Assessing the impact of systemic conditions on periodontal health in Malaysian population: a retrospective study

Abstract

Background

Periodontal diseases, including gingivitis and periodontitis, are among the most prevalent oral health issues globally. They compromise the supportive structures of teeth and are influenced by both local and systemic factors. This study aimed to systematically assess the impact of systemic conditions on periodontal health in Malaysian population, addressing the gap in understanding these factors as potential risk factors.

Methods

A retrospective, non-interventional study was conducted using medical records from Hospital Universiti Sains Malaysia, Kelantan, from September 2019 to December 2022. The study included patients with periodontitis and systemic conditions. Data were analyzed using descriptive statistics, chi-squared tests, Fisher’s exact tests, Mann-Whitney U tests, Kruskal-Wallis tests, Spearman’s correlation, and logistic regression.

Results

Out of 600 records, 274 patients were included. The cohort was 51.8% male, with a median age of 51 years. Malays accounted for 92.3% of the sample. Hypertension and diabetes mellitus were the most common comorbid conditions. Severe periodontitis was significantly associated with age (45–64 years, p = 0.018) and Malay ethnicity (p = 0.011). Logistic regression revealed that age and ethnicity were significant predictors of periodontitis severity, with Malays being 12.5 times more likely to develop severe periodontitis.

Conclusion

Systemic conditions significantly influence periodontitis development and progression. Age and ethnicity are crucial predictors of periodontitis severity in the Malaysian population. Comprehensive risk assessment tools are necessary to incorporate a broader spectrum of risk factors for better management and prevention.

Introduction

Periodontal diseases, such as gingivitis and periodontitis, rank among the most prevalent oral health issues worldwide [1]. These conditions compromise the supportive structures of teeth. Gingivitis, an early, reversible stage of periodontal disease is characterized by inflammation of the gums affects 90% of the global population [2]. Symptoms include gingival erythema, edema and bleeding, along with halitosis and gingival recession. If untreated, gingivitis can advance to periodontitis, a more serious condition involving infection and inflammation of the periodontium. Periodontitis results in persistent halitosis, receding gums, deep pockets and eventual tooth loss. Periodontitis has been identified as the 11th most prevalent disease based on the recent Global Burden of Disease survey. The prevalence varies by region and demographic factors [3]. In the United States, 47% of adults older than 30 years are affected by gingivitis [4]. In Malaysia, around 90% of adults show signs of periodontal disease. Factors influencing the prevalence of these conditions include oral hygiene behaviors, socio-economic factors, availability of dental care, nutritional intake and overall health condition.

The local risk factors for periodontal diseases include dental plaque and calculus, both of which serve as primary causes of the inflammation seen in gingivitis and periodontitis. The role of microbial agents, such as Streptococcus mutans, Actinomyces species, and Porphyromonas gingivalis, in gingivitis is well documented [5]. For periodontitis, the accumulation of anaerobic bacteria in periodontal pockets leads to severe tissue destruction. Additional local risk factors include poor oral hygiene, faulty dental restorations, and malaligned teeth, which can facilitate bacterial accumulation and promote disease progression [6, 7].

The systemic risk factors for periodontal diseases include conditions that affect the immune response or vascular health. These include diabetes mellitus, hypertension, cardiovascular diseases, smoking, and immune deficiencies [8]. Poorly controlled diabetes mellitus (DM) is particularly significant, as it alters wound healing and increases the risk of severe periodontitis due to impaired immune function. Similarly, smoking impairs immune responses and diminishes the body’s ability to fight infections, leading to deeper periodontal pockets and greater attachment loss [9]. Other systemic conditions such as hormonal changes, certain medications, and chronic illnesses also contribute to the development and progression of periodontal disease [10].

