Clinical Characteristics and Outcomes in Hospitalized Patients with COVID-19 and Cancer History: A Multicenter Cross-Sectional Study in Southwestern Iran.

Background: Cancer patients are more exposed to opportunistic infections, such as COVID-19, due to their poor health status. This study aimed to identify the clinical characteristics of cancer and non-cancer patients with COVID-19 that may lead to death, intubation, and ICU admission. Materials and Methods: A Multicenter Cross-Sectional study was conducted on confirmed COVID-19 adult patients with and without a history of cancer from March 2019 to March 2021. Demographic and clinical features, ICU admission, intubation, and discharge status have been extracted from patients' medical records. Chi-square, odds ratio, Mann-Whitney test, and logistic regression were used to analyze the data. Results: The death rate in 1332 cancer patients was 28% compared to the 91464 noncancer patients which was 9% with an odds ratio of 3.94 and p<0.001. ICU admission rates among the cancer group were 43%, while in the noncancer group, it was 17.9% (p<0.001). Moreover, intubation was done for 20.9% of cancer patients and 7.4% of non-cancer patients (p<0.001). However, no significant difference was observed between the two groups in terms of length of stay in the hospital. Multivariable logistic regression analysis showed that age, level of consciousness, SPO2, and autoimmune disorders were associated with mortality in cancer patients with COVID-19. Conclusion: This study showed that older age, loss of consciousness, low oxygen saturation, and suffering from autoimmune disorders were the predictors of death in cancer patients with COVID-19. These results can have important implications for the management and care of cancer patients with COVID-19.

Survey the effectiveness of education based on message framing through mobile phone on women's physical activity.

BACKGROUND: Physical activity in female employees is a healthy behavior and increases strength, endurance, improves flexibility, improves the feeling of vitality and freshness, improves health, and ultimately increases life expectancy. Health messages are one of the most effective ways to engage people and motivate them to perform healthy behaviors. The purpose of this study was to the study of the effectiveness of education based on message framing through mobile phone (whatsapp) on the physical activity of women employees of universities and higher education institutions in Ahvaz city. METHOD: In this interventional study, 90 of female employees of three universities and higher education institutions of Ahvaz city were selected by random sampling and randomly divided into three groups (30 participants) receiving gain framed messages, receiving loss framed messages and the control group. The tools of data collection were demographic information questionnaire and international physical activity questionnaire (IPAQ). The participants of the intervention groups received educational messages about physical activity behavior in two different gain and loss framed messages through whatsapp for one month. Data were collected from three groups at the beginning of the study, immediately and two months after the intervention, and were analyzed using SPSS version 26. RESULTS: The results showed that there was a significant increase in the average physical activity score after the intervention in two interventional groups. by comparing the increase of this score, 53% improvement in physical activity is observed in the gain message group and 15% in loss massage group but there was no significant increase in the control group. CONCLUSION: The results of this study showed that the design and implementation of education programs based on message framing, especially gain framed messages through online education (Whatsapp) can improve and promote physical activity behavior in women employees.

Mediating Roles of Stress, Anxiety, and Depression in the Relationship between Constipation and Sleep Quality among the Elderly: Structural Equation Modeling (SEM).

Introduction Sleep quality is an important health index in the elderly. As age increases, changes occur in sleep quality leading to sleep disorders and recurrent complaints. Sleep quality management of the elderly requires identification of its determinants. The present study aimed to determine the mediating roles of stress, anxiety, and depression in the relationship between constipation and sleep quality among the elderly using structural equation modeling (SEM). Materials and Methods A correlational design was used in the present study through structural equation modeling. In this work, 363 elderlies were examined by multi-stage random sampling. Data collection tools included four questionnaires, namely a demographic information questionnaire, the constipation questionnaire (ROME III), the Depression, Anxiety, and Stress Scale-short form, and the Pittsburgh Sleep Quality Index (PSQI), which were completed by interview and the self-report method. The SPSS Statistics for Windows, version 22.0, and SPSS AMOS (IBM Corp., Armonk, NY, USA) were used to analyze the data. Results The results indicated that the proposed model had an acceptable fit ( p < 0.000, root mean square error of approximation [RMSEA] = 0.062, comparative fit index [CFI] = 0.83, goodness-of-fit index [GFI] = 0.87, and Χ 2 /df = 1.94). The fitted model could explain 60% of the sleep quality variance. According to the proposed model, constipation could significantly predict sleep quality due to the mediation of stress, anxiety, and depression ( p < 0.05). Conclusion The constructs of this model (constipation, stress, anxiety, and depression) can be used as a reference framework to design effective interventions and improve sleep quality in old people.

