Why & Where Perinatal Deaths: Trends and Determinants in Pakistan

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Unfortunately, Pakistan faces poor pregnancy outcomes, which are significantly worse than those of many other low-resource countries worldwide. Realizing the set of targets under Sustainable Development Goal 3 demands a substantial reduction in perinatal mortality in Pakistan. Methods: SPSS data files from the Pakistan Maternal Mortality Survey (PMMS) 2019, with a sample of 136,226 households, were used. The PNMR was computed by urban and rural areas for the regions and provinces of Pakistan and for each category of the common risk factors (independent variables). We applied the chi-square test to determine whether the correlations between the PNMR and the independent variables were statistically significant. Finally, binary logistic regression analysis was conducted via SPSS version 19.0 to compute the adjusted odds ratio (AOR). Results: The PNMR for the entire sample was 70.1 per 1000 live births. The geographical differences were not statistically significant, with the exception of the Gilgit-Baltistan (GB) region, which had a lower PNMR. We found the lowest PNMR among the highest quintile, primigravida, having 3–5 pregnancies, mothers aged 24–35 years, with education 10 years or higher, who had adequate antenatal care and those who delivered at home without skilled birth attendants. Binary logistic regression analysis revealed a twofold greater risk among the lowest wealth quintile: 1.37 times greater among women aged >35 years and 1.5 times greater among women who had skilled birth attendance. After adjusting for socioeconomic and demographic variables, parity and antenatal care were found to have no association with perinatal deaths. Discussion & Conclusion: We found no increase in the risk of PNMR among women younger than 25 years and using antenatal care, whereas other studies reported a greater risk of PNMR among younger and adolescent mothers. Therefore, more robust primary studies are needed to determine the associations of the key variables with perinatal mortality in Pakistan. Perinatal mortality risk factors for perinatal mortality causation of perinatal deaths Introduction The perinatal mortality rate (PMNR) is a litmus test for assessing the availability and quality of healthcare for mothers and newborns. According to the World Health Organization (WHO), perinatal mortality is the death of a baby between 28 weeks of gestation and the first 7 days of life. 1 It may be calculated as the total number of perinatal deaths (still births + early neonatal deaths) divided by the total number of births (still births + live births)) or by the total number of live births only and is reflected as per 1000. 2 The day of birth is the most dangerous time for both mothers and newborns. 3 It has been estimated that each year, more than 1 million newborns die on the day they are born 4 , and 1·3 million stillbirths occur during labor and birth, 5 while 46% of maternal deaths also occur around the same time. 6 Globally, perinatal mortality accounts for three-quarters of neonatal mortality and is one of the major challenges for individuals under five years of age. It is a devastating pregnancy outcome for millions of families in low- and middle-income countries; 7 97% of stillbirths and 98% of neonatal deaths are reported in developing countries worldwide. 8 The PMNRs and intrapartum stillbirth rates are reportedly 5 and 14 times greater, respectively, in developing regions than in developed regions. 9 10 Pakistan faces the poorest pregnancy outcomes worldwide, which are significantly worse than those of many other low-resource countries worldwide. 11 Pakistan is among the top ten countries accounting for the greatest number of perinatal deaths worldwide; Pakistan ranks 2nd in terms of the number of stillbirths and 3rd in terms of the number of neonatal deaths. 12 The Pakistan Maternal Mortality Survey (PMMS) 2019 included information on stillbirths and neonatal deaths. An in-depth analysis of the data is needed to identify the causes and associated risk factors for perinatal deaths so that specific interventions and preventive measures can be devised and implemented. This study aimed to determine the associations of sociodemographic and service utilization factors with perinatal mortality in Pakistan. The findings will be used to guide national policies, programmes and further research. We used the questionnaires from the back of the PMMS 2019 final report to identify the variables of interest for this project. We created a binary dependent (outcome) variable called perinatal death by assigning a code of 1 to the pregnancies that resulted in fetal death after 28 weeks of gestation (reported as stillbirth), the infants who were born alive but died during the first seven days of birth (early neonatal deaths within 0–6 days after birth), and a code of 0 to all live births that survived beyond the first seven days of birth. The perinatal mortality rate (PNMR) was calculated via the following formula: $$\:PNMR=\:\frac{(Stillbirths+Early\:neonatal\:deaths)}{Total\:live\:births}\:\times\:1000$$ The PNMR was computed for the entire sample and separately for the urban and rural areas, as well as for the regions and provinces of Pakistan. The PNMR was then computed for each category of the common risk factors (independent variables), including the mother’s age at birth, parity, education, previous history of lost pregnancies, and socioeconomic status (wealth quintile). We applied the chi-square test to determine whether the correlations between the PNMR and the independent variables were statistically significant. Finally, binary logistic regression analysis was conducted, whereby perinatal death/survival (0,1) was the outcome variable and the independent variables listed above were included as independent variables and covariates. Using SPSS version 19.0, we computed adjusted odds ratios (AORs) reflecting the associations between perinatal death and each of the maternal and socioeconomic risk factors after controlling for the effects of all other independent variables. Data and methods We used the SPSS data files of the Pakistan Maternal Mortality Survey (PMMS) 2019, which are available from the Demographic and Health Surveys (DHS) website as well as from the National Institute of Population Studies (NIPS) in Islamabad. PMMS 2019 was a nationwide household survey that covered the four provinces and territories of Gilgit Baltistan (GB) and Azad Jammu & Kashmir (AJK). The PMMS was implemented by NIPS under the aegis of the Ministry of National Health Services, Regulations and Coordination (MoNHSR&C) from 15 January 2018 through 30 September 2019 1 . The PMMS is the first national survey conducted exclusively on maternal