Sociodemographic and clinical factors associated with early childhood caries in Peruvian pre-schoolers
Early childhood caries (ECC) is a pervasive oral health issue affecting children globally. It is characterised by the rapid destruction of tooth enamel, leading to cavities, pain, infection and, in some cases, tooth loss. The American Academy of Paediatric Dentistry defines ECC as the presence of one or more decayed (cavitated or non-cavitated), missing (due to caries), or filled primary tooth surfaces in children aged 71 months or younger . Globally, ECC affects approximately 530 million children, with higher prevalence rates in low-income countries . Prevalence estimates range from 6 to 90%, with developing nations disproportionately affected . The World Health Organisation identifies ECC as a significant public health issue, classifying it among the most prevalent global diseases . The prevalence of ECC is influenced by the healthcare system in each country and the level of access to preventive and curative care. Although poverty is strongly associated with ECC, countries with higher gross national products may also exhibit elevated rates of ECC. Additionally, ECC prevalence tends to be higher in nations with substantial portions of their populations living in slums or below the poverty line . Vulnerable and marginalised portions are disproportionately affected by ECC, with data indicating that three out of every four individuals affected by this oral disease reside in low- and middle-income countries . Poverty-related factors—such as low education levels, inadequate maternal knowledge, poor attitudes and behaviours and limited resources—often hinder mothers’ ability to provide proper oral healthcare for their children . Early childhood caries is a multifactorial disease resulting from the interaction of various factors, including tooth surface sensitivity, fermentable carbohydrates and cariogenic microorganisms acting over prolonged periods. Risk factors contributing to the occurrence and progression of ECC include sociodemographic factors (e.g. age, parental education level and occupation), biological factors (e.g. salivary pH, buffering capacity and flow rate), dietary habits (e.g. breastfeeding/bottle feeding, night-time feeding and frequency of sugary snacks) and oral health behaviours (e.g. frequency of toothbrushing and dental visits) . Other high-risk factors include poor nutritional status (evidenced by anthropometric measures), vitamin D deficiency and iron deficiency anaemia . If left untreated, ECC may progress to more severe forms, leading to malocclusions, abscesses, oral pain, compromised oral health-related quality of life, malnutrition and growth deficits . Furthermore, preschool children with ECC face an increased risk of developing new caries lesions in the future . Severe cases, such as tooth loss or craniofacial anomalies, can adversely impact social and emotional well-being, learning and employability. In Peru, a study revealed that the prevalence of caries in children under 71 months of age in marginal urban communities in Lima was 62.3%. The condition is recognised as a public health problem due to its significant consequences on children’s health and quality of life as well as the financial burden it imposes on families . To address ECC effectively, a prevention-focused approach tailored to individual caries risk is essential. Risk-based strategies can significantly improve ECC control. It is therefore critical to investigate the risk factors associated with ECC to combat the disease and promote better oral health among children. Beyond poor feeding practices, ECC reflects a complex aetiology encompassing sociodemographic and clinical factors, which must be considered to understand its true scope. However, data on ECC remain limited both globally and nationally, particularly in inland regions such as Ica, where ECC prevalence is alarmingly high (98.75%, according to a national study of children aged 6–15 year) . This study aimed to identify the sociodemographic and clinical factors associated with early childhood caries in a hospital located in the city of Ica, Peru. 

