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.

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.

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.

Background: This study aimed to estimate the prevalence of and determine the factors associated with antihypertensive medication (A-HTNM) non-adherence among hypertension care seekers attending primary health clinics in the Gaza Strip. Methods: A cross-sectional survey was conducted as the recruitment phase of a clustered randomized controlled trial including 538 participants. The participants were randomly selected from 10 primary health care centers by two-stage cluster random sampling. A structured questionnaire was used to collect data through face-to-face interview. The questionnaire was developed based on the World Health Organization determinants for medication non-adherence and the Health Belief Model. The main outcomes of this study were the prevalences of A-HTNM non-adherence and its associated factors. Adherence status was assessed using the eight-item Morisky Self-Report Medication Adherence Scale. Data were analyzed by STATA ver. 14.0 (Stata Corp., College Station, TX, USA) using a standard complex survey, accounting for unresponsiveness and the clustering sampling approach. Results: The overall prevalence of A-HTNM non-adherence was 65.8% (95% confidence interval [CI], 59.2–71.8). Among all studied predictors, only self-efficacy of participants (odds ratio [OR], 3.8; 95% CI, 1.79–2.84) and social support (OR, 2.26; 95% CI, 2.82–5.11) remained significantly associated with A-HTNM non-adherence after adjusting for age, education level, number and frequency of A-HTNM doses per day, and comorbidities. Conclusion The high prevalence of non-adherence highlights the need for serious intervention to enhance the adherence rate among hypertension patients. The associated factors can be considered when developing appropriate interventions.

Background: This study aimed to estimate the prevalence of and determine the factors associated with antihypertensive medication (A-HTNM) non-adherence among hypertension care seekers attending primary health clinics in the Gaza Strip. Methods: A cross-sectional survey was conducted as the recruitment phase of a clustered randomized controlled trial including 538 participants. The participants were randomly selected from 10 primary health care centers by two-stage cluster random sampling. A structured questionnaire was used to collect data through face-to-face interview. The questionnaire was developed based on the World Health Organization determinants for medication non-adherence and the Health Belief Model. The main outcomes of this study were the prevalences of A-HTNM non-adherence and its associated factors. Adherence status was assessed using the eight-item Morisky Self-Report Medication Adherence Scale. Data were analyzed by STATA ver. 14.0 (Stata Corp., College Station, TX, USA) using a standard complex survey, accounting for unresponsiveness and the clustering sampling approach. Results: The overall prevalence of A-HTNM non-adherence was 65.8% (95% confidence interval [CI], 59.2–71.8). Among all studied predictors, only self-efficacy of participants (odds ratio [OR], 3.8; 95% CI, 1.79–2.84) and social support (OR, 2.26; 95% CI, 2.82–5.11) remained significantly associated with A-HTNM non-adherence after adjusting for age, education level, number and frequency of A-HTNM doses per day, and comorbidities. Conclusion The high prevalence of non-adherence highlights the need for serious intervention to enhance the adherence rate among hypertension patients. The associated factors can be considered when developing appropriate interventions.

OBJECTIVES: The emergence of multidrug-resistant tuberculosis (MDR-TB) is a major challenge for the global control of tuberculosis (TB). The aim of this study was to determine the risk factors associated with MDR-TB in Sudan.METHODS: This case-control study was conducted from May 2017 to February 2019. Patients newly diagnosed with MDR-TB were selected as cases, and controls were selected from TB patients who responded to first-line anti-TB drugs. A questionnaire was designed and used to collect data from study participants. Logistic regression was used to evaluate associations between risk factors and MDR-TB infection. The best multivariate model was selected based on the likelihood ratio test.RESULTS: A total of 430 cases and 860 controls were selected for this study. A history of previous TB treatment (adjusted odds ratio [aOR], 54.85; 95% confidence interval [CI], 30.48 to 98.69) was strongly associated with MDR-TB infection. We identified interruption of TB treatment (aOR, 7.62; 95% CI, 3.16 to 18.34), contact with MDR-TB patients (aOR, 5.40; 95% CI, 2.69 to 10.74), lower body weight (aOR, 0.89; 95% CI, 0.87 to 0.91), and water pipe smoking (aOR, 3.23; 95% CI, 1.73 to 6.04) as factors associated with MDR-TB infection.CONCLUSIONS: Previous TB treatment and interruption of TB treatment were found to be the main predictors of MDR-TB. Additionally, this study found that contact with MDR-TB patients and water pipe smoking were associated with MDR-TB infection in Sudan. More efforts are required to decrease the rate of treatment interruption, to strengthen patients' adherence to treatment, and to reduce contact with MDR-TB patients.
Body Weight ; Case-Control Studies ; Humans ; Logistic Models ; Odds Ratio ; Risk Factors ; Smoking ; Sudan ; Tuberculosis ; Tuberculosis, Multidrug-Resistant ; Water

