Neonatal mortality rate and burden of disease in Thai neonates: A nationwide data analysis

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This study is the most extensive nationwide effort to evaluate in-hospital mortality and disease burden among neonates in Thailand. Methods : A descriptive-analytic study used data from neonates born in hospitals under the Universal Health Coverage Scheme between 2015 and 2020. Data were extracted from discharge summaries using the International Statistical Classification of Diseases and Related Health Problems, 10 th Revision, Thai Modification (ICD-10-TM). Results: Overall, 3,141,215 live births were recorded during the 6-year study period, and 10,623 infants died within 28 days of life. In-hospital NMR was 3.38 per 1,000 live births. The annual NMR decreased significantly from 3.60 per 1,000 in 2015 to 3.05 per 1,000 in 2020 (p-value <0.001). Sixty-seven percent (n=7,149) of deaths occurred within 7 days of life (early neonatal death), and 46.7% (n=4,957) died within 3 days. The leading causes of neonatal death were disorders related to prematurity (36.3%), followed by congenital malformations and chromosomal abnormalities (23.5%), respiratory problems and persistent pulmonary hypertension of the newborn (17.8%), neonatal sepsis (12.3%), and perinatal asphyxia (7.6%). The regional NMR varied significantly, from 2.35 per 1,000 in the northern region to 5.22 per 1,000 in Bangkok. Factors significantly associated with NMR include low birth weight, small for gestational age, persistent pulmonary hypertension of the newborn, pulmonary hemorrhage, air leak, major congenital anomalies, severe asphyxia, hypo-hyperglycemia, disturbance of sodium balance, and sepsis. Common comorbidities among Thai neonates were neonatal jaundice (23.9%), respiratory problems (12.1%), disorders related to prematurity and low birth weight (11.1%), congenital malformations and chromosomal abnormalities (7.2%), sepsis (5.8%), and perinatal asphyxia (2.1%). Conclusion: The declining birth rate and NMR in Thailand highlight significant changes in the country’s demographics and improvements in healthcare services. Prematurity remains the leading cause of neonatal death, emphasizing the critical need for targeted interventions in maternal and neonatal care. Regional disparities in NMR indicate uneven distribution and access to healthcare resources, suggesting that strategic allocation and improvement of perinatal and post-natal care services are necessary to address these variations and enhance overall neonatal health outcomes in Thailand. neonates mortality comorbidities burden of disease Figures Figure 1 Introduction The neonatal period encompasses the first 28 days of life and is critical for child survival. The World Health Organization (WHO) and the United Nations Millennium Development Goal (MDG4) set targets to reduce the mortality of children under five by two-thirds between 1990 and 2015 [ 1 ]. While many countries have made significant progress and achieved MDG 4, the global target was ultimately missed, with an overall reduction of approximately half [ 2 ]. This underscores the need for continued and enhanced efforts to improve maternal, neonatal, and child health worldwide. According to the WHO, in 2020, 47% of all under-five deaths globally occurred during the newborn period, which increased from 40% in 1990. This shift is due to the under-five mortality declining more rapidly than the NMR [ 3 ], highlighting the need for focused interventions to further reduce neonatal deaths and improve early childhood survival. NMR is a crucial international indicator that reflects a country’s health challenges and the quality of its healthcare services. A 2010 study in Thailand revealed that neonatal deaths accounted for 58.9%of all deaths in the first year of life (infant mortality)[ 4 ]. Although NMR in Thailand has decreased over the past decade, ongoing efforts are essential to continue this progress, ensuring that more neonates survive through infancy and beyond. Since 2002, Thailand’s public health financing schemes have provided Universal Health Care coverage (UC scheme), benefiting most Thai people, including infants and children. This has significantly improved access to healthcare facilities. With 96–99% of births occurring in hospitals [ 5 ], evaluating neonatal health using in-hospital medical records provides a reliable database for assessing the health status of neonates in the country. This study aimed to evaluate in-hospital mortality and disease burden in neonates in Thailand between 2015 and 2020. Data were sourced from the Bureau of Health Policy and Strategy Database of the Ministry of Public Health. This study also investigated factors associated with in-hospital neonatal mortality. As developing countries grapple with the global public health challenge of addressing the root causes of neonatal deaths, the insights gained from this study could enhance our understanding of critical issues contributing to neonatal mortality. This, in turn, could help prioritize strategies for improving neonatal outcomes. Methods This descriptive-analytic study used data from neonates born in hospitals in the public and private sectors under Thailand’s UC scheme. This study covered the period from January 2015 to December 2020. Data were extracted from the discharge summaries of all hospitals using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Thai Modification (ICD-10-TM) for coding. The data collection process included recording information such as place and date of birth, date of hospital discharge or death, diagnosis of comorbidities, procedures performed, length of hospital stay, and hospital charges. To calculate the length of hospital stay, the time of birth and the time of first discharge home or death were used. For infants transferred to other hospitals after birth, the duration spent at other hospitals was also considered part of their birth hospitalization. This comprehensive approach aimed to thoroughly assess neonatal health outcomes and the factors influencing in-hospital neonatal mortality within a specified period. The diagnosis of comorbidities were collected using ICD-10-TM as follows: slow fetal growth and fetal malnutrition (P05), disorders related to short gestation and low birth weight (P07), disorders related to long gestation and high birth weight (P08), birth injury (P10-P15), perinatal asphyxia (P210, P211, P219), respiratory problems including respiratory distress of the newborn (P22), pneumonia (P23, J13-18), neonatal aspiration syndrome (P24), pulmonary air leak (P25), pulmonary hemorrhage (P26), bronchopulmonary dysplasia: BPD (P271), persistent pulmonary hypertension of the newborn: PPHN (P293), neonatal sepsis (P360-9), intraventricular hemorrhage: IVH (P520-9), neonatal jaundice (P57-59), hematologic disorders (P55-6,P60-1), neonatal hypoglycemia (P704), other transitory disorders of carbohydrate metabolism of newborn approximate synonyms of neonatal hyperglycemia (P708), hyperglycemia (R73), disturbance of sodium balance of newborn (P742), hypernatremia (E870), hypornatremia (E871), necrotizing enterocolitis: NEC (P77), convulsion of newborn (P90), feeding problems of newborn (P92), congenital malformations and chromosomal abnormalities (Q00-99) The ICD-9 codes for the procedures were collected as follows: cardiopulmonary resuscitation (9960), non-invasive respiratory support (9390), continuous invasive mechanical ventilation for less than 96 consecutive hours (9671), continuous invasive mechanical ventilation for 96 consecutive hours or more (9672), intercostal drainage (3404), packed red cell (PRC) transfusion (9904), parenteral nutrition (9915), enterotomy (450-6), stoma creation (460-4), intestinal anastomosis (4590- 4), percutaneous abdominal drainage (5491), and procedure for PDA closure (3885). This study was approved by the Khon Kaen University Ethics Committee in Human Research (HE651030) Statistical analysis Data are described as frequencies and percentages for categorical variables and medians and interquartile ranges (QRs) for continuous variables. The factors associated with neonatal mortality, such as the diagnosis of comorbidities and procedures, were assessed. The results are presented as adjusted odds ratios with 95% confidence intervals (CI), and a p-value < 0.05 was considered statistically significant. Statistical analyses were conducted using Stata version 10.1 (Stata Corp, College Station, TX, USA). Results The birth rate in Thailand has steadily declined. During the study period, 3,141,215 live births were registered under the UC scheme. Geographically, the distribution of births was the highest in the northeastern region (31.4%), followed by the south (19.6%) and the central region (18.3%). Of all births, 8.5% occurred in primary-level hospitals, 52.0% in secondary-level hospitals, and 37.7% in tertiary-level hospitals (Table 1 ). During the 6-year study period, 10,623 infants died within 28 days of life. Of these deaths, 67.3% (n = 7,149) occurred within 7 days after birth ( i.e. , early neonatal death), and 46.7% (n = 4,957) occurred within 3 days of life. Most neonates died in secondary and tertiary care hospitals. The annual NMR significantly decreased from 3.60 per 1,000 live births in 2015 to 3.05 per 1,000 in 2020 (p-value < 0.001). The annual NMR in Thailand exhibited significant decreases in most geographic regions, with exceptions in the eastern, northern, and southern regions. There was variation in regional NMR ranging from 2.35 per 1,000 live births in the northern region to 5.22 per 1,000 live births in Bangkok (Table 2 ). Physicians and ICD-10 codes identified the leading causes of neonatal mortality as disorders related to prematurity (36.3%), followed by major congenital malformations and chromosomal abnormalities (23.5%). Other significant causes included respiratory problems, PPHN (17.8%), neonatal sepsis (12.5%), and perinatal asphyxia (7.6%) (Fig. 1 ). Table 1 Total number of live births born between 2015 and 2020 classified by year, place of birth, hospital level, and sex Year 2015 2016 2017 2018 2019 2020 Total % UC data 566,953 548,815 539,119 518,339 494,907 473,082 3,141,215 100 Region Bangkok 44,099 42,128 43,056 41,477 39,131 37,150 247,041 7.9 Central 10,4253 100,574 99,023 94,247 90,825 85,225 574,147 18.3 East 55,432 54,627 54,230 53,047 51,377 48,726 317,439 10.1 Northeast 180,494 174,234 169,556 162,374 152,905 146,934 986,497 31.4 North 41784 40,760 40,076 38,322 37,260 35,955 234,157 7.4 West 29,,897 28,886 28,862 26,961 26,437 24,891 165,934 5.3 South 111,005 107,606 104,315 101,912 96,971 94,191 616,000 19.6 Hospital level Primary 46,563 45,490 45,887 44,822 43,565 41,455 267,782 8.5 Secondary 296,707 286,085 280,484 268,102 255,083 246,545 1,633,006 52 Tertiary 212,438 205,853 201,917 196,865 188,981 176,649 1,182,703 37.7 Private 11,256 11,387 10,830 8,551 7,277 8,423 57,724 1.8 Sex Male 292,725 28,3019 279,309 267,990 255,486 244,839 1,623,368 51.7 Female 274,239 265,796 259,809 250,350 239,420 228,233 1,517,847 48.3 Outcome Alive 564,924 546,829 537,262 516,630 493,319 471,628 3,130,529 99.7 Dead 2,029 1,986 1,857 1,709 1,588 1,454 10,623 0.3 Table 2 Trends of in-hospital NMR in Thailand 2015 2016 2017 2018 2019 2020 Total p-value Thailand 3.60 3.62 3.44 3.30 3.21 3.05 3.38 < 0.001 Region 1) Bangkok 5.76 5.58 5.55 4.97 4.78 4.55 5.22 0.0026 2) Central 3.69 4.15 4.12 3.70 3.35 3.43 3.75 0.0163 3) East 3.52 4.34 3.93 4.26 3.62 3.80 3.91 0.8932 4) Northeast 3.30 3.04 2.89 2.82 2.79 2.55 2.91 < 0.001 5) North 2.49 2.43 2.84 1.62 2.39 2.31 2.35 0.262 6) West 4.62 3.57 3.46 3.49 3.10 2.05 3.42 < 0.001 7) South 3.32 3.40 2.80 3.09 3.22 3.08 3.16 0.2849 Hospital-Level Primary 1.65 1.82 1.63 1.90 1.86 1.81 1.78 0.4862 Second 2.65 2.61 2.57 2.58 2.41 2.23 2.52 0.0014 Tertiary 5.20 5.26 4.88 4.45 4.50 4.43 4.80 < 0.001 Private 6.57 6.59 6.83 6.55 5.63 4.27 6.17 0.0379 p-value: chi-square test for trend According to the data from Table 3 , the three most common comorbidities diagnosed in neonates during the study period were neonatal jaundice (23.9%), respiratory problems (12.1%), and disorders related to prematurity and low birth weight (11.1%), congenital malformations and chromosomal abnormalities (7.2%), neonatal sepsis (5.8%), hypo- and hyperglycemia (4.3%), perinatal asphyxia (2.1%), and birth injury (1.6%). Table 3 Common comorbidities diagnosed in neonates in Thailand. Comorbidities N % Neonatal jaundice (P590-9) 750,340 23.9 Respiratory problems (P22-25, J13-18) 381,442 12.1 Disorders related to prematurity and low birth weight (P05, P07) 352,095 11.1 Congenital malformations and chromosomal abnormalities (Q00-99) 225,275 7.2 Neonatal sepsis (P360-9) 181,223 5.8 Transitory disorders of carbohydrate metabolism of newborn: neonatal hypo (P704) and hyperglycemia (P708, R73) 135,457 4.3 Perinatal asphyxia (P210, P211, P219) 67,110 2.1 Birth injury (P10-P15) 49,152 1.6 The comorbidities associated with a higher probability of neonatal death include low birth weight, especially extremely low birth weight, small for gestational age, PPHN, pulmonary hemorrhage, air leak, significant congenital anomalies, severe asphyxia, hyperglycemia, hypoglycemia, disturbance of sodium balance, and sepsis. Procedures significantly associated with higher probabilities of death were mechanical ventilation, cardiopulmonary resuscitation, intra-abdominal drainage, intercostal drainage, and packed red cell transfusion, with adjusted odds ratios (95% CI) and p-values (Table 4 ). Table 4 Factors associated with neonatal mortality Adjusted OR 95%CI p-value Male 0.91 0.86, 0.95 < 0.001 Region < 0.001 1) Bangkok 1.81 1.60, 2.05 2) Central 1.92 1.71, 2.16 3) East 2.00 1.77, 2.27 4) Northeast 1.57 1.40, 1.76 5) North 1 6) West 1.78 1.53, 2.06 7) South 1.75 1.56, 1.97 Diagnosis P051 newborn small for gestational age 1.78 1.54, 2.05 < 0.001 P070 extremely low birth weight infant 12.90 11.83,14.06 < 0.001 P071 other low birth weight infant 2.23 2.10, 2.37 < 0.001 P073 other preterm infant 1.06 0.94, 1.18 0.361 P210 severe asphyxia 2.36 2.20, 2.54 < 0.001 P250-8 air leak 1.99 1.77, 2.22 < 0.001 P260-9 pulmonary hemorrhage 4.38 3.98, 4.82 < 0.001 P293 PPHN 8.15 7.53, 8.82 < 0.001 P360-9 sepsis 1.10 1.04, 1.16 0.001 P704 hypoglycemia 1.31 1.23, 1.40 < 0.001 P708, R73 hyperglycemia 2.00 1.78, 2.25 < 0.001 P742, E870,E871 disturbance of sodium 1.14 1.05, 1.23 0.001 Q00-99 major congenital anomalies 3.19 3.02, 3.38 < 0.001 Procedure 9960 CPR 14.48 13.42, 15.62 < 0.001 Respiratory support < 0.001 -9390 non-invasive support 5.96 5.15, 6.90 -9671 invasive ventilation 96 hr 18.38 16.66, 20.29 3404 intercostal drainage 1.83 1.62, 2.07 < 0.001 9904 packed red cell transfusion 1.28 1.20, 1.36 < 0.001 9915 parenteral nutrition 0.35 0.33, 0.37 < 0.001 4500-6 enterotomy 1.03 0.74, 1.44 0.853 4590-4 intestinal anastomosis 0.53 0.38, 0.74 < 0.001 5491 intra-abdominal drainage 4.46 3.34, 5.96 < 0.001 3885 PDA ligation 0.11 0.09, 0.14 < 0.001 PPHN: persistent pulmonary hypertension of the newborn CPR: cardiopulmonary resuscitation PDA: patent ductus arteriosus The median hospital charge of infants who died in the neonatal period was 41,413 baht/infant (IQR 17,772, 89,738) compared to 2,322 baht/infant (IQR 1,361, 4,414) for infants who survived. Discussion Thailand has made significant progress in improving its healthcare system over the last decade owing to the implementation of the UC scheme, which has reduced inequalities in healthcare access, particularly in rural areas. Implementation of the UC scheme succeeded in decreasing neonatal mortality by up to 13 percent [ 6 ]. However, issues in maternal and child health still need to be addressed. This was a nationwide study on in-hospital mortality and the disease burden or comorbidities among neonates in Thailand over 6 years. The consistent decline in the birth rate each year is one of the country’s most significant challenges. The present study found that in-hospital neonatal mortality significantly decreased from 3.60 per 1,000 live births in 2015 to 3.05 per 1000 live births in 2020, with an overall NMR of 3.38 per 1,000 live births over 6 years. This trend of reducing NMR in Thailand indicates positive progress in maternal and neonatal healthcare, reflecting enhanced access to medical facilities and advancements in medical technology and practices. The results of this study were consistent with those of a previous study in 2010 [ 4 ], which reported that the majority of neonatal deaths occurred within seven days of life, particularly within the first three days, highlighting the critical