Determinants of maternal and household social inequalities of dental caries among Senegalese children in the Department of Pikine

Abstract

Introduction the problematic of social Inequalities in oral health remains a global concern; it constitutes evidence of social injustice. The present work aims to study the determinants of maternal and household social inequalities of children´s dental caries in Pikine. Methods cross-sectional epidemiological survey has been conducted in the department of Pikine, Senegal on 315 children aged 3 to 9 and their mothers. The clinical data on children´s caries have been obtained by clinical examination and the socio-economic data by a questionnaire submitted to mothers. Pearson chi-square and trend tests as well as a logistic model were used in the data analysis. Results the prevalence of dental caries in children was 64.8% and the mixed decayed, filled, missing (DFM) index was 2.5 (±2.7). The trend test showed significant inequalities in the prevalence of dental caries according to level of studies (p<0.001), profession (p<0.010) and contacts frequency (p<0.001) of mothers; the level of wealth (p<0.001) and structure (p<0.005) of households. According to the logistic regression model, the level of secondary or university education [OR (IC 95%) = 0.59 (0.33'>OR (IC 95%) = 0.59 (0.33-0.93)] or social network dynamism [OR (IC 95%) = 0.32(0.15'>OR (IC 95%) = 0.32(0.15-0.67)] of mothers; as well as wealthy families [OR (IC 95%) = 0.23(0.08'>OR (IC 95%) = 0.23(0.08-0.64) were associated to fewer risks of dental caries among children. Conclusion some socio-economic characteristics of the mother and the household social conditions are identified as determinants of dental caries social inequalities in Children. Proportionate universalism may be a good approach to reduce this problematic in Pikine.

Reducing Social Inequalities in Access to Dental Care in Senegal: Evaluation of a Flat-Rate Pricing Program at the Health District Level

“…Strati ed sampling based on age and sex was chosen with proportional allocation to the weight of the age and sex categories for both the intervention and control districts. To determine the sample size for each group, the following formula was used: ni = nt = 2P(1-P)(Z α +Z 2β ) 2 /(P i -P t ) 2 ; n = number of individuals in each group (ni = intervention and nt = control); Zα = 1.96 when alpha is 5%; power = 80% is equal to Z2β = 0.84; theoretical dropout = 50% for the control site; and an OR = 0.4 is expected. Thus, the sample size in each group was 106 participants.…”

“…In Africa, there are strong social health disparities and inequalities in access to oral health care. The underserved population is facing social barriers to accessing care, particularly nancial barriers leading to the renunciation of care or the risk of household impoverishment (1)(2)(3). The World Health Organization (WHO) estimated that 1.4 to 1.9 billion individuals were affected by nancial di culties in 2017.…”