In Malaysia, the prevalence of periodontitis is markedly elevated, oral health constitutes a major public health issue. Approximately 94% of the Malaysian adults with natural teeth present with some form of periodontal disease [11]. The Malaysian population, characterized by its diverse genetic backgrounds, lifestyles, and healthcare practices, also bears a substantial prevalence of systemic conditions, including diabetes mellitus (DM), cardiovascular diseases and respiratory infections [12]. These systemic diseases have been associated with an elevated risk of diseases of the periodontium. Elucidating the influence of these diseases on the Malaysian population can facilitate medical practitioners in formulating efficacious strategies for effective monitoring, prophylactic and therapeutic management. There is an evident need for a comprehensive tool that encompasses a broader spectrum of risk factors to accurately assess periodontal disease risk. Existing periodontal risk assessment tools, such as the Periodontal Risk Assessment (PRA) and the Periodontal Risk Calculator (PRC), are limited by their narrow focus on a restricted range of risk factors [13]. The objective of this study was to systematically assess the impact of systemic conditions on periodontal health in Malaysian population, addressing the gap in the exploration of these factors as potential risk factors to periodontal diseases.

Materials and methods

This study entailed a retrospective, non-interventional design utilizing data sourced from medical records. Ethical approval was procured from the Research Ethics Committee at Universiti Sains Malaysia (JEPeM approval code: USM/JEPeM/20100506). Study was carried out at the School of Dental Sciences and the Unit Record Office of Hospital Universiti Sains Malaysia (USM) in Kubang Kerian, Kelantan, Malaysia. Data collection occurred over a period extending from September 2019 to December 2022.

Study population

The study population encompassed individuals afflicted with periodontitis in Kelantan. The source population was composed of periodontitis patients who sought treatment at Hospital Universiti Sains Malaysia, Kubang Kerian. The sampling frame consisted of patients diagnosed with periodontitis who visited Hospital Universiti Sains Malaysia between the months of January 2011 and December 2020. Study population were patients who reported to the dental clinic at Hospital Universiti Sains Malaysia and fulfilled specified inclusion criteria.

Inclusion criteria

• Patients with a confirmed diagnosis of periodontitis.

• Availability of complete demographic and clinicopathological data, including detailed periodontal charting, Decay Missing Filled Teeth (DMFT) records along with oral hygiene scores including dental plaque and gingivitis scores.

Exclusion criteria

• Patients with incomplete or missing dental and medical records.

• Subjects with unclear or unconfirmed diagnoses of systemic conditions, such as undiagnosed diabetes, hypertension, or cardiovascular diseases.

• Subjects with ambiguous demographic information, medical histories, or habits (e.g., smoking or alcohol use).

• Patients with inconsistent or missing clinical data, such as periodontal charting or oral hygiene scores.

The sample size for this study was calculated using G*Power 3.1.9.4 software, based on the primary objective of assessing the association between systemic conditions and periodontitis severity. To achieve a statistically significant result with a power of 80% and an alpha level of 0.05, the initial estimated sample size was 181 participants. However, considering potential exclusions due to incomplete or missing data, we accounted for a 30% dropout rate, which increased the required sample size to 259 participants. By utilizing a convenience sampling method, we ultimately included 274 patients in the final analysis. This sample size was adequate to detect significant associations between systemic conditions, demographic factors, and periodontitis severity, ensuring the robustness of the statistical analysis.

A standardized data collection form was employed to gather pertinent patient information from the medical records unit at HUSM. The collected variables included socio-demographic data (age, gender, ethnicity, smoking status, alcohol use, habits, predisposing factors, and family history of periodontitis and other diseases), periodontal parameters (pocket depth, gingivitis score, plaque score, and DMFT—decayed, missing, and filled teeth), and their associated systemic conditions.

The variables chosen for this study are well-established risk factors for periodontal disease, with varying degrees of influence:

• Systemic diseases such as hypertension and diabetes mellitus are known to exacerbate periodontal disease due to their impact on immune function and inflammation.

• Age was included as a variable because periodontal disease tends to increase in prevalence and severity with advancing age.

• Ethnicity was assessed because genetic and cultural factors can influence oral health behaviours and access to healthcare, thereby affecting the risk of periodontitis.

• Work and habits (e.g., smoking, alcohol consumption) were incorporated due to their known association with stress and lifestyle factors that may contribute to periodontal disease.

• Gingivitis and plaque scores were included as they directly reflect oral hygiene and the local environment of the oral cavity, which are primary contributors to the development and progression of periodontitis.

