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Exploring the spatial patterns of cesarean section delivery in India: Evidence from National Family Health Survey-4

Published:October 04, 2019DOI:https://doi.org/10.1016/j.cegh.2019.09.012

      Abstract

      Introduction

      Almost every day, 800 women die from pregnancy or childbirth-related complications around the world. The risks and costs associated with C-section deliveries are significant, mainly where there was no medical indication. Past research has shown a positive and significant association with C-section and maternal death.

      Objective

      The paper attempts to throw light on the pattern of C-section delivery in India at district levels as the increasing use of medical technologies during childbirth is a matter of concern.

      Methods

      Bivariate, logistic regression and spatial analyses techniques have been used for analysis purpose, using the fourth round of the National Family Health Survey (NFHS-4) data conducted in 2015–16.

      Results

      C-section have shown variability across all the states, and shifting from public to private is associated with an increase in the number of deliveries. Variables like the educational status of women, wealth, ANC, and OOPE were significantly associated with C-section.

      Conclusions

      There should be the provision of maternity benefits given to women who belong to below poverty line (BPL). Routine monitoring and evaluation of emergency obstetric services should be carried out. Further research to improve the quality of care in public health institutions should be made.

      Keywords

      1. Introduction

      Caesarean section (C-section) delivery is a major surgical procedure and obstetric intervention.
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      C-section is an obstetric intervention introduced in late Nineteenth century which aimed at saving lives of both the mother and the foetus/their new-borns by preventing poor obstetric outcomes from life-threatening pregnancy and childbirth-related complications.
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      On the other hand, a rate higher than 15% implies overutilization of the procedure for other than life-saving reasons.
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      The rates above 15% are unsuitable and unnecessary, imposing a financial burden and clinical risks on patients and healthcare systems.
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      However, WHO has recently suggested that they don't recommend a specific rate at either a hospital-level or a country-level as the extremely high or low cesarean delivery rate is an important quality of care issue. It may also indicate the mismatch between evidence and training/practice in obstetrics.
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      Numerous studies have found the high rate of C-section delivery rate throughout the world and have become a serious public health threat for health systems and does not contribute to maternal health and pregnancy outcome.
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      The global numbers and costs of additionally needed and unnecessary caesarean sections performed per year: overuse as a barrier to universal coverage.
      It is an important issue in many parts of the world, not only because of the additional short and long-term health hazards it causes but also due to increased costs associated with caesarean births.
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      In fact, WHO also underscores the importance of focusing on the wants of the pregnant mothers and discourages performing C-sections with no need. C-section delivery without a medical need places both mothers and their babies at a higher risk of short- and long-term health consequences.
      • Betrán A.P.
      • Torloni M.R.
      • Zhang J.J.
      • et al.
      WHO statement on caesarean section rates.
      ,
      • Betrán A.P.
      • Ye J.
      • Moller A.B.
      • Zhang J.
      • Gülmezoglu A.M.
      • Torloni M.R.
      The increasing trend in caesarean section rates: global, regional and national estimates: 1990-2014.
      Worldwide, C-section rates have increased and varied across different countries and albeit unequally. According to a study based on 150 countries, 18.6% of all births occurred by C-Section, ranging from 0.6% to 27.2% in the least and most developed regions, while in some countries, C-Section rates are up to 50%, mainly in the private sector resulting in millions of women undergoing unnecessary surgery respectively.
      • Betrán A.P.
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      • Zhang J.J.
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      WHO statement on caesarean section rates.
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      • Ye J.
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      • Zhang J.
      • Gülmezoglu A.M.
      • Torloni M.R.
      The increasing trend in caesarean section rates: global, regional and national estimates: 1990-2014.
      Another study based on 26 South Asian and sub-Saharan African countries using Demographic and Health Survey (DHS) data, found that rates were lowest among the ‘rural poor’ in 18 countries and highest among the ‘urban rich’ in all countries.
      • Betrán A.P.
      • Merialdi M.
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      Rates of caesarean section: analysis of global, regional and national estimates.
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      Trends in caesarean delivery by country and wealth quintile: cross-sectional surveys in southern Asia and sub-Saharan Africa.
      Moreover, it has also been reported in studies that high cost of C-section may result in catastrophic health expenditure (CHE) for families and exert extra pressure upon overburdened health systems mostly in low- and middle-income countries.