vulnerability in the early postnatal period. As in previous studies [ 4 ], the leading cause of neonatal mortality was prematurity, followed by major congenital malformations and chromosomal abnormalities, which accounted for up to one-fourth of neonatal deaths. . There was a significant variation in the regional NMR, ranging from 2.35 per 1,000 in the northern region to 5.22 per 1,000 in Bangkok. This may indicate that high-risk pregnancies or critically ill neonates were transferred to specialized hospitals or academic centers in Bangkok. In the context of factors associated with neonatal mortality, extremely low birth weight was the most potent risk factor associated with a neonatal mortality rate 12.9 times higher than that of normal birth weight. This finding is consistent with a meta-analysis in which low birth weight was associated with neonatal mortality rates 9.9–15.5 times higher than that of normal birth weight [ 7 ]. Interventions targeting improved care for preterm and low-birth-weight infants may reduce neonatal mortality[ 8 ]. Comprehensive data from this study can help prioritize and implement appropriate interventions to prevent neonatal deaths and improve outcomes [ 9 ]. Prematurity is the leading cause of neonatal mortality in Thailand, which is consistent with the trends in developed countries and worldwide [ 10 ]. Prematurity is also a risk factor for neonatal death associated with other serious complications such as respiratory problems or infections. The challenge is to identify high-risk pregnancies early and strengthen service delivery to effectively prevent premature births as well as to provide proper management of related problems. There are often signs of impending preterm delivery, and interventions such as antenatal corticosteroids, tocolytic agents, and improvements in referral systems are crucial [ 11 , 12 ]. In addition, interventions aimed at improving outcomes for premature and low birth weight infants, expanding quality services, and allocating resources, such as specialized neonatal care and neonatal intensive care units, should be provided according to regional needs [ 13 ]. Community engagement can facilitate the process by developing and strengthening linkages with local health systems, such as the Provincial Maternal and Child Health Committees and Regional Healthcare Services, to ensure better outcomes for all neonates nationwide [ 14 ]. Our study found that the second most common cause of neonatal death was congenital malformation and chromosomal abnormalities. Globally, it is the fourth leading cause of neonatal mortality, with 90% of cases involving serious disorders accounting for low- and middle-income countries [ 15 ]. As the reduction of birth defects is a WHO and global priority [ 16 ], measures to integrate primary prevention programs include raising awareness about the importance of screening for fetal anomalies and improving the quality and accessibility of these screenings is crucial. In the case of prenatal detection of severe congenital abnormalities, a family meeting with a multidisciplinary team could provide comprehensive information and develop an advanced care plan that may include options for palliative care [ 17 ]. Additionally, supporting families with children with congenital disorders and associated disabilities should be addressed by providing appropriate care and offering necessary resources. Apart from low birth weight and small for gestational age, we found that conditions such as PPHN, pulmonary hemorrhage, air leak, major congenital anomalies, severe asphyxia, hypo-hyperglycemia, disturbance of sodium balance, and sepsis were associated with higher probabilities of neonatal death. Asphyxia can be prevented through effective neonatal resuscitation training for healthcare providers. Infections can be identified early and treated without delay using a simplified algorithm, and the early initiation of breastfeeding should be promoted [ 13 ]. Implementing strict hand hygiene and sterile techniques for invasive procedures, central venous catheter care, and antibiotic stewardship are essential strategies for reducing the risk of infection and sepsis [ 18 ]. The strengths of this study include the large number of infants and the retrieval of data at the national level from the UC scheme in Thailand. However, the present study had some limitations that merit consideration. This study provides a 6-year trend in NMR in Thailand using data from most Thai neonates. Nevertheless, this rate may not fully represent the Thai neonatal population because births and deaths are covered by the Civil Servant Medical Benefit (CSMB) scheme, and some private hospitals are not included in the UC database. However, this is the most cost-effective method for monitoring the quality of neonatal care in our setting. Data were extracted from the ICD-10 and ICD-9 coding in medical records from primary through tertiary care and private hospitals nationwide. Therefore, the accuracy of the results depends on diagnosis and coding practices. Some information, such as gestational age, cannot be extracted individually. Despite the internal quality audit process at each hospital and the external audit by the Bureau of Health Policy and Strategy at the Ministry of Public Health, misclassifications may have occurred. Conclusions The birth rate and NMR in Thailand have continuously declined. Our study provides information for identifying key neonatal mortality-related issues. The variation in regional NMR underscores the need for a national health policy accompanied by comprehensive, multi-sectoral approaches to providing good pre-and postnatal care and appropriate allocation of resources per regional problems. Declarations Author Contributions : P.K. conceptualized and designed the study, performed the computations, discussed the results, drafted the initial manuscript, and contributed to the final manuscript. J.J. discussed the results, drafted the initial manuscript, and contributed to the final manuscript. P.P. and S.M. discussed the results and contributed to the final manuscript. KT performed the computations, was involved in data acquisition, was responsible for analyzing and interpreting the data, and contributed to the final manuscript. SS was involved in the data acquisition, discussed the results, and contributed to the final manuscript. All authors have read and approved the final manuscript. Funding : This study received no external funding. Institutional Review Board Statement : This study was approved by the Khon Kaen University Ethics Committee on Human Research (HE651030) on January 22, 2022. Informed Consent Statement : The Center for Ethics in Human Research, Khon Kaen University, waived the requirement for informed consent because no personally identifiable data were collected. The authors confirmed that all methods were performed according to the relevant guidelines and regulations. Data Availability Statement : The datasets used and analyzed during the current study were from Thailand National Health Coverage, but restrictions apply to the availability of these data, which were used under license for the current study, so they are not publicly available. However, data are available from the authors upon reasonable request and with permission from the Thailand National Health Coverage. Acknowledgments : The authors would like to thank the Bureau of Health Policy and Strategy at the Ministry of Public Health for the use of the data from the summary discharge of all hospitals under the National Health Coverage Scheme, the Royal College of Pediatricians of Thailand, and the Pediatric Society of Thailand for permission to analyze and report this information. Conflicts of Interest : The authors declare no conflicts of interest. References UN Millennium Development Goals. Goal 4: reduce child mortality. https://www.un.org/millenniumgoals/childhealth.shtml Hug L, Alexander M, You D, Alkema L, UN Inter-agency Group for Child Mortality Estimation. National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis. 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Bhutta ZA Evidence from community level inputs to improve quality of care for maternal and newborn health: interventions and findings. Reprod Health. 