Severe maternal morbidity and its associated factors: A cross-sectional study in Morang district, Nepal.

BACKGROUND: Understanding maternal morbidity and its determinants can help identify opportunities to prevent obstetric complications and improvements for maternal health. This study was conducted to determine the prevalence of severe maternal morbidity (SMM) and the associated factors.
METHODS: A hospital-based cross-sectional study was conducted at Koshi Hospital, Nepal, from January to March 2020. All women who met the inclusion criteria of age ≥18 years of age, Morang residents of Nepalese nationality, had received routine antenatal care, and given birth at Koshi Hospital were recruited consecutively. The World Health Organization criteria were used to identify the women with SMM. A multiple logistic regression analysis was performed. Overall, 346 women were recruited.
FINDINGS: The prevalence of SMM was 6.6%. Among the SMM cases, the most frequently occurring SMM conditions were hypertensive disorders (12, 56.5%), hemorrhagic disorders (6, 26.1%), and severe management indicators (8, 34.8%). Women with no or primary education (adjusted odds ratio: 0.10, 95% confidence interval: 0.01, 0.76) decreased the odds of SMM compared to secondary education.
CONCLUSION: The approximately 7% prevalence of SMM correlated with global studies. Maternal education was significantly associated with SMM. If referral hospitals were aware of the expected prevalence of potentially life-threatening maternal conditions, they could plan to avert future reproductive complications.

Introduction

Maternal mortality is a public health problem studied worldwide [1], but the existing research on maternal mortality represents only a fraction of the problem [2]. Globally, the maternal mortality ratio has declined by 38% between 2000 and 2017; the greatest decrease during this period was in Southern Asia, with a nearly 60% reduction in maternal mortality ratio [3]. Maternal near-miss (MNM) and severe maternal morbidity (SMM) are new strategic indicators of maternal health conditions [4]. The World Health Organization (WHO) adopted and defined MNM and SMM standard criteria in 2009 [5]. The purpose of developing these uniform criteria was to provide common ground for comparisons across countries [5, 6]. MNM refers to “a woman who nearly died but survived a complication that occurred during pregnancy, childbirth or within 42 days of termination of pregnancy” [5]. The WHO working group has recommended the use of the term MNM as it best reflects the severity of events. However “severe acute maternal morbidity” (SAMM) is also used for MNM [5]. The WHO uses clinical-, laboratory-, and management-based criteria to identify MNM [7].

If observed across a broad spectrum, women’s reproductive health starts from a healthy pregnancy, morbidity, severe morbidity, near miss, and ends at maternal death. SMM lies somewhere between these two spectra before near-miss [8, 9]. Severe maternal morbidities are less in severity than MNM [5]. SMM includes women who did not necessarily have a critical illness but suffered complications related to pregnancy, delivery, and puerperium [5]. The WHO defines SMM as “potentially life-threatening conditions during pregnancy, childbirth, or after the termination of pregnancy from which maternal near-miss cases would emerge” and is assessed based on the four standard conditions, which are (i) hemorrhagic disorders, (ii) hypertensive disorders, (iii) other systemic disorders, and (iv) severe management indicators [5]. The terms “maternal near miss” and “severe maternal morbidity” are used interchangeably in the literature, but SMM reflects a less severe condition than MNM [9, 10]. While both “SMM” and “potentially life-threatening conditions” are used, SMM will be applied in this study.

The extent of MNM has been studied widely [11]; however, limited studies are available on SMM. In Nepal, reported MNM prevalence ranged from 3.8 per 1000 live births in 2013 [12] to a maximum of 23.1 per 1000 deliveries in 2010 [13], while none are reported on SMM. Many studies, especially those in low-income countries, have used a modified version of the WHO near-miss approach, mainly due to its limited applicability in low-income settings, notably due to the laboratory- and management-based criteria [14, 15].

It is necessary to determine a relevant maternal morbidity measurement and investigate its associated factors to improve maternal healthcare services because maternal deaths are becoming rare events [10, 16, 17]. Furthermore, it may be too late for intervention if at-risk women are identified late in labor [18]. Studies on SMM determinants will add valuable information to identify opportunities for prevention and improvements of the quality of obstetric complications at an earlier stage [19]. The purpose of this study was to determine the prevalence of SMM and associated factors. The WHO-based SMM criteria [11] were used in this study.

Materials and methods

A hospital-based cross-sectional study was conducted at Koshi Hospital, Nepal, from January to March 2020. Morang district was chosen for its dense population, high patient flow, diversified ethnic composition, and mixed population of urban and rural areas. This facility was selected purposefully because Koshi Hospital alone covers more than 90% of the Morang district’s total deliveries (i.e., about 9000 deliveries per year) [20]. Koshi Hospital is located in an urban area in the Morang district and is a referral hospital.

The study population comprised women who gave birth in the Morang district, and the source population included all women who gave birth at Koshi Hospital. The eligible participants were women aged ≥18 years, Nepalese citizens residing in Morang district who had received routine antenatal care and had given birth at Koshi Hospital. Women more than 42 days postpartum were excluded from the study. Consecutive sampling was applied to recruit eligible participants based on the birth records at Koshi Hospital.

The sample size was calculated using Power and Sample Size Calculation software version 3.1.6 based on comparing two proportions. The proportion of SMM women without previous cesarean section experience was 13.4% [21], the proportion of SMM women with SMM was taken 28% based on expert opinion. The difference between women with and without SMM with previous cesarean section was estimated at 14.6%. The ratio of non-SMM to SMM was taken as 2:1. 95% confidence interval and 80% statistical power were used. Based on this information, the calculated sample size was 288, 96 respondents of women with SMM and 192 respondents without SMM. After considering a 20% non-response rate, the required sample size was 346.

