Table 2.
Factor loading matrix for major dietary patterns identified among participants aged 40–79 years (n 1326) from Jilin Province, China, enrolled in the International Chronic Disease Cohort, 2010–2011
| Food | Wine pattern | Vegetables pattern | Condiment pattern | Modern pattern | Snack pattern |
|---|---|---|---|---|---|
| White wine | 0·957 | 0·045 | −0·031 | 0·003 | 0·099 |
| Beer | 0·957 | 0·056 | −0·049 | 0·010 | 0·101 |
| Seasoning | 0·522 | 0·236 | 0·120 | 0·069 | −0·134 |
| Cooked vegetables | 0·154 | 0·746 | −0·024 | 0·188 | 0·093 |
| Raw vegetables | 0·130 | 0·735 | 0·007 | 0·040 | 0·110 |
| Pickles | 0·099 | 0·706 | −0·111 | −0·061 | 0·065 |
| Rice | −0·115 | 0·365 | 0·213 | 0·056 | −0·141 |
| Salt | −0·152 | −0·034 | 0·866 | 0·068 | 0·015 |
| Oil | 0·035 | 0·086 | 0·836 | 0·069 | −0·064 |
| Sugar | 0·179 | −0·061 | 0·607 | 0·056 | 0·168 |
| Lean meats | 0·120 | −0·067 | 0·025 | 0·768 | −0·021 |
| Drinks | −0·022 | −0·005 | 0·059 | 0·566 | 0·113 |
| Pasta | 0·010 | 0·181 | 0·009 | 0·489 | 0·221 |
| Eggs | 0·003 | 0·360 | −0·011 | 0·403 | 0·103 |
| Fish | −0·022 | 0·033 | 0·073 | 0·387 | 0·014 |
| Soya products | 0·194 | 0·348 | −0·294 | 0·362 | −0·048 |
| Milk | 0·095 | −0·012 | −0·045 | 0·141 | 0·683 |
| Biscuits | −0·089 | −0·002 | 0·062 | 0·053 | 0·682 |
| Fruits | 0·081 | 0·329 | 0·109 | 0·130 | 0·538 |
In considering the number of factors to retain, we evaluated eigenvalues (>1), the scree plot and the interpretability of the factors to determine which set of factors could most meaningfully describe distinct food patterns. Items were retained in a factor if they had an absolute correlation of ≥0·30 with that factor (indicated in bold font).