Determination of a Reference Interval for Glycated Hemoglobin in Non-Diabetic Early Pregnant Women: A Cross-Sectional Study

Abstract

Background:

Physiological changes during pregnancy alter biochemical parameters, including glycated hemoglobin (HbA1c), making pregnancy-specific reference intervals (RIs) essential. In Ethiopia, such intervals are unavailable. This study aimed to establish HbA1c RIs for early pregnant and non-pregnant women and compare their values.

Methods:

A facility-based cross-sectional study was conducted from December 4, 2024, to March 30, 2025, including non-diabetic pregnant and non-pregnant women in Addis Ababa, Ethiopia. The median gestational age was 9.1 weeks. Data were analyzed using IBM SPSS Statistics (Version 27). Normality of continuous variables was assessed using Shapiro-Wilk and Kolmogorov-Smirnov tests. Normally distributed variables are presented as mean ± standard deviation (SD), while non-normally distributed variables are summarized as median with interquartile range. HbA1c values were normally distributed in both groups, so RIs were calculated using mean ± 2SD.

Result:

Early pregnant women had a mean HbA1c of 5.35% (SD = 0.26), corresponding to an RI of 4.83–5.87% (mean ± 2SD). Non-pregnant women showed a higher mean level of 5.63% (SD = 0.28), with an RIs of 5.07–6.19%. An independent samples t-test demonstrated a significant difference between groups (t (264) = 8.109, p < 0.001).

Conclusion:

Early pregnant women had lower HbA1c values than non-pregnant women, with non-pregnant women showing higher RI limits. The locally derived RIs provided a benchmark for accurate HbA1c interpretation in clinical practice and highlight the need for pregnancy-specific standards.

Keywords

Ethiopia glycated hemoglobin nondiabetic pregnant women reference value

Introduction

The maternal system undergoes extensive physiological adaptations to support fetal development, leading to significant alterations in the normative concentrations of many biochemical parameters.¹ For accurate clinical interpretation of laboratory results during pregnancy, reference intervals (RIs) derived from healthy pregnant populations are imperative. Utilizing a reference range established for non-pregnant women may lead to erroneous conclusions, which can cause significant adverse clinical outcomes.²

The clinical importance of population-specific RI is a cornerstone of modern laboratory medicine. International bodies, such as The International Federation of Clinical Chemistry (IFCC), strongly recommend that RIs be established for specific population and geographical regions to ensure clinical accuracy and relevance.³ This recommendation is particularly vital for pregnancy, a unique physiological state, and underscores that the failure to adopt such population-specific RIs represents a deviation from the international best practice.

This need is actually illustrated in the context of gestational diabetes mellitus (GDM), a major global health issue with a high pooled prevalence in Ethiopia, estimated at 12.04%.^4,5 While the oral glucose tolerance test (OGTT) remains the diagnostic standard for GDM, HbA1c offers advantages of convenience and reproducibility; however, its use in pregnancy is complicated by a lack of established, population-specific RIs.^6,7

Despite these international guidelines and the clear physiological needs,⁸ a significant gap persists in the Ethiopian clinical laboratory landscape, where population-specific RIs for HbA1c in pregnancy are unavailable. Therefore, the primary aim of this study is to delineate a pregnancy-specific RI for HbA1c among non-diabetic early pregnant women. This undertaking will also encompass the development of a parallel RI for nondiabetic, nonpregnant Ethiopian women. The establishment of these novels, population-specific RIs will contribute vital, localized data necessary for accurate HbA1c interpretation and improved clinical decision-making in line with global standard.

Methods and Materials

Study design, area, and period

The facility-based cross-sectional study was conducted in Addis Ababa, Ethiopia, from December 4, 2024, to March 30, 2025, and included early pregnant women along with nonpregnant control participants. The study was reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines, and the completed checklist is provided as Supplementary Table S1.

Study setting and population

This study was conducted at the Janmeda and Teklehaymanot governmental health centers. These centers were selected for their high patient volume, comprehensive antenatal care (ANC) services, and their proximity to Black Lion Hospital. The source population consisted of all pregnant women attending ANC and all nonpregnant women visiting the outpatient departments for routine check-ups at these two health centers during the study period.

Sampling technique

Study participants were consecutively selected from the source population. All eligible nondiabetic early pregnant and nonpregnant women who presented to the clinics were invented to participate until the predetermined sample size was achieved.

