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. 2026 Sep 3;10(9):e2026GH001859. doi: 10.1029/2026GH001859

Maternal Serum Nitrate and Nitrite Associations With Birth Outcomes: A Case‐Control Study

Wael K Al‐Delaimy 1,✉, Omar F Khabour 2, Yousef Khader 3, Fayez A Abdulla 4, Hanan Hammouri 5, Nour Abdo 3, Razan A Saleh 2,6
PMCID: PMC13540271  PMID: 42694627

Abstract

Nitrate and nitrite contamination of groundwater and surface water is a global public health concern, often linked to the increasing use of nitrogen‐based fertilizers. In Jordan's Ghor region, where agriculture is intensive and fertilizer use is widespread, the issue is particularly relevant. This study aimed to investigate the relationship between serum nitrate and nitrite levels with low birth weight and preterm birth. A total of 659 participants were enrolled, comprising 452 controls (normal birth weight and full‐term delivery) and 207 cases (low birth weight/preterm delivery). High maternal serum nitrite levels were significantly associated with increased odds of low birth weight delivery in both the unadjusted model (odds ratio [OR] = 1.43, 95% CI: 1.14–1.80, P = 0.002) and the a priori confounder set adjusted model (OR = 1.33, 95% CI: 1.02–1.74, P = 0.038). Nitrite levels were also significantly associated with the combined outcome of preterm and/or low birth weight delivery in the unadjusted model (OR = 1.26, 95% CI: 1.01–1.57, P = 0.036), and this association remained significant after a priori adjustment in a multiple‐imputation sensitivity analysis (OR = 1.29, 95% CI: 1.03–1.63, P = 0.029). In conclusion, although metabolically interrelated, nitrite and nitrate levels in pregnant women may differentially impact pregnancy outcomes in the largely low income agricultural communities in the Ghor region in Jordan.

Keywords: NO3 − , NO2 − , pregnancy, Jordan, preterm, low birth weight

Plain Language Summary

Nitrate and nitrite pollution in water is a major health issue, especially in farming areas that utilize nitrogen fertilizers like Jordan's Ghor region. Researchers studied 659 pregnant women in this area to see if these pollutants affect birth outcomes. They found that women with higher levels of nitrite in their blood were significantly more likely to have babies with low birth weight. In brief, the study suggests that exposure to nitrite may be putting pregnant women in agricultural communities at higher risk for birth complications.

Key Points

  • Elevated nitrite in maternal blood serum, measured at birth, were associated with an increased likelihood of a low birth weight baby

  • A weak inverse association between maternal serum nitrate and preterm delivery became nonsignificant after a priori confounder adjustment

  • There were no significant differences for these associations between North and South Ghor areas based on stratified analysis

1. Introduction

Nitrate contamination of water resources is a global health problem (Patel et al., 2022), primarily driven by the extensive use of nitrogen fertilizers (Ward, 2009). Studies also indicate that climate change affects nitrate/nitrite leaching through temperature rising and rainfall fluctuations (Boyacioglu et al., 2024). For example, heat waves enhance the nitrification process and the subsequent nitrate accumulation (Dannenmann et al., 2016), while drought season negatively impacts the clearance of nitrate by plants (Lv et al., 2024). Consequently, human exposure to nitrate/nitrite may be heightened during climatic fluctuations.

Humans absorb nitrates from soil through the food chain and from drinking water. Once ingested, it enters the bloodstream and is secreted into saliva, where it is reduced by oral microflora to nitrite (Washio & Takahashi, 2025). Upon swallowing, nitrite may either enter systemic circulation or be further reduced to nitric oxide (NO) in the acidic gastric environment (Lidder & Webb, 2013). In states of hypoxia, circulating nitrite can also be converted to NO, which plays an important physiological role in the body (Christie et al., 2023). However, exposure to high levels of nitrate/nitrite has been associated with several health consequences, including adverse pregnancy outcomes, gastrointestinal cancers, autoimmune diseases, and others (Habermeyer et al., 2015).

Preterm birth (PB) and low birth weight are major drivers of neonatal mortality, resulting in serious immediate and long‐term health, developmental, and cognitive issues for infants (Averin et al., 2023; Frontera et al., 2024). Immediate effects include breathing problems, infections, feeding challenges, and temperature instability, while long‐term consequences involve chronic illnesses such as diabetes, hypertension, and others (Jańczewska et al., 2023). Therefore, preventing low birth weight and preterm delivery is important and achievable if exposure to modifiable risk factors can be prevented or limited.

Studies have reported a potential impact of maternal exposure to nitrate/nitrite on newborn birth weight and PB with some controversy (Blake, 2014; Coffman et al., 2021; Ferguson et al., 2013; Jensen et al., 2023; Migeot et al., 2013; Reuther et al., 2025; Stayner et al., 2017; Temkin et al., 2019). For example, two studies from California, USA, reported an association between low birth weight and PB and nitrate exposure from air and water (Reuther et al., 2025; Sherris et al., 2021). A study conducted in Iowa, USA showed that early prenatal exposure to drinking water nitrate levels (below the 10 mg/L standard) were linked to PB and low birth weight (Semprini, 2025). A recent study from USA indicated that nitrate exposure from drinking water during the second trimester, even at concentrations below regulatory thresholds, is associated with a 1.2 and 1.0% point increase in the risk of PB and low birth weight, respectively (Montoya, 2025). A study from Denmark showed an association between prenatal nitrate exposure from household tap water and small‐for‐gestational‐age fetuses (Jensen et al., 2023). A study conducted in Prince Edward Island, Canada, showed that agricultural contamination of groundwater is a risk factor for low birth weight and PB (Bukowski et al., 2001). On the other hand, no association between nitrate exposure from water/food sources and low birth weight and PB has been reported by studies from different countries (Blake, 2014; Coffman et al., 2021; Stayner et al., 2017). Notably, most prior studies have assessed exposure via diet or drinking water, which might be modulated by metabolic variability between individuals. Serum nitrite and nitrate levels are objective markers representing cumulative exposure to all environmental sources. Although these levels can be influenced by diet, metabolism, and physiology, they represent a more direct internal measurement of human exposure than water‐source monitoring.

In Jordan, the Ghor region (locally known as Al Ghawr) presents a compelling setting for investigating nitrate/nitrite exposure due to its intensive agricultural activity and heavy reliance on fertilizers, as well as sensitivity to drought and heatwaves (Alwedyan & Taani, 2021; Anbar, 1983; Mahmoud, 1983). The Ghor extends approximately 110 km between Lake Tiberias and the Dead Sea and is below sea level. Agricultural activity relies on water from the East Ghor Canal, which receives water primarily from the Yarmuk River, several dams, and reused water (Anbar, 1983). People living in this region are low income farmworkers and day laborers who are likely exposed to high levels of nitrate/nitrite from water and food sources (Alwedyan & Taani, 2021; Mahmoud, 1983). The aim of this study was to investigate the relationship between serum nitrate and nitrite levels (as biomarkers of environmental exposure during pregnancy) at delivery and low birth weight and PB in the Ghor region.