This cross-sectional study employed a quantitative approach to analyse data and explore descriptive associations between factors contributing to ECC . The study population comprised children aged 3–6 years who were treated at the Dental Service of Hospital Santa María del Socorro (HSMSI) in Ica, Peru, in 2023. The sample size was determined using G*Power 3.1.3 software for logistic regression analysis. With an odds ratio of 1.3, a significance level of 0.05 and a power of 0.80, a minimum sample size of 153 participants was calculated. Simple random sampling was used to select participants. Inclusion criteria included cooperative children aged 3–6 years of both genders, while exclusion criteria included children with systemic disease, neurological disorders or those without parental consent. This study was conducted in compliance with the Declaration of Helsinki guidelines . The research protocol was submitted for ethical review and was approved by the Ethics Committee of Santa María del Socorro Hospital (HSMSI), Ica, Peru (Approval No. R-2023-100-16). All mothers/caregivers ( n = 186) accepted their participation and their children, by signing the informed consent form. Data were collected using an ad hoc questionnaire validated for this study. An additional file provides the detailed questionnaire (additional file ). Information gathered from mothers/caregivers included child demographics (e.g. age and gender), parental characteristics (e.g. education level and marital status), household details, oral health practices and dietary habits. Clinical oral examinations were conducted by two paediatric dentists trained in ICDAS II. The examiners were calibrated in two stages: theoretical and practical. The theoretical stage focused on ensuring a robust understanding of assessment criteria, while the practical stage involved the evaluation of images. Inter-examiner and intra-examiner calibration agreements were subsequently assessed using the Kappa test, yielding results of 0.85 and 0.89, respectively. Oral assessments using ICDAS II began with pre-preparation procedures, including cleaning the tooth surface to remove plaque and debris, followed by adequate air drying for at least 5 s. Lighting conditions were optimised, with the dental unit’s light used to ensure proper visibility during the assessment. During visual inspection, each tooth was carefully examined without applying pressure with a periodontal probe to prevent damage to the tooth structure. Dental mirrors were utilised as necessary to evaluate all surfaces comprehensively. Haemoglobin (Hgb) testing was performed by two experienced paediatric nurses using a finger-prick method. Blood samples were collected by pricking the finger with a lancet, discarding the first three drops and then collecting an adequate blood sample to fill the microcuvette in a single step. Measurements were recorded using the HemoCue ® Hb 201 analyser. The collected data were transferred to a database created using Microsoft Office Excel 2019. Data analysis was performed using Stata Software version 17 (StataCorp, College Station, Texas), Jamovi, R programming language version 4.3.2 (Eye Holes) and the RStudio interface. Descriptive analyses were conducted to summarise qualitative variables, such as mother/caregiver education level (primary, secondary or higher), toothbrushing frequency (one per day, twice per day or three times per day), consumption of sweets (none, once or twice per day or more than twice per day), oral hygiene levels (poor, regular or good), gestation type (term or preterm), delivery type (vaginal or caesarean), type of breastfeeding (maternal, artificial or mixed), birth order (first to fifth), mother/caregiver gender (female or male), mother/caregiver occupation (homemaker, employed, labourer or self-employed), mother/caregiver marital status (single, cohabitating, married or divorced), anaemia status (normal or anaemia) and ECC prevalence according to ICDAS II criteria (present or absent). Central tendency and dispersion measures were used for quantitative variables, including the child’s age, height, weight, mother/caregiver’s age, household size, number of children at home, monthly family income and the child’s Hgb level). A multivariate analysis of sociodemographic and clinical factors associated with ECC was conducted using multiple logistic regression. The dependent variable was ECC presence (with or without caries), while sociodemographic and clinical factors served as independent variables [ , – ]. Variables contributing to the model were identified using the maximum likelihood method ( α = 0.05), with odds ratios (ORs) and regression coefficients indicating the magnitude and direction of contributions to the model. 

Of the 183 children evaluated, 76.88% ( n = 143) presented with ECC. Normal Hgb levels were observed in 82.26% ( n = 153), whereas 17.74% ( n = 33) exhibited anaemia. Among mothers/caregivers, 86.56% ( n = 161) were female, and 38.71% ( n = 72) identified as homemakers. Additionally, 35.48% ( n = 66) of caregivers had primary education, and 41.4% ( n = 77) were cohabiting (Table ). Table presents the mean values of key variables. The average age of children was 4.44 ± 0.87 years, with a mean monthly family income of $376.35 ± $153.96. The mean Hgb level was 12.27 ± 1.10 g/dL, and the mean plaque index was 42.71 ± 24.69. The average age of mothers/caregivers was 34.55 ± 6.78 years. Table summarises the logistic regression model’s results. Six factors were included in the final model, with two positive logit coefficients: child’s age and sweet consumption. Conversely, the child’s Hgb level, monthly family income, toothbrushing frequency, and mother/caregiver educational level showed negative coefficients. Key findings include the following: (1) for each additional year of age, the odds of ECC increased by 3.32 times (95% CI, 1.68–6.58); (2) for every unit increase in family income, the odds of ECC decreased by 0.998 times (95% CI, 0.9972–0.9998); (3) higher Hgb levels were associated with reduced odds of ECC by 0.428 times (95% CI, 0.25–0.72); (4) increased brushing frequency reduced ECC odds by 0.127 times (95% CI, 0.02–0.65); (5) frequent sweet consumption significantly increased ECC odds by 4.98 times (95% CI, 1.05–23.56). The model’s overall accuracy was 89.25%, with a sensitivity of 95.10% and a specificity of 69.77%. Figure demonstrates that the probability of ECC increases with the age of the child, with the lowest probability observed at 3.57 years (62.23%) and the highest at 5.32 years (93.10%). Figure illustrates that the probability of ECC decreases as haemoglobin levels (g/dL) increase, with the lowest likelihood at a level of 13.37 g/dL (64.87%) and the highest at 11.16 g/dL (92.33%). Figure shows that the likelihood of ECC decreases with increased frequency of brushing, with the lowest probability of brushing twice or more daily (62.78%) and the highest likelihood of brushing only once daily (92.95%). Figure indicates that the probability of ECC significantly increases with the consumption of sweets, with the lowest probability when children do not consume sweets (67.7%) and the highest probability when they do (91.33%). Figure reveals that the likelihood of ECC decreases as monthly family income increases, with the lowest probability at an income of $523.17 (66.29%) and the highest at $218.05 (91.88%). Figure illustrates that the probability of ECC decreases as the mother’s or caregiver’s educational level increases, with the lowest likelihood associated with higher education (63.04%) and the highest with primary or secondary education (92.88%). 