The case report form (S1 and S2 Files) included sociodemographic information, previous obstetric history, and current obstetric conditions. Categorizations of sociodemographic variables were as follows. Ethnicity was categorized into Brahmin/Chhetri (the advantaged groups), Janajati (indigenous community), Dalits (regarded as untouchables), Muslim, and others (Marwadi), and Terai/Madhesi (native inhabitants of the flat southern region of Nepal) [22]. Religion was categorized into Hindu and Islam/others (Jain) [23]. Wealth quintiles divide the population into five quintiles (lowest, second, middle, fourth, and highest) based on the ownership of assets. The lowest quintile is the poorest population, and the highest quintile is the wealthiest population. In this study, five wealth quintiles were recategorized into lowest/second, middle, highest/fourth [23, 24]. Place of residence is an administrative division based on the population density, previous five years’ annual income, and other facilities available in the area [25]. In this study, the place of residence was categorized into the rural municipality and urban municipality. Education was categorized into no formal education/primary (1 to 5 grade), secondary (6 to 10 grade), and tertiary (11 grade and above). Occupation for women was categorized into housewife/agriculture and others (professional/managerial/self-employed) [23]. Occupation for a husband was categorized into professional/managerial/clerical, sales and services, unskilled manual/agriculture, and others [23]. Hospital records were reviewed, and face-to-face interviews were conducted. The SMM criterion was considered fulfilled if it was stated in the medical record. After childbirth, the medical records of women were retrieved retrospectively on the discharge day, to collect information on SMM conditions based on the standard WHO criteria.

The women were recruited consecutively until the required sample size was achieved. The participants were recruited daily at the postpartum ward and cabins when it was confirmed that the women had been discharged. The data were collected by a trained research assistant with an undergraduate nursing certificate supervised by the Principal Investigator (PI), a Nepalese Ph.D. candidate. After ensuring participants’ eligibility, the women were approached to enroll in the study and asked for their written informed consent. The participants’ sociodemographic characteristics and previous pregnancy history were collected via face-to-face interviews with women in a stable condition on discharge day. The criteria for the WHO SMM were checked from the medical discharge note. SMM was confirmed when a woman had at least one marker among postpartum hemorrhage, severe preeclampsia, eclampsia, sepsis or severe systemic infection, uterine rupture, or when one of the following interventions was performed: the use of blood products, laparotomy, or admission to the intensive care unit. The PI reconfirmed the data on SMM criteria.

The data were cleaned and analyzed using IBM SPSS Statistics version 26.0. The outcome variable was SMM status. The independent variables were sociodemographic variables, previous obstetric history, and current obstetric conditions. A descriptive analysis was used to determine the prevalence of SMM. The numerical variables were presented as means with standard deviations or medians with interquartile ranges. The categorical variables were presented as frequencies and percentages. A simple logistic regression analysis was performed, and all the clinically important variables or variables with p-values ≤0.30 were included in the multiple logistic exploratory regression analysis. Backward and forward methods were employed. Significant variables were analyzed for multicollinearity and interaction, and the Hosmer–Lemeshow goodness of fit test was used. The OR and 95% CI were calculated, and a p-value <0.05 was considered statistically significant.

Ethical approval was obtained from the Human Research Ethics Committee Universiti Sains Malaysia (USM/JEPeM/19060356) and the Nepal Health Research Council (Reg. no. 336/2019). The written consent of the women who agreed to participate in the study was taken before their enrolment. Permission was obtained from the hospital management to review the participants’ medical records.

Results

A total of 346 women were included in the present study. The prevalence of SMM was 6.6%. The most frequently occurring SMM conditions were hypertensive disorders (56.5%) and hemorrhagic disorders (26.1%). Eight (34.8%) women were identified as fulfilling the severe management indicators. One early neonatal death was recorded in this study. The morbidity conditions among the women overlapped, and in total, there were 23 women with SMM (Table 1).

Table 1

Morbidity conditions of the women with severe maternal morbidity (n = 23).

Characteristics	n (%)
Maternal hemorrhagic disorders	6 (26.1)
Postpartum hemorrhage	6 (100.0)
Maternal hypertensive disorders	13 (56.5)
Severe hypertension	11 (84.6)
Eclampsia	2 (15.4)
Maternal severe management indicators	8 (34.8)
Prolonged hospital stays (> 7 postpartum days)	6 (75.0)
Blood transfusion	2 (25.0)

The majority of study participants were housewives (91.0%) from the Hindu religion (90.2%) with secondary or tertiary level education (72.5%). Women in this study belonged to the highest or second-highest wealth quintile (59.8%), and the majority were from Terai/Madhesi ethnicity (48.9%). Participant’s husbands also had secondary or tertiary level education (79.5%), their main occupations were unskilled manual/agriculture (42.2%) followed by sales and services (37.3%), and the majority of them were non-smokers (90.2%). The details of sociodemographic and economic characteristics and previous and current obstetric conditions of the women with and without SMM are shown in Table 2. The proportion of births by cesarean section was higher among the SMM than non-SMM women (43.5% vs. 25.7%). Nearly half (47%) of the information for the variable hemoglobin level was missing, so this variable was removed in the subsequent analysis. However, it was worth to be noted that 32% of the participants had mild (24.3%) and moderate (3.8%) anemia.

Table 2

Sociodemographic characteristics and previous and current obstetric conditions of the participants with and without severe maternal morbidity (n = 346).

Variables	SMMa (n = 23)		non-SMMa (n = 323)
	Mean (SD)b	n (%)	Mean (SD)b	n (%)
Sociodemographic
Mother’s age (year)c	22 (20, 24)		22 (20, 25)
Age of marriage (year)	19.8 (2.23)		19.4 (2.38)
Duration of marriage (year)c	1 (1, 4)		3 (1, 5)
Ethnicity
Brahmin/Chhetri		5 (21.7)		34 (10.5)
Janajati		2 (8.7)		49 (15.2)
Dalits		2 (8.7)		51 (15.8)
Muslim		1 (4.3)		33 (10.2)
Terai/Madhesi		13 (56.5)		156 (48.3)
Religion
Hindu		22 (95.7)		290 (89.8)
Islam		1 (4.3)		33 (10.2)
Wealth quintile
Lowest/second		1 (4.4)		19 (5.8)
Middle		9 (39.1)		110 (34.1)
Highest/fourth		13 (56.5)		194 (60.1)
Place of residence
Rural Municipality		9 (39.1)		129 (39.9)
Urban Municipality		14 (60.9)		194 (60.1)
Mother’s education
No formal education/primary		1 (4.3)		94 (29.1)
Secondary		17 (73.9)		159 (49.2)
Tertiary		5 (21.7)		70 (21.7)
Father’s education
No formal education/primary		1 (4.3)		70 (21.7)
Secondary		14 (60.9)		173 (53.6)
Tertiary		8 (34.8)		80 (24.8)
Mother’s occupation
Housewife/agriculture		21 (91.3)		294 (91.0)
Professional/managerial/self employed		2 (8.7)		29 (9.0)
Father’s occupation
Professional/managerial/clerical		2 (8.7)		33 (10.2)
Sales and services		12 (52.2)		117 (36.2)
Unskilled manual/agriculture		8 (34.8)		138 (42.8)
Others		1 (4.3)		35 (10.8)
Father smoking habit
No		19 (82.6)		293 (90.7)
Yes		4 (17.4)		30 (9.3)
Previous obstetric history
Birth spacing (month)c	60 (29.7, 120)		36 (24, 60)
Parity
Nullipara		17 (73.9)		178 (55.1)
Multipara		6 (26.1)		145 (44.9)
Previous mode of birth
Nulliparous		17 (73.9)		178 (55.1)
Normal birth		4 (17.4)		123 (38.1)
Cesarean section		2 (8.7)		22 (6.8)
History of abortion
No		23 (100)		310 (96.0)
Yes		0 (0.0)		13 (4.0)
Current obstetric conditions Period of gestational (week)	39.0 (1.84)		39.0 (1.73)
Number of ANCd visits
4 visits		7 (30.4)		118 (36.5)
≤3 visits		6 (26.1)		119 (36.9)
≥5 visits		10 (43.5)		86 (26.6)
Pre-pregnancy BMIe (kg/m2)
Normal		19 (82.6)		244 (75.5)
Underweight		2 (8.7)		55 (17.1)
Overweight and obese		2 (8.7)		24 (7.4)
Mode of birth
Normal birth		13 (56.5)		240 (74.3)
Cesarean section		10 (43.5)		83 (25.7)

