Parental education, screen time and oral health: a cross-sectional study among adolescents

Abstract

Background

Adolescence is a critical milestone in the transition to adulthood. Factors affecting oral health, an essential component of general health during this period, also influence public health. This study investigates the potential impact of parental education level (PEL) and daily total daily screen time (DTST) on adolescent oral health using a large sample size.

Methods

A total of 1300 adolescents aged 17 and 18 from Ordu Province were included in this study. A structured questionnaire was used to assess PEL, DTST, and other habits that may influence dental caries. Oral health was evaluated using the Decayed, Missing, and Filled Teeth (DMFT) and Significant Caries Index (SiC). Associations between variables were analyzed using regression analysis and the chi-square test.

Results

Higher PEL was significantly associated with lower DMFT scores (β = −0.37, 95% CI: −0.53 to − 0.21, p < 0.001). A significant relationship was also found between screen time and DMFT scores, with longer screen times associated with higher DMFT values (β = 0.29, 95% CI: 0.14 to 0.45, p < 0.001). Additionally, a significant inverse relationship was identified between PEL and DTST, indicating that higher education was associated with shorter screen exposure (ρ = −0.20, p < 0.001). Increased screen time was also linked to more frequent consumption of sugary snacks and beverages, as well as poorer oral hygiene behavior (p < 0.001). However, no significant association was found between PEL and toothbrushing frequency (p = 0.252).

Conclusions

Parental education and screen time significantly affected adolescents’ oral health, with higher education levels and shorter screen time being associated with lower DMFT and SiC scores, better hygiene, and healthier diets, and must be integrated into public health strategies aimed at improving adolescent oral health.

Trial registration

Not applicable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-025-25923-y.

Background

Dental caries represents a multifactorial infectious disease influenced by both individual and social determinants [1, 2]. It affects people across all age groups and socioeconomic strata and is recognized by the World Health Organization as the fourth most costly disease to treat, despite being completely preventable [3, 4]. Therefore, comprehensive studies are needed to accurately identify these factors and explore their interactions.

Oral health and perceived oral health are shaped by a combination of individual and social variables and represent key components of general health. Since clinical indicators alone are insufficient for a full assessment, oral health must also be evaluated in the context of social determinants [5]. When it comes to child and adolescent oral health, the caregiving parent has been identified as one of the most important social determinants, and the relationship between PEL and oral health has been previously emphasized [6, 7]. A more recent focus in health-related research has been screen time. Although significant associations have been observed between excessive screen exposure and various health disorders, the topic requires more comprehensive investigation [8].

As technology has advanced and become increasingly widespread, the concept of screen time has expanded, leading to greater exposure across a wide range of age groups. As technology use has become widespread, particularly among adolescents, examining the effect of DTST on oral health has become increasingly relevant.

The DMFT index, commonly used in caries studies, reflects population means but not disease distribution or severity. Consequently, it is increasingly acknowledged that the DMFT index is insufficient for capturing skewed distributions and identifying high-risk subgroups. For this reason, in evaluating the results of our study, we also employed the SiC, which was recommended by the World Health Organization (WHO) to focus on the one-third of the population with the highest DMFT scores.

To the best of our knowledge, this is the first study to examine the influence of not only parental-dependent factors but also the adolescent’s own behavioral variable-total daily screen time-on oral health.

Furthermore, this is the first study involving adolescents with such a large sample size to investigate whether DTST, which can be considered an individual behavioral factor, is associated with PEL, thereby reflecting a possible link with a broader social determinant.

Another significant contribution of this research lies in its public health value beyond disease identification. Adolescence, as a transitional period from childhood to adulthood, is marked by numerous physical, cognitive, and behavioral changes. During this phase, independence from parents increases, and new behavioral patterns likely to persist throughout life are formed. In our study, clinical examinations and interviews with adolescents were accompanied by oral health education and referrals for treatment, highlighting the multidimensional nature of public health interventions.