mortality in Pakistan. The sample included 136,226 households in the four provinces, AJK, and GB. Births and deaths in the last three years were recorded, and 1,177 deaths of women in the 15–49 years age group were investigated to identify maternal deaths. In a 10% subsample of households, 14,703 ever-married women aged 15–49 years were interviewed to identify complications of health service utilization during pregnancy, delivery, and postpartum in the last three years. Further details of the survey methodology are available in the PMMS 2019 final report 2 . Results The Pakistan Maternal Mortality Survey (PMMS) 2019 interviewed ever-married women of reproductive age (15–49 years) about their pregnancy, childbirth, and postpartum experiences in terms of any stillbirths and early neonatal death during the last three years. Among the 14,703 women who were interviewed, 8,822 reported having either a live birth, a stillbirth or an early neonatal death during the past three years. Among the total respondents, 93.2% (8224) reported having a live birth, 3.3% (293) reported having a stillbirth, and 3.5% (305) reported having a neonatal death. The PNMR for the entire sample was 70.1 per 1000 live births, which was significantly higher than the PNMR reported in the last Pakistan DHS (2017–18), which was 57 per 1000 live births. There was no difference in the PNMR between urban and rural areas (Table 1 ). Table 1 PNMR estimated for the entire national sample and urban/rural areas. PNMR/1000 live births Pakistan (all regions and provinces) Pakistan (Urban) Pakistan (Rural) 70.1 70.5 69.9 The differences between provinces and regions in the PNMR were not statistically significant, with the exception of the Gilgit-Baltistan (GB) region, where the estimated PNMR was significantly lower than that of the provinces (Table 2 ). However, among the four provinces, the estimated PNMR was the highest in Sindh and the lowest in KP. Table 2 PNMR by province/region. Province/Region PNMR/1000 live births Azad Jammu & Kashmir (AJK) region Gilgit-Baltistan (GB) region Balochistan province Khyber Pakhtunkhwa (KP) province Sindh province Punjab province 64.6 47.3* 79.9 63.7 87.7 67.1 *P < 0.05 (Chi-square test) The PNMR estimated by the wealth quintiles 3 showed a trend of being the lowest in the highest wealth quintile (the richest 20% of households in the sample) and highest in the lowest wealth quintile (the poorest 20% of households in the sample). The differences were statistically significant (P < 0.05). Table 3 PNMR by wealth quintile (entire sample). Risk Factor PNMR/1000 live births Wealth Quintile* : Richest (highest quintile - Q-5) Fourth quintile (Q-4) Middle quintile (Q-3) Second quintile (Q-2) Poorest (lowest quintile - Q-1) 45.4 63.0 67.7 70.6 93.7 *P < 0.05 (Chi-square test) The estimated PNMR varied significantly according to the sociodemographic characteristics of the mothers (Table 4 ): The PNMR was the lowest among mothers whose age at pregnancy was 25–34 years, compared with both younger women (< 25 years) and older women ( ≥ 35 years). The PNMR was approximately 20% lower among women who received adequate antenatal care (at least four visits to a skilled healthcare provider, with the first visit being in the first trimester) than among women who did not receive adequate antenatal care. The differences in the PNMR by parity followed the same pattern as those by age at pregnancy: the PNMR was the lowest among women with 3–5 live births and highest among women with six or more live births. This pattern did not persist when the PNMR was computed by gravidity, whereby the PNMR was the lowest among the primigravid women and the highest among women with six or more pregnancies. The variation in the PNMR by mother’s education level followed the same pattern as that observed in the socioeconomic level (wealth quintiles); the PNMR was significantly lower among women in the 10th grade of schooling or above, whereas it was the highest among women with no schooling at all. Finally, the PNMR was greater among births occurring in a health facility (due to selective referral of high-risk pregnancies to health facilities) than among births occurring at home. However, this difference was not statistically significant. Table 4 PNMR according to selected maternal and sociodemographic risk factors Risk Factor PNMR/1000 live births Mother’s age at pregnancy* : < 25 years 25–34 years 35 + years 82.1 59.5 82.6 Antenatal care 4 received* : No Yes* 72.7 58.4 Parity* : 1–2 prior live births 3–5 6+ 65.3 54.3 79.5 Gravidity (number or pregnancies)* : Nulligravida 1–5 prior pregnancies 6 + prior pregnancies 58.2 65.8 98.6 Mother’s education* : 10th grade or higher 0–9 years of schooling No schooling 46.9 63.5 83.6 Delivery in a health facility : No Yes 65.6 72.3 *P < 0.05 (Chi-square test) Table 5 presents the results of the binary logistic regression analysis showing adjusted odds ratios for selected socioeconomic and demographic variables. The risk of a pregnancy ending in perinatal death (stillbirth or early neonatal death within 0–6 days after birth) was approximately twice that of the poorest wealth quintile compared with the richest wealth quintile (the reference category) (P < 0.001). This result was obtained after controlling for the effects of urban/rural residence, the mother’s age at birth, parity, the mother’s schooling, antenatal care received during pregnancy and delivery by skilled birth attendants. Mothers whose age at pregnancy was ≥ 35 years were at a slightly greater risk of perinatal death than mothers who were in the 25–34 years age group (reference category). The adjusted odds ratio was 1.37. On the other hand, mothers in the youngest age group (< 25 years) at pregnancy were not at greater risk than those in the reference category were (Table 5 ). After adjusting for the socioeconomic and demographic variables listed above, it was found that parity and antenatal care had no role in the causation of perinatal death, as the adjusted odds ratios for these risk factors were not statistically significant (Table 5 ). Women who delivered under care of a skilled birth attendant were at approximately 1.5 times greater risk of having perinatal death than women who did not have their baby delivered by a skilled birth attendant. This reflects the risk of selective referral of high-risk pregnancies to health facilities for delivery, and this risk persists even after adjusting for other socioeconomic and demographic variables (Table 5 ). Table 5 Adjusted odds ratios (AORs) depicting the risk of perinatal death according to selected sociodemographic risk factors. Risk Factor AOR 5 95% CI of AOR P value Wealth Quintile : Lowest Second Middle Fourth Highest (Ref.) 2.10 1.47 1.23 1.29 - 1.40–3.12 1.10–2.21 0.86–1.78 0.90–1.83 < 0.001 0.04 0.26 0.17 Parity : 1–2 3–5 