The Associations of Maternal hemoglobin concentration during pregnancy with the risk of preterm birth

The Associations of Maternal hemoglobin concentration during pregnancy with the risk of preterm birth | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Associations of Maternal hemoglobin concentration during pregnancy with the risk of preterm birth Yuanjun Peng, Liming Qin, Xiaolin Zhou, Bingyan Xie, Qiaoqiao Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9228040/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Anemia represents the most common nutritional deficiency among pregnant women worldwide. Although anemia has been extensively studied, the relationship between its severity and maternal and fetal outcomes is not well characterized. We therefore analyzed the association between anemia severity and preterm birth at various gestational ages to identify potential risk factors for preterm delivery. This study provides scientific evidence to inform prevention strategies and improve neonatal outcomes. Methods This retrospective study enrolled pregnant women receiving early prenatal care and completing full-term maternity checkups in Nanning City between January 2022 and December 2023, with complete follow-up data on birth outcomes.. Data on general demographic characteristics and hemoglobin concentration data at different stages of pregnancy were collected from pregnant women. Univariate and multivariate logistic regression analyses were conducted to analyze the association between hemoglobin concentration and preterm birth, and restricted cubic spline was used to investigate the dose-response relationship between hemoglobin concentration at different gestational stages and preterm birth. Results A total of 180357 pregnant women were recruited, excluding those with missing birth outcomes, incomplete hemoglobin concentrations, twin deliveries, HIV/syphilis seropositivity, hepatitis B virus carrier, and abnormal blood pressure, and finally 127,305 pregnant women were included in the analysis. Multivariate logistic regression analysis demonstrated significantly elevated risks of preterm birth across anemia severity strata during the third trimester compared to normal hemoglobin concentrations controls: the risk of preterm birth was 3.43 times higher in the severe anemia group (OR: 3.43, 95% CI: 2.006–5.865), 1.53 times higher in the moderate anemia group(OR: 1.53, 95% CI: 1.410–1.660), and 1.206 times higher in the mild anemia group(OR: 1.206, 95% CI: 1.133–1.284). Dose-response analysis identified a nonlinear relationship between hemoglobin concentration and the risk of preterm birth during both the first and third trimesters, with third-trimester hemoglobin concentrations demonstrating a U-shaped relationship with preterm delivery probability. Conclusions Hemoglobin concentration in late pregnancy affects the occurrence of preterm birth and there is a U-shaped relationship between hemoglobin concentrations and the risk of preterm birth occurrence.Higher/lower maternal Hb may identify the risk of adverse pregnancy outcomes. Further research is required to investigate if this association is causal and to identify the underlying mechanisms. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Hyperhemoglobin Anemia Preterm birth Risk factors Figures Figure 1 Figure 2 1. Introduction The World Health Organization (WHO) defines preterm birth as any delivery of a live born before 37 completed weeks of gestation[ 1 ]. One study reported that an estimated 10.6% of live births worldwide were preterm in 2014. Of the 14.84 million babies born preterm in 2014[ 2 ]. The global preterm birth rate declined by an average of 0.14% annually from 2010 to 2020. By 2020, the estimated number of preterm births worldwide was approximately 13.4 million, accounting for 9.9% of all live births[ 3 ]. Although the number of preterm births is projected to continue declining, this substantial figure still indicates a severe global preterm birth situations, equivalent to one preterm birth per ten newborns. Certain studies indicated that preterm birth is considered an adverse pregnancy outcome (i.e., the inability of the fetus to continue intrauterine growth and development). Even for infants born between 34–36 weeks of gestation, Even for infants born between 34–36 weeks of gestation, the incomplete maturation of various organs and tissues poses significant challenges due to preterm complications. Although these infants may survive, they often experience long-term adverse physiological or neurodevelopmental consequences, such as bronchial dysplasia, intraventricular hemorrhage, auditory and visual impairments, cardiopulmonary hypoplasia, and language learning dysfunction. Many survivors continue to confront complex and lifelong health challenge,which can bring huge economic burden to families and society[ 4 ][ 5 ][ 6 ]. In 2000, world leaders agreed on the Millennium Development Goals (MDGs). MDG 4 called for a two-thirds reduction in the under-5 mortality rate between 1990 and 2015. However, The global under-5 mortality rate reduced by 53% (50–55%) in the past 25 years and therefore missed the MDG 4 target[ 7 ]. It has been reported that preterm birth remains the leading cause of death among children under five years old. In 2016,16% of all deaths were attributed to neonatal complications caused by preterm birth, accounting for 35% of all neonatal deaths. Preterm birth is unevenly distributed globally, with over 60% occurring in Africa and South Asia, yet it is a genuine global issue. Among these, China has as many as 1.17 million preterm infants annually, ranking second in the world in terms of the number of preterm births[ 8 ]. A cohort study of women aged 20–49 in China found that approximately 7.08% of women experienced premature birth [ 9 ], with about 7.27% of premature infants born annually, and roughly 5.01% of these premature infants die in the neonatal period[ 10 ]. The fortunate survivors of preterm birth are at a significantly higher risk of developmental delays, long-term complications, and chronic disorders during future growth and development compared to full-term infants. Therefore, improving the outcomes of preterm birth and reducing health issues and deaths caused by preterm birth still require more research and efforts. Anemia is one of the most prevalent nutritional deficiencies among pregnant women worldwide and is recognized as a significant global public health issues. One study reported that the estimated global prevalence of anemia was 24.8% from 1993 to 2005, with a prevalence among pregnant women reaching 41.8%[ 11 ]. By 2015, the global anemia prevalence had improved, and the prevalence among pregnant women had decreased to 38%[ 12 ]. Recently, a large-scale retrospective study titled "Gestational Diabetes Mellitus Prevalence Survey(GPS) Study in China " reported that the current status of anemia prevalence among pregnant women in China, which was 23.5%, with a higher prevalence in the second and third trimesters compared to the first trimester[ 13 ]. Furthermore, the prevalence of anemia was even higher among pregnant women in impoverished and rural areas, such as western China[ 14 ]. These findings indicate that anemia during pregnancy remains a considerable problem in China. Studies have demonstrated that anemia during pregnancy is associated with maternal and fetal health outcomes, and that mild anemia is associated with improved maternal and fetal survival and fetal growth [ 15 ]. However, there are discrepancies among studies regarding the impact of different hemoglobin concentrations at various stages on adverse delivery outcomes. Research has found that there is a clear dose-response relationship between hemoglobin concentrations in early, mid-to-late, and late pregnancy and birth weight; high hemoglobin concentrations (> 140 g/L) increase the risk of small for gestational age (SGA) and low birth weight (LBW) in early and late pregnancy, low hemoglobin concentrations (< 100 g/L) in mid-to-late and late pregnancy increase the risk of large for gestational age (LGA) and macrosomia[ 16 ]. However, other studies have reported no significant association between hemoglobin concentrations and LBW, SGA, or preterm birth in mid-to-late pregnancy[ 17 ][ 18 ]. Previous studies on the relationship between hemoglobin concentration and adverse pregnancy outcomes such as preterm birth have shown inconsistencies. This is partly due to fluctuations in hemoglobin concentration during pregnancy, which is a normal physiological changes in gestation, and partly because the timing of hemoglobin measurement varies across studies. Consequently, the association between hemoglobin concentration and preterm birth may differ across gestational periods. There is an urgent need for further research to investigate the relationship between hemoglobin levels and preterm birth in different pregnancy stages. This study collected hemoglobin concentrations in pregnant women during early and late stages of pregnancy in Nanning City and tracked neonatal birth outcomes to analyze the associations between anemia and high hemoglobin levels at different gestational stages with the risk of preterm birth. Restricted cubic spline analysis was employed to examine the dose-response relationship between hemoglobin concentrations and preterm birth, which aim to provide clues for identifying risk factors of preterm birth and to offer scientific evidence for preterm birth prevention, thereby improving the quality of newborn infants. 2. Materials and Methods 2.1. Data Sources The study data were derived from the Guangxi Population Health Information Service Application Platform (GPHISAP), a comprehensive health information management system established under the leadership of Guangxi Zhuang Autonomous Region Health Commission. This platform encompasses whole-life-cycle health data, with its maternal and child health module containing key datasets including antenatal care, delivery records, and pediatric healthcare. All data were entered by certified health information management professionals who undergo annual training programs. Data quality is maintained through a multi-tiered validation system comprising: (1) continuous hospital-level self-audits, (2) routine quality inspections at county, municipal, and provincial levels, and (3) built-in validation algorithms within the data entry software interface. 2.2. Study Population In this retrospective study, we collected basic information from the pregnant women, who registered during early pregnancy in Nanning city, (including their demographic and clinical characteristics, as well as follow-up pregnancy progression and outcomes) from January 2022 to December 2023 through the Guangxi Population Health Information Service Application Platform (GPHISAP). Pregnant women who met the following criteria were included in the study: (1) Natural conception, (2) singleton pregnancy, (3) card establishment before 14 weeks of gestational age, (4) pregnant women who delivered their baby after 28 weeks of gestational age. The exclusion criteria included (1) women with missing pregnancy outcomes, (2) women without the hemoglobin concentration data during pregnancy, (3) the pregnant outcome were ectopic pregnancy, induced abortion, medical termination, or stillbirth, (4) women with hypertensive disorders or gestational diabetes mellitus (GDM), (5) women infected with HIV, HBV or syphilis. The participant flow diagram (Fig. 1 ) illustrates the screening process, with 127305 subjects ultimately included in the final study. 