Inclusion and exclusion criteria

A selective screening strategy based on established risk factors for GDM was employed to ensure a clinically homogeneous and metabolically stable study population. Both pregnant and non-pregnant participants with fasting blood glucose levels above 123 mg/dL or HbA1c values exceeding 6.5%⁹ were excluded to eliminate undiagnosed hyperglycemia. Fasting blood samples were obtained after an overnight fasting of at least 8 hours; participants received standardized fasting instructions at enrollment, and fasting status was verified at the time of blood collection. In the pregnant group, only women aged 18 years or older with singleton pregnancies were included. Additionally, participants with a family history of diabetes, pre-existing diabetes or GDM, multiple pregnancy, anemia have Hb concentrations less than 11 g/dL and 12 g/dL for pregnant and non-pregnant women, respectively,¹⁰ alcoholism, or any hematological, hepatic, immunological, renal, cardiac disease, or other chronic medical conditions were excluded.

Sample size

According to the IFCC guidelines, establishing a population-based RI requires non-parametrically, at least 120 carefully selected reference individuals required.¹¹ Accordingly, we aimed to include a minimum of 120 participants in each group (early pregnant and non-pregnant) to ensure adequate statistical power and reliable interval estimation.

Data collection procedures

Before the initiation of data collection, a 1-day orientation was provided to all participating clinicians and medical laboratory personnel. The session covered the study objectives, standardized protocols for participant recruitment and sample processing, and the communication workflow between the two units to ensure coordinated and efficient teamwork. After getting oral consent, the study health professional gathered data from 137 pregnant women and 129 non-pregnant controls. They used an interview and a semi-structured questionnaire. The interviewer gathered information in an organized manner across several domains relevant to the study’s aim. The semi-structured interview guide included questions adapted from previously published studies.^12–16

For all participants, health professionals recorded basic demographic characteristics, including current occupation and marital status, as well as lifestyle factors such as smoking habits and alcohol consumption patterns. Among pregnant women, health professionals documented reproductive health details such as the date of the last menstrual period, confirmed gestational age, number of children, gravidity, and the type of current pregnancy. All participants had a thorough medical history review during the interview process.

Blood and urine sample collection

Following informed consent, medical laboratory technologists collected biological samples from all participants by using standard protocols. The medical staff drew 5 ml of venous whole blood from each participant under aseptic conditions and immediately dispensed it into appropriate collection tubes. The technician transferred three milliliters to ethylenediaminetetraacetic acid (EDTA)-containing tubes for Hb and HbA1c analysis, while they placed the remaining blood in serum separator tubes for subsequent measurement of fasting blood glucose level.

Besides blood collection, participants provided a urine sample with a volume of 40 milliliters using a sterile, single-use container designed specifically for urine collection. All collected samples were labeled according to standards, stored at the correct temperature, and transported to the testing laboratory specifically for HbA1c on the same day they were collected.

Laboratory sample processing and analysis

After the team collected blood, they processed all samples according to standardized laboratory protocols to ensure sample integrity and timely analysis. For EDTA whole blood samples, the laboratory performed HbA1c analysis within 4 hours of collection to maintain analyte stability, and the technicians conducted Hb analysis within 40 minutes of receiving the sample at the testing facility.

After clot formation in the serum separator tubes, the sample was centrifuged right away. We used 3000g for 10 minutes at room temperature. The resulting supernatant was separated with precision and analyzed for fasting blood glucose levels using validated analytical methods.

Urine samples followed a distinct processing pathway. Pregnancy testing started as soon as the sample arrived. Results were recorded within 10 minutes for quick reporting.

Laboratory measurements

The cobas c 311 (Roche Diagnostic) uses the turbidimetric inhibition immunoassay (TINA) method. This method accurately measures HbA1c. The process starts with a whole blood sample. This sample is collected in an EDTA tube. The EDTA prevents clotting and keeps the red blood cells intact. When the sample goes into the analyzer, a hemolysis step breaks red blood cells. This releases Hb and its glycated part.

The TINA method uses a competitive immunoassay principle, where monoclonal anti-HbA1c antibodies bind specifically to the glycated N-terminal valine of the Hb β-chain. Synthetic polyhaptens, acting as HbA1c analogs, compete with the native HbA1c for antibody binding. The resulting immune complexes generate turbidity, which is inversely proportional to the HbA1c concentration. The system quantifies this turbidimetric shift using the photometric method, which provides high precision and alignment with NGSP and IFCC standards.

