|Year : 2012 | Volume
| Issue : 3 | Page : 279-289
India’s progress towards the Millennium Development Goals 4 and 5 on infant and maternal mortality
Hanimi Reddy1, Manas R Pradhan1, Rohini Ghosh1, AG Khan2
1 South Asia Network for Chronic Disease (SANCD), Public Health Foundation of (PHFI), C1/52, First Floor, Safdarjung Development Area, New Delhi – 110 016, India
2 Department of Sociology, Degree College, Aland, Gulbarga, Karnataka-585 101, India
|Date of Web Publication||25-May-2017|
South Asia Network for Chronic Disease (SANCD), Public Health Foundation of India (PHFI), C1/52, First Floor, Safdarjung Development Area, New Delhi – 110 016
Background: India is in a race against time to achieve the Millennium Development Goals (MDGs) 4 and 5, to reduce Infant Mortality Rate (IMR) to ‘28’ and Maternal Mortality Ratio (MMR) to ‘109’, by 2015. This study estimates the percent net contribution of the states and the periods in shaping India’s IMR/MMR, and predicts future levels.
Methods: A standardized decomposition technique was used to estimate each state’s and period’s percent share in shaping India’s decline in IMR/MMR between two time points. Linear and exponential regression curves were fitted for IMR/MMR values of the past two decades to predict IMR/MMR levels for 2015 for India and for the 15 most populous states.
Results: Due to favourable maternal mortality reduction efforts in Bihar/Jharkhand (19%) and Madhya Pradesh/Chhattisgarh (11%), Uttar Pradesh (33%) - India is predicted to attain the MDG-5 target by 2016, assuming the pace of decline observed in MMR during 1997-2009 continues to follow a linear-trend, while the wait may continue until 2023-2024 if the decline follows an exponential- trend. Attaining MDG-4 may take until 2023-2024, due to low acceleration in IMR drop in Bihar/ Jharkhand, Uttar Pradesh/Uttarakhand and Rajasthan. The maximum decline in MMR during 2004-2009 coincided with the launch and uptake of the National Rural Health Mission (NRHM).
Conclusions: Even though India as a nation is not predicted to attain all the MDG 4 and 5 targets, at least four of its 15 most populous states are predicted to do so. In the past two decades, MMR reduction efforts were more effective than IMR reduction efforts.
Keywords: Achievement, infant mortality rate, maternal mortality ratio, Millennium Development Goals, net contribution, regression equation, target, India.
|How to cite this article:|
Reddy H, Pradhan MR, Ghosh R, Khan A G. India’s progress towards the Millennium Development Goals 4 and 5 on infant and maternal mortality. WHO South-East Asia J Public Health 2012;1:279-89
|How to cite this URL:|
Reddy H, Pradhan MR, Ghosh R, Khan A G. India’s progress towards the Millennium Development Goals 4 and 5 on infant and maternal mortality. WHO South-East Asia J Public Health [serial online] 2012 [cited 2019 Sep 17];1:279-89. Available from: http://www.who-seajph.org/text.asp?2012/1/3/279/207024
| Introduction|| |
Globally, maternal and child mortality are in decline, although the pace of decline is not sufficient to attain Millennium Development Goals (MDGs) 4 and 5 for 128/137 developing countries. Due to slow progress in reducing infant and maternal mortality and the moral urgency of reinvigorating efforts to tackle slow progress; the United Nations (UN) launched the Global Strategy for Women’s and Children’s Health in 2010. As part of this strategy, India committed to spend US$ 3.5 billion annually, for strengthening maternal and child health services in 235 districts, which account for nearly 70% of infant and maternal deaths. In 2010, India recorded 56 000 maternal and 1.3 million infant deaths, the highest for any country.,,
India’s MDG 4 target is to reduce IMR by two-thirds between 1990 and 2015, i.e., from 80 infant deaths per 1000 live births in 1990 to ‘28’ by 2015. Under MDG 4, another target is to improve the proportion of one-year-old children immunized against measles from 42% in 1992-1993 to 100% by 2015. India’s main MDG 5 target is to reduce MMR by three- quarters between 1990 and 2015, i.e., from 437 maternal deaths per 100 000 live births to ‘109’, while it has also committed to improve the ‘proportion of births attended by skilled health personnel’. With only three years left to achieve MDGs 4 and 5 targets, there is a need to understand the progress made by India and as well as its 15 most populous states.