Note:

a severe maternal morbidity.

b standard deviation.

c median, interquartile range, skewed towards the right.

d antenatal care.

e body mass index.

There were 20 independent variables in this study. All the variables were analyzed using simple logistic regression to identify the factors associated with SMM (Table 3). Age of marriage, duration of marriage, mother’s education, father’s education, parity, previous mode of birth, mode of birth, and the number of ANC visits were the independent variables with p-value <0.3 that were analyzed in multivariate regression analysis. All independent variables that had shown significant association with SMM were tested for their collinear relationship. None of these variables were found correlated.

Table 3

Factors associated with severe maternal morbidity using simple logistic regression analysis (n = 346).

Variables	Crude ORa (95% CIb)	Wald statc (df)d	p-value
Sociodemographic
Mother’s age (year)	0.96 (0.85, 1.09)	0.33 (1)	0.565
Age of marriage (year)	1.07 (0.94, 1.30)	1.58 (1)	0.209
Duration of marriage (year)	0.92 (0.79, 1.07)	1.08 (1)	0.299
Ethnicity
Brahmin/Chhetri	1.76 (0.59, 5.28)	1.03 (1)	0.310
Janajati	0.49 0.10, 2.25)	0.84 (1)	0.358
Dalits	0.47 0.10, 2.15)	0.94 (1)	0.332
Muslim	0.36 0.04, 2.88)	0.92 (1)	0.338
Terai/Madhesi	1
Religion
Hindu	1
Islam	0.39 0.05, 3.06)	0.78 (1)	0.377
Wealth quintile
Lowest/second	0.78 0.09, 6.33)	0.05 (1)	0.821
Middle	1.22 0.50, 2.94)	0.19 (1)	0.657
Highest/fourth	1
Place of residence
Rural Municipality	1.03 0.43, 2.46)	0.00 (1)	0.939
Urban Municipality	1
Mother’s education
No formal education/primary	0.09 0.01, 0.76)	4.95 (1)	0.026
Secondary	1
Tertiary	0.69 0.24, 1.88)	0.58 (1)	0.445
Father’s education
No formal education/primary	0.18 0.02, 1.37)	2.75 (1)	0.097
Secondary	1
Tertiary	1.24 0.49, 3.06)	0.21(1)	0.648
Mother’s occupation
Housewife/agriculture	1
Professional/managerial/self-employed	0.97 0.21, 4.32)	0.00 (1)	0.963
Father’s occupation
Professional/managerial/clerical	1.04 0.21, 5.15)	0.00 (1)	0.956
Unskilled manual/agriculture	1
Sales and services	1.77 0.70, 4.47)	1.45 (1)	0.228
Others	0.49 0.06, 4.07)	0.43 (1)	0.511
Father smoking habit
No	0.48 0.15, 1.52)	1.53 (1)	0.216
Yes	1
Previous obstetric history
Birth spacing (month)	1.01 0.99, 1.03)	2.59 (1)	0.107
Parity
Nullipara	1
Multipara	0.43 0.17, 1.13)	2.94 (1)	0.086
Previous mode of birth
Normal birth	1
Cesarean section	2.79 0.48, 16.20)	1.31 (1)	0.251
Nulliparous	2.93 0.96, 8.94)	3.59 (1)	0.058
History of abortion
No	1
Yes	0.00 0.00, 0.00)	0.00 (1)	0.999
Current obstetric conditions Gestational weeks at birth (week)	1.01 0.79, 1.29)	0.00 (1)	0.923
Number of ANCe visits
4 visits	1
≤3 visits	0.85 0.28, 2.60)	0.08 (1)	0.776
≥5 visits	1.96 0.72, 5.35)	1.72 (1)	0.189
Pre-pregnancy BMIf (kg/m2)
Normal	1
Underweight	0.47 0.10, 2.06)	1.01 (1)	0.346
Overweight and obese	1.07 0.23, 4.87)	0.01 (1)	0.930
Mode of birth
Normal birth	1
Cesarean section	2.22 0.94, 5.26)	3.31 (1)	0.069

Note:

a odds ratio.

b confidence interval.

c Wald statistics.

d degree of freedom.

e antenatal care.

f body mass index.

The independent variables associated with SMM (p < 0.05) determined by multiple logistic exploratory regression analysis are shown in Table 4. The determinant found to be significantly associated with SMM was no formal and primary education (adjusted OR: 0.10, 95% CI: 0.01, 0.76). Women having no formal and primary education decreased the odds of SMM by 9 times than women with secondary education (Table 4). However, among the women with higher education, there was no significant difference in SMM status compared to women with secondary education.

Table 4

Factors associated with severe maternal morbidity using multiple logistic regression analysis (n = 346).