2. Methods

2.1. Study Design and Study Participants

A case‐control study was conducted to investigate the association between maternal serum levels of nitrate or nitrite (as environmental exposure biomarkers) and low birth weight and/or PB (cases) in the Ghor. Data collection took place in four maternity hospitals in cities serving the region. The hospitals were: Muath bin Jabal Hospital in Alshuna Alshamalia city, Abu‐Obaidah Hospital in Pella village, Princess Badea Hospital in Irbid city, and Al‐Hussain Hospital in Salt city. At hospitals serving women from regions other than Ghor, only women residing in Ghor were eligible for inclusion. Cases included women aged 18–49 years who delivered babies with low birth weight and/or PB at or after 24 weeks of gestation. Low birth weight was defined as birth weight less than 2,500 g, as per the World Health Organization (WHO). PB was defined as any birth occurring before 37 weeks of gestation, as per WHO. For each low birth weight or PB case, which was selected consecutively from each participating hospital, two or three controls of normal birth weight deliveries were selected. Controls were frequency‐matched to cases by maternal age group and newborn sex. Controls were selected from the hospital/region of the case to allow for better representation of deliveries occurring in the two Ghor regions (North and South). In addition, cases and controls were recruited during the same time period to make sampling and handling constant between the two groups. Exclusion criteria for both cases and controls included having a history of diabetes mellitus, gestational diabetes, hypertension before pregnancy, pre‐eclampsia, eclampsia, severe anemia, cardiovascular diseases, chronic obstructive pulmonary disease, renal diseases, active tuberculosis or hepatitis infection, epilepsy, or pregnancy complications.

2.2. Ethical Approval

The study was approved by the “Institutional Review Board (IRB) at King Abdullah University Hospital/Jordan University of Science and Technology” (ID number: 47/151/2022). Written informed consent was obtained from all participating women after a full explanation of the study objectives and procedures.

2.3. Serum Sampling

Maternal blood samples (3 mL) were collected in plain tubes upon admission to the maternity unit in the included hospitals. In brief, after blood sampling, the blood tubes were kept at room temperature (30 min) to complete the coagulation process. Blood tubes were then centrifuged at 1,500×g. Serum fraction was then ultra‐filtered through a 30 kDa molecular weight cutoff filter. The filtered samples were then stored at −80°C until further analysis.

2.4. Measurements of Serum Nitrate/Nitrite

A calorimetric assay based on Griess reagents was adopted to measure serum nitrate and nitrite levels (Miranda et al., 2001; Sukuroglu et al., 2015). The assay was developed by Cayman Chemical Company (Ann Arbor, MI, USA). Filtered serum samples were diluted 1:3 in “sample diluent” provided by the assay kit. Part of the diluted serum was treated with nitrate reductase enzyme to measure total nitrate/nitrite in the sample. Untreated remaining filtered serum was used to measure nitrite levels. Samples were assayed in duplicates in ELISA plate format. Standard curve samples were assayed in triplicates. ELISA plates were read at 540 nm using a plate reader from Bio‐Tek (Winooski, USA). Nitrate levels were calculated by subtracting the nitrite level from the total nitrate and nitrite levels.

2.5. Study Questionnaire and Data Collection

In each hospital, a trained midwife was responsible for collecting the necessary data from women using a structured questionnaire through face‐to‐face interviews before hospital discharge. The questionnaire included inquiries about socio‐demographic factors (e.g., age, gender, education, occupation, and residence), pre‐pregnancy body mass index, weight gain during pregnancy, lifestyle factors, type and sources of water consumed (municipal/bottled/well/other), history of anemia, and maternal smoking during or before pregnancy. The last part of the questionnaire included information on clinical data, obstetric characteristics, pregnancy outcomes, including gestation age and the weight of newborns.

2.6. Sample Size Calculations

The sample size was calculated to detect an odds ratio (OR) of 1.75 for the association between elevated maternal serum nitrate or nitrite levels and the risk of PB and/or low birth weight. This effect size was selected to fall within the range of associations reported for higher versus lower gestational nitrate/nitrite exposure in prior studies (e.g., adjusted ORs of 1.47–2.52 for PB reported by Sherris et al. (2021)), representing a clinically meaningful but conservative target. Assuming a two‐sided significance level of 0.05, a power of 80%, and a 30% prevalence of elevated nitrate or nitrite exposure among controls—a moderate, conservative assumption for an intensively agricultural region with documented groundwater nitrate contamination, given that power is maximized as the exposed proportion approaches 50%—the required sample size was estimated to be 490 participants (163 cases and 327 controls) for a 1:2 case‐to‐control ratio. The sample size was calculated using EpiCalc 2000.

2.7. Statistical Analysis

Data were analyzed using IBM SPSS version 24. Categorical variables were presented as frequencies and percentages, and continuous variables were summarized using means and standard deviations and medians. Comparisons between cases and controls for categorical variables were performed using the Chi‐square test. For continuous variables, independent samples t‐tests or Mann–Whitney U tests were applied based on data normality.

Associations between maternal serum nitrate and nitrite levels and birth outcomes were examined using logistic regression models. Unconditional logistic regression was employed, as matching was performed at the group level rather than through individual matching. Separate models were fitted for each outcome (low birth weight, PB, and a combined outcome). Nitrate and nitrite exposures were modeled as continuous variables to preserve statistical power.

Confounders were selected a priori on the basis of established causal knowledge rather than by stepwise statistical selection, which is not recommended for effect estimation. A directed acyclic graph (DAG; Figure 1) was used to encode assumed causal relationships and to distinguish confounders from mediators and from determinants of exposure. The minimal sufficient adjustment set, forced into all models irrespective of statistical significance or goodness of fit, comprised maternal age, household income, maternal education, smoking during pregnancy, pre‐pregnancy body mass index, parity, anemia during pregnancy, and maternal history of low birth weight. Variables judged to lie on the causal pathway from exposure to outcome were not adjusted for in the primary models: water source was treated as an upstream determinant of the serum biomarker, and gestational hypertension as a probable mediator of the NO—related vascular pathway. To confirm the adjustment set, the change‐in‐estimate method (10% threshold) was applied to the primary nitrite—low birth weight association by adding each candidate covariate individually to the base model. Gestational hypertension was additionally examined in a sensitivity analysis, and multiple imputation by chained equations (m = 20, pooled using Rubin's rules) was used to assess the influence of missing covariate data. ORs with 95% confidence intervals (CIs) were estimated for both crude (mutually adjusted) and adjusted models.

Figure 1.

Figure 1

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Directed acyclic graph summarizing the assumed causal structure used to select the adjustment set. A priori confounders (maternal age, household income, maternal education, smoking during pregnancy, pre‐pregnancy body mass index, parity, anemia during pregnancy, and history of low birth weight) are common causes of both exposure and outcome and were forced into all models. Water source was treated as an upstream determinant of the serum biomarker, and gestational hypertension as a probable mediator; both were therefore excluded from the primary adjustment set.

Analyses were conducted for the overall study population (North and South Ghor combined) and stratified by region to explore potential geographic differences. Regional variation (North vs. South Ghor) was assessed through stratified analyses to evaluate potential heterogeneity in associations, rather than including region as a covariate in the primary models. Statistical significance was defined as a two‐tailed p‐value < 0.05. Because within‐region sample sizes were modest relative to the number of covariates, the region‐stratified adjusted models were regarded as exploratory and hypothesis‐generating, and the combined‐region models (with multiple‐imputation sensitivity analysis) were used as the primary basis for inference.