Regional disparities in cancer survival in Iran: Insight from a National Surveillance of Cancer Survival in Iran (IRANCANSURV).

BACKGROUND AND OBJECTIVES: We aimed to investigate geographical disparity in cancer survival in 9 provincial population-based cancer registries in Iran from 2015 to 2016. MATERIAL AND METHOD: In the current study, data from 90,862 adult patients (aged >15 years) diagnosed with cancer were retrieved from 9 population-based cancer registries across Iran. Five-year survival rates were estimated by applying relative survival approaches. We also applied the international cancer survival standard weights for age standardization. Finally, we calculated the excess hazard ratio (EHR) for each province adjusted for age, sex, and cancer sites to estimate the excess hazard ratio of mortality compared to the capital province (Tehran). RESULTS: The largest gap in survival was observed in more curable cancer types, including melanoma (41.4%), ovary (32.3%), cervix (35.0%), prostate (26.7%), and rectum (21.4%), while the observed geographical disparity in lethal cancers such as lung, brain, stomach, and pancreas was less than 15%. Compared to Tehran, we found the highest excess hazard of death in Western Azerbaijan (EHR=1.60, 95% CI 1.51, 1.65), Kermanshah (EHR=1.52, 95% CI=1.44, 1.61), and Kerman (EHR=1.46, 95% CI=1.38, 1.53). The hazard ratio of death was almost identical in Isfahan (EHR=1.04, 95% CI=1.03, 1.06) and Tehran provinces. CONCLUSION: Provinces with higher HDI had better survival rates. IRANCANSURV study showed regional disparities in cancer survival in Iran. Cancer patients in provinces with a higher Human Development Index (HDI) had a higher survival rate and lived longer compared to the patients in provinces with medium and low HDI regions.

Sense of loneliness of veterans in Southern Iran: a cross-sectional study.

AIMS: More than three decades have passed since the end of the Iraq-Iran war, and this period has been concurrent with a rapid growth of the older community in Iran which includes the community of veterans who often suffer from serious psychological and behavioral problems. The study aimed to investigate the prevalence and determinants of loneliness in middle and older veterans in southern Iran. MATERIALS & METHODS: A cross-sectional study conducted among 583 middle and older male veterans (50 years <) who were selected by the census method in 2021. Data collection was done using UCLA Loneliness Scales. The collected data were entered into SPSS version-26 and Amos-24 and analyzed by multivariate ANOVA, multivariate regression, and structural equation at a threshold significance level of 0.05. FINDINGS: The mean score of feeling lonely in the veterans was 51.08 ± 4.74. The study found a significant relationship between the participants' education and their feeling of loneliness (P-value = 0.01, effect size = -0.31). Multivariate regression demonstrated that demographic variables (i.e., age, employment status, level of education, type of living) and the severity and type of injury predict 31% of the variance in the middle and older veterans' feeling of loneliness. CONCLUSION: The mental, psychological and physical effects of war disability were associated with the social functions of veterans in the family and community. Strategies such as increasing social support and psychological counseling for veterans along with improving their pension and income can be effective in promoting public health, especially the mental health of this group.

Relationship between health literacy and generalized anxiety disorder during the COVID-19 pandemic in Khuzestan province, Iran.