This study was based on three null hypotheses. First, PEL was assumed to have no effect on adolescents’ oral health outcomes, specifically the DMFT and SiC indices. Second, it was hypothesized that screen time would not influence DMFT and SiC values. Finally, no association was expected between PEL and total daily screen time.

Methods

The aim of this study was to investigate the associations between PEL, DTST, and oral health outcomes (DMFT and SiC indices) among adolescents.

This cross-sectional study was conducted between January 15 and May 20, 2025, in 15 high schools located in Ordu Province, Türkiye, which is the 28th most populous province in the country. To ensure representativeness of high school students in Ordu, 15 schools were selected from the official list provided by the Provincial Directorate of National Education using a simple random sampling method. The study was conducted in accordance with the principles of the Declaration of Helsinki. All necessary approvals were obtained from the Local Ethics Committee (2024/194) and the Ordu Provincial Directorate of National Education.

Before the clinical examination, both students and their parents were provided with informed consent forms and parental permission forms. Students who returned signed parental consent, personally agreed to participate, and had no systemic diseases or pathological conditions that could affect growth and development were included in the study. Participants were excluded if they were unable to cooperate during the examination or if their questionnaire data were incomplete or inaccurately completed.

According to a power analysis conducted using G*Power (v3.1.9.7), for a two-way ANOVA with a medium effect size (f = 0.25), α = 0.05, and power (1 − β) = 0.80, a minimum of 200 participants is required. The sample size of 1300 students in this study greatly exceeded this threshold, providing high statistical reliability. Consent forms were distributed to the principals of 15 high schools, aiming to recruit 100 students randomly per school. After applying inclusion and exclusion criteria, the final sample consisted of 1300 adolescents.

Students who agreed to participate and whose parents provided consent were examined individually in a private room designated by the school administration to ensure confidentiality. No identifying information was collected, and all data were recorded anonymously. Students diagnosed with dental caries or other oral health issues were informed and referred to nearby public dental clinics for further care.

Oral examinations were conducted by a single trained dentist in accordance with the American Dental Association Type 3 examination guidelines, using single-use sterile mirrors, sterile probes, and penlights, with participants seated comfortably on standard chairs with back support while the examiner was positioned directly in front of them. Third molars were excluded from evaluation. Oral health status was assessed using the DMFT (Decayed, Missing, Filled Teeth) and SiC (Significant Caries Index) indices. The examiner was calibrated before the study through a pilot test on 50 students not included in the final sample, and intra-examiner agreement was found to be high (κ = 0.89).

After the oral examination, students’ height and weight were measured using a stadiometer and a calibrated scale. Weight was recorded to the nearest 200 g, with students barefoot and in light clothing. Height was measured while students stood upright without shoes. Body Mass Index (BMI) was calculated using the formula weight (kg)/height (m²).

Following the measurements, students were asked to complete a structured questionnaire. A structured questionnaire was specifically developed for this study to assess parental education, daily screen time, and oral health–related habits among adolescents. To ensure content validity, the questionnaire was reviewed by a panel of five experts, including a dietitian, a public health specialist, a dentist, a guidance counselor, and a biostatistician. Their feedback was used to refine the wording, structure, and conceptual clarity of the items.

Internal consistency reliability was evaluated using Cronbach’s alpha. As the items represented different thematic domains, reliability analyses were conducted separately for each subscale. The Cronbach’s alpha values were α = 0.88 for oral health and hygiene behaviors, α = 0.65 for dietary habits, α = 0.74 for screen time, and α = 0.72 for the combined demographic, anthropometric, socioeconomic, and clinical variables. These findings indicate that the questionnaire demonstrated acceptable to high reliability, and its multidimensional structure accounted for variability across Sects [9, 10]. (values between 0.70 and 0.90 are generally considered good, while values above 0.90 may indicate item redundancy).

In addition, test–retest reliability was evaluated in a pilot study with 100 participants by re-administering the questionnaire after a two-week interval. The Pearson correlation coefficient for the total questionnaire was r = 0.849, indicating good temporal stability and reproducibility [11] (r between 0.70 and 0.90 reflects good test–retest consistency). An English translation of the questionnaire was provided as Supplementary File 1. For the screen time question, participants were asked to report their total daily screen exposure in hours, and the responses were subsequently categorized into five groups for analysis.

