Relationship Geographical Access and Maternal Mortality: Spatial Analysis

Musafaah  Musafaah; Nita  Pujianti; Meitria Syahadatina  Noor; Hadrianti Haji Darise  Lasari; Siti  Maulidah

doi:10.3889/oamjms.2023.10973

Authors

Musafaah Musafaah Department of Biostatistic
Nita Pujianti Department of Health Administration and Policy, Public Health Study Program, Faculty of Medicine, Lambung Mangkurat University, Banjarbaru City, South Kalimantan, Indonesia
Meitria Syahadatina Noor Department of Reproductive Health and Maternal-Child Health, Public Health Study Program, Faculty of Medicine, Lambung Mangkurat University, Banjarbaru City, South Kalimantan, Indonesia
Hadrianti Haji Darise Lasari Department of Biostatistic, Public Health Study Program, Faculty of Medicine, Lambung Mangkurat University, Banjarbaru City, South Kalimantan, Indonesia
Siti Maulidah Department of Biostatistic, Public Health Study Program, Faculty of Medicine, Lambung Mangkurat University, Banjarbaru City, South Kalimantan, Indonesia

DOI:

https://doi.org/10.3889/oamjms.2023.10973

Keywords:

Maternal mortality, Distance, Transportation, Accessibility

Abstract

AIM: Banjar District is included in the top 3 of highest maternal mortality rates in South Kalimantan, Indonesia. The purpose of the study is to analyze the relationship between accessibility (distance, time, and transportation) with the incidence of maternal mortality in Banjar District.

METHODS: The study is an observational analysis using a case–control approach with a retrospective. The population was mothers who gave birth in the Banjar district on January 2015−December 2018. Criteria for inclusion of cases are mothers who experience death during pregnancy, childbirth or within 42 days before the end of the pregnancy period recorded in 2015−2018 at the Health Office and births at health facilities in Banjar District, which is represented by the family who knows the best about the mother’s condition, while controls are respondents who do not died in the same year. Sample for case group is 25, by taking the comparison case: control 1:2, then, the sample size of the control group is 50. Statistical test uses Chi-square test.

RESULTS: The results show that there is the relationship between transportation (p = 0.034) and distance (p = 0.035) with the incidence of maternal mortality with Odds ratio (OR) 3.58 and 3.27. However, there is no relationship between time (p = 0.118) with the mortality of maternal.

CONCLUSION: Increasing the accessibility of health services can reduce maternal mortality, one of which is the provision of transportation to bring mothers closer to health facilities.

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References

Ministry of Health of the Republic of Indonesia. Integrated Antenatal Care Guidelines. Jakarta: Directorate General of Nutrition and Maternal and Child Health; 2012.

Banjar District Health Office. Profile of Banjar District Health Office in 2018. Martapuura: Banjar District Health Office; 2018.

Ministry of Health of the Republic of Indonesia. Indonesia’s Health Profile in 2015. Jakarta: Ministry of Health of the Republic of Indonesia; 2016.

South Kalimantan Provincial Health Office. Profile of South Kalimantan Provincial Health Office in 2018. Banjarmasin: South Kalimantan Provincial Health Office; 2018.

McCarthy J, Maine D. A framework for analyzing the determinants of maternal mortality. Stud Fam Plann. 1992;23(1):22-33. PMid:1557792 DOI: https://doi.org/10.2307/1966825

Achmadi UF. Region-Based Disease Management. Jakarta: Rajawali Press; 2012.

UNFPA and University of Aberdeen. Maternal Mortality Update 2004 Delivery Into Good Hands. New York: UNFPA and University of Aberdeen; 2004.

Rachmah NF, Purhadi P. Modeling the Number of Maternal Deaths and the Number of Infant Deaths in East Java Province Using Bivariate Poisson Regression. ITS Journal of Science and Art. 2014;3(2):194-199.

World Health Organization. Making Pregnancy Safer A Health Sector Strategy For Reducing Maternal and Perinatal Morbidity and Mortality. New Delhi: WHO, SEARO; 2000.

Ranuh S, Gede IG. Child Growth and Development. Jakarta: EGC; 2012.

Kumalasari I, Andhyantoro I. Reproductive Health For Midwifery and Nursing. Jakarta: Salemba Medika; 2014.

Ministry of Health of the Republic of Indonesia. Indonesia Demographic and Health Survey 2017: Preliminary Report on Key Indicators. Jakarta: Ministry of Health of the Republic of Indonesia; 2017.

Phillips DR. Health and Health Care in the Third World. New York: Longman Scientific and Technical, John Wiley and Sons, Inc.; 1990.

Ricketts TC, Savitz LA, Gesler WM, Osborne DN, editors. Geographic Methods for Health Services Research. London: Department of Geography. University of North Carolina; 1984.

World Health Organization. International Statistical Classification of Disease and Related Health Problems, 10th Revisions. Vol. 2. Geneva: World Health Organization; 1993.

Prahasta E. Geographic Information Systems: Basic Concepts (Geodesy and Geomatics Perspectives). Bandung: Penerbit Informatika Bandung; 2009.

De Mars MN. Fundamntals of Geographic Information System. New York: John Willey and Sons; 1997.

Fotheringham AS, Brunsdon C, Charlton M. Quantitative Geography: Perspective on Spatial Data Analysis. London: SAGE Publication; 2000.