مدل‌سازی الگوی فصلی زایمان‎های زودرس: مطالعه سری‌های زمانی شهر مشهد

نوع مقاله : اصیل پژوهشی

نویسندگان

1 دانشجوی دکتری اقلیم‌ شناسی شهری، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران.

2 دکتری اقلیم‌ شناسی، استادیار اقلیم ‌شناسی، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران.

3 استاد گروه زنان و مامایی، مرکز تحقیقات سلامت زنان، دانشکده پزشکی، دانشگاه علوم پزشکی مشهد، مشهد، ایران.

4 کارشناسی ارشد اقلیم ‌شناسی کاربردی، دانشکده جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار، ایران.

چکیده

مقدمه: زایمان زودرس وضعیت پیچیده‎ای است که عوامل خطر آن بر حسب فصل‎های مختلف فرق می کند. یکی از عوامل محیطی که ممکن است بر وقوع زایمان های زودرس تأثیرگذار باشد، فصل است. مطالعه حاضر با هدف بررسی الگوی فصلی زایمان های زودرس شهر مشهد با استفاده از مدل‎های سری زمانی ARIMA انجام شد.
روش‎ کار: اطلاعات مربوط به زایمان‌های زودرس در طی سال های 92-1382 از مرکز تحقیقات سلامت زنان تهیه و با توجه به توابع خودهمبستگی و خودهمبستگی جزئی و نیز وجود و عدم وجود روند در داده‎ها سعی شد تا مدل‎های سری زمانی مناسب برازش داده شود. پس از انتخاب مدل‎ها، معنی‎داری پارامترها با برآورد خطای معیار و مقادیر t بررسی شد و سپس آزمون‎های نکوئی برازش از جمله آزمون کولموگروف- اسمیرنوف و رایان جوینر برای صحت سنجی مدل‎ها به کار گرفته شد. همچنین با استفاده از شاخص فصلی (SI)، الگوی فصلی شیوع زایمان‎های زودرس نیز استخراج شد.
یافته ها: نتایج مطالعه نشان داد که مدل  ARIMA بهترین مدل جهت بررسی الگوی فصلی شیوع زایمان زودرس برازش شد. همچنین از تعداد 4743، گروه های سنی 30-23 سال بیشترین زایمان زودرس را داشتند و فراوانی وقوع فصلی حاکی از آن بود که فصل زمستان و دی ماه بالاترین درصد وقوع را به خود اختصاص داده اند وکمترین تعداد نیز مربوط به فصل بهار بود.
نتیجه‎گیری: به طور کلی زایمان‎های زودرس با تغییرات فصلی دارای تغییرات می‎باشند و عوامل محیطی بر بروز این بیماری تأثیر قابل توجهی دارد.

کلیدواژه‌ها


عنوان مقاله [English]

Modeling the seasonal patterns of preterm deliveries: time series study in Mashhad

نویسندگان [English]

  • Fatemeh Mayvaneh 1
  • Ali Reza Entezari 2
  • Nayereh Khadem 3
  • Tayebeh Shojaee 4
1 PhD student in urban climatology, School of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran.
2 PhD of climatology, Assistant Professor, Department of Climatology, School of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran.
3 Head of Women's health Research Center, Professor, Department of Obstetrics and Gynecology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
4 M.Sc. of practical climatology, School of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
چکیده [English]

Introduction: Preterm delivery is a complicated situation that its risk factors are different based on different seasons. One of the environmental factors which may be effective on the occurrence of preterm delivery is season. This study was conducted with aim to investigate seasonal pattern of preterm deliveries in Mashhad using ARIMA time series models.
Methods:The Preterm delivery related data were collected during 2003 to 2013 from Women's Health Research Center and regarding the autocorrelation function (ACF) and partial autocorrelation function (PACF), and also the absence of trends in data, it was tried to assign goodness of fit to time series models. After selecting the models, the significance of parameters was investigated with the estimation of criterion error and t-values and then, the goodness of fit such as Kolmogorov-Smirnov test and Ryan Joyner test were used for validation of the models. In addition, using the seasonal index (SI), the seasonal pattern of prevalence of preterm delivery was extracted.
Results: The results of this study indicated that ARMIMA model (1,1,1)×(0,0,1) was fitted as the best one for investigation of seasonal pattern of the prevalence of preterm delivery. In addition, among 4743, the age groups of 23-30 years had the highest rate of preterm delivery. The frequency of seasonal occurrence indicates that winter in December had the highest percentage of occurrence of preterm deliveries, and the lowest rate was related to spring.
Conclusion: In general, preterm deliveries vary with seasonal changes, and environmental factors are significantly effective on the occurrence of this disease.

کلیدواژه‌ها [English]

  • Premature birth
  • Season
  • Time series
  • Trend
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