Showing 48 results for Haghdoost
Aa Haghdoost, A Mirzazadeh,
Volume 2, Issue 1 (23 2006)
Abstract
Background & Objectives: There is no shortage of evidence linking coronary heart disease (CHD) to various genetic and environmental factors. Nonetheless, exploring the familial aggregation of major risk factors in the Iranian population could add valuable information to the existing body of knowledge.
Methods: We received data on 656 families (1614 individuals) from the Provincial Health Authority in Kerman. The data had been originally collected in a nationwide non-communicable disease control project, under the auspices of the Health Ministry's Public Health Department.
In this study, we divided subjects into high- and low-risk groups based on the 75th percentiles of risk factor levels. Using a random-effect Poisson regression model, we looked at the association between risk factors within families. In all models, the risk ratios (RR) were adjusted for the age gap between parents and children.
Results: Excessive weight in children showed a stronger association with overweight in the father than with the same problem in the mother (RR: 2.35 versus 1.59). Risk of high blood pressure in the father was significantly related to the risk in the mother and the child. The risk of high blood glucose showed a significant association only between parents. Similarly, hypercholesterolemia did not show a significant association between parents and children, but its RR in parent-parent associations was around 2. We did not find any significant familial aggregation for smoking. However, physical exercise in mothers doubled the rate of exercise in other family members.
Conclusions: Although our sample size was relatively small, we found stronger associations within parent couples than between parents and children. This implies that common lifestyle may be a more prominent factor than genetic make-up.
M Osooli, Aa Haghdoost, Sh Yarahmadi, Mh Foruzanfar, M Dini, K Holakouie Naieni,
Volume 5, Issue 1 (20 2009)
Abstract
Background and Objectives: The aim of this study was to assess the geographical distribution of Congenital Hypothyroidism (CH) in Iran using Geographic Information System
Methods: The incidence of Congenital Hypothyroidism in each city and province calculated based on national CH screening program and then the map of its distribution was depicted. The spatial distribution of CH was assessed in each city by employing binominal test and Hotspot Analysis. The map of distribution of CH was drawn by ArcGIS version 9.2 software.
Results: The national incidence of CH (including both transient and permanent types) has been estimated 2.2/1000 in screened new borne babies. The distribution of CH seems more or less equally around the country and its spatial variation was not statistically significant. We did not find any specific CH Hot Spot in Iran.
Conclusions: We did not find any particular explanation for high incidence of CH is Iran geographically therefore other explanations for such a high risk in screened neonates should be investigated including the non-environmental factors and factors related to quality of screening program in Iran.
Aa Haghdoost,
Volume 5, Issue 1 (20 2009)
Abstract
Sample size estimation is one of the crucial issues in the research methodology in medical sciences. It is an important issue for not only researchers but also readers of medical papers their frequent questions show how much they need to simple but accurate information.
This paper presents the basic concepts of sample size calculation, and simplifies complicated issues using concrete examples to clarify the concept of sample size estimation for none-professional readers in statistics. The paper starts with explaining the basic concepts of sample size calculation such as effect size, confidence interval and confidence coefficient, statistical errors, and assumptions in sample size calculation. Then, it presents the common formulae in the sample size calculation to estimate a mean, a proportion, to compare two means and to compare two proportions.
Aa Haghdoost, A Pourkhandani, Sh Motaghipisheh, B Farhoudi, N Fahimifar, B Sadeghirad ,
Volume 6, Issue 4 (16 2011)
Abstract
Background & Objective: the number of people with HIV/AIDS in Iran is increasing. Populations' knowledge and awareness are crucial steps to prevent HIV/AIDS epidemic. This systematic review aimed to assess the level of knowledge and attitude toward HIV/AIDS in Iranian population.
Methods: Reviewing related titles in national and international databanks resulted in 62 eligible studies published between 1998 and 2008. To explore the source(s) of heterogeneity, meta-regression model was used.
Results: Due to the methodological diversity of included studies (e.g. their sampling or data collection methods) pooled estimation of the results were hard to be applied. The mean for knowledge score among 24 eligible studies (including 24,011 individuals) varied between 14.7 and 84.0 out of 100. Among those 16 eligible studies (including 11,104 individuals), the reported mean for attitude varied between 32.6 and 78.4 out of 100.
