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Statistical testing in medicine is a controversial and commonly misunderstood topic. Despite decades of efforts by renowned associations and international experts, fallacies such as nullism, the magnitude fallacy, and dichotomania are still widespread within clinical and epidemiological research. This can lead to serious health errors (e.g., misidentification of adverse reactions). In this regard, our work sheds light on another common interpretive and cognitive error: the fallacy of high significance, understood as the mistaken tendency to prioritize findings that lead to low p-values. Indeed, there are target hypotheses (e.g., a hazard ratio of 0.10) for which a high p-value is an optimal and desirable outcome. Accordingly, we propose a novel method that goes beyond mere null hypothesis testing by assessing the statistical surprise of the experimental result compared to the prediction of several target assumptions. Additionally, we formalize the concept of interval hypotheses based on prior information about costs, risks, and benefits for the stakeholders (NORD-h protocol). The incompatibility graph (or surprisal graph) is adopted in this context. Finally, we discuss the epistemic necessity for a descriptive, (quasi) unconditional approach in statistics, which is essential to draw valid conclusions about the consistency of data with all relevant possibilities, including study limitations. Given these considerations, this new protocol has the potential to significantly impact the production of reliable evidence in public health.

Abstract Background Healthcare providers (HCPs) practice and correct management of suspected malaria (CMSM) are central components of malaria elimination and prevention of re-establishment (POR) in countries in the elimination phase. However, knowledge of malaria surveillance systems and HCPs practices often wanes in countries aiming to eliminate malaria due to the low numbers of cases. The study aimed to implement a valid Simulated Malaria Online Tool (SMOT) for assessment HCP performance in CMSM and POR in a malaria-free area. Methods HCPs were evaluated using SMOT tool based on four criteria including presenting a suspected malaria case for detection of HCPs’ failures in recognition (a), diagnosis (b), appropriate treatment (c), and urgent reporting (d); and compared with simulated patients (SP). Multiple logistic regression analysis was carried out to estimate adjusted odds ratios (ORs) for the risk of HCPs failures. Results The overall failure proportion was 237 (83%), and the majority of failures were in recognition (a). There was no significant difference between the SMOT and SP based on all failure criteria (P > 0.05). The private clinic (93%) and the public specialized clinic (70%) had the highest and lowest failure proportions. After passing the recognition stage (a), the overall failure proportions decreased to 47.8% and 25.0% for total HCPs and infectious disease specialists, respectively. In the final analysis, private sector (AOR = 4.36: 1.25–15.2), not-specialist providers (AOR = 2.84: 1.29–6.25) and HCPs with ≥ 5 years’ experience (AOR = 2.03: 1.01–6.25) increased the risk of failure. Conclusion Findings confirmed the implementation of SMOT tool in settings where malaria transmission is low or interrupted. The tool is able to identify sub-groups of providers needing strengthening, and contributes to the prevention of malaria re-establishment.

BackgroundSelf-rated health (SRH) is a single-item subjective indicator that asks individuals to assess their overall health and acts as a good indicator to reveal general health status. This study aimed to determine the SRH status and determining factors.MethodsThis was a population-based cross sectional study conducted in Ilam city (West of Iran) in 2023. A total of 1,370 people were invited to participate in the study using multi-stage stratified cluster random sampling method. Demographic and SRH status data were collected by face-to-face interview. SRH was indicated by a single question in five scales of very good, good, fair, poor and very poor. Multiple ordinal logistic regression was used for data analysis.ResultsThe 59.38% (95% CI: 56.76 to 62) participants reported a good SRH status. By ordinal multiple logistic regression, odds ratio (OR) and 95% confidence interval (CI) was calculated and based on that, female gender [OR: 1.68 (1.29 to 2.20)], not having insurance coverage [OR: 1.35; (1.01 to 1.80)], history of job loss [OR: 1.72; (1.28 to 2.31)], hopelessness for the future [OR: 5.07; (3.96 to 6.49)], and having underlying diseases [OR: 2.95; (2.25 to 3.88)], were positively associated with poor SRH status. The Kurd race [OR: 0.45; (0.25 to 0.78)], higher economic status [OR: 0.72; (0.54 to 0.96)] and use of health care service [OR: 0.68; (0.53 to 0.88)] were negatively associated with poor SRH status. The most effective variables for poor SRH status were hopelessness about the future and suffering from underlying diseases.ConclusionIt is important to devise corrective measures and effective public health policies to address causes and factors associated with poor SRH. It is also necessary for local health officials to allocate financial resources and introduce other kinds of supportive initiatives to provide targeted support for those who are struggling with poverty and suffering chronic diseases.

In medical research, some variables are conditionally defined on some levels of another variable, leading to conditional missing data. Imputation of this type of structural missing data is needed given inefficiency of listwise deletion inherent in regression modeling. Using some examples, we illustrate handling of conditional missing values using simple imputation procedures in etiologic and prediction research.

As widely noted in the literature and by international bodies such as the American Statistical Association, severe misinterpretations of P-values, confidence intervals, and statistical significance are sadly common in public health. This scenario poses serious risks concerning terminal decisions such as the approval or rejection of therapies. Cognitive distortions about statistics likely stem from poor teaching in schools and universities, overly simplified interpretations, and – as we suggest – the reckless use of calculation software with predefined standardized procedures. In light of this, we present a framework to recalibrate the role of frequentist-inferential statistics within clinical and epidemiological research. In particular, we stress that statistics is only a set of rules and numbers that make sense only when properly placed within a well-defined scientific context beforehand. Practical examples are discussed for educational purposes. Alongside this, we propose some tools to better evaluate statistical outcomes, such as multiple compatibility or surprisal intervals or tuples of various point hypotheses. Lastly, we emphasize that every conclusion must be informed by different kinds of scientific evidence (e.g., biochemical, clinical, statistical, etc.) and must be based on a careful examination of costs, risks, and benefits.

Abstract There are some discrepancies about the superiority of the off-pump coronary artery bypass grafting (CABG) surgery over the conventional cardiopulmonary bypass (on-pump). The aim of this study was estimating risk ratio of mortality in the off-pump coronary bypass compared with the on-pump using a causal model known as collaborative targeted maximum likelihood estimation (C-TMLE). The data of the Tehran Heart Cohort study from 2007 to 2020 was used. A collaborative targeted maximum likelihood estimation and targeted maximum likelihood estimation, and propensity score (PS) adjustment methods were used to estimate causal risk ratio adjusting for the minimum sufficient set of confounders, and the results were compared. Among 24,883 participants (73.6% male), 5566 patients died during an average of 8.2 years of follow-up. The risk ratio estimates (95% confidence intervals) by unadjusted log-binomial regression model, PS adjustment, TMLE, and C-TMLE methods were 0.86 (0.78–0.95), 0.88 (0.80–0.97), 0.88 (0.80–0.97), and 0.87(0.85–0.89), respectively. This study provides evidence for a protective effect of off-pump surgery on mortality risk for up to 8 years in diabetic and non-diabetic patients.

