Pregnancy Outcomes in Living Kidney Donors: Protocol of a Population-Based Cohort Study in Three Canadian Provinces.

Background: A substantial proportion of living kidney donors are women of childbearing age. Some prior studies report a higher risk of gestational hypertension and pre-eclampsia in living kidney donors compared with nondonors. Further research is needed to better quantify the risk of adverse maternal, fetal/infant, and neonatal outcomes attributable to living kidney donation. Objective: To determine the risk of hypertensive disorders of pregnancy, including gestational hypertension, pre-eclampsia, and eclampsia, and other maternal and fetal/infant outcomes in living kidney donors compared with a matched group of nondonors of similar baseline health. Design and Setting: Protocol for a population-based, matched cohort study using Canadian administrative health care databases. The protocol will be run separately in 3 provinces, Ontario, Alberta, and British Columbia, and results will be combined statistically using meta-analysis. Participants: The cohort will include women aged 18 to 48 years who donated a kidney between July 1992 and March 2022 and had at least one postdonation singleton pregnancy of ≥20 weeks gestation between January 1993 and February 2023. We expect to include at least 150 living kidney donors with over 200 postdonation pregnancies from Ontario and a similar number of donors and pregnancies across Alberta and British Columbia combined. Nondonors will include women from the general population with at least one pregnancy of ≥20 weeks gestation between January 1993 and February 2023. Nondonors will be randomly assigned cohort entry dates based on the distribution of nephrectomy dates in donors. The sample of nondonors will be restricted to those aged 18 to 48 years on their cohort entry dates with delivery dates at least 6 months after their assigned entry dates. A concern with donor and nondonor comparisons is that donors are healthier than the general population. To reduce this concern, we will also apply 30+ exclusion criteria to further restrict the nondonor group so that they have similar health measures at cohort entry as the donors. Donor and nondonor pregnancies will then be matched (1:4) on 5 potential confounders: delivery date, maternal age at delivery date, time between cohort entry and delivery date, neighborhood income quintile, and parity at delivery date. Measurements: The primary outcome will be a composite of maternal gestational hypertension, preeclampsia, or eclampsia. Secondary maternal outcomes will include components of the primary outcome, early pre-eclampsia, severe maternal morbidity, cesarean section, postpartum hemorrhage, and gestational diabetes. Fetal/infant/neonatal outcomes will include premature birth/low birth weight, small for gestational age, neonatal intensive care unit admission, stillbirth, and neonatal death. Methods: The primary unit of analysis will be the pregnancy. We will compute the risk ratio of the primary composite outcome in donors versus nondonors using a log-binomial mixed regression model with random effects to account for the correlation within women with multiple pregnancies and within matched sets of donors and nondonors. We will perform the statistical analyses within each province and then combine aggregated results using meta-analytic techniques to produce overall estimates of the study outcomes. Limitations: Due to regulations that prevent individual-level records from being sent to other provinces, we cannot pool individual-level data from all 3 provinces. Conclusion: Compared to prior studies, this study will better estimate the donation-attributable risk of adverse maternal, fetal/infant, and neonatal outcomes. Transplant centers can use the results to counsel female living donor candidates of childbearing age and to inform recommended practices for the follow-up and care of living kidney donors who become pregnant.

Contexte: Une importante proportion des donneurs de rein vivants sont des femmes en âge de procréer. Quelques études antérieures rapportent un risque plus élevé d'hypertension gestationnelle et de prééclampsie chez les donneuses d'un rein par rapport aux non-donneuses. D'autres recherches sont nécessaires pour mieux quantifier le risque d'issues néonatales négatives attribuables au don de rein par un donneur vivant pour la mère et le fœtus/nouveau-né. Objectif: Déterminer le risque de troubles hypertensifs pendant la grossesse, notamment l'hypertension gestationnelle, la prééclampsie et l'éclampsie, et d'autres résultats pour la mère et le fœtus/nouveau-né chez les donneuses d'un rein par rapport à un groupe apparié de non-donneuses avec caractéristiques de santé initiales similaires. Cadre et conception de l'étude: Protocole pour une étude de cohorte avec populations appariées utilisant les bases de données administratives de santé canadiennes. Le protocole sera réalisé séparément dans trois provinces (Ontario, Alberta et Colombie-Britannique) et les résultats seront combinés statistiquement au moyen d'une méta-analyze. Sujets: La cohorte sera constituée de femmes âgées de 18 à 48 ans ayant donné un rein entre juillet 1992 et mars 2022 et ayant vécu au moins une grossesse unique de plus de 20 semaines post-don entre janvier 1993 et février 2023. Nous prévoyons inclure au moins 150 donneuses de rein vivantes avec plus de 200 grossesses post-don en Ontario et des nombres similaires en combinant les donneuses et les grossesses pour l'Alberta et la Colombie-Britannique. Les non-donneuses seront des femmes de la population générale ayant eu au moins une grossesse de plus de 20 semaines entre janvier 1993 et février 2023. Les non-donneuses se verront attribuer au hasard une date d'entrée dans la cohorte en fonction des dates de néphrectomie chez les donneuses. L'échantillon des non-donneuses sera limité aux femmes âgées de 18 à 48 ans à la date de leur entrée dans la cohorte avec un accouchement prévu au moins 6 mois après la date d'entrée leur ayant été attribuée. Les donneuses sont généralement en meilleure santé que la population générale, ce qui entraîne une préoccupation quant à leur comparaison à des non-donneuses. Pour atténuer cette différence, plus de 30 critères d'exclusion seront appliqués aux non-donneuses afin qu'elles présentent des mesures de santé similaires à celles des donneuses à leur entrée dans la cohorte. Les grossesses des donneuses et non-donneuses seront ensuite appariées (1:4) selon 5 facteurs de confusion potentiels : date d'accouchement, âge maternel à l'accouchement, temps entre l'entrée dans la cohorte et l'accouchement, quintile de revenu du quartier de résidence et parité à la date d'accouchement. Mesures: Le principal critère de jugement sera un composite d'hypertension gestationnelle maternelle, de prééclampsie ou d'éclampsie. Les résultats maternels secondaires comprendront des composantes du résultat primaire, la prééclampsie précoce, la morbidité maternelle grave, la césarienne, l'hémorragie post-partum et le diabète gestationnel. Les résultats fœtaux/néonataux comprendront les naissances prématurées ou de faible poids, un bébé petit pour l'âge gestationnel, l'admission en unité de soins intensifs néonataux, la mortinaissance et le décès néonatal. Méthodologie: La principale unité d'analyze sera la grossesse. Nous calculerons le rapport de risque du résultat composite primaire chez les donneuses comparativement aux non-donneuses à l'aide d'un modèle mixte de régression log-binomiale à effets aléatoires pour tenir compte de la corrélation chez les femmes avec grossesses multiples et au sein d'ensembles appariés de donneuses et de non-donneuses. Nous effectuerons des analyses statistiques dans chaque province, puis nous utiliserons des techniques méta-analytiques pour combiner les résultats agrégés et produire des estimations globales des résultats de l'étude. Limites: En raison des règlements qui empêchent l'envoi de dossiers individuels à d'autres provinces, nous ne pouvons regrouper les données individuelles des sujets des trois provinces. Conclusion: Cette étude permettra de mieux estimer le risque de résultats indésirables maternels, fœtaux et néonataux attribuable au don d'organe que les études précédentes. Les centers de transplantation pourront utiliser ces résultats pour conseiller les candidates au don vivant d'organe en âge de procréer et éclairer les recommandations de pratique pour le suivi et les soins des donneuses de rein vivantes qui deviennent enceintes.