Conclusion: In overall, it seems that the knowledge and attitude in Iranian population still need to be improved however, the results from our systematic review showed a considerable heterogeneity among the results that can be originated from the diversity of target populations and/or their methodology of included studies. Planning for further targeted programs and modifying public education for more effective schemes are necessary to be emphasized, as there was not a significant change in the level of knowledge or attitude based on the included studies.
Aa Haghdoost, Mr Baneshi, M Marzban,
Volume 7, Issue 2 (19 2011)
Abstract
In the previous paper, the basic concepts of sample size calculation were presented. This paper explores main post-calculation adjustments of the sample size calculation in special circumstances such as multiple group comparisons, unbalanced studies (with unequal number of subjects in different groups) sample size correction for missing data, and adjustment for finite population size. In addition, the concept of design effect in multi-stage sampling
Mr Farokhi Noori, K Holakouie Naieni, Aa Haghdoost, A Emami,
Volume 8, Issue 1 (20 2012)
Abstract
Background
& Objectives: The economic costs of cancer care are a burden to people
diagnosed with cancer, their families, and society as a whole. Despite several
studies about cancer in Iran, there is paucity of cost analysis in this area.
The aim of this study was to estimate the cost of cancer subgroups in Kerman,
Iran.
Methods: A retrospective analysis
of administrative 223 diagnosed patients with different cancers was undertaken.
Results: Monthly average cost of
cancer was 3.32 thousand US dollars (average exchange rate in 2010: 10308
Iranian rials= 1 US dollar). Breast cancer, with an average 4.30 thousand US
dollars per month was the most expensive and cancer of male reproductive organs
with average2.16 thousand US dollars were the cheapest cancer.
The
hidden monthly cost of all types of cancer was 2 thousand US dollars, breast
cancer, lung, blood and female reproductive organs were costly and brain and
peripheral nerves cancer, gastrointestinal tract and prostate were medium and
male reproductive organs cancer was less costly.
Conclusion: Economically impact and burden of cancer should be an
important consideration in the health policy making in Iranian health service
system.
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M Karami, H Soori, Y Mehrabi, Aa Haghdoost, Mm Gouya,
Volume 8, Issue 3 (17 2012)
Abstract
Background & Objectives: Knowledge of the presence of seasonal trends and other explainable patterns in the prediagnostic data sources and removing such patterns before applying outbreak detection methods seem very important. This study aimed to detect and remove the explainable patterns such as seasonality, day-of-week (DOW) and holiday effects of the daily counts of suspected cases of measles in Iran.Methods: Data on daily counts of suspected cases of measles as a pre-diagnostic data source were obtained from Iranian national surveillance system between 21 March 2008 and 20 March 2011. We used lines plot, moving average chart, autocorrelation and partial autocorrelation functions for detecting explainable patterns. Moving average (MA) and Holt- Winters (HW) exponential smoothing method are used for removing explainable patterns.
Results: Our findings indicate the presence of seasonality, DOW effect, holidays and weekend effects in the daily counts of suspected cases of measles. The good performance of HW exponential smoothing technique in removing seasonal patterns is evident. MA technique showed better performance regarding assumption violation on outbreak detection methods.
Conclusion: Because of the presence of explainable patterns in the daily counts of suspected cases of measles, considering such patterns before applying outbreak detection algorithms is very important. Implementing both MA (7 days) techniques for its simplicity as a pre- processing method and HW method for its efficacy in removing seasonal patterns is recommended.
M Karami, H Soori, Y Mehrabi, Aa Haghdoost, Mm Gouya,
Volume 8, Issue 3 (17 2012)
Abstract
Background & Objectives: Evaluating the performance of outbreak detection methods using real data testing provide the highest degree of validity. The aim of this study was to determine the performance of the Exponentially Weighted Moving Average (EWMA) in real time detection of two local outbreaks in Iran.
Methods: The EWMA algorithm (both ƛ= 0.3 and 0.6) applied on daily counts of suspected cases of measles to detect local outbreaks which had been occurred in Mashhad and Bandar Abbas cities during 2010. The performance of The EWMA algorithms were evaluated using real data testing approach and reported by correlation analysis.