Introduction: During the COVID-19 pandemic, many changes occurred in various cultural, social, and economic fields, leading to the creation of psychological effects, especially anxiety, in the community. Fear and anxiety about emerging diseases (COVID-19) and less participation in preventive behaviors reduce individual resistance and ultimately lower one's quality of life. Therefore, we aimed to investigate the relationship between health literacy and generalized anxiety disorder during the COVID-19 pandemic in Khuzestan province, Iran. Methods: This was a descriptive-analytical (cross-sectional) study conducted among participants aged 18-65 in Khuzestan province during the years 2020-2021 through online sampling. Due to the prevalence of COVID-19 and the impossibility of face-to-face communication, the questionnaire was designed on the Porseline Survey website and the questionnaire link was provided to participants through WhatsApp and Telegram. The data collection tool includes the Iranian Health Literacy Questionnaire, which includes 33 items, and the Generalized Anxiety Disorder-7 scale, which has 7 items based on a Likert scale. Data analysis was performed using STATA14 software and descriptive and analytical statistical tests at a significant level less than 0.05. Results: The mean (standard deviation) score for health literacy was 52.9 ± 9.3 and for generalized anxiety disorder was 5.2 ± 3.1. A significant negative correlation was found between the mean of anxiety disorder and health literacy (p < 0.05). The frequency of health literacy in individuals included 427 (37.8%) with inadequate health literacy, 628 (55.6%) with marginal health literacy, and 75 (6.6%) with sufficient health literacy. There was a statistically significant difference between the mean of generalized anxiety disorder among individuals with different levels of health literacy (p < 0.05). Conclusion: As the level of health literacy increases, the prevalence of generalized anxiety disorder caused by fear of COVID-19 decreases. Therefore, increasing awareness and health literacy about this virus, its transmission, and prevention methods is very effective in managing anxiety and stress caused by COVID-19. Paying attention to the issue of health literacy and generalized anxiety disorder, and promoting preventive behaviors can be effective tools for planners, health officials, and policymakers to promote health literacy for any type of disease.

Factor affecting the activities of daily living among aging people during the COVID-19 pandemic - a structural equation modelling.

Introduction: The activities of daily living (ADLs) are a set of basic skills necessary for self-care. The inability of elderly people to perform ADLs leads to dependence, insecure conditions, and poor quality of life. The COVID-19 pandemic has affected all aspects of the daily life of the elderly. This study aimed to determine the factors associated with ADLs among elderly people during the COVID-19 pandemic using structural equation modelling/path analysis. Material and methods: It was a descriptive-analytical study which had conducted on 487 elderly people who were selected randomly to participate in the study. Data collection tools included a demographic information questionnaire, an activities of daily living questionnaire, a knee pain and personal performance questionnaire Western Ontario and McMaster Universities Osteoarthritis (WOMAC), and the falls efficacy scale, which were completed by interview and self-report methods. SPSS-22 and AMOS software were used for data analysis. Results: Two structures of the fear of falling (FOF) and knee pain and personal performance questionnaire WOMAC had a significant role in explaining the ADL variance among the studied elderly people (p < 0.001, root mean square error of approximation = 0.063). These variables explained 64% of the ADL variance. Conclusions: The structures of this model (FOF and WOMAC) can be used as a reference framework to design effective interventions for improving ADLs among elderly people during the COVID-19 epidemic. It is also recommended that a multi-component program be provided, which includes exercise and psychological strategies for this population during the COVID-19 pandemic through online videos, distance health programs, etc.

National surveillance of cancer survival in Iran (IRANCANSURV): Analysis of data of 15 cancer sites from nine population-based cancer registries.

