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Estimating Maternal Mortality in 

Remote Rural Regions: an 

Application of the Sisterhood 

Method in Tajikistan 

Kylea Laina Liese1, Heather 

Pauls2, Sarah Robinson3, Crystal 

Patil1 
 
1Department of Women, Children, and 
Family Health Sciences, University of 
Illinois, Chicago, USA; 
2Office of Research Facilitation, 
University of Illinois, Chicago, USA; 

3Department of Psychology and 
Educational Sciences, University of 
Geneva, Switzerland 
 
 

 

Vol. 8, No. 1 (2019)   |   ISSN 2166-7403 (online)  

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Abstract 

Introduction: The sisterhood method of maternal mortality data collection and analysis provides a validated framework for 

estimating maternal mortality ratios in situations of limited infrastructure. The aim of this study is to assess sub-national maternal 

mortality in the Badakhshan region of Tajikistan using the sisterhood method as part of a larger ethnographic study on maternal 

risk.  

Methods: In 2006-2007, 1004 married women of reproductive age in Gorno-Badakhshan Autonomous Oblast, Tajikistan were 

surveyed using the sisterhood method. Respondents were asked eleven questions about the sex, age and survivorship of all children 

born to the respondent’s mother. 

Results: Using a national total fertility rate (TFR) estimate of 4.88, the maternal mortality ratio (MMR) in Tajik Badakhshan was 

141 maternal deaths per 100,000 live births (95% CI 49-235). The lifetime risk of maternal death was 1 in 141 (95% CI 34-103). 

Conclusion: Given the inherent time-lag of the sisterhood method, precise estimates of maternal mortality are dependent on 

accurate TFRs, which may vary based upon regional experiences of demographic transitions. Socio-political instability and the 

dismantling of Soviet welfare programs and civil war following Tajikistan’s independence from the Soviet Union in 1991 likely 

impacted TFR in Tajik Badakhshan. Socio-political trends influencing TFR in rural regions compared to urban, and the 

investigation of factors associated with maternal mortality, require additional investigation. 

Keywords: Maternal Mortality, Sisterhood Method, Tajikistan, Gorno-Badakhshan Autonomous Oblast 

 

Estimating Maternal Mortality in 

Remote Rural Regions: an 

Application of the Sisterhood Method 

in Tajikistan 

Kylea Laina Liese1, Heather Pauls2, 

Sarah Robinson3, Crystal Patil1 
 
1Department of Women, Children, and 
Family Health Sciences, University of Illinois, 
Chicago, USA; 
2Office of Research Facilitation, University of 
Illinois, Chicago, USA; 

3Department of Psychology and Educational 
Sciences, University of Geneva, Switzerland 

 

 

Research 

Introduction 

Countries with the highest rates of maternal 

mortality typically do not have strong health information 

systems. These systems are vital to generate accurate 

maternal mortality ratio (MMR), the statistical backbone 

on which millions of dollars are spent through research, 

programming, monitoring, and evaluation. However, 

maternal mortality ratios are complex indicators with 

estimation requiring both the accurate identification of 

cause of death and large sample sizes.1-2 The sisterhood 

method of maternal mortality data collection and analysis 

provides a validated framework for estimating maternal 

mortality ratios in situations of limited infrastructure.2-3 

The sisterhood method embedded in Demographic and 

Health Surveys (DHS) produce maternal mortality ratios 

for at least 28 countries, comprising 16% of global 

births.3 With better estimates of maternal mortality at the 

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subnational level, health care spending could be tailored 

to address the specific needs of rural populations. 