2014;11(Suppl 2):S2. https://doi.org/10.1186/1742-4755-11-S2-S2 . World Health Organization. Congenital disorders Key facts. 2023. https://www.who.int/news-room/fact-sheets/detail/birth-defects Accessed 07 Nov 2023. World Health Organization. Regional Office for South-East Asia. (‎2013)‎ Prevention and control of birth defects in South-East Asia Region: strategic framework (‎2013–2017)‎ WHO Regional Office for South-East Asia. https://iris.who.int/handle/10665/205644 Perinatal palliative care. ACOG Committee Opinion 786. American College of Obstetricians and Gynecologists. Obstet Gynecol. 2019;134:e84–9. Buetti N, Marschall J, Drees M, Fakih MG, Hadaway L, Maragakis LL, et al. Strategies to prevent central line-associated bloodstream infections in acute-care hospitals: 2022 Update. Infect Control Hosp Epidemiol. 2022;43(5):553–69. 10.1017/ice.2022.87 . Epub 2022 Apr 19. PMID: 35437133; PMCID: PMC9096710. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4798791","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":332173085,"identity":"cc67b6c4-0184-4cf6-9f9b-27b12d31684e","order_by":0,"name":"Pakaphan Kiatchoosakun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYFACNmaGBAYbAwkoN4FYLWkwLQZEamFgOEyCFnP2Y8kGD2rOG0vOSGD88IPhTx5BLZY9aYcTEo7dNpOWSGCW7GEwKCaoxeBAevOBBLbbNnISCQzSQH5iA0Et558Dtfw7B9LC/Js4LTeADktsOwByGBtxtljOeJZskNiXbCzZ87DNssfAmLAWc/40Y8kf3+wMZxxPPnzjR4UcEQ5DMBkbULjEaBkFo2AUjIJRgAMAAHCvOa2xa9NxAAAAAElFTkSuQmCC","orcid":"","institution":"Khon Kaen University","correspondingAuthor":true,"prefix":"","firstName":"Pakaphan","middleName":"","lastName":"Kiatchoosakun","suffix":""},{"id":332173087,"identity":"84c4bc1b-f280-468d-a59d-0817f714b200","order_by":1,"name":"Junya Jirapradittha","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Junya","middleName":"","lastName":"Jirapradittha","suffix":""},{"id":332173088,"identity":"619067ee-35c1-44d3-826c-9da32a7a13ad","order_by":2,"name":"Pongsatorn Paopongsawan","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Pongsatorn","middleName":"","lastName":"Paopongsawan","suffix":""},{"id":332173089,"identity":"eecaa413-0a8b-4b91-9b83-75cf2b45951e","order_by":3,"name":"Kaewjai Thepsuthammarat","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Kaewjai","middleName":"","lastName":"Thepsuthammarat","suffix":""},{"id":332173090,"identity":"fbc9c294-a86b-4a3e-92fc-ce1b2b623618","order_by":4,"name":"Satit Manopunya","email":"","orcid":"","institution":"Chiangmai University","correspondingAuthor":false,"prefix":"","firstName":"Satit","middleName":"","lastName":"Manopunya","suffix":""},{"id":332173091,"identity":"e350de08-1c5c-4576-b683-4921ba5f20c5","order_by":5,"name":"Sumitr Sutra","email":"","orcid":"","institution":"Khon Kaen University","correspondingAuthor":false,"prefix":"","firstName":"Sumitr","middleName":"","lastName":"Sutra","suffix":""}],"badges":[],"createdAt":"2024-07-25 04:03:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4798791/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4798791/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63406865,"identity":"43d9527c-61b0-4882-b17a-c4b5f1ece0b6","added_by":"auto","created_at":"2024-08-27 21:47:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67743,"visible":true,"origin":"","legend":"\u003cp\u003eLeading causes of in-hospital neonatal mortality by birth year\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4798791/v1/c8147fed45fc92f78195ae04.png"},{"id":63790614,"identity":"557a4c6b-4c7d-4dd3-aa3d-a46f7caa9f95","added_by":"auto","created_at":"2024-09-02 11:31:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":748341,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4798791/v1/7b040010-e14d-41d1-9226-f7172f8f5cb8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Neonatal mortality rate and burden of disease in Thai neonates: A nationwide data analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe neonatal period encompasses the first 28 days of life and is critical for child survival. The World Health Organization (WHO) and the United Nations Millennium Development Goal (MDG4) set targets to reduce the mortality of children under five by two-thirds between 1990 and 2015 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While many countries have made significant progress and achieved MDG 4, the global target was ultimately missed, with an overall reduction of approximately half [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This underscores the need for continued and enhanced efforts to improve maternal, neonatal, and child health worldwide. According to the WHO, in 2020, 47% of all under-five deaths globally occurred during the newborn period, which increased from 40% in 1990. This shift is due to the under-five mortality declining more rapidly than the NMR [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], highlighting the need for focused interventions to further reduce neonatal deaths and improve early childhood survival. NMR is a crucial international indicator that reflects a country\u0026rsquo;s health challenges and the quality of its healthcare services. A 2010 study in Thailand revealed that neonatal deaths accounted for 58.9%of all deaths in the first year of life (infant mortality)[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although NMR in Thailand has decreased over the past decade, ongoing efforts are essential to continue this progress, ensuring that more neonates survive through infancy and beyond.\u003c/p\u003e \u003cp\u003eSince 2002, Thailand\u0026rsquo;s public health financing schemes have provided Universal Health Care coverage (UC scheme), benefiting most Thai people, including infants and children. This has significantly improved access to healthcare facilities. With 96\u0026ndash;99% of births occurring in hospitals [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], evaluating neonatal health using in-hospital medical records provides a reliable database for assessing the health status of neonates in the country.\u003c/p\u003e \u003cp\u003eThis study aimed to evaluate in-hospital mortality and disease burden in neonates in Thailand between 2015 and 2020. Data were sourced from the Bureau of Health Policy and Strategy Database of the Ministry of Public Health. This study also investigated factors associated with in-hospital neonatal mortality. As developing countries grapple with the global public health challenge of addressing the root causes of neonatal deaths, the insights gained from this study could enhance our understanding of critical issues contributing to neonatal mortality. This, in turn, could help prioritize strategies for improving neonatal outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis descriptive-analytic study used data from neonates born in hospitals in the public and private sectors under Thailand\u0026rsquo;s UC scheme. This study covered the period from January 2015 to December 2020. Data were extracted from the discharge summaries of all hospitals using the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Thai Modification (ICD-10-TM) for coding. The data collection process included recording information such as place and date of birth, date of hospital discharge or death, diagnosis of comorbidities, procedures performed, length of hospital stay, and hospital charges. To calculate the length of hospital stay, the time of birth and the time of first discharge home or death were used. For infants transferred to other hospitals after birth, the duration spent at other hospitals was also considered part of their birth hospitalization. This comprehensive approach aimed to thoroughly assess neonatal health outcomes and the factors influencing in-hospital neonatal mortality within a specified period.