3. Results

3.1. Socio‐Demographic Characteristics

A total of 659 women were included in the study, comprising 452 in the control group (full‐term, normal birth weight deliveries) and 207 in the case group (preterm and/or low birth weight deliveries). Of these, 381 women resided in North Ghor (264 controls and 117 cases), while 278 lived in South Ghor (188 controls and 90 cases). The gender of newborns for the cases were 48% males and 52% females and for the control 48.7% males and 51.3% females. The socio‐demographic characteristics of the study participants were compared between the two groups, and no statistically significant differences were observed (Table 1). The mean age of the mothers of cases was 29.96 years (SD 6.32) and for controls 29.24 years (SD 6.19). Most mothers in both groups were aged 26–35 years (52.5% in controls vs. 50.5% in cases, p = 0.26). The majority of women (84.8%) in the control group and 81.1% in the case group had a high school education or less, while 15.2% and 18.9%, respectively, had a diploma or higher (p = 0.235). Women's employment status did not significantly differ between the two groups, with most being housewives (92.6% in controls vs. 90.7% in cases, p = 0.404). Household income levels were also similar, with approximately half of participants in both groups reporting an income of 201–300 JOD (p = 0.652), which is considered low to very low income in Jordan.

Table 1.

Socio‐Demographic Characteristics of Women Who Delivered Preterm And/Or Low Birth Weight Infants (Cases) Compared to Those Who Delivered Full‐Term, Normal Birth Weight Infants (Controls)

Variable Controls (n = 452) Cases (n = 207) Total (n = 659) P‐value
Residence 0.649
North Ghor 264 (58.4%) 117 (56.5%) 381 (57.8%)
South Ghor 188 (41.6%) 90 (43.5%) 278 (42.2%)
Women's age 0.260
≤25 years 136 (31.1%) 55 (27.8%) 191 (30.0%)
26–35 years 230 (52.5%) 100 (50.5%) 330 (51.9%)
>35 years 72 (16.4%) 43 (21.7%) 115 (18.1%)
Mother's education 0.235
High school or less 380 (84.8%) 163 (81.1%) 543 (83.7%)
Diploma or higher 68 (15.2%) 38 (18.9%) 106 (16.3%)
Employment status 0.404
Housewife 413 (92.6%) 185 (90.7%) 598 (92.0%)
Employed 33 (7.4%) 19 (9.3%) 52 (8.0%)
Household income 0.652
≤200 JOD 76 (18.2%) 29 (15.2%) 105 (17.2%)
201–300 JOD 202 (48.3%) 97 (50.8%) 299 (49.1%)
>300 JOD 140 (33.5%) 65 (34.0%) 205 (33.7%)
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3.2. Maternal Characteristics

The maternal, obstetric, and clinical characteristics of the participants are shown in Table 2. A history of PB was significantly more likely in the case group (26.3%) compared to the control group (10.7%) (p < 0.001). Similarly, the history of low birth weight was significantly more likely among cases (33.8%) than controls (15.6%) (p < 0.001). While neonatal complications (7.4% in cases vs. 4.1% in controls, p = 0.078) and stillbirths (10.4% in cases vs. 6.4% in controls, p = 0.078) were higher in the case group, the differences were not statistically significant. Hypertension during pregnancy was significantly higher in the case group (11.9%) compared to the control group (4.7%) (p = 0.001).

Table 2.

Maternal, Obstetric, and Clinical Characteristics of Women Who Delivered Low Birth Weight and/or Preterm Infants (Cases) Compared to Those Who Delivered Full‐Term, Normal Birth Weight Infants (Controls)

Variable Controls (n = 452) Cases (n = 207) Total (n = 659) P‐value
Number of children 0.259
≤2 children 223 (53.1%) 94 (48.2%) 317 (51.5%)
>2 children 197 (46.9%) 101 (51.8%) 298 (48.5%)
History of preterm birth 48 (10.7%) 54 (26.3%) 102 (15.6%) <0.001
History of low birth weight 69 (15.6%) 68 (33.8%) 137 (21.3%) <0.001
History of neonatal complications 18 (4.1%) 15 (7.4%) 33 (5.1%) 0.078
History of stillbirths 28 (6.4%) 21 (10.4%) 49 (7.7%) 0.078
History of abortions 159 (36.0%) 65 (32.3%) 224 (34.8%) 0.370
History of cesarean section 226 (51.1%) 117 (57.9%) 343 (53.3%) 0.109
Parental consanguinity 0.691
No relation 263 (59.1%) 116 (57.4%) 379 (58.6%)
First‐degree relatives 99 (22.2%) 51 (25.2%) 150 (23.2%)
Second‐degree relatives 83 (18.7%) 35 (17.3%) 118 (18.2%)
Type of pregnancy 0.504
Singleton 408 (99.0%) 184 (98.4%) 592 (98.8%)
Twin or multiple 4 (1.0%) 3 (1.6%) 7 (1.2%)
Smoking during pregnancy 32 (7.2%) 19 (9.3%) 51 (7.8%) 0.343
Anemia during pregnancy 185 (41.8%) 73 (36.5%) 258 (40.1%) 0.208
Hypertension during pregnancy 21 (4.7%) 24 (11.9%) 45 (6.9%) 0.001
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The percentage of preterm and/or low birth weight infants among the recruited women was not very different in the South Ghor (32.4%) than in the North Ghor (30.7) (P = 0.649). There was no significant difference in the percentage of delivering low birth weight infants between the recruited women in the two regions (North Ghor: 24.3%, South Ghor: 23.4%, P = 0.794). However, the percentage of preterm births was significantly higher in the sample from the South Ghor (24.0%) compared to the North Ghor (14.6%) (P = 0.003).

3.3. Serum Nitrite and Nitrate Levels Across Different Pregnancy Outcomes

Table 3 shows the serum nitrite and nitrate levels among women, stratified by pregnancy outcomes and place of residence. When combining data from both regions, there were no statistically significant differences in maternal serum nitrite or nitrate levels based on gestational age and/or birth weight (p = 0.379 and p = 0.291, respectively). In the North Ghor, although serum nitrite levels did not differ significantly (p = 0.251), median nitrate levels were significantly higher among mothers of preterm and/or low birth weight infants compared to those with normal birth weight (24.53 vs. 19.89 μM, p = 0.015). In the South Ghor, no significant differences were observed in either nitrite or nitrate levels in relation to gestational age and/or birth weight.

Table 3.