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      Caesarean section in four South East Asian countries: reasons for, rates, associated care practices and health outcomes.
      There is an evidence that C-section without medical indication is associated with increased maternal and neonatal mortality and morbidity, which can be reduced when indicated. Also, the rate of C-section delivery was positively related to postpartum, antibiotic treatment, stillbirths, anomalies of the placenta, neonatal survival, obstructed labour, selected breech delivery, mal-presentation of the foetus and foetal distress, even after adjustment for risk factors.
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      Caesarean delivery rates and pregnancy outcomes: the 2005 WHO global survey on maternal and perinatal health in Latin America.
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      In many countries, it is seen that millions of women who need surgical procedures do not have access to them, putting their and their children's lives at risk, while in some countries, unnecessary overuses of surgical practices are common.
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      Many studies have investigated the trends and inequities in use of MCH care services; there is a scarcity of information on clinical indications for C-section particularly from population-based studies, essential for more in-depth understanding of why C-section delivery rate is increasing and what strategies are needed to control its epidemic.
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      This high and rising C-section rate is a reason for concern. However, little information on how or why C-section rate is increasing and what should be done, both demand and supply side factors, attributed for this rapid rise in population-based C-section are important in the contexts.
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      It is often seen that patients request the obstetricians to perform the C-section delivery, and from physician's point of view, it is much more convenient and quicker than normal vaginal delivery, less painful and less time consuming.
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      In India, giving birth to a baby at a predetermined auspicious time and day are driving the patient (women) to go for a C-section, thus increasing the demand for C-sections.
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      In India, the rate of C-section delivery has increased from 8.5% to 17.2% between 2005–06 and 2015–16 (IIPS NFHS-4 Report 2015) which is lower compared to developing countries like Brazil and China. If we follow the guidelines of WHO, the present rate of C-section seems to be alarming both at the national and regional level. The percentage distribution of state-wise C-section deliveries over time (2005–2016) and in rural and urban areas in India (2015–16) are given in the appendix (Table A1). In all the states of India, C-section rates increased from 2005 to 2016 and the highest increase was in Jammu and Kashmir (19.6%). It also showed that there were more C-section deliveries in urban as compared to rural areas in almost all the states. The distribution of C-section by type of health facility are given in Table A2 (appendix). Table A2 shows the percentage of women undergoing C-section by type of Health Facility by states, India, 2015–16. It clearly showed that C-section deliveries were higher in private health care facilities as compared to public health care facilities in almost all the states of India. In private health care facilities, highest C-sections were performed in Jammu and Kashmir (75.5%) followed by Telangana (74.9%), Tripura (73.7%) and West Bengal (70.9%). The states with the lowest C-section deliveries were Rajasthan (23.2%), followed by Haryana (25.3%) and Gujrat (26.6%). A similar pattern was observed in public health care facilities, except for Telangana in which C-sections were highest (40.6%) followed by Jammu and Kashmir and other states. Both the tables show variation across all the states, assuming that there might be variations across the districts too. Although the study has reported a rising rate of caesarean births, the reasons remain unknown.
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      • Vasanthakumari K.P.
      • Babu P.K.
      Increasing trend of caesarean rates in India: evidence from NFHS-4.
      The present study aims to investigate the relationship between C-section deliveries and its associated complications, along with their socio-demographic determinants at district levels to inform policy-makers about equitable and focused strategies to end preventable maternal mortality and to improve MCH services in India. To the best of our knowledge, no previous study has conducted a spatial analysis of C-section delivery at the district level in India. However, we have not overlooked the spatial patterns of inequalities in the public-private sector and rural-urban area.

      1.1 Data source and sampling design

      The analysis is based on the National Family Health Survey (NFHS-4) conducted during 2015–16. All four NFHS surveys have been done under the stewardship of the Ministry of Health and Family Welfare (MoHFW), Government of India (GOI). Total eligible women taken for the analysis were 259,627 which includes 255,726 married women. The NFHS-4 sample is a stratified two-stage sample. The 2011 census served as the sampling frame for the selection of PSUs. PSUs were villages in rural areas and Census Enumeration Blocks (CEBs) in urban areas. In NFHS 2015-16 data is collected at district level and unit of analysis is individual as from every household, individuals are being surveyed.