Variables	Adj. ORa (95% CIb)	Wald statc (dfd)	p-value
Maternal education
No formal education/primary	0.10 (0.01, 0.76)	4.94 (1)	0.026
Secondary	1
Tertiary	0.62 (0.21, 1.76)	0.80 (1)	0.370

Note:

a adjusted odds ratio.

b confidence interval.

c Wald statistics.

d degree of freedom.

Discussions

The overall SMM ratio was 66.5/1000 deliveries in the current study. Maternal no or primary education was significantly associated with SMM. The extent of SMM has been reported in limited studies, and they are generally reported together with MNM. A wide range of SMM rates have been reported: the lowest at 1.15% in China in 2013 [26] and the highest at 19.1% in Brazil in 2017 [27]. Studies conducted among high-risk pregnant women and women with type 1 diabetes mellitus in Brazil in 2019 reported the highest rates of SMM at 35.1% [28] and 37.3% [29], respectively. The reported MNM ratios in Nepal were 22.3/1000 deliveries in 2010 [13], 3.8/1000 live births in 2013 [12], and 32.5/1000 deliveries in 2016 [30]. According to the WHO definition, SMM is lower in severity than MNM, so the higher prevalence of SMM in this study is justifiable.

The highest estimates of MNM at 198/1000 live births and 120/1000 live births have been reported in sub-Saharan Africa and the Asia region, respectively [11]. The lowest estimates reported from the Asian region were 4.4/1000 pregnancies [31] and 2.2/1000 live births [32]. The weighted pooled prevalence of MNM worldwide estimated by a systematic review and meta-analysis in 2019 was 18.67/1000 live births [33]. The vast disparities in the prevalence of MNM between high- and low-income nations could be attributed to differences in healthcare systems, particularly maternity care, study populations, and diagnostic criteria and techniques [8]. These disparities can also be explained by an investigation of a single hospital, city, or province, all of which can yield different results within the same country [11].

Maternal hemorrhagic disorders [34-36] and maternal hypertensive disorders [21, 36, 37] are the leading causes of SMM in most studies. Similarly, hypertensive disorders and hemorrhagic disorders were associated with SMM in this study. Interestingly, the literature has repeatedly noticed that hypertensive disorders are more likely to be the leading cause of SMM [10, 35, 37]. In contrast, hemorrhagic disorders are the leading cause of MNM [10, 35, 37]. It suggests that hemorrhage can occur without warning, and delays in managing hemorrhage may lead to maternal death if appropriate obstetric care is not offered, unlike hypertension that is preventable. Lotufo et al. found that hypertension was the leading cause of hospital admissions and potentially life-threatening conditions in their study; however, hemorrhage was the main cause of MNM or even death [35]. Studies have also shown that the case fatality rate of obstetric hemorrhage is higher than that of hypertensive disorders [35, 38]. Hypertensive disorders were found to cause near-miss events but not maternal deaths in a study in Pakistan; however, hemorrhage was responsible for the higher frequency of near-miss events and maternal deaths [39]. In contrast, studies have found case fatality rates higher among women with hypertensive disorders followed by severe postpartum hemorrhage [40, 41]. The higher percentages of both hypertensive disorders and hemorrhagic disorders among women indicate some form of delay in managing obstetric complications by healthcare providers [42].

In the current study, women with secondary or higher education were at 8.9 times at higher odds of developing SMM than women with no or primary education. Similar to this study, maternal higher education was significantly associated with MNM in a case-control study in southeast Iran [43]. The WHO Global Survey on Maternal and Perinatal Health, which was conducted in 24 countries, found that, compared to women with more than 12 years of education, women with no education were at a 2.7-times higher risk and women with 1–6 years of education had twice the risk of maternal mortality [44]. In the secondary data analysis of a demographic health survey in Brazil, women with no or fundamental education had 2.18 times the odds of MNM [45]. The current study findings were not in agreement with most of those in the literature.

Previous studies have shown that utilization of maternal health services increases with higher maternal education [46]. They are more likely to come from a higher socioeconomic situation, have an increased degree of health concern, and have better healthcare access [47, 48]. Women with a higher level of education are more proactive in their maternal health-seeking behavior, such as arranging prenatal checks, seeking professional health care, and likely to choose to give birth in a setting with competent medical staff and well-equipped facilities [48, 49]. In line with this evidence, in the current study, women with higher education who regularly received ANC care from Koshi Hospital identified high-risk factors. They gave birth in the same hospital. Furthermore, a slightly higher percentage of women with high blood pressure (5.2% vs. 1.1%) had a secondary or higher education than lower educated women.

On the contrary, women with no formal education lack access to health information and have no or inadequate ANC visits, which influences their awareness of obstetric complications and access to better medical services [50, 51]. The percentage of homebirths in the Morang district was 38% in the year 2016 [23]. Additionally, women with no or up to primary education were also more likely to have homebirths and have incomplete ANC. Furthermore, women with a low socioeconomic position and lack of education are more likely to wait until an emergency to seek medical help [52]. Unfortunately, these women were left out of the study, which could be one of the reasons why women with less education have a lower risk of having SMM. Approximately 44% of the women with SMM in this study had undergone a cesarean section.

In contrast, several other studies indicated higher percentages, ranging from 58.4% to 85.8% [21, 26, 35], of women who had given birth via cesarean section among MNM cases. These cesarean sections had been conducted as a required urgent action to prevent complications [37]. Although cesarean section increased the odds of SMM, an association could not be established in this study. Notwithstanding, previous studies have found cesarean section significantly associated with a higher risk of SMM [21, 37].

Studies exploring SMM determinants have found that both nulliparous and multiparous women have the highest risk of SMM [53, 54]. However, parity alone has not been shown to have a consistent association with poor obstetric outcomes [55, 56]. Nulliparous mothers are at an increased risk of hypertension [57] and, if of adolescent age, are not physically capable of childbearing [36], may delay seeking early ANC or birthing services in the event of complications [58, 59], and are in a vulnerable position concerning making decisions for themselves. Grand multipara has been reported as an independent risk factor of gestational diabetes mellitus, antepartum hemorrhage, malpresentation, and postpartum hemorrhage [55, 60].

Studies have shown that parity may be confounded by maternal age [55, 56]. Women of advanced maternal age are likely to have comorbidities [58, 61], which leaves them with less physiological reserve to cope with pregnancy morbidities [62]. Being a mother of advanced age with chronic diseases may influence the gestational prognosis, increasing the chance of complications [10]. Accordingly, parity confounded with younger or advanced age increases the likelihood of SMM. However, similar to this study, studies did not find any significant associations between SMM and maternal age or parity [8, 63]. Although nulliparous women represented 56% of the women in this study, the proportions of women ≤19 and ≥35 years were small, limiting the possibility of drawing further conclusions.