Asymptomatic malaria in pregnancy and associated risk factors in Majang Zone, Gambella Region, Southwest Ethiopia: a hard-to-reach malaria hotspot.

BACKGROUND: Asymptomatic malaria in pregnancy (AMiP) is a daunting public health problem with multifaceted adverse outcomes for mothers, fetuses, newborns and beyond. This study aimed to assess the prevalence and risk factors of AMiP and anaemia in Majang Zone, Gambella, Southwest Ethiopia. METHODS: A facility-based cross-sectional study was conducted among 425 pregnant women attending the antenatal care (ANC) clinics of five health facilities in the Majang Zone from November 2022 to February 2023. Sociodemographic, obstetric, and anti-malarial intervention data were collected using an interviewer-administered questionnaire. A capillary blood specimen was collected to diagnose malaria and anaemia as well as determine the blood group. Malaria was diagnosed by rapid diagnostic test (RDT), microscopy, and quantitative polymerase chain reaction (qPCR). Statistical analyses were done by Statistical Package for Social Science (SPSS) version 26.0. The association between dependent and independent variables was assessed by multivariable binary logistic regression, considering P < 0.05 statistically significant. The magnitude of associations was quantified with the adjusted odds ratio (AOR) along with the corresponding 95% confidence interval (CI). RESULTS: The overall prevalence of AMiP was 15.3% (95% CI 12.1, 18.9). It was 11.3% (95% CI 8.4, 14.7) by RDT, 11.8% (95% CI 8.9, 15.2) by microscopy and 17.6% (95% CI 11.7, 24.9) by qPCR. Plasmodium falciparum, moderate parasitaemia and submicroscopic infection accounted for 55.4% of the AMiP prevalence, 50.8% of the parasite density, and 41.6% of the qPCR-positive AMiP, respectively. Nearly 32.3% of pregnant women with AMiP carried gametocytes. Risk factors of AMiP were: not utilizing insecticide-treated net (ITN) within the previous week (AOR: 9.43 95% CI 1.57, 56.62), having a history of malaria within the previous year (AOR: 2.26 95% CI 1.16, 4.42), lack of indoor residual spraying (IRS) within the previous year (AOR: 3.00 95% CI 1.50, 6.00), and ANC contact below two rounds (AOR: 4.28 95% CI 2.06, 8.87). The prevalence of anaemia was 27.7% (95% CI 23.6, 32.1), and it was higher among AMiP-positives (56.9%) than the negatives (22.5%) (P: 000). CONCLUSION: The prevalence of AMiP and anaemia was high, and remained as a critical public health problem in the study area. Focus on the identified risk factors and introduction of more sensitive diagnostic tools should be considered to mitigate AMiP in the study area.

Multi-state Markov model for time to treatment changes for HIV/AIDS patients: a retrospective cohort national datasets, Ethiopia.