To a large extent, India shapes the global MDGs 4 and 5 targets, because of its share of the global burden of child (23%) and maternal mortality (19%)., Moreover, during the past two decades, the 15 most populous states, which account for 95% of India’s population, have made variable progress on infant and/or maternal mortality reduction efforts. State- wise analysis of IMR/MMR decline provides us an opportunity for learning which strategies did and did not work. In this context, the specific objectives of the study are:
- To estimate percent net contribution of the 15 most populous states and different periods, in shaping India’s IMR and MMR decline;
- To fit linear and exponential regression curves, and understand how IMR/MMR has declined in India and in the 15 most populous states;
- To use the fitted regression estimates, extrapolate the year by which India’s MDGs 4 and 5 targets of IMR ‘28’ and MMR
‘109’ would be achieved by India and the 15 most populous states.
| Methods|| |
Quantifying the contribution of states’ decline during a time period upon overall decline: We have partitioned the difference in IMR/MMR of a state between t1 and t2 into two components: Component-1 is the difference due to variations in state-specific IMR/MMR. Component-2 is the difference due to variations in state-specific distribution of live births. We made this computation for each state by using the formula developed by Fleiss and refined by Buehler et al. (equation-1).
P1 and P2 represent the proportion of live births in a state at t1 and t2
R1 and R2 represent IMR/MMR of a state at t1 and t2
We added two components of equation-1 to arrive at ‘net-excess deaths at t2 as compared to t1’ for each state., We finally calculated what percentage of the total net- excess deaths between t1 and t2 in India was contributed by each of the 15 populous-states. Using Sample Registration System (SRS) data, periodic changes in IMR were measured for the following durations: 1990 and 1996; 1996 and 2001; 2001 and 2006; 2006 and 2010; and for the whole period 1990 and 2010. Using SRS data, periodic changes in MMR were measured for the following durations: 1997–1998 and 1999–2001; 1999–2001 and 2001–2003; 2001–2003 and 2004–2006; 2004–2006 and 2007–2009; and for the total period 1997-1998 and 2007-2009.
Estimation of trends in IMR/MMR:
For understanding the trends in IMR/MMR decline, we fitted regression curves between IMR/MMR values and their reference dates using Ordinary Least Square (OLS) method, as OLS offers a greater degree of objectivity, in the absence of outliers. It is globally assumed; IMR/MMR declines are non-linear and approximate to exponential., If the decline is exponential, it reflects the fact that mortality cannot keep declining linearly below zero. However, there is no evidence that IMR/ MMR decline is best modelled as exponential. In contrast, if decline follows a linear pattern, IMR/MMR declines at a constant rate over a defined period and can decline below zero. Hence, we fitted linear and exponential regression-curves, separately for India and for 15 populous states, using SRS data. Chi- squared goodness-of-fit test was used for assessing the appropriateness of the fitted regression curve.
For fitting regression curves of IMR, we used a moving average figure of three consecutive years as the IMR value for mid- year. Regression curves of IMR were fitted by using moving average IMRs for 21 years, during 1990–2010. By using regression estimates, we have predicted IMR figure for 2015, and/or the year by which it would reach ‘28’ per 1000 live births. As MMRs are periodic estimates, we have measured interpolated value of two consecutive periods as the MMR for the mid-period using linear interpolation. Regression curves of MMR were fit using nine MMR data points, during 1997–2009. Using regression estimates, MMR figure for 2015 and/or the year by which it would reach ‘109’ were derived.
