¶ Membership of the Million Death Study Collaborators is provided in the Acknowledgments.
The authors have declared that no competing interests exist.
Conceived and designed the experiments: AM UR RK PJ. Performed the experiments: AM UR PK RJ. Analyzed the data: AM. Contributed reagents/materials/analysis tools: AM UR RK PJ. Wrote the paper: AM UR RK PJ.
Data on cause-specific mortality, skilled birth attendance, and emergency obstetric care access are essential to plan maternity services. We present the distribution of India's 2001–2003 maternal mortality by cause and uptake of emergency obstetric care, in poorer and richer states.
The Registrar General of India surveyed all deaths occurring in 2001–2003 in 1.1 million nationally representative homes. Field staff interviewed household members about events that preceded the death. Two physicians independently assigned a cause of death. Narratives for all maternal deaths were coded for variables on healthcare uptake. Distribution of number of maternal deaths, cause-specific mortality and uptake of healthcare indicators were compared for poorer and richer states. There were 10 041 all-cause deaths in women age 15–49 years, of which 1096 (11.1%) were maternal deaths. Based on 2004–2006 SRS national MMR estimates of 254 deaths per 100 000 live births, we estimated rural areas of poorer states had the highest MMR (397, 95%CI 385–410) compared to the lowest MMR in urban areas of richer states (115, 95%CI 85–146). We estimated 69 400 maternal deaths in India in 2005. Three-quarters of maternal deaths were clustered in rural areas of poorer states, although these regions have only half the estimated live births in India. Most maternal deaths were attributed to direct obstetric causes (82%). There was no difference in the major causes of maternal deaths between poorer and richer states. Two-thirds of women died seeking some form of healthcare, most seeking care in a critical medical condition. Rural areas of poorer states had proportionately lower access and utilization to healthcare services than the urban areas; however this rural-urban difference was not seen in richer states.
Maternal mortality and poor access to healthcare is disproportionately higher in rural populations of the poorer states of India.
India contributes one-fifth of the global burden of absolute maternal deaths; however, it has experienced an estimated 4.7% annual decline in maternal mortality ratio (MMR)
Within India, there is marked variation in MMR and healthcare access between regions and in socioeconomic factors
In this study, we report on the maternal deaths in India's Sample Registration System (SRS). The SRS, with verbal autopsy, was used to estimate the national and regional distribution of maternal death and uptake of obstetric service indicators among women who died while pregnant or postpartum.
The MDS is an on-going nationally representative survey organized by the Registrar General of India (RGI). It is designed to determine the causes of death and risk factors of death. The design, methodology, and preliminary findings of the MDS have been described elsewhere
Maternal deaths: All verbal autopsies forms with an affirmative answer to any of three questions
The following terms define obstetric care indicators:
We used the RGI categorization of Indian poorer states, which have high-fertility, and maternal and infant mortality (also referred to as Empowered Action Group states and Assam consisting of: Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and Uttarakhand). Richer states are the remaining states and territories of India
All proportional estimates account for weighting for sampling probability. Variance estimations were calculated using Taylor series linearization for the survey subpopulation of maternal deaths
We estimated the number of maternal deaths and distribution of MMR by region and cause-specific mortality using the proportionate distribution of the survey-weighted sample, 2004–2006 SRS maternal mortality ratio estimates, and the United Nations Population Division estimates of live births and deaths in India in 2005
The proportion of missing data were imputed using multiple imputation by chained equations, and the distribution of observed versus imputed datasets were compared
All analyses were conducted using Stata/SE (StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP).
SRS enrolment is on a voluntary basis, and its confidentiality and consent procedures are defined as part of the
Of 122 291 deaths there were 10 041 all-cause deaths in women age 15–49 years. There were 1130 pregnancy-related deaths, of which 34 were excluded as they were either accidental or incidental, resulting in 1096 maternal deaths (11.1% of all-deaths of women age 15–49 years). The national MMR reported by the SRS in 2004–2006 is 254 deaths per 100 000 live births (95%CI 239–269). We estimated that rural areas of poorer states had the highest MMR (397, 95%CI 385–410) compared to the lowest MMR in urban areas of richer states (115, 95%CI 85–146). We estimated 69 400 maternal deaths in India in 2005. Three-quarters of maternal deaths were clustered in rural areas of poorer states (estimated total maternal deaths 52 800), whereas these regions have only half the estimated live births in India (13.3 million births). The proportion of maternal deaths to all-cause deaths in women, 15–49 years, was three times higher in rural areas of poorer states (16.3%) compared to urban areas of richer states (
Datasource: SRS 2001–3, SRS 2004–6 MMR and UN live birth and death estimates for India 2005 *Unweighted sample count of maternal deaths **Survey weighted, (95%CI), rounded to nearest 100th. MDS - Million Death Study. Low-income states Bihar, Jharkhand, Madhya Pradesh, Chhattisgarh, Orissa, Rajasthan, Uttar Pradesh, Uttarakhand and Assam.
