Is the burden of oral diseases higher in urban disadvantaged community compared to the national prevalence?

Abstract

BackgroundThe urban low income has often been assumed to have the greatest dental treatment needs compared to the general population. However, no studies have been carried out to verify these assumptions. This study was conducted to assess whether there was any difference between the treatment needs of an urban poor population as compared to the general population in order to design an intervention programme for this community.MethodsA random sampling of living quarters (households) in the selected areas was done. 586 adults over 19 years old living in these households were clinically examined using World Health Organization (WHO) Oral Health Survey criteria 4th edition (1997).ResultsThe overall prevalence of dental caries, periodontal disease, denture wearers and temporomandibular joint problems were 70.5%, 97.1%, 16.7% and 26%, respectively. The majority (80.5%) needed some form of dental treatment. The highest treatment needs were found in the oldest age group while the lowest were in the youngest group (19-29 years) (p = 0.000). The most prevalent periodontal problem was calculus; regardless of gender, ethnicity and age. Significantly more females (20.5%) wore prosthesis than males (11.1%) (p = 0.003). Prosthetic status and need significantly increased with age (p = 0.000). About one in four adults had Temporo-Mandibular Joint (TMJ) problems. Overall, it was surprising to note that the oral disease burden related to caries, prosthetic status and treatment need were lower in this population as compared to the national average (NOHSA, 2010). However, their periodontal disease status and treatment needs were higher compared to the national average indicating a poor oral hygiene standard.ConclusionsThe evidence does not show that the overall oral disease burden and treatment needs in this urban disadvantaged adult population as higher than the national average, except for periodontal disease. The older age groups and elderly were identified as the most in need for oral health intervention and promotion. An integrated health intervention programme through a multisectoral common risk factor approach in collaboration with the Faculties of Medicine, Dentistry and other agencies is needed for the identified target group.

Prevalence and determinants of oral health conditions and treatment needs among slum and non-slum urban residents: Evidence from Nigeria

“…These include the Community Periodontal Index of Treatment Needs (CPITN), Clinical Attachment Level (CAL), and/or probing depth (PD). The reported prevalence rates varied but were equally high [25,26,81,82]. Our findings that periodontal disease affected close to three-quarters of the slum dwellers and about half of the non-slum residents further buttresses the heavy burden of periodontal disease being borne by populations in LMICs particularly those residing in slums.…”

Spatial distribution analysis of dentists, dental technicians, and dental therapists in Indonesia

“…Spatial analysis was used to identify dental health personnel shortages and geographical distribution. The traditional methods use administrative boundaries such as counties as the basic spatial units as well as dental health personnel to identify shortages based on those numbers [30][31][32] . Such approaches have been criticized for their inability to account for either the spatial variations of population demand and dental health personnel supply within those boundaries or for population-dental health personnel interactions across them.…”

Validation of the Malay Oral Impacts on Daily Performances and Evaluation of Oral Health-Related Quality of Life in a Multi-Ethnic Urban Malaysian Population: A Cross-Sectional Study

“…The participants were conveniently recruited within an urban area, which may not be nationally representative. However, the dental disease level of previous participants surveyed within such urban areas were reported to be similar to the national prevalence [ 54 ]. The number of Indian participants was low and therefore excluded from the partial correlation analysis.…”