Maternal mortality rates in post-Soviet Central 

Asia are lower than those in countries with similar 

income levels, likely due to comprehensive social and 

economic development programs of the Soviet era (e.g., 

paved roads, compulsory education, access to healthcare 

and minimum marriage age). In Tajikistan, the poorest of 

the post-Soviet countries, health care in the mountainous 

region of Gorno-Badakhshan Autonomous Oblast 

(administrative region) (GBAO) is limited compared to 

urban centers. Although GBAO makes up 45% of the 

land of Tajikistan, it is scarcely populated with only 

218,000 residents (3% of the national population).5 

Villages in GBAO are situated along tributaries leading 

into and along the Pyanj River, the border between 

Tajikistan and Afghanistan. As citizens of a former 

Soviet republic (1929-1991), Tajik women in GBAO had 

greater access to quality obstetric care and were rewarded 

for having upwards of ten offspring to grow “The 

Fatherland.” However, with the breakdown of Soviet 

Union in 1991, women were encouraged to curb their 

fertility.6-7 The dismantling of Soviet welfare programs 

and the socio-political instability associated with 

independence contributed to a civil war between 1992-

1997, which further destabilized the country’s health and 

social infrastructure. This transition directly and 

indirectly impacted maternal risk as women’s access to 

high quality obstetric care declined, and funding for 

maintaining roads, schools, and hospitals was reduced. 

The data presented here come from a maternal 

mortality survey using the sisterhood method2 conducted 

in the Darwaz District of GBAO Tajikistan in 2006. This 

survey was part of a larger anthropological study that 

used mixed-methodologies to explore the underlying bio-

social context of maternal risk in the Badakhshan regions 

shared between Tajikistan and Afghanistan. In 2001, 

Afghan Badakhshan was reported to have the highest 

maternal mortality ratio ever recorded (6507 deaths per 

100,000 live births) in a maternal mortality survey that 

utilized the sisterhood method.8 Although national 

estimates suggested that maternal mortality was much 

lower in Tajik Badakhshan, situated directly across the 

Pyanj River, no subnational data existed. Since these 

regions share important ethnic and geopolitical features 

(e.g., poor roads, mountainous terrain, and histories of 

civil war and drug trade), investigating GBAO maternal 

mortality rates is very important. 

The purpose of this study was to obtain an 

estimate of maternal mortality in the Badakhshan region 

of Tajikistan and to compare it with Afghan Badakhshan, 

harnessing previously collected comparative 

ethnographic data.  

 

Materials and methods 

This study was carried out in 2006-2007 in 

GBAO. With a population of 23,600, Darwaz District 

was selected because of a bridge connecting villages on 

either side of the border, permitting the lead researcher a 

unique regular access to otherwise isolated Afghan and 

Tajik villages. The population of Darwaz is 

predominantly ethnically Tajik and religiously Muslim. 

In addition to the survey, the study included semi-

structured interviews (n=184) with married women of 

reproductive age, which collected observations on birth 

and reproductive health care in local clinics and 

hospitals. Also included were key informant interviews 

with community and religious leaders and healthcare 

providers in Tajik and Afghan villages situated opposite 

each other along the border. 

After training, three local female field assistants 

fluent in Tajiki language conducted household surveys, 

recording the data using the standardized validated 

forms. Over the course of 7 months, every third 

household in 24 villages in Tajik Badakhshan was 

selected and visited. The villages were selected based on 

population (< 300 households, > 300 households), 

geographic location (road access, along a river/tributary, 

on a mountainside), and distance from the district 

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hospital in Kalai-Khumb. All women present in the 

household who were 18 and older and who were not 

sisters were invited to participate. A total of 820 

participants answered the minimum four interview 

questions necessary for the analysis. This short survey 

was also embedded in a longer semi-structured interview 

for another 184 participants, resulting in a total of 1004 

participants. The longer ethnographic interview 

instrument elicited a complete reproductive history, 

including onset of sexual activity, contraceptive use, 

details on each pregnancy and birth, and personal 

perspectives on the issues of gender, marriage, and 

childbearing risk in their village. No males were 

interviewed. Three subjects with unknown ages were 

excluded from the long interview group, resulting in the 

final sample size of 1001 research participants. This 

study was approved by the Stanford University IRB, and 

all respondents verbally consented to participating in the 

study.  

