Gender Differences in Dietary Patterns and Their Association with the Prevalence of Metabolic Syndrome among Chinese: A Cross-Sectional Study
Abstract
:1. Introduction
2. Methods
2.1. Study Population
2.2. Definition of MetS
2.3. Blood Sample, Anthropometrics Variables and Blood Pressure
2.4. Assessment of General Information and Covariates
2.5. Assessment of Dietary Intake
2.6. Identification of Dietary Patterns
2.7. Statistic Methods
3. Results
3.1. Dietary Patterns
3.2. Dietary Patterns and Distributions of Sample Characteristics
3.3. Dietary Patterns and Metabolic Syndrome
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
FFQ | Food frequency questionnaire |
MetS | Metabolic syndrome |
IDF | The International Diabetes Federation |
EFA | Exploratory factor analysis |
BMI | Body mass index |
IPAQ | The international physical activity questionnaire |
CFI | Comparative fit index |
RMSEA | Root mean squared error of approximation |
References
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Demographic Factors | MetS (n (%)) | OR (95% CI) | p | |
---|---|---|---|---|
Yes (1232) | No (2219) | |||
Age group, n (%) | 1.54 (1.40-1.68) | <0.0001 | ||
≥35 years | 215 (17.45) | 654 (29.47) | ||
35–45 years | 426 (34.58) | 810 (36.50) | ||
≥45 years | 591 (47.97) | 755 (34.02) | ||
Marital status, n (%) | <0.0001 | |||
Single | 25 (2.03) | 134 (6.04) | 1.00 | |
Married | 1185 (96.19) | 2052 (92.47) | 3.10 (2.01–4.77) | <0.0001 |
Divorced | 33 (1.79) | 22 (1.49) | 3.57 (1.80–7.11) | 0.0003 |
Educational level, n (%) | 1.23 (1.10–1.38) | 0.0004 | ||
Bachelor degree or above | 125 (10.15) | 291 (13.11) | ||
Junior college and senior high school | 737 (59.82) | 1366 (61.56) | ||
Junior high school or below | 370 (30.03) | 562 (25.33) | ||
Work type, n (%) | 1.12 (1.01–1.24) | 0.032 | ||
Heavy physical | 263 (21.35) | 564 (25.42) | ||
Light physical | 679 (55.11) | 1061 (47.81) | ||
Mental labor | 290 (23.54) | 594 (26.77) | ||
Current smoking, n (%) | 1.19 (1.03–1.37) | 0.017 | ||
No | 487 (39.53) | 970 (43.71) | ||
Yes | 745 (60.47) | 1249 (56.29) | ||
Alcohol consumption, n (%) | 1.46 (1.27–1.69) | <0.0001 | ||
No | 653 (53.00) | 1382 (62.28) | ||
Yes | 579 (47.00) | 837 (37.72) | ||
Monthly income (RMB), n (%) | 0.93 (0.89–1.02) | 0.127 | ||
≤4000 | 336 (27.27) | 561 (25.28) | ||
4000–6000 | 525 (42.61) | 943 (42.50) | ||
≥6000 | 371 (30.11) | 715 (32.22) | ||
Physical activity level, n (%) | 0.82 (0.72–0.94) | 0.003 | ||
Inactive | 32 (2.60) | 35 (1.58) | ||
Minimally Active | 404 (32.79) | 654 (29.47) | ||
Health-enhancing physical activity | 796 (64.61) | 1530 (68.95) | ||
Family history, n (%) | 1.37 (1.19–1.57) | <0.0001 | ||
No | 661 (53.65) | 1359 (61.24) | ||
Yes | 571 (46.35) | 860 (38.76) | ||
BMI (kg/m2), n (%) | 2.54 (2.27–2.84) | <0.0001 | ||
Underweight | 9 (0.73) | 60 (2.70) | ||
Normal range | 422 (34.25) | 1350 (60.84) | ||