2.3. Definition of Exposure According to the standard critical values defined by the World Health Organization (WHO) for anemia in pregnancy[ 19 ], hemoglobin concentrations were categorized as follows: ≥150 g/L was defined as high hemoglobin; 110–149 g/L as normal; 100–109 g/L as mild anemia; 70–99 g/L as moderate anemia; and < 70 g/L as severe anemia. 2.4. Definition of Outcome The primary outcome variable of the study was preterm birth, defined as delivery after 28 weeks but less than 37 completed weeks of gestation. 2.5. Statistical Analysis Continuous variables are presented as mean standard deviation (SD), while categorical parameters are described as number (N) and percentage (%). The characteristics of the study participants in the different groups were compared using the analysis of variance (ANOVA) for continuous variables and chi-square test for categorical variables. A restricted cubic spline (RCS) function was applied to analyze the associations of maternal Hb concentration and preterm birth outcomes[ 20 ]. Multinomial logistic regression models were employed to examine the association between hemoglobin concentration and preterm‑birth outcomes, with hemoglobin concentration groups defined as the independent variable and preterm birth as the dependent variable. The maternal Hb concentration at 100–119 g/L was set as the reference in each time point. Model 1 is crude Model of Hemoglobin Concentration and the Risk of Preterm Birth, Model 2 adjusted for age, education level, adverse pregnancy history, Gravida and Parity based on Model 2, Model 3 further adjusted for BMI during pregnancy based on Model 2. All the statistical analyses were performed in R software (version 4.0.3) and p < 0.05 was considered statistically significant. 3. Results 3.1 Analysis of Hemoglobin Concentration During Pregnancy Across Different Demographic Groups In the current study, the median age of the participants was 30.36 years (interquartile range (IQR): 27–34). 22.43% of the participants were older than 35 years, and 40.47% were primipara. Overall, 19297 (15.16%) women had anomalous preconception Hb concentration: 18743(14.72%) were anaemic and 554 (0.44%) had high Hb concentration. Of these individuals,51.35% were of Han ethnicity, 44.08% were Zhuang ethnicity, and 4.57% were other ethnic minorities. A total of 78.62% had a rural Household registration status, 63.55% had a early pregnancy BMI of 25–35 kg/m2, and 3.68% became pregnant through in vitro fertilization. (Table 1 ). The characteristics among different hemoglobin concentration groups in the study population is shown in Table 1 . There were statistically significant differences in residence address, household registration, mode of conception, ethnicity, age, infant gender, gravida, parity, and BMI among pregnant women with different hemoglobin concentration during the first trimester (P 35 years old, female newborns, Gravida ≥ 3 times, multipara, and lower BMI values during pregnancy. Conversely, the high hemoglobin group had lower proportions of rthese characteristics. Similarly, significant differences were found among pregnant women with varying hemoglobin concentrations in terms of residence address, household registration, mode of conception, ethnicity, age, infant gender, gravida, parity, and BMI in the third trimester, (P 35 years of age, gravida ≥ 3 times, multipara, and BMI value < 25 during pregnancy. In contrast, the high hemoglobin group showed lower proportions of rural, farmer, Zhuang ethnicity, Gravida ≥ 3 times, multipara, and BMI 35 years and female newborns (Table 1 ). Table 1 Hemoglobin concentrations by demographic characteristics Early_pregnancy Hemoglobin concentration P value Late_pregnancy Hemoglobin concentration P value overall,N(%) 150 150 Residence_address urban 93155 98(67.59) 3635(64.93) 8861(68.16) 80137(74.20) 424(76.53) < 0.001 69(66.99) 6472(70.87) 14649(67.87) 71710(74.67) 255(75.00) < 0.001 rural 34150 47(32.41) 1963(35.07) 4139(31.84) 27871(25.80) 130(23.47) 34(33.01) 2765(29.93) 6934(32.13) 24332(25.33) 85(25.00) Household_registration non-farmer 27141 16(21.33) 886(11.03) 2335(15.83) 23762(17.97) 142(22.02) < 0.001 20(19.42) 1682(18.23) 4009(18.59) 21354(22.25) 76(22.49) < 0.001 farmer 100081 129(78.67) 4711(88.97) 10658(84.17) 84172(82.03) 411(77.98) 83(80.58) 7547(81.77) 17561(81.41) 74628(77.75) 262(77.51) Mode_of_conception natural conception 121374 140(96.29) 5408(96.55) 12425(97.41) 102875(96.54) 526(96.20) < 0.001 98(95.15) 8877(96.84) 20726(96.81) 91345(96.11) 328(97.04) < 0.001 Assisted reproduction 4681 5 (3.71) 144(3.45) 445 (2.59) 4065 (3.46) 22 (3.80) 5(4.85) 290(3.16) 682(3.19) 3694(3.89) 10(2.96) Ethnicity Han 65376 67(51.35) 2573(46.21) 6202(45.96) 56250(47.71) 284(52.08) < 0.001 41(39.81) 4414(47.79) 10868(50.35) 49885(51.94) 168(49.1) < 0.001 Zhuang 56115 70(44.08) 2804(48.28) 6228(50.09) 46766(47.91) 247(43.30) 58(56.31) 4405(47.69) 9797(45.39) 41695(43.41) 160(47.06) other 5814 8 (4.57) 221(5.52) 570 (3.95) 4992 (4.38) 23 (4.62) 4(3.88) 418(4.53) 918(4.25) 4462(4.65) 12(3.53) Age_years < 25 17846 25(14.02) 1039(17.24) 2119(18.56) 14589(16.30) 74(13.51) < 0.001 15(14.56) 1617(17.51) 3461(16.04) 12709(13.23) 44(12.94) 35 28558 40(22.43) 1444(27.59) 3152(25.79) 23796(24.25) 126(22.03) 22(21.36) 2346(25.40) 5033(23.32) 21072(21.94) 85(25.00) Infant_gender male 68075 73(53.47) 2914(50.34) 6910(52.05) 57904(53.15) 274(53.61) 0.04 58(56.31) 4828(52.27) 11512(53.34) 51510(53.63) 167(49.12) 0.05 female 59229 72(46.53) 2684(49.66) 6090(47.95) 50103(46.85) 280(46.39) 45(43.69) 4409(47.73) 10071(46.66) 44531(46.37) 173(50.88) Gravida 1 33452 34(26.28) 1286(23.45) 3141(22.97) 28836(24.16) 155(26.70) < 0.001 27(26.21) 2009(21.75) 5055(23.42) 26273(27.35) 88(25.88) < 0.001 2 37074 43(29.12) 1481(29.66) 3584(26.46) 31798(27.57) 168(29.44) 18(17.48) 2616(28.32) 6016(27.87) 28321(29.49) 112(32.94) ≥ 3 56779 68(44.60) 2831(46.90) 6275(50.57) 47374(48.27) 231(43.86) 58(56.31) 4612(49.93) 10512(48.70) 41457(43.16) 140(41.18) Parity primipara 51521 54(40.47) 1946(37.24) 4868(34.76) 44401(37.45) 252(41.11) < 0.001 37(35.92) 3138(33.97) 7805(36.16) 40391(42.06) 150(44.12) < 0.001 multipara 75784 91(59.53) 3652(62.76) 8132(65.24) 63607(62.55) 302(58.89) 66(64.08) 6099(66.03) 13778(63.84) 55651(57.94) 190(55.88) BMI < 25 110453 136(86.76) 5147(93.79) 11789(91.94) 92959(90.68) 422(86.07) < 0.001 95(92.23) 8355(90.45) 19151(88.73) 82561(85.96) 291(85.59) 30 1962 1 (1.54) 47 (0.69) 129 (0.84) 1768 (0.99) 17 (1.64) 1(0.97) 103(1.12) 252(1.17) 1598(1.66) 8(2.35) 3.2 Correlation analysis between the different hemoglobin levels and preterm birth This study enrolled 127,305 pregnant women in Nanning City from 2022 to 2023. Among them, 7,122 (5.59%) experienced preterm birth. The preterm birth rates of different hemoglobin groups were 4.83%, 5.61%, 5.76%, 5.57%, and 6.32% in the first trimester, respectively. The preterm birth rate in the group with Hb concentration < 70 g/L was lower than that in the normal Hb group, while the rates in the other groups were higher than that in the normal Hb group, with no statistically significant differences. In the third trimester, the preterm birth rates across different Hb groups were 15.53%, 7.75%, 6.20%, 5.23%, and 7.65%, respectively. The preterm birth rates in all other groups were significantly higher than that in the Hb 110–150 g/L group, and these differences were statistically significant. After adjusting for all covariates, no statistically significant differences in the risk of preterm birth were found between the various degrees of anemia groups or the high hemoglobin group compared to the normal Hb group in the first trimester. However, in the third trimester, the risk of preterm birth was significantly higher in all anemia groups compared to the normal Hb group, and these differences were statistically significant. In contrast, no statistically significant difference in the risk of preterm birth was observed between the high hemoglobin group and the normal Hb group(Table 2 ). Table 2 Logistics regression analysis of hemoglobin and preterm birth during pregnancy Hemoglobin concentration preterm birth,n(%) OR(95%CI) OR(95%CI) OR(95%CI) Model 1 Model 2 Model 3 Early_pregnancy < 70 7(4.83) 0.859(0.402–1.835) 0.873(0.408–1.867) 0.852(0.398–1.824) 70–100 314(5.61) 1.007(0.896–1.132) 1.026(0.912–1.153) 1.010(0.898–1.136) 100–110 749(5.76) 1.036(0.958–1.121) 1.048(0.969–1.133) 1.036(0.958–1.121) 110–150 6017(5.57) 1 1 1 > 150 35(6.32) 1.146(0.813–1.615) 1.1442(0.810–1.609) 1.151(0.816–1.624) Late_pregnancy < 70 16(15.53) 3.366(1.972–5.744) 3.421(2.004–5.840) 3.430(2.006–5.865) 70–100 716(7.75) 1.527(1.408–1.657) 1.545(1.424–1.676) 1.530(1.410–1.660) 100–110 1338(6.20) 1.198(1.126–1.275) 1.213(1.139–1.291) 1.206(1.133–1.284) 110–150 5026(5.23) 1 1 1 > 150 26(7.65) 1.503(1.006–2.244) 1.449(0.963–2.181) 1.443(0.958–2.173) crude Model adjusted for residence address, household registration, ethnicity base on model 1 adjusted for age, infant gender, gravida, parity, BMI base on model 2 3.3 Dose-response relationship between hemoglobin concentration and preterm birth Hemoglobin concentrations during the early and late pregnancy were analyzed as continuous variables using restricted cubic spline (RCS) models, with adjustments for covariates including residential area, household registration status, maternal ethnicity, age, infant sex, gravidity, parity, and body mass index (BMI). The results revealed significant nonlinear associations between hemoglobin levels and preterm birth risk during both early and late pregnancy (P-values < 0.001). During early pregnancy, the risk of preterm birth exhibited a progressive increase when hemoglobin concentrations exceeded approximately 125 g/L. However, a U-shaped relationship was observed during the late pregnancy: preterm birth risk demonstrated an inverse correlation with hemoglobin levels below 125 g/L, while showing a positive correlation when concentrations exceed approximately 125 g/L(Fig. 2 ). 4.Discussion This study investigated the impact of hemoglobin concentrations during the first and third trimesters on preterm birth risk in Nanning city, with particular focus on characterizing the dose-response relationship between hemoglobin levels and preterm delivery. In this large cohort study of 127305 pregnant women in Nanning, Guangxi, China, the rate of preterm birth was 5.59%(7122). A prospective cohort study conducted in China from 2014 to 2018 found that the preterm birth rate was 5.2% among 51,125 pregnant women[ 21 ], another cross-sectional study reported a preterm birth rate as high as 20.6% among pregnant women in Ethiopia[ 22 ], additionally, a study incorporating data from eight population cohorts from the EU Child Cohort Network (EUCCN) found that the preterm birth rate varied between 4.9% and 10.4% across different regions in Europe[ 23 ]. The result of our study about the preterm birth rate is consistent with these studies, with only a slight increase in some economically or medically underdeveloped regions. Given the large population and the relatively underdeveloped economic and medical conditions in Guangxi, there will be projected to still experience approximately 3500 preterm births annually, imposing a substantial burden on healthcare system and socioeconomic development. Therefore, it is great to investigate potential factors contributing to preterm birth in order to improve the regional quality of life and alleviate local healthcare and economic burdens in Nanning. In this study, pregnant women were stratified by hemoglobin concentration into different anemia severity groups. Comparative analysis of preterm birth risk across different hemoglobin concentration groups during early and late pregnancy revealed that the subnormal hemoglobin groups in late pregnancy increased preterm birth risk. After adjusting for confounding factors, the high hemoglobin group no longer remained an independent risk factor for preterm birth. Furthermore, dose-response analysis demonstrated a characteristic U-shaped relationship between late-pregnancy hemoglobin concentrations and preterm birth risk. Extensive prior evidence has found the association between anemia and adverse pregnancy outcomes. A longitudinal study comparing two birth cohorts spanning 20 years found differential associations between hemoglobin concentrations and adverse perinatal outcomes across gestation periods. Low hemoglobin levels in first-trimester correlated with reduced risk of small for gestational age (SGA) infants (OR = 0.73, 95%CI:0.58–0.93), while low hemoglobin concentrations in third-trimester were linked to increased preterm birth risk (OR = 1.60, 95%CI:1.26–2.02)[ 24 ]. Burden et al.