Cancer survival is a key indicator for the national cancer control programs. However, survival data in the East Mediterranean region (EMR) are limited. We designed a national cancer survival study based on population-based cancer registries (PBCRs) from nine provinces in Iran. The current study reports 5-year net survival of 15 cancers in Iranian adults (15-99 years) during 2014 to 2015 in nine provinces of Iran. We used data linkages between the cancer registries and the causes of death registry and vital statistics and active follow-up approaches to ascertain the vital status of the patients. Five-year net survival was estimated through the relative survival analysis. We applied the international cancer survival standard weights for age standardization. Five-year survival was highest for prostate cancer (74.9%, 95% CI 73.0, 76.8), followed by breast (74.4%, 95% CI 72.50, 76.3), bladder (70.4%, 95% CI 69.0, 71.8) and cervix (65.2%, 95% CI 60.5, 69.6). Survival was below 25% for cancers of the pancreas, lung, liver, stomach and esophagus. Iranian cancer patients experience a relatively poor prognosis as compared to those in high-income countries. Implementation of early detection programs and improving the quality of care are required to improve the cancer survival among Iranian patients. Further studies are needed to monitor the outcomes of cancer patients in Iran and other EMR countries.

Machine Learning Models to Predict In-Hospital Mortality among Inpatients with COVID-19: Underestimation and Overestimation Bias Analysis in Subgroup Populations.

Prediction of the death among COVID-19 patients can help healthcare providers manage the patients better. We aimed to develop machine learning models to predict in-hospital death among these patients. We developed different models using different feature sets and datasets developed using the data balancing method. We used demographic and clinical data from a multicenter COVID-19 registry. We extracted 10,657 records for confirmed patients with PCR or CT scans, who were hospitalized at least for 24 hours at the end of March 2021. The death rate was 16.06%. Generally, models with 60 and 40 features performed better. Among the 240 models, the C5 models with 60 and 40 features performed well. The C5 model with 60 features outperformed the rest based on all evaluation metrics; however, in external validation, C5 with 32 features performed better. This model had high accuracy (91.18%), F-score (0.916), Area under the Curve (0.96), sensitivity (94.2%), and specificity (88%). The model suggested in this study uses simple and available data and can be applied to predict death among COVID-19 patients. Furthermore, we concluded that machine learning models may perform differently in different subpopulations in terms of gender and age groups.

Relationship Between Mental Health and Death Anxiety During COVID-19 Pandemic in Dental Staff and Students: A Cross-Sectional Study.

Objective: We aimed to determine the mental health and death anxiety among dental staff and students in school of dentistry during COVID-19 pandemic. Methods: It was a cross-sectional study among students (n = 300) and staff (n = 60) in School of dentistry in Ahvaz University of Medical Sciences during 2020. The instruments were a demographic questionnaire, Death Anxiety Scale, and Kessler Questionnaire. Data was analyze by using SPSS version 22, in all tests, the significance level was set at <0.05. Results: The mean age of dental students and personnel was 23.96 and 40.08 years, respectively. The mean scores of death anxiety were higher in dental staff (8.53) than students (6.02) and the mean scores of mental health status were higher in students (14.78) than personnel (9.18). This indicates that death anxiety was higher in Dental staff, while students were in better mental health status. The correlation coefficient between death anxiety and mental health status was 0.366 among students (p < 0.001), while it was 0.429 among dental staff (p < 0.001), showing a medium relationship between death anxiety and mental health in both groups. Conclusion: The overall findings represent a significant but contradictory relationship between mental health status and death anxiety among dental staff and students during the prevalence of COVID-19 pandemic. This suggests the impact of confounding factors in this area, which can be studied by future researchers and policy makers to design health promotion interventions.

Oral Health-Related Quality of Life Among Narcotic and Stimulant Users Referred to Maintenance Methadone Therapy Centers in Ahvaz City: Iran.