Our analysis is confined to 15 states, as SRS does not provide MMR estimates for smaller states/union territories, and these 15 states (Andhra Pradesh, Assam, Bihar/ Jharkhand, Gujarat, Haryana, Karnataka, Kerala, Madhya Pradesh/Chhattisgarh, Maharashtra, Orissa, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh/Uttarakhand, and West Bengal) cover approximately 95% of India’s population; hence changes in these states will fairly change the national scenario.
| Results|| |
Changes in MDG 4: Trends in IMR of India and of the 15 most populous states - during the past four decades are shown in [Figure 1]. It depicts a uniform declining trend across the states, although the pace of decline was more rapid during 1976–1991 and again in 2006–2010. Decline was the highest in Uttar Pradesh/Uttarakhand, followed by Gujarat and Tamil Nadu. Across all the states, excluding Kerala - two types of declining trends were visible: 1) higher decline when the rates are high (in early 1970s); and 2) a steady rate of decline during 2001–2010.
|Figure 1: Trends in Infant mortality rate: 1971-2010, India and 15 populous states|
Click here to view
[Table 1] provides changes in IMR, percent net contribution of the states and the periods to overall decline in IMR of India, and predicted levels of IMR. In the last two decades, IMR of India has declined by around 40% and number of infant deaths from around 2.2 mi llion to 1.3 million. Percent decline was ≥50% only in three out of 15 states (Maharashtra, Tamil Nadu and West Bengal), while absolute annual decline was above the national average in Orissa, Madhya Pradesh/Chhattisgarh, Uttar Pradesh/Uttarakhand and West Bengal.
|Table 1: State-wise changes in IMR, contribution of states and periods to India's IMR decline and year of achieving India's MDG-4 target|
Click here to view
If total net decline in IMR of India during different periods of 1990-2010 is considered as 100% (last row of Table-1): maximum decline occurred during 1990-1996 (36%) followed by 2001-2006 (26%). On the other hand, if total decline in IMR of India during 1990-2010 among the 15 populous states is considered as 100% (8th column of Table-1): Uttar Pradesh/Uttarakhand contributed maximum (20%) to this decline; followed by Madhya Pradesh/Chhattisgarh (14%); West Bengal (11%); Maharashtra (9%); etc. By comparing states’ per cent share in total net decline in IMR of India with state’s percent share in live births – one can estimate whether a particular state has contributed ‘favourably to net decline’ (state’s percent share in net decline > state’s percent share in live births) or ‘unfavourably to net-decline’ (state’s percent share in net decline ≤ state’s percent share in live births) in IMR of India during a particular period (4th to 8th column vs 9th column, of Table-1). During 1990-2010, Madhya Pradesh/Chhattisgarh contributed most favourably to the net decline (with its share of 10% to live births it has contributed 14.4% to total net decline in IMR of India). Andhra Pradesh, Karnataka, Maharashtra, Orissa, Tamil Nadu and West Bengal were the other states which contributed favourably to net decline. In contrast, Bihar/Jharkhand contributed most unfavourably to net decline. However, during 2006-2010, Bihar/Jharkhand, Madhya Pradesh/Chhattisgarh, Rajasthan and Uttar Pradesh/Uttarakhand transitioned from unfavourable to favourable states; contributing 57% to net decline in IMR of India when their share to live births was 52% [Table 1].
If the declining trend in IMR observed during 1990-2010 continues linearly, India’s IMR would be 42 per 1000 live births (95% CI: 38-45) by 2015 and MDG 4 target level of ‘28’ would be achieved in 2023–2024. If the decline follows an exponential trend? India’s IMR would be 45 per 1000 live births (95% CI: 41–49) by 2015, and MDG 4 target would be achieved in 2033–2034. Unless special efforts are made to reduce IMR in Assam, Bihar/Jharkhand, Haryana, Rajasthan and Uttar Pradesh/Uttarakhand – it may take at least up to 2023–2024 for India to reach the MDG 4 target, and much longer for the aforementioned states.
Measles immunization rates: India is doing well on the other MDG 4 indicator, as the percentage of 12–23 month old children immunized against measles improved from 42% in 1992–199 3 to 74% by 2009.
Goodness of fit of linear and exponential regression curves on IMRs for India during 1990-2010 were appropriate, with respective chi-square values of 0.79 (p<1.000) and 1.36 (p<1.00).