Overweight | 639 (51.87) | 714 (32.18) | ||
Obese | 162 (13.15) | 95 (4.28) |
Model | χ2 | df | CFI | RMSEA | ∆CFI | ∆RMSEA |
---|---|---|---|---|---|---|
Model 1 | 1775.487 | 328 | 0.803 | 0.053 | - | - |
Model 2 | 1800.360 | 345 | 0.802 | 0.051 | −0.001 | −0.002 |
Model 3 | 2955.232 | 394 | 0.651 | 0.065 | −0.152 | 0.012 |
Food Groups | Factor 1: Vegetables, Potatoes and Wheat Flour | Factor 2: Meat and Fried Dough | Factor 3: Fruits, Dairy Products, Rice and Eggs |
---|---|---|---|
Salted and preserved vegetables | 0.533 | - | - |
Pickled vegetables | 0.507 | - | - |
Potatoes | 0.478 | - | - |
Wheat Flour | 0.474 | - | - |
Beans and bean products | 0.463 | - | - |
Vermicelli | 0.460 | - | - |
Pastry | 0.398 | - | - |
Vegetables | 0.397 | - | 0.319 |
Red meat | - | 0.671 | - |
Viscera | - | 0.580 | - |
Poultry | - | 0.575 | - |
Fish and shrimp | - | 0.556 | - |
Pork | - | 0.449 | - |
Fried dough | - | 0.355 | - |
Nuts | - | - | - |
Fruits | - | - | 0.531 |
Dairy products | - | - | 0.510 |
Cereal | - | - | 0.501 |
Rice | - | - | 0.354 |
Eggs and egg dishes | - | - | 0.318 |
Eigen value | 2.555 | 1.751 | 1.363 |
Percentage of variances (%) explained | 12.77 | 8.76 | 6.82 |
Food Groups | Factor 1: Meat and Fried Dough | Factor 2: Fruits, Vegetables, Nuts, Dairy Products | Factor 3: Salt, Vermicelli and Wheat Flour | Factor 4: Beans, Cereal, Potatoes, and Pastry |
---|---|---|---|---|
Viscera | 0.590 | - | 0.343 | - |
Poultry | 0.568 | 0.315 | - | - |
Red meat | 0.547 | - | - | - |
Fried dough | 0.521 | - | 0.344 | - |
Fish and shrimp | 0.485 | 0.363 | - | - |
Rice | 0.411 | - | - | - |
Pork | 0.328 | - | - | - |
Dairy products | - | 0.492 | - | - |
Fruits | - | 0.590 | - | - |
Vegetables | - | 0.582 | - | - |
Nuts | - | 0.579 | - | - |
Wheat Flour | - | - | 0.400 | - |
Pickled vegetables | - | - | 0.705 | - |
Salted and preserved vegetables | - | - | 0.672 | - |
Vermicelli | - | - | 0.506 | - |
Potatoes | - | - | - | 0.583 |
Beans and bean products | - | 0.376 | - | 0.557 |
Cereal | - | - | - | 0.547 |
Pastry | - | - | - | 0.506 |
Eggs and egg dishes | - | - | - | 0.316 |
Eigen value | 2.660 | 2.044 | 1.614 | 1.233 |
Percentage of variances (%) explained | 13.30 | 10.22 | 8.07 | 6.17 |
Factors | Clusters | ||||
---|---|---|---|---|---|
Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | p | |
Men | |||||
Factor 1 | −0.48 | −1.08 | 0.66 | 0.46 | <0.0001 |
Factor 2 | 0.36 | −0.31 | −0.92 | 0.78 | <0.0001 |
Factor 3 | −1.36 | 0.68 | −0.11 | 0.35 | <0.0001 |
Women | |||||
Factor 1 | −0.89 | 0.13 | 0.83 | 0.75 | <0.0001 |
Factor 2 | −0.30 | 0.49 | 0.27 | −2.23 | <0.0001 |
Factor 3 | 0.38 | −0.94 | 0.87 | −0.82 | <0.0001 |
Factor 4 | 0.05 | −0.10 | 0.05 | 0.07 | 0.484 |
Demographic Factors | “Animal and Fried Food” Dietary Pattern | “Fruit and Dairy” Dietary Pattern | “Traditional” Dietary Pattern | “Balanced” Dietary Pattern | χ2 | p |