6+ (Ref.) 1.18 0.88 - 0.87–1.61 0.68–1.14 0.28 0.34 Mother’s age at pregnancy : < 25 years 25–34 years (Ref.) ≥ 35 years 1.03 - 1.37 0.82–1.31 - 1.07–1 .74 0.76 - 0.01 Mother’s schooling : No schooling 0–9 years of schooling 10 grade or higher (Ref.) 1.63 1.35 1.19–2.21 0.99–1.83 0.002 0.057 Adequate antenatal care received : Yes No (Ref.) 0.93 0.70–1.21 0.58 Delivery conducted by skilled birth attendant : Yes No (Ref.) 1.52 1.24–1.87 < 0.001 Discussion and conclusions In this study, we found that the perinatal mortality rate (PNMR) was not significantly different among the four provinces and two regions except that the Gilgit-Baltistan region had the lowest PNMR in the country. It was found to be lowest among primigravida pregnancies and highest among women with 6 or more pregnancies. The overall odds ratios in this study demonstrated the associations of perinatal mortality with younger and older women, low-level or no maternal education and the lowest wealth quintile. However, perinatal mortality was not influenced by parity or antenatal care after adjustments were made for key socioeconomic and demographic variables. Women who delivered at facilities with skilled birth attendants were at a greater risk of perinatal death than those who delivered at home without skilled birth attendants. This is most likely due to the preponderance of complicated delivery cases being managed at facilities by skilled birth attendants. Similar findings have also been reported in other studies. 18 Among the sociodemographic factors, maternal age ≥ 35 years was associated with a greater risk of perinatal mortality than the reference range of 25–34 years. Our study revealed no increase in the risk of PNMR among women aged < 25 years, whereas some studies have reported a greater incidence of perinatal mortality among mothers aged < 20 years. 19 , 20 , 21 Other studies have reported that women with high parity are at greater risk of perinatal mortality than women with low parity. 22 , 23 , 24 , 25 We found a 20% lower PNMR among women who received adequate antenatal care (at least four visits to a skilled healthcare provider, with the first visit being in the first trimester) than women who did not receive adequate antenatal care. However, the multivariate analysis revealed no role of antenatal care in reducing the risk of perinatal mortality. In contrast, evidence shows that women with at least one ANC visit experience 58–66% lower perinatal mortality. 26 The use of ANC visits provides an opportunity for mothers to receive health education and make them aware of danger signs to support the decision to seek healthcare at the right time. The low levels of maternal education and belonging to the lower wealth quintile may also contribute to the low utilization of ANC visits. 27 , 28 , 29 Berhan et al reported similar results to ours in that no or low maternal education is associated with a higher PNMR. 15, 30 , 31 , 32 However, they also reported no association of the PNMR with the household wealth quintile, which is in contrast to the findings of our study and other studies where the PNMR is the highest among women from the lowest wealth quintile. 33 , 34 , 35 Several limitations need to be recognized in the analysis or interpretation of these results. By design, our study data were collected for five years preceding the survey, which increases the chance of recall bias. This number may be higher in uneducated respondents from rural areas, which leads to underreported perinatal deaths from rural areas. The majority of perinatal deaths in developing countries remain unaccounted for and undocumented due to suboptimal reporting and a relatively high prevalence of home births. 23, 36 , 37 A survey was conducted before the COVID-19 pandemic. However, the disruption in essential healthcare services was reversed after the early lockdown measures were implemented, and we believe that there have been no major changes in health service provision and that these results are still relevant to the current status. In conclusion, the findings did not demonstrate a strong association of perinatal mortality with several key selected variables, such as adequate use of ANC and skilled birth attendance. Therefore, more robust primary studies are needed to determine the true associations of these key variables with perinatal mortality in the country. Declarations Author Contribution F.M, E.T. and Q.U. conceived the manuscript.F.M. conducted the statistical analysis and Q.U. drafted the results.F. M. & Q.U. prepared the first draft, S.N, E. T. A. S, I. A and S.A. reviewed and provide technical inputs. Acknowledgement We acknowledge the researchers and supporters of Pakistan Maternal Mortality Survey 2019. Data Availability Data is provided within the manuscript. References World Health Organization (2016) Child Health: Health Topics Geneva. USAID. Measure evaluation population and reproductive health, perinatal mortality rate. https://www.measureevaluation.org/prh/rh_indicators/womens-health/nb/perinatal-mortality-ratepmrandreproductivehealth . Accessed 19 April 2022 Getiye, Y and Fantahun M (2017) Factors associated with perinatal mortality among public health deliveries in Addis Ababa, Ethiopia, an unmatched case control study. BMC Pregnancy and Childbirth 17:245 DOI 10.1186/s12884-017-1420-7 Baqui AH, Mitra DK, Begum N, et al (2016) Neonatal mortality within 24 hours of birth in six low- and lower-middle-income countries. Bull World Health Organ 94: 752–8b. 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Reprod Health 17(Suppl 3):190 https://doi.org/10.1186/s12978-020-01023-5 Lawn JE, et al (2016) Stillbirths: rates, risk factors, and acceleration toward 2030. Lancet 387: 587–603 Published Online January 18, 2016. http://dx.doi.org/10.1016/S0140-6736(15)00837-5 Funding for the PMMS was provided by the United States Agency for International Development (USAID); the United Nations Population Fund (UNFPA); Foreign, Commonwealth & Development Office (FCDO-UK); and the Bill and Melinda Gates Foundation (BMGF). Technical support was provided by Demographic and Health Surveys (DHS) Program (ICF-USA). National Institute of Population Studies (NIPS) Pakistan and ICF-USA. Pakistan Maternal Mortality Survey 2019. Islamabad Pakistan and Rockville, MD, USA. Wealth quintiles are computed in PMMS 2019 on the basis of the total value of the assets owned by the households, including car/motorcycle, television, radio, mobile phones, etc. Four or more visits to a skilled healthcare provider, the first visit being in the first trimester. Adjusted for all the variables shown in this table and for urban/rural residence. Poeran J, Borsboom GJ, de Graaf JP, Birnie E, Steegers EA, Bonsel GJ (2014) Population Attributable Risks of Patient, Child and Organizational Risk Factors for Perinatal Mortality in Hospital Births. Matern Child Health J 19(4):764–75. doi: 10.1007/s10995-014-1562-4 . Jolly MC, Sebire N, Robinson HS, Regan L (2000) Obstetric of pregnancy in women less than 18 years old. Obstet Gynecol 96:962–966. doi: 10.1016/s0029-7844(00)01075-9 . Karabulut A, Ozkan S, Bozkurt AI, Karahan T, Kayan S (2013) Perinatal outcomes and risk factors in adolescent and advanced age pregnancies: comparison with normal reproductive age women. 