Association between Dietary Patterns and Frailty Prevalence in Shanghai Suburban Elders: A Cross-Sectional Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Questionnaire and Anthropometric Measurements
2.3. Frailty Assessment
2.4. Dietary Assessment
2.5. A Priori Dietary Pattern Scores
2.6. A Posteriori Dietary Pattern Scores
2.7. Statistical Analysis
3. Results
3.1. General Information of the Participants
3.2. Dietary Pattern Scores of the Participants
Characteristics a | Total | Robustness | Pre-Frailty | Frailty | p Value b |
---|---|---|---|---|---|
Age (Years) | 68.85 (2.64) | 68.57 (2.60) | 69.14 (2.66) | 68.87 (2.66) | 0.011 |
BMI (kg/m2) | 25.35 (3.29) | 25.04 (2.98) | 25.63 (3.53) | 25.80 (3.75) | 0.041 |
Energy intake (kcal/day) | 1408.39 (579.45) | 1438.06 (586.89) | 1388.88 (579.01) | 1276.43 (467.06) | 0.227 |
Total, N (%) | 780 (100) | 378 (48.46) | 372 (47.69) | 30 (3.85) | |
Sex | |||||
Male | 335 (42.95) | 191 (57.01) | 136 (40.60) | 8 (2.39) | <0.001 |
Female | 445 (57.05) | 187 (42.02) | 236 (53.03) | 22 (4.94) | |
Age | |||||
65–69 years | 472 (60.51) | 247 (52.33) | 208 (44.07) | 17 (3.60) | 0.010 |
70–74 years | 308 (39.49) | 131 (42.53) | 164 (53.25) | 13 (4.22) | |
Education Level | |||||
Primary school or below | 613 (78.59) | 279 (45.51) | 307 (50.08) | 27 (4.40) | 0.004 |
Secondary school or above | 167 (21.41) | 99(59.28) | 65 (38.92) | 3 (1.80) | |
Marital status | |||||
Married | 672 (86.15) | 339 (50.45) | 307 (45.68) | 26 (3.87) | 0.018 |
Others c | 108 (13.85) | 39 (36.11) | 65 (60.19) | 4 (3.70) | |
Annual per capita household income | |||||
<¥10,000 | 58(7.44) | 19 (32.76) | 35 (60.34) | 4 (6.90) | <0.001 |
¥10,000~30,000 | 495 (63.46) | 223 (45.05) | 252 (50.91) | 20 (4.04) | |
≥¥30,000 | 227 (29.10) | 136 (59.91) | 85 (37.44) | 6 (2.64) | |
Behavioral variables | |||||
Current smoker d | 111 (14.23) | 63 (56.76) | 42 (37.84) | 6 (5.41) | 0.006 |
Not current smoker | 669 (85.77) | 315 (47.09) | 330 (42.31) | 24 (0.04) | |
Current alcohol use e | 50 (6.41) | 17 (34.00) | 29 (58.00) | 4 (8.00) | <0.001 |
Not current alcohol user | 730 (93.59) | 361 (49.45) | 343 (46.99) | 26 (3.56) | |
Doing housework everyday | 672 (86.15) | 329 (48.96) | 324 (48.21) | 19 (2.83) | 0.001 |
Not doing housework everyday | 108 (13.85) | 49 (45.37) | 48 (44.44) | 11 (10.19) | |
Being sedentary > 6 h/day | 94 (12.05) | 45 (47.87) | 43 (45.74) | 6 (6.38) | 0.390 |
Not being sedentary > 6 h/day | 686 (87.95) | 333 (48.54) | 329 (47.96) | 24 (3.50) | |
Self-reported diseases | |||||
Hypertension | 405 (51.92) | 198 (48.89) | 189 (46.67) | 18 (4.44) | 0.606 |
Without hypertension | 375 (48.08) | 180 (48.00) | 183 (48.80) | 12 (3.20) | |
Diabetes | 129 (16.54) | 52 (40.31) | 62 (48.06) | 15 (11.63) | <0.001 |
Without diabetes | 651 (93.46) | 326 (50.08) | 310 (47.62) | 15 (2.30) | |
Chronic lung disease | 50 (6.41) | 20 (40.00) | 25 (50.00) | 5 (10.00) | 0.067 |
Without chronic lung disease | 730 (93.59) | 358 (49.04) | 347 (47.53) | 25 (3.42) | |