---|---|---|---|---|---|---|
n (%) | 519 (17.73) | 665 (22.71) | 788 (26.91) | 956 (32.65) | ||
Age group, n (%) | 125.488 | <0.0001 | ||||
≥35 years | 145 (27.94) | 230 (34.59) | 114 (14.47) | 226 (23.64) | ||
35–45 years | 166 (31.98) | 229 (34.44) | 257 (32.61) | 390 (40.79) | ||
≥45 years | 208 (40.08) | 206 (30.98) | 417 (52.92) | 340 (35.56) | ||
Educational level, n (%) | 15.156 | 0.019 | ||||
Bachelor degree or above | 56 (10.79) | 100 (15.04) | 48 (6.09) | 113 (11.82) | ||
Junior college and senior high school | 297 (57.23) | 444 (66.77) | 427 (54.19) | 617 (64.54) | ||
Junior high school or below | 166 (31.98) | 121 (18.20) | 313 (39.72) | 226 (23.64) | ||
Work type, n (%) | 37.557 | <0.0001 | ||||
Heavy physical | 148 (28.52) | 174 (26.17) | 249 (31.60) | 242 (25.31) | ||
Light physical | 276 (53.18) | 324 (48.72) | 427 (54.19) | 487 (50.94) | ||
Mental labor | 95 (18.30) | 167 (25.11) | 112 (14.21) | 227 (23.74) | ||
Alcohol consumption, n (%) | 79.194 | <0.0001 | ||||
No | 210 (40.46) | 379 (56.99) | 493 (62.56) | 449 (46.97) | ||
Yes | 309 (59.54) | 286 (43.01) | 295 (37.44) | 507 (53.03) | ||
Monthly income (RMB), n (%) | 33.699 | <0.0001 | ||||
≤4000 | 140 (26.97) | 158 (23.76) | 206 (26.14) | 190 (19.87) | ||
4000–6000 | 224 (43.16) | 267 (40.15) | 385 (48.86) | 460 (48.12) | ||
≥6000 | 155 (29.87) | 240 (36.09) | 196 (25.00) | 306 (32.01) | ||
BMI (kg/m2), n (%) | 13.573 | 0.138 | ||||
Underweight | 8 (1.54) | 12 (1.80) | 17 (2.16) | 12 (1.26) | ||
Normal range | 252 (48.55) | 328 (49.32) | 405 (51.40) | 459 (48.01) | ||
Overweight | 205 (39.50) | 274 (41.20) | 321 (40.74) | 401 (41.95) | ||
Obese | 54 (10.40) | 51 (7.67) | 45 (5.71) | 84 (8.79) |
Demographic Factors | “Animal and Fried Food” Dietary Pattern | “High-Salt and Energy” Dietary Pattern | “Vegetable and Fruit” Dietary Pattern | “Balanced” Dietary Pattern | χ2 | p |
---|---|---|---|---|---|---|
n (%) | 31 (5.93) | 180 (34.42) | 174 (33.27) | 138 (26.39) | ||
Age group, n (%) | 24.548 | 0.0004 | ||||
≥35 years | 11 (35.48) | 35 (19.44) | 57 (32.76) | 51 (36.96) | ||
35–45 years | 11 (35.48) | 63 (35.00) | 74 (42.53) | 46 (33.33) | ||
≥45 years | 9 (29.03) | 82 (45.56) | 43 (24.71) | 41 (29.71) | ||
Educational level, n (%) | 34.278 | <0.0001 | ||||
Bachelor degree or above | 6 (19.35) | 14 (14.14) | 43 (24.71) | 36 (26.09) | ||
Junior college and senior high school | 14 (45.16) | 116 (64.44) | 107 (61.49) | 81 (58.70) | ||
Junior high school or below | 11 (35.48) | 50 (27.78) | 24 (13.79) | 21 (15.22) | ||
Work type, n (%) | - | 0.082 * | ||||
Heavy physical | 1 (3.23) | 7 (3.89) | 2 (1.15) | 4 (2.90) | ||
Light physical | 17 (54.84) | 88 (48.89) | 67 (38.51) | 54 (39.13) | ||
Mental labor | 13 (41.94) | 85 (47.22) | 105 (60.34) | 80 (57.97) | ||
Monthly income (RMB), n (%) | 16.771 | 0.010 | ||||
≤4000 | 15 (48.39) | 80 (44.44) | 55 (31.61) | 53 (38.41) | ||
