Increasing Trends or Sociodemographic Changes? Decomposition Analyses of Maternal Complication in Indonesia
Abstract
Many Indonesian women experienced self-reported complications during pregnancy and delivery. These complications include prolonged labor, bleeding, infection, and other complications. This study aimed to examine the underlying determinants that influenced the increasing prevalence of maternal complication in Indonesia. Data from the two most recent Indonesian Demographic and Health Surveys (IDHS) were analyzed. We quantified the contribution of socio-demographic factors in the increase of maternal complications, using Oaxaca-Blinder regression-based decomposition analyses with STATA ‘mvdcmp’ procedure. Between IDHS 2007 and IDHS 2012, there was a significant increase in maternal complication prevalence from 50.5% to 54.1% (p < 0.001). Most (approximately 85.0%) was explained by differential responses of determinants, with unmeasured factors as the highest contributor. Differences in characteristics explained 15% of the increase, with parity and area of residence as the main contributors. The increasing prevalence of maternal complications in Indonesia was mostly due to differential responses of unmeasured factors, which might include increasing awareness of maternal complications and increasing prevalence of underlying causes of maternal complications, i.e., chronic diseases, anemia, and infection. A Further research study which identifies the contribution of these factors to
the increasing prevalence of maternal complication is needed.
References
[1] Hardee K, Gay J, and Blanc A K 2012 Maternal morbidity: a Neglected dimension of safe motherhood in the developing world. Glob. Public Health 7 603–17
[2] Chou D Tunçalp Ö Firoz T Barreix M Filippi V von Dadelszen, van den Broek N Cecatti J G and Say L 2016 Constructing maternal morbidity – towards a standard tool to measure and monitor maternal health beyond mortality. BMC Pregnancy Childbirth 16 45
[3] Rocha Filho EA, Costa ML, Cecatti J G, Parpinelli MA, Hadda S M, Sousa M H, Melo E F, Surita F G, Souza JP and The Brazilian Network for Surveillance of Severe Maternal Morbidity Study Group 2015 Contribution of antepartum and intrapartum hemorrhage to the burden of maternal near miss and death in a national surveillance study Acta Obstet. Gynecol. Scand. 94 50–8
[4] Geller S E, Cox S M, Callaghan W M and Berg C J 20016 Morbidity and mortality in pregnancy. Laying the Groundwork for Safe Motherhood. Women’s Heal. Issues 16 176–88
[5] Statistics Indonesia (Badan Pusat Statistik [BPS]), National Population and Family Planning Board (BKKBN), Indonesia Ministry of Health (Depkes RI) and ICF International 2013 Indonesia Demographic and Health Survey 2012 ( Jakarta: Indonesia)
[6] Widyaningsih V, Khotijah and Balqis 2017 Expanding the scope beyond mortality: burden and missed opportunities in maternal morbidity in Indonesia. Glob. Health Action 10 1339534
[7] Adisasmita A, Deviany PE, Nandiaty F, Stanton C and Ronsmans C 2008 Obstetrics near miss and deaths in public and private hospitals in Indonesia. BMC Pregnancy Childbirth 8 10
[8] D’Ambruoso L, Martha E, Izati Y, Kiger A, and Coates A 2013 Maternal mortality and severe morbidity in rural Indonesia Part 1: The community perspective. Soc. Med. 7 47–67
[9] Sikder SS, Labrique AB, Shamim AA, Ali H, Mehra S, Wu L, Shaikh S, West Jr K P and Christian P 2014 Risk factors for reported obstetric complications and near misses in rursal northwest Bangladesh: analysis from a prospective cohort study. BMC Pregnancy Childbirth 14 347
[10] Oliveira F C De, Costa M, Cecatti J G, Pinto E, Silva J L, and Surita F G 2013 Maternal morbidity and near misses associated with maternal age: the innovative approach of the 2006 Brazilian demographic health survey. Clinics (Sao Paulo) 68 922–7
[11] Oliveira F C J, Surita F G, Pinto E Silva J L, Cecatti J G, Parpinelli MA, Haddad SM, Costa ML, Pacagnella R C, Sousa M H and Souza J P 2014 Severe maternal morbidity and maternal near miss in the extremes of reproductive age: results from a national cross-sectional multicentre study. BMC Pregnancy Childbirth 14 77
[12] Gray K E, Wallace ER, Nelson K R, Reed SD and Schiff M A 2012 Population-based study of risk factors for severe maternal morbidity. Paediatr. Perinat. Epidemiol. 26 506–14
[13] Norhayati M N, Nik Hazlina N H, Aniza A A and Sulaiman Z 2016 Factors associated with severe maternal morbidity in Kelantan, Malaysia: A comparative cross-sectional study. BMC Pregnancy Childbirth 16 185
[14] Adisasmita A, Smith CV, El-Mohandes A A E, Deviany PE, Ryon J J, Kiely M, RogersBloch Q, and Gipson R F 2015 Maternal Characteristics and Clinical Diagnoses Influence Obstetrical Outcomes in Indonesia. Matern. Child Health J. 19 1624–33
[15] Severe Maternal Morbidity: A 10-Year Review of the Literature. Asia Pac J Public Heal.
[16] Zanette E, Parpinelli MA, Surita F G, Costa ML, Haddad SM, Sousa M H, E Silva J L, Souza JP and Cecatti J G 2014 Maternal near miss and death among women with severe hypertensive disorders: A Brazilian multicentre surveillance study. Reprod. Health 11 4
[17] Powers D A, Yodhioka H and Yun M S 2011 Mvdcmp: Multivariate decomposition for nonlinear response models. Stata J 11 556–76
[18] O’Donnell O, Doorslaer E, Wagstaff A and Lindelow M 20018 Explaining differences between groups: Oaxaca Decomposition. Analyzing health equity using household survey data: A guide to techniques and their implementation. 147–57