Determinants of delays in travelling to an emergency obstetric care facility in Herat, Afghanistan: an analysis of cross-sectional survey data and spatial modelling

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Background Women’s delays in reaching emergency obstetric care (EmOC) facilities contribute to high maternal and perinatal mortality and morbidity in low-income countries, yet few studies have quantified travel times to EmOC and examined delays
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  RESEARCH ARTICLE Open Access Determinants of delays in travelling to anemergency obstetric care facility in Herat,Afghanistan: an analysis of cross-sectional surveydata and spatial modelling Atsumi Hirose 1* , Matthias Borchert 2,3 , Jonathan Cox 4 , Ahmad Shah Alkozai 5 and Veronique Filippi 2 Abstract Background:  Women ’ s delays in reaching emergency obstetric care (EmOC) facilities contribute to high maternaland perinatal mortality and morbidity in low-income countries, yet few studies have quantified travel times to EmOCand examined delays systematically. We defined a delay as the difference between a woman ’ s travel time to EmOC andthe optimal travel time under the best case scenario. The objectives were to model travel times to EmOC and identifyfactors explaining delays. i.e., the difference between empirical and modelled travel times. Methods:  A cost-distance approach in a raster-based geographic information system (GIS) was used for modellingtravel times. Empirical data were obtained during a cross-sectional survey among women admitted in a life-threateningcondition to the maternity ward of Herat Regional Hospital in Afghanistan from 2007 to 2008. Multivariable linearregression was used to identify the determinants of the log of delay. Results:  Amongst 402 women, 82 (20%) had no delay. The median modelled travel time, reported travel time, anddelay were 1.0 hour [Q1-Q3: 0.6, 2.2], 3.6 hours [Q1-Q3: 1.0, 12.0], and 2.0 hours [Q1-Q3: 0.1, 9.2], respectively. Theadjusted ratio (AR) of a delay of the  “ one-referral ”  group to the  “ self-referral ”  group was 4.9 [95% confidence interval (CI):3.8-6.3]. Difficulties obtaining transportation explained some delay [AR 2.1 compared to  “ no difficulty ” ; 95% CI: 1.5-3.1]. Ahusband ’ s very large social network (>=5 people) doubled a delay [95% CI: 1.1-3.7] compared to a moderate (3-4people) network. Women with severe infections had a delay 2.6 times longer than those with postpartumhaemorrhage (PPH) [95% CI: 1.4-4.9]. Conclusions:  Delays were mostly explained by the number of health facilities visited. A husband ’ s large social network contributed to a delay. A complication with dramatic symptoms (e.g. PPH) shortened a delay while complications withless-alarming symptoms (e.g. severe infection) prolonged it. In-depth investigations are needed to clarify whether timeis spent appropriately at lower-level facilities. Community members need to be sensitised to the signs and symptomsof obstetric complications and the urgency associated with them. Health-enhancing behaviours such as birth plansshould be promoted in communities. Keywords:  Afghanistan, Delays, Emergency obstetric care, Referrals, Maternal health, Near-miss, Geographic informationsystems, Social network, Transportation * Correspondence: atsumi.hirose@gmail.com 1 PhD programme, Faculty of Epidemiology and Population Health, LondonSchool of Hygiene & Tropical Medicine, London, UK Full list of author information is available at the end of the article © 2015 Hirose et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the srcinal work is properly credited. The Creative Commons Public DomainDedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article,unless otherwise stated. Hirose  et al. BMC Pregnancy and Childbirth  (2015) 15:14 DOI 10.1186/s12884-015-0435-1  Background Women ’ s delay in reaching emergency obstetric care(EmOC) facilities contributes to a high burden of maternaland perinatal mortality and morbidity in low-incomecountries. Basic EmOC (BEmOC) services dispense life-saving functions such as the administration of antibiotics,oxytocic drugs, and anticonvulsants, as well as manual re-moval procedures, while comprehensive EmOC (CEmOC)services additionally include blood transfusion and sur-gery. The period from the onset of signs and symptoms of complications to the receipt of EmOC is usually dividedinto three phases or  “ three delays ”  [1]: The first delay re-fers to the interval between the onset of obstetric compli-cation and the decision to seek care; the second delay isthe interval between the decision and the arrival in ahealth facility; and the third delay is between the arrivaland the provision of adequate care. Each interval has adistinctive set of factors determining its duration. Factorsprolonging the second interval include travel distance[2,3], sparsely distributed EmOC health facilities (particu- larly in rural areas) [4], ineffective referrals [5,6], a lack of  transportation means [3,6,7], the cost of transportation [8], and drivers ’  unwillingness to transport women inlabour. While many studies provide these factors as rea-sons for the second delay, few empirical studies haveattempted to quantify travel distances and times forwomen needing EmOC [4,9]. In recent years, the increased