Hb was measured using the Sysmex Xs–500i analyzer, which employs the non-cyanide sodium lauryl sulfate (SLS) method. In this method, SLS lyses red blood cells and forms a stable SLS-Hb complex, which is then measured photometrically to determine total Hb concentration.

The BS 200 analyzer (Mindray) determined fasting glucose levels from serum samples using the hexokinase method, where ATP phosphorylates glucose in a reaction catalyzed by hexokinase, producing glucose-6-phosphate. G6PD oxidizes this compound with NAD⁺ present. This process creates NADH. We measured NADH at 340 nm. The amount of NADH formed relates directly to glucose concentration.

Statistical analysis

All statistical analyses were performed using IBM SPSS Statistics (Version 27). Participants with missing data for major study variables were excluded. Reference distributions were assessed for outliers using Tukey’s fences method,¹⁷ and identified outliers were removed.

The normality of HbA1c and other continuous variables were evaluated using both Shapiro-Wilk and Kolmogorov-Simirnov tests, supported by visual inspection of Q-Q plots. For analytes demonstrating a normal distribution, RIs were calculated parametrically as the mean ± 2 standard deviation (SD). For nonnormally distributed analytes, RIs were estimated parametrically using the 2.5^th and 97.5^th percentiles. For nonnormally distributed variables, data were summarized using median and interquartile ranges (IQR).

Results

Among 154 non-diabetic early pregnant women who were initially screened, 137 satisfied the study inclusion criteria. We excluded 17 participants for the following reasons: three tested positive for HBsAg or HCV rapid serological tests conducted at the health centers, seven had a fasting blood sugar (FBS) level > 123 mg/dL, and three had an HbA1c value above 6.5%, two presented with anemia, and two were excluded due to other medical conditions. In the control group, 174 non-diabetic, non-pregnant women were checked for eligibility. Out of them, 129 were included in the study.

Normality testing

The distribution of HbA1c values was assessed using the Shapiro-Wilk and Kolmogorove-Smirnov tests. Among early pregnant women, the Shapiro-Wilk (W = 0.985, p = 0.129) and Kolmogorov-Smirnov (D = 0.051, p = 0.200) tests confirmed a normality distribution (Fig. 1). Similarly, in non-pregnant women, the Shapiro-Wilk (W = 0.983, p = 0.114) and Kolmogorov-Smirnov (D = 0.071, p = 0.193) tests demonstrated no significant deviation from normality. This results support the use of parametric statistical methods for subsequent analyses.

FIG. 1.

Normal Q-Q plot of HbA1c values among non-diabetic early pregnant women recruited at Janmeda and Teklehaymanot Health Centers, Addis Ababa, Ethiopia (n = 137).

The plot compares observed HbA1c values with the expected normal distribution for the reference sample from Addis Ababa. The close alignment of data points with the reference line supports the assumption of normality for parametric RI estimation.

Comparison of demographic and clinical characteristics between early pregnant and non-pregnant groups

The median age of early pregnant women is slightly lower than that of non-pregnant women (p = 0.033). Systolic and diastolic blood pressure were significantly lower in early pregnant women (p < 0.001 for both), reflecting normal physiological adaptation for pregnancy. Hb levels were also reduced in early pregnant women compared to non-pregnant (13.6 vs. 14.6 g/dL), consistent with pregnancy-related hemodilution.

Early pregnant women showed higher body weight and BMI, likely due to normal gestational weight gain. FBS levels did not differ significantly between the two groups (p > 0.05), suggesting similar glycemic profile. The number of children and pregnancies were comparable, and all early pregnant participants were in early gestation (median = 9 weeks) with singleton pregnancies. None had the history of gestational diabetes or family history of diabetes. All participants tested negative for HBsAg, HCV, and HIV (Table 1).

Table 1.