[ 25 ]investigated the association between maternal hemoglobin concentrations level and adverse pregnancy outcomes in two large prospective cohorts in the UK, which found that there were not statistically significant between the hemoglobin concentrations and preterm birth (PTB), low birth weight (LBW), or small-for-gestational-age (SGA) in first-trimester. However, elevated hemoglobin concentrations significantly were associated with PTB, LBW, and SGA in third-trimester. The authors reported findings regarding hemoglobin's association with preeclampsia and gestational diabetes mellitus - one cohort showed increased adverse outcomes with hemoglobin elevation (OR range:1.35–1.53) while the other haved no effects. Lanlan Wu et al. (PMID: 35387646) demonstrated the associations between the hemoglobin concentrations and pregnancy outcomes through a retrospective cohort study, in the second (16-18th weeks) trimesters of pregnancy, maternal hemoglobin concentration > 130 g/L increased the risk of low birth weight (LBW). In the third (28-30th weeks) trimesters of pregnancy, maternal hemoglobin concentration > 130 g/L increases the risk of low birth weight (LB) and small-for-gestational-age infants (SGA). However, comparative analysis across trimesters revealed adjusted ORs of 0.35 (95% CI: 0.18–0.68) for preterm birth (PTB) and 0.47 (95% CI: 0.23–0.98) for LBW, with risk reductions for PTB and SGA observed upon appropriate third-trimester hemoglobin elevation. Melissa F Young et al.[ 26 ]established that both hypo- and hyper-hemoglobinemia during any gestational period correlated with preterm delivery, confirming that extreme hemoglobin concentrations constitute robust predictors of adverse maternal-fetal outcomes. In our study, we found no association between either low or high hemoglobin levels in early pregnancy and preterm birth, but identified that low hemoglobin concentrations in late pregnancy increased the risk of preterm delivery, while there were no significant between high hemoglobin levels and preterm birth. Although most studies have reported that elevated hemoglobin concentrations increase the risk of preterm birth, some researchers have reported divergent findings. A cross-sectional study in Indian demonstrated that varying degrees of anemia were associated with risks of both preterm birth and low birth weight, whereas high hemoglobin concentrations showed no association with either outcome[ 27 ], consistent with our findings. The inconsistencies among studies may be attributed to differing definitions of "anemia" and "high hemoglobin," as well as variations in hemoglobin measurements at different gestational ages. Whether anemia serves as a protective factor against preterm birth and how to effectively reduce preterm birth rates remain subjects for future studies. Hemoglobin concentration is closely associated with pregnancy outcomes. Anemia during pregnancy may result from nutritional deficiencies, including iron, folate, vitamin A, and vitamin B12, with iron deficiency accounting for 75% of gestational anemia cases[ 28 ]. Iron deficiency during pregnancy results from inadequate dietary intake compounded by increased systemic demand, impaired absorption, or blood loss. Iron requirements and absorption dynamics fluctuate throughout gestation: first-trimester demands decrease, followed by plasma volume and erythrocyte mass expansion in the second and third trimesters due to placental demands, fetal growth, maternal erythropoiesis, and iron store replenishment. Late-pregnancy iron requirements and absorption surge over threefold[ 29 ][ 30 ]. Iron deficiency anemia (IDA) correlates with adverse pregnant outcomes in offspring, including low birth weight, intrauterine growth restriction, preterm birth (PTB), and neonatal anemia. The RCS analysis revealed a characteristic U-shaped relationship between hemoglobin concentrations and preterm birth risk, indicating that both hypo- and hyper-hemoglobinemia can increase the risk of the preterm. Therefore, it is essential to continuously monitor changes in hemoglobin concentration during pregnancy and and timely prevent adverse pregnancy outcomes such as preterm birth. Previous studies have demonstrated a dose-response relationship between hemoglobin concentration and adverse pregnancy outcomes. A Chinese retrospective study corroborated these findings, demonstrating significant associations between hemoglobin levels and intrauterine fetal demise (IUFD) or small-for-gestational-age infants, with elevated hemoglobin linked to SGA, neonatal asphyxia, and NICU admissions[ 31 ]. Malshani L Pathirathna identified 110–129 g/L as the optimal first-trimester hemoglobin range for minimizing preterm birth[ 32 ]. Distinctively, our study modeled hemoglobin as a continuous variable, providing clearer and intuitive representation of the exposure-response relationship between hemoglobin concentration and preterm birth. There were several strengths to this study. First, the data for this study were sourced from the Guangxi Population Health Information Service Application Platform, ensuring a reliable data foundation, which encompassed all maternity care facilities in Nanning. Second, we analyzed the relationship between maternal hemoglobin concentrations and preterm birth at two critical gestational timepoints (first and third trimesters). These findings provide important scientific evidence for antenatal care.However, several limitations must be acknowledged. The study focused solely on Nanning, Guangxi Zhuang Autonomous Region, introducing regional and demographic constraints. Additionally, we lacked data on underlying etiologies of anemia/hyperhemoglobinemia (such as serum iron levels, micro-nutrient levels) and other key risk factors. Future studies should collect more critical data on anemia-related influencing factors to validate the findings of this research. Declarations Ethics approval and consent to participate This study adhered to the Declaration of Helsinki, and was approved by the Ethics Committee of Nanning Maternal and Child Health Hospital. All methods were performed in accordance with the relevant guidelines and regulations of the institutional ethical review board and in accordance with the Declaration of Helsinki Informed written consent was waived due to the retrospective design. Consent for publication Not applicable. Competing Interests The authors declare no competing interests. Funding This study was supported by funds from the first batch of university-level research projects of Youjiang Medical University for Nationalities in 2025 (yy2025ky121) Author Contribution MLQ designed the study. QLM, ZXL, XBY, ZQQ, HYQ and LMZ contributed to the information collection, data analysis and interpretation. PYJ drafted the manuscript and revised the final version and are guarantors of this manuscript. All authors reviewed and approved the final manuscript. Acknowledgements Not applicable. Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References WHO. recommended definitions, terminology and format for statistical tables related to the perinatal period and use of a new certificate for cause of perinatal deaths. Modifications recommended by FIGO as amended October 14, 1976. Acta Obstet. Gynecol. Scand. 56 (3), 247–253 (1977). Chawanpaiboon, S. et al. Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. Lancet Glob Health . 7 (1), e37–e46. 10.1016/S2214-109X(18)30451-0 (2019). Ohuma, E. O. et al. National, regional, and global estimates of preterm birth in 2020, with trends from 2010: a systematic analysis. Lancet 402 (10409), 1261–1271. 10.1016/S0140-6736(23)00878-4 (2023). Ibrahim, H. et al. Narrative review of neurodevelopmental and psychiatric complications associated with prematurity. BMC Pediatr. 25 (1), 933. 10.1186/s12887-025-06306-z (2025). Published 2025 Nov 14. Teune, M. J. et al. A systematic review of severe morbidity in infants born late preterm. Am. J. Obstet. Gynecol. 205 (4), 374. .e1-374.e3749 (2011). Palumbi, R. et al. Neurodevelopmental and emotional-behavioral outcomes in late-preterm infants: an observational descriptive case study. BMC Pediatr. ;18(1):318. Published 2018 Oct 8. (2018). 10.1186/s12887-018-1293-6 You, D. et al. Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. Lancet 386 (10010), 2275–2286. 10.1016/S0140-6736(15)00120-8 (2015). Liu, L. et al. Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet 388 (10063), 3027–3035. 10.1016/S0140-6736(16)31593-8 (2016). Zhang, X. et al. Preconception Hb concentration and risk of preterm birth in over 2·7 million Chinese women aged 20–49 years: a population-based cohort study. Br. J. Nutr. 120 (5), 508–516. 10.1017/S0007114518001721 (2018). Yan JunMei, H. et al. A single-center study on the incidence and mortality of preterm infants from 2006 to 2016[J].Chinese Journal of Contemporary Pediatrics,2018, 20 (05):368–372 . McLean, E. et al. Worldwide prevalence of anaemia, WHO Vitamin and Mineral Nutrition Information System, 1993–2005. Public. Health Nutr. 12 (4), 444–454. 10.1017/S1368980008002401 (2009). Stevens, G. A. et al. Global, regional, and national trends in haemoglobin concentration and prevalence of total and severe anaemia in children and pregnant and non-pregnant women for 1995–2011: a systematic analysis of population-representative data. Lancet Glob Health . 1 (1), e16–e25. 10.1016/S2214-109X(13)70001-9 (2013). Lin, L. et al. Prevalence, risk factors and associated adverse pregnancy outcomes of anaemia in Chinese pregnant women: a multicentre retrospective study. BMC Pregnancy Childbirth. ;18(1):111. Published 2018 Apr 23. (2018). 10.1186/s12884-018-1739-8 Pei, L. et al. Assessment of maternal anemia in rural Western China between 2001 and 2005: a two-level logistic regression approach. BMC Public Health. ;13:366. Published 2013 Apr 19. (2013). 10.1186/1471-2458-13-366 Shi, H. et al. Severity of Anemia During Pregnancy and Adverse Maternal and Fetal Outcomes. JAMA Netw. Open. 5 (2), e2147046. 10.1001/jamanetworkopen.2021.47046 (2022). Published 2022 Feb 1. Peng, Z. et al. The Associations of Maternal Hemoglobin Concentration in Different Time Points and Its Changes during Pregnancy with Birth Weight Outcomes. Nutrients 14 (12), 2542. 