Abstract
Background
Periodontitis is associated with poor pregnancy outcomes, indicating periodontal health as an important health concern for pregnant women. Herein, this study identified risk indicators for periodontitis and developed a nomogram for predicting the risk of periodontitis in pregnancy by analyzing periodontitis and associated factors in pregnant women.
Materials and methods
A community-based cross-sectional study was conducted by including 438 pregnant women at 10–36 gestational weeks from Langfang, China. Pregnant women were examined for periodontal status, and their demographic, socioeconomic, and oral health behavior data were collected. Potential influencing factors of periodontitis were analyzed with univariate and multivariate logistic regression analyses. A nomogram was developed, followed by the assessment of its validation and discriminatory abilities.
Results
The prevalence of periodontitis was 59.8% in pregnant women. Periodontitis-associated variables in pregnant women were gestational age, non-first pregnancy, daily tooth brushing frequency of ≤ 1 before pregnancy, and annual frequency of periodontal treatment < 1 (including no periodontal treatment). The risk of periodontitis was positively associated with gestational age (OR = 1.28, 95% CI = 1.17–1.39, p < 0.001). Pregnancy history showed a strong positive association (OR = 6.57, 95% CI = 1.22–35.43, p = 0.03). Daily tooth brushing frequency before pregnancy was also positively associated with periodontitis (OR = 1.54, 95% CI = 1.03–2.79, p = 0.05). Additionally, the annual frequency of periodontal treatment exhibited a positive association, with higher odds observed for those with less frequent treatment (OR = 2.28, 95% CI = 1.25–4.14, p = 0.05; OR = 7.37, 95% CI = 3.04–22.06, p < 0.001). These four factors were used to develop a nomogram for predicting periodontitis in pregnant women. The area under the receiver operating characteristic curve of the nomogram was 0.855 and 0.831 in the training and testing cohorts, respectively, reflecting the superior prediction accuracy of the nomogram. The calibration curve and decision curve analysis demonstrated the good performance and net benefit of the nomogram.
Conclusion
Risk factors for periodontitis in pregnant Chinese women include gestational age, non-first pregnancy, lower frequency of daily tooth brushing before pregnancy, and lower frequency of periodontal treatment. An easy-to-use nomogram with acceptable accuracy can allow for the prediction of periodontitis risk in pregnant Chinese women.
Clinical relevance
With the assistance of this nomogram, clinicians can evaluate the risk of periodontitis in pregnancy, thereby offering more tailored oral health education to women of reproductive age.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12903-024-04640-9.
Keywords: Nomogram, Periodontitis, Pregnant women, Oral health behaviors
Background
Periodontitis originates from gingival tissues following bacterial biofilm formation, which is characterized by periodontal attachment loss due to microbially-associated, host-mediated inflammation. The onset and progression of periodontitis are determined not only by microbiome changes resulting from tissue breakdown products but also by antibacterial mechanisms curbing microorganisms in gingival tissues [1]. The association between oral health and systemic health has recently garnered increasing attention, and periodontal pathogens have been widely confirmed to promote systemic inflammation and cause organ-specific dysfunctions.
Periodontal pathogens can cause or facilitate cardiovascular diseases, diabetes, Alzheimer’s disease, and adverse pregnancy outcomes (APOs) [2, 3]. Oral changes during pregnancy are attributable to several underlying metabolic and physiological changes. For instance, fluctuating sex steroid hormones produce certain changes in target tissues such as periodontium [4]. Inflammatory and immune responses in pregnant women play an essential role in periodontal disease. Additionally, the initiation and persistence of periodontal disease are associated with increased levels of hormones and subgingival microflora-related factors. In 1996, Offenbacher et al. observed that the risk of preterm labor and low birth weight of newborns was seven times higher in women with periodontitis than in control women. The contributory effect of periodontitis on APOs has been broadly demonstrated [5]. For example, several studies have revealed that periodontitis can compromise the quality of life and the course and outcomes of pregnancy in women [6, 7]. In this context, the relationship between APOs and periodontitis in pregnant women has been extensively studied. APOs, such as preeclampsia, usually occur at a subclinical stage during the first trimester of pregnancy [8]. Treatment of periodontitis may improve birth outcomes [9]. Therefore, early diagnosis of periodontitis and control of its risk factors are crucial for pregnant women. Overall, proper oral health care and oral health preventive services should be provided to women before pregnancy to prevent or reduce the occurrence of periodontitis during pregnancy.