Background and purpose: An unintended pregnancy denotes a conception that occurs without prior planning or intention by the couple involved. The repercussions of such pregnancies can be substantial for both the mother and the child, potentially resulting in inadvertent neglect of fetal health and influencing the quality of caregiving behaviors. These factors may contribute to adverse outcomes, such as low birth weight. This research aims to assess the impact of unintended pregnancy on newborn anthropometric parameters within the marginal neighborhoods of Bandar Abbas. Materials and methods: This study is a component of a prospective cohort project involving pregnant women residing in marginalized areas of Bandar Abbas City in 2015. A total of 1351 participants were enrolled in the cohort project, with 825 individuals included in this investigation. Among these, 132 were categorized into the exposure group representing unintended pregnancies, while 693 comprised the non-exposure (control) group, based on the proportion of unintended pregnancies in the original dataset. Our study delineates the associations between birth weight, height, head circumference, and the primary exposure variable of maternal unintended pregnancy. Data collection on unintended pregnancy and potential confounding factors was conducted through questionnaires and face-to-face interviews during the initial cohort visit, coinciding with the women's pregnancies. Confounding variables pertinent to each outcome were rigorously evaluated utilizing a causal analysis approach, facilitated by the dagitty software, with data management performed using SPSS version 24. Univariate analysis involved the utilization of Pearson's correlation coefficient, independent t-tests, and one-way analysis of variance to explore the relationships between anthropometric indices and individual characteristics. Meanwhile, multivariate analysis entailed the application of multiple linear regression techniques. Results: Among the total of 1351 pregnancies investigated, 219 (16.2%) were identified as unintended. The mean age of mothers experiencing unintended pregnancies was 29.23±6.49 years, compared to 26.98±5.31 years for those with intended pregnancies. For unintended pregnancies, the mean and standard deviation of birth weight, height, and head circumference were calculated as 3059.24±501.11 grams, 48.52±3.11 cm, and 33.80±2.22 cm, respectively. Conversely, for intended pregnancies, these measures were 3080±17.17 grams, 48.63±2.65 cm, and 33.82±1.92 cm, respectively. Statistically significant positive correlations were observed between birth weight and maternal age (P=0.041, r=0.056), paternal age (P=0.008, r=0.073), and maternal BMI (P

Summary: Background: The first 1000 days of life are critical for a child's health and development. Impaired growth during this period is linked to increased child morbidity, mortality, and long-term consequences. Undernutrition is the main cause, and addressing it within the first 1000 days of life is vital. Maternal education is consistently identified as a significant predictor of child undernutrition, but its specific impact remains to be determined. This study presents a systematic review and meta-analysis investigating the influence of high versus low maternal education levels on child growth from birth to age two, using population-based cohort studies. Methods: Databases including PubMed, Scopus, EMBASE, Web of Science, ERIC, and Google Scholar were searched from January 1990 to January 2024 using appropriate search terms. We included population-based cohort studies of healthy children aged two years and under and their mothers, categorizing maternal education levels. Child growth and nutritional outcomes were assessed using various indicators. Two reviewers independently conducted data extraction and assessed study quality. The Newcastle Ottawa scale was utilized for quality assessment. Random-effects models were used for meta-analysis, and heterogeneity was assessed using the Cochrane Q and I2 statistic. Subgroup and sensitivity analyses were performed, and publication bias was evaluated. Findings: The literature search retrieved 14,295 titles, and after full-text screening of 639 reports, 35 studies were included, covering eight outcomes: weight for age z-score (WAZ), height for age z-score (HAZ), BMI for age z-scores (BMIZ), overweight, underweight, stunting, wasting, and rapid weight gain. In middle-income countries, higher maternal education is significantly associated with elevated WAZ (MD 0.398, 95% CI 0.301–0.496) and HAZ (MD 0.388, 95% CI 0.102–0.673) in children. Similarly, in studies with low-educated population, higher maternal education is significantly linked to increased WAZ (MD 0.186, 95% CI 0.078–0.294) and HAZ (0.200, 95% CI 0.036–0.365). However, in high-income and highly educated population, this association is either absent or reversed. In high-income countries, higher maternal education is associated with a non-significant lower BMI-Z (MD −0.028, 95% CI −0.061 to 0.006). Notably, this inverse association is statistically significant in low-educated populations (MD −0.045, 95% CI −0.079 to −0.011) but not in highly educated populations (MD 0.003, 95% CI −0.093 to 0.098). Interpretation: Maternal education's association with child growth varies based on country income and education levels. Further research is needed to understand this relationship better. Funding: This study was a student thesis supported financially by Tehran University of Medical Sciences (TUMS).

Abstract Aim To determine inequality and decompose it’s in Self-Rated Health (SRH). Method This population-based cross-sectional study was undertaken on the entire population of the city of Ilam, Iran, in 2023. Multi-stage stratified cluster random sampling with proportion-to-size approach was used to select the participants. Oaxaca-Blinder decomposition technique was used to show the amount of inequity in SRH and to decompose of the gap of SRH between the poor and the rich group of participants. Results 1370 persons participated in the study. The 59.38% of participants stated good SRH status and just 8.86% of participants had poor SRH status. The results of the Oaxaca-Blinder decomposition revealed a considerable gap (15.87%) in the poor status of SRH between the rich and the poor. A large proportion (89.66%) of this difference was described by explained portion of the model. The results of decomposition showed that economic status was directly responsible for explaining 27.98% of overall inequality gap between rich and poor people. Moreover, hopelessness to future (32.64%), having an underlying disease (18.34%) and difference in the education level (10.71%) were associated with an increase in inequality disfavoring the poor. Conclusion For people suffering from underlying disease, it is suggested to devise policies to improve access to/and remove healthcare utilization barriers. To address hopelessness to future, it is recommended to carry out further studies to reveal factors which affect it in more details. This can help policy makers to formulate more realistic and evidence-informed policies on order to lessen the current socioeconomic inequity in SRH.

Abstract Background The prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis. Methods In this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005–2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014–2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set. Results Based on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome. Conclusions Based on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.

Abstract Purpose This study was conducted to evaluate the effect of alcohol consumption on breast cancer, adjusting for alcohol consumption misclassification bias and confounders. Methods This was a case-control study of 932 women with breast cancer and 1000 healthy control. Using probabilistic bias analysis method, the association between alcohol consumption and breast cancer was adjusted for the misclassification bias of alcohol consumption as well as a minimally sufficient set of adjustment of confounders derived from a causal directed acyclic graph. Population attributable fraction was estimated using the Miettinen’s Formula. Results Based on the conventional logistic regression model, the odds ratio estimate between alcohol consumption and breast cancer was 1.05 (95% CI: 0.57, 1.91). However, the adjusted estimates of odds ratio based on the probabilistic bias analysis ranged from 1.82 to 2.29 for non-differential and from 1.93 to 5.67 for differential misclassification. Population attributable fraction ranged from 1.51 to 2.57% using non-differential bias analysis and 1.54–3.56% based on differential bias analysis. Conclusion A marked measurement error was in self-reported alcohol consumption so after correcting misclassification bias, no evidence against independence between alcohol consumption and breast cancer changed to a substantial positive association.

Abstract Background Hypertension (HTN) and diabetes mellitus (DM) as part of non-communicable diseases are among the most common causes of death worldwide, especially in the WHO’s Eastern Mediterranean Region (EMR). The family physician program (FPP) proposed by WHO is a health strategy to provide primary health care and improve the community’s awareness of non-communicable diseases. Since there was no clear focus on the causal effect of FPP on the prevalence, screening, and awareness of HTN and DM, the primary objective of this study is to determine the causal effect of FPP on these factors in Iran, which is an EMR country. Methods We conducted a repeated cross-sectional design based on two independent surveys of 42,776 adult participants in 2011 and 2016, of which 2301 individuals were selected from two regions where the family physician program was implemented (FPP) and where it wasn't (non-FPP). We used an Inverse Probability Weighting difference-in-differences and Targeted Maximum Likelihood Estimation analysis to estimate the average treatment effects on treated (ATT) using R version 4.1.1. Results The FPP implementation increased the screening (ATT = 36%, 95% CI: (27%, 45%), P-value

[This corrects the article DOI: 10.1371/journal.pone.0279976.].