Myocardial infarction | 17 (2.18) | 6 (35.29) | 10 (58.82) | 1 (5.88) | 0.465 |
Without myocardial infarction | 763 (97.92) | 372 (48.75) | 362 (47.44) | 29 (3.80) | |
Angina | 33 (4.23) | 14 (42.42) | 17 (51.52) | 2 (6.06) | 0.669 |
Without angina | 747 (95.77) | 364 (48.73) | 355 (47.52) | 28 (3.75) | |
Asthma | 26 (3.33) | 8 (30.77) | 13 (50.00) | 5 (19.23) | <0.001 |
Without asthma | 754 (96.67) | 370 (49.07) | 359 (47.61) | 25 (3.32) | |
Arthritis | 286 (36.67) | 132 (46.15) | 139 (48.60) | 15 (5.24) | 0.238 |
Without arthritis | 494 (63.33) | 246 (49.80) | 233 (47.17) | 15 (3.04) | |
Stroke | 102 (13.08) | 37 (36.27) | 56 (54.90) | 9 (8.82) | 0.002 |
Without stroke | 678 (86.92) | 341 (50.29) | 316 (46.61) | 21 (3.10) | |
Kidney disease | 164 (21.03) | 80 (48.78) | 78 (47.56) | 6 (3.66) | 0.988 |
Without kidney disease | 616 (79.97) | 298 (48.38) | 294 (47.73) | 24 (3.90) | |
Cancer | 27 (3.46) | 8 (29.63) | 17 (62.96) | 2 (7.41) | 0.114 |
Without cancer | 753 (96.54) | 370 (49.14) | 355 (47.14) | 28 (3.72) |
3.3. Associations between Each Dietary Pattern Score and Frailty Prevalence
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
Abbreviations
DGC | Dietary Guidelines for Chinese; |
SSAC | Shanghai Suburban Adult Cohort; |
FFQ | food frequency questionnaire; |
BMI | body mass index; |
Cm | Centimeters; |
Kg | Kilograms; |
CES-D | Centers for Epidemiologic Studies Depression Scale; |
CHEI | Chinese Healthy Eating Index; |
DASH | Dietary Approaches to Stop Hypertension; |
MD | Mediterranean Diet; |
OR | odds ratio; |
CI | 95% confidence interval. |
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Food Items | Dietary Patterns b | ||
---|---|---|---|
Factor 1: “Protein-Rich” | Factor 2: “Vegetables” | Factor 3: “Sugar, Oil, and Condiments” | |
Soybean and soybean products | 0.66 | 0.26 | 0.10 |
Red meat | 0.58 | 0.04 | −0.04 |
Poultry | 0.39 | 0.17 | −0.08 |
Freshwater fish | 0.63 | 0.15 | 0.04 |
Ocean fish | 0.44 | 0.40 | −0.06 |
Shellfish, Shrimp, and Crab | 0.74 | 0.05 | −0.07 |
Dark vegetables | 0.01 | 0.88 | 0.02 |
Light colored vegetables | 0.38 | 0.74 | 0.04 |
Added sugars | −0.03 | 0.02 | 0.58 |
Cooking oil | 0.06 | −0.01 | 0.75 |
Condiments | −0.05 | 0.05 | 0.79 |
Fruits | 0.19 | −0.02 | 0.17 |
Juice | 0.00 | −0.02 | −0.02 |
Eggs | 0.04 | 0.17 | −0.03 |
Dairy and dairy products | 0.02 | 0.19 | 0.09 |
Processed meat | 0.07 | 0.01 | 0.00 |
Animal innards | 0.11 | −0.03 | −0.01 |
Rice and rice products | −0.05 | 0.22 | −0.01 |
Wheat and wheat products | 0.07 | 0.05 | −0.02 |
Fried dough foods and potato chips | 0.01 | −0.04 | 0.02 |
Whole Grains and Mixed Beans | −0.06 | 0.14 | −0.09 |
Tubers | 0.12 | 0.00 | −0.01 |
Nuts and Seeds | 0.08 | −0.05 | 0.07 |
Sweets and desserts | 0.00 | 0.01 | 0.08 |
Cakes, cookies, pies, and biscuits | 0.02 | −0.02 | −0.02 |
Beverages | −0.02 | 0.02 | 0.05 |
Alcoholic beverages | 0.08 | −0.08 | 0.23 |
Dietary Pattern Score, Mean (SD) | Sex | Age | ||||
---|---|---|---|---|---|---|