Despite the negative impact of periodontitis in pregnancy on maternal and newborn health, no studies have evaluated the oral health knowledge, oral health behavior habits, and sociodemographic factors of Chinese pregnant women with and without periodontitis and analyzed risk factors for periodontitis in pregnancy. On this basis, this community-based cross-sectional study investigated risk factors for periodontitis in pregnancy and developed a nomogram for predicting periodontitis in Chinese pregnant women. The obtained findings may be helpful in designing and planning interventions to foster periodontal health in target populations.
Materials and methods
Sample size and participant recruitment
This study adhered to the Strengthening the reporting of observational studies in epidemiology (STROBE) checklist [10]. The study recruited 438 pregnant women at 10–36 gestation weeks between December 2019 and December 2020 in eight communities in Langfang, China. After being explained the objective of the study, all participants signed a written informed consent form for participation. Participants underwent pregnancy examinations and clinical periodontal evaluation. Women aged 20–35 years at 10–36 gestation weeks were included in the study. Pregnant women were excluded due to a history of systemic diseases such as diabetes mellitus, hypertension, cardiovascular diseases, autoimmune disorders, or renal diseases; high-risk pregnancy including preeclampsia, multiple pregnancies, or placental abnormalities; long-term medication, especially immunosuppressants or anticoagulants.
Convenience sampling was used as the sampling method. Pregnant women attending routine prenatal check-ups at the selected health centers were approached for participation. Those meeting the inclusion criteria and providing informed consent were enrolled in the study. The study protocol was approved by the Ethics Committee of the Peking University Health Science Center (PKUSSIRB-2,020,085,713).
Definition of periodontitis
Women In the context of clinical care, a patient was considered a “periodontitis case” if interdental clinical attachment loss (CAL) is detectable at two or more non-adjacent teeth, or if buccal or oral CAL of 3 mm or more with pocketing of 3 mm or more is detectable at two or more teeth, provided that the observed CAL cannot be attributed to non-periodontitis-related causes such as gingival recession of traumatic origin, dental caries extending into the cervical area of the tooth, the presence of CAL on the distal aspect of a second molar associated with malposition or extraction of a third molar, an endodontic lesion draining through the marginal periodontium, or the occurrence of a vertical root fracture [11].
Data collection
Explanatory variables were obtained via face-to-face interviews with a structured standardized questionnaire involving information on explanatory variables, including demographic variables, socioeconomic factors, and oral health behavior factors. The details of the questionnaire were depicted in the Supplementary martials. Demographic variables comprised age, gestational age (weeks), pregnancy history, ethnicity, and residence type. Socioeconomic factors consisted of monthly household income and educational level. Oral health behavior factors were frequencies of tooth brushing (the total number of tooth brushing per day) and dental flossing, brushing duration and method, smoking status, and annual frequency of periodontal treatment (including supragingival scaling, subgingival scaling and root planing, and oral prophylaxis).
Clinical periodontal evaluation
The periodontal status was diagnosed by examining periodontal clinical parameters, including CAL, probing depth (PD), bleeding index (BI), and plaque index (PLI). CAL and PD were measured at six sites (mesio-buccal, mid-buccal, disto-buccal, mesio-palatal, mid-palatal, and disto-palatal) for all teeth, excluding the third molar, with a Williams periodontal probe. BI was recorded as the probing-induced bleeding index at the buccal/labial and palatal/lingual sides for all teeth except the third molar 30 s after probing. PLI was assessed by gently running a probe along the tooth surface and scoring based on the amount and thickness of the plaque. The Kappa index was calculated based on the inter-examiner agreement for the above periodontal clinical parameters. Clinical periodontal evaluation was performed by two equally experienced dentists, with a mean Kappa value of 0.85 for inter-examiner agreement.