Statistical analyses were conducted using IBM SPSS Statistics v26. The Kolmogorov–Smirnov test was used to assess normality. Non-normally distributed data were analyzed using the Kruskal–Wallis test, and pairwise comparisons were performed with the Mann–Whitney U test. Categorical variables were analyzed using the chi-square test. Significant variables were further examined by regression analysis, and the relationship between PEL and screen time was assessed using Spearman’s correlation test.

Results

This study, which evaluated the association between PEL, DTST, and adolescent oral health using the DMFT and SiC indices, included 1300 participants (48.0% female, 51.9% male), aged 17–18 years (mean 17.61 ± 1.14, 95% CI: 17.5–17.7). BMI ranged from 9.64 to 34.26 (mean 21.55 ± 2.68, 95% CI: 21.4–21.7). Among mothers, 23.0% completed primary school, 37.1% high school, and 39.9% university; among fathers, 15.8% completed primary school, 42.2% high school, and 42.0% university. The average daily screen time was 5.13 ± 2.34 h (95% CI: 4.9–5.3). Distribution was as follows: 0–2 h (13.8%), 2–4 h (16.7%), 4–6 h (26.2%), 6–8 h (24.6%), and > 8 h (17.5%). The mean DMFT score was 6.48 ± 4.85 (95% CI: 6.2–6.8), while the SiC index was 11.96 ± 2.52 (95% CI: 11.8–12.1).

The survey questions and the distribution of responses are presented in Table 1.

Table 1.

Survey questions and response distribution

		Children	Mother	Father
Age, mean (SD)		17.6 (1.14) (17.5–17.7)	-	-
Female/male, n (%)		625(48)/675(51.9)	-	-
BMI, mean (SD)		21.55(2.68) (21.4–21.7)
PEL, n (%)	Elementary	-	299(23)	206(15.8)
	High School	-	482(37.1)	548(42.2)
	University	-	519(39.9)	546(42)
DTST, n (%)	0–2	195(15)	-	-
	2–4	217(16.7)	-	-
	4–6	340(26.2)	-	-
	6–8	320(24.6)	-	-
	8-	228(17.5)	-	-
DMF, mean (SD)		6.48(4.86) (6.2–6.8)	-	-
D, mean (SD)		4.75 (3.86) (4.6–4.9)	-	-
M, mean (SD)		0.26 (0.76) (0.22–0.30)	-	-
F, mean (SD)		1.42 (2.55) (1.3–1.5)	-	-
SİC, mean (SD)		11.96(2.52) (11.8–12.1)
Tooth Brushing Frequency, n (%)	Never	20(1,5)	-	-
	Once a day	280(21.5)	-	-
	Twice a day	895(68.8)	-	-
	Three times or more per day	105(8.1)	-	-
Frequency of Between-Meal Sweet Consumption, n (%)	Never	11(0.8)	-	-
	A few times a month	9(0.7)	-	-
	A few times a week	385(29.6)	-	-
	Every day	808(62.2)	-	-
	More than once a day	87(6.7)	-	-
Frequency of Sugary Drink Consumption, n (%)	Never	0	-	-
	A few times a month	67(5.2)	-	-
	A few times a week	583(44.8)	-	-
	Every day	600(46.2)	-	-
	More than once a day	50(3.8)	-	-
Frequency of Fast Food Consumption, n (%)	Never	15(1.2)	-	-
	A few times a month	299(23)	-	-
	A few times a week	590(45.4)	-	-
	Every day	391(30.1)	-	-
	More than once a day	5(0.4)	-	-

Distribution of responses to the survey questions assessing sociodemographic characteristics, PEL, oral hygiene habits, dietary behaviors, and screen time among adolescents (N = 1300)

Values are presented as mean ± standard deviation (SD) with 95% confidence intervals (CI) for continuous variables and as number (percentage) for categorical variables

PEL were classified as elementary (1–8 years of elementary), high school (9–12 years), and university (> 12 years)

A significant inverse association was found between PEL and DMFT scores. Kruskal–Wallis analysis indicated significant differences based on maternal (χ²(2) = 330.54, p < 0.001, η² = 0.253, large effect) and paternal education (χ²(2) = 310.93, p < 0.001, η² = 0.238, large effect).