Demographic and Clinical Characteristics of Early Pregnant and Non-Pregnant Women Recruited at Janmeda and Teklehaymanot Health Centers, Addis Ababa, Ethiopia

Variable	Early pregnant women (n = 137)median (IQR)	Non-pregnant women (n = 129)median (IQR)	p Value
Age (years)	28 (26–30)	30 (23.5–36.5)	0.033
SBP(mmHg)	110 (102.5–117.5)	116 (111–121)	<0.001
DBP (mmHg)	69 (60.5–76.5)	78 (76–80)	<0.001
Hb (g/dL)	13.6 (12.9–14.2)	14.6 (13.6–15.6)	<0.001
Weight (kg)	56 (50–62.0)	51.5 (46.8–56.3)	<0.001
BMI (kg/m²)	22.9 (20.9–24.8)	20.3 (19.1–21.5)	<0.001
FBS (mg/dL)	90 (83.5–96.5)	93 (89–97)	>0.05
Number of children	2 (1–5)	1 (0–5)	—
Number of Pregnancies	2 (1– ≥3)	2 (1– ≥3)	—
Gestational age (weeks)	9.1 (7.1–11.1)	—	—
Pregnancy type	All singleton	—	—
History of GDM	None	—	—
Family history of DM	None	None	—
hCG	Positive	Negative	—

Data are presented as median (interquartile range, IQR). The Mann–Whitney U test was used to compare continuous variables between groups. A p value <0.05 was considered statistically significant. All participants tested negative for HBsAg, HCV, and HIV.

SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; FBS, fasting blood sugar; HBsAg, hepatitis B surface antigen; HCV, hepatitis C virus; HIV, human immunodeficiency virus.

Comparison of mean HbA1c levels between early pregnant and Non-Pregnant women

Table 2 presents the comparison of mean HbA1c (%) values between early pregnant and non-pregnant women. The mean HbA1c levels among early pregnant women was 5.35 ± 0.26%, which was significantly lower than that of the non-pregnant women 5.63 ± 0.28%. The mean difference of 0.29% percentage points was statistically significant (t (264) = 8.109, p < 0.001). Levene’s tests for equality of indicated no significance differences between the groups (F = 0.175, p = 0.677), suggesting that the assumption of equal variance was appropriate. The calculated RIs were 4.8%–5.9% for early pregnant women and 5.1–6.2 for non-pregnant women, indicating a physiologically lower HbA1c range during pregnancy.

Table 2.

Summary of Comparison of HbA1c Levels between Early Pregnant and Non-Pregnant Women Recruited at Janmeda and Teklehaymanot Health Centers, Addis Ababa, Ethiopia

Parameter	Early-pregnant women (N = 137)	Non-Pregnant women (N = 129)	Comparison/Statistical test
Mean HbA1c (%)	5.35	5.63	Mean difference: 0.2889 percentage points (non-pregnant higher)
Standard deviation (SD)	0.26	0.28	Standard error of difference: 0.0356
Levene’s Test for equality of variances	F = 0.174, p = 0.677		Equal variance assumed
t-test results	T(264) = 8.109, p < 0.001		Statistically significant difference
Reference interval (HbA1c %)	4.83–5.87	5.07–6.19	—

Data are presented as mean ± standard deviation (SD). The independent sample t-test was used to compare HbA1c levels between pregnant and non-pregnant women . Levene’s test indicated equality of variances (p = 0.677); therefore, equal variances were assumed. The differences in mean HbA1c levels was statistically significant.

HbA1c, glycated hemoglobin; t, t-statistic; p, probability.

Distribution of HbA1c levels in Non-Diabetic early pregnant and Non-Pregnant women

Figure 2 shows the distribution of HbA1c (%) values among non-diabetic pregnant and non-pregnant women using box plots. The median HbA1c levels was lower in pregnant women compared to non-pregnant women, reflecting the physiological decline in glycemic markers during pregnancy. The IQR for pregnant women was slightly narrow, indicating less variability in HbA1c values. A few mild outlier were observed in both groups. Overall, the figure demonstrates that HbA1c levels are significantly lower among pregnant women (p < 0.001).

FIG. 2.

Distribution of HbA1c levels in non-diabetic early pregnant and non-pregnant Women recruited at Janmeda and Teklehaymanot Health Centers, Addis Ababa, Ethiopia (n = 129, and 137, respectively).

Data are expressed as HbA1c percentages derived using the IFCC standardized method. The box represents the IQR, the horizontal line within the box indicates the median, and the whiskers denote the minimum and maximum values within 1.5 × IQR. Circles indicate outliers beyond this range.