Half the maternal deaths were in the age range of 20–29 years, with a median age of 26 years (interquartile range 21–32 years), with no significant difference noted between poorer and richer states. Adolescent women (≤18) represented 6.0% (95%CI 4.4–7.6) of maternal deaths, and adolescent maternal deaths were not significantly over-represented in a single religious group, or rural versus urban areas (data not shown). The proportion of non-literate women was significantly higher for maternal deaths in poorer versus richer states (72.3% versus 46.1%) (
Sample count, unweighted | Proportion, sample weighted | ||||||||||
Characteristics | India | Poorer states |
Richer states | India (%) | (95%CI) | Poorer states |
(95%CI) | Richer states (%) | (95%CI) | p-value |
|
Age group (years) | 15–19 | 112 | 81 | 31 | 11.2 | (9.1–13.3) | 11.0 | (8.6–13.4) | 11.8 | (7.3–16.2) | 0.2418 |
20–24 | 290 | 188 | 102 | 30.5 | (27.4–33.7) | 29.1 | (25.4–32.7) | 34.9 | (28.6–41.3) | ||
25–29 | 210 | 125 | 85 | 20.1 | (17.4–22.9) | 19.3 | (16.1–22.5) | 22.5 | (17.1–27.9) | ||
30–34 | 183 | 131 | 52 | 20.0 | (17.2–22.7) | 21.5 | (18.2–24.9) | 15.3 | (10.8–19.9) | ||
35–39 | 118 | 81 | 37 | 12.4 | (10.2–14.7) | 12.9 | (10.2–15.6) | 11.1 | (7.0–15.1) | ||
40–44 | 40 | 29 | 11 | 4.3 | (2.9–5.7) | 4.6 | (2.9–6.2) | 3.5 | (1.2–5.8) | ||
45–49 | 15 | 9 | 6 | 1.4 | (0.6–2.3) | 1.6 | (0.5–2.7) | 0.9 | (0.0–1.9) | ||
Missing | 128 | 69 | 59 | . | . | . | |||||
Marital status | Married | 988 | 652 | 336 | 96.9 | (95.7–98.1) | 97.4 | (96.1–98.6) | 95.5 | (92.4–98.5) | 0.1843 |
Single |
32 | 19 | 13 | 3.1 | (1.9–4.3) | 2.6 | (1.4–3.9) | 4.5 | (1.5–7.6) | ||
Missing | 76 | 42 | 34 | . | . | . | . | ||||
Literacy status | Non-literate | 636 | 476 | 160 | 65.4 | (62.3–68.6) | 72.3 | (68.8–75.8) | 46.1 | (39.9–52.3) | 0.0001 |
Literate | 388 | 194 | 194 | 34.6 | (31.4–37.7) | 27.7 | (24.2–31.2) | 53.9 | (47.7–60.1) | ||
Missing | 72 | 43 | 29 | . | . | . | |||||
Religion | Hindu | 790 | 556 | 234 | 79.3 | (76.6–82.1) | 82.0 | (78.8–85.1) | 71.9 | (66.3–77.4) | 0.0001 |
Muslim | 157 | 100 | 57 | 16.9 | (14.3–19.5) | 16.3 | (13.2–19.3) | 18.7 | (13.7–23.7) | ||
Other | 71 | 12 | 59 | 3.8 | (2.6–4.9) | 1.8 | (0.7–2.8) | 9.4 | (6.2–12.6) | ||
Missing | 78 | 45 | 33 | . | . | . | |||||
Place of residence | Rural | 992 | 660 | 332 | 86.3 | (83.6–88.9) | 89.2 | (86.4–92.0) | 78.1 | (72.2–84.0) | 0.0002 |
Urban | 104 | 53 | 51 | 13.7 | (11.1–16.4) | 10.8 | (8.0–13.6) | 21.9 | (16.0–27.8) | ||
Total | 1096 | 713 | 383 | 100.0 | . | 100.0 | . | 100.0 |
Datasource: Indian SRS 2001–3.
States Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and Uttarakhand.
Rao-Scott Chi-squared comparison of poorer versus richer states distribution.
Never married, separated, divorced, widowed.
There were no differences in the major causes of maternal deaths between poorer and richer states, or between rural and urban areas (data not shown). Most maternal deaths were attributed to direct obstetric causes (81.8%, n = 919) (
Datasource: Indian SRS 2001–3 data, SRS 2004–6 MMR and UN live birth and death estimates for India 2005. ICD-10 categorization of cause of death
Sample count, unweighted | Proportion, survey weighted | |||||||||
Cause of death |
India | Poorer states |
Richer states | India | (95%CI) | Poorer states | (95%CI) | Richer states | (95%CI) | p-value |
Total direct maternal deaths | 919 | 604 | 315 | 81.8 | (79.3–84.3) | 83.8 | (80.9–86.6) | 76.5 | (71.3–81.6) | |
296 | 177 | 119 | 24.5 | (21.8–27.2) | 25.2 | (22.4–28.0) | 24.5 | (21.8–27.2) | 0.1649 | |
O44–46, O67, O72 | ||||||||||
248 | 170 | 78 | 22.6 | (19.9–25.2) | 23.3 | (20.5–26.0) | 22.6 | (19.9–25.2) | ||
O22, O26, O71, O75, O87, O88, O90, X60–84, F53 | ||||||||||
184 | 124 | 60 | 17.2 | (14.8–19.7) | 17.8 | (15.3–20.3) | 17.2 | (14.8–19.7) | ||
A34, O23, O41, O85–86 | ||||||||||
108 | 81 | 27 | 9.4 | (7.6–11.2) | 9.7 | (7.8–11.5) | 9.4 | (7.6–11.2) | ||
O00–01, O03–O06 | ||||||||||
79 | 50 | 29 | 7.1 | (5.5–8.8) | 7.3 | (5.6–9.1) | 7.1 | (5.5–8.8) | ||
O11, O16 | ||||||||||
4 | 2 | 2 | 0.4 | (0.0–0.8) | 0.4 | (0.0–0.8) | 0.4 | (0.0–0.8) | ||
O29, O74, O89 | ||||||||||
Total indirect maternal deaths O98, O99 | 177 | 109 | 68 | 15.9 | (13.5–18.2) | 15.3 | (12.5–18.0) | 19.1 | (14.2–24.0) | |
Total maternal deaths | 1096 | 713 | 383 | 100.0 | . | 100.0 | . | 100.0 | . |
Datasource: Indian SRS 2001–3.
WHO 2012 ICD-10 categorization of cause of death versus unweighted distribution of maternal deaths in an early report was hemorrhage (38%, n = 526), other (including indirect deaths) (34%, n = 471), sepsis (11%, n = 152), abortion (8%, n = 111), obstructed labour (5%, n = 69, and hypertensive disorders (5%, n = 69)
States Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and Uttarakhand.
Rao-Scott Chi-squared comparison of poorer versus richer states distribution of direct obstetric causes and indirect cause.
Unanticipated - anesthetic complication during cesarean delivery.
One-quarter of maternal death were due to obstetric hemorrhage (n = 296), with most deaths occurring in the intrapartum period (n = 258). One-quarter of maternal deaths were due to ‘other obstetric complications’ (n = 248), which included ill-defined cause of death in labour (n = 125) and the antenatal and postpartum period (n = 81). Fifteen per cent of maternal deaths were due to indirect causes (n = 177).
Maternal deaths making up the remaining sample were pregnancy-related infection, abortion, hypertension, and anesthetic complications from obstetric surgery. Pregnancy-related infection (n = 184) included puerperal sepsis (n = 130), antepartum deaths of sepsis onset following prolonged rupture of membranes (n = 30), and obstetric tetanus in the postpartum period (n = 24). Of the 108 maternal deaths due to complication in early pregnancy, most were reported complications following spontaneous abortion (n = 64).