Cohorts for construction and evaluation of the nomogram model
In the process of model construction, the Langfang cohort was utilized, employing random sampling to divide the entire cohort dataset into training and testing chorts at a 7:3 ratio. The training cohort, consisting of 307 individuals, was used for constructing the nomogram prediction model, while the testing cohort, comprising 131 individuals, served for model validation.
Statistical analysis
The characteristics and related variables of participants were compared between the periodontitis (P) and non-periodontitis (NP) groups. Variables were presented as mean ± standard deviation or number (percentage). Continuous variables were analyzed with the Student’s t-test (normal distribution) and Mann–Whitney (skewed distribution) test, while categorical variables were analyzed with the χ2 test. Periodontitis-associated factors were determined with univariate and multivariate logistic regression analyses using the generalized estimating equation. The nomogram was finally selected through a backward step-down selection process with a threshold of p < 0.05, and insignificant factors were excluded from the complete nomogram. Receiver operating characteristic (ROC) curves were utilized to evaluate the discriminatory ability of the nomogram. Statistical analyses were two-tailed and p < 0.05 represented statistically significant differences. All statistical analyses were conducted with R (http://www.R-project.org) and EmpowerStats software (www.empowerstats.com; X&Y Solutions, Boston, Massachusetts, USA).
Results
A total of 438 women at 10 − 36 gestation weeks between December 2019 and December 2020 were enrolled in this study. The participants were allocated into the P and NP groups according to the new classification of periodontal and peri-implant diseases [11]. No significant differences were observed between the P and NP groups in terms of age, smoking status, or ethnicity (p > 0.05; Table 1). PD was obviously different between the two groups (p = 0.01). CAL and PD ≥ 5 mm were markedly higher in the P group than in the NP group (p < 0.001). PLI and BI were insignificantly different between the two groups.
Table 1.
Characteristics of participants
| NP group | P group | p-value | |
|---|---|---|---|
| N (%) | 176 (40.2%) | 262 (59.8%) | |
| Age (years, mean ± SD) | 27.4 ± 4.11 | 28.1 ± 3.54 | 0.53 |
| Ethnicity, n (%) | 0.62 | ||
| Han | 168 (95.4%) | 246 (93.9%) | |
| Non-Han | 8 (4.6%) | 16 (6.1%) | |
| Smoking status, n (%) | 1 | ||
| Never smoking | 171 (97.2%) | 255 (97.3%) | |
| Occasional smoking | 5 (2.8%) | 7 (2.7%) | |
| PLI (mean ± SD) | 1.60 ± 0.05 | 1.79 ± 0.04 | 0.72 |
| PD (mean ± SD) | 2.35 ± 0.18 | 3.49 ± 0.15 | 0.01* |
| BI (mean ± SD) | 1.36 ± 0.19 | 1.58 ± 0.18 | 0.86 |
| CAL (mean ± SD) | 0.00 ± 0.00 | 1.86 ± 0.12 | < 0.001* |
| PD ≥ 5 mm (%, mean ± SD) | 0.00 ± 0.00 | 5.88 ± 1.71 | < 0.001* |
Note P: periodontitis group; NP: non-periodontitis; N: number; SD: standard deviation; PLI: plaque index; PD: probing depth; BI: bleeding index; CAL: clinical attachment loss. *Statistically significant differences between the two groups
Table 2 presents the demographic, socioeconomic, and oral health behavior variables of participants. At the time of examinations, the prevalence of periodontitis was 59.8% in pregnant women. The distributions of gestational age, pregnancy history (first/non-first), residence type (agriculture/non-agriculture), educational level, frequency of daily tooth brushing before pregnancy (≤ 1/≥2), and annual frequency of periodontal treatment (never/< 1/≥ 1) showed marked differences between the NP and P groups (p < 0.05). The educational level and annual frequency of periodontal treatment were remarkably higher in the NP group than in the P group (p < 0.001). There were no significant differences in other variables between the NP and P groups.
Table 2.
