Table 2. Baseline characteristics of women in different fruit consumption quartiles.
| Quartiles of fruit consumption | |||||
|---|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | pvaluea | |
| Age (years) | 25.73 ± 3.11 | 26.09 ± 3.12 | 26.24 ± 3.16 | 26.73 ± 3.3 | 0.03 |
| Gestational weight gain (kg) | 14.11 ± 2.77 | 14.25 ± 2.22 | 14.34 ± 2.65 | 14.45 ± 2.67 | 0.611 |
| Dietary factors | |||||
| Energy (kcal/d) | 1603 (1365, 1958) | 1671 (1457, 2019) | 1817 (1600, 2246) | 2579 (2116, 3338) | <0.001 |
| Carbohydrate (g/d) | 216 (178, 268) | 227 (197, 284) | 259 (219, 316) | 389 (303, 493) | <0.001 |
| Protein (g/d) | 58 (44, 72) | 59 (48, 71) | 67 (51.1, 86) | 87 (71, 126) | <0.001 |
| Fat (g/d) | 60 (50, 71) | 58 (51, 69) | 66 (57, 78) | 86 (65, 104) | <0.001 |
| Fruit (g/d) | 182 (133, 206) | 285 (266, 316) | 425 (383, 471) | 710 (601, 870) | <0.001 |
| Grain (g/d) | 272 (223, 331) | 272 (232, 331) | 290 (248, 364) | 418 (306, 525) | <0.001 |
| Vegetables (g/d) | 220 (162, 300) | 250 (180, 324) | 228 (170, 318) | 326 (205, 555) | <0.001 |
| Meat (g/d) | 107 (68, 163) | 106 (75, 144) | 126 (80, 190) | 180 (120, 279) | <0.001 |
| Fish (g/d) | 33 (0, 80) | 33 (0, 79) | 36 (0, 100) | 53 (0, 113) | 0.005 |
| Education | 0.029 | ||||
| Elementary/none | 0 (0.0) | 1 (0.5) | 1 (0.5) | 0 (0) | |
| Junior high school | 30 (15.5) | 20 (10.4) | 23 (11.9) | 12 (6.2) | |
| High school | 53 (27.3) | 44 (22.9) | 50 (25.9) | 43 (22.3) | |
| Junior college | 45 (23.2) | 69 (35.9) | 61 (31.6) | 55 (28.5) | |
| College | 66 (34.0) | 58 (30.2) | 58 (30.1) | 83 (43.0) | |
| Occupation | 0.789 | ||||
| White-collar worker | 63 (32.5) | 66 (34.4) | 64 (33.2) | 60 (31.1) | |
| Blue-collar worker | 68 (35.1) | 68 (35.4) | 67 (34.7) | 72 (37.3) | |
| Farmer/other | 8 (4.1) | 15 (7.8) | 10 (5.2) | 15 (7.8) | |
| Housewife/retired | 55 (28.4) | 43 (22.4) | 52 (26.9) | 46 (23.8) | |
| Income level (yuan/month) | 0.145 | ||||
| <1000 | 2 (1.0) | 2 (1.0) | 1 (0.5) | 2 (1.0) | |
| 1000- | 28 (14.4) | 21 (10.9) | 17 (8.8) | 17 (8.8) | |
| 3001- | 81 (41.8) | 65 (33.9) | 62 (32.1) | 57 (29.5) | |
| 5001- | 62 (32.0) | 78 (40.6) | 84 (43.5) | 81 (42.0) | |
| 10, 001- | 21 (10.8) | 26 (13.5) | 29 (15.0) | 36 (18.7) | |
| Pre-pregnancy BMI | 0.246 | ||||
| <18.5 | 78 (40.2) | 60 (31.3) | 53 (27.5) | 57 (29.5) | |
| 18.5- | 107 (55.2) | 125 (65.1) | 127 (65.8) | 124 (64.2) | |
| 24- | 7 (3.6) | 7 (3.6) | 11 (5.7) | 10 (5.2) | |
| 28- | 2 (1.0) | 0 (0.0) | 2 (1.0) | 2 (1.0) | |
| Exercise (yes) | 43 (22.2) | 49 (25.5) | 45 (23.3) | 54 (28.0) | 0.562 |
| Smoking (yes) | 7 (3.6) | 4 (2.1) | 6 (3.1) | 4 (2.1) | 0.732 |
| Alcohol drinking (yes) | 5 (2.6) | 5 (2.6) | 6 (3.1) | 4 (2.1) | 0.938 |
| Family history of diabetes (yes) | 23 (11.8) | 16 (8.3) | 20 (10.4) | 28 (14.5) | 0.203 |
Continuous variables were shown as mean ± SD or medians (P25, P75), and categorical variables were shown as n (percentages). aChi-square test or Fisher exact test for categorical variables, and analysis of variance or the Kruskal-Wallis test for continuous variables.