in normal range in initial echo prior to surgery. We used normal index RA phasic volumes published by European Society of Echocardiography. There was the increasing trend of indexed RA phasic volume on follow up echo immediately before TOF repair. These phasic volumes continued to remain elevated after complete surgical repair (Table 1). Trends in RA stroke volumes for all available echos before and after surgery were modeled using a population-averaged model with an exchangeable within-panel correlation structure (Figure 2), showing no statistically significant difference after surgery. But there was statistical significance noted in RA ejection fraction. Please see attached image for statistical analysis and results of the study. Conclusions: The indexed RA phasic volumes in children with TOF are normal initially and increases before TOF repair and it continued to increase after TOF repair. The increase RA phasic volumes suggest RV diastolic dysfunction similar to the findings of LA phasic volumes and left ventricular diastolic dysfunction. Our findings indicate slow worsening RV diastolic function in patients with TOF after surgical repair. RA volume and function can be the novel marker to diagnose and monitor right ventricular diastolic dysfunction.

A population-averaged approach to diagnostic test meta-analysis.

The meta-analysis of diagnostic accuracy studies is often of interest in screening programs for many diseases. The typical summary statistics for studies chosen for a diagnostic accuracy meta-analysis are often two dimensional: sensitivities and specificities. The common statistical analysis approach for the meta-analysis of diagnostic studies is based on the bivariate generalized linear-mixed model (BGLMM), which has study-specific interpretations. In this article, we present a population-averaged (PA) model using generalized estimating equations (GEE) for making inference on mean specificity and sensitivity of a diagnostic test in the population represented by the meta-analytic studies. We also derive the marginalized counterparts of the regression parameters from the BGLMM. We illustrate the proposed PA approach through two dataset examples and compare performance of estimators of the marginal regression parameters from the PA model with those of the marginalized regression parameters from the BGLMM through Monte Carlo simulation studies. Overall, both marginalized BGLMM and GEE with sandwich standard errors maintained nominal 95% confidence interval coverage levels for mean specificity and mean sensitivity in meta-analysis of 25 of more studies even under misspecification of the covariance structure of the bivariate positive test counts for diseased and nondiseased subjects.

Country-level analysis of household fuel transitions

Abstract Solid fuel combustion remains a dominant energy source for household heating and cooking in less developed countries. As a result, almost three billion people are exposed to household air pollution, causing four million premature deaths annually, primarily among poor women and children. We analyze data from Demographic and Health Surveys in 69 countries to identify determinants of transition from solid to cleaner fuel. Estimates from a population-averaged linear model show that population density and size, rural population share, income inequality, and charcoal production are positively associated with countries’ solid fuel use, while GDP per capita, electricity and natural gas production have the opposite effect. Economic development, measured as GDP per capita, has the strongest link to solid fuel use: a standard deviation increase in per capita GDP above its mean reduces solid fuel use from 70% to 57% of households. Electricity production is another strong predictor: solid fuel use drops by 11% when electricity production increases by one standard deviation above the mean. In addition, in a fixed-effects linear model, population size has a positive association with solid fuel use, while increases in GDP per capita and the number of governments’ renewable energy incentives are associated with lower dependence on solid fuels.