BACKGROUND: Virological failure, drug resistance, toxicities, and other issues make it difficult for ART to maintain long-term sustainability. These issues would force a modification in the patient's treatment plan. The aim of this research was to determine whether first-line antiretroviral therapy is durable and to identify the factors that lead to patients on HAART changing their first highly active antiretroviral therapy regimen. METHODS: A retrospective cohort study was conducted from October, 2019-March, 2020 across all regional states including Addis Ababa and Dire Dawa administrative cities. The target population is from all health facilities that have been providing ART service for at least the past 6 months as of October 2019. Multi-stage clustered sampling method was used to select study facilities and participants. Simple random selected ART medical records of patients ever enrolled in ART treatment services. We adopted a multi-state survival modelling (msm) approach assuming each treatment regimen as state. We estimate the transition probability of patients to move from one regimen to another for time to treatment change/switch. We estimated the transition probability, prediction probabilities and length of stay and factor associated with treatment modification of patients to move from one regimen to another. RESULTS: Any of the six therapy combinations (14.4%) altered their treatment at least once during the follow-up period for a variety of reasons. Of the patients, 4,834 (13.26%) changed their treatments just once, while 371 (1.1%) changed it more than once. For 38.6% of the time, a treatment change was undertaken due to toxicity, another infection or comorbidity, or another factor, followed by New drugs were then made accessible and other factors 18.3% of the time, a drug was out of supply; 2.6% of those instances involved pregnancy; and 43.1% involved something else. Highly active anti-retroviral therapy (HAART) combinations TDF + 3TC + NVP, d4T + 3TC + NVP, and TDF + 3TC + EFV were high to treatment alterations in all reasons of treatment modifications, with 29.74%, 26.52%, and 19.52% treatment changes, respectively. Early treatment modification or regime change is one of the treatment combinations that include the d4T medication that creates major concern. The likelihood of staying and moving at the the start of s = 0 and 30-month transitions increased, but the likelihood of staying were declined. For this cohort dataset, the presence of opportunistic disease, low body weight, baseline CD4 count, and baseline TB positive were risk factors for therapy adjustment. CONCLUSION: Given that the current study took into account a national dataset, it provides a solid basis for ART drug status and management. The patient had a higher likelihood of adjusting their treatment at some point during the follow-up period due to drug toxicity, comorbidity, drug not being available, and other factors, according to the prediction probability once more. Baseline TB positivity, low CD4 count, opportunistic disease, and low body weight were risk factors for therapy adjustment in this cohort dataset.

Clinical prediction models in children that use repeated measurements with time-varying covariates: a scoping review.

BACKGROUND: Emerging evidence suggests that clinical prediction models that use repeated (time-varying) measurements within each patient may have higher predictive accuracy than models that use patient information from a single measurement. OBJECTIVE: To determine the breadth of the published literature reporting the development of clinical prediction models in children that use time-varying predictors. DATA SOURCES: MEDLINE, EMBASE and Cochrane databases. ELIGIBILITY CRITERIA: We included studies reporting the development of a multivariable clinical prediction model in children, with or without validation, to predict a repeatedly measured binary or time-to-event outcome and utilizing at least one repeatedly measured predictor. SYNTHESIS METHODS: We categorized included studies by the method used to model time-varying predictors. RESULTS: Of 99 clinical prediction model studies that had a repeated measurements data structure, only 27 (27%) used methods that incorporated the repeated measurements as time-varying predictors in a single model. Among these 27 time-varying prediction model studies, we grouped model types into nine categories: time-dependent Cox regression, generalized estimating equations, random effects model, landmark model, joint model, neural network, K-nearest neighbor, support vector machine and tree-based algorithms. Where there was comparison of time-varying models to single measurement models, using time-varying predictors improved predictive accuracy. CONCLUSIONS: Various methods have been used to develop time-varying prediction models in children, but there is a paucity of pediatric time-varying models in the literature. Incorporating time-varying covariates in pediatric prediction models may improve predictive accuracy. Future research in pediatric prediction model development should further investigate whether incorporation of time-varying covariates improves predictive accuracy.

Probiotics, Prebiotics, Lactoferrin, and Combination Products for Prevention of Mortality and Morbidity in Preterm Infants: A Systematic Review and Network Meta-Analysis.

Importance: Modulation of intestinal microbiome by administering probiotics, prebiotics, or both may prevent morbidity and mortality in premature infants. Objective: To assess the comparative effectiveness of alternative prophylactic strategies through a network meta-analysis (NMA) of randomized clinical trials. Data Sources: MEDLINE, EMBASE, Science Citation Index Expanded, CINAHL, Scopus, Cochrane CENTRAL, and Google Scholar from inception until May 10, 2023. Study Selection: Eligible trials tested probiotics, prebiotics, lactoferrin, and combination products for prevention of morbidity or mortality in preterm infants. Data Extraction and Synthesis: A frequentist random-effects model was used for the NMA, and the certainty of evidence and inferences regarding relative effectiveness were assessed using the GRADE approach. Main Outcomes and Measures: All-cause mortality, severe necrotizing enterocolitis, culture-proven sepsis, feeding intolerance, time to reach full enteral feeding, and duration of hospitalization. Results: A total of 106 trials involving 25 840 preterm infants were included. Only multiple-strain probiotics were associated with reduced all-cause mortality compared with placebo (risk ratio [RR], 0.69; 95% CI, 0.56 to 0.86; risk difference [RD], -1.7%; 95% CI, -2.4% to -0.8%). Multiple-strain probiotics alone (vs placebo: RR, 0.38; 95% CI, 0.30 to 0.50; RD, -3.7%; 95% CI, -4.1% to -2.9%) or in combination with oligosaccharides (vs placebo: RR, 0.13; 95% CI, 0.05 to 0.37; RD, -5.1%; 95% CI, -5.6% to -3.7%) were among the most effective interventions reducing severe necrotizing enterocolitis. Single-strain probiotics in combination with lactoferrin (vs placebo RR, 0.33; 95% CI, 0.14 to 0.78; RD, -10.7%; 95% CI, -13.7% to -3.5%) were the most effective intervention for reducing sepsis. Multiple-strain probiotics alone (RR, 0.61; 95% CI, 0.46 to 0.80; RD, -10.0%; 95% CI, -13.9% to -5.1%) or in combination with oligosaccharides (RR, 0.45; 95% CI, 0.29 to 0.67; RD, -14.1%; 95% CI, -18.3% to -8.5%) and single-strain probiotics (RR, 0.61; 95% CI, 0.51 to 0.72; RD, -10.0%; 95% CI, -12.6% to -7.2%) proved of best effectiveness in reduction of feeding intolerance vs placebo. Single-strain probiotics (MD, -1.94 days; 95% CI, -2.96 to -0.92) and multistrain probiotics (MD, -2.03 days; 95% CI, -3.04 to -1.02) proved the most effective in reducing the time to reach full enteral feeding compared with placebo. Only single-strain and multistrain probiotics were associated with greater effectiveness compared with placebo in reducing duration of hospitalization (MD, -3.31 days; 95% CI, -5.05 to -1.58; and MD, -2.20 days; 95% CI, -4.08 to -0.31, respectively). Conclusions and Relevance: In this systematic review and NMA, moderate- to high-certainty evidence demonstrated an association between multistrain probiotics and reduction in all-cause mortality; these interventions were also associated with the best effectiveness for other key outcomes. Combination products, including single- and multiple-strain probiotics combined with prebiotics or lactoferrin, were associated with the largest reduction in morbidity and mortality.