      1.2 Statistical analysis

      Bivariate and logistic regression analyses were used to study the socioeconomic differentials in caesarean section deliveries in India. To examine spatial dependence and clustering of caesarean section deliveries over various explanatory variables, Moran's I, Univariate Local indicator of Spatial Association (LISA), Bivariate Local indicator of Spatial Association (LISA), LISA cluster map were produced. The Spatial weight matrix (w) of order 1 has been generated using the Queen's contiguity method to quantify the spatial proximity between each possible pair of observational entities in the dataset.
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      • Ord J.K.
      The analysis of spatial association by use of distance statistics.
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      • Getis A.
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      The analysis of spatial association by use of distance statistics.
      A positive spatial autocorrelation indicates that points with similar attribute values are closely distributed in space whereas negative spatial autocorrelation indicates that closely associated points are more dissimilar. Moran's I usually takes values in between −1 to +1, where positive values suggest the spatial clustering of the similar values and negative values indicate the clustering of different values. A zero value indicates a random spatial pattern with no spatial autocorrelation. Univariate LISA measures the correlation of neighbourhood values around a specific spatial location.
      • Anselin L.
      Local indicators of spatial association—LISA.
      It determines the extent of spatial randomness and clustering present in the data.
      • Clark P.J.
      • Evans F.C.
      Distance to nearest neighbor as a measure of spatial relationships in populations.
      ,
      • Cliff A.D.
      • Ord K.
      Spatial autocorrelation: a review of existing and new measures with applications.

      1.3 Four types of spatial autocorrelation were generated

      • 1.
        Hot Spots: Locations with high values, with similar neighbours (High-High).
      • 2.
        Cold Spots: Locations with low values, with similar neighbours (Low-Low).
      • 3.
        Spatial Outliers: Locations with high values, but with low-value neighbours (High-Low).
      • 4.
        Spatial Outliers: locations with low values, but with higher values of neighbours (Low-High).
      To see the potential regional correlates of C-section deliveries we performed spatial regression analysis which includes ordinary least square (OLS) model, Spatial Lag Model (SLM) and Spatial Error Model (SEM).
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      • Syabri I.
      • Kho Y.
      GeoDa: an introduction to spatial data analysis.

