Exploring Gene-Diet Interactions for Mother-Child Health: A Systematic Review of Epidemiological Studies.

BACKGROUND: Maternal-child health suggests the critical impact of maternal nutrition during the pre-conception and gestational periods, with some genetic variants also playing a significant role. Our systematic review provides an overview of epidemiological studies exploring the interactions between genetic variants, maternal dietary habits, and neonatal and/or maternal pregnancy outcomes. METHODS: From its inception until June 2023, we conducted a comprehensive literature search on PubMed, Embase, and Web of Science databases. RESULTS: On a total of 29 epidemiological studies, 11 studies were conducted to explore the interplay between genetic variants and dietary factors, focusing on the risks associated with gestational diabetes mellitus, hypertensive disorders of pregnancy, recurrent spontaneous abortion, recurrent pregnancy loss, iron deficiency anemia, and gestational weight gain. Concerning neonatal outcomes, six studies investigated the interplay between genetic variants, dietary factors, and anthropometric measures, while eight studies delved into abnormal embryonic development, two studies focused on preterm birth, and two studies explored other neonatal outcomes. CONCLUSIONS: Deeply understanding gene-diet interactions could be useful in developing highly personalized approaches to maternal and child nutrition, as well as in exploring the potential implications in disease prevention and the promotion of the long-term well-being of both mothers and their offspring.

Language bias in orthodontic systematic reviews: A meta-epidemiological study.

BACKGROUND: Orthodontic systematic reviews (SRs) include studies published mostly in English than non-English languages. Including only English studies in SRs may result in a language bias. This meta-epidemiological study aimed to evaluate the language bias impact on orthodontic SRs. DATA SOURCE: SRs published in high-impact orthodontic journals between 2017 and 2021 were retrieved through an electronic search of PubMed in June 2022. Additionally, Cochrane oral health group was searched for orthodontic systematic reviews published in the same period. DATA COLLECTION AND ANALYSIS: Study selection and data extraction were performed by two authors. Multivariable logistic regression was implemented to explore the association of including non-English studies with the SRs characteristics. For the meta-epidemiological analysis, one meta-analysis from each SRs with at least three trials, including one non-English trial was extracted. The average difference in SMD was obtained using a random-effects meta-analysis. RESULTS: 174 SRs were included in this study. Almost one-quarter (n = 45/174, 26%) of these SRs included at least one non-English study. The association between SRs characteristics and including non-English studies was not statistically significant except for the restriction on language: the odds of including non-English studies reduced by 89% in SRs with a language restriction (OR: 0.11, 95%CI: 0.01 0.55, P< 0.01). Out of the sample, only fourteen meta-analyses were included in the meta-epidemiological analysis. The meta-epidemiological analysis revealed that non-English studies tended to overestimate the summary SMD by approximately 0.30, but this was not statistically significant when random-effects model was employed due to substantial statistical heterogeneity (ΔSMD = -0.29, 95%CI: -0.63 to 0.05, P = 0.37). As such, the overestimation of meta-analysis results by including non-English studies was statistically non-significant. CONCLUSION: Language bias has non-negligible impact on the results of orthodontic SRs. Orthodontic systematic reviews should abstain from language restrictions and use sensitivity analysis to assess the impact of language on the conclusions, as non-English studies may have a lower quality.

Safety of fluoroquinolones / Seguridad de las fluoroquinolonas

Fluoroquinolones (FQs) are one of the most commonly prescribed classes of antibiotics. Although they were initially well tolerated in randomized clinical trials, subsequent epidemiological studies have reported an increased risk of threatening, severe, long-lasting, disabling and irreversible adverse effects (AEs), related to neurotoxicity and collagen degradation, such as tendonitis, Achilles tendon rupture, aortic aneurysm, and retinal detachment. This article reviews the main potentially threatening AEs, the alarms issued by regulatory agencies and therapeutic alternatives. (AU)

Las fluoroquinolonas son una de las clases de antibióticos más prescritas. Aunque inicialmente fueron bien toleradas en ensayos clínicos aleatorizados, estudios epidemiológicos posteriores han informado de un mayor riesgo de efectos adversos efectos adversos amenazantes, graves, duraderos, incapacitantes e irreversibles, relacionados con la neurotoxicidad y la degradación del colágeno, como tendinitis, rotura del tendón de Aquiles, aneurisma aórtico y desprendimiento de retina. Este artículo repasa los principales efectos adversos potencialmente amenazadores, las alarmas emitidas por las agencias reguladoras y las alternativas terapéuticas. (AU)

Participant recruitment and attrition in surgical randomised trials with placebo controls versus non-operative controls: a meta-epidemiological study and meta-analysis.