Protocol for a living evidence synthesis on variants of concern and COVID-19 vaccine effectiveness.

BACKGROUND: It is evident that COVID-19 will remain a public health concern in the coming years, largely driven by variants of concern (VOC). It is critical to continuously monitor vaccine effectiveness as new variants emerge and new vaccines and/or boosters are developed. Systematic surveillance of the scientific evidence base is necessary to inform public health action and identify key uncertainties. Evidence syntheses may also be used to populate models to fill in research gaps and help to prepare for future public health crises. This protocol outlines the rationale and methods for a living evidence synthesis of the effectiveness of COVID-19 vaccines in reducing the morbidity and mortality associated with, and transmission of, VOC of SARS-CoV-2. METHODS: Living evidence syntheses of vaccine effectiveness will be carried out over one year for (1) a range of potential outcomes in the index individual associated with VOC (pathogenesis); and (2) transmission of VOC. The literature search will be conducted up to May 2023. Observational and database-linkage primary studies will be included, as well as RCTs. Information sources include electronic databases (MEDLINE; Embase; Cochrane, L*OVE; the CNKI and Wangfang platforms), pre-print servers (medRxiv, BiorXiv), and online repositories of grey literature. Title and abstract and full-text screening will be performed by two reviewers using a liberal accelerated method. Data extraction and risk of bias assessment will be completed by one reviewer with verification of the assessment by a second reviewer. Results from included studies will be pooled via random effects meta-analysis when appropriate, or otherwise summarized narratively. DISCUSSION: Evidence generated from our living evidence synthesis will be used to inform policy making, modelling, and prioritization of future research on the effectiveness of COVID-19 vaccines against VOC.

Resistance training prescription for muscle strength and hypertrophy in healthy adults: a systematic review and Bayesian network meta-analysis.

OBJECTIVE: To determine how distinct combinations of resistance training prescription (RTx) variables (load, sets and frequency) affect muscle strength and hypertrophy. DATA SOURCES: MEDLINE, Embase, Emcare, SPORTDiscus, CINAHL, and Web of Science were searched until February 2022. ELIGIBILITY CRITERIA: Randomised trials that included healthy adults, compared at least 2 predefined conditions (non-exercise control (CTRL) and 12 RTx, differentiated by load, sets and/or weekly frequency), and reported muscle strength and/or hypertrophy were included. ANALYSES: Systematic review and Bayesian network meta-analysis methodology was used to compare RTxs and CTRL. Surface under the cumulative ranking curve values were used to rank conditions. Confidence was assessed with threshold analysis. RESULTS: The strength network included 178 studies (n=5097; women=45%). The hypertrophy network included 119 studies (n=3364; women=47%). All RTxs were superior to CTRL for muscle strength and hypertrophy. Higher-load (>80% of single repetition maximum) prescriptions maximised strength gains, and all prescriptions comparably promoted muscle hypertrophy. While the calculated effects of many prescriptions were similar, higher-load, multiset, thrice-weekly training (standardised mean difference (95% credible interval); 1.60 (1.38 to 1.82) vs CTRL) was the highest-ranked RTx for strength, and higher-load, multiset, twice-weekly training (0.66 (0.47 to 0.85) vs CTRL) was the highest-ranked RTx for hypertrophy. Threshold analysis demonstrated these results were extremely robust. CONCLUSION: All RTx promoted strength and hypertrophy compared with no exercise. The highest-ranked prescriptions for strength involved higher loads, whereas the highest-ranked prescriptions for hypertrophy included multiple sets. PROSPERO REGISTRATION NUMBER: CRD42021259663 and CRD42021258902.

Development and validation of asthma risk prediction models using co-expression gene modules and machine learning methods.