Pairwise Mann–Whitney U comparisons showed no difference between primary and high school–educated mothers (p = 0.053, r = 0.12, small effect), whereas university-educated mothers had significantly lower DMFT scores (p < 0.001, r = 0.46, large effect).

For fathers, all education levels differed significantly (p < 0.001, r = 0.41, large effect).

On average, children of university-educated mothers exhibited approximately 23% lower DMFT values compared with those of primary-educated mothers; the corresponding reduction.

The results are shown in Table 2.

Table 2.

Parental education and related oral health outcomes

		Mother Education Level			Father Education Level
	Total	Elementary education	High school	University degree	Elementary education	High school	University degree
DMFT, mean ± SD	6.48 ± 4.86 (6.2–6.8)	8.99 ± 4.25 (8.3–9.6)	8.02 ± 4.42 (7.6–8.4)	3.61 ± 4.06 (3.3–3.9)	9.36 ± 3.82 (8.8–9.9)	8.07 ± 4.70 (7.6–8.5)	3.80 ± 3.96 (3.5–4.1)
D, mean ± SD	4.75 ± 3.86 (4.6–4.9)	6.20 ± 3.77 (5.8–6.6)	5.75 ± 3.58 (5.4–6.1)	2.98 ± 3.46 (2.7–3.3)	6.37 ± 3.17 (5.9–6.8)	5.72 ± 3.91 (5.4–6.1)	3.16 ± 3.45 (2.9–3.4)
M, mean ± SD	0.26 ± 0.76 (0.22–0.30)	0.53 ± 1.21 (0.4–0.6)	0.30 ± 0.68 (0.25–0.35)	0.07 ± 0.32 (0.05–0.09)	0.44 ± 0.94 (0.37–0.51)	0.31 ± 0.88 (0.25–0.37)	0.15 ± 0.49 (0.12–0.18)
F, mean ± SD	1.42 ± 2.55 (1.3–1.5)	1.92 ± 2.95 (1.6–2.2)	1.97 ± 2.94 (1.7–2.2)	0.63 ± 1.49 (0.52–0.74)	2.23 ± 3.17 (1.9–2.5)	1.97 ± 2.92 (1.7–2.2)	0.57 ± 1.36 (0.48–0.66)
D/DMFT %	0.73 (0.81)	0.69 (0.53)	0.72 (0.6)	0.83 (1.34)	0.68 (0.44)	0.71 (0.64)	0.83 (1.25)
M/DMFT %	0.04 (0.12)	0.06 (0.43)	0.04 (0.48)	0.02 (0.99)	0.05 (0.36)	0.04 (0.51)	0.04 (0.92)
F/DMFT %	0.22 (0.43)	0.21 (0.42)	0.25 (0.47)	0.18 (1.1)	0.24 (0.35)	0.24 (0.5)	0.15 (0.96)
SiC, mean ± SD	11.96 ± 2.52 (11.8–12.1)	13.42 ± 1.84 (13.2–13.6)	12.85 ± 2.78 (12.6–13.1)	8.60 ± 2.46 (8.4–8.8)	13.32 ± 1.91 (13.1–13.5)	13.38 ± 2.46 (13.1–13.6)	8.69 ± 1.96 (8.5–8.9)
DTST, mean ± SD	5.13 ± 2.34 (4.9–5.3)	5.61 ± 1.88 (5.4–5.8)	5.31 ± 2.27 (5.1–5.5)	4.68 ± 2.58 (4.5–4.9)	5.98 ± 1.59 (5.7–6.1)	5.38 ± 2.21 (5.2–5.6)	4.54 ± 2.57 (4.3–4.8)