Earlier reporting of the same dataset found somewhat similar distribution of maternal deaths
For most maternal deaths, the complication leading to death arose at term (≥7 months gestation), and the timing of complication onset were evenly distributed between the periods of pregnancy, intrapartum, and postpartum (≥24 hours–6 weeks post-delivery). One-quarter of the postpartum deaths occurred within the first three days and half died within 7 days of delivery (
Sample count, unweighted | Proportion, survey weighted | ||||||||||
Event | India | Poorer states |
Richer states | India | (95%CI) | Poorer states | (95%CI) | Richer states | (95%CI) | p-value |
|
Gestational age | Term (≥7 mos) | 784 | 511 | 273 | 82.8 | (80.2–85.3) | 81.6 | (78.5–84.7) | 86.3 | (81.8–90.8) | 0.0033 |
Preterm | 173 | 125 | 48 | 17.2 | (14.7–19.8) | 18.4 | (15.3–21.5) | 13.7 | (9.2–18.2) | ||
Missing | 139 | 77 | 62 | . | . | . | . | . | . | ||
Antenatal care | Yes | 508 | 323 | 185 | 61.8 | (58.2–65.4) | 58.3 | (54.0–62.5) | 73.1 | (66.9–79.3) | 0.0038 |
No | 175 | 131 | 44 | 21.5 | (18.5–24.6) | 23.4 | (19.8–27.1) | 15.4 | (10.2–20.5) | ||
NA |
145 | 107 | 38 | 16.7 | (14.0–19.4) | 18.3 | (15.0–21.6) | 11.5 | (7.4–15.7) | ||
Missing | 268 | 152 | 116 | . | . | . | . | . | . | ||
Planned place of birth/abortion | Home | 487 | 334 | 153 | 48.9 | (45.5–52.2) | 50.2 | (46.3–54.2) | 44.8 | (38.5–51.1) | 0.0001 |
Health-facility | 233 | 123 | 110 | 22.9 | (20.1–25.8) | 19.1 | (16.0–22.3) | 34.4 | (28.4–40.4) | ||
NA |
293 | 208 | 85 | 28.2 | (25.2–31.2) | 30.6 | (27.0–34.2) | 20.8 | (15.7–25.9) | ||
Missing | 83 | 48 | 35 | . | . | . | . | . | . | ||
Primary care provider | Midwife/Doctor | 283 | 168 | 115 | 30.3 | (27.1–33.5) | 27.9 | (24.3–31.6) | 37.6 | (31.2–44.0) | 0.2597 |
TBA | 291 | 198 | 93 | 31.0 | (27.8–34.2) | 31.2 | (27.5–35.0) | 30.5 | (24.4–36.6) | ||
Other |
94 | 62 | 32 | 8.8 | (7.0–10.7) | 8.7 | (6.5–10.9) | 9.3 | (5.5–13.1) | ||
NA |
292 | 208 | 84 | 29.8 | (26.7–33) | 32.1 | (28.4–35.9) | 22.6 | (17.1–28.0) | ||
Missing | 136 | 77 | 59 | . | . | . | . | . | . | ||
Timing of death | Pregnant | 268 | 185 | 83 | 24.8 | (22.0–27.6) | 26.2 | (22.9–29.6) | 20.7 | (15.7–25.7) | 0.4062 |
Intrapartum | 369 | 225 | 144 | 33.6 | (30.5–36.7) | 32.2 | (28.6–35.8) | 37.6 | (31.7–43.5) | ||
Postpartum | 447 | 296 | 151 | 41.6 | (38.4–44.8) | 41.6 | (37.8–45.4) | 41.7 | (35.7–47.7) | ||
Missing | 12 | 7 | 5 | . | . | . | . | . | . | ||
. | . | . | . | . | . | ||||||
. | . | . | . | . | . | . | |||||
Total | 1096 | 713 | 383 | 100.0 | . | 100.0 | . | 100.0 | . | . |
Datasource: Indian SRS 2001–3.
States Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and Uttarakhand.
Rao-Scott Chi-squared comparison of poorer versus richer states distribution.
Not applicable - early gestation.
Excludes pregnancies≤4 months gestation.