Results: Mashhad outbreak was detected with a delay of about 2 to 7 days using EWMA algorithms as outbreak detection method while the utility of EWMA algorithms in real time detection of Bandar Abbas’ outbreak were on time good optimal. Maximum correlation value for EWMA 2 in relation to Mashhad outbreak was 0.60 at lag 2.
Conclusion: Applying the EWMA algorithm as an outbreak detection method at local levels is not suggested. However the characteristics of data are determinant of the performance of such detection methods.
M Karami, H Soori, Y Mehrabi, Aa Haghdoost, Mm Gouya, N Esmailnasab,
Volume 9, Issue 2 (Vol 9, No 2, Summer 2013 2013)
Abstract
Background & Objectives: Timely response to emerging diseases and outbreaks are a major public health and health systems priority. There are few published studies that evaluate the performance of cumulative sum (CUSUM) on identical data using semi- synthetic simulation approach. This study was undertaken to determine the performance of the CUSUM in timely detection of 831 days of simulated outbreaks.
Methods: We evaluated the performances of the CUSUM as an outbreak detection method on simulated outbreaks injected to daily counts of suspected cases of measles as baseline data in Iran between 21 March 2008 till 20 March 2011. Data obtained from the Iranian national surveillance system. The performance of algorithms was evaluated using sensitivity, false alarm rate, likelihood ratios and Area under the Receiver Operating Characteristic (ROC) curve.
Results: Generally the sensitivity of the CUSUM algorithm in detecting simulated outbreaks was 50%
(95% CI: 47- 54). The corresponding values are disaggregated according to outbreak size, shape and duration. The CUSUM algorithm detected the half of outbreaks after 13.84 days on average.
Conclusion: We concluded that CUSUM algorithm performed good in detection of large outbreaks with short periods and poorly in detecting long period outbreaks, particularly those simulated outbreaks that did not begin with a surge of cases.
P Bagheri, Aa Haghdoost, E Dortaj Rabori,
Volume 9, Issue 3 (2-2014)
Abstract
Background & Objectives: Nowadays, human values for example quality of life has important place to be considered as health index along with other measurements like morbidity and mortality indexes. This study intended to compare the quality of life for residents living in apartment’s flats more than 15 years with residents living in non-apartment housing in Shiraz.
Methods: The World Health Organization Quality of Life (WHOQOL_BREF) standard questionnaire was completed by participants. This population was chosen by a multi-stage sampling method in Shiraz city. Type of living accommodation, physical, psychological, social, and environmental health factors were adjusted in the linear model.
Results: The mean score of health aspects in people who lived in apartment vs non apartment living were: physical 13.57 and 16.41, psychological 10.71and 14.87, social 8.57and 13.84 and in environmental 13.59 and 10.18 respectively, however after adjustment for gender, education, marital status, age, job, family size, income, type of disease (chronic, acute, chronic- acute), possession of house and area of house, changed to 14.41 for physical and 15.61, psychological 12.6 and 14.47, social 8.74 and 13.72 and environmental 15.42 and 9.23 (P<0.0001).
Conclusion: The results of this study show that the health of apartment-living residents even after adjustment of some other influencing factors, in major of domains was less than non apartment-living residents which indicating this issue should be considered in urban-living health.
M Shokouhi, E Mohebbi, A Rastegari, S Hajimaghsoudi, Aa Haghdoost, Mr Baneshi,
Volume 10, Issue 1 (Vol 10, No 1 2014)
Abstract
Knowing the population size of rare diseases or special subpopulations like injection drug users (IDUs) is one of the most important challenges in public health and health surveillance systems but it is difficult to estimate these groups. During the last few years, new methods have been suggested to estimate hidden or hard-to-reach populations, one of which is the network scale-up method (NSUM). The NSUM itself includes measuring the personal network size and estimating the prevalence of hidden and hard-to-count populations. In this paper, we basically discussed the indirect methods of calculating the population size, and the history of NSUM and its concepts, and then addressed the estimation of hidden populations with NSUM and the applicable notes for such populations.