Asthma is a heterogeneous respiratory disease characterized by airway inflammation and obstruction. Despite recent advances, the genetic regulation of asthma pathogenesis is still largely unknown. Gene expression profiling techniques are well suited to study complex diseases including asthma. In this study, differentially expressed genes (DEGs) followed by weighted gene co-expression network analysis (WGCNA) and machine learning techniques using dataset generated from airway epithelial cells (AECs) and nasal epithelial cells (NECs) were used to identify candidate genes and pathways and to develop asthma classification and predictive models. The models were validated using bronchial epithelial cells (BECs), airway smooth muscle (ASM) and whole blood (WB) datasets. DEG and WGCNA followed by least absolute shrinkage and selection operator (LASSO) method identified 30 and 34 gene signatures and these gene signatures with support vector machine (SVM) discriminated asthmatic subjects from controls in AECs (Area under the curve: AUC = 1) and NECs (AUC = 1), respectively. We further validated AECs derived gene-signature in BECs (AUC = 0.72), ASM (AUC = 0.74) and WB (AUC = 0.66). Similarly, NECs derived gene-signature were validated in BECs (AUC = 0.75), ASM (AUC = 0.82) and WB (AUC = 0.69). Both AECs and NECs based gene-signatures showed a strong diagnostic performance with high sensitivity and specificity. Functional annotation of gene-signatures from AECs and NECs were enriched in pathways associated with IL-13, PI3K/AKT and apoptosis signaling. Several asthma related genes were prioritized including SERPINB2 and CTSC genes, which showed functional relevance in multiple tissue/cell types and related to asthma pathogenesis. Taken together, epithelium gene signature-based model could serve as robust surrogate model for hard-to-get tissues including BECs to improve the molecular etiology of asthma.

Integrative multiomics analysis of infant gut microbiome and serum metabolome reveals key molecular biomarkers of early onset childhood obesity.

Evidence supports a complex interplay of gut microbiome and host metabolism as regulators of obesity. The metabolic phenotype and microbial metabolism of host diet may also contribute to greater obesity risk in children early in life. This study aimed to identify features that discriminated overweight/obese from normal weight infants by integrating gut microbiome and serum metabolome profiles. This prospective analysis included 50 South Asian children living in Canada, selected from the SouTh Asian biRth cohorT (START). Serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry and the relative abundance of bacterial 16S rRNA gene amplicon sequence variant was evaluated at 1 year. Cumulative body mass index (BMIAUC) and skinfold thickness (SSFAUC) scores were calculated from birth to 3 years as the total area under the growth curve (AUC). BMIAUC and/or SSFAUC >85th percentile was used to define overweight/obesity. Data Integration Analysis for Biomarker discovery using Latent cOmponent (DIABLO) was used to identify discriminant features associated with childhood overweight/obesity. The associations between identified features and anthropometric measures were examined using logistic regression. Circulating metabolites including glutamic acid, acetylcarnitine, carnitine, and threonine were positively, whereas γ-aminobutyric acid (GABA), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were negatively associated with childhood overweight/obesity. The abundance of the Pseudobutyrivibrio and Lactobacillus genera were positively, and Clostridium sensu stricto 1 and Akkermansia were negatively associated with childhood overweight/obesity. Integrative analysis revealed that Akkermansia was positively whereas Lactobacillus was inversely correlated with GABA and SDMA, and Pseudobutyrivibrio was inversely correlated with GABA. This study provides insights into metabolic and microbial signatures which may regulate satiety, energy metabolism, inflammatory processes, and/or gut barrier function, and therefore, obesity trajectories in childhood. Understanding the functional capacity of these molecular features and potentially modifiable risk factors such as dietary exposures early in life may offer a novel approach for preventing childhood obesity.

Do Psychological and Behavioural Factors Change Over Pregnancy?

OBJECTIVES: To investigate how psychological and behavioural factors change from the first to the last half of pregnancy. METHODS: In this prospective cohort study, we assessed the changes in psychological and behavioural factors across 10 domains among 445 women (mean age = 30.9 years) in Ontario, Canada. We collected data using 2 standardized questionnaires administered at <21 and 32-36 weeks of gestation. We computed intraclass correlation coefficients, percentages of no change, decrease, and increase, and mean differences between the 2 surveys. RESULTS: Most psychological and behavioural factors had intraclass correlation coefficients < 0.50 between the first and the second half of pregnancy, suggesting remarkable changes over the course of pregnancy. We observed significant decreases in self-efficacy, compensatory health beliefs, guilt regarding binge eating, emotional eating, dietary restriction, pregnancy-related nausea and food cravings, sleep duration, and physical activity. We also found increases in anxious and depressive symptoms and the tendency to accept friends' and family's beliefs regarding pregnancy. CONCLUSIONS: In the first prospective analysis, we found that many psychological and behavioural factors changed significantly over pregnancy.

Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis.