Not applicable - complication arose prior to the onset of labour.
Traditional doctor, family members, unattended.
Subpopulation of those who delivered.
Includes 1 forceps delivery.
Subpopulation of postpartum women day 1–42. TBA, traditional birth attendant.
The proportion of maternal deaths who had ≥1 antenatal visit was significantly lower in the poorer versus richer states (58.3% versus 73.1%), and 11.5% delivered by caesarean, with no significant difference found between poorer and richer states.
Maternal deaths in poorer states were more likely to seek consultation in the community; whereas, maternal deaths in richer states were more likely to transport directly to a health-facility or be there already whilst receiving routine care (
Sample count, unweighted | Proportion, survey weighted | ||||||||||
Event | India | Poorer states |
Richer states | India | (95%CI) | Poorer states | (95%CI) | Richer states | (95%CI) | p-value |
|
Community consult | Yes | 274 | 214 | 60 | 29.7 | (26.6–32.9) | 33.6 | (29.8–37.3) | 18.0 | (12.9–22.3) | 0.0001 |
No | 281 | 188 | 93 | 24.1 | (21.3–26.9) | 25.3 | (22.0–28.7) | 20.3 | (15.5–27.0) | ||
NA |
459 | 265 | 194 | 46.2 | (42.8–49.6) | 41.1 | (37.2–45.0) | 61.7 | (55.6–66.5) | ||
Missing | 82 | 46 | 36 | . | . | . | . | . | . | ||
Emergency transport for complication | Yes | 357 | 240 | 117 | 38.8 | (35.4–42.1) | 38.8 | (34.9–42.7) | 38.5 | (32.2–44.4) | 0.0001 |
No | 468 | 330 | 138 | 44.0 | (40.6–47.3) | 47.0 | (43.0–50.9) | 34.5 | (28.4–41.9) | ||
NA |
176 | 91 | 85 | 17.3 | (14.7–19.9) | 14.2 | (11.4–17.0) | 27.1 | (21.4–31.4) | ||
Missing | 95 | 52 | 43 | . | . | . | . | . | . | ||
Health-facility admission (routine or emergency) | Yes | 433 | 253 | 180 | 40.8 | (37.6–44.0) | 37.5 | (33.8–41.2) | 50.4 | (44.4–55.7) | 0.0038 |
No | 662 | 459 | 203 | 59.2 | (56.0–62.4) | 62.5 | (58.8–66.2) | 49.6 | (43.5–56.7) | ||
Missing | 1 | 1 | 0 | . | . | . | . | . | . | ||
Place of death | Home | 511 | 369 | 142 | 49.7 | (46.4–53.1) | 53.8 | (49.8–57.7) | 37.2 | (31.1–44.6) | 0.0001 |
In transit | 138 | 92 | 46 | 13.8 | (11.5–16.1) | 14.0 | (11.2–16.7) | 13.3 | (9.1–17.2) | ||
Health-facility | 363 | 207 | 156 | 36.5 | (33.2–39.7) | 32.3 | (28.5–36.0) | 49.5 | (43.1–54.6) | ||
Missing | 84 | 45 | 39 | . | . | . | . | . | . | ||
Healthcare contacts | 0 | 209 | 164 | 45 | 25.8 | (22.4–29.2) | 27.6 | (23.8–31.5) | 16.3 | (10.2–27.8) | 0.0001 |
1 | 334 | 239 | 95 | 46.7 | (42.8–50.7) | 44.7 | (40.3–49.0) | 57.1 | (48.2–62.1) | ||
2 | 120 | 94 | 26 | 18.2 | (15.1–21.3) | 18.5 | (15.0–21.9) | 17.0 | (10.1–23.0) | ||
≥3 | 56 | 42 | 14 | 9.3 | (6.9–11.7) | 9.2 | (6.5–12.0) | 9.6 | (4.1–14.1) | ||
Missing | 377 | 174 | 203 | . | . | . | . | . | |||
Total | 1096 | 713 | 383 | 100.0 | . | 100.0 | . | 100.0 | . |
Datasource: Indian SRS 2001–3.
States Assam, Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and Uttarakhand.
Rao-Scott Chi-squared comparison of poorer versus richer states distribution.
Not applicable - transported or planned health-facility birth.
