Table 3.
Regression analysis of correlation of infection rate of COVID-19 with dietary factors in the world
| Dietary factors (n=158) | Dependent variable: Crude infection rate of COVID-19 in the world | ||||
|---|---|---|---|---|---|
| Standardized Coefficients | t | P-Value | 95.0% Confidence Interval for B | ||
| Beta | Lower Bound | Upper Bound | |||
| Fruits (g/d) | 0.237 | 2.811 | 0.006 | 0.005 | 0.027 |
| Non-starchy vegetables (g/d) | −0.036 | −0.472 | 0.638 | −0.011 | 0.007 |
| Beans and legumes (g/d) | −0.145 | −2.097 | 0.038 | −0.044 | −0.001 |
| Nuts and seeds (g/d) | 0.032 | 0.464 | 0.644 | −0.090 | 0.146 |
| Unprocessed red meats (g/d) | 0.152 | 1.761 | 0.080 | −0.002 | 0.033 |
| Sugar-sweetened beverages (g/d) | −0.067 | −0.878 | 0.381 | −0.004 | 0.001 |
| Fruit juices (g/d) | −0.007 | −0.073 | 0.942 | −0.025 | 0.023 |
| Total protein (g/d) | −0.009 | −0.129 | 0.898 | −0.031 | 0.028 |
| Calcium (mg/d) | 0.286 | 2.746 | 0.007 | 0.001 | 0.006 |
| Potassium (mg/d) | 0.109 | 1.429 | 0.155 | 0.000 | 0.001 |
| Total milk (g/d) | 0.073 | 0.757 | 0.450 | −0.006 | 0.013 |
Linear regression was performed for statistical analysis.