Introduction: We aimed to assess quality of life related to oral health in narcotic or stimulant users those were referred to maintenance methadone therapy (MMT) centers in Ahvaz City, Iran. Methods: It was a cross-sectional study based on exploratory approach which has conducted on 187 narcotic and stimulant users in Ahvaz city; during 15th May till September 2020. Data was selected by available non-random sampling method. The data collection tools included the demographic variables and the standard OHIP-14 questionnaires. All tests were used as descriptive statistics, Kolmogorov-Smirnov tests, independent t-test, one-way analysis of variance. P-values of less than 0.05 was considered significant. Results: The mean and standard deviation of the participants' age was 36.03 ± 8.98 years. The quality-of-life scores related to oral health were totally 34.89 ± 6.50 as well as 37.37 and 33.96 in narcotic and stimulant users, respectively. The total quality of life related to OHIP-14 did not have a significant relationship with variables of age, life companions, level of education, number of children, economic status, employment status, insurance status, underlying disease, toothbrush use status, last dentist visit, and number of missing teeth (P > 0.05). However, a significant difference was found between the quality of life related to oral health based on the type of substance used (narcotic or stimulant), so that the mean quality of life related to oral health was higher in narcotic than stimulant users (P < 0.05). Conclusion: Quality of life related to OHIP-14 was more unfavorable in stimulant users than narcotic users. So, policy makers and authorities are required to focus their interventions and research programs to improve health-related quality of life in users, especially stimulant.

Higher education students' achievement emotions and their antecedents in e-learning amid COVID-19 pandemic: A multi-country survey.

The outbreak of the COVID-19 pandemic has had a wide range of negative consequences for higher education students. We explored the generalizability of the control-value theory of achievement emotions for e-learning, focusing on their antecedents. We involved 17019 higher education students from 13 countries, who completed an online survey during the first wave of the pandemic. A structural equation model revealed that proximal antecedents (e-learning self-efficacy, computer self-efficacy) mediated the relation between environmental antecedents (cognitive and motivational quality of the task) and positive and negative achievement emotions, with some exceptions. The model was invariant across country, area of study, and gender. The rates of achievement emotions varied according to these same factors. Beyond their theoretical relevance, these findings could be the basis for policy recommendations to support stakeholders in coping with the challenges of e-learning and the current and future sequelae of the pandemic.

Academic student satisfaction and perceived performance in the e-learning environment during the COVID-19 pandemic: Evidence across ten countries.

The outbreak of the COVID-19 pandemic has dramatically shaped higher education and seen the distinct rise of e-learning as a compulsory element of the modern educational landscape. Accordingly, this study highlights the factors which have influenced how students perceive their academic performance during this emergency changeover to e-learning. The empirical analysis is performed on a sample of 10,092 higher education students from 10 countries across 4 continents during the pandemic's first wave through an online survey. A structural equation model revealed the quality of e-learning was mainly derived from service quality, the teacher's active role in the process of online education, and the overall system quality, while the students' digital competencies and online interactions with their colleagues and teachers were considered to be slightly less important factors. The impact of e-learning quality on the students' performance was strongly mediated by their satisfaction with e-learning. In general, the model gave quite consistent results across countries, gender, study fields, and levels of study. The findings provide a basis for policy recommendations to support decision-makers incorporate e-learning issues in the current and any new similar circumstances.

A study to design minimum data set of COVID-19 registry system.

BACKGROUND: From the beginning of the COVID-19 pandemic, the development of infrastructures to record, collect and report COVID-19 data has become a fundamental necessity in the world. The disease registry system can help build an infrastructure to collect data systematically. The study aimed to design a minimum data set for the COVID-19 registry system. METHODS: A qualitative study to design an MDS for the COVID-19 registry system was performed in five phases at Ahvaz University of Medical Sciences in Khuzestan Province in southwestern Iran, 2020-2021. In the first phase, assessing the information requirements was performed for the COVID-19 registry system. Data elements were identified in the second phase. In the third phase, the MDS was selected, and in the four phases, the COVID-19 registry system was implemented as a pilot study to test the MDS. Finally, based on the experiences gained from the COVID-19 registry system implementation, the MDS were evaluated, and corrections were made. RESULTS: MDS of the COVID-19 registry system contains eight top groups including administrative (34 data elements), disease exposure (61 data elements), medical history and physical examination (138 data elements), findings of clinical diagnostic tests (101 data elements), disease progress and outcome of treatment (55 data elements), medical diagnosis and cause of death (12 data elements), follow-up (14 data elements), and COVID-19 vaccination (19 data elements) data, respectively. CONCLUSION: Creating a standard and comprehensive MDS can help to design any national data dictionary for COVID-19 and improve the quality of COVID-19 data.