      1.4 Findings

      Map 1 indicates the prevalence of C-section deliveries in districts of India. The darker regions show a high incidence of C-section deliveries among women in various states. The high prevalence is visible in southern parts of India which includes Andhra Pradesh, Karnataka, Tamil Nadu and Kerala and also in the upper part of Northern India which provides for Himachal Pradesh and Jammu and Kashmir.
      Map 1
      Map 1Prevalence of C-section deliveries in districts of India, NFHS -4, 2015-16.
      Table A3 depicts binary logistic regression analysis for C-section deliveries in India, NFHS-4, 2015–16. It shows the ORs for the association between C-section and the background characteristics. Women of age-group 25–29 and 30–49 were 1.15 [95% CI: 1.118–1.196] and 1.37 [95% CI: 1.310–1.448] times more likely to undergo C-section as compared to women of age group 15–24. Women of rural areas were 9% [95% CI: 0.884–0.939] less likely to undergo C-section as compared to women of urban areas. The odds ratios were significantly higher among educated women compared to uneducated women. The women from poorer HHs (OR = 1.27; 95% CI: [1.211–1.348]), middle-income HHs (OR = 1.69; 95% CI: [1.610–1.789]), richer HHs (OR = 1.73; 95% CI: [1.643–1.834]) and richest HHs (OR = 1.56; 95% CI: [1.471–1.659]) were significantly more likely to go for C-section than those from poorest HHs. Religion, caste, birth order and CEB were significantly associated with C-section. As compared to underweight women, normal, overweight and obese women 1.27 [95% CI: 1.225–1.318], 2.16 [95% CI: 2.064–2.261] and 3.31 [95% CI: 3.104–3.547] times more likely to go for C-section. Size of the child at birth was also significant factors associated with C-section delivery. Women who go to a private health care facility for their delivery were 3.34 [95% CI: 3.252–3.438] times more likely to undergo C-section. Women who went for ANC 1–3 times and more than four times were 18% [95% CI: 1.115–1.259] and 84% [95% CI: 1.740–1.951] respectively, more likely to undergo C-section as compared to women who never had any ANC visit.
      Table 1 indicates Univariate, and Bivariate Moran's I for the dependent and independent variables. Moran's I value for Caesarean-section delivery is 0.693 (p < 0.001) which indicates that there is high spatial auto-correlation in Caesarean-section deliveries in districts of India. The value of Moran's I ranges from 0.440 (p < 0.001) for an urban place of residence to 0.685 (p < 0.001) for deliveries in private hospitals. The value of Bivariate Moran's I indicates the spatial dependence of C-section delivery on other dependent variables. The value of Bivariate Moran's I ranges from 0.089 (p < 0.001) for respondents among SC/ST categories to 0.503 (p < 0.001) for obese women.
      Table 1Univariate and Bivariate Moran's I for the dependent and independent variables.
      Source: Authors' calculations.
      VariablesUnivariate Moran's IBivariate Moran's I
      C-section (%)0.693*N.A
      Women aged 35 and above (%)0.676*−0.016*
      Age first birth 35 and above (%)0.518*0.215*
      Muslim (%)0.680*0.156*
      Delivery in Private facility (%)0.685*0.417*
      SC/ST (%)0.651*0.089*
      Multiple birth (%)0.0150.123*
      BMI (obesity) (%)0.504*0.503*
      No colostrum feeding (%)0.675*−0.208*
      Urban place of residence (%)0.440*0.292*
      Terminated the pregnancy (%)0.482*0.002
      Interpretation: Values of I range from −1 (indicating perfect dispersion) to +1 (perfect correlation). A zero value indicates a random spatial pattern.
      *P ≤ 0.05.
      N.A- Not Applicable.
      Table 2 inspects the regional determinants and influential factors affecting caesarean-section delivery among women aged 15–49 in 640 districts of India. After establishing the significant bivariate spatial association between the dependent and independent variables, spatial OLS model, the spatial lag model and the spatial error model was fitted. Spatial error model was the best fit model as AIC value was least and hence it was considered an appropriate model for the study. The value of Lambda is 0.790 (p < 0.001) which is highly significant and depicts that there is positive spatial autocorrelation among the regions of India having a high prevalence of caesarean-section deliveries. Age at first birth 35 and above, delivery in private facility, SC/ST respondents, multiple births, obesity and urban place of residence was significantly spatially associated with caesarean-section among women in districts of India. Obesity was most strongly related to caesarean-section delivery among women in India i.e. 10% points increase in obesity level would be significantly associated with 6.45% increase in caesarean-section delivery. Similarly, 10% points increase among deliveries in private facility was significantly associated with 3% point increase in caesarean-section delivery. The value of the lag coefficient from the spatial lag model suggested that a change in the caesarean-section delivery in a particular district may statistically lag the rate of caesarean-section delivery by 51.4% in the neighbouring districts.
      Table 2Spatial Regression models for C-section among women in India, NFHS-4, 2015-16.
      Source: Author's calculations
      VariablesSpatial OLSSpatial lagSpatial error
      Age at first birth (35+) (%)0.360* (0.114)0.394* (0.092)0.241* (0.096)
      Muslim (%)0.088* (0.016)0.050* (0.013)0.018 (0.018)
      Delivery in Private facility (%)0.231* (0.021)0.167* (0.018)0.304* (0.022)
      SC/ST (%)0.048 (0.028)0.027 (0.022)0.071* (0.027)
      Multiple birth (%)−0.122 (0.265)−0.348 (0.214)−0.458* (0.169)
      BMI (obesity) (%)1.148* (0.151)0.666* (0.125)0.645* (0.107)
      Urban place of residence (%)−0.009 (0.016)0.016 (0.013)0.051* (0.013)
      R square0.7060.8050.862
      adj. R square0.701
      AIC433741153963
      Rho0.514
      Lambda0.790*
      Regions640640640
      *P ≤ 0.05.
      Map 2 shows the bivariate LISA cluster maps indicating the spatial auto-correlation of C-section delivery with various explanatory variables. Map A indicates 53 hop-spot regions (Moran's I = 0.215, p < 0.001) depicting high regional dependence of C-section deliveries on women having age at first birth 35 and above which includes regions of Himachal Pradesh and Jammu & Kashmir in Northern India and parts of Maharashtra, Kerala, Andhra Pradesh, Karnataka and Tamil Nadu in Southern India. Map B shows 86 hot-spot regions (Moran's I = 0.417, p < 0.001) indicating high regional dependence of C-section deliveries on deliveries in private facilities which includes regions of Himachal Pradesh, West Bengal and a major part of southern India including Maharashtra. Map C shows 63 hop-spot regions (Moran's I = 0.089, p < 0.001) depicting high regional dependence of C-section deliveries on women belonging to SC/ST category which includes parts of Himachal Pradesh, West-Bengal, Andhra Pradesh, Karnataka, Tamil Nadu and Kerala. Map D indicates 52 hop-spot regions (Moran's I = 0.123, p < 0.001) depicting high regional dependence of C-section deliveries on women giving multiple births which includes parts of Jammu and Kashmir, Himachal Pradesh, West Bengal and major region of Southern India including Maharashtra. Map E shows 85 hot-spot regions (Moran's I = 0.503, p < 0.001) depicting high regional dependence of C-section deliveries on women having high BMI (obesity) which includes Jammu and Kashmir, Himachal Pradesh, West-Bengal, Maharashtra Andhra Pradesh, Karnataka, Tamil Nadu and Kerala. Map F indicates 65 hot-spot regions (Moran's I = 0.503, p < 0.001) depicting high regional dependence of Caesarean-section deliveries on women belonging to Urban areas which include Jammu and Kashmir, Himachal Pradesh, West-Bengal, Maharashtra Andhra Pradesh, Karnataka, Tamil Nadu and Kerala.
      Map 2
      Map 2Bivariate LISA maps showing the spatial clustering and outliers of different independent variables across the districts of India, 2015–16
      (A) Age at first birth
      (B) deliveries in private facilities
      (C) SC/ST category
      (D) multiple births
      (E) BMI (obesity)
      (F) Urban Place of Residence.