Related variables of participants
| Variables | NP group | P group | p-value |
|---|---|---|---|
| Gestational age (weeks, mean ± SD) | 18.8 ± 8.04 | 19.7 ± 7.93 | 0.01* |
| Pregnancy history, n (%) | 0.01* | ||
| First pregnancy | 174 (98.9%) | 245 (93.5%) | |
| Non-first pregnancy | 2 (1.1) | 17 (6.5) | |
| Residence type, n (%) | 0.04* | ||
| Agriculture | 35 (19.9%) | 76 (29.0%) | |
| Non-agriculture | 141 (80.1%) | 186 (71.0%) | |
| Educational level, n (%) | < 0.001* | ||
| Junior high school or below | 34 (19.3%) | 81 (30.9%) | |
| High school or vocational school | 39 (22.2%) | 46 (17.6%) | |
| Junior college or associate degree | 50 (28.4%) | 77 (29.4%) | |
| Bachelor’s degree and above | 53 (30.1%) | 58 (22.1%) | |
| Family household income (RMB), n (%) | 0.22 | ||
| < 3000 | 25 (14.2%) | 43 (16.4%) | |
| 3000–5000 | 72 (40.9%) | 82 (31.3%) | |
| 5000–8000 | 33 (18.8%) | 54 (20.6%) | |
| > 8000 | 46 (26.1%) | 83 (31.7%) | |
| Daily tooth brushing frequency before pregnancy, n (%) | 0.03* | ||
| ≤ 1 | 102 (58.0%) | 162 (61.8%) | |
| ≥ 2 | 74 (42.0%) | 100 (38.2%) | |
| Daily tooth brushing frequency during pregnancy, n (%) | 0.23 | ||
| ≤ 1 | 104 (59.1%) | 157 (59.9%) | |
| ≥ 2 | 72 (40.9%) | 105 (40.1%) | |
| Brushing duration (min), n (%) | 0.19 | ||
| 1–2 | 15 (8.52%) | 19 (7.25%) | |
| ≥ 2 | 103 (58.5%) | 134 (51.1%) | |
| < 1 | 58 (33.0%) | 109 (41.6%) | |
| Brushing method, n (%) | 0.83 | ||
| Horizontal or vertical | 64 (36.4%) | 88 (33.6%) | |
| Both horizontal and vertical | 95 (54.0%) | 147 (56.1%) | |
| Rotational and horizontal vibration method | 17 (9.66%) | 27 (10.3%) | |
| Toothbrush replacement time (month), n (%) | 0.81 | ||
| ≤ 1 | 30 (17.0%) | 51 (19.5%) | |
| 1–3 | 115 (65.3%) | 167 (63.7%) | |
| ≥ 3 | 31 (17.6%) | 44 (16.8%) | |
| Daily dental flossing frequency, n (%) | 0.97 | ||
| ≥ 2 | 6 (3.41%) | 9 (3.44%) | |
| ≤ 1 | 15 (8.52%) | 24 (9.16%) | |
| Never | 155 (88.1%) | 229 (87.4%) | |
| Annual frequency of periodontal treatment, n (%) | < 0.001* | ||
| ≥ 1 | 36 (20.5%) | 42 (16.1%) | |
| < 1 | 40 (22.7%) | 53 (20.2%) | |
| Never | 100 (56.8%) | 167 (63.7%) |
Note P: periodontitis group; NP: non-periodontitis; N: number, SD: standard deviation. * Statistically significant differences between the two groups
Table 3 displays the results of the univariate logistic analysis of risk factors for periodontitis in pregnant women. Periodontitis in pregnant women was associated with gestational age (weeks; odds ratio [OR] = 1.29, 95% confidence interval [CI] = 1.20–1.38, p < 0.001), pregnancy history (OR = 5.45, 95%CI = 1.22–24.26, p < 0.03), residence type (OR = 0.57, 95%CI = 0.33–0.99, p = 0.03), educational level (OR = 2.26, 95%CI = 1.18–4.39, p = 0.01), daily tooth brushing frequency before pregnancy (OR = 0.64, 95%CI = 0.40–1.03, p = 0.05), and annual frequency of periodontal treatment (OR = 1.69, 95%CI = 0.93–3.13, p = 0.05; OR = 2.91, 95%CI = 1.45–6.27, p = 0.004).
Table 3.