A Asadabadi , A Bahrampour, Aa Haghdoost,
Volume 10, Issue 3 (Vol 10, No.3 2014)
Abstract
Background and Objectives : recent years, considerable attention has been paid to statistical models for classification of medical data according to various diseases and their outcomes. Artificial neural networks have been successfully used for pattern recognition and prediction since they are not based on prior assumptions in clinical studies. This study compared two statistical models, artificial neural network and logistic regression, to predict the survival of patients with breast cancer.
Methods: Two models were applied on cancer registry data, Kerman, southeast of Iran, to predict survival. The data of 712 breast cancer patients in the age group 15 to 85 years was used in this study. The logistic regression and three-layer perceptron neural network models were compared in terms of predicting the survival. Sensitivity, specificity, prediction accuracy, and the area under ROC curve were used for comparing the two models.
Results : In this study, the sensitivity and specificity of logistic regression and artificial neural network models were (0.594, 0.70) and (0.621, 0.723), respectively. Prediction accuracy and the area under ROC curve for two models were (0.688, 0.725) and (0.70, 0.725), respectively.
Conclusion: Although there were insignificant differences in the performance of the two models for predicting the survival of the patients with breast cancer, the corresponding results of artificial neural network were more appropriate for predicting survival in such data.
S Daneshi, Aa Haghdoost, Mr Baneshi, F Zolala,
Volume 10, Issue 3 (Vol 10, No.3 2014)
Abstract
Background & Objectives: After an earthquake, casualty information is needed for planning and providing health care. However, developing countries do not have an efficient health information system even in normal conditions. In these countries, health information systems become worse in critical conditions. The aim of this study was to estimate the number of mortalities, limb amputations, and spinal cord injuries after the Bam earthquake.
Methods: In this cross sectional study, the network scale up method was used to estimate the number of casualties. We selected 80 residents of Bam and asked them whether they knew any one with spinal cord injury or limb amputation in three houses on the right and three houses on the left.
Results: The total estimated number of deaths was 54,041 in the earthquake. The number of people with spinal cord injury and limb amputation was 622 and 519, respectively.
Conclusion: For tertiary prevention measures and better resource allocation, an accurate health information system is needed. In the absence of such a system, there are limitations in using direct methods. It sounds that the network scale up method is an appropriate method for estimating such casualties.
A Raeisvandi, Aa Haghdoost, Mr Baneshi, S Garousi, S Farvahari, F Zolala,
Volume 10, Issue 4 (Vol 10, No 4 2015)
Abstract
Background and Objectives : Knowledge transition is an important issue in social epidemiology. Taking into account the importance of knowledge translation network among vulnerable young people in closed environments, this study was conducted to recognize and survey knowledge transition in school lessons. The study aimed at teenagers residing in orphanages in the city of Kerman, using social network analysis.
Methods: The study samples of this cross-sectional study were all teenagers aged 12-18 years old residing in orphanages. Data was collected via a checklist. In order to study the structural cohesion of social networks and the position of teenagers, density and centrality indices were calculated. Local structure of networks was studied using the triad census method. Finally, the effects of independent variables on indegree index were investigated using a mixed model.
Results : The mean density in knowledge transition was 0.34 (0.42 and 0.27 in girls and boys, respectively. (P=0.2)). Completely null and completely mutual triads were 17.1% and 11.2% in girls and 33.7% and 0.09% in boys, respectively. Indegree increased with an increase in age (P<0.001), the average of the scores in school exams (P=0.002), and studying non school materials (P=0.04).
Conclusion: Age, average score of school exams, and studying non school materials were important factors in indegree. In general, density of social network was rather low. The rate of knowledge transition was small. Therefore, activities are required to enhance knowledge sharing and transition.
H Sharifi, Aa Haghdoost,
Volume 11, Issue 1 (Vol 11, No 1 2015)
Abstract
Background & Objectives : Management of time-dependent variables is the advantages of survival analysis. This study compares time-dependent and -independent variables in survival analysis in culling of dairy cows.