availability of geo-referenced data has made it easier to calculate distancesbetween patients ’  residences and the locations of careand hence provide a direct measure of geographical ac-cessibility [10-13]. Since many women reach an EmOC facility in life-threatening condition after considerabledelay [14,15], detailed analyses of distances and travel times are warranted for this particular group of women.We postulate that the use of geo-referenced data may create new knowledge of care-seeking behaviours whichcontribute to travel delay in complicated pregnanciesand childbirth.Afghanistan has one of the highest maternal mortality ratios in the world, much of which is explained by women ’ s difficult physical access and socio-cultural bar-riers to care [16]. The country is very mountainous witha rudimentary road network and limited means of trans-portation. Due to threats by anti-government elementsand insecurity, vehicle drivers may be unwilling to trans-port pregnant women, particularly in rural areas. Fur-thermore, the Afghan society is based on a strongpatriarchy, where women are viewed as  “ receptacles of honour ”  [17]. To protect family honour, a woman ’ s mo-bility is controlled by her male relatives [17], limiting heraccess to health care. Women are often brought toEmOC facilities in moribund conditions after consider-able access delay [18].We undertook the current study to understand thetravel delays of women who were in a life-threateningcondition at admission to a large maternity hospital inAfghanistan. The study operationalised in statisticalterms the second phase of delay presented in Thaddeusand Maine ’ s seminal work [1]. Specific objectives wereto (1) estimate the distance and travel time to a CEmOCfacility using geo-referenced data in a geographic infor-mation system (GIS); (2) assess factors associated withthe travel times modelled in GIS and reported by thesewomen; and (3) explore factors explaining the differ-ences between the modelled and reported travel times. Methods Study setting The study was set in the western region of Afghanistan,which includes Herat, Badghis, Ghor, and Farah prov-inces. Despite decades of conflict, the city of Herat, theprovincial capital and location of our study hospital, iswell developed in terms of basic infrastructure comparedwith other parts of the country. Paved roads connect theprovincial capital to Turkmenistan via the border townof Turgundi in the north (2 hours by vehicle) and to theIslamic Republic of Iran via Islam Qala in the west (1.5-2 hours by vehicle). East of Herat and at the end of theHindu Kush (a mountain range stretching between cen-tral Afghanistan and northern Pakistan) is Ghor prov-ince; its capital, Chaghcharan, is at about 2500 m abovesea level, a much higher altitude than Herat (Figure 1).In both Ghor and Badghis (northeast of Herat) prov-inces, transportation links are particularly poor due torugged terrain and the lack of paved roads, and existingroads are often blocked by snowfall in winter. South of Herat is sparsely populated Farah province, with half of its land being mountainous. Herat Regional Hospital wasthe only CEmOC facility in western Afghanistan. Data collection Empirical travel times were collected during a cross-sectional survey of women admitted to the maternity wardof Herat Regional Hospital in a life-threatening conditionand of their male relatives between February 2007 andJanuary 2008. Details of the survey are presented else-where [18]. In short, we recruited prospectively all thewomen meeting disease-specific criteria of   “ near-miss ” morbidity at admission during the study period. Thedisease-specific criteria of   “ near-miss ”  were adapted fromother studies conducted in resource-limited settings[20-22]. Face-to-face interviews were conducted mostly  before discharge, except for four interviews conducted athome with female relatives who cared for four womenwho died in hospital. A wide range of topics was coveredduring the interview, amongst which the residence of thewoman ’ s birth family and the utilization of health care Hirose  et al. BMC Pregnancy and Childbirth  (2015) 15:14 Page 2 of 13  during pregnancy were considered in this particular ana-lysis. From the male relative (usually the husband), we ob-tained information on departure time from home andarrival time at the study hospital and, if relevant, at lowerhealth facilities; access to and utilization of transportationmeans; family composition; household assets; his occupa-tion and education status; his participation in community activities; the size of his social network; the village of resi-dence; and a nearby notable village (for the ease of villageidentification). Estimation of Euclidian distance To obtain the geographical coordinates of each woman ’ s village, we used a settlement database provided by theAfghanistan Information Management Services (AIMS,available at http://www.aims.org.af/). The woman ’ s re-ported village of residence was manually identified in thedatabase, and its coordinates extracted. Herat Hospital ’ sgeographical coordinates were obtained with a handheldglobal positioning system (GPS) receiver (eTrex, Garmin[KS, USA]). Point locations for villages and Herat Hos-pital were imported into a GIS (ArcGIS version 10; CA,USA), and then into a raster-based GIS (IDRISI Andes,Clark Lab, MA, USA), to compute the Euclidian (straight-line) distance from a woman ’ s village of residence to HeratHospital. Modelling of travel time in a GIS Travel times between individual residences or com-pounds and Herat Hospital were predicted with a cost-surface modelling approach in IDRISI. This methodinvolves assigning  “ friction ”  values to represent the landsurface types that either impede or facilitate travel. Weconsidered travel speeds by the most suitable local trans-portation means under optimal conditions (best-casescenario). Vehicle travel speeds along the transportation Figure 1  “ Afghanistan physiography ”  2009.  