Mean values (± SD) of the DMFT index and its components (D, M, F), proportional indices (D/DMFT, M/DMFT, F/DMFT), SiC index, and DTST among adolescents, categorized according to mothers’ and fathers’ education levels (elementary, high school, and university)

Values are presented as mean ± standard deviation (SD) with 95% confidence intervals (CI)

The D/DMFT ratio differed significantly by both maternal (χ²(2) = 13.67, p < 0.001, η² = 0.011, small effect) and paternal education (χ²(2) = 25.66, p < 0.001, η² = 0.020, small-to-medium effect).

The M/DMFT ratio varied significantly by maternal education (χ²(2) = 22.75, p < 0.001, η² = 0.018, small-to-medium effect) but not by paternal education (p = 0.332).

The F/DMFT ratio did not differ across maternal education levels (p = 0.205) but was significant for paternal education (χ²(2) = 25.66, p < 0.001, η² = 0.020, small-to-medium effect).

The results of this present study are presented in Figs. 1 and 2.

Fig. 1.

Distribution of oral health indicators by mother’s education level. Distribution of DMFT index, its components (D, M, F), SiC index, and DTST according to mother’s education level. Letters above the bars indicate statistically significant differences (p < 0.001; Kruskal–Wallis and Mann–Whitney U tests). Groups sharing the same letters do not differ significantly. DTST was analyzed using Spearman’s correlation; therefore, no letter annotations were applied

Fig. 2.

Distribution of oral health indicators by father’s education level. Distribution of DMFT index, its components (D, M, F), SiC index, and DTST according to father’s education level. Letters above the bars indicate statistically significant differences (p < 0.001; Kruskal–Wallis and Mann–Whitney U tests). Groups sharing the same letters do not differ significantly. DTST was analyzed using Spearman’s correlation; therefore, no letter annotations were applied

Figures 1 and 2 showed significant associations between PEL and SiC (p < 0.001, η² = 0.16, large effect). There was no difference between primary and high school paternal education (p = 0.809), but other comparisons (esp. high school vs. university) were significant (p < 0.001). Poisson regression revealed maternal education had a stronger effect on DMFT. Each maternal education level increase reduced DMFT by 0.92 points (β = − 0.2, 95% CI: −0.27 to − 0.15, p < 0.001) and paternal by 0.58 points (β = − 0.1, 95% CI: −0.19 to − 0.03, p = 0.006), both p < 0.001. No significant association was found between PEL and brushing frequency (χ² = 5.32, p = 0.252).

DMFT scores significantly differed across screen time groups (χ² = 227.127, p < 0.001, η² = 0.17, large effect). The lowest scores were in the 0–2 h group; the highest were in the 6–8 h group. >6 h screen time associated with significantly higher DMFT (p < 0.01). Regression showed each 1 h increase in screen time raised DMFT by 19.1% (β = 0.170, 95% CI: 0.13–0.22, p < 0.001; Exp(β) = 1.19). Mean DMFT was 8.12 (> 2 h) vs. 5.44 (< 2 h)—a 1.49× increase. A significant inverse correlation was found between PEL and screen time (ρ = −0.20 for fathers, ρ = −0.13 for mothers; both p < 0.001), indicating that higher parental education was associated with shorter daily screen exposure, with paternal education showing a stronger association. Longer screen time was linked to higher intake of fast food, sugary snacks, and beverages. Those in the 0–2 h group mostly reported monthly consumption; the 6–8 h and 8 + h groups reported daily or multiple-times-daily consumption. The highest frequencies for all three food categories were in the 8 + h group.

The results are presented in Figs. 3.

Fig. 3.

Association Between Screen Time and Dietary Consumption Frequency. Heatmap showing the average frequency of consumption of fast food, sugary drinks, and between-meal sweets by DTST. Screen time categories are defined as follows: 1 = 0–2 h, 2 = 2–4 h, 3 = 4–6 h, 4 = 6–8 h, 5 = 8 or more hours per day. Consumption frequency ranges from “Never” to “More than once a day”

Conversely, brushing behavior declined with increasing screen time. Brushing twice daily was most frequent in the 0–2 h group (n = 142) and lowest in the 8 + h group (n = 159). Brushing 3 + times per day was most frequent in the lowest screen time group (n = 8) and consistently low in higher screen groups.