IntroductionThe Dietary Inflammatory Index (DII) is a composite nutritional index that has gained significant attention in the past decade due to its association with physical and mental well-being. To accurately assess the precise effects of DII on health outcomes, the effects of nutrients and foods need to be adjusted. This study aimed to investigate the association between DII and mental disorders (depression, anxiety, and stress) using multilevel modeling to minimize the bias of the previous methods.MethodsThis cross-sectional analytical study was conducted using data from the initial phase of the Tehran University of Medical Sciences Employees’ Cohort Study (TEC). Nutritional information was obtained through a dish-based semi-quantitative food frequency questionnaire (DFQ), while psychological data were collected using the depression, anxiety and stress scale (DASS-42). The acquired data were analyzed using multilevel modeling in three levels (foods, nutrients, and DII, respectively) through GLIMMIX in the SAS software.ResultsA total of 3,501 individuals participated in this study. The results of the multilevel model demonstrated a significant statistical association between DII and mental disorders after adjusting for baseline characteristics, nutrients and foods. For each unit increase in DII, the mean scores for stress, anxiety, and depression increased by 3.55, 4.26, and 3.02, respectively (p

Introduction: Opium and cigarette smoking have been identified as significant cancer risk factors. Recently, the International Agency for Research on Cancer (IARC) classified opium as a Group 1 carcinogen in 2020. Method: Using data from a multicenter case-control study in Iran called IROPICAN, involving 717 cases of bladder cancer and 3477 controls, we assessed the interactions on the causal additive scale between opium use and cigarette smoking and their attributing effects to evaluate public health relevance and test for different mechanistic interaction forms to provide new insights for developing of bladder cancer. A minimally sufficient set of confounders was identified using a causal directed acyclic graph, and the data were analysed employing multiple logistic regression and the inverse probability-of-treatment weighting estimator of the marginal structural linear odds model. Results: Our findings indicated a significant increase in the risk of bladder cancer associated with concurrent opium use and cigarette smoking (adjusted OR = 6.34, 95 % CI 5.02–7.99; p

Background: Causal directed acyclic graphs (cDAGs) are frequently used to identify confounding and collider bias. We demonstrate how to use causal directed acyclic graphs to adjust for collider bias in the hospitalized Covid-19 setting. Materials and methods: According to the cDAGs, three types of modeling have been performed. In model 1, only vaccination is entered as an independent variable. In model 2, in addition to vaccination, age is entered the model to adjust for collider bias due to the conditioning of hospitalization. In model 3, comorbidities are also included for adjustment of collider bias due to the conditioning of hospitalization in different biasing paths intercepting age and comorbidities. Results: There was no evidence of the effect of vaccination on preventing death due to Covid-19 in model 1. In the second model, where age was included as a covariate, a protective role for vaccination became evident. In model 3, after including chronic diseases as other covariates, the protective effect was slightly strengthened. Conclusion: Studying hospitalized patients is subject to collider-stratification bias. Like confounding, this type of selection bias can be adjusted for by inclusion of the risk factors of the outcome which also affect hospitalization in the regression model.

Background: COVID-19 is associated with severe pneumonia lung damage, acute respiratory distress syndrome (ARDS), and mortality. In this study, we aimed to compare corticosteroids' effect on the mortality risk in patients hospitalized with COVID-19. Methods: PubMed, Web of Science, Scopus, Cochrane Library, and Embase, were searched using a predesigned search strategy. Randomized controlled trials (RCTs) that had compared the corticosteroid drugs were included. The hazard ratio (HR) with a 95% confidence interval (CI) was used to summarize the effect size from the network meta-analysis (NMA). Results: Out of 329 retrieved references, 12 RCTs with 11,455 participants met the eligibility criteria in this review. The included RCTs formed one network with six treatments. In addition, five treatments in two RCTs were not connected to the network. Methylprednisolone + usual care (UC) versus UC decreased the risk of death by 0.65 (95% CI: 0.47, 0.90). Among treatments in the network the highest P-score (0.89) was related to Methylprednisolone + UC. Conclusion: Based on the results of this NMA it seems Methylprednisolone + UC to be the best treatment option in patients with COVID-ARDS and COVID pneumonia.

Abstract Previous analysis of the action to control cardiovascular risk in diabetes showed an increased risk of mortality among patients receiving intensive glucose lowering therapy using conventional regression method with intention to treat approach. This method is biased when time-varying confounder is affected by the previous treatment. We used 15 follow-up visits of ACCORD trial to compare the effect of time-varying intensive vs. standard treatment of glucose lowering drugs on cardiovascular and mortality outcomes in diabetic patients. The treatment effect was estimated using G-estimation and compared with accelerated failure time model using two modeling strategies. The first model adjusted for baseline confounders and the second adjusted for both baseline and time-varying confounders. While the hazard ratio of all-cause mortality for intensive compared to standard therapy in AFT model adjusted for baseline confounders was 1.17 (95% CI 1.01–1.36), the result of time-dependent AFT model was compatible with both protective and risk effects. However, the hazard ratio estimated by G-estimation was 0.64 (95% CI 0.39–0.92). The results of this study revealed a protective effect of intensive therapy on all-cause mortality compared with standard therapy in ACCORD trial.

Abstract Background The main objective of this study was to construct and validate a composite socioeconomic status indicator containing material capital, human capital, and social capital (CAPSES scale) and also appropriate it for CVDs in a large population-based study. Methods This cross-sectional study, the Urban HEART-2 project, was conducted in Tehran, Iran, in 2011. A total of 34,116 households covering 118,542 individuals were assessed in this study. A 14-parts questionnaire was completed for all selected households. All the gathered data were based on the participants’ self-reports. Literacy, wealth index, expenditure, skill level, and Townsend index were used as SES indexes. CVDs, including Hypertension, Myocardial infarction, and stroke, were considered the main outcomes. A structural equation model (SEM) was used to construct a CAPSES scale and a composition index of SES. Criterion validity and Construct validity were used to assess this scale. Results A total of 91,830 subjects consisting of 33,884 (49%) men were included in this analysis. The mean age of the participants was 41.5 ± 11.37 years. Among the assessed participants, 5904(6.4%) reported hypertension, 1507(1.6%) myocardial infarction, and 407(0.4%) strokes. The overall weighted prevalence of self-reported cardiovascular events (hypertension, stroke, and MI) was 8.03% (95%CI: 7.8–8.2). Inverse associations were seen between the CAPSES scale and its domains with CVDs, adjusted for sex, age, BMI, smoking, and diabetes by a multiple logistic regression model. Conclusion The CAPSES scale was significantly associated with stroke and hypertension. Our findings showed that the CAPSES index could be useful for public health research.

Abstract Background Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15–59 years across SSA. Methods We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. Results We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. Conclusions As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.

Abstract Background Identifying breast cancer risk factors is a critical component of preventative strategies for this disease. This study aims to identify modifiable and non-modifiable risk factors of breast cancer in Iranian women. Methods We used international databases (PubMed/Medline, Scopus, Web of Knowledge, and Embase) and national databases (SID, Magiran, and ISC) to retrieve relevant studies until November 13, 2022. The odds ratio (OR) with a 95% confidence interval using the random-effect model was used to estimate the pooled effect. The publication bias was assessed by the Egger and Begg test. A sensitivity analysis was conducted to evaluate the effect of each included study on the final measurement. Results Of the 30,351 retrieved articles, 24 matched case–control records were included with 12,460 participants (5675 newly diagnosed cases of breast cancer and 6785 control). This meta-analysis showed that of the known modifiable risk factors for breast cancer, obesity (vs normal weight) had the highest risk (OR = 2.17, 95% CI 1.47 to 3.21; I 2 = 85.7) followed by age at marriage (25–29 vs

Summary: Background: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. Funding: The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38).