Changes in MDG 5: [Figure 2] depicts changes in MMRs of India and of 15 populous states, during 1997–2009. During this period, there was a precipitous decline in MMR of India from 398 to 212 per 100 000 live births, even though variations in the base (1997–1998) MMR levels of states were mainly responsible for recent (2007–2009) variations.
|Figure 2: Trends in maternal mortality ratio: 1997-2009, India and 15 populous states|
Click here to view
[Table 2] provides changes in MMR, percent net contribution of 15 populous states and periods to overall decline in MMR of India, and predicted levels of MMR. During 1997–2009, MMR of India declined by 47%, with an annual absolute decline of 15.5 points. Maternal deaths decreased from around 100 000 to 60 000, assuming MMRs provided by SRS are correct. If total decline in MMR of India during different periods of 1997–2009 is considered as 100%, the maximum decline occurred between 2004-2006 and 2007–2009 (32%), followed by 2001-2003 and 2004–2006 (27%). Uttar Pradesh/ Uttarakhand contributed most favourably to net-decline in MMR of India (with its share of 18% to the live births, contributed 33% to MMR decline). Bihar/Jharkhand, Madhya Pradesh/Chhattisgarh, Rajasthan and Assam also contributed favourably to net decline. It is encouraging that between 2004-2006 and 2007–2009, Bihar/Jharkhand, Madhya Pradesh/Chhattisgarh, Rajasthan and Uttar Pradesh/Uttarakhand – together contributed 75% to the net decline in India’s MMR, when their collective share in live births was only 43%.
|Table 2: State-wise changes in MMR, contribution of states and periods to India's MMR decline and year of achieving India's MDG-5 target|
Click here to view
If the declining trend in MMR observed during 1997-2009 continues linearly, India will be very close to achieving the MDG 5 target level of ‘109’ by 2016, as the MMR is predicted to be 117 (95% CI: 109–125) in 2015. However, if the decline follows an exponential trend, India’s MMR would be 159 (95% CI: 153–166) in 2015, and MDG-5 target would only be reached in 2023–2024. Kerala, Tamil Nadu and Maharashtra had already reached MMR of 109 by 2009, and if the same pace of decline continues linearly or exponentially, Andhra Pradesh, Gujarat and West Bengal have a good chance of touching 109 MMR, by 2017-2018. India is doing well on ‘percent deliveries attended by skilled health personnel’, with an improvement from 33% in 1992–199 3 to 76% by 2009. Goodness-of-fit of linear regression curve on MMRs of India during 1997-2009 suggests moderate deviation from the observed values [chi-squared = 0.2 (p<0.032)], while the exponential fit suggests negligible deviation [chi-squared=0.36 (p<0.055)].
| Discussion|| |
If the pace of linear decline in MMR during 1997-2009 continues, India will be very close to attaining MDG-5 target level of ‘109’ per 100 000 live births by 2016. However, India’s IMR would be hovering around 42 in 2015 if the decline follows a linear trend, and the MDG 4 target level of ‘28’ would only be achieved in 2023-2024. If the declines in IMR/MMR follow exponential trends, reaching MDGs 4&5 targets gets further postponed by India and most states. India’s MMR decline during 1997-2009 may mainly be attributed to favourable contributions from Uttar Pradesh/ Uttarakhand, Bihar/Jharkhand, Madhya Pradesh/Chhattisgarh, and Rajasthan. Due to unfavourable contributions in IMR reduction efforts by Bihar/Jharkhand, Uttar Pradesh/ Uttarakhand, Rajasthan and Assam, India’s run for MDG-4 target is delayed.
How comparable are our IMR/MMR predictions with others? Were the state- specific changes in IMR/MMR during a particular period reflected in national level changes in a standardized way or not? Which one of the two regression curves (linear/ exponential) Indian IMRs/MMRs fits better? Due to paucity of reliable MMR estimates for India/states prior to 1997, predictions were based on IMR. A recent Lancet series, projected India’s IMR and MMR in 2015 as 43 and 153 respectively, while another report projected India’s IMR in 2015 as 46–49. These predictions matched with our IMR predictions. Our IMR extrapolations for 2015 are in synchronization with predictions of the Central Statistical Organization, Government of India. For the states of Assam, Orissa, and Rajasthan, there is good comparability between our MMR predictions and the Annual Health Survey (AHS, 2010-2011). For MMR, our exponential regression-based predictions match closely with other findings.,
Lozano et al., in their paper on tracking the progress of MDGs 4 and 5 in 163 countries predicted India’s IMR and MMR in 2011 respectively as 49 (95% CI: 41–56) and 187 (95% CI: 142–238), while our linear and exponential regression-based estimates respectively were 48 (95% CI: 47–49) and 50 (95% CI: 46-54); and 178 (95% CI: 173–184) and 196 (95% CI: 195–197). As compared to referred predictions,,,,,,, ours are more robust due to the use of more recent IMR/ MMR data, moving-average IMR estimates, and predicted IMRs/MMRs through the use of linear and exponential regression curves.