Multiple factors associated with life satisfaction in older adults.

INTRODUCTION: The population of older adults is increasing as science progresses and health conditions improve. Social, psychological and behavioral factors will influence life satisfaction in older adults. We aimed to assess multiple factors associated with life satisfaction in older adults in Qom city, Iran. MATERIAL AND METHODS: It was a descriptive-analytical study which has conducted on 679 older adults through convenience sampling from Qom city, Iran during 2018. The data were collected using demographic characteristics, life satisfaction, well-being, cognitive status, social support, and daily activities of life questionnaire. Data were analyzed by SPSS version 22 software and independent t-test, ANOVA, Pearson's correlation coefficient and multiple regression analysis. RESULTS: The mean older adult's age was 70.43 ± 7.62 years. The mean life satisfaction score was 13.77 ± 3.73. The results showed a significant relationship of job and education with life satisfaction (p < 0.001). The results also showed that social support (p = 0.001) and daily activities (p = 0.017) significantly predict the level of life satisfaction, and the dimensions of health (p = 0.001) and cognitive status (p = 0.007) have a larger share in predicting the satisfaction of older adults' life. CONCLUSIONS: We found that some parts of life changes in older adults can be predicted with the help of social support, health status, cognitive status, and everyday life activities. Therefore, in order to increase the level of life satisfaction of older adults, it is suggested that promotion of social support, health status, and cognitive status be provided.

Cancer in Iran 2008 to 2025: Recent incidence trends and short-term predictions of the future burden.

Policymakers require estimates of the future number of cancer patients in order to allocate finite resources to cancer prevention, treatment and palliative care. We examine recent cancer incidence trends in Iran and present predicted incidence rates and new cases for the entire country for the year 2025. We developed a method for approximating population-based incidence from the pathology-based data series available nationally for the years 2008 to 2013, and augmented this with data from the Iranian National Population-based Cancer Registry (INPCR) for the years 2014 to 2016. We fitted time-linear age-period models to the recent incidence trends to quantify the future cancer incidence burden to the year 2025, delineating the contribution of changes due to risk and those due to demographic change. The number of new cancer cases is predicted to increase in Iran from 112 000 recorded cases in 2016 to an estimated 160 000 in 2025, a 42.6% increase, of which 13.9% and 28.7% were attributed to changes in risk and population structure, respectively. In terms of specific cancers, the greatest increases in cases are predicted for thyroid (113.8%), prostate (66.7%), female breast (63.0%) and colorectal cancer (54.1%). Breast, colorectal and stomach cancers were the most common cancers in Iran in 2016 and are predicted to remain the leading cancers nationally in 2025. The increasing trends in incidence of most common cancers in Iran reinforce the need for the tailored design and implementation of effective national cancer control programs across the country.

Relationship between Life Satisfaction and Sleep Quality and Its Dimensions among Older Adults in City of Qom, Iran.