By interviewing women about the survival of 

their adult sisters, the sisterhood method allows for 

retrospective maternal mortality estimates in remote 

regions like GBAO because it reduces sample size 

requirements and costs. The WHO has relied on maternal 

mortality estimates collected via the sisterhood method 

to provide crucial maternal health programming in the 

absence of vital registration systems since the 1980’s.4 

According to the procedure for the direct sisterhood 

method (S1),2 respondents were asked eleven questions 

about the sex, age and survivorship of all children born 

to the respondent’s mother. For all sisters reported to be 

deceased who were married, respondents were asked for 

the year of death, age at death, and whether the sister died 

while pregnant, in childbirth, or within the 42 days 

following pregnancy or childbirth. Answers to these 

questions were used to obtain data on four indicators: 1) 

the number of sisters born to the same mother who 

reached the age of 15 years or older; 2) how many of 

these sisters were still alive; 3) how many of these sisters 

died; and 4) of those who died, how many died during 

pregnancy or within 42 days of birth. Undergraduate 

research assistants from the University of Central Asia in 

Dushanbe entered the data into an Excel database. Data 

were cleaned prior to analysis by reviewing and 

comparing the data in the excel spreadshees and the paper 

forms. Erroneous values and missing data were coded as 

missing (less than 2%).  

Although the legal age of marriage in Tajikistan 

is 17, women regularly married at younger ages.7 To 

consider these cultural factors, we followed the method 

of Smith et al9 and counted every female sibling over the 

age of 15 as married. Siblings under the age of 15 were 

excluded, but their data were used to compute total 

reported siblings. Polygyny is illegal in Tajikistan and 

not routinely practiced. No homes with multiple wives 

were visited. 

For the 820 participants who completed the 

short survey, the respondent’s exact age was not 

collected. Respondent age was estimated, and age 

categories were assigned using birth order and reported 

sibling ages.  To estimate respondent age, the 

population mean interbirth interval, the total age range of 

siblings divided by total number of siblings (IBI = 2.78), 

was added to the age of the sibling born just prior to the 

respondent.  For the 181 women who received more in-

depth interviews as part of the larger ethnographic study, 

year of birth was collected, and we therefore used exact 

age. Five groups were used to produce age category 

estimates. We used R (2018) version “Joy in Playing” for 

calculations based on the methodology suggested by 

Graham [Table 1].2 Confidence intervals (95%) were 

calculated for lifetime risk [Table 2] and MMR [Figure 

1] using the method published by Hanley.6  

The lifetime risk of maternal death was 

calculated by dividing the number of maternal deaths by 

the sister units of risk exposure, q(w) = ri Bi⁄ , where the 

sister units of risk exposure was given by the number of 

ever-married sisters multiplied by an adjustment 

factor,  Bi = NiAi . Adjustment factors are corrections 

based on a found age-distributed pattern between the 

proportion of sisters dying of maternity related causes

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Table 1. Estimation of maternal mortality using the Sisterhood method for GBAO Tajikistan, 2006. 

and the probability of dying from those causes.2 We also 

applied a correction to the number of sisters at risk in the 

younger respondent group by multiplying the number of 

respondents by the average number of sisters reported by 

older respondents (25 and older). This adjusts for under-

estimation of the number of total lifetime sisters for 

young respondents.3 Finally, because sample size was too 

small to rely on age group estimates, the data were 

aggregated over all age groups to give the total lifetime 

risk of maternal death, Q = ∑ ri ∑ Bi⁄  [Table 1 and Table 

2]. To reduce the impact of potential reporting biases, we 

also followed Graham et al2 in restricting respondent age 

to 49 and under, however, a maternal death of a sister is 

a very memorable event,7 and we had no reason to believe 

that the memories of these older respondents were 

impaired. 

The Maternal Mortality Ratio (MMR), is a 

function of the lifetime mortality risk and the total 

fertility rate, MMR = 1 - P1 TFR⁄
, where P = 1 - Q , the 

lifetime probability of avoiding death from maternal 

causes, and TFR is the total fertility rate, the total number 

of children born per woman in her lifetime, or likely to 

be, if exposed to current rates of age-specific fertility. 

When lifetime cumulative risk, Q, remains constant or 

increases in tandem with lower TFRs, the MMR 

increases, showing an increased risk of dying per 

pregnancy. 