OBJECTIVE: To compare differences in recruitment and attrition between placebo control randomised trials of surgery, and trials of the same surgical interventions and conditions that used non-operative (non-placebo) controls. DESIGN: Meta-epidemiological study. DATA SOURCES: Randomised controlled trials were identified from an electronic search of MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials from their inception date to 21 November 2018. STUDY SELECTION: Placebo control trials evaluating efficacy of any surgical intervention and non-operative control trials of the same surgical intervention were included in this study. 25 730 records were retrieved from our systemic search, identifying 61 placebo control and 38 non-operative control trials for inclusion in analysis. OUTCOME MEASURES: Primary outcome measures were recruitment and attrition. These were assessed in terms of recruitment rate (number of participants enrolled, as a proportion of those eligible) and overall attrition rate (composite of dropout, loss to follow-up and cross-overs, expressed as proportion of total sample size). Secondary outcome measures included participant cross-over rate, dropout and loss to follow-up. RESULTS: Unadjusted pooled recruitment and attrition rates were similar between placebo and non-operative control trials. Study characteristics were not significantly different apart from time to primary timepoint which was shorter in studies with placebo controls (365 vs 274 days, p=0.006). After adjusting for covariates (follow-up duration and number of timepoints), the attrition rate of placebo control trials was almost twice as high compared with non-operative controlled-trials (incident rate ratio (IRR) (95% CI) 1.8 (1.1 to 3.0), p=0.032). The incorporation of one additional follow-up timepoint (regardless of follow-up duration) was associated with reduced attrition in placebo control surgical trials (IRR (95% CI) 0.64 (0.52 to 0.79), p<0.001). CONCLUSIONS: Placebo control trials of surgery have similar recruitment issues but higher attrition compared with non-operative (non-placebo) control trials. Study design should incorporate strategies such as increased timepoints for given follow-up duration to mitigate losses to follow-up and dropout. PROSPERO REGISTRATION NUMBER: CRD42019117364.

Preconceptional micronutrient adequacy among women in Greece: a prospective epidemiological study.

INTRODUCTION: The importance of micronutrient intake during the preconceptional and early pregnancy period for both maternal and fetal outcomes is well-known, however, relevant data are not available for Greek pregnant women. The aim of the present study is to delineate the nutritional status preceding conception among a representative cohort of Greek pregnant women. METHODS: This was a prospective study of pregnant women from routine care, recruited at 11+0-13+6 gestational weeks, between December 2020 and October 2022, at the 3rd Department of Obstetrics and Gynecology, Aristotle University of Thessaloniki, Greece. Eligible participants for the study included healthy pregnant women aged 20 years or older, possessing a proficient understanding of the Greek language, and not engaged in specific nutritional programs. A validated Food Frequency Questionnaire was applied to gather information regarding nutritional habits in the last 6 months prior to conception. The consumption of nutrients was compared to the reference intake levels suggested by the European Food Safety Authority. Further analyses between different participants' subgroups were performed. RESULTS: Overall, 1100 pregnant women (mean age: 32.4 ± 4.9 years) were enrolled. Almost all examined micronutrients' intake was significantly different from dietary reference values. Furthermore, nutrient adequacy ratio was below 60% in 6 out of 22 micronutrients examined, and Mean Adequacy Ratio was 93%. However, Mean Adequacy Ratio is characterized by extreme variance between the examined values. Iodine, folic acid, potassium, and vitamin D intake levels were significantly lower than the recommended intake levels (p < .001 for all), while vitamin K and niacin (p < .001 for both) were consumed in great extent. Sodium median intake, without calculating extra salt addition also exceeded the reference value levels (p = .03). Notably, magnesium intake exceeded the upper safety limits in 12.4% of the sample. CONCLUSION: Potential inadequacies in important micronutrients for uneventful pregnancy outcomes have been revealed.. Special attention is needed for magnesium to balance possible toxicity with evident benefits.

