Frequency, inequalities and spatial distribution of oral health services utilization in Peruvian children under twelve years of age: a population-based comparative analysis of the years 2017 and 2021.

BACKGROUND: Oral diseases pose a significant public health challenge among Peruvian children. However, oral health services utilization among them is marked by inequalities, which may have been exacerbated by the COVID-19 pandemic. The objective was to compare the frequency, inequalities, determinants of inequality, and spatial distribution in oral health services utilization in Peruvian children under 12 years of age in 2017 and 2021. METHODS: Comparative secondary data analysis from the Demographic and Family Health Survey (ENDES) for the years 2017 (38,787 minors) and 2021 (36,729 minors). Age-adjusted prevalence ratios (PR) with 95% confidence intervals (CI) were calculated to assess the change in oral health services utilization in the last 12 months between the years 2017 and 2021, stratifying by demographic and socioeconomic covariates. Inequality was assessed by decomposing the Erreygers Concentration Index (ECI) and calculating the percentage contribution to inequality of the independent variables. Spatial analysis was performed using spatial autocorrelation methods, Hot Spot Analysis, Cluster and Outlier analysis, Inverse Distance Weighting, ordinary Kriging, and Kulldorff analysis. RESULTS: The probability of Peruvian children under 12 years of age using oral health services in the last 12 months was reduced by 45% in 2021 compared to 2017. The ECI identified a significant reduction in oral health services utilization inequalities at the national level (Diff: -0.0963; p < 0.001). The main contributor to inequality was higher tutor education level (55.2% in 2017 and 82.7% in 2021). In the comparison of spatial distribution, there was a greater dispersion of the conglomerates in which the use of oral health services is concentrated in 2021. CONCLUSIONS: The frequency of oral health services utilization in the Peruvian children under 12 years of age was halved between 2017 and 2021. This problem is transversal to the entire population at the demographic and socioeconomic level. The key factor contributing to inequalities in the utilization of oral health services was the higher educational attainment of caregivers or guardians. Despite the improvement observed in inequalities and spatial distribution of the concentration of oral health services utilization, it is necessary to keep monitoring these patterns to guide decision-making.

[Spatial analysis of hypertension in Peruvian adults, 2022]. / Análisis espacial de la hipertensión arterial en adultos peruanos, 2022.

Objectives: To perform a spatial analysis of arterial hypertension in the Peruvian adult population to identify geographic patterns with a higher concentration of cases. Materials and methods: A spatial analysis was conducted using data from the Demographic and Family Health Survey (ENDES) 2022. A sample of 29,422 adults was included, and the global Moran's index and Getis-Ord Gi* analysis were used to evaluate spatial autocorrelation and cluster concentration. Results: The age-standardized prevalence of arterial hypertension was 19.2%. Clusters with a high concentration of arterial hypertension were observed in departments along the Peruvian coast such as Tumbes, Piura, Lambayeque, La Libertad, Ancash, and Lima, as well as in the northern regions of the Highlands. Clusters were also found in the regions of Loreto and Madre de Dios in the Peruvian jungle. Conclusions: This study revealed geographic patterns of arterial hypertension in Peru, with a higher concentration of cases along the Peruvian coast and in certain regions of the Highlands and Jungle. These findings highlight the need to develop strategies for the prevention and control of the disease, especially in the areas identified as high-prevalence clusters.

Determinants, inequalities, and spatial patterns of diarrhea in the Peruvian under-five population: findings from nationally representative survey data.

Objective: To determine the associated factors, decompose the socioeconomic inequalities, and analyze the spatial distribution of childhood diarrhea in Peru. Methods: A cross-sectional analytical study was conducted using data from the National Demographic and Family Health Survey 2021. The dependent variable was the presence of diarrhea in the last two weeks. Three types of analysis were performed: (i) to evaluate the associated factors, generalized linear models of the Poisson family with logarithmic link were applied and prevalence ratios with their 95% confidence intervals were reported; (ii) for the analysis of inequalities, a decomposition of the Erreygers concentration index was performed using a generalized linear model; and (ii) a spatial autocorrelation analysis, hot spot analysis and cluster and outlier analysis were performed. Results: A total of 18,871 children under 5 years of age were included. The prevalence of diarrhea in this population was 10.0%. Determinants such as being aged 0-23 months, being male, belonging to the poorest, poorer and rich wealth index, and residing in the Highlands and Jungle increased the probability of presenting diarrhea. In the decomposition analysis, diarrhea had a pro-poor orientation, with the greatest contributors were age 0-23 months, belonging to the poorest and poorer wealth indexes, and residing in the Highlands and Jungle. Spatial analysis showed that the highest concentrations and occurrence of this event were observed in departments of the Highlands and Jungle. Conclusion: Government institutions seeking to reduce the numbers and burden of childhood diarrhea should focus their strategies on promoting hygiene measures and improving access to water and sanitation services, especially in poor populations living in the Peruvian Highlands and Jungle.

Indigenous communities of Peru: Level of accessibility to health facilities.

Objectives: This study aimed to geospatially model the level of geographic accessibility to health facilities among Amazonian Indigenous communities in a region of Peru. Methods: Spatial modeling of the physical accessibility of the Indigenous communities to the nearest health facility was performed through cost-distance analysis. The study area was Loreto, the region with the largest territorial area and number of Indigenous communities in Peru. The time required to reach a health facility was determined by cumulatively adding the time needed to cross the grids on the lowest cost route from the Indigenous communities' locations to the nearest health facility, by considering Amazonian geographical conditions and the main types of transport used. Results: The median time to reach a health facility was 0.96 h (interquartile range: 0.45-2.41). Of the total communities (n = 1043), only 479 (45.93%) communities were within 1 h from the nearest health facility, and 161 (15.44%) were more than 8 h away. The Indigenous communities more than 8 h away from a health establishment were located in the border areas of the department of Loreto. Conclusion: One in two Indigenous communities is more than 1 h from the nearest health facility.