A trend analysis of IMRs in India during 1970–2000 by Saikia et al., concluded that the decline was much steeper during the 1970s and 1980s, and that IMR had stagnated during 1996–2000, 2000–2004 and 2002–2006. We also noticed that the decline in IMR was the lowest during 1996–2001. Our decomposition of the decline in India’s IMR among the states also matched this finding.. Analysis of India’s IMRs during 1981–1997 found that the decline tended to stagnate for brief periods and was often followed by a subsequent rapid decline. We are of the view that India’s IMR decline still followed a similar phenomenon, as we noted that a plateau during 1996–2001 was followed by a rapid decline during 2001–2006 [Table 1]. Our findings agree with previous studies for Kerala, Maharashtra, Tamil Nadu, and West Bengal as the only states likely to achieve MDG 4 and 5 targets.,
Contribution of state-specific changes in rate/ratio onto national-level change:
If populations are similar with respect to factors associated with the event under study, there is no problem in comparing events across states. If populations are not similarly constituted, direct comparison of the overall events may be misleading. In the present analysis, rather than measuring changes in IMR/MMR of India between two time points as mere percent/absolute change, we estimated it as: net-effect of state-wise distribution of live births and state-specific mortality rates/ ratios - a technique used extensively, for understanding birth weight-specific or regional differences in mortality.
Linear versus exponential regression?
While estimating the progress made by different countries including India towards MDGs 4 and 5, linear regression curves were used., However, for understanding the decline in IMRs of India and Nepal in the past three decades, exponential regression curves were found to be more appropriate. IMR decline in 18 Western nations in the 20th century was, for the most part, neither linear nor exponential. For India’s IMR decline during 1990-2010, both linear and exponential regressions fitted well, while for MMR declines, exponential regression fits better than linear. As India’s IMR/MMR decline during the past two decades is an outcome of heterogeneous progress made by different states, sometimes linear and sometimes exponential, and also taking into account high IMR/MMR levels in a majority of the states - it is difficult to conclude which of the two regression curves is more appropriate for the Indian scenario.
Strengths/limitations: Our analysis included the latest IMRs/MMRs from SRS, the most reliable source for national and state specific estimates. For fitting regression curves, we used moving averages or periodic estimates, instead of point estimates. One of the limitations of this study is that our analysis/interpretation relied completely on the quality and completeness of SRS data. An evaluation of SRS data showed omission rates of 1.8% for births and 2.5% for deaths. IMRs of SRS are considered to be robust, and they matched closely with all the three National Family Health Survey (NFHS) estimates, for India. However, IMRs of SRS in 2010 were lower than AHS estimates by 1–10 absolute points, in eight states. India’s MMRs of SRS deviated substantially with NFHS-2 and UN estimates. As MMR estimates of UN are usually indirect estimates,,, we are of the opinion that SRS estimates are still robust for India.
Is maximum decline in MMR between 2004-2006 and 2007-2009 due to NRHM or an artefact? Periodic analysis of MMR decline in India during 1997–2009 indicated maximum drop between 2004–2006 and 2007–2009. Is this finding an artefact or influence of NRHM? Lim et al., indicated that India’s conditional cash transfer scheme Janani Suraksha Yojana (JSY)' of NRHM contributed to an increase in institutional deliveries, and was associated with reduction of about four perinatal and two neonatal deaths per 1000 live births, while having no significant effect on maternal mortality. Since its launch in 2005, NRHM is credited with deploying more than 750 000. Accredited Social Health Activists (ASHAs), as change agents between the women and the health system, resulting in improved prospects for maternal and newborn care as compared to the past.
