| Literature DB >> 35268061 |
Yuan-Yuei Chen1,2, Ying-Jen Chen3.
Abstract
BACKGROUND: Micronutrients are considered to have an important role in metabolic process. The relationships between micronutrients and diabetic complication, such as retinopathy, are rarely discussed. The main purpose of the current study was to investigate the relationship between dietary micronutrients and diabetic retinopathy in an adult population.Entities:
Keywords: dietary calcium; micronutrients; retinopathy
Mesh:
Substances:
Year: 2022 PMID: 35268061 PMCID: PMC8912727 DOI: 10.3390/nu14051086
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1Flow chart of the study.
Characteristics of Study Population.
| Variables | Diabetic Retinopathy | No Diabetic Retinopathy | |
|---|---|---|---|
| Continuous variables, mean (SD) | |||
| Age (years) | 62.430 (11.790) | 58.961 (12.421) | <0.001 |
| Serum glucose (mg/dL) | 135.830 (71.782) | 102.671 (31.910) | <0.001 |
| Alanine aminotransferase (U/L) | 26.191 (34.730) | 25.530 (16.942) | 0.428 |
| Hemoglobin (g/dL) | 14.071 (1.682) | 14.290 (1.522) | <0.001 |
| Dietary calcium (g) | 0.796 (0.482) | 0.866 (0.531) | <0.001 |
| Dietary phosphorus (g) | 1.164 (0.548) | 1.259 (0.623) | <0.001 |
| Dietary magnesium (g) | 0.266 (0.139) | 0.287 (0.142) | <0.001 |
| Dietary zinc (g) | 0.011 (0.006) | 0.012 (0.011) | 0.027 |
| Dietary copper (g) | 0.001 (0.001) | 0.001 (0.001) | 0.030 |
| Dietary sodium (g) | 3.003 (1.552) | 3.197 (1.711) | 0.005 |
| Dietary potassium (g) | 2.437 (1.135) | 2.628 (1.224) | <0.001 |
| Dietary selenium (mg) | 0.098 (0.051) | 0.103 (0.058) | 0.038 |
| Dietary energy (kcal) | 1848.71 (839.15) | 2010.08 (922.90) | <0.001 |
| Dietary carbohydrate (gm) | 221.47 (111.48) | 242.64 (113.72) | <0.001 |
| Dietary sugar (gm) | 96.63 (74.96) | 110.60 (70.55) | <0.001 |
| Category variables, (%) | |||
| Gender (male) | 389 (55.9) | 2257 (50.0) | 0.004 |
| Non-Hispanic white | 298 (42.8) | 2560 (56.7) | 0.400 |
| Cigarette smoking status | 120 (17.2) | 817 (18.1) | 0.603 |
Figure 2Association between dietary micronutrients and diabetic retinopathy.
Association between quartiles of calcium and potassium and the presence of diabetic retinopathy.
| Model 1 | Model 2 | Model 3 | |||||
|---|---|---|---|---|---|---|---|
|
| |||||||
| Calcium | Q1 vs. Q4 | 0.802 (0.594–1.084) | 0.152 | 0.790 (0.584–1.070) | 0.128 | 0.814 (0.592–1.120) | 0.206 |
| Q2 vs. Q4 | 0.618 (0.450–0.850) | 0.003 | 0.606 (0.440–0.835) | 0.002 | 0.622 (0.444–0.871) | 0.006 | |
| Q3 vs. Q4 | 0.631 (0.459–0.869) | 0.005 | 0.628 (0.454–0.870) | 0.005 | 0.664 (0.472–0.933) | 0.018 | |
| Potassium | Q1 vs. Q4 | 0.899 (0.657–1.229) | 0.504 | 0.846 (0.616–1.161) | 0.300 | 0.842 (0.604–1.173) | 0.309 |
| Q2 vs. Q4 | 0.816 (0.593–1.123) | 0.212 | 0.766 (0.553–1.059) | 0.107 | 0.778 (0.555–1.092) | 0.147 | |
| Q3 vs. Q4 | 0.714 (0.518–0.983) | 0.039 | 0.663 (0.476–0.924) | 0.015 | 0.700 (0.495–0.989) | 0.043 | |
Adjusted variables: Model 1: unadjusted; Model 2: age, gender, race/ethnicity; Model 3: age, gender, race/ethnicity, serum glucose, ALT, hemoglobin, cigarette smoking status.
Figure 3Areas under receiver operating characteristic curve for calcium and potassium.
Association between cutoff points of calcium and potassium, and the presence of diabetic retinopathy.
| Cutoff Points | Model 1 | Model 2 | Model 3 | |||
|---|---|---|---|---|---|---|
|
| ||||||
| Calcium | 0.683 (0.540–0.864) | <0.001 | 0.677 (0.534–0.858) | <0.001 | 0.701 (0.546–0.900) | 0.005 |
| Potassium | 0.754 (0.601–0.946) | 0.015 | 0.724 (0.574–0.914) | 0.007 | 0.761 (0.596–0.972) | 0.029 |
Adjusted covariates: Model 1: unadjusted; Model 2: age, gender, race/ethnicity; Model 3: age, gender, race/ethnicity, serum glucose, ALT, hemoglobin, cigarette smoking status.