The global impact of SARS-CoV-2 variant BA.2.86: a comprehensive analysis with the latest developments and transmission trends - an epidemiological study.

OBJECTIVE: The variant BA.2.86 of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing concern globally. The virus contains a large number of mutations, and transmission trends are rapidly changing globally. This study investigates the global epidemiological and transmission trends of SARS-CoV-2 new variant BA.2.86 in various continents and countries. MATERIALS AND METHODS: The data were recorded using key terms, including SARS-CoV-2, Omicron, BA.2.86, epidemiology, occurrence, incidence, prevalence, and transmission trends. The data on SARS-CoV-2 variant BA.2.86 were searched by the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), the Global Initiative on Sharing All Influenza Data (GSIAD), PubMed, and Web of Science. Initially, 40 documents were identified, and finally, 8 documents were included for the data analysis and discussion. The analysis of findings on transmission trends was based on the data from August 14, 2023, to February 28, 2024. RESULTS: The SARS-CoV-2, novel variant BA.2.86, crossed the international borders of 6 continents and 89 countries and infected 19,532 people. In Europe, 32 countries are affected and involved 12,667 people (64.85%), North and South America 18 countries with 3,515 cases (17.99%), Asia 27 countries with 2,063 people (10.56%), Oceania 2 countries with 689 cases (3.52%), and Africa 10 countries with 598 (3.06%) cases. The BA.2.86 rapidly spread and mainly affected the people in the United Kingdom 3,228 (16.52%), Sweden 2,380 (12.18%), USA 1,929 (9.87%), Denmark 1,621 (8.29%), Canada 1,516 (7.67%), France 833 (4.26%), Japan 810 (4.14%), Netherlands 725 (3.71%), Germany 681 (3.48%), Spain 665 (3.40%), South Korea 556 (2.84%), and Australia 512 (2.62%). CONCLUSIONS: The SARS-CoV-2, novel variant BA.2.86, spread over six continents and 89 countries and affected 19,532 people worldwide. The disease is more prevalent in the United Kingdom, United States of America, and European countries. The detection of the disease in multiple continents and countries suggests some degree of transmissibility. Global health authorities need to rethink their policies and implement strict strategies to eradicate emerging variants and minimize the global disease burden.

Bayesian estimation of the measurement of interactions in epidemiological studies.

Background: Interaction identification is important in epidemiological studies and can be detected by including a product term in the model. However, as Rothman noted, a product term in exponential models may be regarded as multiplicative rather than additive to better reflect biological interactions. Currently, the additive interaction is largely measured by the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (S), and confidence intervals are developed via frequentist approaches. However, few studies have focused on the same issue from a Bayesian perspective. The present study aims to provide a Bayesian view of the estimation and credible intervals of the additive interaction measures. Methods: Bayesian logistic regression was employed, and estimates and credible intervals were calculated from posterior samples of the RERI, AP and S. Since Bayesian inference depends only on posterior samples, it is very easy to apply this method to preventive factors. The validity of the proposed method was verified by comparing the Bayesian method with the delta and bootstrap approaches in simulation studies with example data. Results: In all the simulation studies, the Bayesian estimates were very close to the corresponding true values. Due to the skewness of the interaction measures, compared with the confidence intervals of the delta method, the credible intervals of the Bayesian approach were more balanced and matched the nominal 95% level. Compared with the bootstrap method, the Bayesian method appeared to be a competitive alternative and fared better when small sample sizes were used. Conclusions: The proposed Bayesian method is a competitive alternative to other methods. This approach can assist epidemiologists in detecting additive-scale interactions.

Molecular epidemiological study of Scrub Typhus in residence, farm and forest habitats from Yunnan Province, China.

The number of people suffering from scrub typhus, which is not of concern, is increasing year by year, especially in Yunnan Province, China. From June 1, 2021 to August 15, 2022, a total of 505 mammalian samples were collected from farm, forest, and residential habitats with high incidence of scrub typhus in Yunnan, China, for nPCR (nested PCR) and qPCR (quantitative real-time PCR) detection of Orientia tsutsugamushi. A total of 4 orders of murine-like animals, Rodentia (87.52%, n = 442), Insectivora (10.29%, n = 52), Lagomorpha (1.79%, n = 9) and Scandentia (0.40%, n = 2) were trapped. Comparing the qPCR infection rates in the three habitats, it was no significant difference that the infection rate of residential habitat (44.44%) and that of the farm habitat (45.05%, P>0.05), which is much larger than that of the forest habitat (3.08%) (P<0.001). Three genotypes (Karp-like, Kato-like and TA763-like) of O. tsutsugamushi were found from Yunnan, China in this study.