Conclusions: Even though the pace of decline in IMR accelerated during 2001–2010 after a period of stagnation (1996–2001), India is still predicted to fall short of achieving its MDG 4 target level of ‘28’ per 1000 live births by 2015, in 11 out of the 15 most populous states, and in India as a nation. Assam, Bihar/ Jharkhand, Rajasthan and Uttar Pradesh/ Uttarakhand, need to put special efforts for accelerating decline in IMR. Considering the pace of MMR decline during 1997–2009, six out of the 15 most populous states have a fairly good chance of attaining India’s MDG 5 target level of ‘109’, albeit two–three years behind schedule (2017–2018).
| Acknowledgements|| |
We sincerely acknowledge the active guidance and support of Prof. Shah Ebrahim and Dr Fiona Taylor. We thank Dr Ulla Sovio, Dr Jai and Dr Preet Dhillon for reviewing the manuscript and Prof PM Kulkarni and Prof RM Pandey for providing valuable inputs.
| References|| |
Lozano R, Wang H, Foreman KJ, Rajaratnam JK, Naghavi M, Marcus JR, et al. Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis. The Lancet
. 2011; 378(9797): 1139-65.
WHO, UNICEF, UNFPA, and the World Bank estimates (2012). Trends in Maternal Mortality: 1990 to 2010
. Geneva, World Health Organization.
Paul VK, Sachdev HS, Mavalankar D, Ramachandran P, Sankar MJ, Bhandari N, et al. Reproductive health, and child health and nutrition in India: meeting the challenge. The Lancet
. 2011 Jan 22; 377(9762): 332-49.
Claeson M, Bos ER, Mawji T, Pathmanathan I. Reducing child mortality in India in the new millennium. Bull World Health Organ
. 2000; 78(10): 1192-9.
Chatterjee A, Paily VP. Achieving Millennium Development Goals 4 and 5 in India. BJOG
. 2011; 118(Suppl 2): 47–59.
International Institute for Population Sciences (IIPS). National family health survey (MCH and Family Planning): India 1992-93. Bombay: IIPS, 1995.
Government of India (GOI). National health profile of India 2010. New Delhi, 2010.
Fleiss JL, Levin B, Paik MC. Statistical methods for rates and proportions
. 3rd edn. New York: John Wiley & Sons, 2003.
Buehler JW, Kleinman JC, Hogue CJ, Strauss LT, Smith JC. Birth weight-specific infant mortality, United States, 1960 and 1980. Public Health Rep
. 1987 Mar-Apr; 102(2): 151-61.
United Nations Children’s Fund. Background note on methodology for under-five mortality estimation. New York: UNICEF.
Thapa S. Declining trends of infant, child and under-five mortality in Nepal. J Trop Pediatr
. 2008 Aug; 54(4): 265-8.
Bishai D, Opuni M. Are infant mortality rate declines exponential, The general pattern of 20th century infant mortality rate decline. Popul Health Metr
. 2009; 7: 13.
United Nations Development Programme. Fact sheet: goal 5: improve maternal health. New York: UNDP, 2008
Ram F, Mohanty SK, Usha R. Progress and prospects of Millennium Development Goals
in India. Mumbai: International Institute for Population Sciences, .2009
Saikia N, Singh A, Ram F. Has child mortality in India really increased in the last two decades, Economic and Political Weekly
. 2010; XLV (51): 62-70.
State of Georgia. Georgia epidemiology report: Quantifying the effect of low birth weight on racial differences in infant mortality rate, Georgia: Department of Public Health.1989
Allen DM, Buehler JW, Hogue CJ, Strauss LT, Smith JC. Regional differences in birth weight-specific infant mortality, United States, 1980. Public Health Rep
. 1987 Mar-Apr; 102(2): 138-45.
Registrar General of India. Report on intensive enquiry conducted in sub-sample of SRS units. Occasional paper No. 1. New Delhi: Office of the Registrar General of India, Ministry of Home Affairs, .1988
International Institute for Population Sciences (IIPS) and Macro International. National family health survey (NFHS-3)2005-06 : India: Volume I. Mumbai: IIPS.2007
International Institute for Population Sciences (IIPS) and ORC Macro. National family health survey (NFHS-2)1998-99 ,: India. Mumbai: IIPS.2000
Lim SS, Dandona L, Hoisington JA, James SL, Hogan MC, Gakidou E. India’s Janani Suraksha Yojana, a conditional cash transfer programme to increase births in health facilities: an impact evaluation. The Lancet
. 2010 Jun 5; 375(9730): 2009-23.