\u003c/p\u003e \u003cp\u003eThe diagnosis of comorbidities were collected using ICD-10-TM as follows: slow fetal growth and fetal malnutrition (P05), disorders related to short gestation and low birth weight (P07), disorders related to long gestation and high birth weight (P08), birth injury (P10-P15), perinatal asphyxia (P210, P211, P219), respiratory problems including respiratory distress of the newborn (P22), pneumonia (P23, J13-18), neonatal aspiration syndrome (P24), pulmonary air leak (P25), pulmonary hemorrhage (P26), bronchopulmonary dysplasia: BPD (P271), persistent pulmonary hypertension of the newborn: PPHN (P293), neonatal sepsis (P360-9), intraventricular hemorrhage: IVH (P520-9), neonatal jaundice (P57-59), hematologic disorders (P55-6,P60-1), neonatal hypoglycemia (P704), other transitory disorders of carbohydrate metabolism of newborn approximate synonyms of neonatal hyperglycemia (P708), hyperglycemia (R73), disturbance of sodium balance of newborn (P742), hypernatremia (E870), hypornatremia (E871), necrotizing enterocolitis: NEC (P77), convulsion of newborn (P90), feeding problems of newborn (P92), congenital malformations and chromosomal abnormalities (Q00-99)\u003c/p\u003e \u003cp\u003eThe ICD-9 codes for the procedures were collected as follows: cardiopulmonary resuscitation (9960), non-invasive respiratory support (9390), continuous invasive mechanical ventilation for less than 96 consecutive hours (9671), continuous invasive mechanical ventilation for 96 consecutive hours or more (9672), intercostal drainage (3404), packed red cell (PRC) transfusion (9904), parenteral nutrition (9915), enterotomy (450-6), stoma creation (460-4), intestinal anastomosis (4590- 4), percutaneous abdominal drainage (5491), and procedure for PDA closure (3885).\u003c/p\u003e \u003cp\u003eThis study was approved by the Khon Kaen University Ethics Committee in Human Research (HE651030)\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData are described as frequencies and percentages for categorical variables and medians and interquartile ranges (QRs) for continuous variables. The factors associated with neonatal mortality, such as the diagnosis of comorbidities and procedures, were assessed. The results are presented as adjusted odds ratios with 95% confidence intervals (CI), and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Statistical analyses were conducted using Stata version 10.1 (Stata Corp, College Station, TX, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe birth rate in Thailand has steadily declined. During the study period, 3,141,215 live births were registered under the UC scheme. Geographically, the distribution of births was the highest in the northeastern region (31.4%), followed by the south (19.6%) and the central region (18.3%). Of all births, 8.5% occurred in primary-level hospitals, 52.0% in secondary-level hospitals, and 37.7% in tertiary-level hospitals (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDuring the 6-year study period, 10,623 infants died within 28 days of life. Of these deaths, 67.3% (n\u0026thinsp;=\u0026thinsp;7,149) occurred within 7 days after birth (\u003cem\u003ei.e.\u003c/em\u003e, early neonatal death), and 46.7% (n\u0026thinsp;=\u0026thinsp;4,957) occurred within 3 days of life. Most neonates died in secondary and tertiary care hospitals. The annual NMR significantly decreased from 3.60 per 1,000 live births in 2015 to 3.05 per 1,000 in 2020 (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The annual NMR in Thailand exhibited significant decreases in most geographic regions, with exceptions in the eastern, northern, and southern regions. There was variation in regional NMR ranging from 2.35 per 1,000 live births in the northern region to 5.22 per 1,000 live births in Bangkok (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Physicians and ICD-10 codes identified the leading causes of neonatal mortality as disorders related to prematurity (36.3%), followed by major congenital malformations and chromosomal abnormalities (23.5%). Other significant causes included respiratory problems, PPHN (17.8%), neonatal sepsis (12.5%), and perinatal asphyxia (7.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal number of live births born between 2015 and 2020 classified by year, place of birth, hospital level, and sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUC data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e566,953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e548,815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e539,119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e518,339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e494,907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e473,082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3,141,215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBangkok\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44,099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42,128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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\u003cp\u003e48,726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e317,439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180,494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174,234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e169,556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e162,374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152,905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e146,934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e986,497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40,760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40,076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38,322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37,260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35,955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e234,157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29,,897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28,862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26,961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26,437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24,891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e165,934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111,005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107,606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104,315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101,912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96,971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94,191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e616,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46,563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45,490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45,887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44,822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43,565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41,455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e267,782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e296,707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286,085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e280,484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e268,102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e255,083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e246,545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,633,006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e212,438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205,853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e201,917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e196,865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e188,981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e176,649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,182,703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11,387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57,724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e292,725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28,3019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e279,309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e267,990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e255,486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e244,839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,623,368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e274,239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e265,796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e259,809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250,350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e239,420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e228,233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1,517,847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e564,924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e546,829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e537,262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e516,630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e493,319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e471,628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3,130,529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10,623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTrends