AIMS: To evaluate the prevalence of DF in children residing in Salem and also to find any correlation between DF and other related factors.
MATERIALS AND METHODS: One school from each block of Salem (total 21 blocks) was selected for the study. A single examiner had evaluated untreated caries, lesions, and DF (for permanent anterior teeth and molars) using the Dean's fluorosis index, in all children. Water fluoride level determination at each school was done using the Tamil Nadu Water Fluoridation and Drainage Board field kit. Other factors that may have contributed to DF were assessed using a questionnaire, which was provided to each student. The data obtained were statistically analyzed using the SPSS software version 11.5.
STATISTICAL ANALYSIS: Chi-square test was used for statistical analysis.
RESULTS: DF was present in 56.9% of the children examined. It was mostly seen in 9 years old (72%) and male (59%) children. A positive correlation was found between the occurrence of DF and the duration of residence in a place with high water fluoride content, consumption of borewell water (64%), the parts per million of fluoride in drinking water, consumption of black tea (59%). However, no correlation was found between DF, dental caries, consumption of milk, or consumption of foods cooked in aluminum vessels.
CONCLUSION: There was a correlation between DF and factors such as male gender, bore well water consumption, black tea consumption and the duration of residence in a place with high water fluoride content.
CONTENT: Multiple databases were searched (MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science). Two reviewers independently screened sources, extracted data and assessed study quality. Results were synthesised qualitatively and quantitatively. The main outcome measure was the prevalence of dental fluorosis.
SUMMARY: Six studies of cross-sectional design were included. Two studies were scored as evidence level B (moderate) and the remaining four publications were evidence level C (poor). Meta-analysis indicated fluorosis prevalence was significantly decreased following either a reduction in the concentration of fluoride or cessation of adding fluoride to the water supply (OR:6.68; 95% CI:2.48 to 18.00).
OUTLOOK: The evidence suggests a significant decrease in the prevalence of fluorosis post cessation or reduction in the concentration of fluoride added to the water supply. However, this work demonstrates that when studies are subject to current expectations of methodological and experimental rigour, there is limited evidence with low methodological quality to determine the effect of stopping or reducing the concentration of fluoride in the water supply on dental fluorosis.
METHODS: We included 12,595 invasive BC cases and 12,884 controls for the analysis of rs671 and BC risk, and 2,849 invasive BC cases and 3,680 controls for the analysis of the gene-environment interaction between rs671 and alcohol intake for BC risk. The pooled odds ratios (OR) with 95% confidence intervals (CI) associated with rs671 and its interaction with alcohol intake for BC risk were estimated using logistic regression models.
RESULTS: The Lys/Lys genotype of rs671 was associated with increased BC risk (OR = 1.16, 95% CI 1.03-1.30, p = 0.014). According to tumor characteristics, the Lys/Lys genotype was associated with estrogen receptor (ER)-positive BC (OR = 1.19, 95% CI 1.05-1.36, p = 0.008), progesterone receptor (PR)-positive BC (OR = 1.19, 95% CI 1.03-1.36, p = 0.015), and human epidermal growth factor receptor 2 (HER2)-negative BC (OR = 1.25, 95% CI 1.05-1.48, p = 0.012). No evidence of a gene-environment interaction was observed between rs671 and alcohol intake (p = 0.537).
CONCLUSION: This study suggests that the Lys/Lys genotype confers susceptibility to BC risk among women of Asian ancestry, particularly for ER-positive, PR-positive, and HER2-negative tumor types.
Methods: Cross-sectional data from 62 developing countries were used to run several multivariate linear regressions. R2 was used to compare the powers of MPI with income-poverties (income poverty gaps [IPG] at 1.9 and 3.1 USD) in explaining LE.
Results: Adjusting for controls, both MPI (β =-0.245, P<0.001) and IPG at 3.1 USD (β=-0.135, P=0.044) significantly correlates with LE, but not IPG at 1.9 USD (β=-0.147, P=0.135). MPI explains 12.1% of the variation in LE compared to only 3.2% explained by IPG at 3.1 USD. The effect of MPI on LE is higher on female (β=-0.210, P<0.001) than male (β=-0.177, P<0.001). The relative influence of the deprivation indictors on LE ranks as follows (most to least): Asset ownership, drinking water, cooking fuel, flooring, child school attendance, years of schooling, nutrition, mortality, improved sanitation, and electricity.
Conclusion: Interventions to reduce poverty and improve LE should be guided by MPI, not income poverty indices. Such policies should be female-oriented and prioritized based on the relative influence of the various poverty deprivation indicators on LE.