Our study findings have paved the path for referral institutions to begin routine surveillance of SMM cases using WHO criteria derived from standard medical records. Because the standard WHO criteria were followed, our findings are comparable across countries. The current study had limitations that need to be considered, i.e., it was a single hospital-based study; therefore, the findings can be generalized only to the local context in similar demographic and hospital settings. Furthermore, because homebirths, which accounted for 38 percent of births in the Morang district, were not included in the study design, the actual prevalence of SMM is predicted to be greater.

Conclusions and recommendations

The prevalence of SMM in the current study was in line with that of other studies worldwide. Maternal lower education was associated with SMM. Women who receive routine antenatal checkups should be carefully monitored to, at a minimum, prevent hypertensive and preventable hemorrhage disorders, although postpartum hemorrhage is unpredictable. The study of SMM and its determinants can contribute to formulating strategies to prevent progression to near-miss cases and reduce maternal mortality. The study of potentially life-threatening maternal conditions can reduce future reproductive complications if health institutions know its estimate and are prepared in advance.

Case report form in English.

(PDF)

Click here for additional data file.

Case report form in Nepali.

(PDF)

Click here for additional data file.

Severe maternal morbidity data set.

(DTA)

Click here for additional data file.

10 Sep 2021

PONE-D-21-21068

Severe maternal morbidity and its associated factors: a cross-sectional study in Morang district, Nepal

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: No

**********

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Dear Authors,

I congratulate you on this study, the study has been elaborated nicely and manuscript is understandable the tables are elaborate and self explanatory. the discussion part needs to be build up a little more, especially the part where education was negatively correlated with Severe maternal mortality. The authors need to justify the findings why that is applicable for Nepal settings. the Authors need to write the recommendation of their findings and also propose the utlization of their research findings to make the paper acceptable.

Reviewer #2: PONE-D-21-21068

The authors had made an interesting attempt at exploring SMM and its associated factors among Nepalese women. However, there are serious concerns and flaws that need to be addressed.

I suspect ethical concern for this manuscript with regards to previously published article in PLoS One (Rajbanshi et al., 2020, 15(2), e0244072, PLoS ONE), as the ethical approval number for two different studies are same (USM/JEPeM/19060356) and NHRC (Reg. no. 336/2019). However, the methodology described is different including sample size, its calculation, and data collection and so on. Moreover, there is no mention of anything regarding this in this manuscript. This is an unfortunate issue as it then raises ethical questions.

Moreover, there are other major concerns in the technicality of this manuscript.

1. A single center study cannot generalize the data for an entire district.

2. The selection of study site (Morang district) has not been justified. Moreover, if it’s about total number of deliveries per annum, why the authors did not consider taking Thapathali Maternity Hospital of Kathmandu. Moreover, Morang itself is not the district with highest maternal morbidity and mortality in Nepal.

3. Sample size calculation has been done taking the data from Malaysia. Malaysian and Nepalese context is very different. Despite having data of SMM on similar population, for example, Indian women, authors have overlooked its validation of appropriateness in scientific sample size estimation.

4. The authors have mentioned that data was collected by trained research assistant. But, what was the basis? Who has trained them? Did they have prior similar experience?

5. Why history of abortion been taken as independent variable in Table 3, though it did not have data for category “No”?

6. The authors have not mentioned anything about which variables were included in multiple logistic regressions. Which method did they use? Moreover, it seems they have only introduced variables with p<0.05 in bivariate analysis, which is statistically incorrect.

7. Discussion need to be relooked. The authors need to consider studies in similar contexts such as India, Bangladesh etc to compare and contrast as the context in these countries is more or less same with Nepal.

8. Conclusion is not in line with study objective and findings.

Other minor concerns:

1. No explanation of results of table 3 in text. It’d hinder readers from understanding the findings clearly.

2. The logic behind clubbing secondary education with tertiary is not justifiable. Moreover, these level of education need to be defined contextually from a larger readers’ perspective.

3. It’s not enough to mention “no formal education….decreased the odds of SMM” in the abstract. Need to interpret the meaning of the value from a larger readers’ perspective.

4. The concluding remarks in the abstract contrasts with the findings presented in the abstract itself. “no formal education….decreased the odds of SMM” vs women with higher education more likely to utilize hospital referral….”. How come the authors have concluded that “birthing practice of women with lower education at the well-equipped hospital should increase”, which is in no line with the study objectives and the findings.

5. Why had the authors clubbed “Newar” with “Brahmin and Chhetri” in the Ethnicity, despite the fact that “Newar” itself comes under “Janajati”? This is not valid and logical.

6. What did the authors mean by professional category in occupation? They need to define it. Also, they need to justify regarding clubbing of professional with clerical under father’s occupation while analyzing the data to explore associations.

7. Authors need to check the interpretation of their results of table 4 in the text “…decreased odds by 0.11 times…” ?????

8. Check Mesh terms for keywords.

Reviewer #3: Dear author,

The research article seems excellent and wonderful. It would have been better if proper correction on introduction of abstract with proper word and clear language will be use. Other seems brilliant.

Reviewer #4: Dear authors ,

There are some comments on your manuscripts:

1) Line 34: Is "WHO criteria" an appropriate Keyword? please find other important key word rather than this.

2) Line 88-93:

a) You are aiming to calculate hospital based prevalence of SMM. But in sample size calculation you are using two proportion sample size calculation with the two group (with and without SMM). I think there is miss-match between your objective and sample size calculation. Could you please clarify this.

b) What is the basis for "The difference between women with and without SMM with previous cesarean section was estimated at 14.6%" sentence?

c) Specify power and confidence level that you have used for sample size calculation

d) As you have two proportion situation for sample size calculation, please specify sample size in each group.

3. Line 97 and 99: Please specify what others are in ethnicity and religion

4. Line 134. On what basis you have set cut off of p-value <0.3 for the selection of variables for multivariate logistic regression model.

5. What is the difference in the outcome of maternal education vs SMM in tabel3 and table 4. In table 4 you told it as a multivariate regression model but there is only one variables. Where are other variables ? Where are the variables that has p-value <0.3 in the univariate model? Please specify which variables have you adjusted to find the result on table 4.

