2023 CiteScore: 0.8
pISSN: 2383-4196
eISSN: 2383-420X
Editor-in-Chief:
Hojjat Zeraati, PhD.
Vol 10 No 2 (2024): summer
Articles
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The genetic variant of interest is referred to be a weak instrumental variable in Mendelian randomization If the relevance assumption is not met. By and large, a weak instrument bias occurs when there is insufficient statistical evidence to support an association between IV and exposure. Weak instruments can result in a variety of problems, including (i) insufficient statistical power to hypothesis testing, (ii) increasing bias with deviation from IV assumptions, and (iii) asymptotic estimation of standard errors and confidence intervals. Several statistical techniques have been presented thus far for reducing weak instrumental bias. However, the absence of a comprehensive document comparing and reviewing all of these strategies is particularly evident. As such, we seek to present an overview of Mendelian Randomization, the challenges associated with weak instrumental bias, an adequate statistical remedy for weak instrumental bias, and the limits of MR, as well as a critical comparison.
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Background: The incidence of hyperlipidemia in Iran is on a consistent rise, potentially contributing significantly to increased susceptibility to cardiovascular diseases and other health complications linked to elevated blood lipid levels. This study employs hierarchical Bayesian model to assess the heightened lipid risk on a broader scale across Iran's provinces. Thise model play a pivotal role in spatial modeling, adeptly handling uncertainties arising from diverse spatial data sources.
Methods: This study included individuals diagnosed with hyperlipidemia from all provinces of Iran in 2019. The primary focus of the investigation included essential variables such as the mean age, gender distribution, and the documented incidence of hyperlipidemia cases in each province. Population data, stratified by province, age group, and gender, were sourced from the Iranian Statistics Center database. Utilizing a direct approach, disease prevalence and expected case numbers were calculated. The analysis employed the Besag-York-Mollié (BYM) model, with parameter estimation executed through the Hamiltonian Monte Carlo method.
Results: In this investigation, the prevalence and spatial distribution of hyperlipidemia were explored within a diverse population of 1,609,538 patients across various regions in Iran. The relative risk of hyperlipidemia surpassed 1 in 16% of Iranian provinces (posterior probability > 0.8), with a calculated 95% confidence interval of 0.304 to 0.879. The overall prevalence of hyperlipidemia was determined to be 0.815. Significant heterogeneity in hyperlipidemia was identified among different provinces, with Tehran exhibiting the highest relative risk (RR=1.701; 95% CrI: 1.69, 1.713). Notably, gender (RR=1.008; CI: 1.007, 1.009 for males and RR=1.005; CI: 1.003, 1.007 for females) and age were not found to have a statistically significant effect on the relative risk of the disease.
Conclusions: In conclusion, this investigation employed hierarchical Bayesian models to evaluate the prevalence and spatial distribution of hyperlipidemia across the provinces of Iran. The analysis unveiled a significant escalation in the relative risk of hyperlipidemia in 16% of Iranian provinces, underscoring the spatial heterogeneity in disease prevalence. This study contributes invaluable insights into the spatial dynamics of hyperlipidemia in Iran, establishing a groundwork for the formulation of targeted public health strategies.
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Introduction
The burden of childhood morbidity and mortality are still huge in most sub-Saharan African countries with West African sub-region contributing largely to the burden. Previous findings have demonstrated strong link between early life events such as low birth weight (LBW) with later events particularly malnutrition. We aim at estimating the specific and shared spatial patterns of LBW and stunting among under-five children in multiple West African countries.
Method
Data set for the study was sourced from the Demographic and Health Surveys conducted in fourteen West African countries. We used a Bayesian shared component model allows us to split the spatial surface into those specific to each of the outcomes and one shared by the two, with inference based on a Bayesian approximation procedure through the integrated nested Laplace approximation.
Results
The findings show spatial clustering in the shared and specific effects of the health outcomes, demonstrating high likelihood in northern Nigeria spanning through Niger and that the spatial pattern for the shared effects are similar to those of the specific effects of stunting. Furthermore, mother’s level of education, attendance in antenatal care and household wealth index are strongly associated with the shared health outcomes.
Conclusion
The study provides insight into the spatial pattern of LBW and stunting among West African children and can be useful in targeted interventions in regions with high burden of LBW and malnutrition which may include more advocacy that promote the use of antenatal care services during pregnancy.
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Context/Background: Sexually transmitted infections (STIs) include a range of clinical syndromes that may be acquired/transmitted from one individual to another through sexual activity.
Aims/Objectives: This study aimed to determine the awareness and knowledge of sexually transmitted infections and its associated factors among clinically suspected cases.
Methodology: A hospital-based cross-sectional study design was used among 194 STIs patients between aged 15 to 60 years from a tertiary care hospital during August 2022 to March 2023. Data were collected through self-administered structured schedule. A multivariate logistic regression analysis was used to identify factors associated with awareness and knowledge of STIs.
Results: The proportion of respondents with good awareness and knowledge about STIs was 62% and 50% respectively. Respondents with poor awareness and poor knowledge of STIs were found to be more likely to engage in informal treatment care (AOR = 7.39, 95% CI [2.14-25.52] P = 0.002),) and (AOR = 1.21, 95% CI [1.34-4.30], P = 0.021). Place of residence, educational status, occupation, type of treatment care was found to be significantly associated with awareness of STIs and type of treatment care, referral status, delay in seeking treatment were found to be significantly associated with knowledge of STIs.
Conclusions: The current findings show that the knowledge level on STIs has slightly increased compared to previous studies, but it was still unsatisfactory. The existing education programs in the country should be enhanced, by conveying more information on STIs.