of in-hospital NMR in Thailand\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1) Bangkok\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2) Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3) East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.8932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4) Northeast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5) North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6) West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7) South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.2849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital-Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.4862\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ep-value: chi-square test for trend\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccording to the data from Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the three most common comorbidities diagnosed in neonates during the study period were neonatal jaundice (23.9%), respiratory problems (12.1%), and disorders related to prematurity and low birth weight (11.1%), congenital malformations and chromosomal abnormalities (7.2%), neonatal sepsis (5.8%), hypo- and hyperglycemia (4.3%), perinatal asphyxia (2.1%), and birth injury (1.6%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCommon comorbidities diagnosed in neonates in Thailand.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal jaundice (P590-9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e750,340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory problems (P22-25, J13-18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e381,442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisorders related to prematurity and low birth weight (P05, P07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e352,095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital malformations and chromosomal abnormalities (Q00-99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225,275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal sepsis (P360-9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e181,223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransitory disorders of carbohydrate metabolism of newborn: neonatal hypo (P704) and hyperglycemia (P708, R73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e135,457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerinatal asphyxia (P210, P211, P219)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67,110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth injury (P10-P15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49,152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe comorbidities associated with a higher probability of neonatal death include low birth weight, especially extremely low birth weight, small for gestational age, PPHN, pulmonary hemorrhage, air leak, significant congenital anomalies, severe asphyxia, hyperglycemia, hypoglycemia, disturbance of sodium balance, and sepsis. Procedures significantly associated with higher probabilities of death were mechanical ventilation, cardiopulmonary resuscitation, intra-abdominal drainage, intercostal drainage, and packed red cell transfusion, with adjusted odds ratios (95% CI) and p-values (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with neonatal mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.86, 0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1) Bangkok\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.60, 2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2) Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.71, 2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3) East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.77, 2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4) Northeast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.40, 1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5) North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6) West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.53, 2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7) South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.56, 1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP051 newborn small for gestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.54, 2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP070 extremely low birth weight infant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.83,14.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP071 other low birth weight infant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.10, 2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP073 other preterm infant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.94, 1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP210 severe asphyxia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.20, 2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP250-8 air leak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.77, 2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP260-9 pulmonary hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.98, 4.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP293 PPHN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.53, 8.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP360-9 sepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.04, 1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP704 hypoglycemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.23, 1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP708, R73 hyperglycemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.78, 2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP742, E870,E871 disturbance of sodium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05, 1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ00-99 major congenital anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.02, 3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProcedure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9960 CPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.42, 15.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-9390 non-invasive support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.15, 6.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-9671 invasive ventilation\u0026thinsp;\u0026lt;\u0026thinsp;96 hr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.00, 93.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-9672 invasive ventilation\u0026thinsp;\u0026gt;\u0026thinsp;96 hr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.66, 20.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3404 intercostal drainage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.62, 2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9904 packed red cell transfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.20, 1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9915 parenteral nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.33, 0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4500-6 enterotomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74, 1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4590-4 intestinal anastomosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38, 0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5491 intra-abdominal drainage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.34, 5.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3885 PDA ligation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09, 0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ePPHN: persistent pulmonary hypertension of the newborn\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCPR: cardiopulmonary resuscitation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ePDA: patent ductus arteriosus\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median hospital charge of infants who died in the neonatal period was 41,413 baht/infant (IQR 17,772, 89,738) compared to 2,322 baht/infant (IQR 1,361, 4,414) for infants who survived.