Source:  U.S. Central Intelligence Agency [19]. Hirose  et al. BMC Pregnancy and Childbirth  (2015) 15:14 Page 3 of 13  network were estimated based on observations and dis-cussions with local drivers (80 km/h on primary roads;55 km/h on secondary roads; and 40 km/h on tracks). Awalking speed of 1.75 km/h was assumed for areas trav-ersable by foot only [13]. Water bodies were deemed tobe essentially impassable (very close to 0 km/h).AIMS spatial data on the road network, land cover,and drainage were used to derive a composite frictionsurface for the study area with a spatial resolution (i.e.,pixel size) of 100 m. A cost-surface grid was then de-rived, indicating the minimum accumulative travel timebetween each compound and the hospital. Initial resultsfrom this exercise were compared with travel times to12 major villages in the study area as reported by experi-enced NGO drivers ( “ reference time ” , shown in Table 1).We preferred to rely on drivers ’  reports (instead of hav-ing them travel just to measure the time), because of in-security in the area and the need to restrict travel to theessential. The deviations of the modelled times from thereference times were greatest in mountain areas. Hence,we decided to incorporate an additional barrier, slopeangle, so that steeply inclined surfaces would be assignedhigher friction values than flat surfaces. After iterationswith different friction values, estimated travel times to12 major villages reached reasonable values (Table 1).The travel time was then extracted for the residence of each woman in our sample. The definition of a delay and the variables in theconceptual framework  For the remaining part of this paper, we defined a delay as the difference between the travel time computed frominterview results and the expected travel time derivedfrom the GIS model [1]. We postulated that consultationtimes at lower-level health facilities would inevitably prolong the travel time to the final CEmOC facility.Additionally, we hypothesised that social, relational, en- vironmental, and obstetric factors would affect access toand the use of transportation between home and healthfacilities and cause delays. Variables were selected foreach of these themes (Table 2). The first set of variableswas intended to capture the social class hierarchy in arural society. Those with greater social, economic, orpolitical power in the rural community often have agreater command over the transportation business andservices [23,24]. Not only do scarce financial resources hamper the rural poor from using transportation, thepoor may also be charged higher rates for sub-optimalservices, because the low demand in rural villages doesnot promote fair competition [25]. Three proxy variablesfor social class were included: (1) Asset-based householdsocio-economic status (created by adding weights equalto the inverse of the proportion of households owningselected household items and creating quartiles); (2) thehusband ’ s occupation group; and (3) the husband ’ s edu-cation (whether he has ever attended formal school). Lit-erature suggests that a woman ’ s education is positively associated with her utilisation of health care services andhealth-promoting behaviours. Nonetheless, we postu-lated that the husband ’ s education would have a strongerinfluence than the woman ’ s, because of the cultural con-text in which male relatives chaperone women, the ur-gency of the situations, and the fact that some of thewomen became very ill quickly after signs and symptomswere recognised. Hence, the benefits of female education — such as an educated woman ’ s new values and attitudes (e.g.,enhanced self-confidence, self-worth) that are favourableto her use of health care and her increased discussion with Table 1 Model validation results: reference and modelled travel times by major destination Village/area of residence District Province Features of the roads betweenthe village and Herat HospitalReferencetime(minutes)Initial modelresults(minutes)Final modelresults(minutes) Guzara district centre Guzara Herat Paved roads 15 21.5 21.5Qala-i-Naw district centre Qala-i-Naw Badghis All types of roads passing throughmountains240-300 188.9 244.7Karukh district centre Karukh Herat Paved roads 30-40 38.8 38.8 Turghundi Kushk Herat Paved roads but not very smooth 120 93.7 93.7Islam Qala Kohsan Herat Paved roads only 90-100 97.1 97.1Shahrak district centre Shahrak Ghor In the mountains 540-600 304.7 415.1Dara-Takht Chishiti Sherif Herat Tracks 360 244.9 250.9Shindand district centre Shindand Herat Paved roads 100-120 128.3 130.3Chishiti Sherif district centre Chishiti Sherif Herat Tracks 270 208.4 208.4Obe