This study evaluated 183 children through clinical assessments and a questionnaire addressed to their mothers or caregivers to explore the sociodemographic and clinical factors associated with ECC. The results revealed that 76.88% of the children assessed had ECC [ – ], consistent with findings reported in similar studies , although some studies have reported lower prevalence rates [ – ] or higher rates . However, most research concurs that ECC remains highly prevalent. Key findings of this study indicate that ECC occurrence is significantly associated with the child’s age, monthly family income, haemoglobin levels, mother’s or caregiver’s educational level, brushing frequency and sweet consumption. Specifically, as the child’s age and sweet consumption increase, so does the likelihood of ECC. Conversely, as monthly household income, haemoglobin levels, and the mother’s or caregiver’s educational level increase, the likelihood of ECC decreases. These findings align with those of other studies examining similar variables and age groups [ – ]. Regarding the association between ECC and age, several explanations have been proposed. Ogordi et al.,  citing Park et al.,  suggested that older children are more likely to consume cariogenic foods and beverages due to increased access to money from parents. Jamshidi et al.  argued that the longer exposure of teeth to cariogenic factors with age contributes to higher ECC prevalence, a view echoed by Nneka et al.  Anderson et al.  attributed the increased prevalence of ECC with age to the natural progression of the condition over time. Concerning the association between ECC and family income, several studies have corroborated the findings of this research [ – ]. De Barros et al.,  along with Texeira , Al Marshad , and Carvalho , reported that low socioeconomic status is linked to a higher incidence of dental caries. These studies highlighted that children from low-income families often lack oral hygiene practices before tooth eruption and rarely use toothbrushes or toothpaste after eruption [ – ]. Additionally, economic hardships can lead to parental stress, adversely affecting children’s oral care . In contrast, Folayan et al.  argued that monetary poverty accounts for only 1% of ECC occurrences, emphasising other poverty indicators such as access to food, water, sanitation, healthcare, housing and education. The educational level of the mother or caregiver emerged as a critical sociodemographic factor influencing ECC occurrence [ , – ]. Carrada et al.  identified low maternal education (< 9 years of schooling) as a risk factor for ECC. Similarly, Chen et al.  linked higher caries prevalence to lower maternal educational attainment, noting that less educated parents tend to exhibit poor dental care practices. This study also found haemoglobin levels to be a significant predictor of ECC. The association may stem from the inflammatory response of oral tissues in children with caries, leading to reduced haemoglobin levels, as observed in other chronic conditions [ – ]. Nutritional deficiencies due to poor dietary habits in low-income families or unhealthy eating patterns in wealthier households may contribute to anaemia, further exacerbating the risk of ECC. A systematic review by Ji et al. . revealed that children with ECC are more likely to have iron deficiency, with significantly lower haemoglobin levels compared with children without ECC. The increased risk of ECC associated with iron deficiency is explained by two theories. The first posits that iron deficiency affects the salivary glands, reducing salivary secretion and thereby weakening the protective capacity against dental caries. The second suggests that, as iron ions exhibit anticavity properties that inhibit Streptococcus mutans activity, iron deficiency compromises this defence mechanism, preventing iron ions from combining with dissolved phosphates and calcium ions in the oral environment . Faheem et al.  further reported that low haemoglobin levels impair the ability of cells and tissues to maintain normal physiological function, adversely affecting not only the physical and mental development of children but also the oral cavity’s defence mechanisms. In addition, other factors are associated with ECC. In this study, brushing frequency was identified as a significant predictor of ECC occurrence. Chamli et al.  reported a statistically significant association between brushing frequency and ECC, with a higher prevalence among children who never brushed their teeth. Susceptibility to ECC is linked to factors such as incorrect brushing techniques, delayed initiation of toothbrushing, and irregular brushing habits [ – ]. Chouchene et al.  observed that very young children, while under parental supervision, may not yet know how to brush their teeth correctly. However, this supervision often diminishes as children grow older. Nassar et al.  found that parents frequently assume children can achieve effective tooth cleaning without their help, leading to less frequent brushing at older ages. The consumption of sweets is another significant predictor of ECC, as observed in this study and others. Poor dietary habits, particularly the consumption of sugar-laden foods, are strongly associated with an increased incidence of dental caries [ , , – ]. Parsaie et al.  and Araújo et al.  reported that the burden of chronic oral diseases is evident even in early childhood, attributable to higher sugar consumption by both mothers and children. However, some studies differ. For instance, Sandoval-Lovon et al.  noted that while children with caries consumed sweets more frequently, this association was not statistically significant. This study has several limitations, and the findings should be interpreted with caution. First, although various potential factors have been considered, other unexamined factors may also contribute to the presence of ECC. Second, the study’s regional scope and sample population may limit the generalisability of its findings to other areas. Third, as a cross-sectional survey, the study could not capture longitudinal data. For example, more precise details about the duration of toothbrushing and the quantity of sweets consumed would enhance the analysis of ECC risk factors, necessitating future prospective longitudinal studies. 

The study revealed that a child’s age, monthly family income, mother/caregiver education level, haemoglobin level, brushing frequency and sweet consumption are significantly associated with ECC occurrence. Identifying these factors can facilitate the development of targeted preventive interventions for at-risk children, thereby reducing ECC prevalence and improving paediatric oral health outcomes. 

Below is the link to the electronic supplementary material. Supplementary Material 1 