Standard errors for Q were calculated as SEQ =

 √(r B) ∗ 1 − (r B)⁄⁄ B⁄ . Upper and lower confidence 

limits of 95%, Q ±1.96(SE), were then substituted into 

the MMR equation to give upper and lower bounds on 

these estimates.6 Time-lags using this method2 also place 

Age group of 

respondents, 𝒊 

(a) 

Number of 

Respondents 

(b) 

 

Sisters Ever-

married, 𝑵𝒊 

(c) 

Maternal 

deaths, 𝒓𝒊 

(d) 

Adjustment 

factor, 𝑨𝒊 

(e) 

 

Sister-units 

of risk 

exposure, 

𝑩𝒊 

(f = ce) 

Life-time risk 

of maternal 

death, 𝒒(𝒘) 

(g = d/f) 

Proportion of 

dead sisters 

dying of 

maternal 

causes 

(h) 

18-24 173 593 * 2 0.151 90 0.0222 0.4000 

25-34 254 807 4 0.421 340 0.0118 0.2222 

35-44 208 798 2 0.737 588 0.0034 0.1429 

45-54 188 659 1 0.934 616 0.0016 0.0500 

55+ 178 572 6 0.992 567 0.0106 0.1304 

Total 1001 429 15 -- 2201 0.0068 ** 

(1 in 147) 

-- 

* Derived for age 18-24 by multiplying the # of respondents 18-24 (n=173) by the average number of ever married 

sisters per respondent for age groups 25+ (3.425).  This corrects for under-estimation of the number of total sisters 

for young respondents (Graham, 1989). Reported number of ever married for respondents 18-24 is 358. 

** Lifetime risk of maternal death for respondents under 54 years of age = 9/1634 = 0.0055 (1 in 182) n = 823.  

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aggregated estimates of MMR for ≤49 about 12 years 

before data collection. For our sample, the MMR then 

refers to the post-soviet transitional period, 

approximately 1994 – 1995. 

 

Results 

The average number of siblings (brothers and 

sisters) reported was M = 6.5 (SD = 3.0) with a maximum 

of 23, however 93% of respondents reported 10 or less 

siblings. An average of M = 4.95 (SD = 2.26) sisters with 

a maximum of 11 was found. Results for each age group 

are reported in Table 1. For all respondents, the ever-

married number of sisters was N = 3429, with 103 

reported as deceased (15/103 mortality events attributed 

to maternal causes).  

We report both the total lifetime risk, Q, for 

population age groups ≤ 49 and for ≤ 54 [Table 2].  

For Tajik Badkhstan using all respondents, Q = 0.0068, 

95% CI [0.0034, 0.0103], or a lifetime risk of maternal 

death of 1 in 147. Lifetime risk of maternal death for age 

49 and under is Q = 0.0069, 95% CI [0.0024, 0.0114], or 

1 in 145. The lifetime risk for those 54 and under is 

0.0055, 95% CI [0.0019, 0.0091], or 1 in 182.  

The national TFR estimate for 1994-1995 is 

4.88.8 Using this TFR, our estimate of the maternal 

mortality ratio (MMR) in Tajik Badakhshan is 141 

maternal deaths per 100,000 live births, 95% CI [49, 

235].  This figure is congruent with the MMR national 

estimate for that time frame, MMR = 129, CI [112, 149]9 

represented in Figure 1 by the grey shaded region, 

matching the spike in MMR experienced nationally in 

Tajikistan in the immediate post-Soviet transition. This 

confirms the usability of MMR best estimates using the 

sisterhood method, despite small sample sizes and large 

confidence intervals. Our research also suggests the need 

for local estimates of TFR and the need for repeated 

studies to track MMR trends in rural areas. 

As can be seen in Figure 1, MMR is highly dependent on 

TFR.  Urban areas typically have lower fertility 

compared to rural regions, and the fertility transition is 

typically slower in these areas. While fast rates of fertility 

transition are similar across urban contexts, the diffusion 

to non-urban areas is, in contrast, characterized by large 

heterogeneity.10 In this study, 62% of respondents 

reported using some form of birth control, but given the 

limited ability to estimate TFR directly using the current 

data, we relied on the national TFR point estimate. For 

comparison, we also computed the MMR using the 

national TFR for the three following five-year periods 

(1995-2000, 2000-2005, 2005-2010), and contrasted 

these results with those given by WHO, UNICEF, 

UNFPA, World Bank Group, and the United Nations 

Population Division.9 [Figure 1]  

 

Discussion 

We used the sisterhood method to produce a 

sub-national estimate of maternal mortality, MMR, for an 

isolated region in Tajikistan. The estimates we provide 

(using a range of national TFR estimates for four-time 

periods) refer to a period about 12 years before the

  Q, Lifetime Risk [CI] 