district centre Obe Herat Tracks but relatively flat 150-180 162.4 162.5Pashtun Zarghun district centre Pashtun Zarghun Herat Tracks but relatively flat 90 117.2 117.2Chartaz Jawand Badghis All types of roads passing throughmountains720 383.4 728.6 Hirose  et al. BMC Pregnancy and Childbirth  (2015) 15:14 Page 4 of 13  her husband [26] — may not have a strong influence on thetravel to a health facility in the context of this study.The second set of variables was intended to measurethe size and strength of the husband ’ s social network.When travel entails a long distance, families with greatersocial networks may more easily overcome financial andlogistical barriers to transportation. Three variables iden-tified from the group and network section of a socialcapital questionnaire [27] were considered: (1) The hus-band ’ s participation in community activities in the last12 months; (2) the number of people the husband reportsto be able to rely on in case of long-term emergency (suchas a job loss or harvest failure); and (3) the number of people the husband reports to be able to borrow a smallamount of money from. Two additional variables, house-hold type (extended or nuclear family) and distance to thewoman ’ s birth family, were included. In Afghanistan, as inother countries in South Asia,  “ the patriarchal extendedfamily is the central social unit ”  [28], and the society isbased on the institutionalized relationships of mutual de-pendency among the patriarchal kin. Members of thepatriarchal kinship network help each other during hardtimes, emotionally or materially. The woman ’ s birth family can be another important source of support around thetime of childbirth. We hypothesised that couples livingwith their extended family or close to the woman ’ s birthfamily have better access to material resources.Third, two variables were selected to capture environ-mental factors. Concerning the season of admission, wehypothesised that travel in winter and summer may takelonger due to road damage or obstruction by rain orsnow during the winter, and to difficulties travelling inthe midday sun during the summer. We included urbanor rural residence as an independent variable because of two possible scenarios: Urban residents may experiencea delay due to city congestion, while residents in remoteareas may experience a delay because of vehicle main-tenance on the way.Fourth, we considered maternal and obstetric factorsand selected three variables: Complication type, parity,and the number of antenatal care (ANC) visits. A woman ’ scomplications with typically dramatic symptoms (i.e.,eclampsia and postpartum haemorrhage) and her past ex-perience of childbirth or lack of it may reinforce care-takers ’ perception of the urgency of the situation, and the womanmay be transported to a health facility as rapidly as possible.Finally, we included three variables that indicate accessto and utilization of vehicles, as they directly affect traveltimes to the hospital: Transfer in an ambulance; thecommunity normally has a vehicle; and reported diffi-culty obtaining transportation. Data analysis Survey data and travel distance and time data created inIDRISI were imported into Stata (version 9; Stata Corp,TX, USA) for analysis. Euclidian distances, GIS-modelledtravel times, and self-reported travel times were describedby key determinants. Because these data were skewed, theKruskal-Wallis test was used, and medians plus inter-quartile ranges presented. Delay, the main outcome of thestudy, was expressed as the difference between the re-ported travel time and the GIS-modelled travel time. Thedelay data were log-transformed to achieve a normal dis-tribution after a minimal value was added to the data toadjust for non-positive delays. We used multivariable re-gression methods with forward selection to identify deter-minants, and likelihood ratio tests (p<0.05) to decide onthe inclusion of a variable in the model. Final results werereverted to normal scale and presented as ratios to thebaseline group. Ethics clearance Ethics approval was obtained from the ethics commit-tees of the Ministry of Public Health in Afghanistan andthe London School of Hygiene & Tropical Medicine. In-dividual informed consent was obtained from all womenand husbands who agreed to participate in the study. Ei-ther a thumb-print or a signature was obtained. Results Of the 472 women and their husbands recruited for thestudy, 410 couples were included in the current analysis. Table 2 Variables considered in the analysis 1. Referral 2. Social classhierarchy3. Relational factors 4. Environmentalfactors5. Obstetricfactors6. Transportationfactors No. health facilitiesbefore admissionto CEmOCAsset-basedsocio-economicstatusHusband ’ s participation in communityactivities in last 12 monthsSeason Complicationtype Transferred inan ambulanceHusband ’ soccupationNo. people the husband can rely onto borrow a small amount of money fromUrban/rural Antenatal careutilizationCommunity usuallyhas a vehicleHusband ’ seducationNo. people the husband can relyon in long-term emergencyParity Reported difficultyobtaining a vehicleFamily type (nuclear vs. extended family)Woman ’ s birth family lives nearby Hirose  et al. BMC Pregnancy and Childbirth  (2015) 15:14 Page 5 of 13
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