BackgroundBreast cancer (BC) is the most common cancer in women globally. The North Africa and Middle East (NAME) region is coping hard with the burden of BC. We aimed to present the latest epidemiology of BC and its risk factors in this region.MethodsWe retrieved the data on BC burden and risk factors from the Global Burden of Disease Study 2019 to describe BC status in the 21 countries of the NAME region from 1990 to 2019. We explored BC incidence, prevalence, deaths, disability-adjusted life years (DALYs), and attributable burden to seven risk factors of female BC, namely, alcohol use, diet high in red meat, low physical activity, smoking, secondhand smoke, high body mass index, and high fasting plasma glucose. Decomposition analysis on BC incidence trend was done to find out the contributing factors to this cancer’s growth.ResultsIn 2019, there were 835,576 (95% uncertainty interval: 741,968 to 944,851) female and 10,938 (9,030 to 13,256) male prevalent cases of BC in the NAME region. This number leads to 35,405 (30,676 to 40,571) deaths among female patients and 809 (654 to 1,002) deaths in male patients this year. BC was responsible for 1,222,835 (1,053,073 to 1,411,009) DALYs among female patients in 2019, with a greater proportion (94.9%) of burden in years of life lost (YLLs). The major contributor to female BC incidence increase in the past three decades was found to be increase in age-specific incidence rates of BC (227.5%), compared to population growth (73.8%) and aging (81.8%). The behavioral risk factors were responsible for majority of attributable female BC burden (DALYs: 106,026 [66,614 to 144,247]). High fasting plasma glucose was found to be the risk factor with the largest effect (DALYs: 84,912 [17,377 to 192,838]) on female BC burden.ConclusionThe increasing incidence and burden of BC in the NAME region is remarkable, especially when considering limited resources in the developing countries of this region. Proper policies like expanding screening programs and careful resource management are needed to effectively manage BC burden.

Leukaemia is a dangerous malignancy that causes thousands of deaths every year throughout the world. The rate of morbidity and mortality is significant despite many advancements in therapy strategies for affected individuals. Most antitumour medications used now in clinical oncology use apoptotic signalling pathways to induce cancer cell death. Accumulated data have shown a direct correlation between inducing apoptosis in cancer cells with higher tumour regression and survival. Until now, the efficacy of melatonin as a powerful antitumour agent has been firmly established. A change in melatonin concentrations has been reported in multiple tumours such as endometrial, hematopoietic, and breast cancers. Findings show that melatonin’s anticancer properties, such as its prooxidation function and ability to promote apoptosis, indicate the possibility of utilizing this natural substance as a promising agent in innovative cancer therapy approaches. Melatonin stimulates cell apoptosis via the regulation of many apoptosis facilitators, including mitochondria, cytochrome c, Bcl-2, production of reactive oxygen species, and apoptosis receptors. This paper aimed to further assess the anticancer effects of melatonin through the apoptotic pathway, considering the role that cellular apoptosis plays in the pathogenesis of cancer. The effect of melatonin may mean that it is appropriate for use as an adjuvant, along with other therapeutic approaches such as radiotherapy and chemotherapy.

Abstract Background The alertness and practice of health care providers (HCPs) in the correct management of suspected malaria (CMSM) (vigilance) is a central component of malaria surveillance following elimination, and it must be established before malaria elimination certification can be granted. This study was designed to develop and validate a rapid tool, Simulated Malaria Online Tool (SMOT), to evaluate HCPs’ practice in relation to the CMSM. Methods The study was conducted in East Azerbaijan Province, Islamic Republic of Iran, where no malaria transmission has been reported since 2005. An online tool presenting a suspected malaria case for detection of HCPs’ failures in recognition, diagnosis, treatment and reporting was developed based on literature review and expert opinion. A total of 360 HCPs were allocated to two groups. In one group their performance was tested by simulated patient (SP) methodology as gold standard, and one month later by the online tool to allow assessment of its sensitivity. In the other group, they were tested only by the online tool to allow assessment of any possible bias incurred by the exposure to SPs before the tool. Results The sensitivity of the tool was (98.7%; CI 93.6–99.3). The overall agreement and kappa statistics were 96.6% and 85.6%, respectively. In the group tested by both methods, the failure proportion by SP was 86.1% (CI 80.1–90.8) and by tool 87.2% (CI 81.4–91.7). In the other group, the tool found 85.6% (CI 79.5–90.3) failures. There were no significant differences in detecting failures within or between the groups. Conclusion The SMOT tool not only showed high validity for detecting HCPs’ failures in relation to CMSM, but it had high rates of agreement with the real-world situation, where malaria transmission has been interrupted. The tool can be used by program managers to evaluate HCPs’ performance and identify sub-groups, whose malaria vigilance should be strengthened. It could also contribute to the evidence base for certification of malaria elimination, and to strengthening prevention of re-establishment of malaria transmission.

Background Recent evidence recommended stepwise screening methods for identifying individuals at high risk of type 2 diabetes to be recruited in the lifestyle intervention programs for the prevention of the disease. This study aims to assess the performance of different stepwise screening methods that combine non-invasive measurements with lab-based measurements for identifying those with 5-years incident type 2 diabetes. Methods 3037 participants aged ≥30 years without diabetes at baseline in the Tehran Lipid and Glucose Study (TLGS) were followed. Thirty-two stepwise screening methods were developed by combining a non-invasive measurement (an anthropometric measurement (waist-to-height ratio, WtHR) or a score based on a non-invasive risk score [Australian Type 2 Diabetes Risk Assessment Tool, AUSDRISK]) with a lab-based measurement (different cut-offs of fasting plasma glucose [FPG] or predicted risk based on three lab-based prediction models [Saint Antonio, SA; Framingham Offspring Study, FOS; and the Atherosclerosis Risk in Communities, ARIC]). The validation, calibration, and usefulness of lab-based prediction models were assessed before developing the stepwise screening methods. Cut-offs were derived either based on previous studies or decision-curve analyses. Results 203 participants developed diabetes in 5 years. Lab-based risk prediction models had good discrimination power (area under the curves [AUCs]: 0.80-0.83), achieved acceptable calibration and net benefits after recalibration for population’s characteristics and were useful in a wide range of risk thresholds (5%-21%). Different stepwise methods had sensitivity ranged 20%-68%, specificity 70%-98%, and positive predictive value (PPV) 14%-46%; they identified 3%-33% of the screened population eligible for preventive interventions. Conclusion Stepwise methods have acceptable performance in identifying those at high risk of incident type 2 diabetes.

IntroductionMetabolic risk factors (MRFs) predispose populations to a variety of chronic diseases with a huge burden globally. With the increasing burden of these risk factors in Iran, in this study, we aimed to report the estimated burden attributed to MRFs at national and subnational scales in Iran, from 1990 to 2019.MethodsBased on the comparative risk assessment method of the Global Burden of Disease (GBD) Study 2019, data of deaths and disability-adjusted life years (DALYs) attributable to four top MRFs in Iran including high systolic blood pressure (SBP), high fasting plasma glucose (FPG), high body mass index (BMI), and high low-density lipoprotein (LDL) for the 1990–2019 period, were extracted. The socio-demographic index (SDI) was used to report the data based on the corresponding socio-economic stratifications. The results were reported in national and subnational 31 provinces of Iran to discover disparities regarding the attributable burden to MRFs. Furthermore, we reported the causes of diseases to which the attributable burden to MRFs was related.ResultsOverall, the age-standardized high LDL, high SBP, high BMI, and high FPG-attributed death rate changed by −45.1, −35.6, +2.8, and +19.9% from 1990 to 2019, respectively. High SBP was the leading risk factor regarding attributed age-standardized death rates reaching 157.8 (95% uncertainty interval: 135.3–179.1) and DALY rates reaching 2973.4 (2652.2–3280.2) per 100,000 person-years, in 2019. All rates increased with aging, and men had higher rates except for the +70 years age group. At the subnational level, provinces in the middle SDI quintile had the highest death and DALY rates regarding all four MRFs. Total deaths, DALYs, YLLs and YLDs number by the causes of diseases linked to MRFs increased over the study period. Cardiovascular diseases, diabetes mellitus, and kidney diseases were the main causes of burden of disease attributable to MRFs.ConclusionHerein, we found divergent patterns regarding the burden of MRFs as well as disparities in different regions, sex, and age groups for each risk factor and related causes. This could provide policymakers with a clearer vision toward more appropriate decision-making and resource allocation to prevent the burden of MRFs in Iran.