      2. Discussion

      In India, the population-based proportion of C-section greatly exceeds the threshold of 5–15% recommended by WHO.
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      C-section has increased over time with a wide heterogeneity in the incidence, and our findings are in line with many studies.
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      Women living in rural area are generally uneducated, lack of awareness, belongs to low socio-economic status, doesn't receive proper antenatal care or counselling for pregnancy. Moreover, hospitals located in urban areas often deal with pregnancy complications which include both urban as well as rural patients.
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      Study on rising trends of caesarean section (c-section): a bio-sociological effect.
      Mothers living in high SES, obesity, pregnancy resulting in multiple babies, high-risk birth weight, were found to be significantly associated with C-section. Previous evidence shows that older mothers are more likely to use healthcare services, to experience complications during pregnancy and delivery, and likely to have C-section delivery compared to younger ones even in the absence of complications.
      • Mishra U.S.
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      Delivery-related complications and determinants of caesarean section rates in India.
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      • Webster L.A.
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      Prevalence and determinants of caesarean section in Jamaica.
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      • Padmadas S.S.
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      • Rahman M.
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      • Diamond-Smith N.
      • Sudhinaraset M.
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      • Nazir S.
      Determinants of Cesarean Deliveries in Pakistan.
      • Radha K.
      • Prameela Devi G.
      • Manjula R.V.
      Study on rising trends of caesarean section (c-section): a bio-sociological effect.
      • Khanal V.
      • Karkee R.
      • Lee A.H.
      • Binns C.W.
      Adverse obstetric symptoms and rural–urban difference in cesarean delivery in Rupandehi district, western Nepal: a cohort study.
      • Singh P.
      • Hashmi G.
      • Swain P.K.
      High prevalence of cesarean section births in private sector health facilities-analysis of district level household survey-4 (DLHS-4) of India.
      Studies have also proven, the rural-urban, public-private, tribal/non-tribal gap also exist in the community.
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      In order to understand why these inequalities, exist, spatial analysis will be the most suitable technique to trap the insights in the society. Women going for more ANC check-ups might be facing some complications during pregnancy, due to which it is more likely to have C-section delivery; thus positive association has been found between ANC visit and C-section, reiterated by various studies also earlier.
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      Various government schemes such as Janani Shishu Suraksha Karyakram (JSSK), Rashtriya Swasthya Bima Yojana (RSBY), Mother-Child tracking system under the National Rural Health Mission (NRHM), and National Ambulance services has increased awareness about the health facilities as well as the strengthening of primary health centres (PHCs). It has helped to improve transport facilities and increase institutional deliveries all over India. Most of the south Indian states have already reported a high number of institutional deliveries with a positive correlation with C-section and has been well documented.
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      Due to the increase in health care coverage, the diagnosis has been better with ease of referral, increased the rate of C-section deliveries at tertiary-care hospitals also.
      Findings of other study revealed that C-section is often attributed to the moderately higher costs which are consistent with our results.
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      High out-of-pocket (OOP) expenditure for unnecessary C-section induced by physicians could also lead to financial strain for the underprivileged. Thus, physicians play a crucial role is such cases as they have opportunity to decide whether it should be vaginal delivery to C-section. The main factors that influence the use of C-section facility are possible financial exploitation, reflected from the economic status of the women, i.e. wealth index, and higher-educated women are more informed about the costs and benefit of the use of maternal healthcare services.
      • Kamal S.M.
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      ,
      • Kamal S.M.
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      Secondly, poorer household fails to pay for the surgery and the extra cost associated with C-section.
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      Additionally, rich are likely to be aware of their existing illnesses, and this knowledge may prompt them and doctors to consider CS. Sparse distribution of the necessary health facilities is another important reason.
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      In other countries, this phenomenon is called as ‘reverse equity’ where women with higher socioeconomic status (wealth index), presumably with less medical risks, have higher caesarean rates.
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      3. Conclusion