Discussion

To our knowledge, this is the first study conducted in Turkey to evaluate the effects of PEL and screen time on oral health among high school students. Adolescence was chosen as the target group since it represents a critical transitional stage, reflecting both habits carried from childhood and early signs of adult behaviors. At this age, all permanent teeth, except for third molars, have usually erupted [12].

Educational level is a core indicator of socioeconomic status, alongside income and occupation [13]. Although parental education often correlates with household income, variations in income across professions at the same educational level can lead to inconsistencies. Literature also suggests that education level is a stronger predictor of health outcomes than other socioeconomic indicators [14].

The mean DMFT score in our study was 6.48 (± 4.85). This aligns with some studies in comparable age groups [15, 16], though it is higher than others [17, 18]. For instance, a study among health technician students reported that 31.2% had DMFT ≥ 6 [19]. The SiC score was 11.96 (± 2.52), as expected higher than the mean DMFT. A SiC/DMFT ratio of 1.5–2.0 is often interpreted as a marker of inequality; our ratio of 1.85 highlights a disproportionate burden of caries in certain subgroups, consistent with reports that DMFT may mask inequalities [20, 21]. These findings emphasize the need for targeted preventive strategies.

Effect of parental education on oral health

As parental education increased, DMFT and SiC scores showed a declining trend. This may be related to greater oral health literacy and healthier habit patterns observed among more educated parents. These findings indicate that the first null hypothesis was rejected, as PEL significantly affected adolescents’ oral health outcomes, with higher education levels associated with lower DMFT and SiC scores. Although earlier research has linked parental education with more frequent toothbrushing [22], our study did not find such an association. This inconsistency may be related to self-reported measures or sample-specific factors, and the effect of sample size should also be considered.

Parental education may be associated with diet and access to healthcare. Caries have been reported to be associated with dietary factors, and both obesity and nutritional deficiencies have been linked to a higher likelihood of caries occurrence [23]. Higher parental education has been associated with healthier dietary patterns and greater access to timely and quality healthcare, which may increase the likelihood of early diagnosis [24, 25]. In our study, higher parental education was associated with fewer untreated carious and missing teeth. Paternal education was significantly related to the number of filled teeth, possibly reflecting financial resources, whereas maternal education emerged as a stronger overall predictor of oral health, consistent with previous findings [26]. The primary caregiving role of mothers in early life may explain this stronger influence.

Based on evidence in the literature indicating that mothers and fathers may influence children’s health through different mechanisms [27, 28], maternal and paternal education levels were analyzed separately in this study to determine which parent’s education had a more specific or pronounced impact on oral health outcomes.

Effect of screen time on oral health behaviors

Unlike earlier research focusing on television or computers alone, this study considered screen time across all electronic media. Both the WHO and the American Academy of Pediatrics recommend limiting children’s daily screen use to under two hours [29, 30].

Our findings revealed a strong association between prolonged screen time and unhealthy eating behaviors, such as frequent fast food and sugary snack consumption during screen use. Most students reported consuming cariogenic snacks while watching screens. Previous studies similarly linked screen time above two hours with higher DMFT scores and increased consumption of cariogenic foods [31, 32]. Advertising is another important factor, as media exposure has been associated with unhealthy eating habits and higher caries prevalence. Hammond et al. reported that food advertisements are particularly broadcast during prolonged evening hours when adolescents are more likely to be screen-active [33]. Al-Saffan et al. also showed that targeted online advertising is shaped primarily by prior browsing history [34]. Therefore, the second null hypothesis was also rejected, as prolonged screen exposure was significantly associated with higher DMFT values and poorer oral hygiene behaviors.