Discussion

In recent years, HbA1c measurement has increasingly been incorporated into routine ANC as a screening tool for identifying previously unrecognized preexisting diabetes at the first prenatal visit. Beyond its diagnostic role, there is growing interest in defining clinically meaningful HbA1c thresholds that may inform early intervention during pregnancy.¹⁸ Importantly, accumulating evidence indicates that HbA1c concentrations in health non-pregnant women are modestly higher than those observed in normal pregnancy,¹⁹ underscoring the limitation of applying non-pregnancy reference value to pregnant population and reinforcing the need for pregnancy-specific RIs.

In this context, the present study established RI for HbA1c in non-diabetic Ethiopian early pregnant and non-pregnant women using rigorously verified parametric statistical methods. The mean HbA1c values in our cohort (5.35% ± 0.26% for early pregnant and 5.63% ± 0.28% for non-pregnant women) were significantly different between the two groups (p < 0.001).

During normal pregnancy, HbA1c concentrations are physiologically reduced compared with non-pregnant women due to combined metabolic and hematological adaptations. In early pregnancy, particularly during the first 10–12 weeks of gestation, rising levels of estrogen and progesterone enhance maternal insulin sensitivity, leading to increased peripheral glucose uptake and lower fasting plasma glucose levels. This early improvement in insulin sensitivity precedes the progressive insulin resistances that develop later in pregnancy. Concurrently, pregnancy is characterized by plasma volume expansion and hemodilution. In addition, increased erythropoiesis and shorten red blood cell life span decrease the duration of Hb exposure to glucose.^20–23 These within-population variations underscore the essential need for pregnancy-specific RIs to avoid misclassification of glycemic status.

A key contribution of this study is the demonstration of systematically higher HbA1c RIs in Ethiopian women compared to the global population. When compared with studies conducted using similar parametric approaches, a clear gradient emerges. The lowest HbA1c values were reported by the Nordic Caucasian cohort.²⁴ Intermediate range intervals have been observed in multi-ethnic U.S. populations¹³ and Japanese cohort,²⁵ whereas our Ethiopian samples demonstrate the highest HbA1c distribution. The persistence of this pattern across studies that used a matching statistical framework is consistent with the hypothesis that population-specific biological determinants such as genetic variability affecting erythrocyte lifespan, glucose transport, or Hb glycation may contribute to differences in HbA1c expression. However, we acknowledge that these are cross-study comparisons; differences in laboratory protocols, calibration, and potential unmeasured confounders preclude a definitive causal attribution to ethnicity alone.

These findings are further reinforced by comparisons with studies that employed non-parametric methods. Research from Caucasian and Indian populations reported significantly lower RIs than those observed in our dataset, both among pregnant and non-pregnant women.^26–28 The consistent direction of these differences across methodological approaches strengthens the possibility of ethnic heterogeneity in HbA1c. Nevertheless, this interpretation must be made cautiously, as the studies were not performed simultaneously or under uniform laboratory conditions.

A comparison with another Sudanese study²⁹ reveals significant methodological and analytical limitations that likely accounts for the discrepant RIs reported. Notably, the study reports an implausible low mean early-pregnancy HbA1c value of 4.4%, which is inconsistent with established physiological patterns and international reference data. This anomaly is further compounded by the absence of essential statistical validation, such as assessment of data normality, and by an unusual large standard deviation (≥1.0), suggesting extreme data dispersion. Collectively, these issues indicate the possible influence of unrecognized outliers, pre-analytical variability, or analytical error. Consequently, the reported RIs appear unreliable and of limited clinical relevance.

The clinical implications are substantial. Many laboratories in Ethiopia and similar settings continue to rely on manufacturer-provided reference range derived primarily from non-African and non-pregnant populations. Applying such inappropriate intervals could result in over or under-diagnosis of dysglycemia during pregnancy, adversely affecting maternal and neonatal outcomes.

Conclusion

This study establishes robust and clinically relevant HbA1c RIs for pregnant Ethiopian women. The significantly lower HbA1c concentrations observed during pregnancy highlight the need for pregnancy-specific RI to prevent misclassification of glycemic status. Furthermore, the consistent higher HbA1c values in Ethiopian women compared to global populations indicate that ethnicity is a major determinant of HbA1c levels. These findings support the adoption of population- and pregnancy-specific RIs in clinical practice and underscore the need for future research to explore underlying biological determinants of HbA1c variability in African population.