Data collection

Data collection commenced with the retrieval of registration numbers (RNs) for periodontal patients from the medical records unit at HUSM. These RNs were extracted from a computerized database encompassing patients who had visited HUSM over the preceding nine years. Patient records were subsequently accessed from the records office using a standardized request form. Out of 600 RNs submitted, 326 were excluded due to incomplete or missing records. The final dataset included 274 subjects (N = 274).

Inclusion of DMFT index

Although the primary focus of this study was on periodontitis, the DMFT index (Decayed, Missing, and Filled Teeth) was included to provide a comprehensive assessment of the participants’ overall oral health status. The “Missing” component of the DMFT score reflects tooth loss, which is often a consequence of advanced periodontitis. DMFT scores were obtained from pre-existing data sheets, categorizing teeth as decayed, missing due to caries, or filled, and the mean DMFT was calculated.

Plaque scores and gingivitis scores were extracted from pre-existing periodontal charting. Pocket depth data, also sourced from pre-existing records, were categorized into mild (< 4 mm), moderate (4–6 mm) and severe (> 6 mm). Percentages for each pocket depth category were computed.

Statistical analysis

Data cleaning and exploration identified missing values and entry errors. Descriptive statistics were calculated, including medians, interquartile ranges, frequencies, and percentages. Normality of the measured variables (DMFT, decay, missing, filled teeth, gingivitis score, plaque score, pocket depth) was assessed using histograms and Kolmogorov-Smirnov test. Non-parametric tests were utilized owing to the deviation from normality in the data distribution Associations between patient characteristics, medical conditions, and periodontitis severity were analysed with chi-squared, Fisher exact, Mann-Whitney U, and Kruskal-Wallis tests. Spearman’s correlation assessed relationships between DMFT, gingivitis, plaque scores, and pocket depth categories. Logistic regression identified factors associated with periodontitis severity (≥ 4 mm), with significant predictors (p < 0.25) from simple regression included in multiple regression models. Model fitness was assessed through interaction tests, the Hosmer-Lemeshow test, classification accuracy metrics and area under the receiver operating characteristic curve (AUC). Statistical analyses were conducted using SPSS version 27 (SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp).

Results

A total of 274 patients’ data was retrieved, comprising 51.8% males and 48.2% females. The median age of the cohort was 51.0 years. The majority of patients were of Malay ethnicity, accounting for 92.3% of the sample, and a substantial proportion, 70.8%, were employed. A significant patients reported no habitual behaviors (71.2%) and no history of allergic reactions (84.7%). Medically, 57.9% of the participants had no comorbid conditions, while hypertension and DM were prevalent, affecting 31.8% and 15.0% of the cohort, respectively. Clinically, the median plaque score was 73.75%, and the average pocket depth was 2.47 mm. The majority of patients were diagnosed with mild periodontitis, characterized by an average pocket depth of less than 4 mm in 96.5% of cases and an average maximum pocket depth of less than 4 mm in 62.0% of cases. The highest median percentage of periodontal pockets was observed at less than 4 mm, accounting for 80.70%.

Ethnicity was significantly associated with periodontitis severity (p = 0.003). Malay individuals exhibited a higher likelihood of mild (36.0%) and severe (4.7%) periodontitis compared to other ethnic groups, which showed rates of 4.8% and 0%, respectively. Severe periodontitis prevalence was elevated among those aged 18–44 years (5.5%, p = 0.142), males (4.9%, p = 0.88), employed individuals (5.7%, p = 0.777), and smokers (6.7%, p = 0.744).

Table 1 demonstrates that individuals aged 45–64 and Malays have a significantly higher risk of periodontitis severity (≥ 4 mm) compared to other age groups and ethnicities, respectively. No significant associations were found between gender, work history, smoking, or alcohol consumption and periodontitis severity.

Table 1.