Geospatial Science for the Environmental Epidemiology of Cancer in the Exposome Era.

Geospatial science is the science of location or place that harnesses geospatial tools, such as geographic information systems (GIS), to understand the features of the environment according to their locations. Geospatial science has been transformative for cancer epidemiologic studies through enabling large-scale environmental exposure assessments. As the research paradigm for the exposome, or the totality of environmental exposures across the life course, continues to evolve, geospatial science will serve a critical role in determining optimal practices for how to measure the environment as part of the external exposome. The objectives of this article are to provide a summary of key concepts, present a conceptual framework that illustrates how geospatial science is applied to environmental epidemiology in practice and through the lens of the exposome, and discuss the following opportunities for advancing geospatial science in cancer epidemiologic research: enhancing spatial and temporal resolutions and extents for geospatial data; geospatial methodologies to measure climate change factors; approaches facilitating the use of patient addresses in epidemiologic studies; combining internal exposome data and geospatial exposure models of the external exposome to provide insights into biological pathways for environment-disease relationships; and incorporation of geospatial data into personalized cancer screening policies and clinical decision making.

Using Negative Control Populations to Assess Unmeasured Confounding and Direct Effects.

Sometimes treatment effects are absent in a subgroup of the population. For example, penicillin has no effect on severe symptoms in individuals infected by resistant Staphylococcus aureus , and codeine has no effect on pain in individuals with certain polymorphisms in the CYP2D6 enzyme. Subgroups where a treatment is ineffective are often called negative control populations or placebo groups. They are leveraged to detect bias in different disciplines. Here we present formal criteria that justify the use of negative control populations to rule out unmeasured confounding and mechanistic (direct) causal effects. We further argue that negative control populations, satisfying our formal conditions, are available in many settings, spanning from clinical studies of infectious diseases to epidemiologic studies of public health interventions. Negative control populations can also be used to rule out placebo effects in unblinded randomized experiments. As a case study, we evaluate the effect of mobile stroke unit dispatches on functional outcomes at discharge in individuals with suspected stroke, using data from a large trial. Our analysis supports the hypothesis that mobile stroke units improve functional outcomes in these individuals.

Do statistical heterogeneity methods impact the results of meta- analyses? A meta epidemiological study.

BACKGROUND: Orthodontic systematic reviews (SRs) use different methods to pool the individual studies in a meta-analysis when indicated. However, the number of studies included in orthodontic meta-analyses is relatively small. This study aimed to evaluate the direction of estimate changes of orthodontic meta-analyses (MAs) using different between-study variance methods considering the level of heterogeneity when few trials were pooled. METHODS: Search and study selection: Systematic reviews (SRs) published over the last three years, from the 1st of January 2020 to the 31st of December 2022, in six main orthodontic journals with at least one MA pooling five or lesser primary studies were identified. Data collection and analysis: Data were extracted from each eligible MA, which was replicated in a random effect model using DerSimonian and Laird (DL), Paule-Mandel (PM), Restricted maximum-likelihood (REML), Hartung Knapp and Sidik Jonkman (HKSJ) methods. The results were reported using median and interquartile range (IQR) for continuous data and frequencies for categorical data and analyzed using non-parametric tests. The Boruta algorithm was used to assess the significant predictors for the significant change in the confidence interval between the different methods compared to the DL method, which was only feasible using the HKSJ method. RESULTS: 146 MAs were included, most applying the random effect model (n = 111; 76%) and pooling continuous data using mean difference (n = 121; 83%). The median number of studies was three (range 2, 4), and the overall statistical heterogeneity (I2 ranged from 0 to 99% with a median of 68%). Close to 60% of the significant findings became non-significant when HKSJ was applied compared to the DL method and when the heterogeneity was present I2>0%. On the other hand, 30.43% of the non-significant meta-analyses using the DL method became significant when HKSJ was used when the heterogeneity was absent I2 = 0%. CONCLUSION: Orthodontic MAs with few studies can produce different results based on the between-study variance method and the statistical heterogeneity level. Compared to DL, HKSJ method is overconservative when I2 is greater than 0% and may result in false positive findings when the heterogeneity is absent.

