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Background: This study aimed to comprehensively analyze the overall congenital heart disease (CHD) prevalence in live births and children in Iran, along with evaluating the spatial distribution of CHD birth prevalence across various geographical regions within the country. Methods: A Bayesian hierarchical meta-analysis (PROSPERO 2022: CRD42022331281) was performed to determine the pooled prevalence. A systematic search was conducted using Web of Science, ScienceDirect, PubMed, Iranian Research Institute for Information Science and Technology (IranDoc), Scientific Information Database (SID), and Magiran until October 4, 2023. Cross-sectional and cohort studies in both English and Persian languages, focusing on the age range of 0-10 years, were considered for the study population. The study quality was evaluated using the Agency for Healthcare Research and Quality (AHRQ) Risk of Bias tool. Heterogeneity was assessed by I2 and t2 statistics, and publication bias by Egger's and Begg's tests. Results: The meta-analysis included 62 studies, revealing an overall CHD prevalence of 2.5 per 1000 births. Over time, CHD birth prevalence in Iran has consistently increased. Spatial distribution analysis, including spatial autocorrelation and local spatial autocorrelation, indicated no spatial clustering (P = .46) or aggregation (P = .65) among Iran's provinces. Geographic disparities were significant (P = .000), with the northern and eastern regions showing the highest and lowest CHD prevalence, respectively. Conclusion: The overall CHD prevalence in Iran is lower than global rates, but it continues to rise. Furthermore, there are variations in birth prevalence among different regions of Iran. Environmental, genetic, socioeconomic, and diagnostic accessibility differences are possibly involved in regional variation. The limitations like heterogeneity among studies, the potential inaccuracy of reports due to limited use of accurate diagnostic methods in some studies, and the absence of population-based models to investigate prevalence, underscore the urgent need for standardized diagnostic approaches, and the utilization of population-wide birth defect registries to accurately assess CHD prevalence in Iran. [ABSTRACT FROM AUTHOR]

Background: This study aimed to comprehensively analyze the overall congenital heart disease (CHD) prevalence in live births and children in Iran, along with evaluating the spatial distribution of CHD birth prevalence across various geographical regions within the country., Methods: A Bayesian hierarchical meta-analysis (PROSPERO 2022: CRD42022331281) was performed to determine the pooled prevalence. A systematic search was conducted using Web of Science, ScienceDirect, PubMed, Iranian Research Institute for Information Science and Technology (IranDoc), Scientific Information Database (SID), and Magiran until October 4, 2023. Cross-sectional and cohort studies in both English and Persian languages, focusing on the age range of 0-10 years, were considered for the study population. The study quality was evaluated using the Agency for Healthcare Research and Quality (AHRQ) Risk of Bias tool. Heterogeneity was assessed by I 2 and τ 2 statistics, and publication bias by Egger's and Begg's tests., Results: The meta-analysis included 62 studies, revealing an overall CHD prevalence of 2.5 per 1000 births. Over time, CHD birth prevalence in Iran has consistently increased. Spatial distribution analysis, including spatial autocorrelation and local spatial autocorrelation, indicated no spatial clustering ( P =.46) or aggregation ( P =.65) among Iran's provinces. Geographic disparities were significant ( P =.000), with the northern and eastern regions showing the highest and lowest CHD prevalence, respectively., Conclusion: The overall CHD prevalence in Iran is lower than global rates, but it continues to rise. Furthermore, there are variations in birth prevalence among different regions of Iran. Environmental, genetic, socioeconomic, and diagnostic accessibility differences are possibly involved in regional variation. The limitations like heterogeneity among studies, the potential inaccuracy of reports due to limited use of accurate diagnostic methods in some studies, and the absence of population-based models to investigate prevalence, underscore the urgent need for standardized diagnostic approaches, and the utilization of population-wide birth defect registries to accurately assess CHD prevalence in Iran., (© 2024 The Author(s); Published by Kerman University of Medical Sciences This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Background: Obesity, as a risk factor for many noncommunicable diseases, is a common public health problem in developed and developing countries. Among Iranian children and adolescents, the prevalence of being overweight has increased by almost 50% in the past two decades., Aims: To visualize the geographic differences in general and abdominal obesity risks and related determinants among Iranian children and adolescents., Methods: Participants consisted of 14 880 students, aged 7-19 years, living in urban and rural areas of the Islamic Republic of Iran. Spatial patterns of obesity and its association with related risk factors were identified using Bayesian spatial modeling., Results: The highest spatial risks of general obesity (odds ratio 1.21-1.66 for males and 1.81-2.02 for females) and abdominal obesity (odds ratio 1.20-1.82 for males and 1.25-1.78 for females) were observed in the north, northwest and southwest of the country. Risk of obesity was significantly higher in areas with a higher rate of urban residence, active current smokers and prolonged screen time., Conclusion: Identification of high-risk regions for obesity and spatially related risk factors can be used as informative tools for decision-making and planning in health systems at national and subnational levels., (Copyright © World Health Organization (WHO) 2020. Open Access. Some rights reserved. This work is available under the CC BY-NC-SA 3.0 IGO license (https://creativecommons.org/licenses/by-nc-sa/3.0/igo).)