Summary: Background: The objective of this study is to investigate the trends of exposure and burden attributable to the four main metabolic risk factors, including high systolic blood pressure (SBP), high fasting plasma glucose (FPG), high body-mass index (BMI), and high low-density lipoproteins cholesterol (LDL) in North Africa and the Middle East from 1990 to 2019. Methods: The data were retrieved from Global Burden of Disease Study 2019. Summary exposure value (SEV) was used for risk factor exposure. Burden attributable to each risk factor was incorporated in the population attributable fraction to estimate the total attributable deaths and disability-adjusted life-years (DALYs). Findings: While age-standardized death rate (ASDR) attributable to high-LDL and high-SBP decreased by 26.5% (18.6–35.2) and 23.4% (15.9–31.5) over 1990–2019, respectively, high-BMI with 5.1% (−9.0–25.9) and high-FPG with 21.4% (7.0–37.4) change, grew in ASDR. Moreover, age-standardized DALY rate attributed to high-LDL and high-SBP declined by 30.2% (20.9–39.0) and 25.2% (16.8–33.9), respectively. The attributable age-standardized DALY rate of high-BMI with 8.3% (−6.5–28.8) and high-FPG with 27.0% (14.3–40.8) increase, had a growing trend. Age-standardized SEVs of high-FPG, high-BMI, high-SBP, and high-LDL increased by 92.4% (82.8–103.3), 76.0% (58.9–99.3), 10.4% (3.8–18.0), and 5.5% (4.3–7.1), respectively. Interpretation: The burden attributed to high-SBP and high-LDL decreased during the 1990–2019 period in the region, while the attributable burden of high-FPG and high-BMI increased. Alarmingly, exposure to all four risk factors increased in the past three decades. There has been significant heterogeneity among the countries in the region regarding the trends of exposure and attributable burden. Urgent action is required at the individual, community, and national levels in terms of introducing effective strategies for prevention and treatment that account for local and socioeconomic factors. Funding: Bill & Melinda Gates Foundation.

AimTo determine the age- and sex-standardized prevalence and risk factors of depression, anxiety, and stress symptoms in the city of Ilam.MethodIn this population-based cross-sectional study, 1,350 people were invited using a multi-stage stratified cluster random sampling method. Depression, anxiety, and stress symptoms were measured using the DASS-21 standard questionnaire. For data analysis, multiple ordinal logistic regression was used in Stata version 12 software. A significance level of 5% was considered.ResultsThe data of 1,431 people were analyzed. The age- and sex-standardized prevalence (95% CI) of severe depression, anxiety, and stress symptoms was 19.90% (17.64 to 22.16), 25.95% (23.48 to 28.43), and 15.75% (13.69 to 17.81), respectively. There was a positive association among depression symptoms with female sex (OR: 1.52; p

Abstract Background There is no region-specific publication investigating the attributable burden of breast cancer, particularly among females. This article reported the burden of female breast cancer in the Middle East and North Africa (MENA) region, and its attributable risk factors between 1990 and 2019, by age, sex, and socio-demographic index (SDI). Methods Publicly available data on the incidence, death and disability-adjusted life years (DALY) were retrieved from the Global Burden of Disease (GBD) 2019 study for the 21 countries and territories in MENA, between 1990 and 2019, along with 95% uncertainty intervals (UIs). The relationship between the burden of female breast cancer, in terms of DALYs, and the SDI were also assessed using Smoothing Spline models. Results In 2019, the regional age-standardised incidence and death rates of female breast cancer were 37.5 and 15.2 per 100,000, which represent a 90.9 and 24.0% increase since 1990, respectively. In addition, in 2019 the regional age-standardised DALY rate was 472.7 per 100,000, which was 19.5% higher than in 1990. In 2019, the death rate increased steadily with advancing age, while the DALY rate increased steeply with age and reached its peak in the 70–74 age group. There was a positive association between SDI and the burden of breast cancer over the period 1990 to 2019. Moreover, in 2019 high fasting plasma glucose (6.9%) contributed to the largest proportion of attributable DALYs for female breast cancer in the MENA region. Conclusions There was a significant increase in the incidence rate of female breast cancer in MENA over the past three decades, although the death and DALY rates were both largely unchanged. Preventive programs targeting the major risk factors should be implemented in the region.

Abstract Background Cancers are leading causes of mortality and morbidity, with smoking being recognized as a significant risk factor for many types of cancer. We aimed to report the cancer burden attributable to tobacco smoking by sex, age, socio‐demographic index (SDI), and cancer type in 204 countries and territories from 1990 to 2019. Methods The burden of cancers attributable to smoking was reported between 1990 and 2019, based upon the Comparative Risk Assessment approach used in the Global Burden of Disease (GBD) study 2019. Results Globally, in 2019 there were an estimated 2.5 million cancer‐related deaths (95% UI: 2.3 to 2.7) and 56.4 million DALYs (51.3 to 61.7) attributable to smoking. The global age‐standardized death and DALY rates of cancers attributable to smoking per 100,000 decreased by 23.0% (−29.5 to −15.8) and 28.6% (−35.1 to −21.5), respectively, over the period 1990–2019. Central Europe (50.4 [44.4 to 57.6]) and Western Sub‐Saharan Africa (6.7 [5.7 to 8.0]) had the highest and lowest age‐standardized death rates, respectively, for cancers attributable to smoking. In 2019, the age‐standardized DALY rate of cancers attributable to smoking was highest in Greenland (2224.0 [1804.5 to 2678.8]) and lowest in Ethiopia (72.2 [51.2 to 98.0]). Also in 2019, the global number of DALYs was highest in the 65–69 age group and there was a positive association between SDI and the age‐standardized DALY rate. Conclusions The results of this study clearly illustrate that renewed efforts are required to increase utilization of evidence‐based smoking cessation support in order to reduce the burden of smoking‐related diseases.

Abstract Objective Spinopelvic alignment is increasingly considered as an essential factor for maintaining an energy-efficient posture in individuals with normal or pathological status. Although several previous studies have shown that changes in the sagittal spinopelvic alignment may occur in patients undergoing total hip arthroplasty (THA), no review of this area has been completed so far. Thus, the objective of this scoping review was to summarize the evidence investigating changes in spinopelvic alignment and low back pain (LBP) following THA. Data sources We adhered to the established methodology for scoping reviews. Four electronic databases were systematically searched from inception-December 31, 2021. Study selection We selected prospective or retrospective observational or intervention studies that included patients with THA. Data extraction Data extraction and levels of evidence were independently performed using standardized checklists. Data synthesis A total of 45 papers were included in this scoping review, involving 5185 participants with THA. Pelvic tilt was the most common parameter measured in the eligible studies (n = 26). The results were not consistent across all studies; however, it was demonstrated that the distribution of pelvic tilt following THA had a range of 25° posterior to 20° anterior. Moreover, decreased sacral slope and lower pelvic incidence were associated with increased risk of dislocation in patients with THA. Lumbar spine scoliosis did not change significantly after THA in patients with bilateral hip osteoarthritis (5.50°(1.16°) vs. 3.73°(1.16°); P-value = 0.29). Finally, one study indicated that LBP improvement was not correlated with postoperative changes in spinopelvic alignment parameters. Several methodological issues were addressed in this study, including no sample size calculation and no type-I error adjustment for outcome multiplicity. Conclusions Changes in spinopelvic alignment may occur after THA and may improve with time. Patients with a THA dislocation usually show abnormal spinopelvic alignment compared to patients without a THA dislocation. LBP usually improves markedly over time following THA.