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Int J Gynecol Obstet 106(1):85–88. doi: 10.1016/j.ijgo.2009.04.008 Footnotes [1] Funding for the PMMS was provided by the United States Agency for International Development (USAID); the United Nations Population Fund (UNFPA); Foreign, Commonwealth & Development Office (FCDO-UK); and the Bill and Melinda Gates Foundation (BMGF). Technical support was provided by Demographic and Health Surveys (DHS) Program (ICF-USA). [2] National Institute of Population Studies (NIPS) Pakistan and ICF-USA. Pakistan Maternal Mortality Survey 2019. Islamabad Pakistan and Rockville, MD, USA. [3] Wealth quintiles are computed in PMMS 2019 on the basis of the total value of the assets owned by the households, including car/motorcycle, television, radio, mobile phones, etc. [4] Four or more visits to a skilled healthcare provider, the first visit being in the first trimester. [5] Adjusted for all the variables shown in this table and for urban/rural residence. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 08 Jan, 2026 Read the published version in Maternal Health, Neonatology and Perinatology → Version 1 posted Editorial decision: Revision requested 18 Oct, 2025 Reviews received at journal 08 Oct, 2025 Reviews received at journal 08 Oct, 2025 Reviewers agreed at journal 08 Oct, 2025 Reviewers agreed at journal 06 Oct, 2025 Reviewers agreed at journal 05 Oct, 2025 Reviewers invited by journal 05 Oct, 2025 Editor assigned by journal 28 Jul, 2025 Submission checks completed at journal 28 Jul, 2025 First submitted to journal 28 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Islamabad","correspondingAuthor":false,"prefix":"","firstName":"Sayema","middleName":"","lastName":"Awais","suffix":""},{"id":530152199,"identity":"e7f1dad0-6eb3-4ec9-9166-853ec17b4ffa","order_by":6,"name":"Farid Midhet","email":"","orcid":"","institution":"Health Services Academy","correspondingAuthor":false,"prefix":"","firstName":"Farid","middleName":"","lastName":"Midhet","suffix":""}],"badges":[],"createdAt":"2025-07-28 08:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7231551/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7231551/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40748-025-00246-3","type":"published","date":"2026-01-08T15:57:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93695589,"identity":"1f24699b-92d6-443c-be7e-fd23a7f077cf","added_by":"auto","created_at":"2025-10-16 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14:40:36","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":60380,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7231551/v1/ffd5458edf1dbd6521301974.html"},{"id":100069265,"identity":"00fa79ab-f46f-4e3b-afa1-e4d322b4acea","added_by":"auto","created_at":"2026-01-12 16:12:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":527620,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7231551/v1/f68e946b-bb26-4511-8444-881303fdf8e6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eWhy \u0026amp; Where Perinatal Deaths: Trends and Determinants in Pakistan\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe perinatal mortality rate (PMNR) is a litmus test for assessing the availability and quality of healthcare for mothers and newborns. According to the World Health Organization (WHO), perinatal mortality is the death of a baby between 28 weeks of gestation and the first 7 days of life.\u003csup\u003e1\u003c/sup\u003e It may be calculated as the total number of perinatal deaths (still births + early neonatal deaths) divided by the total number of births (still births + live births)) or by the total number of live births only and is reflected as per 1000.\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe day of birth is the most dangerous time for both mothers and newborns.\u003csup\u003e3\u003c/sup\u003e It has been estimated that each year, more than 1\u0026nbsp;million newborns die on the day they are born\u003csup\u003e4\u003c/sup\u003e, and 1·3\u0026nbsp;million stillbirths occur during labor and birth,\u003csup\u003e5\u003c/sup\u003e while 46% of maternal deaths also occur around the same time.\u003csup\u003e6\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eGlobally, perinatal mortality accounts for three-quarters of neonatal mortality and is one of the major challenges for individuals under five years of age. It is a devastating pregnancy outcome for millions of families in low- and middle-income countries;\u003csup\u003e7\u003c/sup\u003e 97% of stillbirths and 98% of neonatal deaths are reported in developing countries worldwide.\u003csup\u003e8\u003c/sup\u003e The PMNRs and intrapartum stillbirth rates are reportedly 5 and 14 times greater, respectively, in developing regions than in developed regions.\u003csup\u003e9\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e10\u003c/sup\u003ePakistan faces the poorest pregnancy outcomes worldwide, which are significantly worse than those of many other low-resource countries worldwide.\u003csup\u003e11\u003c/sup\u003e Pakistan is among the top ten countries accounting for the greatest number of perinatal deaths worldwide; Pakistan ranks 2nd in terms of the number of stillbirths and 3rd in terms of the number of neonatal deaths.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe Pakistan Maternal Mortality Survey (PMMS) 2019 included information on stillbirths and neonatal deaths. An in-depth analysis of the data is needed to identify the causes and associated risk factors for perinatal deaths so that specific interventions and preventive measures can be devised and implemented. This study aimed to determine the associations of sociodemographic and service utilization factors with perinatal mortality in Pakistan. The findings will be used to guide national policies, programmes and further research.