      Findings demonstrated that C-section rates have increased significantly in almost all the states of India (Table A1) in recent years and has reached an alarming level. Shifting of birth deliveries from the public to the private sector appears to be associated with an increase in the number of deliveries that occurred (Table A2). It indicates the need for growth of the health care delivery system and to encourage institutional deliveries in public sector in India. C-section have shown variations among the population across geographical locations of different socioeconomic status. Women in the south region reported a higher C-section than women in other areas. Our study found significant interactive associations between C-section with age, religion, place of residence, tribes, BMI and location of delivery (shown in regression Table A3). Other variables like the educational status of women, wealth, ANC, and OOPE were also significant in the regression table (Table A3) but were controlled while performing spatial analysis.

      3.1 Recommendations

      Although schemes like Janani Suraksha Yojana (JSY) and RSBY have a significant impact on poor women accepting institutional deliveries and improving financial risk protection respectively, these schemes seem to be biased towards prioritizing surgical procedures over normal deliveries, indicating a moneymaking process for the private healthcare providers.
      • Nandi S.
      • Dasgupta R.
      • Garg S.
      • Sinha D.
      • Sahu S.
      • Mahobe R.
      Uncovering coverage: utilisation of the universal health insurance scheme, Chhattisgarh by women in slums of Raipur.
      ,
      • Selvaraj S.
      • Karan A.K.
      Why publicly-financed health insurance schemes are ineffective in providing financial risk protection.
      Considering the current rising trend of institutional deliveries as a reason for the increase uptake of C-section in India, measures protecting the beneficiaries need to be put in place. Improvement through financial support (provision of maternity benefits) should be given to those below poverty line (BPL) to reduce out of pocket (OOP) expenditure.
      • Mohanty S.K.
      • Srivastava A.
      Out-of-pocket expenditure on institutional delivery in India.
      Delivering high-quality timely care and counselling measures throughout the gestation period as a measure to minimise C-sections is the responsibility of every midwife healthcare provider, is an effective way as suggested by professionals. Improving the quality of care component in public health institutions will play a significant role in drawing women's attention to seek maternal health care. C-section without medical indication should be discouraged amongst the beneficiaries and providers. There is an urgent need to monitor the deliveries in clinics and hospitals to find the right balance between the demand and provisioning of adequate and high quality care services. The government should inform practitioners and women of the unnecessary risks of non-medically justified C-sections. India has to face a “double burden” of providing C-sections to population that still have no access to it (because of poverty, remoteness or lack of facilities, etc.) and at the same time curbing an overuse which is the key challenge for the Indian healthcare system.
      Additional research is needed to examine the attitude of service providers in future. C-section deliveries have other serious implications on breastfeeding initiation, duration and difficulties in the first four months of postpartum and post-natal care need to be studied in future. It is also recommended to explore future trends in the magnitude of spatial inequalities in rural-urban tribal/non-tribal and public-private sector institutions. Rigorous in-depth investigations with routine monitoring and evaluation of emergency obstetric services should also be carried out to address the overuse of C-section and its effect on maternal and child health (MCH) outcomes.