Background: Knowing the prevalence of multimorbidity among adults across continents is a crucial piece of information for achieving Sustainable Development Goal 3.4, which calls for reducing premature death due to non-communicable diseases. A high prevalence of multimorbidity indicates high mortality and increased healthcare utilization. We aimed to understand the prevalence of multimorbidity across WHO geographic regions among adults. Methods: We performed a systematic review and meta-analysis of surveys designed to estimate the prevalence of multimorbidity among adults in community settings. We searched PubMed, ScienceDirect, Embase and Google Scholar databases for studies published between January 1, 2000, and December 31, 2021. The random-effects model estimated the pooled proportion of multimorbidity in adults. Heterogeneity was quantified using I2 statistics. We performed subgroup analyses and sensitivity analyses based on continents, age, gender, multimorbidity definition, study periods and sample size. The study protocol was registered with PROSPERO (CRD42020150945). Findings: We analyzed data from 126 peer-reviewed studies that included nearly 15.4 million people (32.1% were male) with a weighted mean age of 56.94 years (standard deviation of 10.84 years) from 54 countries around the world. The overall global prevalence of multimorbidity was 37.2% (95% CI = 34.9-39.4%). South America (45.7%, 95% CI = 39.0-52.5) had the highest prevalence of multimorbidity, followed by North America (43.1%, 95% CI = 32.3-53.8%), Europe (39.2%, 95% CI = 33.2-45.2%), and Asia (35%, 95% CI = 31.4-38.5%). The subgroup study highlights that multimorbidity is more prevalent in females (39.4%, 95% CI = 36.4-42.4%) than males (32.8%, 95% CI = 30.0-35.6%). More than half of the adult population worldwide above 60 years of age had multimorbid conditions (51.0%, 95% CI = 44.1-58.0%). Multimorbidity has become increasingly prevalent in the last two decades, while the prevalence appears to have stayed stable in the recent decade among adults globally. Interpretation: The multimorbidity patterns by geographic regions, time, age, and gender suggest noticeable demographic and regional differences in the burden of multimorbidity. According to insights about prevalence among adults, priority is required for effective and integrative interventions for older adults from South America, Europe, and North America. A high prevalence of multimorbidity among adults from South America suggests immediate interventions are needed to reduce the burden of morbidity. Furthermore, the high prevalence trend in the last two decades indicates that the global burden of multimorbidity continues at the same pace. The low prevalence in Africa suggests that there may be many undiagnosed chronic illness patients in Africa. Funding: None.

Associations of abdominal obesity with different types of bone fractures in adults: A systematic review and dose-response meta-analysis of prospective cohort studies.

Findings on the association between abdominal obesity and hip fracture were summarized in a meta-analysis in 2017; however, no study has examined the dose-response association between abdominal fat indices and hip fracture. Also, we found no meta-analysis investigating other types of bone fractures including any vertebral fractures in relation to abdominal obesity. Therefore, the present systematic review and dose-response meta-analysis of prospective cohort studies were conducted to examine the association between abdominal obesity and different types of bone fractures. A comprehensive literature search was done by searching PubMed, Scopus, Web of Science, and Google Scholar until October 2021. In total, 23 articles from prospective cohort studies with a total sample size of 3,456,631 participants were included. During the follow-up periods ranging between 4 and 26 years, 137,989 cases of bone fracture were recorded. After comparing the highest and lowest categories of abdominal fat indices, the summary relative risks (RRs) of any, hip, and vertebral fractures were 0.99 (95% CI: 0.81-1.20), 1.09 (95% CI: 0.82-1.43), and 1.18 (95% CI: 1.05-1.33), respectively, indicating a significant positive association between abdominal obesity and risk of vertebral fracture. In the non-linear dose-response analysis, abdominal obesity based on the waist-to-hip ratio (WHR) was positively associated with an increased risk of hip fracture from 0.7 to 1.1 units of WHR. In the linear analysis, a 10 cm increase in waist circumference (WC) was associated with a 3% higher risk of vertebral fracture. We found no other dose-response association for other types of bone fractures. In conclusion, abdominal obesity may be associated with a higher risk of hip and vertebral fractures.

Assessment of Concordance between Chairside Ultrasonography and Digital Palpation in Detecting Myofascial Trigger Points in Masticatory Myofascial Pain Syndrome.

INTRODUCTION: Masticatory myofascial pain is a musculoligamentous syndrome that can mimic odontogenic pain. Pain referral to odontogenic structures can be traced to hyperirritated myofascial trigger points (MTrPs). This pragmatic study evaluated the concordance between ultrasonography and palpation in detecting MTrPs in the masseter and temporalis muscles. METHODS: Fifty-seven patients suspected to have temporomandibular disorder were included. MTrPs were palpated manually by expert clinicians. Ultrasonography was then performed by a blind sonographer. The quantity of MTrPs and the involved muscle sections, the pain occurrence, and the location of the MTrPs within the muscle sections were compared using the mean difference (MD) and concordance statistics (Cohen κ and the interclass correlation coefficient [ICC]) as applicable. RESULTS: Ultrasonography located MTrPs as 2.1 ± 1.3 mm2 hypoechoic nodules at a depth of 7 ± 3.3 mm. Ultrasonography moderately agreed with palpation on the quantity of MTrPs per patient (MD = 1; 95% confidence interval [CI], 0.06-1.9; ICC = 0.56; 95% CI, 0.32-0.72). Palpation detected marginally more involved muscle sections per patient (MD = 0.7; 95% CI, 0.06-1.34.05; ICC = 0.64; 95% CI, 0.44-0.77) with more pain occurrence per patient (MD = 1.4; 95% CI, 0.56-2.28; ICC = 0.13; 95% CI, -0.26 to 0.41). There was a discordance in the location of the MTrPs within the muscle sections per patient (κ = -0.46; 95% CI, -0.77 to -0.14). CONCLUSIONS: Ultrasonography and palpation concurred moderately to substantially on the quantity of MTrPs and the involved muscle sections but disagreed on the location of the MTrPs within the muscle sections. Ultrasonography has the potential as a chairside diagnostic aid to help clinicians determine an accurate diagnosis, enhance patient experience during examination, and avoid unnecessary treatments that can mitigate the risk of iatrogenic damage.