Maternal Serum Nitrite and Nitrate Levels Are Stratified by Pregnancy Outcomes and Place of Residence

Region/outcome N Nitrite (μM) mean ± SD Median P‐value Nitrate (μM) mean ± SD Median P‐value
Both Regions Combined
Gestational age/birth weight 0.379 0.291
Normal 352 0.86 ± 0.71 0.63 23.12 ± 16.37 19.17
Preterm and/or Low Birth Weight 159 1.03 ± 1.04 0.72 24.03 ± 16.03 21.14
Gestational age 0.107 0.111
Full‐term 398 0.93 ± 0.79 0.67 23.89 ± 16.36 20.20
Preterm 91 0.87 ± 0.98 0.58 21.41 ± 15.31 17.31
Birth weight 0.014 0.243
Normal BW 384 0.85 ± 0.73 0.61 23.01 ± 16.10 19.16
Low BW 118 1.14 ± 1.09 0.83 24.64 ± 17.07 21.57
North Ghor
Gestational age/birth weight 0.251 0.015
Normal 202 1.05 ± 0.79 0.83 22.46 ± 12.50 19.89
Preterm and/or Low Birth Weight 93 1.25 ± 1.08 0.96 26.30 ± 14.60 24.53
Gestational age 0.652 0.348
Full‐term 245 1.09 ± 0.80 0.83 23.56 ± 13.57 20.80
Preterm 41 1.22 ± 1.31 0.83 24.98 ± 12.55 24.53
Birth weight 0.040 0.034
Normal BW 217 1.04 ± 0.82 0.83 22.77 ± 12.67 20.08
Low BW 73 1.32 ± 1.07 1.06 26.31 ± 14.79 23.16
South Ghor
Gestational age/birth Weight 0.874 0.354
Normal 150 0.61 ± 0.48 0.45 24.00 ± 20.47 18.21
Preterm and/or Low Birth Weight 66 0.72 ± 0.90 0.45 20.84 ± 17.48 16.28
Gestational age 0.796 0.025
Full‐term 153 0.66 ± 0.69 0.45 24.42 ± 20.07 19.18
Preterm 50 0.58 ± 0.40 0.43 18.48 ± 16.81 15.94
Birth weight 0.282 0.412
Normal BW 167 0.59 ± 0.47 0.41 23.32 ± 19.73 17.96
Low BW 45 0.83 ± 1.05 0.46 21.93 ± 20.13 16.02
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Note. P‐values calculated using the Mann–Whitney U test.

In both regions combined, serum nitrite levels were significantly higher in mothers of low birth weight infants compared to those with normal birth weight (0.83 vs. 0.61 μM, p = 0.014), while no significant differences were observed for nitrate levels (p = 0.243). In the North Ghor, both serum nitrite and nitrate levels were significantly elevated in mothers of low birth weight infants compared to those with normal birth weight (nitrite: 1.06 vs. 0.83 μM, p = 0.040; nitrate: 23.16 vs. 20.08 μM, p = 0.034).

With respect to gestational age, South Ghor was the only region showing a significant difference, where mothers of preterm infants had lower median nitrate levels than those of full‐term infants (15.94 vs. 19.18 μM, p = 0.025). No other comparisons by gestational age showed statistically significant differences in either nitrite or nitrate levels.

3.4. Multivariate Analysis

In the combined analysis of the North and the South Ghor (Table 4), higher maternal serum nitrite levels were significantly associated with increased odds of low birth weight delivery in both the unadjusted model (OR = 1.43, 95% CI: 1.14–1.80, P = 0.002), and the adjusted model with an a priori confounder set (OR = 1.33, 95% CI: 1.02–1.74, P = 0.038). Nitrite was also significantly associated with increased odds of the combined outcome of preterm and/or low birth weight delivery in the unadjusted model (OR = 1.26, 95% CI: 1.01–1.57, P = 0.036). After a priori confounder adjustment, the inverse association between nitrate and preterm delivery was attenuated and no longer statistically significant (OR = 0.98, 95% CI: 0.96–1.00, P = 0.104). In the North Ghor region, nitrite levels remained significantly associated with low birth weight in the unadjusted model (OR = 1.35, 95% CI: 1.02–1.79, P = 0.034), and nitrate levels were significantly, but weakly, associated with the combined outcome in the unadjusted model (OR = 1.02, 95% CI: 1.00–1.04, P = 0.033). In South Ghor, the inverse association between nitrate and preterm delivery did not persist after a priori adjustment (OR = 0.98, 95% CI: 0.96–1.01, P = 0.140), while nitrite levels were significantly associated with low birth weight in the unadjusted model (OR = 1.66, 95% CI: 1.02–2.68, P = 0.040). These findings suggest that elevated maternal nitrite may increase the risk of low birth weight. The inverse association between nitrate and preterm delivery, by contrast, was weak and did not remain statistically significant after a priori confounder adjustment, and should be interpreted with caution. In a multiple‐imputation sensitivity analysis accounting for missing covariate data, nitrite remained significantly associated with low birth weight (OR = 1.45, 95% CI: 1.13–1.86, P = 0.003) and with the combined outcome of preterm and/or low birth weight (OR = 1.29, 95% CI: 1.03–1.63, P = 0.029).

Table 4.

Unadjusted and Adjusted Logistic Regression Models Assessing Associations Between Maternal Serum Nitrite/Nitrate Levels and Low Birth Weight/Preterm Pregnancy Outcomes

Region/outcome/exposure Unadjusted analysis Adjusted analysis a
Unadjusted OR 95% CI P‐value Adjusted OR 95% CI P‐value
North and South Ghor combined
Preterm and/or low birth weight
Nitrite (μM) 1.26 1.01–1.57 0.036 1.25 0.96–1.61 0.093
Nitrate (μM) 1.00 0.99–1.01 0.670 1.00 0.99–1.02 0.570
Preterm delivery
Nitrite (μM) 0.93 0.69–1.25 0.616 1.00 0.71–1.40 0.978
Nitrate (μM) 0.99 0.97–1.01 0.201 0.98 0.96–1.00 0.104
Low birth weight
Nitrite (μM) 1.43 1.14–1.80 0.002 1.33 1.02–1.74 0.038
Nitrate (μM) 1.00 0.99–1.02 0.494 1.01 1.00–1.02 0.169
North Ghor
Preterm and/or low birth weight
Nitrite (μM) 1.25 0.96–1.64 0.100 1.13 0.80–1.59 0.484
Nitrate (μM) 1.02 1.00–1.04 0.033 1.03 1.01–1.06 0.013
Preterm delivery
Nitrite (μM) 1.15 0.82–1.61 0.422 1.25 0.83–1.89 0.275
Nitrate (μM) 1.01 0.98–1.03 0.564 0.99 0.96–1.03 0.759
Low birth weight
Nitrite (μM) 1.35 1.02–1.79 0.034 1.10 0.77–1.59 0.598
Nitrate (μM) 1.02 1.00–1.04 0.074 1.04 1.01–1.07 0.006
South Ghor
Preterm and/or low birth weight
Nitrite (μM) 1.36 0.87–2.12 0.179 1.48 0.89–2.44 0.129
Nitrate (μM) 0.99 0.97–1.01 0.224 0.99 0.97–1.01 0.387
Preterm delivery
Nitrite (μM) 0.79 0.41–1.52 0.481 0.85 0.43–1.68 0.635
Nitrate (μM) 0.98 0.96–1.00 0.071 0.98 0.96–1.01 0.140
Low birth weight
Nitrite (μM) 1.66 1.02–2.68 0.040 1.74 1.02–2.99 0.044
Nitrate (μM) 0.99 0.98–1.01 0.499 1.00 0.98–1.02 0.816
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a

Unadjusted models include both nitrite and nitrate (mutually adjusted). Adjusted models force in an a priori confounder set (maternal age, household income, maternal education, smoking during pregnancy, pre‐pregnancy body mass index, parity, anemia during pregnancy, and maternal history of low birth weight); gestational hypertension was excluded from the primary models as a probable mediator. Each exposure (nitrate and nitrite) was entered as a continuous variable in the models.