      3.2 Strengths and limitations

      The major strength of this study is that it is based on one of the largest-scale surveys conducted in India covering the geographical regions at the district level. On the other hand, some limitations of the study are also noted. The data being cross-sectional in nature didn't allow making causal inferences about the association between ANC and delivery care and the risk factors. Various demographic, socioeconomic and cultural factors and costs of delivery services have been included in this analysis, however women's role in the decision-making process also likely to influence the delivery practices of women. The survey didn't cover evidence about accessibility (i.e., distance to a health facility) and the quality of health-care facility which might have influenced the use of health facility delivery. Nevertheless, we believe that the conclusions of our study can still be relevant and beneficial for programme planners and policy-makers not merely to encourage health facility-based deliveries but also to address the high rates of C-sections among married women in India.

      Author Contributions

      Conceived and designed the research paper: SS, and HC; analysed the data: SS, HC, and PC; Contributed agents/materials/analysis tools: PC, and HC; Wrote the manuscript: SS, HC, Refined the manuscript: HC, SS, PC, and JKS.

      Informed consent

      Informed consent was obtained from all individual participants included in the study.

      Ethical treatment of experimental subjects (Animal and human)

      Disclosure of potential conflicts of interest has been provided. This study was based on a large dataset that is publicly available on DHS website (https://dhsprogram.com/data/) conducted by the MOHFW and International Institute for Population Sciences (IIPS) in India with ethical standards being complied with including informed consent obtained from participants.

      India digital map

      The district level shape file of India was acquired from GitHub at https://github.com/datameet/maps/tree/master/Districts. The digital map has been used under the Creative Commons Attributions 2.5 India license. The shape file was created using the administrative atlas of Census 2011, India. And the map was projected in WGS 1984 UTM zone 43 N.

      Declaration of competing interest

      The authors declare no conflict of interest.

      Appendix.