Univariate logistic regression analysis of risk factors for periodontitis in pregnant women
| Variables | Statistics | OR (95%CI) | p-value |
|---|---|---|---|
| Gestational age (weeks, mean ± SD) | 19.3 ± 6.24 | 1.29 (1.20–1.38) | < 0.001* |
| Pregnancy history, n (%) | |||
| First pregnancy | 419 (95.7%) | 1.00 | |
| Non-first pregnancy | 19 (4.3%) | 5.45 (1.22–24.26) | 0.03* |
| Residence type, n (%) | |||
| Agriculture | 111 (25.3%) | 1.00 | |
| Non-agriculture | 327 (74.7%) | 0.57 (0.33–0.99) | 0.05* |
| Educational level, n (%) | |||
| Bachelor’s degree and above | 115 (26.3%) | 1.00 | |
| Junior college or associate degree | 127 (29.0%) | 1.42 (0.79–2.56) | 0.24 |
| High school or vocational school | 85 (19.4%) | 1.31 (0.67–2.59) | 0.43 |
| Junior high school or below | 111 (25.3%) | 2.26(1.18–4.39) | 0.01 |
| Family household income (RMB), n (%) | |||
| < 3000 | 68 (15.5%) | 1.00 | |
| 3000–5000 | 154 (35.2%) | 0.74 (0.36–1.47) | 0.39 |
| 5000–8000 | 87 (19.8%) | 1.04 (0.48–2.21) | 0.92 |
| > 8000 | 129 (29.5%) | 0.91 (0.44–1.87) | 0.79 |
| Daily tooth brushing frequency before pregnancy, n (%) | |||
| ≤ 1 | 264 (60.3%) | 1.00 | |
| ≥ 2 | 174 (39.7%) | 0.64 (0.40–1.03) | 0.05* |
| Daily tooth brushing frequency during pregnancy, n (%) | |||
| ≤ 1 | 261 (59.6%) | 1.00 | |
| ≥ 2 | 177 (40.4%) | 0.77 (0.49–1.22) | 0.27 |
| Brushing duration (min), n (%) | |||
| 1–2 | 34 (7.8%) | 1.00 | |
| ≥ 2 | 237 (54.1%) | 0.85 (0.35–2.02) | 0.72 |
| < 1 | 167 (38.1%) | 1.45 (0.58–3.52) | 0.42 |
| Brushing method, n (%) | |||
| Horizontal or vertical | 152 (34.7%) | 1.00 | |
| Both horizontal and vertical | 242 (55.3%) | 1.34 (0.83–2.18) | 0.23 |
| Rotational and horizontal vibration method | 44 (10.0%) | 1.53 (0.72–3.37) | 0.28 |
| Toothbrush replacement time (month), n (%) | |||
| ≤ 1 | 81 (18.5%) | 1.00 | |
| 1–3 | 282 (64.4%) | 0.94 (0.52–1.68) | 0.83 |
| ≥ 3 | 75 (17.1%) | 1.16 (0.54–2.51) | 0.71 |
| Daily dental flossing frequency, n (%) | |||
| ≥ 2 | 15 (3.4%) | 1.00 | |
| ≤ 1 | 39 (8.9%) | 1.16 (0.28–4.61) | 0.82 |
| Never | 384 (87.7%) | 1.04 (0.30–3.35) | 0.95 |
| Annual frequency of periodontal treatment, n (%) | |||
| ≥ 1 | 78 (17.8%) | 1.00 | |
| < 1 | 93 (21.2%) | 1.69 (0.93–3.13) | 0.05* |
| Never | 267 (61.0%) | 2.91 (1.45–6.27) | 0.004* |
Note OR: odds ratio; CI: confidence interval; N: number; SD: standard deviation. * Statistical significance
Table 4 lists the results of the multivariate logistic analysis of risk factors for periodontitis in pregnant women. The risk of periodontitis in pregnant women was associated with gestational age (OR = 1.28, 95%CI = 1.17–1.39, p < 0.001), pregnancy history (OR = 6.57, 95%CI = 1.22–35.43, p = 0.03), daily tooth brushing frequency before pregnancy (OR = 1.54, 95%CI = 1.03–2.79, p = 0.05), and annual frequency of periodontal treatment (OR = 2.28, 95%CI = 1.25–4.14, p = 0.05; OR = 7.37, 95%CI = 3.04–22.06, p < 0.001) after adjustment for age, smoking status, and ethnicity.