4. Discussion

This study demonstrated a significant association between elevated maternal serum nitrite levels (as biomarkers of environmental exposure) and an increased risk of delivering low birth weight infants consistent across both unadjusted and adjusted models. Higher maternal serum nitrate levels showed a weak inverse association with PB that did not remain statistically significant after a priori confounder adjustment. These findings underscore the complex and potentially divergent roles of nitrate and nitrite in pregnancy physiology.

Previous research has reported mixed findings regarding gestational exposure to nitrate and low birth weight/preterm pregnancy outcomes (Blake, 2014; Coffman et al., 2021; Ferguson et al., 2013; Jensen et al., 2023; Migeot et al., 2013; Reuther et al., 2025; Stayner et al., 2017; Temkin et al., 2019). A large population‐based study in California involving 1.4 million births reported a higher risk of very early PB among women exposed to elevated nitrate levels in drinking water (Sherris et al., 2021). Similarly, Bukowski et al. (Bukowski et al., 2001) identified a dose–response relationship between groundwater nitrate and PB in Prince Edward Island. Conversely, other studies have found minimal or no associations (Albouy‐Llaty et al., 2016; Stayner et al., 2017), reflecting inconsistencies in existing literature. Super et al. (1981), for instance, reported no direct association between high water nitrate levels and outcomes such as birth weight or PB, although increased infant mortality was observed among previous offspring of mothers residing in high‐nitrate areas. Serum‐based assessments of nitrate and nitrite, while less commonly employed, offer valuable insights. One such study found that serum nitrite concentrations were significantly lower during both induced and spontaneous preterm labor compared to controls, whereas serum nitrate levels did not differ significantly (Diejomaoh et al., 2003). In addition, prenatal exposure to nitrosatable drugs in conjunction with higher levels of dietary nitrite intake have been shown to increase the risk of PB (Vuong et al., 2016). Methodological limitations, including potential exposure misclassification, small sample sizes, and inconsistent outcome definitions, limit the comparability and generalizability of many previous studies (Manassaram et al., 2007; Ward, 2009).

From a biological perspective, nitrate may exert a protective effect through its role as a precursor of NO, a key mediator of vasodilation and uteroplacental blood flow (Mukosera et al., 2020). Nitric oxide is essential in maintaining placental function and supporting fetal growth (Pels et al., 2023; Zullino et al., 2018). As a reservoir for NO, nitrate may enhance placental perfusion, reduce uterine contractility, and support full‐term gestation. Thus, elevated nitrate levels could indicate adequate NO bioavailability, contributing to a decreased risk of PB, which is what we found in our study. Because we measured serum levels near delivery, our findings may not reflect exposures during critical earlier stages of pregnancy, limiting our ability to draw causal conclusions. Prior studies have shown that maternal nitrate and nitrite levels vary across trimesters, with levels peaking during the second and third trimesters and declining near term (Diejomaoh et al., 2003), suggesting that the timing of exposure measurement is an important consideration.

On the other hand, the observed association between elevated maternal serum nitrite and the increased risk of low birth weight may reflect underlying oxidative or nitrosative stress that may reflect pathological conditions (Hanff et al., 2017; Rozanova et al., 2012). Nitrite may indicate a disturbance in the NO homeostasis and the production of NO metabolites, which may impair the physiological function of the placenta and the transport of nutrients (Mukosera et al., 2020, 2022). Given that pregnancy is already a state characterized by heightened oxidative stress, elevated nitrite levels may further exacerbate placental dysfunction and fetal compromise. In support of this, NO levels in the fetal‐placental circulation have been shown to be elevated in intrauterine growth restriction (Lyall et al., 1996). The changes of nitrite levels during pregnancy and the factors associated with them have not been adequately investigated. One study showed that nitrite concentrations in amniotic fluid remain stable throughout pregnancy until the 37th week, after which they begin to decrease (Morris et al., 1995). A previous study comparing nitrite and nitrate levels in newborns found that urinary excretion levels were significantly higher in preterm infants than in full‐term infants (Tsukahara, Hiraoka, et al., 1997; Tsukahara, Takeuchi, et al., 1997). An alternative mechanism by which maternal blood nitrite might affect birth weight is by modulation of the insulin sensitivity pathway. Nitrite has been shown to stimulate insulin secretion and to increase insulin sensitivity of body cells (Nyström et al., 2012). High circulating nitrite levels might lead to low blood sugar levels and, subsequently, low fetal weight gain. In support of this, maternal diabetes is associated with increased birth weight (Silveira et al., 2021). Finally, serum nitrite levels may reflect pregnancy‐related infections and placental dysfunction. For example, PB and low birth weight have been shown to be associated with asymptomatic bacteriuria (Romero et al., 1989). In addition, nitrite and nitrate levels in vaginal secretions are higher in PB compared to full term birth (Nakatsuka et al., 2000). In this case, vaginal and urinary tract infections can lead to elevated blood nitrite levels by bacterial conversion of nitrate to nitrite and subsequent body reabsorption. Moreover, Placental insufficiency presents a paradox: while NO‐mediated signaling is required, traditional production methods fail. Nitrite serves as a vital, stress‐responsive reservoir that converts into NO to compensate, yet it contributes to damaging stress when this system is overwhelmed and nitrite levels buildup (Hollenberg & Cinel, 2009). Thus, the relationships between nitrite and pregnancy outcomes seem to be complex and require further studies. Moreover, because elevated nitrite levels could be a consequence, rather than a cause of PB or fetal growth restriction, the interpretability of these findings is limited.

It is worth noting that nitrite and nitrate play beneficial roles in the body, such as protecting the cardiovascular system, regulating blood pressure, and the proper functioning of the immune system (Ashworth & Bescos, 2017; Bondonno et al., 2016). Nitrate supplements are suggested to be effective in the management of preeclampsia (Ormesher et al., 2018). The human body appears to require adequate levels of nitrate and nitrite, and low or high levels may be associated with health conditions, as observed in the current study. Furthermore, the relationship between nitrate or nitrite and health appears complex and may depend on an individual's health status.

Finally, the study showed slight regional differences (North Ghor vs. South Ghor) in the observed associations between nitrite and nitrite and pregnancy outcomes. The degree of exposure to these particles depends on several factors, including the quality of water used for irrigation and drinking, dietary lifestyles, oral microbiome, and environmental/climate factors (Blekkenhorst et al., 2018; Dirnböck et al., 2016; Hord et al., 2009).

Unlike prior studies that primarily assessed environmental or drinking water nitrate exposure, this study focused on maternal serum concentrations, which may more accurately reflect individual internal exposure. However, the observed inverse association between nitrate levels and PB should be interpreted with caution. The effect size was modest, and the CI approached the null value, suggesting that the finding may be attributable to residual confounding or chance. Moreover, given the multiple comparisons conducted across outcomes, exposures, and models, some borderline associations, particularly the inverse relationship between nitrate and PB, should be interpreted cautiously. In addition, given the observational nature of this study, causality cannot be inferred. Moreover, blood nitrite levels, in addition to environmental exposure, are strongly influenced by infection, inflammation, and oral microbiome activity, which should be accounted for in future studies. We also did not directly validate serum nitrate and nitrite levels against environmental measurements (e.g., drinking water sources). Although these biomarkers reflect internal exposure from multiple sources, they are also influenced by physiological and metabolic factors during pregnancy, which limits the ability to attribute observed associations to specific exposure pathways during the full period of pregnancy.