\u003c/p\u003e\u003cp\u003eWe used the questionnaires from the back of the PMMS 2019 final report to identify the variables of interest for this project. We created a binary dependent (outcome) variable called perinatal death by assigning a code of 1 to the pregnancies that resulted in fetal death after 28 weeks of gestation (reported as stillbirth), the infants who were born alive but died during the first seven days of birth (early neonatal deaths within 0–6 days after birth), and a code of 0 to all live births that survived beyond the first seven days of birth. The perinatal mortality rate (PNMR) was calculated via the following formula:\u003c/p\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:PNMR=\\:\\frac{(Stillbirths+Early\\:neonatal\\:deaths)}{Total\\:live\\:births}\\:\\times\\:1000$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe PNMR was computed for the entire sample and separately for the urban and rural areas, as well as for the regions and provinces of Pakistan. The PNMR was then computed for each category of the common risk factors (independent variables), including the mother’s age at birth, parity, education, previous history of lost pregnancies, and socioeconomic status (wealth quintile). We applied the chi-square test to determine whether the correlations between the PNMR and the independent variables were statistically significant. Finally, binary logistic regression analysis was conducted, whereby perinatal death/survival (0,1) was the outcome variable and the independent variables listed above were included as independent variables and covariates. Using SPSS version 19.0, we computed adjusted odds ratios (AORs) reflecting the associations between perinatal death and each of the maternal and socioeconomic risk factors after controlling for the effects of all other independent variables.\u003c/p\u003e"},{"header":"Data and methods","content":"\u003cp\u003eWe used the SPSS data files of the Pakistan Maternal Mortality Survey (PMMS) 2019, which are available from the Demographic and Health Surveys (DHS) website as well as from the National Institute of Population Studies (NIPS) in Islamabad. PMMS 2019 was a nationwide household survey that covered the four provinces and territories of Gilgit Baltistan (GB) and Azad Jammu \u0026amp; Kashmir (AJK).\u003c/p\u003e\u003cp\u003eThe PMMS was implemented by NIPS under the aegis of the Ministry of National Health Services, Regulations and Coordination (MoNHSR\u0026amp;C) from 15 January 2018 through 30 September 2019\u003csup\u003e1\u003c/sup\u003e. The PMMS is the first national survey conducted exclusively on maternal mortality in Pakistan. The sample included 136,226 households in the four provinces, AJK, and GB. Births and deaths in the last three years were recorded, and 1,177 deaths of women in the 15–49 years age group were investigated to identify maternal deaths. In a 10% subsample of households, 14,703 ever-married women aged 15–49 years were interviewed to identify complications of health service utilization during pregnancy, delivery, and postpartum in the last three years. Further details of the survey methodology are available in the PMMS 2019 final report\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe\u003c/strong\u003e Pakistan Maternal Mortality Survey (PMMS) 2019 interviewed ever-married women of reproductive age (15\u0026ndash;49 years) about their pregnancy, childbirth, and postpartum experiences in terms of any stillbirths and early neonatal death during the last three years. Among the 14,703 women who were interviewed, 8,822 reported having either a live birth, a stillbirth or an early neonatal death during the past three years. Among the total respondents, 93.2% (8224) reported having a live birth, 3.3% (293) reported having a stillbirth, and 3.5% (305) reported having a neonatal death.\u003c/p\u003e\n\u003cp\u003eThe PNMR for the entire sample was 70.1 per 1000 live births, which was significantly higher than the PNMR reported in the last Pakistan DHS (2017\u0026ndash;18), which was 57 per 1000 live births. There was no difference in the PNMR between urban and rural areas (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePNMR estimated for the entire national sample and urban/rural areas.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePNMR/1000 live births\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePakistan (all regions and provinces)\u003c/p\u003e\n \u003cp\u003ePakistan (Urban)\u003c/p\u003e\n \u003cp\u003ePakistan (Rural)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.1\u003c/p\u003e\n \u003cp\u003e70.5\u003c/p\u003e\n \u003cp\u003e69.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;The differences between provinces and regions in the PNMR were not statistically significant, with the exception of the Gilgit-Baltistan (GB) region, where the estimated PNMR was significantly lower than that of the provinces (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). However, among the four provinces, the estimated PNMR was the highest in Sindh and the lowest in KP.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePNMR by province/region.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProvince/Region\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePNMR/1000 live births\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzad Jammu \u0026amp; Kashmir (AJK) region\u003c/p\u003e\n \u003cp\u003eGilgit-Baltistan (GB) region\u003c/p\u003e\n \u003cp\u003eBalochistan province\u003c/p\u003e\n \u003cp\u003eKhyber Pakhtunkhwa (KP) province\u003c/p\u003e\n \u003cp\u003eSindh province\u003c/p\u003e\n \u003cp\u003ePunjab province\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.6\u003c/p\u003e\n \u003cp\u003e47.3*\u003c/p\u003e\n \u003cp\u003e79.9\u003c/p\u003e\n \u003cp\u003e63.7\u003c/p\u003e\n \u003cp\u003e87.7\u003c/p\u003e\n \u003cp\u003e67.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Chi-square test)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;The PNMR estimated by the wealth quintiles\u003csup\u003e3\u003c/sup\u003e showed a trend of being the lowest in the highest wealth quintile (the richest 20% of households in the sample) and highest in the lowest wealth quintile (the poorest 20% of households in the sample). The differences were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePNMR by wealth quintile (entire sample).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRisk Factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePNMR/1000 live births\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eWealth Quintile*\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eRichest (highest quintile - Q-5)\u003c/p\u003e\n \u003cp\u003eFourth quintile (Q-4)\u003c/p\u003e\n \u003cp\u003eMiddle quintile (Q-3)\u003c/p\u003e\n \u003cp\u003eSecond quintile (Q-2)\u003c/p\u003e\n \u003cp\u003ePoorest (lowest quintile - Q-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.4\u003c/p\u003e\n \u003cp\u003e63.0\u003c/p\u003e\n \u003cp\u003e67.7\u003c/p\u003e\n \u003cp\u003e70.6\u003c/p\u003e\n \u003cp\u003e93.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Chi-square test)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe estimated PNMR varied significantly according to the sociodemographic characteristics of the mothers (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e):\u003c/p\u003e\n\u003cp\u003eThe PNMR was the lowest among mothers whose age at pregnancy was 25\u0026ndash;34 years, compared with both younger women (\u0026lt;\u0026thinsp;25 years) and older women (\u003cspan class=\"Underline\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;35 years).