4000–6000 | 7 (22.58) | 53 (29.44) | 39 (22.41) | 33 (23.91) | ||
≥6000 | 9 (29.03) | 47 (26.11) | 80 (45.98) | 52 (37.68) | ||
Alcohol consumption, n (%) | - | 0.450 * | ||||
No | 31 (100.00) | 174 (96.67) | 169 (97.13) | 130 (94.20) | ||
Yes | 0 (0.00) | 6 (3.33) | 5 (2.87) | 8 (5.80) | ||
BMI (kg/m2), n (%) | 7.352 | 0.601 | ||||
Underweight | 1 (3.23) | 6 (3.33) | 7 (4.02) | 6 (4.35) | ||
Normal range | 19 (61.29) | 106 (58.89) | 119 (68.39) | 84 (60.87) | ||
Overweight | 8 (25.81) | 58 (32.22) | 43 (24.71) | 43 (31.16) | ||
Obese | 3 (9.68) | 10 (5.56) | 5 (2.87) | 5 (3.62) |
Prevalence of Metabolic Syndrome | Men | Women | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
“Balanced” Dietary Pattern | “Fruit and Dairy” Dietary Pattern | “Traditional” Dietary Pattern | “Animal and Fried Food” Dietary Pattern | p | “Balanced” Dietary Pattern | “Vegetable and Fruit” Dietary Pattern | “High-Salt and Energy” Dietary Pattern | “Animal and Fried Food” Dietary Pattern | p | |
Case, n (%) | 350 (36.61) | 258 (38.80) | 277 (35.15) | 218 (42.00) | 23 (16.67) | 35 (20.11) | 64 (35.56) | 7 (22.58) | ||
Crude OR | 1.0 | 1.10 (0.90, 1.35) p = 0.371 | 0.94 (0.77, 1.14) p = 0.528 | 1.25 (1.00, 1.56) p = 0.042 | 0.069 | 1.0 | 1.26 (0.70, 2.25) p = 0.437 | 2.76 (1.61, 4.74) p = 0.0002 | 1.46 (0.56, 3.78) p = 0.438 | 0.0005 |
Age adjusted | 1.0 | 1.17 (0.95, 1.44) p = 0.141 | 0.85 (0.69, 1.03) p = 0.099 | 1.26 (1.01, 1.57) p = 0.042 | 0.003 | 1.0 | 1.31 (0.72, 2.38) p = 0.380 | 2.29 (1.31, 4.02) p = 0.004 | 1.49 (0.56, 3.99) p = 0.428 | 0.019 |
Multivariable adjusted 2 | 1.0 | 1.28 (1.03, 1.59) p = 0.028 | 0.98 (0.80, 1.22) p = 0.882 | 1.27 (1.01, 1.60) p = 0.043 | 0.029 | 1.0 | 1.45 (0.77, 2.73) p = 0.250 | 2.27 (1.24, 4.14) p = 0.008 | 1.18 (0.40, 3.52) p = 0.763 | 0.047 |
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
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Xu, S.-H.; Qiao, N.; Huang, J.-J.; Sun, C.-M.; Cui, Y.; Tian, S.-S.; Wang, C.; Liu, X.-M.; Zhang, H.-X.; Wang, H.; et al. Gender Differences in Dietary Patterns and Their Association with the Prevalence of Metabolic Syndrome among Chinese: A Cross-Sectional Study. Nutrients 2016, 8, 180. https://doi.org/10.3390/nu8040180
Xu S-H, Qiao N, Huang J-J, Sun C-M, Cui Y, Tian S-S, Wang C, Liu X-M, Zhang H-X, Wang H, et al. Gender Differences in Dietary Patterns and Their Association with the Prevalence of Metabolic Syndrome among Chinese: A Cross-Sectional Study. Nutrients. 2016; 8(4):180. https://doi.org/10.3390/nu8040180
Chicago/Turabian StyleXu, Shu-Hong, Nan Qiao, Jian-Jun Huang, Chen-Ming Sun, Yan Cui, Shuang-Shuang Tian, Cong Wang, Xiao-Meng Liu, Hai-Xia Zhang, Hui Wang, and et al. 2016. "Gender Differences in Dietary Patterns and Their Association with the Prevalence of Metabolic Syndrome among Chinese: A Cross-Sectional Study" Nutrients 8, no. 4: 180. https://doi.org/10.3390/nu8040180