The impact of blinding on estimated treatment effects in randomized clinical trials on acupuncture: A meta-epidemiological study.

OBJECTIVE: To evaluate the sole impact of blinding patients and outcome assessors in acupuncture randomized controlled trials (RCTs) on treatment effects while considering the type of outcome measures. METHODS: We searched databases for the meta-analyses on acupuncture with both blinded and non-blinded RCTs. Mixed-effects meta-regression models estimated the average ratio of odds ratios (ROR) and differences in standardized mean differences (dSMD) for non-blinded RCTs versus blinded mixed-effects meta-regression model. RESULTS: The study included 96 meta-analyses (1012 trials). The average ROR for lack of patient blinding was 1.08 (95% confidence intervals 0.79-1.49) in 18 meta-analyses with binary patient-reported outcomes. The average ROR for lack of outcome assessor blinding was 0.98 (0.77-1.24) in 43 meta-analyses with binary subjective outcomes. The average dSMD was -0.38 (-0.96 to 0.20) in 10 meta-analyses with continuous patient-reported outcomes. The average dSMD was -0.13 (-0.45 to 0.18) in 25 meta-analyses with continuous subjective outcomes. The results of the subgroup analysis were consistent with the primary analysis findings. CONCLUSIONS: Blinding of participants and outcome assessors does not significantly influence acupuncture treatment efficacy. It underscores the practical difficulties of blinding in acupuncture RCTs and the necessity to distinguish between trials with and without successful blinding to understand treatment expectations' effects. Enhancing blinding procedures' quality and assessment in future research is crucial for improving RCTs' internal validity and reliability.

Evaluating ChatGPT-4.0's data analytic proficiency in epidemiological studies: A comparative analysis with SAS, SPSS, and R.

Background: OpenAI's Chat Generative Pre-trained Transformer 4.0 (ChatGPT-4), an emerging artificial intelligence (AI)-based large language model (LLM), has been receiving increasing attention from the medical research community for its innovative 'Data Analyst' feature. We aimed to compare the capabilities of ChatGPT-4 against traditional biostatistical software (i.e. SAS, SPSS, R) in statistically analysing epidemiological research data. Methods: We used a data set from the China Health and Nutrition Survey, comprising 9317 participants and 29 variables (e.g. gender, age, educational level, marital status, income, occupation, weekly working hours, survival status). Two researchers independently evaluated the data analysis capabilities of GPT-4's 'Data Analyst' feature against SAS, SPSS, and R across three commonly used epidemiological analysis methods: Descriptive statistics, intergroup analysis, and correlation analysis. We used an internally developed evaluation scale to assess and compare the consistency of results, analytical efficiency of coding or operations, user-friendliness, and overall performance between ChatGPT-4, SAS, SPSS, and R. Results: In descriptive statistics, ChatGPT-4 showed high consistency of results, greater analytical efficiency of code or operations, and more intuitive user-friendliness compared to SAS, SPSS, and R. In intergroup comparisons and correlational analyses, despite minor discrepancies in statistical outcomes for certain analysis tasks with SAS, SPSS, and R, ChatGPT-4 maintained high analytical efficiency and exceptional user-friendliness. Thus, employing ChatGPT-4 can significantly lower the operational threshold for conducting epidemiological data analysis while maintaining consistency with traditional biostatistical software's outcome, requiring only specific, clear analysis instructions without any additional operations or code writing. Conclusions: We found ChatGPT-4 to be a powerful auxiliary tool for statistical analysis in epidemiological research. However, it showed limitations in result consistency and in applying more advanced statistical methods. Therefore, we advocate for the use of ChatGPT-4 in supporting researchers with intermediate experience in data analysis. With AI technologies like LLMs advancing rapidly, their integration with data analysis platforms promises to lower operational barriers, thereby enabling researchers to dedicate greater focus to the nuanced interpretation of analysis results. This development is likely to significantly advance epidemiological and medical research.

Substance addictions and suicidal thoughts and behaviors: Evidence from a multi-wave epidemiological study.