All women 0.0068 [0.0034 - 0.0103] 1 in 147 [1/294 to 1/97] 

≤49 years 0.0069 [0.0024 - 0.0114] 1 in 145 [1/417 to 1/88] 

≤54 years 0.0055 [0.0019 - 0.0091] 1 in 182 [1/526 to 1/110] 

Table 2. Lifetime risk of maternal death 

 

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Figure 1. GBAO Tajikistan Sisterhood estimated MMR (per 100,000) with 95% confidence intervals  

MMR estimates using the national TFR (4.88) for the same period based on time-lag (1990-1995) are congruent with the spike 

shown for national levels in 1995. MMR estimates using dropping TFR values during the post-Soviet fertility transition illustrate 

the stability or potential increase in MMR in this region compared to the national estimates for the same time period if urban 

improvements in maternal mortality outpace rural. 

survey, approximately 1994 – 1995. WHO, UNICEF, 

UNFPA, World Bank Group, and the United Nations 

Population Division (2015) found an MMR 129, CI [112, 

149] for this timeframe, demonstrating a spike in 

maternal mortality during the post-Soviet transition.12 

This estimate is higher than maternal mortality ratios in 

neighboring post-Soviet countries such as Uzbekistan 

(MMR 54) and Kazakhshan (MMR 91), though similar 

to Kyrgyzstan (MMR 120).12  

Our result for GBAO is congruent with the 

national Tajikistan estimate, MMR = 141, CI [49, 235]. 

We suspected that the MMR for GBAO would be higher 

than the national MMR given its isolation as a semi-

autonomous region in the Pamir mountains along the 

border with Afghanistan. Despite the stabilizing power of 

socialized health care during the Soviet era, emergency 

obstetric care was not always available in the region, 

though skilled midwives did attend most births.7 The 

post-Soviet transition involved dismantling key socialist 

welfare programs that contributed to conditions that 

increased maternal mortality risk nationwide.  

There are multiple limitations to consider in this 

study. Though recall bias may be unlikely because a 

sister’s death is a significant and memorable socio-

cultural event, it is possible some respondents failed to 

report maternal deaths of sisters who may have moved 

out of the area, resulting in an underestimation of 

maternal deaths. Recall bias may have also produced an 

overestimation of maternal deaths if some respondents 

incorrectly attributed deaths of sisters to maternal factors. 

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It is possible that sisters living in the same village 

produced duplicated accounts. However, in this 

patrilineal society, women move to their husband’s 

village when they are married, making this limitation 

unlikely or uncommon.  

The results are also potentially impacted by the 

lack of a local estimate of TFR during a period of 

dropping fertility nationwide. Figure 1 shows the effect 

of TFR estimates on estimates of the MMR. TFR 

decreases after the Soviet period ended (approximately 

1991), yet the MMR spikes nationwide before quickly 

dropping.  This is likely a reflection of the dramatic 

socio-political instability which followed independence 

from the Soviet Union. Tajikistan was not only cut off 

from Soviet benefits such as nutritional supplies, roads, 

and hospital supplies, but also plummeted into a lengthy 

civil war between 1992 and 1997, making it unique 

among the former Soviet countries of Central Asia. Cut 

off from the capital and bordering Afghanistan, GBAO 

was particularly impacted by the upheaval of the civil war 

and its aftermath.  

However, a lower TFR is likely applicable to 

respondents in our study, rather than the TFR of their 

parents during the decades when the Soviets enforced 

pro-natal agendas in GBAO, which increased fertility 

substantially. The Tajikistan Demographic and Health 

Survey suggests that the region-specific TFR is 3.30, 

close to the 2005-2010 United Nations (2015) estimate 

(3.48). A lower TFR increases the MMR if individuals 

continue to be exposed to the 1994-1995 risk profile. This 

problem could be exacerbated as inequality between 

urban and rural areas often widens in periods of economic 

transition; maternal mortality may improve in urban 

areas but worsen in rural, requiring further investigation. 

These aspects of fertility and mortality require 

investigation. For this population, using national TFRs 

based on model life tables (as we do) may be a more 

reliable approach due to small sample sizes, but fertility 

transitions make applicability to rural areas uncertain. 