10.3390/nu14122542 (2022). Published 2022 Jun 19. Dewey, K. G. & Oaks, B. M. U-shaped curve for risk associated with maternal hemoglobin, iron status, or iron supplementation. Am. J. Clin. Nutr. 106 (Suppl 6), 1694S–1702S. 10.3945/ajcn.117.156075 (2017). Rahmati, S. et al. Maternal Anemia during pregnancy and infant low birth weight: A systematic review and Meta-analysis. Int. J. Reprod. Biomed. 15 (3), 125–134 (2017). WHO. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity [Z]. (2011). Perperoglou, A. et al. A review of spline function procedures in R. BMC Med. Res. Methodol. 19 , 46 (2019). Gong, Y. et al. A prospective analysis of optimal total weight gain ranges and trimester-specific weight gain rates for Chinese pregnant women. BMC Pregnancy Childbirth. ;23(1):60. Published 2023 Jan 24. (2023). 10.1186/s12884-023-05398-8 Negesse, Y. & Abebe, G. F. The bayesian approach of factors associated with preterm birth among mothers delivered at public hospitals in Southeast Ethiopia. Front. Public. Health . 10 , 881963. 10.3389/fpubh.2022.881963 (2023). Published 2023 Jan 9. Elhakeem, A. et al. Effect of common pregnancy and perinatal complications on offspring metabolic traits across the life course: a multi-cohort study. BMC Med. ;21(1):23. Published 2023 Jan 18. (2023). 10.1186/s12916-022-02711-8 Ronkainen, J. et al. Maternal hemoglobin associates with preterm delivery and small for gestational age in two Finnish birth cohorts. Eur. J. Obstet. Gynecol. Reprod. Biol. 238 , 44–48. 10.1016/j.ejogrb.2019.04.045 (2019). Burden, C. A., Smith, G. C., Sovio, U., Clayton, G. L. & Fraser, A. Maternal hemoglobin levels and adverse pregnancy outcomes: individual patient data analysis from 2 prospective UK pregnancy cohorts. Am. J. Clin. Nutr. 117 (3), 616–624. 10.1016/j.ajcnut.2022.10.011 (2023). Young, M. F. et al. Maternal low and high hemoglobin concentrations and associations with adverse maternal and infant health outcomes: an updated global systematic review and meta-analysis. BMC Pregnancy Childbirth. ;23(1):264. Published 2023 Apr 19. (2023). 10.1186/s12884-023-05489-6 Kumari, S. et al. Maternal and severe anaemia in delivering women is associated with risk of preterm and low birth weight: A cross sectional study from Jharkhand, India. One Health . 8 , 100098. 10.1016/j.onehlt.2019.100098 (2019). Published 2019 Aug 19. Di Renzo, G. C. et al. Iron deficiency anemia in pregnancy. Womens Health (Lond) . 11 (6), 891–900. 10.2217/whe.15.35 (2015). Wawer, A. A., Hodyl, N. A., Fairweather-Tait, S. & Froessler, B. Are Pregnant Women Who Are Living with Overweight or Obesity at Greater Risk of Developing Iron Deficiency/Anaemia? Nutrients 13 (5), 1572. 10.3390/nu13051572 (2021). Published 2021 May 7. Lynch, S. et al. Biomarkers of Nutrition for Development (BOND)-Iron Review. J. Nutr. 148 (suppl_1), 1001S–1067S. 10.1093/jn/nxx036 (2018). Lian, Y., Lv, Y., Qiao, Y. & He, T. Relationships between hemoglobin levels at admission and adverse maternal and perinatal outcomes in patients with preeclampsia. PLoS One. ;20(10):e0335079. Published 2025 Oct 16. (2025). 10.1371/journal.pone.0335079 Pathirathna, M. L. et al. Maternal Hemoglobin Concentrations in Early and Late Pregnancy and Adverse Birth Outcomes: A Nationwide Cohort Study in Sri Lanka. J. Nutr. 155 (11), 3938–3948. 10.1016/j.tjnut.2025.06.029 (2025). 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. 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Qin","email":"","orcid":"","institution":"Nanning Maternal and Child Health Hospital Affiliated to Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Liming","middleName":"","lastName":"Qin","suffix":""},{"id":625445897,"identity":"6fcaeaa7-ba94-4307-946d-ba1fe3c45736","order_by":2,"name":"Xiaolin Zhou","email":"","orcid":"","institution":"Nanning Maternal and Child Health Hospital Affiliated to Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Xiaolin","middleName":"","lastName":"Zhou","suffix":""},{"id":625445898,"identity":"85593e72-2a95-4c8d-a761-56caf56122df","order_by":3,"name":"Bingyan Xie","email":"","orcid":"","institution":"Nanning Maternal and Child Health Hospital Affiliated to Youjiang Medical University for 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Health Hospital Affiliated to Youjiang Medical University for Nationalities","correspondingAuthor":false,"prefix":"","firstName":"Mingzhen","middleName":"","lastName":"Liang","suffix":""},{"id":625445902,"identity":"3907d9eb-b651-455a-8204-2f4947c9a098","order_by":7,"name":"Liangqin Mao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBACNmbmgw8+VNjIybM3EKmFj50t2XDGmTRjw54DRGqR4+cxE+ZtO5zYcCOBaIfxmDHOYGNObJz5eOMNhhqbaCK0sJU9+MDDZtwunVZswXAsLbeBsBbm7YYzJHhkG2fnmEkwNhwmRguDmTSPAVDxzTNEa2EBakkwUGy4wUO0FlAgH0gABjLQLwnE+EW+//DBBx///QdG5eGNNz7U2BDWggwMJBJIUQ7RQqqOUTAKRsEoGBkAAFmHO4xBI5mLAAAAAElFTkSuQmCC","orcid":"","institution":"Nanning Maternal and Child Health Hospital Affiliated to Youjiang Medical University for Nationalities","correspondingAuthor":true,"prefix":"","firstName":"Liangqin","middleName":"","lastName":"Mao","suffix":""}],"badges":[],"createdAt":"2026-03-26 01:53:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9228040/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9228040/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107832738,"identity":"5fe83ddf-77b5-490b-9bae-d86c11cec19f","added_by":"auto","created_at":"2026-04-26 15:35:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97838,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of the study participants in Nanning, Guangxi, China from 2022-2023.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9228040/v1/bf6f5ce13b5543f72f22d145.png"},{"id":107832739,"identity":"28abf31f-c3a2-4e73-a9f1-8aa3d721f7a3","added_by":"auto","created_at":"2026-04-26 15:35:59","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":246739,"visible":true,"origin":"","legend":"\u003cp\u003eDose-response relationship curve between hemoglobin concentration during pregnancy and the risk of preterm delivery.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9228040/v1/c09c09fd8301ca6a5fe8b834.jpeg"},{"id":109297867,"identity":"dad0e07b-abb8-4fdf-916a-6fab110d42cd","added_by":"auto","created_at":"2026-05-15 09:07:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":679122,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9228040/v1/9d49fafa-57a3-4af6-930e-7c1900647b03.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Associations of Maternal hemoglobin concentration during pregnancy with the risk of preterm birth","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe World Health Organization (WHO) defines preterm birth as any delivery of a live born before 37 completed weeks of gestation[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. One study reported that an estimated 10.6% of live births worldwide were preterm in 2014. Of the 14.84\u0026nbsp;million babies born preterm in 2014[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The global preterm birth rate declined by an average of 0.14% annually from 2010 to 2020. By 2020, the estimated number of preterm births worldwide was approximately 13.4\u0026nbsp;million, accounting for 9.9% of all live births[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although the number of preterm births is projected to continue declining, this substantial figure still indicates a severe global preterm birth situations, equivalent to one preterm birth per ten newborns. Certain studies indicated that preterm birth is considered an adverse pregnancy outcome (i.e., the inability of the fetus to continue intrauterine growth and development). Even for infants born between 34\u0026ndash;36 weeks of gestation, Even for infants born between 34\u0026ndash;36 weeks of gestation, the incomplete maturation of various organs and tissues poses significant challenges due to preterm complications. Although these infants may survive, they often experience long-term adverse physiological or neurodevelopmental consequences, such as bronchial dysplasia, intraventricular hemorrhage, auditory and visual impairments, cardiopulmonary hypoplasia, and language learning dysfunction. Many survivors continue to confront complex and lifelong health challenge,which can bring huge economic burden to families and society[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In 2000, world leaders agreed on the Millennium Development Goals (MDGs). MDG 4 called for a two-thirds reduction in the under-5 mortality rate between 1990 and 2015. However, The global under-5 mortality rate reduced by 53% (50\u0026ndash;55%) in the past 25 years and therefore missed the MDG 4 target[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt has been reported that preterm birth remains the leading cause of death among children under five years old. In 2016,16% of all deaths were attributed to neonatal complications caused by preterm birth, accounting for 35% of all neonatal deaths. Preterm birth is unevenly distributed globally, with over 60% occurring in Africa and South Asia, yet it is a genuine global issue. Among these, China has as many as 1.17\u0026nbsp;million preterm infants annually, ranking second in the world in terms of the number of preterm births[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. A cohort study of women aged 20\u0026ndash;49 in China found that approximately 7.08% of women experienced premature birth [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], with about 7.27% of premature infants born annually, and roughly 5.01% of these premature infants die in the neonatal period[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The fortunate survivors of preterm birth are at a significantly higher risk of developmental delays, long-term complications, and chronic disorders during future growth and development compared to full-term infants. Therefore, improving the outcomes of preterm birth and reducing health issues and deaths caused by preterm birth still require more research and efforts.\u003c/p\u003e \u003cp\u003eAnemia is one of the most prevalent nutritional deficiencies among pregnant women worldwide and is recognized as a significant global public health issues. One study reported that the estimated global prevalence of anemia was 24.8% from 1993 to 2005, with a prevalence among pregnant women reaching 41.8%[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. By 2015, the global anemia prevalence had improved, and the prevalence among pregnant women had decreased to 38%[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Recently, a large-scale retrospective study titled \"Gestational Diabetes Mellitus Prevalence Survey(GPS) Study in China \" reported that the current status of anemia prevalence among pregnant women in China, which was 23.5%, with a higher prevalence in the second and third trimesters compared to the first trimester[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, the prevalence of anemia was even higher among pregnant women in impoverished and rural areas, such as western China[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These findings indicate that anemia during pregnancy remains a considerable problem in China.