The subject’s general characteristics with risk of periodontitis severity (≥ 4 mm)

Variables	n		COR (95% CI)	Wald (df)	p	AOR (95% CI)	Wald (df)	p
Age
	91	18–44	3.00 (1.05, 8.59)	4.19 (1)	0.041	2.73 (0.94, 7.98)	3.39 (1)	0.066
	154	45–64	3.41 (1.23, 9.42)	5.62 (1)	0.018	3.04 (1.08, 8.53)	4.44 (1)	0.035
	29	≥ 65	1
Gender
	142	Male	0.93 (0.57, 1.52)	0.08 (1)	0.784	-	-	-
	132	Female	1
Ethnicity
	253	Malay	13.7 (1.82, 103.94)	6.44 (1)	0.011	12.50 (1.64, 95.20)	5.95 (1)	0.015
	21	Others	1
Work History
	194	Employed	1.32 (0.24, 7.36)	0.10 (1)	0.754	-	-	-
	43	Unemployed	0.87 (0.14, 5.34)	0.02 (1)	0.877	-	-	-
	31	Retired	1.26 (0.20, 8.00)	0.06 (1)	0.804	-	-	-
	6	Others	1
Habits
	195	Nohabits	1
	75	Smoking	-
	4	Alcohol	1.60 (0.10, 25.88)	0.11 (1)	0.743	-	-	-

Figure 1 shows the association between allergic reactions and periodontitis severity. Patients without allergies primarily exhibited mild periodontitis (60.8%), while moderate and severe cases accounted for 35.8% and 3.4%, respectively. Among those allergic to food and the environment, 68.6% had mild, 22.6% had moderate, and 8.6% had severe periodontitis. In patients allergic to medication, 71.4% had mild, 14.3% moderate, and 4.3% severe periodontitis.

Fig. 1.

The prevalence of periodontitis based on allergic reactions

A significant negative correlation was observed between the gingivitis score and the percentage of pockets with depths less than 4 mm (r = -0.13, p = 0.038), along with a significant positive correlation with the percentage of pockets with depths of 4–6 mm (r = 0.15, p = 0.032). No significant associations were found between other medical and clinical conditions (gastrointestinal disorders, neurological issues, and endocrine abnormalities) and pocket depths (p > 0.05). The highest median values for pocket depths less than 4 mm were noted in individuals with medication allergies (M = 84.5, p = 0.978) and asthma (M = 90.3, p = 0.238). For pocket depths of 4–6 mm, the highest median values were found in those without allergic reactions (M = 15.7, p = 0.745) and other medical conditions (M = 18.6, p = 0.507). For pocket depths greater than 6 mm, the highest median values were observed in those without allergic reactions (M = 4.2, p = 0.359) and with hypertension (M = 5.0, p = 0.221) (Table 2; Fig. 2).

Table 2.

Association between subjects’ medical and clinical characteristics and periodontitis severity

		Periodontitis severity
Variables		Mild (< 4 mm)	Modeate (4–6 mm)	Severe (> 6 mm)
		F (%)	F (%)	F (%)	χ2 statisic (df)	p
Allergic reactions to food
No allergic	232	141 (60.8)	83 (35.8)	8 (3.4)
Food and Environment	35	24 (68.6)	8 (22.6)	3 (8.6)	6.70 (4)	0.122 b
Medication	7	5 (71.4)	1 (14.3)	1 (14.3)
Medical conditions
Healthy	158	92 (58.2)	58 (36.7)	8 (5.1)
HT	56	31 (55.4)	23 (41.1)	2 (3.6)
DM	38	30 (78.9)	7 (18.4)	1 (2.6)	13.82 (10)	0.127 b
Asthma	8	8 (100)	0 (0)	0 (0)
Gastritis	7	5 (71.4)	2 (28.6)	0 (0)
Others	7	4 (57.1)	2 (28.6)	1 (14.3)
		Median (IQR)	Median (IQR)	Median (IQR)	Kruskal H (df)	p
DMFT	274	4.7 (3.33)	5.0 (3.25)	6.2 (3.58)	3.98 (2)	0.136 c
Decay	274	2.0 (4.00)	2.0 (4.00)	3.5 (7.00)	0.21 (2)	0.902 c
Missing	274	6.0 (8.00)	8.0 (9.00)	11.0 (9.00)	5.51 (2)	0.064 c
Filled	274	2.0 (4.00)	2.0 (4.00)	2.5 (3.00)	0.93 (2)	0.629 c
Gingivitis score	269	49.1 (39.99)	65.8 (49.50)	62.6 (49.5)	14.00 (2)	0.001 c
Plaque score	268	75.0 (33.00)	75.0 (35.70)	72.0 (49.13)	0.41 (2)	0.816 c

F = frequency, ^aChi-square test, ^bFisher exact test, ^CKruskal Wallis H test. Significant level was set at p = 0.05

Fig. 2.

