Evidence map›Paper›PMID 34729273›Full record

ArticleCureus2021

Impact of Sociodemographic Factors on Dental Caries in Children and Availing Fluoride Treatment: A Study Based on National Survey of Children's Health (NSCH) Data 2016-2019.

Thevasha Sathiyakumar, Deepa Vasireddy, Sumona Mondal

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Thevasha SathiyakumarMathematics, Clarkson University, Potsdam, USA.
Deepa VasireddyPediatrics, Pediatric Group of Acadiana, Lafayette, USA.
Sumona MondalMathematics, Clarkson University, Potsdam, USA.
Clarkson University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Dental caries is a global health issue. It is a largely preventable, multifactorial non-communicable disease. Given the gravity of the situation, in 2014 United States Preventive Services Task Force recommended that the primary care physician apply fluoride varnish from the eruption of the first tooth till the child attains five years of age. Using 2016-2019 National Survey of Children's Health (NSCH) cross-sectional representative data, the aim of this study was to determine if the child's age, gender, and race are predictors of the child having decayed teeth or cavities in the past 12 months and if they had availed preventative dental services from the dentist in the past 12 months in the US and if so, did they receive fluoride treatment. Methods The prevalence of dental caries and dental treatment among children under each category of sociodemographic risk factors were estimated using 2016-2019 NSCH's cross-sectional representative data on two survey questions. Then, the statistical significance of the association of the categorical risk factors with the prevalence of dental caries and the association of the categorical risk factors with the prevalence of fluoride dental treatment were tested using two-sample proportion tests and chi-square tests. Further, chi-square residual analysis was employed to better understand the nature of the association and to reveal the degree of contribution to the test statistic from each categorical combination of risk factors. Results Prevalence and associative risk of tooth decay in children was the highest in the 6-11 years age group across all three years under study. The 6-11 years age group had the highest prevalence and association of receiving fluoride treatment across all three years. In our study, the prevalence of dental caries in children by race varied according to the year. In 2016-2017 and 2018-2019, it was the Hispanic population with the highest prevalence of tooth decay. In 2017-2018 the highest prevalence was seen in the Non-Hispanic Black (NHB) population. Across all three years, the Hispanic population had the highest associative risk of tooth decay. The Non-Hispanic White (NHW) population had the highest prevalence and association with receiving fluoride treatment across all three years. Male children were found to have the higher prevalence and associative risk of decayed teeth across all three survey years. Conclusion Dental caries is a worldwide health burden. However, it can be prevented by different precautionary measures. The results of our study revealed that certain sociodemographic factors such as age, gender, and race of the child make certain groups of the child population more at risk for the development of dental caries; most notable findings were that the male children were significantly associated to have decayed teeth and not availing dental fluoride treatment for which limited information is available in the literature. Additionally, the age groups 1-5 and 6-11 were significantly associated with the prevalence of not receiving dental treatment and the prevalence of dental caries, respectively. More active participation of pediatricians in getting trained for the application of fluoride varnish and helping getting their patients established with dental services per recommendations will help streamline preventative dental care.

Indexed as

agedental cavitiesfluoridefluoride varnishgenderhispanic populationnational survey of children's healthracesociodemographic differencesteeth decay

Identifiers

PMID34729273
PMCPMC8555922
OpenAlexW3202454743

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.