Limitation

This study has limitations that should be considered when interpreting the findings. The study involved participants from an urban settings, which may limit generalizability to Ethiopian diverse rural population. In addition, since GDM is typically diagnosed at 24–28 weeks of gestation, some women classified as non-diabetic in early pregnancy may later develop GDM; therefore, a normal HbA1c in early pregnancy does not exclude GDM later in gestation.

Recommendation

Future studies should focus on creating and validating trimester-specific RIs. This will help track the change in the body during pregnancy. By doing this, HbA1c measurements can better monitor a mother’s blood sugar level throughout all stages of gestation.

Footnotes

Acknowledgments

The authors extend their sincere gratitude to all individuals whose invaluable support made this research possible. They are profoundly grateful to Mrs. Laura Goosen Miler for her generous donation of the HbA1c reagents, controls, and calibrators, which were fundamental to the initiation and execution of this project. Beyond this material support, she followed the project’s progress closely, offering continuous encouragement and guidance throughout all phases of the study. Her unwavering commitment, generosity, and voluntary support were instrumental to the successful completion of this work. The authors deeply appreciate her kindness, dedication, and exemplary sprit of academic collaboration.

They also express their heartfelt appreciation to Mr.Teshalle Mulugeta Abebe, for his invaluable support in the laboratory analysis. His expert advice from the selection of appropriate reagent to the analysis and interpretation of results—greatly enhanced the quality of the laboratory work.

This work would not have been possible without their collective support.

Authors’ Contributions

T.K. contributed to the conceptualization and project administration, and was responsible for the original drafting of the article as well as subsequent review and editing. A.L. supported project administration and supervision and contributed to article review and editing. A.T. was responsible for the methodology, validation, and formal analysis. M.D. contributed to the methodology and provided article review and editing. A.W. contributed to the investigation, data curation, formal analysis, and methodology.

Ethical Approval and Consent to Participate

This study was conducted in accordance with the Declaration of Helsinki.³⁰ Ethical approval was obtained from The Institutional Research Ethics Review Committee (IRERC) of Addis Ababa University (protocol No. 014/24/Physio). All study participants gave written informed consent.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request at teklekassahun@gmail.com.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This research received no specific grant from funding agencies, in the public, commercial, or not-for-profit sectors.

Supplemental Material

Abbreviations Used

References

1. Soma-Pillay

, Nelson-Piercy

, Tolppanen

, et al. Physiological changes in pregnancy. Cardiovasc J Afr 2016;27(2):89–94.

2. So

, Kwon

, Jung

, et al. Physiological changes and trimester-specific reference intervals for complete blood count parameters in Korean pregnant women. Medicina (Kaunas) 2025;61(9):1665.

3. Doyle

, Bunch

. Reference intervals: Past, present, and future. Crit Rev Clin Lab Sci 2023;60(6):466–482.

4. Guariguata

, Linnenkamp

, Beagley

, et al. Global estimates of the prevalence of hyperglycaemia in pregnancy. Diabetes Res Clin Pract 2014;103(2):176–185.

5. Beyene

, Kassa

, Mihretie

, et al. Gestational diabetes mellitus and its associated factors in Ethiopia: A systematic review and meta-analysis. Eur J Med Res 2023;28(1):125.

6. Renz

, Cavagnolli

, Weinert

, et al. HbA1c test as a tool in the diagnosis of gestational diabetes mellitus. PLoS One 2015;10(8):e0135989.

7.Committee ADAPP. Classification and diagnosis of diabetes: Standards of medical care in diabetes—2022. Diabetes Care 2021;45(Supplement_1):S17–S38.

8. Yu

, Qi

, Wang

. Application of glycated hemoglobin in the perinatal period. Int J Clin Exp Med 2014;7(12):4653–4659.

9.Association AD. Classification and diagnosis of diabetes. Diabetes Care 2015;39(Supplement_1):S13–S22.

10.

10.Safety WHODoNaF. WHO methods and data sources for mean haemoglobin and anaemia estimates in women of reproductive age and pre-school age children 2000-2019. Safety NaF: Geneva, Switzerland; 2021.

11.

11. Coskun

, Ceyhan

, Inal

, et al. The comparison of parametric and nonparametric bootstrap methods for reference interval computation in small sample size groups. Accred Qual Assur 2013;18(1):51–60.