OBJECTIVES: The emergence of multidrug-resistant tuberculosis (MDR-TB) is a major challenge for the global control of tuberculosis (TB). The aim of this study was to determine the risk factors associated with MDR-TB in Sudan. METHODS: This case-control study was conducted from May 2017 to February 2019. Patients newly diagnosed with MDR-TB were selected as cases, and controls were selected from TB patients who responded to first-line anti-TB drugs. A questionnaire was designed and used to collect data from study participants. Logistic regression was used to evaluate associations between risk factors and MDR-TB infection. The best multivariate model was selected based on the likelihood ratio test. RESULTS: A total of 430 cases and 860 controls were selected for this study. A history of previous TB treatment (adjusted odds ratio [aOR], 54.85; 95% confidence interval [CI], 30.48 to 98.69) was strongly associated with MDR-TB infection. We identified interruption of TB treatment (aOR, 7.62; 95% CI, 3.16 to 18.34), contact with MDR-TB patients (aOR, 5.40; 95% CI, 2.69 to 10.74), lower body weight (aOR, 0.89; 95% CI, 0.87 to 0.91), and water pipe smoking (aOR, 3.23; 95% CI, 1.73 to 6.04) as factors associated with MDR-TB infection. CONCLUSIONS: Previous TB treatment and interruption of TB treatment were found to be the main predictors of MDR-TB. Additionally, this study found that contact with MDR-TB patients and water pipe smoking were associated with MDR-TB infection in Sudan. More efforts are required to decrease the rate of treatment interruption, to strengthen patients’ adherence to treatment, and to reduce contact with MDR-TB patients.
Body Weight ; Case-Control Studies ; Humans ; Logistic Models ; Odds Ratio ; Risk Factors ; Smoking ; Sudan ; Tuberculosis ; Tuberculosis, Multidrug-Resistant ; Water

OBJECTIVES: The emergence of multidrug-resistant tuberculosis (MDR-TB) is a major challenge for the global control of tuberculosis (TB). The aim of this study was to determine the risk factors associated with MDR-TB in Sudan. METHODS: This case-control study was conducted from May 2017 to February 2019. Patients newly diagnosed with MDR-TB were selected as cases, and controls were selected from TB patients who responded to first-line anti-TB drugs. A questionnaire was designed and used to collect data from study participants. Logistic regression was used to evaluate associations between risk factors and MDR-TB infection. The best multivariate model was selected based on the likelihood ratio test. RESULTS: A total of 430 cases and 860 controls were selected for this study. A history of previous TB treatment (adjusted odds ratio [aOR], 54.85; 95% confidence interval [CI], 30.48 to 98.69) was strongly associated with MDR-TB infection. We identified interruption of TB treatment (aOR, 7.62; 95% CI, 3.16 to 18.34), contact with MDR-TB patients (aOR, 5.40; 95% CI, 2.69 to 10.74), lower body weight (aOR, 0.89; 95% CI, 0.87 to 0.91), and water pipe smoking (aOR, 3.23; 95% CI, 1.73 to 6.04) as factors associated with MDR-TB infection. CONCLUSIONS Previous TB treatment and interruption of TB treatment were found to be the main predictors of MDR-TB. Additionally, this study found that contact with MDR-TB patients and water pipe smoking were associated with MDR-TB infection in Sudan. More efforts are required to decrease the rate of treatment interruption, to strengthen patients' adherence to treatment, and to reduce contact with MDR-TB patients.