[Figure 1], [Figure 2]
[Table 1], [Table 2]
|This article has been cited by|
||Epidemiological study of maternal death in Assam
| ||Tushar Manohar Rane,Tulika Goswami Mahanta,Manjit Baruah,Swarnali Devi Baruah |
| ||Clinical Epidemiology and Global Health. 2019; |
|[Pubmed] | [DOI]|
||Spatial clustering and risk factors of infant mortality: district-level assessment of high-focus states in India
| ||Ashish Kumar Gupta,Laishram Ladusingh,Kakoli Borkotoky |
| ||Genus. 2016; 72(1) |
|[Pubmed] | [DOI]|
||An Assessment of Association between Neighborhood Socioeconomic Status and Infant Mortality in High Focus States in India
| ||Ashish Kumar Gupta,Laishram Ladusingh |
| ||Health. 2016; 08(07): 630 |
|[Pubmed] | [DOI]|
||Post Millennium Development Goals Prospect on Child Mortality in India: An Analysis Using Autoregressive Integrated Moving Averages (ARIMA) Model
| ||Partha De,Damodar Sahu,Arvind Pandey,B. K. Gulati,Nomita Chandhiok,Arvind Kumar Shukla,Pavitra Mohan,Raj Gautam Mitra |
| ||Health. 2016; 08(15): 1845 |
|[Pubmed] | [DOI]|
||Birth preparedness and place of birth in rural Mysore, India: A prospective cohort study
| ||Meredith L. Wilcox,Karl Krupp,Bhavana Niranjankumar,Vijaya Srinivas,Poornima Jaykrishna,Anjali Arun,Purnima Madhivanan |
| ||Midwifery. 2016; 34: 245 |
|[Pubmed] | [DOI]|
||Does Breastfeeding Have an Effect on Infant Mortality in India? An Analysis of National Family Health Survey Data
| ||Nomita Chandhiok,Lucky Singh,Kh. Jitenkumar Singh,Damodar Sahu,Arvind Pandey |
| ||Open Journal of Preventive Medicine. 2015; 05(09): 359 |
|[Pubmed] | [DOI]|
||Association of child health and household amenities in high focus states in India: a district-level analysis
| ||J. Gouda,A. K. Gupta,A. K. Yadav |
| ||BMJ Open. 2015; 5(5): e007589 |
|[Pubmed] | [DOI]|
||Coverage and Financial Risk Protection for Institutional Delivery: How Universal Is Provision of Maternal Health Care in India?
| ||Shankar Prinja,Pankaj Bahuguna,Rakesh Gupta,Atul Sharma,Saroj Kumar Rana,Rajesh Kumar,Maarten Postma |
| ||PLOS ONE. 2015; 10(9): e0137315 |
|[Pubmed] | [DOI]|
||Maternal mortality and its relationship to emergency obstetric care (EmOC) in a tertiary care hospital in South India
| ||Papa Dasari |
| ||Obstetric Medicine. 2015; 8(2): 86 |
|[Pubmed] | [DOI]|
||Male engagement as a strategy to improve utilization and community-based delivery of maternal, newborn and child health services: evidence from an intervention in Odisha, India
| ||Jean Christophe Fotso,Ariel Higgins-Steele,Satyanarayan Mohanty |
| ||BMC Health Services Research. 2015; 15(S1) |
|[Pubmed] | [DOI]|
||Trek to MDG 4: State of Indian States
| ||Vinod K. Paul,M. Jeeva Sankar,Shyla Saini |
| ||The Indian Journal of Pediatrics. 2014; 81(10): 993 |
|[Pubmed] | [DOI]|
||More Evidence on the Impact of Indiaæs Conditional Cash Transfer Program, Janani Suraksha Yojana: Quasi-Experimental Evaluation of the Effects on Childhood Immunization and Other Reproductive and Child Health Outcomes
| ||Natalie Carvalho,Naveen Thacker,Subodh S. Gupta,Joshua A. Salomon,Jeremy D. Goldhaber-Fiebert |
| ||PLoS ONE. 2014; 9(10): e109311 |
|[Pubmed] | [DOI]|