\u003c/p\u003e \u003cp\u003eStudies have demonstrated that anemia during pregnancy is associated with maternal and fetal health outcomes, and that mild anemia is associated with improved maternal and fetal survival and fetal growth [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, there are discrepancies among studies regarding the impact of different hemoglobin concentrations at various stages on adverse delivery outcomes. Research has found that there is a clear dose-response relationship between hemoglobin concentrations in early, mid-to-late, and late pregnancy and birth weight; high hemoglobin concentrations (\u0026gt;\u0026thinsp;140 g/L) increase the risk of small for gestational age (SGA) and low birth weight (LBW) in early and late pregnancy, low hemoglobin concentrations (\u0026lt;\u0026thinsp;100 g/L) in mid-to-late and late pregnancy increase the risk of large for gestational age (LGA) and macrosomia[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, other studies have reported no significant association between hemoglobin concentrations and LBW, SGA, or preterm birth in mid-to-late pregnancy[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e][\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Previous studies on the relationship between hemoglobin concentration and adverse pregnancy outcomes such as preterm birth have shown inconsistencies. This is partly due to fluctuations in hemoglobin concentration during pregnancy, which is a normal physiological changes in gestation, and partly because the timing of hemoglobin measurement varies across studies. Consequently, the association between hemoglobin concentration and preterm birth may differ across gestational periods. There is an urgent need for further research to investigate the relationship between hemoglobin levels and preterm birth in different pregnancy stages.\u003c/p\u003e \u003cp\u003eThis study collected hemoglobin concentrations in pregnant women during early and late stages of pregnancy in Nanning City and tracked neonatal birth outcomes to analyze the associations between anemia and high hemoglobin levels at different gestational stages with the risk of preterm birth. Restricted cubic spline analysis was employed to examine the dose-response relationship between hemoglobin concentrations and preterm birth, which aim to provide clues for identifying risk factors of preterm birth and to offer scientific evidence for preterm birth prevention, thereby improving the quality of newborn infants.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Data Sources\u003c/h2\u003e \u003cp\u003eThe study data were derived from the Guangxi Population Health Information Service Application Platform (GPHISAP), a comprehensive health information management system established under the leadership of Guangxi Zhuang Autonomous Region Health Commission. This platform encompasses whole-life-cycle health data, with its maternal and child health module containing key datasets including antenatal care, delivery records, and pediatric healthcare. All data were entered by certified health information management professionals who undergo annual training programs. Data quality is maintained through a multi-tiered validation system comprising: (1) continuous hospital-level self-audits, (2) routine quality inspections at county, municipal, and provincial levels, and (3) built-in validation algorithms within the data entry software interface.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study Population\u003c/h2\u003e \u003cp\u003eIn this retrospective study, we collected basic information from the pregnant women, who registered during early pregnancy in Nanning city, (including their demographic and clinical characteristics, as well as follow-up pregnancy progression and outcomes) from January 2022 to December 2023 through the Guangxi Population Health Information Service Application Platform (GPHISAP). Pregnant women who met the following criteria were included in the study: (1) Natural conception, (2) singleton pregnancy, (3) card establishment before 14 weeks of gestational age, (4) pregnant women who delivered their baby after 28 weeks of gestational age. The exclusion criteria included (1) women with missing pregnancy outcomes, (2) women without the hemoglobin concentration data during pregnancy, (3) the pregnant outcome were ectopic pregnancy, induced abortion, medical termination, or stillbirth, (4) women with hypertensive disorders or gestational diabetes mellitus (GDM), (5) women infected with HIV, HBV or syphilis. The participant flow diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) illustrates the screening process, with 127305 subjects ultimately included in the final study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Definition of Exposure\u003c/h2\u003e \u003cp\u003eAccording to the standard critical values defined by the World Health Organization (WHO) for anemia in pregnancy[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], hemoglobin concentrations were categorized as follows: \u0026ge;150 g/L was defined as high hemoglobin; 110\u0026ndash;149 g/L as normal; 100\u0026ndash;109 g/L as mild anemia; 70\u0026ndash;99 g/L as moderate anemia; and \u0026lt;\u0026thinsp;70 g/L as severe anemia.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Definition of Outcome\u003c/h2\u003e \u003cp\u003eThe primary outcome variable of the study was preterm birth, defined as delivery after 28 weeks but less than 37 completed weeks of gestation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are presented as mean standard deviation (SD), while categorical parameters are described as number (N) and percentage (%). The characteristics of the study participants in the different groups were compared using the analysis of variance (ANOVA) for continuous variables and chi-square test for categorical variables. A restricted cubic spline (RCS) function was applied to analyze the associations of maternal Hb concentration and preterm birth outcomes[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Multinomial logistic regression models were employed to examine the association between hemoglobin concentration and preterm‑birth outcomes, with hemoglobin concentration groups defined as the independent variable and preterm birth as the dependent variable. The maternal Hb concentration at 100\u0026ndash;119 g/L was set as the reference in each time point. Model 1 is crude Model of Hemoglobin Concentration and the Risk of Preterm Birth, Model 2 adjusted for age, education level, adverse pregnancy history, Gravida and Parity based on Model 2, Model 3 further adjusted for BMI during pregnancy based on Model 2. All the statistical analyses were performed in R software (version 4.0.3) and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Analysis of Hemoglobin Concentration During Pregnancy Across Different Demographic Groups\u003c/h2\u003e \u003cp\u003eIn the current study, the median age of the participants was 30.36 years (interquartile range (IQR): 27\u0026ndash;34). 22.43% of the participants were older than 35 years, and 40.47% were primipara. Overall, 19297 (15.16%) women had anomalous preconception Hb concentration: 18743(14.72%) were anaemic and 554 (0.44%) had high Hb concentration. Of these individuals,51.35% were of Han ethnicity, 44.08% were Zhuang ethnicity, and 4.57% were other ethnic minorities. A total of 78.62% had a rural Household registration status, 63.55% had a early pregnancy BMI of 25\u0026ndash;35 kg/m2, and 3.68% became pregnant through in vitro fertilization. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe characteristics among different hemoglobin concentration groups in the study population is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There were statistically significant differences in residence address, household registration, mode of conception, ethnicity, age, infant gender, gravida, parity, and BMI among pregnant women with different hemoglobin concentration during the first trimester (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with the normal hemoglobin group, the first-trimester anemia groupr had higher proportions of rural, farmer, Zhuang ethnicity,\u0026gt;35 years old, female newborns, Gravida\u0026thinsp;\u0026ge;\u0026thinsp;3 times, multipara, and lower BMI values during pregnancy. Conversely, the high hemoglobin group had lower proportions of rthese characteristics. Similarly, significant differences were found among pregnant women with varying hemoglobin concentrations in terms of residence address, household registration, mode of conception, ethnicity, age, infant gender, gravida, parity, and BMI in the third trimester, (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared to the normal hemoglobin group, the anemic group exhibited higher proportions of rural, farmer, Zhuang ethnicity,\u0026gt;35 years of age, gravida\u0026thinsp;\u0026ge;\u0026thinsp;3 times, multipara, and BMI value\u0026thinsp;\u0026lt;\u0026thinsp;25 during pregnancy. In contrast, the high hemoglobin group showed lower proportions of rural, farmer, Zhuang ethnicity, Gravida\u0026thinsp;\u0026ge;\u0026thinsp;3 times, multipara, and BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 during pregnancy, but higher proportions of age\u0026thinsp;\u0026gt;\u0026thinsp;35 years and female newborns (Table\u0026nbsp;\u003cspan refid=\"Tab1\" 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\u003eHemoglobin concentrations by demographic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\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=\"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=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eEarly_pregnancy Hemoglobin concentration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c14\" namest=\"c10\"\u003e \u003cp\u003eLate_pregnancy Hemoglobin concentration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoverall,N(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\u0026ndash;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u0026ndash;110\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110\u0026ndash;150\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;150\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e70\u0026ndash;100\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e100\u0026ndash;110\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e110\u0026ndash;150\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;150\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence_address\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eurban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98(67.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3635(64.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8861(68.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80137(74.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e424(76.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e69(66.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6472(70.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e14649(67.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e71710(74.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e255(75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003erural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(32.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1963(35.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4139(31.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27871(25.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e130(23.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e34(33.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2765(29.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6934(32.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e24332(25.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e85(25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold_registration\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enon-farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(21.