12.

12. Sánchez-González

, Castillo-Mora

, Alvarado-Maldonado

, et al. Reference intervals for hemoglobin A1c (HbA1c) in healthy Mexican pregnant women: A cross-sectional study. BMC Pregnancy Childbirth 2018;18(1):424.

13.

13. Lu

, Huo

, Ge

, et al. Pregnancy status is associated with lower hemoglobin A1c among nondiabetes women in the United States from NHANES 2005–2016. Int J Endocrinol 2022;2022:4742266.

14.

14. Deng

, Cheng

, Liao

, et al. Trimester-specific reference intervals for hemoglobin A1c in non-diabetic pregnancy in a Chinese population. BMC Pregnancy Childbirth 2023;23(1):671.

15.

15. Claire

, Sharon

. Should HbA1C be used to screen pregnant women for undiagnosed diabetes in the first trimester? A review of the evidence. J Public Health (Oxf) 2020;42(1):132–140.

16.

16. Chellamma

, Jayakumar

, Nair

, et al. Reference range for glycated haemoglobin in full term non diabetic pregnant women: A multicentric cross sectional study. Arch Gynecol Obstet 2024;310(3):1377–1383.

17.

17. Schwertman

, Silva

. Identifying outliers with sequential fences. Computational Statistics & Data Analysis 2007;51(8):3800–3810.

18.

18. Hughes

, Rowan

, Florkowski

. Is there a role for HbA1c in pregnancy? Curr Diab Rep 2016;16(1):5.

19.

19. Bi

, Ji

, Wu

, et al. Association between maternal normal range HbA1c values and adverse birth outcomes. J Clin Endocrinol Metab 2020;105(6):dgaa127.

20.

20. Carlsen

EØ

, Harmon

, Magnus

, et al. Glycated haemoglobin (HbA1c) in mid-pregnancy and perinatal outcomes. Int J Epidemiol 2022;51(3):759–768.

21.

21. Cheung

, Au

TS-T

, Lee

C-H

, et al. Hemoglobin A1c in early pregnancy to identify preexisting diabetes mellitus and women at risk of hyperglycemic pregnancy complications. AJOG Glob Rep 2024;4(1):100315.

22.

22. Coetzee

, David

, Conradie

. Hyperglycemia first detected in pregnancy in South Africa: Fact, gaps, and opportunities. Front Clin Diabetes Healthc 2022;3:895743.

23.

23. Sanghavi

, Rutherford

. Cardiovascular physiology of pregnancy. Circulation 2014;130(12):1003–1008.

24.

24. Nielsen

, Ekbom

, Damm

, et al. HbA1c Levels are significantly lower in early and late pregnancy. Diabetes Care 2004;27(5):1200–1201.

25.

25. Hiramatsu

, Shimizu

, Omori

, JGA (Japan Glycated Albumin) Study Group. et al.; Determination of reference intervals of glycated albumin and hemoglobin A1c in healthy pregnant Japanese women and analysis of their time courses and influencing factors during pregnancy. Endocr J 2012;59(2):145–151.

26.

26. Mosca

, Paleari

, Dalfrà

, et al. Reference intervals for hemoglobin A1c in pregnant women: Data from an italian multicenter study. Clin Chem 2006;52(6):1138–1143.

27.

27. O’Connor

, O’Shea

, Owens

, et al. Trimester-specific reference intervals for haemoglobin A(1c) (HbA(1c)) in pregnancy. Clinical Chemistry and Laboratory Medicine: CCLM/FESCC 2011;50:905–909.

28.

28. Punnose

, Malhotra

, Sukhija

, et al. Establishing trimester-specific haemoglobin A1c reference intervals in pregnant women: A retrospective study of healthy South Asian women with normal pregnancy outcomes. Sultan Qaboos Univ Med J 2023;23(1):81–89.

29.

29. Elmugadam

, Ismail

, Eltom

. Appraisal of A1c% level in healthy Sudanese pregnant women in reference to body mass index. Int J Reprod Contracept Obstet Gynecol 2019;8(5):1835–1839.

30.

30. Shrestha

. The declaration of helsinki in relation to medical research: Historical and current perspectives. J Nepal Health Res Counc 2012;10(22):254–257.

Supplementary Material

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