Therefore, estimating TFR locally while incorporating 

the uncertainty in this calculation could improve our 

grasp of region specific needs in these contexts.  

Discussion of important trends in TFR in rural regions 

compared to urban and the investigation of associated 

impacts on maternal mortality requires repeated studies 

of both local TFR and maternal mortality risk. This point 

is especially important to consider in similar post-Soviet 

countries of Central Asia where the collapse of the Soviet 

Union heightened health and social disparities between 

rural and urban populations. 

Regional variation in maternal mortality may be 

as high as variation across international borders, 

necessitating targeted interventions to improve maternal 

outcomes at the local level.9 Global health efforts to reach 

developed countries’ standards may have greater impact 

when subnational variation in maternal mortality is 

addressed. Our results indicate that where social, 

political, and economic conditions contribute to rapidly 

changing mortality and fertility rates in small subnational 

populations, it is crucial that researchers use effective and 

accessible methods to estimate local TFR in order to 

better understand variation in maternal health outcomes 

at the local level. For example, the fall of the Soviet 

Union changed women’s lives in GBAO in ways that 

directly impact maternal risk, including education, 

marriage age, medical education, availability of medical 

supplies and contraceptives, hospital infrastructure, and 

accessibility.7 Understanding trends in maternal 

mortality in subnational areas in relation to those found 

using national metrics will require repeated studies.  

 

References  

1. Blencowe, H., Calvert, C., Lawn, J. E., Cousens, 

S., & Campbell, O. M. Measuring maternal, 

foetal and neonatal mortality: Challenges and 

solutions. Best practice & research Clinical 

obstetrics & gynaecology. 2016; 36: 14-29. 

2. Graham, W., Brass, W., & Snow, R. W. 

Estimating maternal mortality: the sisterhood 

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method. Studies in family planning. 

1989;20(3):125-135 

3. Hill, Kenneth, et al. Estimates of maternal 

mortality worldwide between 1990 and 2005: an 

assessment of available data. The 

Lancet 370.9595. 2007: 1311-1319. 

4. Shiffman, Jeremy. "Can poor countries 

surmount high maternal mortality?." Studies in 

family planning. 2000; 31.4: 274-289. 

5.  Population of the Republic of Tajikistan as of 1 

January 2008, State Statistical Committee, 

Dushanbe, 2008. 

6. Khalid, A. Islam after Communism: Religion 

and Politics in Central Asia. Berkeley: 

University of California Press. 2007. 

7. Liese, K. L. Motherdeath in Childbirth: 

Explaining maternal mortality on the roof of the 

world. Stanford: Stanford University. 2009. 

8. Bartlett, L. A., Mawji, S., Whitehead, S., 

Crouse, C., Dalil, S., Ionete, D., ... & Afghan 

Maternal Mortality Study Team.  Where 

giving birth is a forecast of death: maternal 

mortality in four districts of Afghanistan, 1999–

2002. The Lancet, 2005; 365(9462), 864-870. 

9. Smith, J. B., Fortney, J. A., Wong, E., Amatya, 

R., Coleman, N. A., & Johnson, J. D. G. 

Estimates of the maternal mortality ratio in two 

districts of the Brong-Ahafo region, 

Ghana. Bulletin of the World Health 

Organization. 2001;79(5): 400-408. 

10. Hanley, J. A., Hagen, C. A., & Shiferaw, T. 

Confidence intervals and sample-size 

calculations for the sisterhood method of 

estimating maternal mortality. Studies in Family 

Planning. 1996; 220-227. 

11. Graham, W. J., Foster, L. B., Davidson, L., 

Hauke, E., & Campbell, O. M. Measuring 

progress in reducing maternal mortality. Best 

practice & research Clinical obstetrics & 

gynaecology. 2008;22(3): 425-445. 

12. United Nations, Department of Economic and 

Social Affairs, Population Division. World 

Population Prospects: The 2015 Revision, DVD 

Edition. 2015. 

13. World Health Organization. Trends in Maternal 

Mortality: 1990 to 2015 Estimates by WHO, 

UNICEF, UNFPA, World Bank Group and the 

United Nations Population Division. WHO: 

Switzerland; 2015. 

 

 

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