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e886(11.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2335(15.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23762(17.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e142(22.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e20(19.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1682(18.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4009(18.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e21354(22.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e76(22.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003efarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129(78.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4711(88.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10658(84.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84172(82.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e411(77.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e83(80.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7547(81.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e17561(81.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e74628(77.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e262(77.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMode_of_conception\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enatural conception\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140(96.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5408(96.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12425(97.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e102875(96.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e526(96.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e98(95.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8877(96.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e20726(96.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e91345(96.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e328(97.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003eAssisted reproduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003e(3.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144(3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e445\u003c/p\u003e \u003cp\u003e(2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4065\u003c/p\u003e \u003cp\u003e(3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003cp\u003e(3.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5(4.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e290(3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e682(3.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e3694(3.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e10(2.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67(51.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2573(46.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6202(45.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56250(47.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e284(52.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e41(39.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4414(47.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e10868(50.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e49885(51.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e168(49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003eZhuang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70(44.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2804(48.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6228(50.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46766(47.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e247(43.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e58(56.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4405(47.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e9797(45.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e41695(43.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e160(47.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(4.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e221(5.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e570\u003c/p\u003e \u003cp\u003e(3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4992\u003c/p\u003e \u003cp\u003e(4.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003cp\u003e(4.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4(3.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e418(4.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e918(4.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e4462(4.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e12(3.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge_years\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(14.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1039(17.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2119(18.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14589(16.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74(13.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e15(14.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1617(17.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3461(16.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e12709(13.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e44(12.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003e25\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(63.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3115(55.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7729(55.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69623(59.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e354(64.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e66(64.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5274(57.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e13089(60.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e62261(64.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e211(62.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(22.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1444(27.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3152(25.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23796(24.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e126(22.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e22(21.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2346(25.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e5033(23.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e21072(21.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e85(25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfant_gender\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(53.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2914(50.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6910(52.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57904(53.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e274(53.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e58(56.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4828(52.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e11512(53.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e51510(53.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e167(49.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e0.05\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72(46.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2684(49.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6090(47.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50103(46.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e280(46.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e45(43.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4409(47.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e10071(46.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e44531(46.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e173(50.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravida\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(26.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1286(23.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3141(22.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28836(24.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e155(26.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e27(26.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2009(21.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e5055(23.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e26273(27.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e88(25.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(29.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1481(29.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3584(26.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31798(27.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e168(29.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e18(17.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2616(28.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e6016(27.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e28321(29.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e112(32.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68(44.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2831(46.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6275(50.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47374(48.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e231(43.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e58(56.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4612(49.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e10512(48.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e41457(43.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e140(41.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eprimipara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54(40.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1946(37.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4868(34.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44401(37.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e252(41.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e37(35.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3138(33.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e7805(36.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e40391(42.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e150(44.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003emultipara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91(59.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3652(62.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8132(65.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63607(62.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e302(58.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e66(64.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6099(66.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e13778(63.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e55651(57.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e190(55.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\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 \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136(86.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5147(93.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11789(91.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92959(90.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e422(86.