Abstract Background Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate prediction of minority diabetes class more challenging. Methods Deep neural network (DNN), extremely gradient boosting (XGBoost), and random forest (RF) performance is compared in predicting minority diabetes class in Tehran Lipid and Glucose Study (TLGS) cohort data. The impact of changing threshold, cost-sensitive learning, over and under-sampling strategies as solutions to class imbalance have been compared in improving algorithms performance. Results DNN with the highest accuracy in predicting diabetes, 54.8%, outperformed XGBoost and RF in terms of AUROC, g-mean, and f1-measure in original imbalanced data. Changing threshold based on the maximum of f1-measure improved performance in g-mean, and f1-measure in three algorithms. Repeated edited nearest neighbors (RENN) under-sampling in DNN and cost-sensitive learning in tree-based algorithms were the best solutions to tackle the imbalance issue. RENN increased ROC and Precision-Recall AUCs, g-mean and f1-measure from 0.857, 0.603, 0.713, 0.575 to 0.862, 0.608, 0.773, 0.583, respectively in DNN. Weighing improved g-mean and f1-measure from 0.667, 0.554 to 0.776, 0.588 in XGBoost, and from 0.659, 0.543 to 0.775, 0.566 in RF, respectively. Also, ROC and Precision-Recall AUCs in RF increased from 0.840, 0.578 to 0.846, 0.591, respectively. Conclusion G-mean experienced the most increase by all imbalance solutions. Weighing and changing threshold as efficient strategies, in comparison with resampling methods are faster solutions to handle class imbalance. Among sampling strategies, under-sampling methods had better performance than others.

BackgroundConsidering the importance of cardiovascular disease (CVD) risk prediction for healthcare systems and the limited information available in the Middle East, we evaluated the SCORE and Globorisk models to predict CVD death in a country of this region.MethodsWe included 24 427 participants (11 187 men) aged 40-80 years from four population-based cohorts in Iran. Updating approaches were used to recalibrate the baseline survival and the overall effect of the predictors of the models. We assessed the models’ discrimination using C-index and then compared the observed with the predicted risk of death using calibration plots. The sensitivity and specificity of the models were estimated at the risk thresholds of 3%, 5%, 7%, and 10%. An agreement between models was assessed using the intra-class correlation coefficient (ICC). We applied decision analysis to provide perception into the consequences of using the models in general practice; for this reason, the clinical usefulness of the models was assessed using the net benefit (NB) and decision curve analysis. The NB is a sensitivity penalized by a weighted false positive (FP) rate in population level.ResultsAfter 154 522 person-years of follow-up, 437 cardiovascular deaths (280 men) occurred. The 10-year observed risks were 4.2% (95% CI: 3.7%-4.8%) in men and 2.1% (1.8-2%.5%) in women. The c-index for SCORE function was 0.784 (0.756-0.812) in men and 0.780 (0.744-0.815) in women. Corresponding values for Globorisk were 0.793 (0.766-0.820) and 0.793 (0.757-0.829). The deviation of the calibration slopes from one reflected a need for recalibration; after which, the predicted-to-observed ratio for both models was 1.02 in men and 0.95 in women. Models showed good agreement (ICC 0.93 in men, and 0.89 in women). Decision curve showed that using both models results in the same clinical usefulness at the risk threshold of 5%, in both men and women; however, at the risk threshold of 10%, Globorisk had better clinical usefulness in women (Difference: 8%, 95% CI: 4%-13%).ConclusionOriginal Globorisk and SCORE models overestimate the CVD risk in Iranian populations resulting in a high number of people who need intervention. Recalibration could adopt these models to precisely predict CVD mortality. Globorisk showed better performance clinically, only among high-risk women.

Summary: Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019; 293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, $1·8 billion in DAH contributions was provided towards pandemic preparedness in LMICs, and $37·8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12·2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health-related COVID-19 response is 252·2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11–21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP. Interpretation: There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained. Funding: Bill & Melinda Gates Foundation.

Introduction The association between socioeconomic status (SES) and Parkinson’s disease (PD) has been investigated in few studies. To our knowledge, SES measurement based on wealth index and perceived SES in PD patients has not been investigated in any study. Also, the simultaneous measurement of objective and perceived SES and their association with PD has not been conducted yet. This study aimed to determine the association between various SES indicators and PD.Methods This incident case–control study was conducted on 508 patients with PD and 1015 controls randomly selected from the general population in Iran in 2021–2022. A telephone interviewing method was used for data collection. The wealth index and educational level were used to measure objective SES. Perceived SES was also recorded. Multiple logistic regression was used to calculate the adjusted OR (AOR).Results A significant association based on the wealth index was found, where the intermediate category had lower odds of developing PD than the deprived category (AOR 0.75 (95% CI 0.58 to 0.99)). The odds of PD was significantly higher in the people with academic education compared with illiterate and primary-level education (AOR 2.17 (95% CI 1.58 to 2.99). Additionally, the odds of PD were significantly lower in the intermediate (AOR 0.26 (95% CI 0.13 to 0.52)) and affluent (AOR 0.21 (95% CI 0.11 to 0.40)), compared with the deprived categories based on perceived SES. Similar results were obtained in the analysis by sex.Conclusion This study demonstrated that lower wealth index, a lower perceived SES and academic education are associated with increased the odds of PD.

Abstract This study aims to assess the effects of central and general adiposity on development of cardiovascular diseases (CVDs) mediated by cardiometabolic risk factors and to analyze their degree of dependency for mediating their effects. To this end, data from the the Tehran Lipid and Glucose Study cohort with 6280 participants were included in this study. The hazard ratios were calculated using a 2-stage regression model in the context of a survival model. Systolic blood pressure (BP), total serum cholesterol, and fasting plasma glucose were designated as mediators. Assessing the interactions revealed that BP was the most important mediator for general ( (HRNIE: 1.11, 95% CI 1.17–1.24) and central obesity (CO) (HRNIE: 1.11, 95% CI 1.07–1.15) with 60% and 36% proportion of the effects mediated in the total population, respectively. The proportion of mediated risk for all three metabolic risk factors was 46% (95% CI 31–75%) for overweight, 66% (45–100%) for general obesity and 52% (39–87%) for central obesity. BP was the most important mediator for overweight and central obesity in men, comprising 29% and 36% of the risk, respectively. The proportion of the risk mediated through all three metabolic risk factors in women was 23% (95% CI 13–50%) for overweight, 36% (21–64%) for general obesity and 52% (39–87%) for central obesity. Based on the results of this study, cardiometabolic mediators have conciliated more than 60% of the adverse effects of high BMI on CVDs in men. Controlling the metabolic risk factors in women does not efficiently contribute to decreasing CVDs as effectively.