\u003c/p\u003e\n\u003cp\u003eThe PNMR was approximately 20% lower among women who received adequate antenatal care (at least four visits to a skilled healthcare provider, with the first visit being in the first trimester) than among women who did not receive adequate antenatal care.\u003c/p\u003e\n\u003cp\u003eThe differences in the PNMR by parity followed the same pattern as those by age at pregnancy: the PNMR was the lowest among women with 3\u0026ndash;5 live births and highest among women with six or more live births.\u003c/p\u003e\n\u003cp\u003eThis pattern did not persist when the PNMR was computed by gravidity, whereby the PNMR was the lowest among the primigravid women and the highest among women with six or more pregnancies.\u003c/p\u003e\n\u003cp\u003eThe variation in the PNMR by mother\u0026rsquo;s education level followed the same pattern as that observed in the socioeconomic level (wealth quintiles); the PNMR was significantly lower among women in the 10th grade of schooling or above, whereas it was the highest among women with no schooling at all.\u003c/p\u003e\n\u003cp\u003eFinally, the PNMR was greater among births occurring in a health facility (due to selective referral of high-risk pregnancies to health facilities) than among births occurring at home. However, this difference was not statistically significant.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePNMR according to selected maternal and sociodemographic risk factors\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRisk Factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePNMR/1000 live births\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eMother\u0026rsquo;s age at pregnancy*\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;25 years\u003c/p\u003e\n \u003cp\u003e25\u0026ndash;34 years\u003c/p\u003e\n \u003cp\u003e35\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e82.1\u003c/p\u003e\n \u003cp\u003e59.5\u003c/p\u003e\n \u003cp\u003e82.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eAntenatal care\u003c/span\u003e\u003csup\u003e4\u003c/sup\u003e \u003cspan class=\"BoldUnderline\"\u003ereceived*\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e72.7\u003c/p\u003e\n \u003cp\u003e58.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eParity*\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;2 prior live births\u003c/p\u003e\n \u003cp\u003e3\u0026ndash;5\u003c/p\u003e\n \u003cp\u003e6+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e65.3\u003c/p\u003e\n \u003cp\u003e54.3\u003c/p\u003e\n \u003cp\u003e79.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eGravidity (number or pregnancies)*\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eNulligravida\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;5 prior pregnancies\u003c/p\u003e\n \u003cp\u003e6\u0026thinsp;+\u0026thinsp;prior pregnancies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58.2\u003c/p\u003e\n \u003cp\u003e65.8\u003c/p\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eMother\u0026rsquo;s education*\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003e10th grade or higher\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;9 years of schooling\u003c/p\u003e\n \u003cp\u003eNo schooling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46.9\u003c/p\u003e\n \u003cp\u003e63.5\u003c/p\u003e\n \u003cp\u003e83.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eDelivery in a health facility\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e65.6\u003c/p\u003e\n \u003cp\u003e72.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Chi-square test)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the results of the binary logistic regression analysis showing adjusted odds ratios for selected socioeconomic and demographic variables. The risk of a pregnancy ending in perinatal death (stillbirth or early neonatal death within 0\u0026ndash;6 days after birth) was approximately twice that of the poorest wealth quintile compared with the richest wealth quintile (the reference category) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This result was obtained after controlling for the effects of urban/rural residence, the mother\u0026rsquo;s age at birth, parity, the mother\u0026rsquo;s schooling, antenatal care received during pregnancy and delivery by skilled birth attendants.\u003c/p\u003e\n\u003cp\u003eMothers whose age at pregnancy was \u003cspan class=\"Underline\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;35 years were at a slightly greater risk of perinatal death than mothers who were in the 25\u0026ndash;34 years age group (reference category). The adjusted odds ratio was 1.37. On the other hand, mothers in the youngest age group (\u0026lt;\u0026thinsp;25 years) at pregnancy were not at greater risk than those in the reference category were (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAfter adjusting for the socioeconomic and demographic variables listed above, it was found that parity and antenatal care had no role in the causation of perinatal death, as the adjusted odds ratios for these risk factors were not statistically significant (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eWomen who delivered under care of a skilled birth attendant were at approximately 1.5 times greater risk of having perinatal death than women who did not have their baby delivered by a skilled birth attendant. This reflects the risk of selective referral of high-risk pregnancies to health facilities for delivery, and this risk persists even after adjusting for other socioeconomic and demographic variables (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAdjusted odds ratios (AORs) depicting the risk of perinatal death according to selected sociodemographic risk factors.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRisk Factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAOR\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI of AOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eWealth Quintile\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eLowest\u003c/p\u003e\n \u003cp\u003eSecond\u003c/p\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003cp\u003eFourth\u003c/p\u003e\n \u003cp\u003eHighest (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.10\u003c/p\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.40\u0026ndash;3.12\u003c/p\u003e\n \u003cp\u003e1.10\u0026ndash;2.21\u003c/p\u003e\n \u003cp\u003e0.86\u0026ndash;1.78\u003c/p\u003e\n \u003cp\u003e0.90\u0026ndash;1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eParity\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003cp\u003e3\u0026ndash;5\u003c/p\u003e\n \u003cp\u003e6+ (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.87\u0026ndash;1.61\u003c/p\u003e\n \u003cp\u003e0.68\u0026ndash;1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eMother\u0026rsquo;s age at pregnancy\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;25 years\u003c/p\u003e\n \u003cp\u003e25\u0026ndash;34 years (Ref.)