ArticleTranslational vision science & technology2024
Macular Pigment Assessment in Indian Population Using Degree of Polarization Threshold: Impact of Diet on Macular Pigment Density.
Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed, 1 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
Purpose: To determine macular pigment (MP) density scores in healthy Indians and examine correlations with demographic and lifestyle variables. Methods: We observed 484 Indians without an ocular pathology. Body mass index (BMI) and self-reported lifestyle factors (sunglasses usage, physical activity, and smoking) were noted. MP density was assessed as the threshold of perception of the shadow of their macular pigments on their retina using a new MP assessment tool (MP-eye). Lutein and zeaxanthin intake was assessed using a prevalidated questionnaire regionally designed for the Indian diet. Clusters of participants were created for statistical analysis based on MP-eye scores secondarily to detect any relevant effects in very low, low, medium, and high ranges of MPs. Results: Data analyzed included 235 males and 249 females with mean age of 36.1 ± 12.9 years (range, 14-72). The median MP-eye score was 6 (range, 0-10, with 10 being high). Most were non-smokers (413, 85.3%) and did not use sunglasses (438, 90.5%), and 314 (64.9%) had low physical activity. Diabetes was present in 62 participants (12.8%) and hypertension in 53 (10.9%). Advancing age (r = -0.209; P < 0.000) and BMI (r = -0.094; P = 0.038) had weak negative correlation with MP-eye scores. Hypertension was less prevalent (7/88) in the cluster with the highest median MP-eye score (P = 0.033). Dietary intake of MPs and other lifestyle factors did not correlate significantly with MP-eye score overall or when analyzed in clusters. Conclusions: MP-eye scores of an Indian population were normally distributed. Higher age, high BMI, and presence of hypertension were weakly associated with lower MP-eye scores. The impact of diet on MPs requires further evaluation. Translational Relevance: This normative regional database enables risk stratification of macular degeneration.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.