Abstract Study Design Psychometric study. Objective The purpose of this study is to translate, culturally adapt and evaluate the validity and reliability of the Persian (Farsi) version of GLTEQ in patients with multiple sclerosis. Methods This study had three phases, including translation of the questionnaire into Persian and making cultural adaptation, evaluation of pre-final version of questionnaire’s comprehensibility in a pilot study, and investigation of reliability and validity of the final version of the translated questionnaire. Content validity, and convergent validity (correlations among the Persian version of GLTEQ and Global physical activity questionnaire (GPAQ), and international physical activity questionnaire (IPAQ)) and after all test-retest reliability were studied. Results The subjects were 87 MS patients. The Persian version demonstrated moderate to good convergent validity; the correlation coefficient between the Persian version and GPAQ was r=0.64 (p

BackgroundLower respiratory infections (LRIs) cause a substantial mortality, morbidity and economic burden. The present study reported the global, regional and national burden of LRIs and their attributable risk factors in 204 countries and territories, between 1990 and 2019, by age, sex, etiology, and Socio-demographic Index (SDI).MethodsUsing publicly available data from the Global Burden of Disease (GBD) study 2019, we reported the incidence, deaths and disability-adjusted life-years (DALYs), due to LRIs. Estimates were presented as counts and age-standardized rates per 100,000 population with their associated uncertainty intervals (UIs).ResultsGlobally, in 2019 there were 488.9 million (95% UI: 457.6 to 522.6) incident cases and 2.4 million (2.3–2.7) deaths due to LRIs. The global age-standardized incidence and death rates for LRIs were 6,295 (5,887.4–6,737.3) and 34.3 (31.1–37.9) per 100,000 in 2019, which represents a 23.9% (22.5–25.4) and 48.5% (42.9–54.0) decrease, respectively since 1990. In 2019, Guinea [12,390.4 (11,495.5–13,332.8)], Chad [12,208.1 (11,289.3–13,202.5)] and India [11,862.1 (11,087.0–12,749.0)] had the three highest age-standardized incidence rates of LRI. Equatorial Guinea [−52.7% (95% UI: −55.8 to −49.3)], Chile [−50.2% (95% UI: −53.4 to −47.0)] and Albania [−48.6% (95% UI: −51.7 to −45.3)] showed the largest decreases from 1990 to 2019. In 2019, a decrease in the incidence rate of LRI was observed at the global level up to the 25–29 age group, then the incidence rates increased with age. The burden of LRIs decreased with increasing SDI at both the regional and national levels. Globally, child wasting (33.1%), household air pollution from solid fuels (24.9%) and a lack of access to handwashing facilities (14.4%) made the largest contributions to the LRI burden in 2019.ConclusionsAlthough the burden of LRIs decreased over the period 1990–2019, LRIs still contribute to a large number of incident cases, deaths and DALYs. Preventative programs with a focus on reducing exposure to attributable risk factors should be implemented, especially in less developed countries.

It is currently debated whether vitamin D requirements during pregnancy differ from those during non-gravid states. In current analyses, we aimed to determine the best model for the association between PTH and serum 25-hydroxyvitamin D (25(OH)D) and the threshold for circulating 25(OH)D at which serum parathyroid hormone (PTH) is suppressed. This multicenter prospective cross-sectional study was conducted on 227 Iranian pregnant women aged 15–45 years in their third trimester of pregnancy. The locally weighted smoothing scatter plot (LOWESS) was used to determine the curvilinear shape of the 25(OH)D/PTH relationship. Linear and non-linear methods were employed to determine the best fit and cut-point for serum 25(OH)D concentration. The median serum 25(OH)D and corresponding serum PTH concentration were 17⋅26 (13⋅44–23⋅08) ng/ml and 19⋅46 (15⋅08–25⋅04) pg/ml in our study population, respectively. The LOWESS curve suggested a non-linear and monotonic with a negative slope relation between PTH (pg/ml) and serum 25(OH)D (ng/ml). The optimal model for the association between PTH and serum 25(OH)D was a one-term fractional polynomial (FP1) (AIC = 1640⋅463). The FP1 analysis identified the 25(OH)D threshold of 12⋅48 ng/ml at which serum PTH rapidly rose. The expected degree of PTH stimulation seems to have a linear trend as 25(OH)D falls below 40 ng/ml. 25(OH)D (ng/ml) and PTH (pg/ml) had a non-linear and monotonic relationship with a negative slope. Our data suggest that a 25(OH)D threshold of 12⋅48 ng/ml is sufficient for parathyroid hormone suppression, which could be used to screen for deficient individuals.

IntroductionThis study used Targeted Maximum Likelihood Estimation (TMLE) as a double robust method to estimate the causal effect of previous tuberculosis treatment history on the occurrence of multidrug-resistant tuberculosis (MDR-TB). TMLE is a method to estimate the marginal statistical parameters in case-control study design. The aim of this study was to estimate the causal effect of the previous tuberculosis treatment on the occurrence of MDR-TB using TMLE in Sudan.MethodA case-control study design combined with TMLE was used to estimate parameters. Cases were MDR-TB patients and controls were and patients who cured from tuberculosis. The history of previous TB treatment was considered the main exposure, and MDR-TB as an outcome. A designed questionnaire was used to collect a set of covariates including age, time to reach a health facility, number of times stopping treatment, gender, education level, and contact with MDR-TB cases. TMLE method was used to estimate the causal association of parameters. Statistical analysis was carried out with ltmle package in R-software. Result presented in graph and tables.ResultsA total number of 430 cases and 860 controls were included in this study. The estimated risk difference of the previous tuberculosis treatment was (0.189, 95% CI; 0.161, 0.218) with SE 0.014, and p-value (ConclusionOur findings indicated that previous tuberculosis treatment history was determine as a risk factor for MDR-TB in Sudan. Also, TMLE method can be used to estimate the risk difference and the risk ratio in a case-control study design.

We aimed to review the validity of existing prediction models for cardiovascular diseases (CVDs) in Asia. In this systematic review and meta-analysis, we included studies that validated prediction models for CVD risk in the general population in Asia. Various databases, including PubMed, Web of Science conference proceedings citation index, Scopus, Global Index Medicus of the World Health Organization (WHO), and Open Access Thesis and Dissertations (OATD), were searched up to November 2022. Additional studies were identified through reference lists and related reviews. The risk of bias was assessed using the PROBAST prediction model risk of bias assessment tool. Meta-analyses were performed using the random effects model, focusing on the C-statistic as a discrimination index and the observed-to-expected ratio (OE) as a calibration index. Out of 1315 initial records, 16 studies were included, with 21 external validations of six models in Asia. The validated models consisted of Framingham models, pooled cohort equations (PCEs), SCORE, Globorisk, and WHO models, combined with the results of the first four models. The pooled C-statistic for men ranged from 0.72 (95% CI 0.70 to 0.75; PCEs) to 0.76 (95% CI 0.74 to 0.78; Framingham general CVD). In women, it varied from 0.74 (95% CI 0.22 to 0.97; SCORE) to 0.79 (95% CI 0.74 to 0.83; Framingham general CVD). The pooled OE ratio for men ranged from 0.21 (95% CI 0.018 to 2.49; Framingham CHD) to 1.11 (95%CI 0.65 to 1.89; PCEs). In women, it varied from 0.28 (95%CI 0.33 to 2.33; Framingham CHD) to 1.81 (95% CI 0.90 to 3.64; PCEs). The Framingham, PCEs, and SCORE models exhibited acceptable discrimination but poor calibration in predicting the 10-year risk of CVDs in Asia. Recalibration and updates are necessary before implementing these models in the region.