Mapping and determinants of consumption of egg and/or flesh foods and zero vegetables or fruits among young children in SSA.

Zero vegetable or fruit and egg and/or flesh foods are the latest indicators for assessing infant and young child feeding practices. Understanding national and subnational heterogeneity and regional clustering in children with SSA is becoming increasingly essential for geographic targeting and policy prioritization. Geographical case identification, determinants, and impacts were all investigated. SSA children's consumption of vegetable or fruit, egg and/or flesh food, and both were low. In SSA, some portions of the Southern, South direction of the Western and Central regions have a lower weight of all bad conditions than others, although children continue to suffer in considerable numbers in all disadvantage circumstances. Children under the age of 1 year, from rural areas, uneducated families, and low income were all disadvantaged by both feeding techniques. To improve child nutrition status, multisectoral collaboration is essential. This framework allows for the tracking, planning, and implementation of nutritional treatments.

Egg and Dietary Cholesterol Intake and Risk of All-Cause, Cardiovascular, and Cancer Mortality: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies.

Objective: This systematic review and meta-analysis of prospective cohort studies examined the associations between egg and dietary cholesterol intake and the risk of mortality from all causes, including cardiovascular disease (CVD) and cancer. Methods: We searched PubMed, Scopus, ISI Web of Knowledge, and Google Scholar until April 2021, as well as references to the relevant articles retrieved. Random-effects models were used to calculate summary relative risk (RR) and 95% confidence intervals (CIs) for the highest vs. lowest categories of egg and dietary cholesterol intake. Also, linear and non-linear dose-response analyses were conducted to examine the dose-response relationships. Results: We included 55 studies, comprising data from 2,772,486 individuals with 228,425, 71,745, and 67,211 cases of all-cause, CVD, and cancer mortality, respectively. Intake of each additional egg per day was associated with a 7% higher risk of all-cause (1.07, 95% CI: 1.02-1.12, I2 = 84.8%) and a 13% higher risk of cancer mortality (1.13, 95% CI: 1.06-1.20, I2 = 54.2%), but was not associated with CVD mortality (1.00, 95% CI: 0.92-1.09, I2 = 81.5%). Non-linear analyses showed increased risks for egg consumption of more than 1.5 and 0.5 eggs/day, respectively. Each 100 mg/day increment in dietary cholesterol intake was associated with a 6% higher risk of all-cause mortality (1.06, 95% CI: 1.03-1.08, I2 = 34.5%) and a 6% higher risk of cancer mortality (1.06, 95% CI: 1.05-1.07, I2 = 0%), but was not associated with CVD mortality (1.04, 95% CI: 0.99-1.10, I2 = 85.9%). Non-linear analyses demonstrated elevated risks of CVD and cancer mortality for intakes more than 450 and 250 mg/day, respectively. Conclusions and Relevance: High-dietary intake of eggs and cholesterol was associated with all-cause and cancer mortality. Little evidence for elevated risks was seen for intakes below 0.5 egg/day or 250 mg/day of dietary cholesterol. Our findings should be considered with caution because of small risk estimates and moderate between-study heterogeneity. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=252564, PROSPERO, identifier: CRD42021252564.

An improved method for analysis of interrupted time series (ITS) data: accounting for patient heterogeneity using weighted analysis.

Interrupted time series (ITS) design is commonly used to evaluate the impact of interventions in healthcare settings. Segmented regression (SR) is the most commonly used statistical method and has been shown to be useful in practical applications involving ITS designs. Nevertheless, SR is prone to aggregation bias, which leads to imprecision and loss of power to detect clinically meaningful differences. The objective of this article is to present a weighted SR method, where variability across patients within the healthcare facility and across time points is incorporated through weights. We present the methodological framework, provide optimal weights associated with data at each time point and discuss relevant statistical inference. We conduct extensive simulations to evaluate performance of our method and provide comparative analysis with the traditional SR using established performance criteria such as bias, mean square error and statistical power. Illustrations using real data is also provided. In most simulation scenarios considered, the weighted SR method produced estimators that are uniformly more precise and relatively less biased compared to the traditional SR. The weighted approach also associated with higher statistical power in the scenarios considered. The performance difference is much larger for data with high variability across patients within healthcare facilities. The weighted method proposed here allows us to account for the heterogeneity in the patient population, leading to increased accuracy and power across all scenarios. We recommend researchers to carefully design their studies and determine their sample size by incorporating heterogeneity in the patient population.

A Roadmap for Building Data Science Capacity for Health Discovery and Innovation in Africa.

Technological advances now make it possible to generate diverse, complex and varying sizes of data in a wide range of applications from business to engineering to medicine. In the health sciences, in particular, data are being produced at an unprecedented rate across the full spectrum of scientific inquiry spanning basic biology, clinical medicine, public health and health care systems. Leveraging these data can accelerate scientific advances, health discovery and innovations. However, data are just the raw material required to generate new knowledge, not knowledge on its own, as a pile of bricks would not be mistaken for a building. In order to solve complex scientific problems, appropriate methods, tools and technologies must be integrated with domain knowledge expertise to generate and analyze big data. This integrated interdisciplinary approach is what has become to be widely known as data science. Although the discipline of data science has been rapidly evolving over the past couple of decades in resource-rich countries, the situation is bleak in resource-limited settings such as most countries in Africa primarily due to lack of well-trained data scientists. In this paper, we highlight a roadmap for building capacity in health data science in Africa to help spur health discovery and innovation, and propose a sustainable potential solution consisting of three key activities: a graduate-level training, faculty development, and stakeholder engagement. We also outline potential challenges and mitigating strategies.