Additional research is warranted to validate these findings and elucidate the underlying mechanisms including sources of exposure and the impact of climate change. Future work should link nitrate and nitrite serum levels with drinking‐water measurements, diet, and repeated pregnancy sampling across gestation. Exposure levels according to reported agricultural work, water source, or region should be evaluated. Finally, more studies with larger samples are needed to better examine regional differences in exposure and nitrite/nitrate serum levels.

5. Conclusion

The study indicates that higher maternal serum nitrite near delivery is linked to increased odds of low birth weight in an agricultural Jordanian population. A weak inverse association between nitrate and PB was observed in some models but did not remain statistically significant after a priori confounder adjustment, and therefore warrants cautious interpretation. These findings could be useful in interventions aimed at managing low birth weight and preterm pregnancy outcomes in the Ghor region of Jordan. Potential preventive interventions should focus on water quality monitoring, maternal nutrition, or broader agricultural‐environmental controls.

Global Research Collaboration

This work was possible as a result of several years of planning and collaboration through the GeoHealth Hub on Climate Change and Health in the Middle East and North Africa, funded by the Fogarty International Center. Through this collaboration with the University of California, San Diego, the Jordan University of Science and Technology, represented by the Principal Investigators, Dr. Abdullah spearheaded the team that carried out the data collection and coordinated the sampling and analyses through the effort of Dr. Khabour. The invaluable insight and expertise of Dr. Khader helped the research team overcome the logistical hurdles and achieve a high participation rate. This collaborative approach is important for similar work between high‐income and low and middle‐income researchers and institutions.

Conflict of Interest

The authors declare no conflicts of interest relevant to this study.

Acknowledgments

The study was supported by funds from the GeoHealth Hub for Climate Change and Health in the Middle East and North Africa (Fogarty NIH awards number 5U2RTW012228 and U01TW012237).

Availability Statement

The data set supporting this study can be accessed via the Mendeley Data repository (Al‐Delaimy et al., 2026) under https://doi.org/10.17632/jr55h7krrk.1.