Background: This study assesses the effect of blood lipid indices and lipid ratios on cardiovascular diseases (CVDs) using inverse probability-of-exposure weighted estimation of marginal structural models (MSMs). Methods: A pooled dataset of two US representative cohort studies, including 16736 participants aged 42–84 years with complete information at baseline, was used. The effect of each lipid index, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), ratios of TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C on coronary heart disease (CHD) and stroke were estimated using weighted Cox regression. Results: There were 1638 cases of CHD and 1017 cases of stroke during a median follow-up of 17.1 years (interquartile range: 8.5 to 25.7). Compared to optimal levels, the risk of CVD outcomes increased substantially in high levels of TC, LDL-C, TC/HDL-C, and LDL-C/HDL-C. If everyone had always had high levels of TC (≥240 mg/dL), risk of CHD would have been 2.15 times higher, and risk of stroke 1.35 times higher than if they had always had optimal levels (

Competing events are events that preclude the occurrence of the primary outcome. Much has been written on mainly the statistics behind competing events analyses. However, many of these publications and tutorials have a strong statistical tone and might fall short in providing a practical guide to clinician researchers as to when to use a competing event analysis and more importantly which method to use and why.Here we discuss the different target effects in the Fine-Gray and cause-specific methods using simple causal diagrams and provide strengths and limitations of both approaches for addressing etiologic questions. We argue why the Fine-Gray method might not be the best approach for handling competing events in etiological time-to-event studies.

Misinterpretations of P-values and 95% confidence intervals are ubiquitous in medical research. Specifically, the terms significance or confidence, extensively used in medical papers, ignore biases and violations of statistical assumptions and hence should be called overconfidence terms. In this paper, we present the compatibility view of P-values and confidence intervals; the P-value is interpreted as an index of compatibility between data and the model, including the test hypothesis and background assumptions, whereas a confidence interval is interpreted as the range of parameter values that are compatible with the data under background assumptions. We also suggest the use of a surprisal measure, often referred to as the S-value, a novel metric that transforms the P-value, for gauging compatibility in terms of an intuitive experiment of coin tossing.

Abstract Background Health workers (HWs) appropriate malaria case management includes early detection and prompt treatment with appropriate anti-malarial drugs. Subsequently, HWs readiness and practice are considered authentic evidence to measure the health system performance regarding malaria control programme milestones and to issue malaria elimination certification. There is no comprehensive evidence based on meta-analysis, to measure the performance of HWs in case management of malaria. This study aimed to evaluate HWs performance in early malaria case detection (testing) and the appropriate treatment. Methods The published literature in English was systematically searched from Medline, Scopus, Embase, and Malaria Journal up to 30th December 2020. The inclusion criteria were any studies that assessed HWs practice in early case detection by malaria testing and appropriate treatment. Eligibility assessment of records was performed independently in a blinded, standardized way by two reviewers. Pooled prevalence estimates were stratified by HWs cadre type. Meta-regression analysis was performed to explore the impact of the appropriateness of the method and risk of bias as potential sources of the heterogeneity in the presence of effective factors. Results The study pooled data of 9245 HWs obtained from 15 included studies. No study has been found in eliminating settings. The pooled estimate for appropriate malaria treatment and malaria testing were 60%; 95% CI: 53–67% and 57%; 95% CI: 49–65%, respectively. In the final multivariable meta-regression, HWs cadre and numbers, appropriateness of study methods, malaria morbidity and mortality, total admissions of malaria suspected cases, gross domestic product, availability of anti-malarial drugs, and year of the publication were explained 85 and 83% of the total variance between studies and potential sources of the heterogeneity for malaria testing and treating, respectively. Conclusion HWs adherence to appropriate malaria case management guidelines were generally low while no study has been found in eliminating countries. Studies with the inappropriateness methods and risk of bias could be overestimating the actual proportion of malaria appropriate testing and treating. Strategies that focus on improving readiness and early identification of acute febrile diseases especially in the countries that progress to malaria elimination should be highly promoted.

Introduction: It could be valuable for surgeons and patients to use one chart in different groups and evaluate weight loss during the post-surgery period. Methods: This retrospective study used the Iran National Obesity Surgery Database. patients with clinically severe obesity aged 18-70 undergoing sleeve gastrectomy participated in this study. Body mass Index (BMI) reduction and 5 other metrics measured over the study period were modeled using LMS (Lambda-mu-sigma) method. Our data were split into the train (70%) and test (30%) sets. Results: In this study, 1,258 patients (75% female) met the eligibility criteria to participate. Mean age and initial BMI were 36.87 ± 10.51 and 42.74 (40.37-46.36), respectively. Percentile charts for various metrics have been presented for the first 2 years after surgery. Conclusions: For sleeve surgery, all metrics are acceptable for clinical applications. Using the statistical view, BMI reduction is the most acceptable metric according to the lowest bias values and its variation between all the metrics.

Summary: Background: More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels. Methods: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution. Findings: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000–257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution. Interpretation: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Funding: Bill & Melinda Gates Foundation.

Abstract Background Understanding the distinct patterns (trajectories) of variation in blood lipid levels before diagnosing cardiovascular disease (CVD) might carry important implications for improving disease prevention or treatment. Methods We investigated 14,373 participants (45.5% men) aged 45–84 from two large US prospective cohort studies with a median of 23 years follow-up. First, we jointly estimated developmental trajectories of lipid indices, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) concentrations using group-based multi-trajectory modeling. Then, the association of identified multi-trajectories with incident CVD, heart failure, and all-cause mortality were examined using Cox proportional hazard model. Results Seven distinct multi-trajectories were identified. The majority of participants (approximately 80%) exhibited decreasing LDL-C but rising TG levels and relatively stable HDL-C levels. Compared to the individuals with healthy and stable LDL-C, HDL-C, and TG levels, those in other groups were at significant risk of incident CVD after adjusting for other conventional risk factors. Individuals with the highest but decreasing LDL-C and borderline high and rising TG levels over time were at the highest risk than those in other groups with a 2.22-fold risk of CVD. Also, those with the highest and increased triglyceride levels over time, over optimal and decreasing LDL-C levels, and the lowest HDL-C profile had a nearly 1.84 times CVD risk. Even individuals in the multi-trajectory group with the highest HDL-C, optimal LDL-C, and optimal TG levels had a significant risk (HR, 1.45; 95% CI 1.02–2.08). Furthermore, only those with the highest HDL-C profile increased the risk of heart failure by 1.5-fold (95% CI 1.07–2.06). Conclusions The trajectories and risk of CVD identified in this study demonstrated that despite a decline in LDL-C over time, a significant amount of residual risk for CVD remains. These findings suggest the impact of the increasing trend of TG on CVD risk and emphasize the importance of assessing the lipid levels at each visit and undertaking potential interventions that lower triglyceride concentrations to reduce the residual risk of CVD, even among those with the optimal LDL-C level.

Abstract Objectives The relationship between reproductive factors and breast cancer (BC) risk has been investigated in previous studies. Considering the discrepancies in the results, the aim of this study was to estimate the causal effect of reproductive factors on BC risk in a case-control study using the double robust approach of targeted maximum likelihood estimation. Methods This is a causal reanalysis of a case-control study done between 2005 and 2008 in Shiraz, Iran, in which 787 confirmed BC cases and 928 controls were enrolled. Targeted maximum likelihood estimation along with super Learner were used to analyze the data, and risk ratio (RR), risk difference (RD), andpopulation attributable fraction (PAF) were reported. Results Our findings did not support parity and age at the first pregnancy as risk factors for BC. The risk of BC was higher among postmenopausal women (RR = 3.3, 95% confidence interval (CI) = (2.3, 4.6)), women with the age at first marriage ≥20 years (RR = 1.6, 95% CI = (1.3, 2.1)), and the history of oral contraceptive (OC) use (RR = 1.6, 95% CI = (1.3, 2.1)) or breastfeeding duration ≤60 months (RR = 1.8, 95% CI = (1.3, 2.5)). The PAF for menopause status, breastfeeding duration, and OC use were 40.3% (95% CI = 39.5, 40.6), 27.3% (95% CI = 23.1, 30.8) and 24.4% (95% CI = 10.5, 35.5), respectively. Conclusions Postmenopausal women, and women with a higher age at first marriage, shorter duration of breastfeeding, and history of OC use are at the higher risk of BC.