The prevalence of periodontitis based on medical reactions

The logistic regression analysis identified age and ethnicity as significant predictors of periodontitis. Individuals aged 18–44 and 45–64 were significantly more likely to have periodontitis compared to those aged ≥ 65 years, with odds ratios of 2.7 and 3.0, respectively. Malays had a notably higher risk, being 12.5 times more predisposed to developing periodontitis than individuals from other ethnicities. In terms of medical conditions, diabetes mellitus decreased the likelihood of severe periodontitis by 68%, while each unit increase in missing and gingivitis scores raised the odds of severe periodontitis by 6% and 2%, respectively. Both models showed no significant interactions between predictors and demonstrated similar model fit values, with Hosmer and Lemeshow Test p-values of 0.992 and 0.952, classification accuracies of 61.7–62.0%, and AUCs of 60.0–70.3% (Figs. 3 and 4).

Fig. 3.

Receiver operating characteristic (ROC) curve for the final logistic regression model predicting periodontitis (≥ 4 mm), incorporating medical conditions, missing score, and gingivitis score

Fig. 4.

Receiver operating characteristics (ROC) curve of the final logistic regression model of periodontitis (≥ 4 mm) severity with age and ethnicity

Discussion

Dental plaque and calculus accumulation are primary causes of periodontal diseases, systemic conditions also significantly influence the development and progression of periodontitis. Comprehending this interplay is vital for effective prevention, diagnosis, and management. Existing tools have limitations, often focusing on a few risk factors without considering the full range of systemic influences. In Malaysia, where 94% of dentate adults are affected by some form of periodontal disease [11], the high prevalence of systemic conditions such as DM, cardiovascular diseases and respiratory ailments further exacerbates this issue. Malaysia’s diverse genetic backgrounds, lifestyles, and healthcare practices necessitate a comprehensive assessment of systemic conditions as specific risk factors.

Although conventional probes are reliable and effective, electronic probes are favored in research due to their capacity for automatic recording. In this retrospective analysis, periodontitis severity was precisely categorized using maximum pocket depth, a methodology corroborated by other studies [14–16]. The National Health and Nutrition Examination Survey (2009–2012) reported an increase in the prevalence of periodontitis with advancing age [17]. Contributing factors in the elderly include deteriorating oral hygiene due to impaired vision, motor skills, and hyposalivation. Our study identified the highest prevalence of severe periodontitis within the 18–44 age group (5.5%), with age emerging as a significant predictor in the logistic regression analysis. Previous research has associated periodontitis in young, otherwise healthy males with subclinical atherosclerosis, aligning with our results that show increased periodontitis incidence among younger adults [18, 19]. Conversely, in individuals aged 65 and older, severe periodontitis was predominantly mild, consistent with American survey data indicating a reduction in severe periodontitis in this age group due to tooth loss [20]. Our study comprised 274 participants (51.8% male, 48.2% female). Severe periodontitis was predominantly observed in males, which aligns with literature [21]. This gender disparity may be attributed to poorer oral hygiene practices among males. Literature indicates that men are more likely to harbor periodontal pathogens and possess specific testosterone receptors in periodontal tissues, which could affect disease progression [13, 22]. In our analysis, females exhibited higher prevalence rates for pocket depths < 4 mm and 4–6 mm, whereas males were more likely to have pocket depths > 6 mm. Conversely, Al-Abdaly et al. reported a greater prevalence of severe periodontitis in females [14].

In our study, ethnicity was a significant predictor of periodontal disease severity, with Malays showing higher prevalence rates of both mild (36.0%) and severe periodontitis (4.7%) compared to other ethnicities (4.8% and 0%, respectively). This association was statistically significant (p = 0.003) and persisted in the final regression model, indicating a 12.5-fold increased risk for Malays of severe periodontitis. However, the predominance of Malays in our sample may introduce sample bias, suggesting the need for further research with a more diverse and larger cohort to confirm these findings. Similar patterns have been observed in other studies; Selvaraj et al. (2022) noted a significant ethnic association with periodontal disease among South Indians, though their sample was predominantly Tamil [15]. Additionally, Gillone et al. reported that Black Americans were twice as likely to suffer from periodontitis compared to White Americans, and Hispanics were 1.5 times more susceptible than non-Hispanics [16]. Weatherspoon et al. (2016) also found higher periodontal disease prevalence among Black and Chinese populations compared to Whites, supporting the role of ethnicity in periodontal health [20].