Dietary intake and biomarkers of alpha linolenic acid and risk of all cause, cardiovascular, and cancer mortality: systematic review and dose-response meta-analysis of cohort studies.

OBJECTIVE: To examine the associations between dietary intake and tissue biomarkers of alpha linolenic acid (ALA) and risk of mortality from all causes, cardiovascular disease (CVD), and cancer. DESIGN: Systematic review and meta-analysis of prospective cohort studies. DATA SOURCES: PubMed, Scopus, ISI Web of Science, and Google Scholar to 30 April 2021. STUDY SELECTION: Prospective cohort studies that reported the risk estimates for death from all causes, CVD, and cancer. DATA SYNTHESIS: Summary relative risks and 95% confidence intervals were calculated for the highest versus lowest categories of ALA intake using random effects and fixed effects models. Linear and non-linear dose-response analyses were conducted to assess the dose-response associations between ALA intake and mortality. RESULTS: 41 articles from prospective cohort studies were included in this systematic review and meta-analysis, totalling 1 197 564 participants. During follow-up ranging from two to 32 years, 198 113 deaths from all causes, 62 773 from CVD, and 65 954 from cancer were recorded. High intake of ALA compared with low intake was significantly associated with a lower risk of deaths from all causes (pooled relative risk 0.90, 95% confidence interval 0.83 to 0.97, I2=77.8%, 15 studies), CVD (0.92, 0.86 to 0.99, I2=48.2%, n=16), and coronary heart disease (CHD) (0.89, 0.81 to 0.97, I2=5.6%, n=9), and a slightly higher risk of cancer mortality (1.06, 1.02 to 1.11, I2=3.8%, n=10). In the dose-response analysis, a 1 g/day increase in ALA intake (equivalent to one tablespoon of canola oil or 0.5 ounces of walnut) was associated with a 5% lower risk of all cause (0.95, 0.91 to 0.99, I2=76.2%, n=12) and CVD mortality (0.95, 0.91 to 0.98, I2=30.7%, n=14). The pooled relative risks for the highest compared with lowest tissue levels of ALA indicated a significant inverse association with all cause mortality (0.95, 0.90 to 0.99, I2=8.2%, n=26). Also, based on the dose-response analysis, each 1 standard deviation increment in blood concentrations of ALA was associated with a lower risk of CHD mortality (0.92, 0.86 to 0.98, I2=37.1%, n=14). CONCLUSIONS: The findings show that dietary ALA intake is associated with a reduced risk of mortality from all causes, CVD, and CHD, and a slightly higher risk of cancer mortality, whereas higher blood levels of ALA are associated with a reduced risk of all cause and CHD mortality only. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42021229487.

Subnational mapping for targeting anaemia prevention in women of reproductive age in Ethiopia: A coverage-equity paradox.

Anaemia in women of reproductive age (WRA) can be effectively addressed if supported by a better understanding of the spatial variations, magnitude, severity and distribution of anaemia. This study aimed to map the subnational spatial distribution of anaemia (any, moderate and severe forms) among WRA in Ethiopia. We identified and mapped (any, moderate and severe) anaemia hotspots in WRA (n = 14,923) at the subnational level and identified risk factors using multilevel logistic regression. Kulldorff scan statistics were used to identify hotspot regions. Ordinary kringing was used to predict the anaemia prevalence in unmeasured areas. The overall anaemia prevalence increased from 16.6% in 2011 to 23.6% in 2016, a rise that was mostly related to the widening of existing hotspot areas. The primary clusters of (any) anaemia were in Somali and Afar regions. The horn of the Somali region represented a cluster of 330 km where 10% of WRA were severely anaemic. The Oromia-Somali border represented a significant cluster covering 247 km, with 9% severe anaemia. Population-dense areas with low anaemia prevalence had high absolute number of cases. Women education, taking iron-folic-acid tablets during pregnancy and birth-delivery in health facilities reduced the risk of any anaemia (P < 0.05). The local-level mapping of anaemia helped identify clusters that require attention but also highlighted the urgent need to study the aetiology of anaemia to improve the effectiveness and safety of interventions. Both relative and absolute anaemia estimates are critical to determine where additional attention is needed.

Mapping of mothers' suffering and child mortality in Sub-Saharan Africa.

Child death and mothers who suffer from child death are a public health concern in Sub-Saharan Africa. The location and associated factors of child death and mothers who suffer child death were not identified. To monitor and prioritize effective interventions, it is important to identify hotspots areas and associated factors. Data from nationally representative demographic and health survey and Multiple Indicator Cluster administrated in 42 Sub-Sahara Africa countries, which comprised a total of 398,574 mothers with 1,521,312 children. Spatial heterogeneity conducted hotspot regions identified. A mixed-effect regression model was run, and the adjusted ratio with corresponding 95% confidence intervals was estimated. The prevalence of mothers who suffer child death 27% and 45-49 year of age mother 48%. In Niger, 47% of mothers were suffering child death. Women being without HIV knowledge, stunted, wasted, uneducated, not household head, poor, from rural, and from subtropical significantly increased the odds of the case (P < 0.05). The spatial analysis can support the design and prioritization of interventions. Multispectral interventions for mothers who suffer from child death are urgently needed, improve maternal health and it will reduce the future risk of cases.