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e95(92.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8355(90.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e19151(88.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e82561(85.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e291(85.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\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\u003e25\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(11.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e404(5.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1082\u003c/p\u003e \u003cp\u003e(7.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13281(8.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e115(12.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7(6.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e779(8.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2180(10.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e11883(12.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e41(12.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e(1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003cp\u003e(0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e129\u003c/p\u003e \u003cp\u003e(0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1768\u003c/p\u003e \u003cp\u003e(0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17\u003c/p\u003e \u003cp\u003e(1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1(0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e103(1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e252(1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1598(1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e8(2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Correlation analysis between the different hemoglobin levels and preterm birth\u003c/h2\u003e \u003cp\u003eThis study enrolled 127,305 pregnant women in Nanning City from 2022 to 2023. Among them, 7,122 (5.59%) experienced preterm birth. The preterm birth rates of different hemoglobin groups were 4.83%, 5.61%, 5.76%, 5.57%, and 6.32% in the first trimester, respectively. The preterm birth rate in the group with Hb concentration\u0026thinsp;\u0026lt;\u0026thinsp;70 g/L was lower than that in the normal Hb group, while the rates in the other groups were higher than that in the normal Hb group, with no statistically significant differences. In the third trimester, the preterm birth rates across different Hb groups were 15.53%, 7.75%, 6.20%, 5.23%, and 7.65%, respectively. The preterm birth rates in all other groups were significantly higher than that in the Hb 110\u0026ndash;150 g/L group, and these differences were statistically significant. After adjusting for all covariates, no statistically significant differences in the risk of preterm birth were found between the various degrees of anemia groups or the high hemoglobin group compared to the normal Hb group in the first trimester. However, in the third trimester, the risk of preterm birth was significantly higher in all anemia groups compared to the normal Hb group, and these differences were statistically significant. In contrast, no statistically significant difference in the risk of preterm birth was observed between the high hemoglobin group and the normal Hb group(Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eLogistics regression analysis of hemoglobin and preterm birth during pregnancy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHemoglobin concentration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003epreterm birth,n(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly_pregnancy\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7(4.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.859(0.402\u0026ndash;1.835)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.873(0.408\u0026ndash;1.867)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.852(0.398\u0026ndash;1.824)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e314(5.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.007(0.896\u0026ndash;1.132)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.026(0.912\u0026ndash;1.153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.010(0.898\u0026ndash;1.136)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u0026ndash;110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e749(5.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.036(0.958\u0026ndash;1.121)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.048(0.969\u0026ndash;1.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.036(0.958\u0026ndash;1.121)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e110\u0026ndash;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6017(5.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35(6.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.146(0.813\u0026ndash;1.615)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1442(0.810\u0026ndash;1.609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.151(0.816\u0026ndash;1.624)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLate_pregnancy\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16(15.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.366(1.972\u0026ndash;5.744)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.421(2.004\u0026ndash;5.840)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.430(2.006\u0026ndash;5.865)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e716(7.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.527(1.408\u0026ndash;1.657)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.545(1.424\u0026ndash;1.676)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.530(1.410\u0026ndash;1.660)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u0026ndash;110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1338(6.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.198(1.126\u0026ndash;1.275)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.213(1.139\u0026ndash;1.291)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.206(1.133\u0026ndash;1.284)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e110\u0026ndash;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5026(5.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26(7.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.503(1.006\u0026ndash;2.244)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.449(0.963\u0026ndash;2.181)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.443(0.958\u0026ndash;2.173)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecrude Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eadjusted for residence address, household registration, ethnicity base on model 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eadjusted for age, infant gender, gravida, parity, BMI base on model 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Dose-response relationship between hemoglobin concentration and preterm birth\u003c/h2\u003e \u003cp\u003eHemoglobin concentrations during the early and late pregnancy were analyzed as continuous variables using restricted cubic spline (RCS) models, with adjustments for covariates including residential area, household registration status, maternal ethnicity, age, infant sex, gravidity, parity, and body mass index (BMI). The results revealed significant nonlinear associations between hemoglobin levels and preterm birth risk during both early and late pregnancy (P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.001). During early pregnancy, the risk of preterm birth exhibited a progressive increase when hemoglobin concentrations exceeded approximately 125 g/L. However, a U-shaped relationship was observed during the late pregnancy: preterm birth risk demonstrated an inverse correlation with hemoglobin levels below 125 g/L, while showing a positive correlation when concentrations exceed approximately 125 g/L(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4.Discussion","content":"\u003cp\u003eThis study investigated the impact of hemoglobin concentrations during the first and third trimesters on preterm birth risk in Nanning city, with particular focus on characterizing the dose-response relationship between hemoglobin levels and preterm delivery.\u003c/p\u003e \u003cp\u003eIn this large cohort study of 127305 pregnant women in Nanning, Guangxi, China, the rate of preterm birth was 5.59%(7122). A prospective cohort study conducted in China from 2014 to 2018 found that the preterm birth rate was 5.2% among 51,125 pregnant women[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], another cross-sectional study reported a preterm birth rate as high as 20.6% among pregnant women in Ethiopia[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], additionally, a study incorporating data from eight population cohorts from the EU Child Cohort Network (EUCCN) found that the preterm birth rate varied between 4.9% and 10.4% across different regions in Europe[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The result of our study about the preterm birth rate is consistent with these studies, with only a slight increase in some economically or medically underdeveloped regions. Given the large population and the relatively underdeveloped economic and medical conditions in Guangxi, there will be projected to still experience approximately 3500 preterm births annually, imposing a substantial burden on healthcare system and socioeconomic development. Therefore, it is great to investigate potential factors contributing to preterm birth in order to improve the regional quality of life and alleviate local healthcare and economic burdens in Nanning.\u003c/p\u003e \u003cp\u003eIn this study, pregnant women were stratified by hemoglobin concentration into different anemia severity groups. Comparative analysis of preterm birth risk across different hemoglobin concentration groups during early and late pregnancy revealed that the subnormal hemoglobin groups in late pregnancy increased preterm birth risk. After adjusting for confounding factors, the high hemoglobin group no longer remained an independent risk factor for preterm birth. Furthermore, dose-response analysis demonstrated a characteristic U-shaped relationship between late-pregnancy hemoglobin concentrations and preterm birth risk. Extensive prior evidence has found the association between anemia and adverse pregnancy outcomes. A longitudinal study comparing two birth cohorts spanning 20 years found differential associations between hemoglobin concentrations and adverse perinatal outcomes across gestation periods. Low hemoglobin levels in first-trimester correlated with reduced risk of small for gestational age (SGA) infants (OR\u0026thinsp;=\u0026thinsp;0.73, 95%CI:0.58\u0026ndash;0.93), while low hemoglobin concentrations in third-trimester were linked to increased preterm birth risk (OR\u0026thinsp;=\u0026thinsp;1.60, 95%CI:1.26\u0026ndash;2.02)[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Burden et al.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]investigated the association between maternal hemoglobin concentrations level and adverse pregnancy outcomes in two large prospective cohorts in the UK, which found that there were not statistically significant between the hemoglobin concentrations and preterm birth (PTB), low birth weight (LBW), or small-for-gestational-age (SGA) in first-trimester. However, elevated hemoglobin concentrations significantly were associated with PTB, LBW, and SGA in third-trimester. The authors reported findings regarding hemoglobin's association with preeclampsia and gestational diabetes mellitus - one cohort showed increased adverse outcomes with hemoglobin elevation (OR range:1.35\u0026ndash;1.53) while the other haved no effects.