\u003c/p\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;35 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.82\u0026ndash;1.31\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e1.07\u0026ndash;1 .74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eMother\u0026rsquo;s schooling\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eNo schooling\u003c/p\u003e\n \u003cp\u003e0\u0026ndash;9 years of schooling\u003c/p\u003e\n \u003cp\u003e10 grade or higher (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.19\u0026ndash;2.21\u003c/p\u003e\n \u003cp\u003e0.99\u0026ndash;1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eAdequate antenatal care received\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.70\u0026ndash;1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldUnderline\"\u003eDelivery conducted by skilled birth attendant\u003c/span\u003e:\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.24\u0026ndash;1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion and conclusions","content":"\u003cp\u003eIn this study, we found that the perinatal mortality rate (PNMR) was not significantly different among the four provinces and two regions except that the Gilgit-Baltistan region had the lowest PNMR in the country. It was found to be lowest among primigravida pregnancies and highest among women with 6 or more pregnancies.\u003c/p\u003e\u003cp\u003eThe overall odds ratios in this study demonstrated the associations of perinatal mortality with younger and older women, low-level or no maternal education and the lowest wealth quintile. However, perinatal mortality was not influenced by parity or antenatal care after adjustments were made for key socioeconomic and demographic variables. Women who delivered at facilities with skilled birth attendants were at a greater risk of perinatal death than those who delivered at home without skilled birth attendants. This is most likely due to the preponderance of complicated delivery cases being managed at facilities by skilled birth attendants. Similar findings have also been reported in other studies.\u003csup\u003e18\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eAmong the sociodemographic factors, maternal age ≥ 35 years was associated with a greater risk of perinatal mortality than the reference range of 25–34 years. Our study revealed no increase in the risk of PNMR among women aged \u0026lt; 25 years, whereas some studies have reported a greater incidence of perinatal mortality among mothers aged \u0026lt; 20 years.\u003csup\u003e19\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e20\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e21\u003c/sup\u003e Other studies have reported that women with high parity are at greater risk of perinatal mortality than women with low parity.\u003csup\u003e22\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e23\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e24\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e25\u003c/sup\u003e We found a 20% lower PNMR among women who received adequate antenatal care (at least four visits to a skilled healthcare provider, with the first visit being in the first trimester) than women who did not receive adequate antenatal care. However, the multivariate analysis revealed no role of antenatal care in reducing the risk of perinatal mortality. In contrast, evidence shows that women with at least one ANC visit experience 58–66% lower perinatal mortality.\u003csup\u003e26\u003c/sup\u003e The use of ANC visits provides an opportunity for mothers to receive health education and make them aware of danger signs to support the decision to seek healthcare at the right time. The low levels of maternal education and belonging to the lower wealth quintile may also contribute to the low utilization of ANC visits.\u003csup\u003e27\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e28\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e29\u003c/sup\u003e Berhan et al reported similar results to ours in that no or low maternal education is associated with a higher PNMR.\u003csup\u003e15,\u003c/sup\u003e \u003csup\u003e30\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e31\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e32\u003c/sup\u003e However, they also reported no association of the PNMR with the household wealth quintile, which is in contrast to the findings of our study and other studies where the PNMR is the highest among women from the lowest wealth quintile.\u003csup\u003e33\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e34\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e35\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eSeveral limitations need to be recognized in the analysis or interpretation of these results. By design, our study data were collected for five years preceding the survey, which increases the chance of recall bias. This number may be higher in uneducated respondents from rural areas, which leads to underreported perinatal deaths from rural areas. The majority of perinatal deaths in developing countries remain unaccounted for and undocumented due to suboptimal reporting and a relatively high prevalence of home births.\u003csup\u003e23,\u003c/sup\u003e \u003csup\u003e36\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e \u003csup\u003e37\u003c/sup\u003e A survey was conducted before the COVID-19 pandemic. However, the disruption in essential healthcare services was reversed after the early lockdown measures were implemented, and we believe that there have been no major changes in health service provision and that these results are still relevant to the current status.\u003c/p\u003e\u003cp\u003eIn conclusion, the findings did not demonstrate a strong association of perinatal mortality with several key selected variables, such as adequate use of ANC and skilled birth attendance. Therefore, more robust primary studies are needed to determine the true associations of these key variables with perinatal mortality in the country.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eF.M, E.T. and Q.U. conceived the manuscript.F.M. conducted the statistical analysis and Q.U. drafted the results.F. M. \u0026amp; Q.U. prepared the first draft, S.N, E. T. A. S, I. A and S.A. reviewed and provide technical inputs.