      Table A1Percentage distribution of C-section delivery in India and states, NFHS-4, 2015-16
      States/UTsTotal2015–16
      2005–062015–16UrbanRural
      India8.517.228.312.9
      Andhra Pradesh27.540.148.437.1
      Arunachal Pradesh2.98.920.15.8
      Assam5.313.436.910.8
      Bihar3.16.213.95.4
      Chandigarhna22.6nana
      Chhattisgarh4.19.918.97.5
      NCT Delhi13.723.723.725.9
      Daman and Diuna15.814.917.7
      Dadra and Nagar Havelina16.226.78.7
      Goa25.731.433.527.7
      Gujarat8.918.427.812.0
      Haryana5.311.713.610.6
      Himachal Pradesh12.616.729.615.6
      Jammu and Kashmir13.533.153.126.9
      Jharkhand3.99.922.47.0
      Karnataka15.523.629.219.9
      Kerala30.125.837.134.6
      Madhya Pradesh3.58.619.15.1
      Maharashtra11.620.126.315.2
      Manipur9.021.133.015.2
      Meghalaya4.17.620.55.6
      Mizoram6.212.719.05.7
      Nagaland2.05.812.43.4
      Odisha5.113.824.112.1
      Punjab16.524.625.823.7
      Puducherryna33.630.939.8
      Rajasthan3.88.616.46.5
      Sikkim12.320.928.817.1
      Tamil Nadu20.334.136.132.3
      Telanganana58.063.253.4
      Tripura12.920.545.812.2
      Uttar Pradesh4.49.418.96.9
      Uttarakhand8.113.119.410.2
      West Bengal10.223.836.618.9
      Note: 1) na: data not available. 2) Telangana is a newly formed state, which was the part of Andhra Pradesh and hence CS rate of Andhra Pradesh up to 2005–06.
      UTs: Union Territories.
      Table A2Percentage of women undergoing C-section by Type of Health Facility by States, India, NFHS-4, 2015–16
      State/UTsPrivate Health FacilityPublic Health FacilityState/UTsPrivate Health FacilityPublic Health Facility
      India40.911.9Madhya Pradesh40.85.8
      Andhra Pradesh57.025.5Maharashtra33.113.1
      Arunachal Pradesh37.512.5Manipur46.222.6
      Assam53.312.9Meghalaya31.49.8
      Bihar31.02.6Mizoram30.012.3
      Chandigarh46.65.7Nagaland31.413.5
      NCT Delhi42.921.0Odisha53.711.5
      Goa51.319.9Punjab39.717.8
      Gujarat26.610.8Rajasthan23.26.1
      Haryana25.38.6Tamil Nadu51.326.3
      Himachal Pradesh44.416.4Telangana74.940.6
      Jammu and Kashmir75.535.1Tripura73.718.1
      Jharkhand39.54.6Uttar Pradesh31.34.7
      Karnataka40.316.9Uttarakhand36.49.3
      Kerala38.631.4West Bengal70.918.8
      UTs: Union Territories.
      Table A3Odds ratio of C-section delivery by selected background characteristics, India, NFHS-4, 2015-16
      Background VariablesO.R95% C.IBackground VariablesO.R95% C.I
      Age of motherCEB
      15–241[1,1]11[1,1]
      25–291.156***[1.118,1.196]21.057[0.948,1.179]
      30–491.378***[1.310,1.448]30.684***[0.565,0.827]
      Place of ResidenceMore than 30.345***[0.256,0.466]
      Urban1[1,1]BMI
      Rural0.912***[0.884,0.939]Underweight1[1,1]
      EducationNormal1.271***[1.225,1.318]
      No education1[1,1]Overweight2.160***[2.064,2.261]
      Primary1.128***[1.070,1.190]Obese3.318***[3.104,3.547]
      Secondary1.333***[1.278,1.390]
      Higher1.323***[1.253,1.396]
      CasteEver had a terminated pregnancy
      SC/ST1[1,1]No1[1,1]
      non SC/ST0.902***[0.871,0.934]Yes1.187***[1.147,1.228]
      ReligionSize of child at birth
      Hindu1[1,1]Large1[1,1]
      Muslim1.303***[1.256,1.352]Average0.818***[0.792,0.845]
      Others0.894***[0.856,0.934]Small0.834***[0.795,0.874]
      WealthMultiple birth
      Poorest1[1,1]Single birth1[1,1]
      Poorer1.278***[1.211,1.348]Multiple birth3.186***[2.921,3.475]
      Middle1.697***[1.610,1.789]Place of Delivery
      Richer1.736***[1.643,1.834]Public1[1,1]
      Richest1.562***[1.471,1.659]Private3.344***[3.252,3.438]
      Age of respondent at 1st birthOthers1[1,1]
      15–241[1,1]ANC Visit
      25–291.345***[1.291,1.401]No ANC1[1,1]
      30–492.011***[1.872,2.160]1–31.185***[1.115,1.259]
      Birth OrderFull ANC1.842***[1.740,1.951]
      11[1,1]OOPE
      20.740***[0.665,0.823]No expense1[1,1]
      30.669***[0.551,0.811]Up to 200000.877***[0.820,0.938]
      More than 30.731*[0.545,0.981]More than 200001.550***[1.465,1.640]
      Note: SC/ST- Scheduled Caste/Scheduled Tribes, CEB- Children ever born, BMI- Body Mass Index, PNC- Postnatal Care, ANC- Antenatal Care, OOPE- Out of pocket expenditure.
      *if p < 0.01 **if p < 0.05 and ***if p < 0.1.
      O.R: Odds Ratio C.I: Confidence Interval.

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      Biography

      Mr. Shobhit Srivastava is an M.Phil. Scholar of International Institute for Population Sciences, Mumbai-400088. His research interests include ageing issues, maternal and child health, reproductive and child health, fertility, and gender.
      Mr. Himanshu Chaurasia is working as Scientist-B (Statistician) at National Institute for Research in Reproductive Health, ICMR, Parel, Mumbai. His research interests include population and development; ageing issues and health; fertility; public health and mortality; maternal and child health, reproductive and child health, migration and urbanization.
      Mr. KH Jiten Kumar Singh is Scientist D at National Institute of Medical Statistics, New Delhi. His research interests include population and development; fertility; public health and mortality; maternal and child health, reproductive and child health.
      Ms. Pratishtha Chaudhary is an M.Phil. Scholar of International Institute for Population Sciences, Mumbai-400088. Her research interests include ageing issues, maternal and child health, reproductive and child health, fertility, and gender