\u003c/p\u003e \u003cp\u003eLanlan Wu et al. (PMID: 35387646) demonstrated the associations between the hemoglobin concentrations and pregnancy outcomes through a retrospective cohort study, in the second (16-18th weeks) trimesters of pregnancy, maternal hemoglobin concentration\u0026thinsp;\u0026gt;\u0026thinsp;130 g/L increased the risk of low birth weight (LBW). In the third (28-30th weeks) trimesters of pregnancy, maternal hemoglobin concentration\u0026thinsp;\u0026gt;\u0026thinsp;130 g/L increases the risk of low birth weight (LB) and small-for-gestational-age infants (SGA). However, comparative analysis across trimesters revealed adjusted ORs of 0.35 (95% CI: 0.18\u0026ndash;0.68) for preterm birth (PTB) and 0.47 (95% CI: 0.23\u0026ndash;0.98) for LBW, with risk reductions for PTB and SGA observed upon appropriate third-trimester hemoglobin elevation. Melissa F Young et al.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]established that both hypo- and hyper-hemoglobinemia during any gestational period correlated with preterm delivery, confirming that extreme hemoglobin concentrations constitute robust predictors of adverse maternal-fetal outcomes. In our study, we found no association between either low or high hemoglobin levels in early pregnancy and preterm birth, but identified that low hemoglobin concentrations in late pregnancy increased the risk of preterm delivery, while there were no significant between high hemoglobin levels and preterm birth. Although most studies have reported that elevated hemoglobin concentrations increase the risk of preterm birth, some researchers have reported divergent findings. A cross-sectional study in Indian demonstrated that varying degrees of anemia were associated with risks of both preterm birth and low birth weight, whereas high hemoglobin concentrations showed no association with either outcome[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], consistent with our findings. The inconsistencies among studies may be attributed to differing definitions of \"anemia\" and \"high hemoglobin,\" as well as variations in hemoglobin measurements at different gestational ages. Whether anemia serves as a protective factor against preterm birth and how to effectively reduce preterm birth rates remain subjects for future studies.\u003c/p\u003e \u003cp\u003eHemoglobin concentration is closely associated with pregnancy outcomes. Anemia during pregnancy may result from nutritional deficiencies, including iron, folate, vitamin A, and vitamin B12, with iron deficiency accounting for 75% of gestational anemia cases[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Iron deficiency during pregnancy results from inadequate dietary intake compounded by increased systemic demand, impaired absorption, or blood loss. Iron requirements and absorption dynamics fluctuate throughout gestation: first-trimester demands decrease, followed by plasma volume and erythrocyte mass expansion in the second and third trimesters due to placental demands, fetal growth, maternal erythropoiesis, and iron store replenishment. Late-pregnancy iron requirements and absorption surge over threefold[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Iron deficiency anemia (IDA) correlates with adverse pregnant outcomes in offspring, including low birth weight, intrauterine growth restriction, preterm birth (PTB), and neonatal anemia.\u003c/p\u003e \u003cp\u003eThe RCS analysis revealed a characteristic U-shaped relationship between hemoglobin concentrations and preterm birth risk, indicating that both hypo- and hyper-hemoglobinemia can increase the risk of the preterm. Therefore, it is essential to continuously monitor changes in hemoglobin concentration during pregnancy and and timely prevent adverse pregnancy outcomes such as preterm birth. Previous studies have demonstrated a dose-response relationship between hemoglobin concentration and adverse pregnancy outcomes. A Chinese retrospective study corroborated these findings, demonstrating significant associations between hemoglobin levels and intrauterine fetal demise (IUFD) or small-for-gestational-age infants, with elevated hemoglobin linked to SGA, neonatal asphyxia, and NICU admissions[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Malshani L Pathirathna identified 110\u0026ndash;129 g/L as the optimal first-trimester hemoglobin range for minimizing preterm birth[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Distinctively, our study modeled hemoglobin as a continuous variable, providing clearer and intuitive representation of the exposure-response relationship between hemoglobin concentration and preterm birth.\u003c/p\u003e \u003cp\u003eThere were several strengths to this study. First, the data for this study were sourced from the Guangxi Population Health Information Service Application Platform, ensuring a reliable data foundation, which encompassed all maternity care facilities in Nanning. Second, we analyzed the relationship between maternal hemoglobin concentrations and preterm birth at two critical gestational timepoints (first and third trimesters). These findings provide important scientific evidence for antenatal care.However, several limitations must be acknowledged. The study focused solely on Nanning, Guangxi Zhuang Autonomous Region, introducing regional and demographic constraints. Additionally, we lacked data on underlying etiologies of anemia/hyperhemoglobinemia (such as serum iron levels, micro-nutrient levels) and other key risk factors. Future studies should collect more critical data on anemia-related influencing factors to validate the findings of this research.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003e This study adhered to the Declaration of Helsinki, and was approved by the Ethics Committee of Nanning Maternal and Child Health Hospital. All methods were performed in accordance with the relevant guidelines and regulations of the institutional ethical review board and in accordance with the Declaration of Helsinki Informed written consent was waived due to the retrospective design.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by funds from the first batch of university-level research projects of Youjiang Medical University for Nationalities in 2025 (yy2025ky121)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMLQ designed the study. QLM, ZXL, XBY, ZQQ, HYQ and LMZ contributed to the information collection, data analysis and interpretation. PYJ drafted the manuscript and revised the final version and are guarantors of this manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. recommended definitions, terminology and format for statistical tables related to the perinatal period and use of a new certificate for cause of perinatal deaths. Modifications recommended by FIGO as amended October 14, 1976. \u003cem\u003eActa Obstet. Gynecol. Scand.\u003c/em\u003e \u003cb\u003e56\u003c/b\u003e (3), 247\u0026ndash;253 (1977).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChawanpaiboon, S. et al. 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Nutr.\u003c/em\u003e \u003cb\u003e155\u003c/b\u003e (11), 3938\u0026ndash;3948. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tjnut.2025.06.029\u003c/span\u003e\u003cspan address=\"10.1016/j.tjnut.2025.06.029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\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":"Hyperhemoglobin, Anemia, Preterm birth, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-9228040/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9228040/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAnemia represents the most common nutritional deficiency among pregnant women worldwide. Although anemia has been extensively studied, the relationship between its severity and maternal and fetal outcomes is not well characterized. We therefore analyzed the association between anemia severity and preterm birth at various gestational ages to identify potential risk factors for preterm delivery. This study provides scientific evidence to inform prevention strategies and improve neonatal outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e This retrospective study enrolled pregnant women receiving early prenatal care and completing full-term maternity checkups in Nanning City between January 2022 and December 2023, with complete follow-up data on birth outcomes.. Data on general demographic characteristics and hemoglobin concentration data at different stages of pregnancy were collected from pregnant women. Univariate and multivariate logistic regression analyses were conducted to analyze the association between hemoglobin concentration and preterm birth, and restricted cubic spline was used to investigate the dose-response relationship between hemoglobin concentration at different gestational stages and preterm birth.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 180357 pregnant women were recruited, excluding those with missing birth outcomes, incomplete hemoglobin concentrations, twin deliveries, HIV/syphilis seropositivity, hepatitis B virus carrier, and abnormal blood pressure, and finally 127,305 pregnant women were included in the analysis. Multivariate logistic regression analysis demonstrated significantly elevated risks of preterm birth across anemia severity strata during the third trimester compared to normal hemoglobin concentrations controls: the risk of preterm birth was 3.43 times higher in the severe anemia group (OR: 3.43, 95% CI: 2.006\u0026ndash;5.865), 1.53 times higher in the moderate anemia group(OR: 1.53, 95% CI: 1.410\u0026ndash;1.660), and 1.206 times higher in the mild anemia group(OR: 1.206, 95% CI: 1.133\u0026ndash;1.284). Dose-response analysis identified a nonlinear relationship between hemoglobin concentration and the risk of preterm birth during both the first and third trimesters, with third-trimester hemoglobin concentrations demonstrating a U-shaped relationship with preterm delivery probability.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHemoglobin concentration in late pregnancy affects the occurrence of preterm birth and there is a U-shaped relationship between hemoglobin concentrations and the risk of preterm birth occurrence.Higher/lower maternal Hb may identify the risk of adverse pregnancy outcomes. Further research is required to investigate if this association is causal and to identify the underlying mechanisms.\u003c/p\u003e","manuscriptTitle":"The Associations of Maternal hemoglobin concentration during pregnancy with the risk of preterm birth","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 15:35:55","doi":"10.21203/rs.3.rs-9228040/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":"109a40f7-80f4-4b91-8541-543b8163cd6d","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-14T23:54:25+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66575363,"name":"Health sciences/Diseases"},{"id":66575364,"name":"Health sciences/Health care"},{"id":66575365,"name":"Health sciences/Medical research"},{"id":66575366,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-15T00:08:44+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 15:35:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9228040","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9228040","identity":"rs-9228040","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}