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge the researchers and supporters of Pakistan Maternal Mortality Survey 2019.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e World Health Organization (2016) Child Health: Health Topics Geneva.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e USAID. 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Int J Gynecol Obstet 106(1):85\u0026ndash;88. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijgo.2009.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.ijgo.2009.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003cp\u003e[1]\u003cem\u003e\u0026nbsp;Funding for the PMMS was provided by the United States Agency for International Development (USAID); the United Nations Population Fund (UNFPA); Foreign, Commonwealth \u0026amp; Development Office (FCDO-UK); and the Bill and Melinda Gates Foundation (BMGF). Technical support was provided by Demographic and Health Surveys (DHS) Program (ICF-USA).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e[2] \u003cem\u003eNational Institute of Population Studies (NIPS) Pakistan and ICF-USA. Pakistan Maternal Mortality Survey 2019. Islamabad Pakistan and Rockville, MD, USA.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e[3] Wealth quintiles are computed in PMMS 2019 on the basis of the total value of the assets owned by the households, including car/motorcycle, television, radio, mobile phones, etc.\u003c/p\u003e\n\u003cp\u003e[4] Four or more visits to a skilled healthcare provider, the first visit being in the first trimester.\u003c/p\u003e\n\u003cp\u003e[5] Adjusted for all the variables shown in this table and for urban/rural residence.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"maternal-health-neonatology-and-perinatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mhnp","sideBox":"Learn more about [Maternal Health, Neonatology and Perinatology](http://mhnpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mhnp/default.aspx","title":"Maternal Health, Neonatology and Perinatology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Perinatal mortality, risk factors for perinatal mortality, causation of perinatal deaths","lastPublishedDoi":"10.21203/rs.3.rs-7231551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7231551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The perinatal mortality rate is a proxy indicator of healthcare quality for mothers and newborns. Unfortunately, Pakistan faces poor pregnancy outcomes, which are significantly worse than those of many other low-resource countries worldwide. Realizing the set of targets under Sustainable Development Goal 3 demands a substantial reduction in perinatal mortality in Pakistan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e SPSS data files from the Pakistan Maternal Mortality Survey (PMMS) 2019, with a sample of 136,226 households, were used. The PNMR was computed by urban and rural areas for the regions and provinces of Pakistan and for each category of the common risk factors (independent variables). We applied the chi-square test to determine whether the correlations between the PNMR and the independent variables were statistically significant. Finally, binary logistic regression analysis was conducted via SPSS version 19.0 to compute the adjusted odds ratio (AOR).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe PNMR for the entire sample was 70.1 per 1000 live births. The geographical differences were not statistically significant, with the exception of the Gilgit-Baltistan (GB) region, which had a lower PNMR. We found the lowest PNMR among the highest quintile, primigravida, having 3–5 pregnancies, mothers aged 24–35 years, with education 10 years or higher, who had adequate antenatal care and those who delivered at home without skilled birth attendants. Binary logistic regression analysis revealed a twofold greater risk among the lowest wealth quintile: 1.37 times greater among women aged \u0026gt;35 years and 1.5 times greater among women who had skilled birth attendance. After adjusting for socioeconomic and demographic variables, parity and antenatal care were found to have no association with perinatal deaths.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion \u0026amp; Conclusion:\u003c/strong\u003e We found no increase in the risk of PNMR among women younger than 25 years and using antenatal care, whereas other studies reported a greater risk of PNMR among younger and adolescent mothers. Therefore, more robust primary studies are needed to determine the associations of the key variables with perinatal mortality in Pakistan.\u003c/p\u003e","manuscriptTitle":"Why \u0026amp; Where Perinatal Deaths: Trends and Determinants in Pakistan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 14:40:31","doi":"10.21203/rs.3.rs-7231551/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-18T17:38:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T01:51:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-08T10:46:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"98695875813948674920574558961646254688","date":"2025-10-08T06:21:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324867293595840747953019649019777828494","date":"2025-10-06T09:35:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126622900495877251231356618881261280219","date":"2025-10-06T03:28:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-05T15:02:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-28T10:19:53+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-28T10:17:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Maternal Health, Neonatology and Perinatology","date":"2025-07-28T08:25:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"maternal-health-neonatology-and-perinatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mhnp","sideBox":"Learn more about [Maternal Health, Neonatology and Perinatology](http://mhnpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mhnp/default.aspx","title":"Maternal Health, Neonatology and Perinatology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"97824461-6171-4f14-af96-2d9b33841147","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:03:06+00:00","versionOfRecord":{"articleIdentity":"rs-7231551","link":"https://doi.org/10.1186/s40748-025-00246-3","journal":{"identity":"maternal-health-neonatology-and-perinatology","isVorOnly":false,"title":"Maternal Health, Neonatology and Perinatology"},"publishedOn":"2026-01-08 15:57:13","publishedOnDateReadable":"January 8th, 2026"},"versionCreatedAt":"2025-10-16 14:40:31","video":"","vorDoi":"10.1186/s40748-025-00246-3","vorDoiUrl":"https://doi.org/10.1186/s40748-025-00246-3","workflowStages":[]},"version":"v1","identity":"rs-7231551","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7231551","identity":"rs-7231551","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}