Methods: In this historical cohort, 7067 dairy cows in the Province of Tehran were recruited. Cows were followed to the next calving or culling. Data on the occurrence of health disorders, calving season, parity, and milk production was obtained. Model 1 treated diseases as time-independent covariates. In models 2, up to 5 diseases were considered time-dependent covariates. For each observation, we split follow-up time in intervals each corresponding to a different lactation month using Lexis expansion of the original dataset. Model 2 assumed that an animal experienced a certain disease from the beginning of the occurrence of that disease by the end of the period. Model 3 assumed that cows were at risk from the begging of the study until the disease occurred (inverse of model 2). In models 4 and 5, an animal was assumed to experience a certain disease for 1 month if the disease occurred during this period. In Model 4 assumed diseases occurred only one time, and in model 5, multiple disease occurrences at different months were considered as different episodes.
Results : AIC in model 1 and 5 was 10809 and 10366 moreover, BIC was 10926 and 10528. According to this numbers and the shape of the Cox-Snell Residuals, model 5 with Gompertz distribution was the best model.
Conclusion : Models without time dependency tended to seriously underestimate the risk of a disease on culling.
Y Mokhayeri , Aa Haghdoost, M Mahmoudi, M Asadi-Lari, Ss Hashemi Nazari , S Taravat Manesh , N Rajaie, Z Khorrami, K Holakouie-Naieni ,
Volume 11, Issue 2 (Vol 11, No 2 2015)
Abstract
Background & Objectives: Measuring the impact of various diseases on Life Expectancy( LE) is an important step toward prioritization in health. The present study was conducted to measure the impact of heart diseases, neoplasm, and respiratory diseases on life expectancy (LE) in 2010.
Methods: Data on death and population for all 22 districts of Tehran were obtained from the main cemetery of Tehran and statistical center of Iran, respectively. Age-specific mortality rates and consequently LE were calculated for all 22 districts and both genders. Finally, the death probability assuming complete elimination of the diseases was calculated and the resulting life tables were obtained.
Results: The LE at birth was estimated 74.6 and 78.4 years for total males and females in Tehran, respectively. The maximum and minimum LE at birth was 80 years in females and 72.7 years in males, respectively. Assuming complete elimination of heart diseases, the LE increased to 82.39 and 85.51 years in males and females, respectively while complete elimination of neoplasm resulted in an increase in LE to 76.27 years in men and 80.49 years in women. Finally, elimination of respiratory diseases increased the LE of men to 75.98 years and the LE of women to 79.97 years.
Conclusion: The results indicated the high impact of the diseases on LE, especially the heart diseases. As a main result, LE will upgrade to more focus on this category.
M Mehrolhassani, B Najafi, V Yazdi Feyzabadi , Aa Haghdoost, M Abolhallaje, M Ansari, R Dehnavieh, M Ramezanian, F Kouhi, M Jafari, Lashkari M,
Volume 12, Issue 0 (Special Issue Vol.12 2017)
Abstract
Background and Objectives: Out-of-pocket (OOP) expenditure is one of the main indicators in health financing, indicating risk pooling and risk spreading. This study aimed to calculate the total health expenditure (THE), the THE per capita and share of OOP in each province from 2008 to 2014.
Methods: The present cross-sectional study was done by collecting provincial health expenditure data from public and private organizations during 2008-2014. The data were approved by board of trustees or board of directors in each organization. The relevant data on household health expenditures were collected from the Statistical Centre of Iran, as well.
Results: Even though the absolute monetary value (IRR) of OOP in the study years showed an increase, it decreased from 51.9% in 2008 to 40.6% in 2014 in terms of share. The absolute monetary value (IRR) of THE and THE per capita increased about 3.5 times in all provinces. So, during the study years, Tehran and Sistan and Baluchistan Provinces had the highest and lowest absolute monetary values (IRR) in THE per capita and this difference increased from 2.12 million Rials in 2008 to 10.56 million Rials in 2014.
Conclusion: Although the share of OOP decreased in all provinces in the country during the study years, it is still far from the objective of the national development plans (30% OOP). In order to improve the study indices and reduce the provincial inequity, it is suggested to put more emphasis on prepaid-based mechanisms, insurance system improvement, and equitable distribution of financial resources should be compatible with the deprivation of the area and its infrastructures.
V Yazdi Feyzabadi , Mh Mehrolhassani, Aa Haghdoost, M Bahrampour,
Volume 12, Issue 0 (Special Issue Vol.12 2017)
Abstract
Background and Objectives: One of the fair financial protection indexes in monitoring health systems is estimating impoverishment due to health care expenditure. The aim of this study was to measure the percentage of households impoverished due to out-of-pocket(OOP) payments in Iran provinces during2008-2014.