Table 4.
Multivariate logistic regression analysis of risk factors for periodontitis in pregnant women
| Variables | Adjusted OR (95%CI) | p-value |
|---|---|---|
| Gestational age (weeks) | 1.28 (1.17–1.39) | < 0.001* |
| Residence type | ||
| Agriculture | 1.00 | |
| Non-agriculture | 0.92 (0.44–1.93) | 0.84 |
| Educational level | ||
| Bachelor’s degree and above | 1.00 | |
| Junior college or associate degree | 1.57 (0.74–3.33) | 0.23 |
| High school or vocational school | 1.27 (0.53–3.03) | 0.59 |
| Junior high school or below | 1.58 (0.64–3.86) | 0.31 |
| Pregnancy history | ||
| First pregnancy | 1.00 | |
| Non-first pregnancy | 6.57 (1.22–35.43) | 0.03* |
| Daily tooth brushing frequency before pregnancy | ||
| ≥ 2 | 1.00 | |
| ≤ 1 | 1.54 (1.03–2.79) | 0.05* |
| Annual frequency of periodontal treatment | ||
| ≥ 1 | 1.00 | |
| < 1 | 2.28 (1.25–4.14) | 0.01* |
| Never | 7.37 (3.04–22.06) | < 0.001* |
Note Adjusted OR: odds ratio adjusted for age, smoking status, and ethnicity; CI: confidence interval; N: number; SD: standard deviation. * Statistical significance
A multivariate logistic regression model was used to develop a nomogram for predicting periodontitis in pregnant women. Specifically, a nomogram for predicting periodontitis in pregnant women was established based on the four independent risk factors (Fig. 1). The nomogram was subjected to internal validation with the Bootstrap method (after repeated sampling of the original data 1000 times), and external validation was performed by testing the cohort. Calibration curves revealed that the predicted values in the training and testing cohorts were consistent with the measured values (Fig. 2B and E). ROC curves exhibited that the area under the ROC curve (AUC) of the nomogram was higher in the training cohort (0.855) than in the testing cohort (95%CI = 0.81–0.89), with high accuracy of 83.1% in the testing cohort (Fig. 2A and D), indicating the high prediction accuracy of the nomogram. Furthermore, the decision curve analysis was conducted to evaluate the net benefit of the nomogram, which demonstrated excellent clinical utility (Fig. 2C and F).
Fig. 1.
A nomogram constructed to predict the risk of periodontitis in pregnant women. Each factor was scored based on the nomogram, and the final total score was obtained by adding the individual scores of the four risk factors, subsequently obtaining the estimated probability
Fig. 2.
Evaluation of the nomogram. (1) Receiver-operating characteristic (ROC) curves for the nomogram in the training (A) and testing (D) cohort. AUC, area under the ROC curve; (2) Calibration curves for the nomogram in the training (B) and testing (E) cohort. When the solid line (performance nomogram) is closer to the dotted line (ideal model), the prediction accuracy of the nomogram is higher. (3) Decision curve analysis of the nomogram in the training (C) and testing (F) cohorts. The blue solid line represents the nomogram, the gray line represents all participants with periodontitis, and the solid horizontal line indicates that none of the participants have periodontitis. The graph depicts the expected net benefit per patient relative to the risk of periodontitis in pregnant women predicted by the nomogram
Discussion
Previous studies have reported a prevalence of periodontitis ranging from 6 to 96% in pregnancy [12, 13]. The prevalence and influencing factors of periodontitis vary across pregnant women, which may be attributed to differences in ethnicity, socioeconomic factors, oral health behaviors, assessment methods of periodontal status, and classification of periodontal disease [14]. In a Spanish study, the periodontal status of pregnant women with a mean age of 32 years significantly deteriorated between the first and second trimesters of pregnancy, and oral health in the first trimester of pregnancy, as assessed by the plaque index, was associated with periodontitis in the third trimester of pregnancy, but not with gingivitis [15]. In conclusion, periodontitis can develop in pregnancy. Accordingly, our study probed the clinical prevalence and potential risk factors for periodontitis in Chinese pregnant women at 10–36 gestation weeks, with a prevalence rate of periodontitis of 59.8%.