Substance addiction (SA) is a risk factor of suicidal thoughts and behaviors (STB), although it is still unclear which SAs are reliably associated with increased risk for suicidal ideation, planning, and attempt. The current study aimed to meet this goal using data from the National Survey on Drug Use and Health (NSDUH) referring to years from 2008 to 2020. The information extracted included sociodemographic and contextual information, eleven SAs (e.g., nicotine, alcohol, marijuana, cocaine, pain relievers, heroin, inhalants, hallucinogens, sedatives, stimulants, and tranquillizers), and STB. The analysis revealed that SAs for alcohol, pain relievers, marijuana, and cocaine were stable and reliable predictors for STB (e.g., suicidal ideation, planning, and attempt), while cocaine was not a stable predictor for suicide attempt. The selected SAs model showed a greater predictive accuracy than only sociodemographic and contextual factors as well as not selected SAs. Moreover, selected SAs showed comparable predictive accuracy to the full model. Furthermore, SA to alcohol showed to be an extremely effective predictor of STB, having a comparable predictive accuracy to all the other ten SAs together. In conclusion, SAs to pain relievers, alcohol, marijuana, and cocaine can be considered as important risk factors for concurrent STB.

Drug utilization in patients starting haemodialysis with a focus on cardiovascular and antidiabetic medications: an epidemiological study in the Lazio region (Italy), 2016-2020.

BACKGROUND: Entering dialysis is a critical moment in patients' healthcare journey, and little is known about drug therapy around it. A study funded by the Italian Medicines Agency offered the opportunity to leverage data from the Lazio Regional Dialysis and Transplant Registry (RRDTL) and perform an observational study on drug use patterns before and after initiating chronic dialysis. METHODS: Individuals initiating dialysis in 2016-2020 were identified from RRDTL, excluding patients with prior renal transplantation, stopping dialysis early, or dying within 12 months. Use of study drugs, predefined by clinicians, in the two years around the index date was retrieved from the drug claims register and described by semester. For each drug group, proportions of users (min 2 claims in 6 months) by semester, and intensity of treatment in terms of Defined Daily Doses (DDDs) for cardiovascular and antidiabetic agents were compared across semesters, stratifying by sex and age. RESULTS: In our cohort of 3,882 patients we observed a general increase in drug use after initiating dialysis, with the mean number rising from 5.5 to 6.2. Cardiovascular agents accounted for the highest proportions, along with proton pump inhibitors and antithrombotics over all semesters. Dialysis-specific therapies showed the most evident increase, in particular anti-anaemics (iron 4-fold, erythropoietins almost 2-fold), anti-parathyroids (6-fold), and chelating agents (4-fold). Use of cardiovascular and antidiabetic drugs was characterised by significant variations in terms of patterns and intensity, with some differences between sexes and age groups. CONCLUSIONS: Entering dialysis is associated with increased use of specific drugs and goes along with adaptations of chronic therapies.

Recommendations for effective collaboration and capacity building in epidemiological studies on the effect of alcohol and drug use on traffic safety in low- and middle-income countries.

OBJECTIVE: Alcohol or drug impairment is a major risk factor for road traffic crashes, and studies on this issue are essential to provide evidence-based data for policymakers. In low- and middle-income countries (LMICs), such studies are often conducted in partnership with one or more organizations in high-income countries (HICs). The aim of this article is to provide recommendations for improving project planning and decision-making processes in epidemiological studies on alcohol, drug and traffic safety in LMICs involving HICs. METHODS: We searched Pubmed, Google Scholar, and Google Search for articles and reports in English about lessons learned when conducting collaborative research in LMIC as well as papers presenting recommendations for effective research collaboration with partners in LMICs. RESULTS: Based on the search results, we selected 200 papers for full text examination. Few were related to studies on the effect of alcohol or drug use on road traffic safety. However, several conclusions and recommendations from other studies were found to be relevant. We combined the findings with our own experience in a narrative review. We also present a checklist for risk and quality assessment. CONCLUSIONS: Many papers presented similar recommendations, which included the importance of addressing local needs, ensuring adequate resources, local project ownership and leadership, establishing strong partnerships among all involved stakeholders, promoting shared decision-making and planning, and implementing strategies to translate research findings into policy, practice, and publications. It is also important to avoid HIC bias, which prioritizes the interests or perspectives of HICs over those of LMICs.