References

  1. Albouy‐Llaty, M. , Limousi, F. , Carles, C. , Dupuis, A. , Rabouan, S. , & Migeot, V. (2016). Association between exposure to endocrine disruptors in drinking water and preterm birth, taking neighborhood deprivation into account: A historic cohort study. International Journal of Environmental Research and Public Health, 13(8), 796. 10.3390/ijerph13080796 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Al‐Delaimy, W. , Abdulla, F. , Khader, Y. , & Khabour, O. (2026). Blood nitrate and nitrite associations with birth outcomes [Dataset]. Mendeley Data. 10.17632/JR55H7KRRK.1 [DOI]
  3. Alwedyan, S. , & Taani, A. (2021). Adoption of sustainable agriculture practices by citrus farmers and its determinants in the Jordan valley: The case of Northern Ghor. Slovak Journal of Food Sciences/Potravinarstvo, 15(1), 768–775. 10.5219/1676 [DOI] [Google Scholar]
  4. Anbar, A. (1983). Socio‐Economic aspects of the East Ghor canal Project, Jordan (PhD thesis). University of Southampton. Retrieved from https://www.researchgate.net/publication/344403625_Socio_Economic_Aspects_of_the_East_Ghor_Canal_Project_Jordan_almzahr_alajtmayt_w_alaqtsadyt_lmshrw_qnat_alghwr_alshrqyt_alardn [Google Scholar]
  5. Ashworth, A. , & Bescos, R. (2017). Dietary nitrate and blood pressure: Evolution of a new nutrient? Nutrition Research Reviews, 30(2), 208–219. 10.1017/s0954422417000063 [DOI] [PubMed] [Google Scholar]
  6. Averin, K. , Ryerson, L. , Hajihosseini, M. , Dinu, I. A. , Freed, D. H. , Bond, G. , et al. (2023). Infants less than or equal to 2.5 kg have increased mortality and worse motor neurodevelopmental outcomes at 2 years of age after Norwood–Sano palliation. JTCVS open, 14, 417–425. 10.1016/j.xjon.2023.03.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Blake, S. B. (2014). Spatial relationships among dairy farms, drinking water quality, and maternal‐child health outcomes in the San Joaquin Valley. Public Health Nursing, 31(6), 492–499. 10.1111/phn.12166 [DOI] [PubMed] [Google Scholar]
  8. Blekkenhorst, L. C. , Bondonno, N. P. , Liu, A. H. , Ward, N. C. , Prince, R. L. , Lewis, J. R. , et al. (2018). Nitrate, the oral microbiome, and cardiovascular health: A systematic literature review of human and animal studies. American Journal of Clinical Nutrition, 107(4), 504–522. 10.1093/ajcn/nqx046 [DOI] [PubMed] [Google Scholar]
  9. Bondonno, C. P. , Croft, K. D. , & Hodgson, J. M. (2016). Dietary nitrate, nitric oxide, and cardiovascular health. Critical Reviews in Food Science and Nutrition, 56(12), 2036–2052. 10.1080/10408398.2013.811212 [DOI] [PubMed] [Google Scholar]
  10. Boyacioglu, H. , Gunacti, M. C. , Barbaros, F. , Gul, A. , Gul, G. O. , Ozturk, T. , & Kurnaz, M. L. (2024). Impact of climate change and land cover dynamics on nitrate transport to surface waters. Environmental Monitoring and Assessment, 196(3), 270. 10.1007/s10661-024-12402-x [DOI] [PubMed] [Google Scholar]
  11. Bukowski, J. , Somers, G. , & Bryanton, J. (2001). Agricultural contamination of groundwater as a possible risk factor for growth restriction or prematurity. Journal of Occupational and Environmental Medicine, 43(4), 377–383. 10.1097/00043764-200104000-00016 [DOI] [PubMed] [Google Scholar]
  12. Christie, I. N. , Theparambil, S. M. , Braga, A. , Doronin, M. , Hosford, P. S. , Brazhe, A. , et al. (2023). Astrocytes produce nitric oxide via nitrite reduction in mitochondria to regulate cerebral blood flow during brain hypoxia. Cell Reports, 42(12), 113514. 10.1016/j.celrep.2023.113514 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Coffman, V. R. , Jensen, A. S. , Trabjerg, B. B. , Pedersen, C. B. , Hansen, B. , Sigsgaard, T. , et al. (2021). Prenatal exposure to nitrate from drinking water and markers of fetal growth restriction: A population‐based Study of nearly one million Danish‐Born children. Environmental Health Perspectives, 129(2), 27002. 10.1289/ehp7331 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dannenmann, M. , Bimüller, C. , Gschwendtner, S. , Leberecht, M. , Tejedor, J. , Bilela, S. , et al. (2016). Climate change impairs nitrogen cycling in European Beech forests. PLoS One, 11(7), e0158823. 10.1371/journal.pone.0158823 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Diejomaoh, M. F. , Omu, A. E. , Taher, S. , Al‐Busiri, N. , Fatinikun, T. , Fernandes, S. , & Al‐Othman, S. (2003). Nitric oxide metabolites in preterm and induced labor. Gynecologic and Obstetric Investigation, 56(4), 197–202. 10.1159/000074452 [DOI] [PubMed] [Google Scholar]
  16. Dirnböck, T. , Kobler, J. , Kraus, D. , Grote, R. , & Kiese, R. (2016). Impacts of management and climate change on nitrate leaching in a forested karst area. J Environ Manage, 165, 243–252. 10.1016/j.jenvman.2015.09.039 [DOI] [PubMed] [Google Scholar]
  17. Ferguson, K. K. , O'Neill, M. S. , & Meeker, J. D. (2013). Environmental contaminant exposures and preterm birth: A comprehensive review. Journal of Toxicology and Environmental Health Part B: Critical Reviews, 16(2), 69–113. 10.1080/10937404.2013.775048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Frontera, W. , Spicer, C. M. , & Applegate, A. (2024). Low birth weight babies and disability. The National Academies Press. [PubMed] [Google Scholar]
  19. Habermeyer, M. , Roth, A. , Guth, S. , Diel, P. , Engel, K. H. , Epe, B. , et al. (2015). Nitrate and nitrite in the diet: How to assess their benefit and risk for human health. Molecular Nutrition & Food Research, 59(1), 106–128. 10.1002/mnfr.201400286 [DOI] [PubMed] [Google Scholar]
  20. Hanff, E. , Eisenga, M. F. , Beckmann, B. , Bakker, S. J. , & Tsikas, D. (2017). Simultaneous pentafluorobenzyl derivatization and GC‐ECNICI‐MS measurement of nitrite and malondialdehyde in human urine: Close positive correlation between these disparate oxidative stress biomarkers. Journal of Chromatography, B: Analytical Technologies in the Biomedical and Life Sciences, 1043, 167–175. 10.1016/j.jchromb.2016.07.027 [DOI] [PubMed] [Google Scholar]
  21. Hollenberg, S. M. , & Cinel, I. (2009). Bench‐to‐bedside review: Nitric oxide in critical illness–update 2008. Critical Care, 13(4), 218. 10.1186/cc7706 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Hord, N. G. , Tang, Y. , & Bryan, N. S. (2009). Food sources of nitrates and nitrites: The physiologic context for potential health benefits. American Journal of Clinical Nutrition, 90(1), 1–10. 10.3945/ajcn.2008.27131 [DOI] [PubMed] [Google Scholar]
  23. Jańczewska, I. , Wierzba, J. , Jańczewska, A. , Szczurek‐Gierczak, M. , & Domżalska‐Popadiuk, I. (2023). Prematurity and low birth weight and their impact on childhood growth patterns and the risk of long‐term cardiovascular sequelae. Children, 10(10), 1599. 10.3390/children10101599 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Jensen, A. S. , Coffman, V. R. , Schullehner, J. , Trabjerg, B. B. , Pedersen, C. B. , Hansen, B. , et al. (2023). Prenatal exposure to tap water containing nitrate and the risk of small‐for‐gestational‐age: A nationwide register‐based study of Danish births, 1991–2015. Environment International, 174, 107883. 10.1016/j.envint.2023.107883 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lidder, S. , & Webb, A. J. (2013). Vascular effects of dietary nitrate (as found in green leafy vegetables and beetroot) via the nitrate‐nitrite‐nitric oxide pathway. British Journal of Clinical Pharmacology, 75(3), 677–696. 10.1111/j.1365-2125.2012.04420.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lv, P. , Sun, S. , Li, Y. , Zhao, S. , Zhang, J. , Hu, Y. , et al. (2024). Plant composition change mediates climate drought, nitrogen addition, and grazing effects on soil net nitrogen mineralization in a semi‐arid grassland in North China. Science of the Total Environment, 908, 168282. 10.1016/j.scitotenv.2023.168282 [DOI] [PubMed] [Google Scholar]
  27. Lyall, F. , Greer, I. A. , Young, A. , & Myatt, L. (1996). Nitric oxide concentrations are increased in the feto‐placental circulation in intrauterine growth restriction. Placenta, 17(2–3), 165–168. 10.1016/s0143-4004(96)80009-9 [DOI] [PubMed] [Google Scholar]
  28. Mahmoud, A. A. (1983). Climate and agriculture of Jordan (Master's thesis). South Dakota State University. Retrieved from https://openprairie.sdstate.edu/etd/4379/ [Google Scholar]
  29. Manassaram, D. M. , Backer, L. C. , & Moll, D. M. (2007). A review of nitrates in drinking water: Maternal exposure and adverse reproductive and developmental outcomes. Ciência & Saúde Coletiva, 12(1), 153–163. 10.1590/s1413-81232007000100018 [DOI] [PubMed] [Google Scholar]