Methods: The present retrospective descriptive study was conducted based on data from Household Income and Expenditure Survey in both rural and urban households. The proportion of households that moved below the poverty line after deducting health care costs was calculated. The poverty line for urban and rural areas was calculated based on household food expenditure. To show the provincial dispersion of the index during this period, the coefficient of variation(CV) was used. Mann-WhitneyU test and descriptive statistics were used to analyze the data.
Results: Golestan, North Khorasan, and Kerman had the highest impoverishment rate due to OOP Moreover, Alborz, Tehran, and Bushehr had the lowest impoverishment rate due to OOP. In all the study years, the average impoverishment due to OOP was significantly higher in rural areas compared to urban areas. Provincial dispersion CV for this index did not have a constant trend.
Conclusion: The results of this study provide valuable evidence for policy-makers to estimate the impact of OOPs on household impoverishment. In order to reduce impoverishment due to OOP, supportive targeted interventions for vulnerable and low-income households, especially rural households, in addition to decreasing the share of OOP, are essential, such as developing health subsidies and improving insurance service packages.
V Yazdi Feyzabadi, M Bahrampour, A Rashidian, Aa Haghdoost, M Abolhallaje, B Najafi, Mr Akbari Javar , Mh Mehrolhassani,
Volume 12, Issue 0 (Special Issue Vol.12 2017)
Abstract
Background and Objectives: Catastrophic health expenditure (CHE) is a key indicator for measuring households' financial protection in the health system. This study was conducted to measure the incidence and intensity of CHE in Iranian provinces 2008-2014.
Methods: When the out-of-pocket (OOP) spending of each household amounts to at least 40% of the household's capacity to pay, it is called a catastrophe. The incidence of CHE in Iranian provinces was estimated using the data obtained from household-expenditure-and-income-surveys. The intensity was calculated as the average extent to which OOPs exceeded the 40% threshold. Descriptive statistics and Mann-WhitneyU test were used for data analysis. The index of disparity(ID) was also calculated for geographical disparities across the provinces.
Results: On average, the lowest and highest CHE incidence and intensity were seen in Fars and South Khorasan provinces respectively. However, the highest and lowest rate for CHE households that actually experienced catastrophe at the 40% threshold belonged to Fars and Kurdistan provinces. The incidence of CHE in rural was more than urban areas. ID of CHE incidence for targeted amount was high and had no constant trend.
Conclusion: CHE incidence had a remarkable difference in different provinces and in the rural area compared to the urban area. Due to the importance of this index in promoting health financial protection, like indexes such as OOP, its distribution in rural and urban areas as well as in different provinces is considerable. It requires a structured format to identify the disadvantaged and low-income groups and provide financial-support and insurance for them.
Mh Mehrolhassani, M Emami, Aa Haghdoost, R Dehnavieh, S Amanpour, F Sabbah, M Bazrafshan,
Volume 12, Issue 0 (Special Issue Vol.12 2017)
Abstract
Background and Objectives: Universities of medical sciences play a vital role in promoting population health and without a doubt, their performance should be measured and evaluated.
Methods: The study was a mixed method study (consecutive combination) and the universities were examined by census. In the qualitative phase of the study, by examining the documents and focused group discussions, the basic framework of the performance evaluation model and its associated challenges were elicited. Then, the policies, objectives, and strategies related to each dimension were extracted and finally, key indicators were selected. Finally, by running Analytic Hierarchy Process method, the weight of dimensions and their key aspects were calculated and the model was implemented.
Results: BSC was designed in accordance with the universities. In this model, four main aspects including population health, services, finance, and development were identified. Then, by reviewing the documents, key policies and strategies, key policies and criteria, primary and secondary strategies were extracted. 13 key indicators were chosen as the final indexes. Moreover, 3 main challenges and 11 secondary challenges were identified. The results of the AHP-BSC model indicated that categorizing (ranking) universities had an impact on their functional status.
Conclusion: The main challenge for evaluating the performance of universities was the presence of a logical connection between policies, strategies, and criteria to have comprehensive and concise indexes for evaluation and ranking.