Not applicable - planned health-facility birth.
About half of the maternal deaths occurred at home (49.7%) and 13.8% occurred in transit (home to health-facility, from health-facility to referral unit, or from health-facility to home). A significantly higher proportion of maternal death occurred at home in poorer versus richer states (53.8% versus 37.2). One-quarter of women in the sample received no healthcare contact from a midwife or physician (25.8%), either in the home, community, or health-facility.
We looked at distribution of highest healthcare uptake sought by women with direct obstetric deaths at the time that the obstetric complication arose (
x-axis: Survey weighted proportion of timing of direct maternal death (n = 919) with respect to the pregnancy: early termination (spontaneous or therapeutic), term antenatal complication (≥7 months), intrapartum, postpartum. y-axis: Highest healthcare sought at onset of complication leading to death: routine admission to health-facility/hospital for abortion or labour, emergency admission for complication, community consultation for complication, no facility-based healthcare utilization at time of complication.
Our a priori subpopulation analysis compared rural to urban areas of two routine obstetric service indicators in both poorer and richer states (
Datasource: Indian SRS 2001–3 data.
Maternal deaths are a significant cause of death in women in the 15–49 years age group, and they make up a larger proportion of all-cause deaths in the rural areas of poorer states, compared to other regions of India. We found that the distribution of cause-specific mortality was the same across poorer and richer states, suggesting that the high burden of maternal death in poorer states is not due to an excess of one or more causes of direct obstetric deaths.
Use of healthcare was significantly lower in rural areas of poorer states compared with urban ares; whereas there was no difference between rural and urban areas of richer states. Furthermore, emergency obstetric care (community consultation and/or health-facility admission) was a significant point of access to care for most women in a critical medical state in both poorer and richer states.
One-third of complications arose in pregnancy prior to the onset of labour. This was higher than we expected. Narrative review permitted us to identify the timing of the complication relative to the onset of labour and we were able to identify the antepartum precedents of intrapartum mortality, unlike previous studies
We were also able to differentiate between planned and actual place of birth, in order to differentiate between those seeking care for routine services and those seeking care in a critical medical condition. Routine care plays an important role in prevention and early identification of complications leading to maternal death
Our study is the first nationally representative study of maternal mortality in India. The strength of this study is its size, as maternal deaths are relatively rare, permitting comparison across regions of India. Previous studies have been limited by small sample size, non-representative sampling, and measurement bias that does not differentiate between primary care provider versus emergency consultation care, and planned versus actual place of birth (
Nonetheless, there are certain limitations to this study. These data are 10 years old however they do provide a national baseline of the characteristics of maternal deaths and healthcare use by these women, prior to the introduction of two major national health policy changes: the National Rural Health Mission, and the conditional cash-transfer scheme called Janani Suraksha Yojana. Secondly, a recent review of verbal autopsy coding found that physician coding performed as well or better than various automated coding methods, using hospital-based deaths as a reference
Misclassification of cause-specific mortality may have occurred in differentiating between the types of maternal deaths, given the absence of medical care received in this population, leading to an underestimation of certain causes that often rely on objective measures (e.g. blood pressure for hypertensive disorders). In a systematic review of vital statistics and surveys, Khan et al. estimated the proportion of South Asian maternal deaths due to hypertensive disorders to be 9% (2–35%), and our estimate of 7% is within this range
Misclassification of healthcare services may have occurred if the respondent was unaware of the skilled birth attendant's credentials or the health-facilities capacity to provide obstetric care, thus access to care may be over estimated. However, we do not have reason to believe that this misclassification occurred differentially across India.