6. You have checked for collinearity but you have not specified about this in the result section. Could you please specify that in the result section too.

7. You have mentioned that you used consecutive sampling. In a year there seems to be 9000 cases in the hospital. In your study duration it is around 2300 cases (rough). There might have been declined cases, incomplete cases etc during data collection. You have started with 346 study participants but Please specify all declined percentage along with the reasons for decline, non-response proportion, etc in the result section. This would be helpful to determine generalizability of the study findings.

8. You have mentioned limitations in the last paragraph of discussion. Please add strengths of your study

**********

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Reviewer #1: Yes: DEBLINA ROY

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: Bikram Adhikari

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15 Oct 2021

Reviewer #1:

Dear Authors,

I congratulate you on this study, the study has been elaborated nicely and manuscript is understandable the tables are elaborate and self-explanatory. The discussion part needs to be build up a little more, especially the part where education was negatively correlated with Severe maternal mortality. The authors need to justify the findings why that is applicable for Nepal settings. the Authors need to write the recommendation of their findings and also propose the utlization of their research findings to make the paper acceptable.

Authors response: In the abstract section, the text below was added.

“If referral hospitals were aware of the expected prevalence of potentially life-threatening maternal conditions, they can plan to avert future reproductive complications.”

The discussion section has been elaborated further as below

“Previous studies have shown, utilization of maternal health services increase with higher maternal education [46] as they are more likely to come from a higher socioeconomic situation, had an increased degree of health concerned, and had better access to health care [47, 48]. Women with a higher level of education are more proactive in their maternal health-seeking behavior, such as arranging prenatal checks, seeking professional health care, and likely to choose to give birth in a setting with competent medical staff and well-equipped facilities [48, 49]. In line with this evidence, in the current study, women with higher education who regularly received ANC care from Koshi Hospital identified with high-risk factors, they gave birth in the same hospital. Furthermore, a slightly higher percentage of women with high blood pressure (5.2% vs. 1.1%) had a secondary or higher education than lower educated women.

On the contrary, women with no formal education lack access to health information and have no or inadequate ANC visits, which influences their awareness of obstetric complications and access to better medical services [50, 51]. The percentage of homebirths in the Morang district was 38% in the year 2016 [23]. Additionally, women with no or up to primary education were also more likely to have homebirths and have incomplete ANC. Furthermore, women with a low socioeconomic position and lack education are more likely to wait until an emergency to seek medical help [52]. Unfortunately, these women were left out of the study, which could be one of the reasons why women with less education have a lower risk of having SMM.” (Pgs. 16-17, lines 26-286)

Reviewer #2: PONE-D-21-21068

The authors had made an interesting attempt at exploring SMM and its associated factors among Nepalese women. However, there are serious concerns and flaws that need to be addressed.

I suspect ethical concern for this manuscript with regards to previously published article in PLoS One (Rajbanshi et al., 2020, 15(2), e0244072, PLoS ONE), as the ethical approval number for two different studies are same (USM/JEPeM/19060356) and NHRC (Reg. no. 336/2019). However, the methodology described is different including sample size, its calculation, and data collection and so on. Moreover, there is no mention of anything regarding this in this manuscript. This is an unfortunate issue as it then raises ethical questions.

Authors response: Thank you. The previously submitted manuscript and the current manuscript submitted to PLoS One are part of the mixed-method study by the author Rajbanshi, S. for her Doctor of Philosophy thesis at Universiti Sains Malaysia (USM). Ethical approval was taken for this research from USM ethical board and Nepal Health Research Council, which has been mentioned in all submitted manuscripts for publications, in this and other journals. The current manuscript is of a different study design i.e. cross-sectional study. It was one of the phases involved in the research.

Moreover, there are other major concerns in the technicality of this manuscript.

1. A single center study cannot generalize the data for an entire district.

Authors response: Corrections made in the strengths and limitation sections as below.

“The current study had limitations that need to be taken into consideration, i.e., it was a single hospital-based study; therefore, the findings can be generalized only to the local context in similar demographic and hospital settings.” (Pg. 18, lines 314-318)

2. The selection of study site (Morang district) has not been justified. Moreover, if it’s about total number of deliveries per annum, why the authors did not consider taking Thapathali Maternity Hospital of Kathmandu. Moreover, Morang itself is not the district with highest maternal morbidity and mortality in Nepal.

Authors response: Corrections made in the materials and methods sections as below.

“Morang district was chosen for its dense population, high patient flow, diversified ethnic composition, and mixed population of urban and rural areas.” (Pg. 5, lines 88-89).

It was mentioned above that this study was part of a bigger study that required a mixed population of urban and rural areas where other aspects of maternal health were explored; therefore, although Thapathali Maternity Hospital had the highest number of births, Morang district was purposively selected.

3. Sample size calculation has been done taking the data from Malaysia. Malaysian and Nepalese context is very different. Despite having data of SMM on similar population, for example, Indian women, authors have overlooked its validation of appropriateness in scientific sample size estimation.

Authors response: Thank you for your comment. There were numerous studies on maternal near miss, which can be referred to in this study for sample size calculation. This research has utilized a study by Norhayati (2016) because it is recent and applies the same defining WHO criteria for severe maternal morbidity for its outcome.

4. The authors have mentioned that data was collected by trained research assistant. But, what was the basis? Who has trained them? Did they have prior similar experience?

Authors response: The research assistants were recently graduate nursing from Koshi Hospital. They did not have any experience in research and the utilization of the WHO criteria. They were trained by the Principal Researcher and monitored daily.

5. Why history of abortion been taken as independent variable in Table 3, though it did not have data for category “No”?

Authors response: During the literature review, few studies had shown that history of abortion was associated with maternal near miss and also severe maternal morbidity. Therefore, it was taken as one of the possible determinants for SMM in this study.

6. The authors have not mentioned anything about which variables were included in multiple logistic regressions. Which method did they use? Moreover, it seems they have only introduced variables with p<0.05 in bivariate analysis, which is statistically incorrect.

Authors response: The authors mentioned in the manuscript that those variables that had p-values lesser than 0.3 and clinically important variables were forwarded to multiple logistic regressions. The analysis process was mentioned clearly in the methods section as below. We have also added a sentence to clarify further the variables included.