Our results corroborate previous research connecting employment status to periodontal disease. Individuals employed in high-stress jobs were found to have a higher prevalence of severe periodontitis. Zaitsu et al. (2017) reported that those with heavier workloads were more likely to experience periodontal issues, and extended working hours were linked to increased periodontitis risk, potentially attributable to stress-induced activation of the hypothalamic-pituitary-adrenal (HPA) axis and subsequent glucocorticoid secretion [23]. Furthermore, Morita et al. (2007) found that Japanese professionals had lower Community Periodontal Index (CPI) scores than those in less skilled occupations [24], supporting our finding that occupational status affects periodontal health. Workers in lower-grade jobs exhibited higher CPI scores, reflecting more severe periodontal disease.

The study revealed that most patients with periodontitis did not have recorded systemic conditions, with hypertension being the most prevalent comorbidity at 31.8%. This finding was consistent with research linking hypertension to periodontitis, such as Tsakos et al. (2010) and Yalin et al. (2023), who identified significant associations between hypertension and severe periodontitis [25, 26]. Mechanisms include endothelial dysfunction and oxidative stress, which exacerbate periodontal inflammation. DM, the second most common systemic condition (15.0%), was not statistically significant in our study, aligning with Madi and Abuohashish et al., who reported similar prevalence in Saudi patients [27]. Meta-analyses also confirmed a strong link between type 2 diabetes and severe periodontitis, with a bidirectional relationship where chronic periodontal inflammation can worsen glycemic control. Asthma and gastritis were less prevalent, at 2.91% and 2.55%, respectively [28, 29].

Although associations between periodontitis and asthma and chronic gastritis are noted, the evidence is less conclusive. The finding that all asthma patients in this study had mild periodontitis contrasts with existing literature [30–32], suggesting a potential link between asthma and increased risk of periodontal disease due to the chronic inflammatory nature of asthma. It is possible that the use of inhalers, which can reduce salivary flow and contribute to oral dryness, might predispose asthma patients to periodontal problems. However, in this study, no moderate or severe periodontitis was observed among asthma patients, which may suggest that other factors, such as better oral hygiene practices or well-managed asthma, could have mitigated the severity of periodontal disease in this cohort. Additionally, the small sample size of asthma patients (n = 8) may have limited the ability to observe more severe cases, and further research with a larger sample is needed to investigate the relationship between asthma and periodontitis more comprehensively. Our study found a higher prevalence of periodontitis among smokers, with 27% of patients reporting tobacco use. This is consistent with prior research showing that smokers have deeper probing depths, more attachment loss, and increased alveolar bone loss [9]. Smoking impairs wound healing and diminishes immune responses, exacerbating periodontal disease. A systematic review by Leite et al. (2018b) reported an 85% increased risk of periodontitis associated with smoking [33]. In contrast, alcohol consumption showed minimal association with periodontitis in our study, likely due to the low prevalence of alcohol use among Malays. This aligns with findings that alcohol consumption is less common in certain ethnic groups [34].

There was no significant association between allergic reactions and periodontitis, with 84.7% of patients reporting no allergies. This is consistent with previous research indicating an inverse relationship between allergy prevalence and periodontal disease severity [35]. Although allergic reactions may be linked to poor periodontal health through systemic inflammation, further research is needed to elucidate these connections. The DMFT index showed a trend towards higher missing teeth scores in patients with severe periodontitis, though this association was not statistically significant. Previous studies have shown variable associations between dental caries and periodontal disease, with some populations experiencing higher tooth loss due to periodontal reasons [36]. The relationship between caries and periodontal disease can differ based on age and carious involvement.