Incomplete data occurred as the primary study was not designed specifically to capture the reported variables of interest. Our missing data analysis (
The maternal mortality ratio and the proportion of maternal deaths to all-cause death was higher in the poorer versus the richer states. We hypothesize that this difference is not due to any single specific cause of maternal death; however, perhaps our study did not have the power to demonstrate a difference in cause-specific mortality distribution between poorer and richer states. Further areas of research should look at how cause-specific mortality profile changes with various levels of MMR - as increasing healthcare uptake leads to a decline in preventable maternal deaths (e.g. improved outcomes in hypertensive disorders of pregnancy with primary and secondary prevention, active management of third stage, and clean delivery)
Reduction in India's maternal mortality rate would make an important contribution to the worldwide reduction of maternal mortality. Our analysis presents the important local variations from global characteristics of maternal mortality as well as the substantial internal variations within India. For policy-makers, faced with constrained budgets but committed to India's goal of effectively addressing a relatively rare yet highly important health priority, these variations may provide some targets for intensifying or initiating maternal health interventions. The majority of maternal deaths took place after 7 months gestational age and in the immediate post-partum period, and women are often presenting at obstetric facilities only in very serious condition. Thus, one priority is to provide health education on the early recognition of potentially hazardous conditions as part of an enhanced antenatal care program. As well, reduction in avoidable maternal deaths in India will require skilled healthcare providers with the capacity to deliver service for not only routine delivery but emergency obstetric care including community consultation and emergency admission to a health-facility. Secondly, obstetric services themselves could be a target area for intervention, particularly for investments in infrastructure, staffing and training in the rural areas of poorer states. Finally, we note that there was no difference in many outcomes between the rural and urban areas of the richer states, suggesting that national health and development programs focusing on poorer states must be maintained and even intensified. From 1999–2010, the proportion of safe deliveries has increased annually at twice the rate in the rural areas of poorer compared to richer states (8% versus 4%)
Data sharing statement: The data used in this study are the property of the Registrar General of India and the overall mortality results have been published in 2006. Application for data access can be made to the Office of the Registrar General of India.
(PDF)
The Registrar General of India has managed the SRS since they established the survey in 1971, and is collaborating with several of the authors in the ongoing Million Death Study. All study materials are available at HYPERLINK "
1. Department of Community Medicine Gujarat Medical College, Ahmedabad: DV Bala, P Seth, KN Trivedi
2. Department of Community Medicine Kolkatta Medical College, Kolkatta: SK Roy
3. Department of Community Medicine Regional Institute of Medical Sciences, Imphal: L Usharani
4. Department of Community Medicine S.C.B. Medical College Cuttack, Orissa: B Mohapatra
5. Department of Community Medicine SMS Medical College Jaipur: AK Bharadwaj, R Gupta
6. Epidemiological Research Center, Chennai: V Gajalakshmi, CV Kanimozhi
7. Gandhi Medical College, Bhopal: RP Dikshit, S Sorangi
8. Healis-Seskarhia Institute of Public Health, Navi Mumbai: PC Gupta, MS Pednekar, S Sreevidya
9. Apollo Institute of Medical Sciences & Research, Hyderabad: P Bhatia
10. St. John's Academy of Health Sciences, Bangalore: A Shet, AS Shet, D Xavier, S Rathi, V Habbare
11. King George Medical College, Lucknow: S Awasthi
12. Najafgarh Rural Health Training Centre Ministry of Health Government of India, New Delhi: N Dhingra, J Sudhir, I Rawat (until 2007)
13. Regional Medical Research Center, ICMR Institute, Bhubaneshwar: AS Karketta, SK Dar
14. School of Preventative Oncology, Patna: DN Sinha
15. School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh: N Kaur, R Kumar, JS Thakur
16. Tata Memorial Cancer Hospital, Mumbai: RA Badwe, R Dikshit, M Mallath, K Panse, A Budukh
1. Office of the Registrar-General India, RK Puram, New Delhi India: C Chandramouli (Registrar General of India [RGI]), B Mishra, AK Saxena, MS Thapa, N Kumar, JK Banthia and DK Sikri (former RGIs)
2. Million Death Study Coordinating, Centre for Global Health Research (CGHR), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Dalla Lana School of Public Health, University of Toronto, Canada: P Jha (Principal Investigator), R Kamadod, S Neale, S Rathi, P Rodriguez, P Sati, J Sudhir, C Ramasundarahettige, W Suraweera
1. Indian Council of Medical Research, New Delhi India: VM Katoch (Director General or DG from 2008), NK Ganguly (DG to 2008), L Kant, B Bhattacharya, B Shah, DK Shukla
2. World Health Organization, Geneva and SEARO Office, New Delhi: T Boerma, A Fric, S Habayeb (former WHO Representative-India), S Khanum, CD Mathers, DN Sinha, N Singh, P Singh (Deputy Regional Director)
3. Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, England: J Boreham, R Peto, G Whitlock