“A simple logistic regression analysis was performed, and all the clinically important variables or variables with p-values ≤0.30 were included in the multiple logistic exploratory regression analysis. Backward and forward methods were employed. Significant variables were analyzed for multicollinearity and interaction, and the Hosmer–Lemeshow goodness of fit test was used. The OR and 95% CI were calculated, and a p-value <0.05 was considered statistically significant.” (Pg. 8, lines 148-153)

7. Discussion need to be relooked. The authors need to consider studies in similar contexts such as India, Bangladesh etc to compare and contrast as the context in these countries is more or less same with Nepal.

Authors response: The text below was added in the discussion section to make the findings comparable in a wider context.

“The reported MNM ratios in Nepal were 22.3/1000 deliveries in 2010 [13], 3.8/1000 live births in 2013 [12], and 32.5/1000 deliveries in 2016 [30]. According to the WHO definition, SMM is lower in severity than MNM, so the higher prevalence of SMM in this study is justifiable.” (Pg. 14, lines 216-219)

“The highest estimates of MNM at 198/1000 live births and 120/1000 live births have been reported in sub-Saharan Africa and the Asia region, respectively [11]. The lowest estimates reported from the Asian regions were 4.4/1000 pregnancies [31] and 2.2/1000 live births [32]. The weighted pooled prevalence of MNM worldwide estimated by a systematic review and meta-analysis in 2019 was 18.67/1000 live births [33]. The vast disparities in the prevalence of MNM between high- and low-income nations could be attributed to differences in healthcare systems, particularly maternity care, study populations, and diagnostic criteria and techniques [8]. These disparities can also be explained by an investigation of a single hospital, city, or province, all of which can yield different results within the same country [11].” (Pg. 14, lines 223-232)

8. Conclusion is not in line with study objective and findings.

Authors response: Conclusions in the abstract and the conclusion section was rewritten as below.

Abstract: “The approximately 7% prevalence of SMM correlated with global studies. Maternal education was significantly associated with SMM. If referral hospitals were aware of the expected prevalence of potentially life-threatening maternal conditions, they could plan to avert future reproductive complications.” (Pg. 2, lines 35-41)

Conclusion section: “The study of potentially life-threatening maternal conditions can reduce future reproductive complications if health institutions know its estimate and are prepared in advance.” (Pg. 18, lines 328-332)

Other minor concerns:

1. No explanation of results of table 3 in text. It’d hinder readers from understanding the findings clearly.

Authors response: The text below was added just above Table 3.

“Age of marriage, duration of marriage, mother’s education, father’s education, parity, previous mode of birth, mode of birth, and the number of ANC visits were the independent variables with p-value <0.3 that were analyzed in multivariate regression analysis.” (Pg. 11, line 187-190)

2. The logic behind clubbing secondary education with tertiary is not justifiable. Moreover, these level of education need to be defined contextually from a larger readers’ perspective.

Authors response: We have redefined the education variable and made necessary changes in Tables 2, 3, and 4. We have also included an explanation of the term in the methods and materials section as below.

“Education was categorized into no formal education/primary (1 to 5 grade), secondary (6 to 10 grade), and tertiary (11 grade and above).” (Pg. 7, lines 120-122)

3. It’s not enough to mention “no formal education….decreased the odds of SMM” in the abstract. Need to interpret the meaning of the value from a larger readers’ perspective.

Authors response: Corrections made as below

“Women having no formal and primary education decreased the odds of SMM by nine times than women with secondary education (Table 4). However, among the women with higher education, there was no significant difference in SMM status compared to women with secondary education.” (Pg. 13, lines 205-208)

The explanation of the term education variable was added in the methods and materials section as below.

“Education was categorized into no formal education/primary (1 to 5 grade), secondary (6 to 10 grade), and tertiary ( 11 grade and above).” (Pg. 7, lines 120-122)

4. The concluding remarks in the abstract contrasts with the findings presented in the abstract itself. “no formal education….decreased the odds of SMM” vs women with higher education more likely to utilize hospital referral….”. How come the authors have concluded that “birthing practice of women with lower education at the well-equipped hospital should increase”, which is in no line with the study objectives and the findings.

Authors response: Thank you for your comments. The conclusion was rewritten as below.

Abstract: “The approximately 7% prevalence of SMM correlated with global studies. Maternal education was significantly associated with SMM. If referral hospitals were aware of the expected prevalence of potentially life-threatening maternal conditions, they could plan to avert future reproductive complications.” (Pg. 2, lines 35-41)

Conclusion section: “The study of potentially life-threatening maternal conditions can reduce future reproductive complications if health institutions know its estimate and are prepared in advance.” (Pg. 18, lines 328-332)

5. Why had the authors clubbed “Newar” with “Brahmin and Chhetri” in the Ethnicity, despite the fact that “Newar” itself comes under “Janajati”? This is not valid and logical.

Authors response: Thank you for your critical review. The Newar ethnicity was combined together with Janajati, and reanalysis was done. Changes were made in Table 2 and 3.

6. What did the authors mean by professional category in occupation? They need to define it. Also, they need to justify regarding clubbing of professional with clerical under father’s occupation while analyzing the data to explore associations.

Authors response: The authors had taken the reference from the Demographic and Health Survey, which was also mentioned in the manuscript. The Professional category is very broad to mention in the manuscript and interested audience can refer to the reference. The reasons for grouping the professional and clerical occupations were that there were only three that belonged to clerical occupation. It cannot be grouped with unskilled manual as clerical were table work job; therefore it was grouped with the professional category.

7. Authors need to check the interpretation of their results of table 4 in the text “…decreased odds by 0.11 times…” ?????

Authors response: The interpretation was corrected as below.

“Women having no formal and primary education decreased the odds of SMM by nine times than women with secondary education (Table 4). However, among the women with higher education, there was no significant difference in SMM status compared to women with secondary education.” (Pg. 3, lines 205-208)

8. Check Mesh terms for keywords.

Authors response: The keyword “WHO criteria” was removed and replaced with “maternal health”.

Reviewer #3: Dear author,

The research article seems excellent and wonderful. It would have been better if proper correction on introduction of abstract with proper word and clear language will be use. Other seems brilliant.

Authors response: Thank you for your comments. The conclusion was rewritten as below.