In the present study, periodontitis in pregnant women was associated with gestational age (weeks), pregnancy history, residence type, educational level, daily tooth brushing frequency before pregnancy, and annual frequency of periodontal treatment, which supports the implementation of special dental care before and during pregnancy. Moreover, a simple and easy-to-use nomogram was constructed based on multivariate analysis results to predict the risk of developing periodontitis in pregnant women. The final nomogram involved four risk factors: gestational age, non-first pregnancy, daily tooth brushing frequency of ≤ 1 before pregnancy, and annual frequency of periodontal treatment < 1 (including no periodontal treatment).
Several underlying metabolic and physiological changes occur during pregnancy, which can trigger oral changes in pregnant women [16]. From the second trimester of pregnancy, the periodontal status is aggravated owing to alterations in the estrogen and progesterone levels, which may negatively affect immune responses in women, consequently contributing to the colonization of microorganisms, such as Bacteroides melaninogenicus subspecies intermedius and Aggregatibacter actinomycetemcomitans. Reportedly, the subgingival microbiota becomes increasingly anaerobic as gestation progresses [17], which may elevate the risk of periodontitis. In the present study, the multivariable analysis unveiled that gestational age was associated with the risk of periodontitis in pregnant women independent of age (OR = 1.28, 95%CI = 1.17–1.39, p < 0.001). In the literature, the percentage of pregnant women with periodontitis varies markedly from 0.6 to 47.0% and is dependent not only on sociodemographic and environmental factors but also on the stage of pregnancy [18–21]. According to the latest diagnostic criteria for periodontal disease [11], Gil-Montoya et al. found that the risk of periodontitis was elevated with the duration of pregnancy, with the highest percentage of women with periodontitis in late pregnancy [15].
In our study, there was an association between pregnancy history and the risk of periodontitis in pregnant women, with non-first pregnancy (OR = 6.57, 95%CI = 1.22–35.43) as a risk factor for periodontitis in pregnancy. A large-scale Korean study disclosed that the number of childbirths was associated with both the risk and severity of periodontitis [22]. Endocrine shifts in pregnant women affect the immune system as a result of the interactions among the hormonal environment, innate and adaptive immune systems, and pro- and anti-inflammatory cytokines. These factors subsequently modulate the susceptibility of pregnant women to autoimmune diseases, and such endocrine shifts are tightly associated with the development of various autoimmune diseases [23]. The research by Jørgensen et al. unraveled that an elevation in the number of deliveries was associated with an increased risk of autoimmune diseases, including Hashimoto’s thyroiditis, Graves’ disease, erythema nodosum, and sarcoidosis [24]. Importantly, the immunopathology of these autoimmune diseases, such as self-reactive T-cells, anti-neutrophil cytoplasmic autoantibodies, and genetic factors, has been reported to be associated with periodontitis [25].
Changes in estrogen and progesterone levels also provoke alterations in the composition of the oral microbiota, which is compatible with the development of periodontitis [26]. Prior studies revealed that the abundance of Porphyromonas gingivalis and Prevotella intermedia in the subgingival plaque was positively correlated with maternal hormone levels and the destruction degree of periodontal tissues during pregnancy [27, 28]. These pathogenic bacterial colonies proliferate and invade periodontal tissues, evoking the development of periodontitis. The risk of periodontitis is elevated in the absence of timely intervention or prevention through effective oral health instructions and plaque control. Bacterial plaque control and periodontal treatment can ameliorate periodontal inflammation, improve the quality of life of women during pregnancy [29], and reduce the incidence of APOs in women with periodontitis [30]. Hence, early interventions for both healthy and high-risk pregnant women are vital to sustaining adequate periodontal health throughout pregnancy [21]. Through analyses of the oral health awareness and behaviors of pregnant women, we observed that periodontitis during pregnancy was associated with daily tooth brushing frequency before pregnancy and annual frequency of periodontal treatment. Specifically, daily tooth brushing frequency of ≤ 1 before pregnancy (OR = 1.54, 95%CI = 1.03–2.79), annual frequency of periodontal treatment < 1 (OR = 2.28, 95%CI = 1.25–4.14), and no history of periodontal treatment (OR = 7.37, 95%CI = 3.04–22.06) were independent risk factors associated with the development of periodontitis in pregnant women (p < 0.05). Consequently, once the inflammatory cascade is activated during pregnancy, interventions targeting this cascade may be ineffective in diminishing preterm birth rates [31, 32]. Therefore, healthcare providers should encourage women to adopt oral health interventions and provide advice on preventing periodontitis before pregnancy.