OBJECTIVES: Consecutive community health assessments revealed that water-pipe smoking in women and impaired growth in children were among the main health concerns in suburban communities in southern Iran. The aim of the present study was to identify the effects of water-pipe smoking during pregnancy on birth weight. METHODS: Data from a population-based prospective cohort study of 714 singleton live pregnancies in the suburbs of Bandar Abbas in southern Iran in 2016–2018 were used in this study. Data about water-pipe smoking patterns and birth weight were collected by questionnaires during and after the pregnancy. Low birth weight (LBW) was defined as a birth weight below 2,500 g. Statistical analyses were performed using generalized linear models, and the results were presented in terms of relative risk (RR) and 95% confidence intervals (CI). RESULTS: Fifty (8.2%) of the study subjects smoked water-pipe. The adjusted risk of LBW increased 2-fold in water-pipe smokers (adjusted RR [aRR], 2.09; 95% CI, 1.18 to 3.71), and by 2.0% for each 1-year increase in the duration of water-pipe smoking (aRR, 1.02; 95% CI, 0.99 to 1.05). CONCLUSIONS: Our results showed that water-pipe smoking during pregnancy was an important risk factor for LBW in this population sample from southern Iran. The introduction of regulations onto prevent water-pipe smoking and the implementation of community health action plans aiming at empowering women and increasing women's knowledge and awareness regarding the health consequences of water-pipe smoking are proposed.
Birth Weight* ; Child ; Cohort Studies* ; Female ; Humans ; Infant, Low Birth Weight ; Infant, Newborn ; Iran* ; Linear Models ; Parturition* ; Pregnancy ; Prospective Studies* ; Risk Factors ; Smoke* ; Smoking* ; Social Control, Formal ; Suburban Population

OBJECTIVES: We analyzed dietary patterns using reduced rank regression (RRR), and assessed how well the scores extracted by RRR predicted stroke in comparison to the scores produced by partial least squares and principal component regression models. METHODS: Dietary data at baseline were used to extract dietary patterns using the 3 methods, along with 4 response variables: body mass index, fibrinogen, interleukin-6, and low-density lipoprotein cholesterol. The analyses were based on 5,468 males and females aged 45–84 years who had no clinical cardiovascular disease, using data from the Multi-Ethnic Study of Atherosclerosis. RESULTS: The primary factor derived by RRR was positively associated with stroke incidence in both models. The first model was adjusted for sex and race and the second model was adjusted for the variables in model 1 as well as smoking, physical activity, family and sibling history of stroke, the use of any lipid-lowering medication, the use of any anti-hypertensive medication, hypertension, and history of myocardial infarction (model 1: hazard ratio [HR], 7.49; 95% confidence interval [CI], 1.66 to 33.69; p for trend=0.01; model 2: HR, 6.83; 95% CI, 1.51 to 30.87 for quintile 5 compared with the reference category; p for trend=0.02). CONCLUSIONS: Based primarily on RRR, we identified that a dietary pattern high in fats and oils, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, and fried potatoes and low in dark-yellow and cruciferous vegetables may increase the incidence of ischemic stroke.
Atherosclerosis* ; Body Mass Index ; Cardiovascular Diseases ; Chickens ; Cholesterol ; Continental Population Groups ; Diet ; Fabaceae ; Fats ; Female ; Fibrinogen ; Humans ; Hypertension ; Incidence ; Interleukin-6 ; Least-Squares Analysis ; Lipoproteins ; Lycopersicon esculentum ; Male ; Meat ; Methods* ; Motor Activity ; Myocardial Infarction ; Oils ; Ovum ; Poultry ; Risk Factors* ; Siblings ; Smoke ; Smoking ; Solanum tuberosum ; Stroke* ; Tuna ; Vegetables