Prolonged screen use has been associated with poorer self-care routines. In our study, students with more than two hours of daily screen time reported lower rates of nighttime toothbrushing. Many admitted falling asleep with their devices without brushing, a pattern consistent with other studies reporting an association between excessive screen time and poorer self-care behaviors [35]. Screen time, toothbrushing, and dietary behaviors were assessed through self-reported questionnaires, which may be subject to recall bias and social desirability bias, potentially leading to under- or over-reporting. Extended screen use has been linked to disrupted circadian rhythms and reduced immune function, which may indirectly contribute to increased caries susceptibility [36, 37].

In addition to its dietary and behavioral associations, screen use has been associated with stress-related conditions such as bruxism. Online bullying and gaming addiction have been identified as potential stressors. One study reported that children using the internet for more than three hours per day were 2.78 times more likely to experience severe bruxism [38].

Interaction between parental education and screen time

Parental education influences oral health directly and appears to moderate screen-related behaviors. Our study found significant negative correlations between both maternal and paternal education and screen time, with the association stronger for fathers (ρ = −0.20 vs. −0.13). This may suggest greater paternal involvement in setting limits or routines. Nonetheless, the education of both parents plays a critical role in reducing screen exposure. Consequently, the third null hypothesis was rejected, as PEL showed a significant inverse relationship with adolescents’ total daily screen time. Improving parental digital media literacy may be an important approach associated with healthier screen habits and, consequently, better oral health outcomes. The findings suggest that public health interventions should not only target adolescents but also address parental education and digital media literacy. Integrating oral health promotion with school-based programs addressing screen-related behaviors may be beneficial and could yield complementary outcomes.

This study has several limitations. First, caries were assessed clinically without radiographs, which may have led to underestimation of early or interproximal lesions. Second, oral health behaviors such as screen time, toothbrushing, and dietary patterns were self-reported, making the data subject to recall and social desirability bias. Third, the cross-sectional design precludes causal inference. Fourth, the regional scope of the sample may limit generalizability to broader populations. Finally, as the study included only late adolescents (17–18 years), developmental differences across earlier stages of adolescence could not be captured. Other socioeconomic indicators such as household income, parental occupation, and neighborhood environment were not examined, which may partly explain the observed associations. Longitudinal and multicenter studies with objective behavioral measurements are needed to confirm these associations and establish causality. Additionally, other potential confounding factors such as dietary habits, socioeconomic status, sleep quality, and parental involvement were not directly measured in this study. Although these factors may influence both screen time and caries development, their absence should be considered when interpreting the results.

Conclusion

This study identified parental education and screen time as factors associated with adolescents’ oral health. Higher parental education levels were correlated with lower DMFT and SiC scores, shorter screen time, more frequent toothbrushing, and fewer unhealthy eating habits. Paternal education showed a stronger correlation with screen time, whereas maternal education was more closely related to DMFT scores. No significant association was observed between parental education and toothbrushing frequency. Longer screen time was associated with higher caries experience, less frequent brushing, and greater consumption of cariogenic foods. These findings emphasize the coexistence of parental education and screen time as correlates of adolescent oral health, underscoring the need for public health strategies that address both educational and behavioral dimensions.

Abbreviations

PEL

Parental Education Level

DTST

Daily Total Screen Time

DMFT

Decayed, Missing, and Filled Teeth

D

Decayed teeth

M

Missing teeth

F

Filled teeth

SiC

Significant Caries Index

Authors’ contributions

HÖ contributed to the conception and design of the study, as well as to data collection, analysis, and interpretation. The drafting of the manuscript and its critical revision for important intellectual content were carried out by HÖ and SB. The final approval of the version to be submitted was provided by both authors, HÖ and SB.

Funding

Not applicable.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

Local Ethics Committee (Approval No: 2024/194) and Ordu Provincial Directorate of National Education, Türkiye.

Consent for publication

No individual identifying information is included in this manuscript. Written informed consent was obtained both from the parents/legal guardians and from all participating students for inclusion in the study and for publication of anonymized data.

Competing interests

The authors declare no competing interests.