Showing 3 results for Clustering
Z Hashemi , M Keikha, R Keikhaee, A Ansari Moghadam , M Salehi Marzijarani , A Nasiri,
Volume 9, Issue 2 (10-2013)
Abstract
Background & Objectives: Relationship between jobs and different aspects of health, including quality of life has been considered by researchers however the employment aim has risen in Iranian women in Iran but there is little known about the quality of life in this group, therefore the aim of this study was to investigate the relationship between employment and quality of life of women in the city of Zabol.
Methods: This cross-sectional study was carried out during 2009-2010 in Zabol, Iran. The sample consisted of 420 women selected randomly from health care centers. Health-related quality of life was assessed using the SF-36 and classified using k-means clustering method. The relationship between the independent variables with the quality of life was assessed by multinomial logistic regression.
Results: The mean age of participants was 30.46 ± 8.75 years. Quality of life indicated as low (35.4%), medium (33.7%) and high classes (30.9%), respectively. The results indicated that employed women were more likely than housewives to hadhigher quality of life. An increase age, significantly reduced respectively five and four percent of chance to had moderate and high level of quality of life.
Conclusion: More than half of women had medium and low quality of life. Increasing age was associated with decreased quality of life, but employment was an independent predictor for higher quality of life.
M Olfatifar, Sm Hosseini, , , M Parvin,
Volume 13, Issue 1 (6-2017)
Abstract
Background and Objectives: One of the applications of population attributable risk percent (PAR%) is to estimate the disease burden in a population exposed to several risk factors. Therefore, this study was conducted to estimates the PAR% of the space-time clusters of pulmonary tuberculosis.
Methods: In this study, the data of pulmonary TB cases were obtained from the health department of Hamadan University of Medical Sciences. After detecting significant clusters using the spatiotemporal scan statistic, PAR% was used to analyze the clusters and to detect the location of clusters more accurately.
Results: Four primary space-time clusters and three secondary spatiotemporal clusters were detected for patients with pulmonary tuberculosis and 92% of the patients who did not have a clear state in term of HIV infection. Despite differences in the location of clusters and PAR% attributed to them, the second primary cluster of pulmonary tuberculosis cases (consisting of the cities of Razan, Famenain and Kabudrahang) had the highest amount of PAR% that needs more attention.
Conclusion: The presence of significance spatiotemporal clusters in Hamadan highlights the necessity of the use of PAR% to distinguish cluster areas and to implement prevention and control policy. However, more analytical studies are needed to detect the on the determinants of the occurrence of pulmonary TB.
Sm Hosseini , A Afshari Safavi , A Esmaeil Zade , S Beig Rezaei ,
Volume 13, Issue 2 (9-2017)
Abstract
Background and Objectives: Using the anthropometric indicators of children is one of the ways of monitoring their growth. Because of the racial divisions and levels of health and welfare, comparing these indicators with the global reference is not reasonable; therefore, designing a local reference seems necessary. This study aimed to evaluate the growth indices for boys and girls aged 5 to 18 years old living in Isfahan and to compare the indices with standard values.
Methods: In this cross-sectional study, 53,839 subjects were included. Percentiles of body mass index, height, and weight were calculated using the LMS method in the LMS Light software. After normalization of the growth indices, their mean and standard deviation were calculated for each age group and anthropometric indices curves were plotted versus the 5th, 50th and 95th percentiles of the NCHS reference.
Results: In all age categories, the mean SDS scores of BMI in boys and girls was -0.004 ± 0.029 and 0.014 ± 0.062, respectively, indicating no difference with reference values. However, the 95th percentile of the body mass index for the reference population was consistent with the 90th percentile for the population studied. Also, weight in boys below 13 years of age was higher than the reference line while in girls, weight was always higher than the reference value.
Conclusion: Due to differences in the pattern of growth and also lower anthropometric values, particularly among boys, it seems that a national growth curve can be a better guide for future decisions.