Purpose: Considering the increase in incidence of breast and cervix uteri cancers in Iran, this study investigates spatio-temporal patterns of the incidence of these two cancers by estimating the step changes between pairs of adjacent regions and between the Iranian women from 2004 to 2009., Methods: Using an adaptive smoothing model, spatio-temporal mapping of the breast and cervix uteri cancers and their changes were studied. Identification of step changes between the neighboring spatial units was carried out by modeling adjacency matrix elements as random variables., Results: There was a high relative risk of breast cancer around the central northern half of Iran, and a high relative risk of cervix uteri cancer was seen in the northeastern part of Iran. Northwest and southeast of Iran had a relatively low risk of breast and cervix uteri cancer. In general, step changes were largely similar between the two diseases with an agreement coefficient of 56%. This was observed in the Chaharmahal & Bakhtiari, and Kohgiluye & Boyerahmad provinces on the central band of Iran, as well as some eastern and northern regions on the map that were distinct from their adjacent provinces from the aspect of relative risk of both cancers., Conclusion: Identifying areas with high/low incidence risk can help health authorities to make better decisions to prevent and control breast and cervix uteri cancers and allocate resources more efficiently. In addition, determining and identifying the step changes in unexplained components of the disease risk can lead to a deeper understanding of the spatial structure of unmeasured confounding factors.

Cervical cancer in women is one of the most common cancers and breast cancer has grown dramatically in recent years. The purpose of this study was to map the incidence of breast and cervix uteri cancer among Iranian women over a 6-year period (2004-2009) searching for trend changes and risk factors. Cancer incidence data were extracted from the annual reports of the National Cancer Registry in Iran. Hierarchical Bayesian models, including random spatial and temporal effects was utilized together with bivariate, spatio-temporal shared component modelling. The provinces Tehran, Isfahan, Mazandaran and Gilan were found to have the highest relative risk (RR) of breast cancer, while the highest RR of cervix uteri cancer was observed in Tehran, Golestan, Khuzestan and Khorasan Razavi. Shared risk factors (smoking component) between the two cancers were seen to have the highest influence in Tehran, Khorasan Razavi, Yazd, Isfahan, Golestan, Khuzestan, Fars and Mazandaran, while the least were observed in Kohgiluyeh Boyerahmad. Apparent differences and distinctions between high-risk and low-risk provinces reveal a pattern of obvious dispersion for these cancers in Iran that should be considered when allocating healthcare resources and services in different areas.

Background: Breast cancer is the most frequently diagnosed cancer in women and estimating its relative risks and trends of incidence at the area-level is helpful for health policy makers. However, traditional methods of estimation which do not take spatial heterogeneity into account suffer from drawbacks and their results may be misleading, as the estimated maps of incidence vary dramatically in neighboring areas. Spatial methods have been proposed to overcome drawbacks of traditional methods by including spatial sources of variation in the model to produce smoother maps., Materials and Methods: In this study we analyzed the breast cancer data in Iran during 2004-2008. We used a method proposed to cover spatial and temporal effects simultaneously and their interactions to study trends of breast cancer incidence in Iran., Results: The results agree with previous studies but provide new information about two main issues regarding the trend of breast cancer in provinces of Iran. First, this model discovered provinces with high relative risks of breast cancer during the 5 years of the study. Second, new information was provided with respect to overall trend trends o. East-Azerbaijan, Golestan, North-Khorasan, and Khorasan-Razavi had the highest increases in rates of breast cancer incidence whilst Tehran, Isfahan, and Yazd had the highest incidence rates during 2004-2008., Conclusions: Using spatial methods can provide more accurate and detailed information about the incidence or prevalence of a disease. These models can specify provinces with different health priorities in terms of needs for therapy and drugs or demands for efficient education, screening, and preventive policy into action.

Background: The aim of this study was to model the geographical variation in incidence and risk factors of seven prevalent cancers in Iran., Methods: The data for cancers of esophagus, stomach, bladder, colorectal, lung, prostate, and female breast along with their risk factors in all 30 provinces of Iran for the year 2007 were included into study. Smoking, overweight, inadequate consumption of fruits and vegetables, socioeconomic status and low physical activity were studied as risk factors. Standardized incidence ratios were estimated using full bayesian model. In addition, the shared component model was used to explore the spatial pattern of the cancers and to estimate the relative importance of their corresponding risk factors., Results: Fars and the Northwestern provinces were observed as high risk areas and Hormozgan (a Persian Gulf coastal province), Sistan and Baluchestan, South Khorasan, and Kerman provinces located in Southeast were areas of low risk for most cancers. For all five risk factors, larger effects on incidence of the relevant cancers were found in the Northern provinces compared to other areas. Smoking, overweight, inadequate consumption of fruit and vegetable, socioeconomic status, and low physical activity were found to have more effects on incidence of stomach, breast, esophagus, and breast cancers, respectively., Conclusions: Most of the high risk areas for seven cancers were in accordance with the results for spatial patterns of related risk factors and their relative weights on relevant cancers. The multivariate shared component model of the seven cancers achieves a considerable improvement in terms of Deviance Information Criterion over the individual modeling of diseases.