Binary logistic regression analysis identified significant predictors of periodontitis (≥ 4 mm), including age group, ethnicity, DM, missing score and gingivitis score. While older individuals generally show higher prevalence due to cumulative risk factors and age-related immune decline. Our study found that individuals aged 18–44 and 45–64 were significantly more likely to have periodontitis compared to those aged ≥ 65. This unexpected finding may relate to lifestyle factors such as smoking, diet, and oral hygiene practices, suggesting the need for targeted public health interventions for these age groups. Ethnicity also emerged as a significant predictor, with Malays being 12.5 times more predisposed to periodontitis compared to other ethnic groups, supporting previous research that highlights the role of genetic, cultural, and socioeconomic factors in periodontal disease prevalence. However, in our study, the logistic regression analysis yielded an unexpected finding that individuals with diabetes mellitus were less likely to have severe periodontitis, with a 68% decrease in likelihood. This finding may have been influenced by several factors, such as the management of diabetes in the study population. For example, participants with well-controlled diabetes might have received more frequent dental check-ups and better oral care, which could have mitigated the severity of periodontitis. Additionally, the specific characteristics of our study cohort, including the possibility of underreporting or differences in healthcare access, might have played a role in this observation. Further research is required to fully understand the relationship between diabetes and severe periodontitis in this specific population and to investigate whether factors such as diabetes management and healthcare access may have influenced these findings.

The strength of the study was evident in its comprehensive analysis of both modifiable and non-modifiable risk factors linked to the severity and localization of periodontal pockets. The statistical analysis alongside binary logistic regression, to elucidate significant predictors of periodontal disease. Concentrating on patients of Malay ethnicity, the research offers critical insights into demographic-specific risk factors, thereby contributing valuable data to the existing body of literature. Despite the study’s strengths, several limitations must be acknowledged. The cross-sectional design limits the ability to determine causality or track disease progression. Self-reported data on smoking and alcohol use may introduce recall bias, affecting accuracy. While the sample size was adequate, it may not fully represent the diversity of periodontal conditions, potentially impacting generalizability. Additionally, focusing solely on Malay patients may limit the applicability to other ethnic groups. Future research should use longitudinal designs, objective measures, and more diverse populations to enhance robustness and generalizability.

Future directions

To enhance oral health and deepen our understanding of periodontitis, several key recommendations are proposed. Future research should involve diverse ethnic groups to explore how ethnicity influences periodontitis, particularly in relation to systemic conditions. Multi-center studies with larger, varied populations could offer a more comprehensive perspective. Employing detailed periodontal recording systems and conducting prospective clinical studies will help clarify the impact of systemic conditions as risk factors for periodontitis. Additionally, investigating the potential bidirectional relationship between periodontal pathogens, inflammation, and systemic conditions is crucial. Finally, integrating care from a multidisciplinary team of medical and dental professionals will be essential to effectively address the complex interplay between systemic and oral health.

Conclusion

Ethnicity and gingivitis scores are crucial factors in determining periodontitis severity, with ethnicity emerging as a significant predictor. Systemic conditions and socio-demographic factors, apart from ethnicity, did not show significant associations with periodontitis severity or pocket depth. This emphasizes the need for targeted management strategies that address ethnic-specific risks in periodontal health. Given the often-asymptomatic nature of periodontitis, early diagnosis and comprehensive management are essential. Attention to both local and systemic factors is vital for effective disease management and treatment outcomes. Regular, multidisciplinary evaluations are necessary for addressing periodontal issues and ensuring long-term stability.

Author contributions

SA, RAR and MIK conceptualize and design the study; SA, RAR and MIK did data collection; SA, NAR, ABH and MIK wrote the manuscript; WMA did analysis; RNM, SB and MIK critically reviewed and edited the manuscript; RAR and MIK supervised; All authors reviewed the manuscript.

Funding

None.

Data availability

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

Declarations

Ethics approval and consent to participate

This study was conducted according to the guidelines of the Declaration of Helsinki, and Ethical approval was procured from the Research Ethics Committee at Universiti Sains Malaysia (JEPeM approval code: USM/JEPeM/20100506). Informed consent was obtained from the participants to participate in the study. Additionally, the patients sign a general consent before any treatment or investigation is rendered, including consent to use the samples or the findings in future studies without any personal identification.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.