Male (n = 335) | Female (n = 445) | p value a | 65–59 (n = 472) | 70–74 (n = 308) | p Value a | |
CHEI | 66.10 (11.58) | 68.25 (11.70) | 0.011 | 68.18 (11.55) | 66.02 (11.80) | 0.012 |
DASH | 24.79 (4.57) | 25.55 (4.43) | 0.020 | 25.52 (4.56) | 24.77 (4.39) | 0.023 |
MD | 3.54 (1.37) | 4.13 (1.42) | <0.001 | 3.94 (1.45) | 3.77 (1.38) | 0.108 |
Factor 1: Protein-rich | 0.12 (1.16) | −0.09 (0.85) | 0.005 | 0.09 (1.12) | −0.13 (0.75) | 0.003 |
Factor 2: Vegetables | 0.02 (0.70) | −0.02 (1.18) | 0.605 | 0.02 (1.13) | −0.02 (0.76) | 0.686 |
Factor 3: Sugar, oil and condiments | 0.07 (1.14) | −0.05 (0.88) | 0.104 | −0.04 (1.07) | 0.06 (0.88) | 0.160 |
Dietary Pattern Score | Model 1 | Model 2 a | Model 3 b | ||||||
---|---|---|---|---|---|---|---|---|---|
OR | 95%CI | p Value | OR | 95%CI | p Value | OR | 95%CI | p Value | |
All 780 subjects | |||||||||
DASH | 0.97 | 0.94–1.00 | 0.060 | 0.97 | 0.94–0.99 | 0.033 | 0.98 | 0.95–1.01 | 0.219 |
CHEI | 0.99 | 0.98–1.00 | 0.193 | 0.99 | 0.98–1.00 | 0.125 | 0.99 | 0.98–1.01 | 0.388 |
MD | 1.02 | 0.93–1.12 | 0.688 | 0.98 | 0.89–1.09 | 0.719 | 1.01 | 0.91–1.12 | 0.885 |
Factor 1: Protein-rich | 0.76 | 0.64–0.91 | 0.002 | 0.81 | 0.68–0.96 | 0.015 | 0.82 | 0.69–0.98 | 0.033 |
Factor 2: Vegetables | 0.90 | 0.77–1.06 | 0.200 | 0.90 | 0.77–1.06 | 0.211 | 0.90 | 0.76–1.06 | 0.219 |
Factor 3: Sugar, oil and condiments | 0.94 | 0.81–1.08 | 0.391 | 0.95 | 0.82–1.09 | 0.451 | 0.96 | 0.82–1.13 | 0.639 |
555 subjects without Diabetes, Stroke, and Asthma | |||||||||
DASH | 0.95 | 0.92–0.99 | 0.013 | 0.95 | 0.91–0.99 | 0.007 | 0.96 | 0.92–1.00 | 0.032 |
CHEI | 0.99 | 0.98–1.00 | 0.136 | 0.99 | 0.97–1.00 | 0.115 | 0.99 | 0.98–1.01 | 0.272 |
MD | 0.97 | 0.86–1.08 | 0.548 | 0.94 | 0.83–1.05 | 0.271 | 0.95 | 0.84–1.08 | 0.450 |
Factor 1: Protein-rich | 0.80 | 0.66–0.97 | 0.022 | 0.84 | 0.69–1.00 | 0.049 | 0.84 | 0.68–1.03 | 0.085 |
Factor 2: Vegetables | 0.86 | 0.70–1.06 | 0.148 | 0.87 | 0.71–1.06 | 0.176 | 0.84 | 0.67–1.06 | 0.139 |
Factor 3: Sugar, oil and condiments | 0.89 | 0.75–1.06 | 0.182 | 0.90 | 0.75–1.08 | 0.248 | 0.91 | 0.74–1.12 | 0.389 |
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Wang, Y.; Huang, Y.; Wu, H.; He, G.; Li, S.; Chen, B. Association between Dietary Patterns and Frailty Prevalence in Shanghai Suburban Elders: A Cross-Sectional Study. Int. J. Environ. Res. Public Health 2021, 18, 10852. https://doi.org/10.3390/ijerph182010852
Wang Y, Huang Y, Wu H, He G, Li S, Chen B. Association between Dietary Patterns and Frailty Prevalence in Shanghai Suburban Elders: A Cross-Sectional Study. International Journal of Environmental Research and Public Health. 2021; 18(20):10852. https://doi.org/10.3390/ijerph182010852
Chicago/Turabian StyleWang, Yingchuan, Yue Huang, Han Wu, Gengsheng He, Shuguang Li, and Bo Chen. 2021. "Association between Dietary Patterns and Frailty Prevalence in Shanghai Suburban Elders: A Cross-Sectional Study" International Journal of Environmental Research and Public Health 18, no. 20: 10852. https://doi.org/10.3390/ijerph182010852