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThailand has made significant progress in improving its healthcare system over the last decade owing to the implementation of the UC scheme, which has reduced inequalities in healthcare access, particularly in rural areas. Implementation of the UC scheme succeeded in decreasing neonatal mortality by up to 13 percent [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, issues in maternal and child health still need to be addressed. This was a nationwide study on in-hospital mortality and the disease burden or comorbidities among neonates in Thailand over 6 years. The consistent decline in the birth rate each year is one of the country\u0026rsquo;s most significant challenges. The present study found that in-hospital neonatal mortality significantly decreased from 3.60 per 1,000 live births in 2015 to 3.05 per 1000 live births in 2020, with an overall NMR of 3.38 per 1,000 live births over 6 years. This trend of reducing NMR in Thailand indicates positive progress in maternal and neonatal healthcare, reflecting enhanced access to medical facilities and advancements in medical technology and practices. The results of this study were consistent with those of a previous study in 2010 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which reported that the majority of neonatal deaths occurred within seven days of life, particularly within the first three days, highlighting the critical vulnerability in the early postnatal period. As in previous studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], the leading cause of neonatal mortality was prematurity, followed by major congenital malformations and chromosomal abnormalities, which accounted for up to one-fourth of neonatal deaths. .\u003c/p\u003e \u003cp\u003eThere was a significant variation in the regional NMR, ranging from 2.35 per 1,000 in the northern region to 5.22 per 1,000 in Bangkok. This may indicate that high-risk pregnancies or critically ill neonates were transferred to specialized hospitals or academic centers in Bangkok.\u003c/p\u003e \u003cp\u003eIn the context of factors associated with neonatal mortality, extremely low birth weight was the most potent risk factor associated with a neonatal mortality rate 12.9 times higher than that of normal birth weight. This finding is consistent with a meta-analysis in which low birth weight was associated with neonatal mortality rates 9.9\u0026ndash;15.5 times higher than that of normal birth weight [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Interventions targeting improved care for preterm and low-birth-weight infants may reduce neonatal mortality[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComprehensive data from this study can help prioritize and implement appropriate interventions to prevent neonatal deaths and improve outcomes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Prematurity is the leading cause of neonatal mortality in Thailand, which is consistent with the trends in developed countries and worldwide [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Prematurity is also a risk factor for neonatal death associated with other serious complications such as respiratory problems or infections.\u003c/p\u003e \u003cp\u003eThe challenge is to identify high-risk pregnancies early and strengthen service delivery to effectively prevent premature births as well as to provide proper management of related problems. There are often signs of impending preterm delivery, and interventions such as antenatal corticosteroids, tocolytic agents, and improvements in referral systems are crucial [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In addition, interventions aimed at improving outcomes for premature and low birth weight infants, expanding quality services, and allocating resources, such as specialized neonatal care and neonatal intensive care units, should be provided according to regional needs [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Community engagement can facilitate the process by developing and strengthening linkages with local health systems, such as the Provincial Maternal and Child Health Committees and Regional Healthcare Services, to ensure better outcomes for all neonates nationwide [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study found that the second most common cause of neonatal death was congenital malformation and chromosomal abnormalities. Globally, it is the fourth leading cause of neonatal mortality, with 90% of cases involving serious disorders accounting for low- and middle-income countries [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. As the reduction of birth defects is a WHO and global priority [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], measures to integrate primary prevention programs include raising awareness about the importance of screening for fetal anomalies and improving the quality and accessibility of these screenings is crucial. In the case of prenatal detection of severe congenital abnormalities, a family meeting with a multidisciplinary team could provide comprehensive information and develop an advanced care plan that may include options for palliative care [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Additionally, supporting families with children with congenital disorders and associated disabilities should be addressed by providing appropriate care and offering necessary resources.\u003c/p\u003e \u003cp\u003eApart from low birth weight and small for gestational age, we found that conditions such as PPHN, pulmonary hemorrhage, air leak, major congenital anomalies, severe asphyxia, hypo-hyperglycemia, disturbance of sodium balance, and sepsis were associated with higher probabilities of neonatal death. Asphyxia can be prevented through effective neonatal resuscitation training for healthcare providers. Infections can be identified early and treated without delay using a simplified algorithm, and the early initiation of breastfeeding should be promoted [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Implementing strict hand hygiene and sterile techniques for invasive procedures, central venous catheter care, and antibiotic stewardship are essential strategies for reducing the risk of infection and sepsis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe strengths of this study include the large number of infants and the retrieval of data at the national level from the UC scheme in Thailand. However, the present study had some limitations that merit consideration. This study provides a 6-year trend in NMR in Thailand using data from most Thai neonates. Nevertheless, this rate may not fully represent the Thai neonatal population because births and deaths are covered by the Civil Servant Medical Benefit (CSMB) scheme, and some private hospitals are not included in the UC database. However, this is the most cost-effective method for monitoring the quality of neonatal care in our setting.\u003c/p\u003e \u003cp\u003eData were extracted from the ICD-10 and ICD-9 coding in medical records from primary through tertiary care and private hospitals nationwide. Therefore, the accuracy of the results depends on diagnosis and coding practices. Some information, such as gestational age, cannot be extracted individually. Despite the internal quality audit process at each hospital and the external audit by the Bureau of Health Policy and Strategy at the Ministry of Public Health, misclassifications may have occurred.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe birth rate and NMR in Thailand have continuously declined. Our study provides information for identifying key neonatal mortality-related issues. The variation in regional NMR underscores the need for a national health policy accompanied by comprehensive, multi-sectoral approaches to providing good pre-and postnatal care and appropriate allocation of resources per regional problems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eP.K.