A nomogram is of tremendous value for risk estimation, clinical decision-making, and better patient communication since it is a statistical tool that enables users to calculate the overall probability of a specific clinical outcome in individual patients. In this study, a novel and practical nomogram with high sensitivity and specificity was constructed to predict the risk of periodontitis in pregnant women. The nomogram exhibited excellent performance in predicting periodontitis in pregnant women (AUC = 0.855). To our knowledge, our nomogram is the first nomogram developed for predicting periodontitis in pregnant women, which may be used as a tool for healthcare providers to offer useful oral health recommendations and calculate the risk of periodontitis after pregnancy.
Several strengths exist in the present study. First, this community-based cross-sectional study identified “gestational age”, “non-first pregnancy”, “daily tooth brushing frequency of ≤ 1 before pregnancy”, and “annual frequency of periodontal treatment < 1 (including no periodontal treatment)” as risk factors for periodontitis in pregnant women. Second, a novel easy-to-use nomogram was developed based on these four risk factors. Accordingly, high-risk women should receive more intensive oral health education and regular periodontal examinations, treatment, and follow-up to minimize the incidence of periodontitis.
The current study has some limitations. First, our study was a cross-sectional study, which could not demonstrate a causal association between the related factors and periodontitis in pregnant women. Therefore, longitudinal studies are warranted in the future. Second, studies with a larger sample size and randomized participants are necessary to ensure the generalization of our findings to the target population. Third, the strength of evidence in this study might be limited by inadequate interpretation of confounding factors and lack of external validation of the nomogram. Accordingly, more data should be acquired for more rigorous prospective trials and multicenter studies to validate our nomogram. Fourth, while many recent studies have demonstrated the association of obesity with periodontitis during pregnancy [33–35], the current study did not investigate the anthropometric parameters of pregnant women. As a result, it was unable to exclude the confounding effect of weight gain due to gestation. Additionally, we did not specifically address the potential issue of clustering effects, which may have impacted the statistical validity of the results. Lastly, it is worth noting that the population in Langfang city may not fully represent the diverse demographic and socioeconomic characteristics of the entire Chinese population.
Conclusion
This study provides evidence that gestational age, non-first pregnancy, lower daily tooth brushing frequency before pregnancy, and lower frequency of periodontal treatment may be risk factors for periodontitis in Chinese pregnant women. A nomogram based on these four risk factors can intuitively and accurately predict the risk of periodontitis in pregnant women. The findings may be helpful in designing and planning interventions to foster periodontal health in pregnant women.
Electronic supplementary material
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Acknowledgements
Not applicable.
Author contributions
Qingxian Luan and Qiao Shi designed this study. Qiao Shi, Yu Cai and Xiaoxuan Wang acquired data. Qiao Shi, Yu Cai and Guojing Liu performed statistical analyses. Qiao Shi and Yu Cai wrote the manuscript. All authors contributed to the editing and approval of the final version of the manuscript. All authors reviewed the manuscript.
Funding
This study was supported by the Scientific Research Foundation of Peking University School and Hospital of Stomatology (PKUSS20210108) and the National Program for the Multidisciplinary Cooperative Treatment of Major Diseases (Grant number: PKUSSNMP201905).
Data availability
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethical approval and consent to Participate
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee. This study protocol received ethical approval from the Ethics Committee of Peking University Health Science Centre (PKUSSIRB-2020085713). After being explained the objective of the study, all participants signed a written informed consent form for participation.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Qiao Shi and Yu Cai contributed equally to this manuscript as the first author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.