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Background: Estimating the First Birth Interval (FBI) from cross-sectional data often presents challenges related to truncation effects. These challenges stem from the data’s inability to capture the enough exposure for a event, resulting in potential biases and inaccuracies in FBI estimates. Recognizing and addressing truncation effects is essential for obtaining more precise and meaningful fertility parameter estimates in a cross-sectional survey.
Objective: This study seeks to mitigate truncation effects in the estimation of the FBI by utilizing the Current Status Data Technique. This approach involves focusing on women with specific marital durations, providing a means to counteract the bias caused by truncation and thereby yielding more accurate and reliable FBI estimates.
Methodology: Data from the National Family Health Survey (NFHS-IV) are employed for this study. The Current Status Data Technique is applied to the dataset, considering exclusively those women with marital durations less than 120 months. This methodology enables the adjustment of truncation effects and facilitates a more precise estimation of the FBI. Statistical analysis is conducted to determine the FBI distribution and ascertain the necessary sample size.
Results: The application of the Current Status Data Technique yields an FBI estimate of 30.70 months. To achieve reliable estimations of the FBI using Current Status Techniques, a minimum sample size exceeding ”5000” observations is required.
Conclusion: Truncation effect in FBI is address and some non parametric adjustment is used for estimating the duration of FBI. The Current Status Data Technique emerges as a valuable tool for mitigating these effects and enhancing the precision of FBI estimates. This research contributes to an improved understanding of fertility dynamics and provides valuable insights for future studies on the First Birth Interval.
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Introduction: Colorectal cancer (CRC) represents the second leading cause of cancer-related mortality. This study focused on the development of a robust conceptual causal model designed to predict early recurrence and mortality following curative surgery in colorectal cancer patients.
Methods: In this retrospective cohort study, we included 284 patients with colorectal cancer (CRC) who underwent surgery at the Imam Khomeini (RA) Clinic in Hamadan, Iran, between 2001 and 2017. Demographic characteristics, treatment modalities, and other relevant data were extracted from patient records. Predictors were analyzed using Generalized Structural Equation Modeling (GSEM) for survival analysis, employing an accelerated failure time (AFT) approach. Both unadjusted and adjusted time ratios (TRs) were calculated using STATA software.
Results: The results of our developed causal model indicated that receiving chemotherapy was significantly associated with a shorter survival time ratio (TR = 0.415, 95% CI: 0.290-0.593), and recurrence time (TR = 0.363, 95% CI: 0.190-0.696). Conversely, patients who underwent multiple chemotherapy sessions exhibited a longer survival time (TR = 2.130, 95% CI: 1.790-2.534) and recurrence time (TR = 2.206, 95% CI: 1.609-3.023). Age had a direct impact on the recurrence time (TR = 0.758, 95% CI: 0.602-0.955). Additionally, age had a significant direct effect on the receipt of chemotherapy, the cancer site, and the receipt of radiotherapy.
Conclusion: In summary, our study's causal model reveals that chemotherapy shortens survival time but multiple sessions can extend both survival and recurrence times. Age significantly affects recurrence time and chemotherapy receipt. These findings highlight the importance of personalized treatment strategies in colorectal cancer management.
Keywords: Generalized Structural Equation Model, Conceptual causal model, Accelerated failure time, Early recurrence, Colorectal cancer
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Background: “Low birth weight” (LBW) is defined as birth weight < 2.5 kg (2500 grams). LBW infants remain at a relatively higher risk of mortality than those with normal birth weight. This is still a major public health problem in developing countries like India. This study examines the trend and prevalence of LBW in India and its data characteristics. Methods: National Family Health Survey (N.F.H.S.) data rounds were collected from 1992-2021. The study sample included women aged 15-49 years. The logistic regression model was fitted to assess the maternal determinants affecting the birth weight among newborns. Also, the heaping pattern of the data for each round of N.F.H.S. data was analyzed. Results: The trend and prevalence of low birth weight were reported 1884 (25.2%) in the first round of the National Family Health Survey, 1859 (22.7 %) in the second, 4146 (21.5%) in the third, 35476 (18.2%) in fourth, and 38167 (18.2%) in fifth, which remains constant in comparison to the previous round. Conclusion: The prevalence of LBW in India has declined over the past decades as reported in data like NFHS-I, II & III, but NFHS-IV and V are constant. Sociodemographic factors are shown as a risk factor for LBW. Data heaping is a key challenge to give the correct estimate of LBW and it is found in each round of the data set. Maternal health services are required during the gestation period to reduce the LBW and.
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MD NAHID HASSAN NISHAN; M Z E M Naser Uddin Ahmed
, Sayeda Jahan Oishy , Aria Alam , Saidur Rahman Mashreky (Co-Corresponding Author)
Abstract
Background
Dengue fever in Bangladesh, particularly in Dhaka, faces significant healthcare access barriers. Understanding these barriers is crucial for targeted interventions. Therefore, this study aims to analyze the barriers to accessing dengue healthcare through a multicenter survey in Dhaka, a major dengue hotspot in Bangladesh.
Methods
This cross-sectional study was employed throughout the study. The study was conducted in Dhaka City. this study used two-stage stratified sampling based on hospital type (public/private) and randomly selected 16 hospitals (7 public and 9 private), focusing on patients admitted with dengue. A total of 101 patients comprised the final sample.
Result
The study reveals overall 96.04% of participants perceived dengue as a serious threat. Demographically, the patients mostly lived in urban (85.15%) and varied in education. MANOVA indicates that demographic variables significantly impact access barriers, highlighting age, and education status as influential factors (P-value <0.05).
Conclusion
This study highlights the importance of age and education as key determinants of access barriers in dengue healthcare. Addressing the unique needs of children and older adults, as well as enhancing educational opportunities, could be pivotal in mitigating these barriers.