Background and Objective: Assessment of sleep quality is necessary in the older adults' management program so that good sleep quality will lead to a successful older adult's life. The present study aims to determine the relationship between life satisfaction and quality of sleep and its dimensions among the older adults' population residing in Qom city, Iran.Method: This was a cross-sectional descriptive-analytic study conducted in 2018. The population of the study consisted of older adults resident Qom, of whom 679 were selected by simple sampling. The data were collected using demographic characteristics, Life Satisfaction Inventory-Z(LSI-Z) and Pittsburgh Sleep Quality Index (PSQI). Data were analyzed with statistical package SPSS (version 22) using independent t-test, and one-way analysis of variance (ANOVA).Results: The mean ± standard deviation (SD)of the older adults was 70.43 ± 7.62 years. Mean of life satisfaction score and sleep quality were 13.00 ± 3.00 and 10.00 ± 3.00, respectively. There was a significant relationship between life satisfaction and sleep quality (P < .001). Moreover, life satisfaction was associated with the use of hypnotic drugs, mental sleep quality, daily functional disorders, and sleep disorders (P < .001). There was a significant relationship between sleep duration (P = .003) and delay to fall asleep (P = .048) with life satisfaction. However, there was no significant relationship between life satisfaction and sleep efficiency (P = .226).Conclusion: Our findings showed that sleep quality was not desirable in older adults. On the other hand, sleep quality and its dimensions were related to the satisfaction of life among the older adults. It is necessary to utilize solutions to improve the sleep quality in the older adults' community.

Regional COVID-19 registry in Khuzestan, Iran: A study protocol and lessons learned from a pilot implementation.

Disease registry systems provide a strong information infrastructure for decision-making and research. The purpose of this study is to describe the implementation method and protocol of the COVID-19 registry in Khuzestan province, Iran. We established a steering committee and formulated the purposes of the registry. Then, based on reviewing the literature, and expert panels, the minimum data set, the data collection forms and the web-based software were developed. Data collection is done retrospectively through Hospital Information Systems, Medical Care Monitoring Center system (MCMC), Management of Communicable Disease Prevention and Control system (MCDPC) as well as, patients' records. For prospective data collection, the data collection forms are compiled with patients' medical records by the medical staff and are then entered into the registry system. We collect patients' administrative and demographic data, history and physical examinations, test and imaging results, disease progression, treatment, outcomes, and follow-ups of the confirmed and suspected inpatients and outpatients. From April 20 to December 5, 2020, the data of 4,812 confirmed cases and 7,113 suspected cases were collected from two COVID-19 referral hospitals. Based on our experience, recording information along with providing care for patients and putting patients' data registration in the medical staff's routine, structuring data, having a flexible technical team and rapid software development for multiple and continuous updates, automating data collection by connecting the registry to existing information systems and having different incentives, the registration process can be strengthened.

Prenatal exposure to ambient air pollution and adverse pregnancy outcomes in Ahvaz, Iran: a generalized additive model.

OBJECTIVE: There is some evidence about the short-term effects of air pollutants on adverse pregnancy outcomes. The aim of this study was to determine the association between air pollutants and spontaneous abortion, stillbirth, gestational hypertension, preeclampsia, gestational diabetes and macrosomia in Ahvaz, which is one of the most polluted cities in the Middle East. METHODS: Data on adverse pregnancy outcomes and air pollutants including ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particles with a diameter of less than 10 µm (PM10) and particles with a diameter less than 2.5 µm (PM2.5) were inquired from the Health Department of Ahvaz Jundishapur University of Medical Sciences and the Environmental Protection Agency of Khuzestan Province for the years 2008-2018. A time series analysis using the generalized additive model (GAM) with up to 6-day lags was used. RESULTS: The results showed that the SO2 pollutant on 0, 1, 3, 4, and 6-day lags and PM10 on lag 0 had direct and significant associations with spontaneous abortion. NO, NO2 and CO on 0-6-day lags, and O3 on 6-day lags showed direct and significant associations with preeclampsia. NO and NO2 pollutants showed significant and direct associations with gestational diabetes, during 0- and 6-day lags. NO on 0-, 3- and 4-day lags, CO in all 0-6-day lags and PM2.5 on 1-, 3-, 5-, and 6-day lags showed direct and significant associations with macrosomia. None of the pollutants showed significant associations with stillbirth or gestational hypertension. CONCLUSIONS: The results of this study suggest that some air pollutants are associated with spontaneous abortion, preeclampsia, gestational diabetes and macrosomia. This study further emphasizes the need to control ambient air pollution.