  30. Migeot, V. , Albouy‐Llaty, M. , Carles, C. , Limousi, F. , Strezlec, S. , Dupuis, A. , & Rabouan, S. (2013). Drinking‐water exposure to a mixture of nitrate and low‐dose atrazine metabolites and small‐for‐gestational age (SGA) babies: A historic cohort study. Environmental Research, 122, 58–64. 10.1016/j.envres.2012.12.007 [DOI] [PubMed] [Google Scholar]
  31. Miranda, K. M. , Espey, M. G. , & Wink, D. A. (2001). A rapid, simple spectrophotometric method for simultaneous detection of nitrate and nitrite. Nitric Oxide, 5(1), 62–71. 10.1006/niox.2000.0319 [DOI] [PubMed] [Google Scholar]
  32. Montoya, E. S. (2025). Birth outcome effects of nitrate contamination in drinking water. Journal of Environmental Economics and Management, 133, 103197. 10.1016/j.jeem.2025.103197 [DOI] [Google Scholar]
  33. Morris, N. H. , Carroll, S. , Nicolaides, K. H. , Steer, P. J. , & Warren, J. B. (1995). Exhaled nitric oxide concentration and amniotic fluid nitrite concentration during pregnancy. European Journal of Clinical Investigation, 25(2), 138–141. 10.1111/j.1365-2362.1995.tb01539.x [DOI] [PubMed] [Google Scholar]
  34. Mukosera, G. T. , Clark, T. C. , Ngo, L. , Liu, T. , Schroeder, H. , Power, G. G. , et al. (2020). Nitric oxide metabolism in the human placenta during aberrant maternal inflammation. The Journal of Physiology, 598(11), 2223–2241. 10.1113/jp279057 [DOI] [PubMed] [Google Scholar]
  35. Mukosera, G. T. , Principe, P. , Mata‐Greenwood, E. , Liu, T. , Schroeder, H. , Parast, M. , & Blood, A. B. (2022). Iron nitrosyl complexes are formed from nitrite in the human placenta. Journal of Biological Chemistry, 298(7), 102078. 10.1016/j.jbc.2022.102078 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Nakatsuka, M. , Habara, T. , Kamada, Y. , Tada, K. , & Kudo, T. (2000). Elevation of total nitrite and nitrate concentration in vaginal secretions as a predictor of premature delivery. American Journal of Obstetrics and Gynecology, 182(3), 644–645. 10.1067/mob.2000.104223 [DOI] [PubMed] [Google Scholar]
  37. Nyström, T. , Ortsäter, H. , Huang, Z. , Zhang, F. , Larsen, F. J. , Weitzberg, E. , et al. (2012). Inorganic nitrite stimulates pancreatic islet blood flow and insulin secretion. Free Radical Biology and Medicine, 53(5), 1017–1023. 10.1016/j.freeradbiomed.2012.06.031 [DOI] [PubMed] [Google Scholar]
  38. Ormesher, L. , Myers, J. E. , Chmiel, C. , Wareing, M. , Greenwood, S. L. , Tropea, T. , et al. (2018). Effects of dietary nitrate supplementation, from beetroot juice, on blood pressure in hypertensive pregnant women: A randomised, double‐blind, placebo‐controlled feasibility trial. Nitric Oxide, 80, 37–44. 10.1016/j.niox.2018.08.004 [DOI] [PubMed] [Google Scholar]
  39. Patel, N. , Srivastav, A. L. , Patel, A. , Singh, A. , Singh, S. K. , Chaudhary, V. K. , et al. (2022). Nitrate contamination in water resources, human health risks and its remediation through adsorption: A focused review. Environmental Science and Pollution Research International, 29(46), 69137–69152. 10.1007/s11356-022-22377-2 [DOI] [PubMed] [Google Scholar]
  40. Pels, A. , Ganzevoort, W. , Kenny, L. C. , Baker, P. N. , von Dadelszen, P. , Gluud, C. , et al. (2023). Interventions affecting the nitric oxide pathway versus placebo or no therapy for fetal growth restriction in pregnancy. Cochrane Database of Systematic Reviews, 7(7), Cd014498. 10.1002/14651858.cd014498 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Reuther, P. S. , Geng, G. , Liu, Y. , Darrow, L. A. , & Strickland, M. J. (2025). Associations between satellite‐derived estimates of PM2.5 species concentrations for organic carbon, elemental carbon, nitrate, and sulfate with birth weight and preterm birth in California during 2005–2014. Journal of Exposure Science and Environmental Epidemiology, 35(2), 233–241. 10.1038/s41370-024-00673-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Romero, R. , Oyarzun, E. , Mazor, M. , Sirtori, M. , Hobbins, J. C. , & Bracken, M. (1989). Meta‐analysis of the relationship between asymptomatic bacteriuria and preterm delivery/low birth weight. Obstetrics & Gynecology, 73(4), 576–582. [PubMed] [Google Scholar]
  43. Rozanova, S. , Cherkashina, Y. , Repina, S. , Rozanova, K. , & Nardid, O. (2012). Protective effect of placenta extracts against nitrite‐induced oxidative stress in human erythrocytes. Cellular & Molecular Biology Letters, 17(2), 240–248. 10.2478/s11658-012-0007-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Semprini, J. (2025). Early prenatal nitrate exposure and birth outcomes: A study of Iowa’s public drinking water (1970–1988). PLoS Water, 4(6), e0000329. 10.1371/journal.pwat.0000329 [DOI] [Google Scholar]
  45. Sherris, A. R. , Baiocchi, M. , Fendorf, S. , Luby, S. P. , Yang, W. , & Shaw, G. M. (2021). Nitrate in drinking water during pregnancy and spontaneous preterm birth: A retrospective within‐mother analysis in California. Environmental Health Perspectives, 129(5), 57001. 10.1289/ehp8205 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Silveira, L. , Schmidt, M. I. , Reichelt, A. A. J. , & Drehmer, M. (2021). Obesity, gestational weight gain, and birth weight in women with gestational diabetes: The LINDA‐Brasil (2014–2017) and the EBDG (1991–1995) studies. Journal of Pediatrics, 97(2), 167–176. 10.1016/j.jped.2020.02.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Stayner, L. T. , Almberg, K. , Jones, R. , Graber, J. , Pedersen, M. , & Turyk, M. (2017). Atrazine and nitrate in drinking water and the risk of preterm delivery and low birth weight in four Midwestern states. Environmental Research, 152, 294–303. 10.1016/j.envres.2016.10.022 [DOI] [PubMed] [Google Scholar]
  48. Sukuroglu, E. , Güncü, G. N. , Kilinc, K. , & Caglayan, F. (2015). Using salivary nitrite and nitrate levels as a biomarker for drug‐induced gingival overgrowth. Frontiers in Cellular and Infection Microbiology, 5, 87. 10.3389/fcimb.2015.00087 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Super, M. , Heese, H. d. V. , MacKenzie, D. , Dempster, W. , Du Plessis, J. , & Ferreira, J. (1981). An epidemiological study of well‐water nitrates in a group of South West African/Namibian infants. Water Research, 15(11), 1265–1270. 10.1016/0043-1354(81)90103-2 [DOI] [Google Scholar]
  50. Temkin, A. , Evans, S. , Manidis, T. , Campbell, C. , & Naidenko, O. V. (2019). Exposure‐based assessment and economic valuation of adverse birth outcomes and cancer risk due to nitrate in United States drinking water. Environmental Research, 176, 108442. 10.1016/j.envres.2019.04.009 [DOI] [PubMed] [Google Scholar]
  51. Tsukahara, H. , Hiraoka, M. , Hori, C. , Tsuchida, S. , Hata, I. , Nishida, K. , et al. (1997). Urinary nitrite/nitrate excretion in infancy: Comparison between term and preterm infants. Early Human Development, 47(1), 51–56. 10.1016/s0378-3782(96)01768-9 [DOI] [PubMed] [Google Scholar]
  52. Tsukahara, H. , Takeuchi, M. , Hata, I. , Hiraoka, M. , Kotsuji, F. , Sudo, M. , & Mayumi, M. (1997). Assessment of endogenous nitric oxide formation in newborns: Measurement of urinary nitrite and nitrate concentrations. Biology of the Neonate, 72(5), 322–326. 10.1159/000244499 [DOI] [PubMed] [Google Scholar]
  53. Vuong, A. M. , Shinde, M. U. , Brender, J. D. , Shipp, E. M. , Huber Jr, J. C. , Sharkey, J. R. , et al. (2016). Prenatal exposure to nitrosatable drugs, dietary intake of nitrites, and preterm birth. American Journal of Epidemiology, 183(7), 634–642. 10.1093/aje/kwv250 [DOI] [PubMed] [Google Scholar]
  54. Ward, M. H. (2009). Too much of a good thing? Nitrate from nitrogen fertilizers and cancer. Reviews on Environmental Health, 24(4), 357–363. 10.1515/reveh.2009.24.4.357 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Washio, J. , & Takahashi, N. (2025). Nitrite production from nitrate in the oral microbiome and its contribution to oral and systemic health. Advances in Experimental Medicine and Biology, 1472, 89–101. 10.1007/978-3-031-79146-8_6 [DOI] [PubMed] [Google Scholar]
  56. Zullino, S. , Buzzella, F. , & Simoncini, T. (2018). Nitric oxide and the biology of pregnancy. Vascular Pharmacology, 110, 71–74. 10.1016/j.vph.2018.07.004 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Al‐Delaimy, W. , Abdulla, F. , Khader, Y. , & Khabour, O. (2026). Blood nitrate and nitrite associations with birth outcomes [Dataset]. Mendeley Data. 10.17632/JR55H7KRRK.1 [DOI]

Data Availability Statement

The data set supporting this study can be accessed via the Mendeley Data repository (Al‐Delaimy et al., 2026) under https://doi.org/10.17632/jr55h7krrk.1.

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