Utilisation of dental services by Brazilian adults in rural and urban areas: a multi-group structural equation analysis using the Andersen behavioural model

Abstract

Background: The utilisation of health services is determined by complex interactions. In this context, rural populations face greater barriers in accessing dental services than do urban populations, and they generally have poorer oral health status. The evaluation of the determinants of health services utilisation is important to support planning and management of dental services. The aim of this study was to evaluate the predictors of dental services utilisation of Brazilian adults living in rural and urban areas.

Methods: Data from 60,202 adults aged 18 years or older who took part in the Brazilian National Health Survey carried out in 2013 were analysed. Predisposing (age, sex, education, social networks), enabling financing (income, durable goods and household's crowding), enabling organisation (health insurance, registration in primary health care [PHC]) and need variables (eating difficulties, self-perceived tooth loss and self-perceived oral health) were selected based upon the Andersen behavioural model. Multi-group structural equation modeling assessed the direct and indirect associations of independent variables with non-utilisation of dental services and the interval since the last dental visit for individuals living in rural and urban areas.

Results: Adults living in urban areas were more likely to use dental services than those living in rural areas. Lower enabling financing, lower perceived dental needs and lack of PHC registration were directly associated with lower utilisation of dental services (non-utilisation, β = - 0.36, β = - 0.16, β = - 0.03, respectively; and interval since last dental visit, β = 1.25, β = 0.82, β = - 0.12, respectively). The enabling financing (non-utilisation, β_rural = - 0.02 [95%CI: - 0.03 to - 0.02], β_urban = 0.00 [95%CI: - 0.01 to 0.00]) and PHC registration (non-utilisation, β_rural = - 0.03 [95%CI: - 0.04 to - 0.02], β_urban = - 0.01 [95%CI, - 0.01 to - 0.01]) non-standardised total effects were stronger in rural areas. Enabling organisation (β = 0.16) and social network (β = - 2.59) latent variables showed a direct effect on the interval since last dental visit in urban areas. Education and social networks influenced utilisation of dental services through different pathways. Males showed less use of dental services in both urban and rural areas (non-utilisation, β_rural = - 0.07, β_urban = - 0.04; interval since last dental visit, β_rural = - 0.07, β_urban = - 0.07) and older adults have used dental services longer than younger ones, mainly in rural areas (β_rural = 0.26, β_urban = 0.17).

Conclusion: Dental services utilisation was lower in rural areas in Brazil. The theoretical model was supported by empirical data and showed different relationships between the predictors in the two geographical contexts. In rural areas, financial aspects, education, primary care availability, sex and age were relevant factors for the utilisation of services.

Keywords: Dental health services utilisation; Health surveys; Rural population; Theoretical models.

Fig. 1

Hypothesised theoretical model for dental services utilisation in Brazilian adults using the Andersen behavioural model. Arrows indicate hypothesised direct relationships between variables. Measured variables are in rectangles and latent variables in ellipses

Fig. 2

Confirmatory factor analysis of the 4-factors 13 items (measurement model). Obtained through bootstrapped ADF item loadings (standardised coefficients / bias-corrected 95% confidence intervals). ^**Significant standardised coefficients (P < 0.01)

Fig. 3

Parsimonious models of associations between predisposing, enabling and need factors and dental services utilisation outcomes. A, non-utilisation of dental services, and B, interval since the last dental visit. Solid lines indicate standardised direct effects. ** P < 0.01

Fig. 4

Parsimonious models for non-utilisation of dental services in urban and rural areas. Solid lines indicate standardised direct effects. ** P < 0.01

Fig. 5

Parsimonious models for the interval since the last dental visit in urban and rural areas. Solid lines indicate standardised direct effects. * P < 0.05, ** P < 0.01