Abstract: “The approximately 7% prevalence of SMM correlated with global studies. Maternal education was significantly associated with SMM. If referral hospitals were aware of the expected prevalence of potentially life-threatening maternal conditions, they could plan to avert future reproductive complications.” (Pg. 2, lines 35-41)

Conclusion section: “The study of potentially life-threatening maternal conditions can reduce future reproductive complications if health institutions know its estimate and are prepared in advance.” (Pg. 18, lines 328-332)

Reviewer #4: Dear authors ,

There are some comments on your manuscripts:

1) Line 34: Is "WHO criteria" an appropriate Keyword? please find other important key word rather than this.

Authors response: Thank you for your suggestion.

The keyword “WHO criteria” was removed and replaced with “maternal health”.

2) Line 88-93:

a) You are aiming to calculate hospital based prevalence of SMM. But in sample size calculation you are using two proportion sample size calculation with the two group (with and without SMM). I think there is miss-match between your objective and sample size calculation. Could you please clarify this.

Authors response: The study aimed to calculate both the prevalence of SMM and also its associated factors. Sample size calculated using a single proportion for SMM using the prevalence of SMM of 17.5% (Pacheco et al., 2014) was 267. It was smaller than the sample size calculated for the associated factors for SMM of 346. Therefore, comparing two proportion sample size calculation for the associated factors was utilized and shown in this manuscript.

b) What is the basis for "The difference between women with and without SMM with previous cesarean section was estimated at 14.6%" sentence?

Authors response: The text below was added to the manuscript.

“The proportion of SMM women without previous cesarean section experience was 13.4% [21], the proportion of SMM women with SMM was taken 28% based on expert opinion.” (Pg. 6, lines 100-101)

c) Specify power and confidence level that you have used for sample size calculation

Authors response: The text below was added to the manuscript.

“95% confidence interval and 80% statistical power was used.” (Pg. 6, line 104)

d) As you have two proportion situation for sample size calculation, please specify sample size in each group.

Authors response: Below line was added to the manuscript in the materials and methods section

“Based on this information, the calculated sample size was 288, 96 respondents of women with SMM and 192 respondents without SMM.” (Pg. 5, line 104-106)

3. Line 97 and 99: Please specify what others are in ethnicity and religion

Authors response: “Others” in ethnicity and religion were specified as Marwadi and Jain within the manuscript.

4. Line 134. On what basis you have set cut off of p-value <0.3 for the selection of variables for multivariate logistic regression model.

Authors response: The cut off of p-value of <0.3 was taken for screening purposes for selection of variables from simple to multiple logistic regression. It is aimed to obtain more variables for multiple logistic regression analysis. In multiple logistic regression analysis, the p-value of <0.05 is still taken to indicate the significance level.

5. What is the difference in the outcome of maternal education vs SMM in tabel3 and table 4. In table 4 you told it as a multivariate regression model but there is only one variables. Where are other variables ? Where are the variables that has p-value <0.3 in the univariate model? Please specify which variables have you adjusted to find the result on table 4.

Authors response: All the variables with p-value <0.3 were listed in the last column of Table 3. It is now added as texts just above Table 3 as well.

“Age of marriage, duration of marriage, mother’s education, father’s education, parity, previous mode of birth, mode of birth, and number of ANC visits were the independent variables with p-value <0.3 that were analyzed in multivariate regression analysis.” (Pg. 11, lines 187-190)

6. You have checked for collinearity but you have not specified about this in the result section. Could you please specify that in the result section too.

Authors response: Below lines were added to the result section

“All independent variables that had shown significant association with SMM were tested for their collinear relationship. None of these variables were found correlated.” (Pg. 11, lines 190-192)

7. You have mentioned that you used consecutive sampling. In a year there seems to be 9000 cases in the hospital. In your study duration it is around 2300 cases (rough). There might have been declined cases, incomplete cases etc during data collection. You have started with 346 study participants but Please specify all declined percentage along with the reasons for decline, non-response proportion, etc in the result section. This would be helpful to determine generalizability of the study findings.

Authors response: Those respondents listed in the discharge sheets and fulfill the eligibility criteria were approached for their consent for participation. This includes respondents of Morang district residents. All the eligible respondents approached agreed to participation.

8. You have mentioned limitations in the last paragraph of discussion. Please add strengths of your study

Authors response: The text below was added to the paragraph where limitations was mentioned.

“Our study findings have paved the path for referral institutions to begin routine surveillance of SMM cases using WHO criteria derived from standard medical records.” (Pg. 18, line 312-313)

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf.

Authors response: Manuscript contents were changed according to PLOS ONE’s style requirements.

2. Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information. If the original language is written in non-Latin characters, for example Amharic, Chinese, or Korean, please use a file format that ensures these characters are visible

Authors response: The Case Reporting Form both in English and Nepali language are submitted.

3. Please state whether you validated the questionnaire prior to testing on study participants. Please provide details regarding the validation group within the methods section.

Authors response: The Case Reporting Form (CRF) used in this study was burrowed from the World Health Organization SMM criteria. There were few questions regarding the demographic information of the study participants. The CRF sociodemographic information section was translated into the Nepali language. This section was pre-tested among 15 women from the same hospital to test for logical flow, content, and language comprehensibility. To identify the SMM cases, the hospital medical reports had to be referred to; therefore, they were not translated and used in English. Face-to-face training was provided to the research assistant by the Principal Investigator.

4. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

Authors response: The correct grant number is 311/PPSP/4404808

5. Thank you for stating the following in the Acknowledgments Section of your manuscript:

“This research was funded by the Universiti Sains Malaysia Graduate Development Incentive Grant 311/PPSP/4404808. The funder had no role in the study design, data collection, analysis, decision to publish, or manuscript preparation.”

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

“The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

Authors response: The funding-related text is removed from the manuscript. Please include in the Funding Statement “This research was funded by the Universiti Sains Malaysia Graduate Development Incentive Grant 311/PPSP/4404808. The funder had no role in the study design, data collection, analysis, decision to publish, or manuscript preparation.”

Submitted filename: 20210927 PLoS One response SMM.docx

Click here for additional data file.

23 Nov 2021

Severe maternal morbidity and its associated factors: a cross-sectional study in Morang district, Nepal

PONE-D-21-21068R1

Dear Dr. Noor,

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PLOS ONE

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20 Dec 2021

PONE-D-21-21068R1

Severe maternal morbidity and its associated factors: a cross-sectional study in Morang district, Nepal

Dear Dr. Norhayati:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Russell Kabir

Academic Editor

PLOS ONE