\u0026nbsp;conceptualized and designed the study, performed the computations, discussed the results, drafted the initial manuscript, and contributed to the final manuscript.\u0026nbsp;J.J.\u0026nbsp;discussed\u0026nbsp;the results, drafted the initial manuscript, and contributed to the final manuscript.\u0026nbsp;P.P.\u0026nbsp;and S.M.\u0026nbsp;discussed the results\u0026nbsp;and\u0026nbsp;contributed to the final manuscript.\u0026nbsp;KT performed the computations, was involved in data acquisition, was responsible for analyzing and interpreting\u0026nbsp;the data, and contributed to the final manuscript.\u0026nbsp;SS was involved in the data acquisition, discussed the results, and contributed to the final manuscript. \u0026nbsp;All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThis study received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThis study was approved by the Khon Kaen University Ethics Committee on Human Research\u0026nbsp;(HE651030)\u0026nbsp;on January 22, 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe\u0026nbsp;Center for Ethics in Human Research, Khon Kaen University,\u0026nbsp;waived the requirement for\u0026nbsp;informed\u0026nbsp;consent\u0026nbsp;because no personally identifiable data\u0026nbsp;were collected.\u0026nbsp;The authors confirmed that all methods were performed according to the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe datasets used and analyzed during the current study were from Thailand National Health Coverage, but restrictions apply to the availability of these data, which were used under license for the current study, so they are not publicly available.\u0026nbsp;However,\u0026nbsp;data are available from the authors upon reasonable request and with permission from\u0026nbsp;the Thailand National Health Coverage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe authors would like to thank the Bureau of Health Policy and Strategy at the Ministry of Public Health for the use of the data from the summary discharge of all hospitals under the National Health Coverage Scheme, the Royal College of Pediatricians of Thailand, and the Pediatric Society of Thailand for permission to analyze and report this information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUN Millennium Development Goals. Goal 4: reduce child mortality. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.un.org/millenniumgoals/childhealth.shtml\u003c/span\u003e\u003cspan address=\"https://www.un.org/millenniumgoals/childhealth.shtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHug L, Alexander M, You D, Alkema L, UN Inter-agency Group for Child Mortality Estimation. National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis. Lancet Glob Health. 2019;7(6):e710-e720. doi: 10.1016/S2214-109X(19)30163-9. Erratum in: Lancet Glob Health. 2019;7(9):e1179. PMID: 31097275; PMCID: PMC6527519.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eImproving maternal. and newborn health and survival and reducing stillbirth: progress report 2023. 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PMID: 33368142; PMCID: PMC8094626.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. (\u0026lrm;2015)\u0026lrm;. WHO recommendations on interventions to improve preterm birth outcomes. World Health Organ. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/handle/10665/183037\u003c/span\u003e\u003cspan address=\"https://iris.who.int/handle/10665/183037\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Newborn Mortality. 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(\u0026lrm;2013)\u0026lrm; Prevention and control of birth defects in South-East Asia Region: strategic framework (\u0026lrm;2013\u0026ndash;2017)\u0026lrm; WHO Regional Office for South-East Asia. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iris.who.int/handle/10665/205644\u003c/span\u003e\u003cspan address=\"https://iris.who.int/handle/10665/205644\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerinatal palliative care. ACOG Committee Opinion 786. American College of Obstetricians and Gynecologists. Obstet Gynecol. 2019;134:e84\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuetti N, Marschall J, Drees M, Fakih MG, Hadaway L, Maragakis LL, et al. Strategies to prevent central line-associated bloodstream infections in acute-care hospitals: 2022 Update. Infect Control Hosp Epidemiol. 2022;43(5):553\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/ice.2022.87\u003c/span\u003e\u003cspan address=\"10.1017/ice.2022.87\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Apr 19. PMID: 35437133; PMCID: PMC9096710.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"neonates, mortality, comorbidities, burden of disease","lastPublishedDoi":"10.21203/rs.3.rs-4798791/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4798791/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u0026nbsp; Neonatal mortality rate (NMR) is an international indicator reflecting a country’s health problems and services. This study is the most extensive nationwide effort to evaluate in-hospital mortality and disease burden among neonates in Thailand.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e:\u003cstrong\u003e \u003c/strong\u003eA descriptive-analytic study used data from neonates born in hospitals under the Universal Health Coverage Scheme between 2015 and 2020. Data were extracted from discharge summaries using the International Statistical Classification of Diseases and Related Health Problems, 10\u003csup\u003eth\u003c/sup\u003e Revision, Thai Modification (ICD-10-TM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Overall, 3,141,215 live births were recorded during the 6-year study period, and 10,623 infants died within 28 days of life. In-hospital NMR was 3.38 per 1,000 live births. The annual NMR decreased significantly from 3.60 per 1,000 in 2015 to 3.05 per 1,000 in 2020 (p-value \u0026lt;0.001). \u0026nbsp;Sixty-seven percent (n=7,149) of deaths occurred within 7 days of life (early neonatal death), and 46.7% (n=4,957) died within 3 days. The leading causes of neonatal death were disorders related to prematurity (36.3%), followed by congenital malformations and chromosomal abnormalities (23.5%), respiratory problems and persistent pulmonary hypertension of the newborn (17.8%), neonatal sepsis (12.3%), and perinatal asphyxia (7.6%). The regional NMR varied significantly, from 2.35 per 1,000 in the northern region to 5.22 per 1,000 in Bangkok. Factors significantly associated with NMR include low birth weight, small for gestational age, persistent pulmonary hypertension of the newborn, pulmonary hemorrhage, air leak, major congenital anomalies, severe asphyxia, hypo-hyperglycemia, disturbance of sodium balance, and sepsis.\u003c/p\u003e\n\u003cp\u003eCommon comorbidities among Thai neonates were neonatal jaundice (23.9%), respiratory problems (12.1%), disorders related to prematurity and low birth weight (11.1%), congenital malformations and chromosomal abnormalities (7.2%), sepsis (5.8%), and perinatal asphyxia (2.1%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe\u003cstrong\u003e \u003c/strong\u003edeclining birth rate and NMR in Thailand highlight significant changes in the country’s demographics and improvements in healthcare services. Prematurity remains the leading cause of neonatal death, emphasizing the critical need for targeted interventions in maternal and neonatal care. Regional disparities in NMR indicate uneven distribution and access to healthcare resources, suggesting that strategic allocation and improvement of perinatal and post-natal care services are necessary to address these variations and enhance overall neonatal health outcomes in Thailand.\u003c/p\u003e","manuscriptTitle":"Neonatal mortality rate and burden of disease in Thai neonates: A nationwide data analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-27 21:47:27","doi":"10.21203/rs.3.rs-4798791/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3c3f8e24-5bf0-4228-a7b4-4ce7704be8fe","owner":[],"postedDate":"August 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-02T11:23:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-27 21:47:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4798791","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4798791","identity":"rs-4798791","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}