-
Table 1 shows the subject characteristics, stratified by malnutrition status. A total of 6,752 men (48.3%) and 7,235 women (51.7%) were included in the analysis, among which 82.9% were aged 60–74 y and 17.1% ≥ 75 y. Overall, based on BMI, 5.7% of the subjects were considered underweight, 34.8% overweight, and 12.4% obese. The prevalence of underweight elderly was higher among older old (≥ 75 y), rural residents, and those with low income, low education status, living with others rather than with spouse, and residing in provinces in the West area. Correspondingly, the prevalence of the overweight and obese was higher among younger old (60–74 y), females, urban residents, and those with high income, higher education status, living with spouse, and residing in the East. Anemia had an overall prevalence of 12.5% in the elderly subjects, which almost doubled (191/797, 24.0%) among those who were underweight.
Table 1. Prevalence of underweight, normal weight, overweight and obesity in demographic subgroups of Chinese elderly1
Item Underweight Normal weight Overweight Obesity Total2 P-value3 n (%) n (%) n (%) n (%) n (%) National 797 (5.7) 6,596 (47.2) 4,866 (34.8) 1,728 (12.4) 13,987 (100.0) Age (years) 60–74 564 (4.9) 5,394 (46.5) 4,134 (35.7) 1,497 (12.9) 11,589 (82.9) < 0.0001 75– 233 (9.7) 1,202 (50.1) 732 (30.5) 231 (9.6) 2,398 (17.1) Gender Male 404 (6.0) 3,418 (50.6) 2,269 (33.6) 661 (9.8) 6,752 (48.3) < 0.0001 Female 393 (5.4) 3,178 (43.9) 2,597 (35.9) 1,067 (14.8) 7,235 (51.7) Residence Urban 265 (3.4) 3,261 (41.8) 3,123 (40.0) 1,154 (14.8) 7,803 (55.8) < 0.0001 Rural 532 (8.6) 3,335 (53.9) 1,743 (28.2) 574 (9.3) 6,184 (44.2) Income Low 454 (6.4) 3,398 (47.9) 2,380 (33.6) 857 (12.1) 7,089 (50.7) < 0.0001 Middle 161 (6.1) 1,260 (48.1) 879 (33.5) 321 (12.3) 2,621 (18.7) High 156 (4.3) 1,642 (45.2) 1,365 (37.6) 472 (13.0) 3,635 (26.0) No response 26 (4.1) 296 (46.1) 242 (37.7) 78 (12.2) 642 (4.6) Education Primary or below 617 (7.2) 4,253 (49.7) 2,730 (31.9) 963 (11.3) 8,563 (61.2) < 0.0001 Junior high school 124 (3.8) 1,437 (44.4) 1,196 (37.0) 478 (14.8) 3,235 (23.1) Senior high or above 56 (2.6) 906 (41.4) 940 (42.9) 287 (13.1) 2,189 (15.7) Living condition Living alone 30 (3.8) 378 (47.4) 295 (37.0) 94 (11.8) 797 (5.7) < 0.0001 Living with spouse 335 (4.7) 3,213 (45.2) 2,608 (36.7) 946 (13.3) 7,102 (50.8) Living with others4 432 (7.1) 3,005 (49.4) 1,963 (32.2) 688 (11.3) 6,088 (43.5) Area East 275 (4.8) 2,459 (42.9) 2,184 (38.1) 809 (14.1) 5,727 (41.0) < 0.0001 Central 255 (5.9) 2,116 (49.3) 1,421 (33.1) 503 (11.7) 4,295 (30.7) West 267 (6.7) 2,021 (51.0) 1,261 (31.8) 416 (10.5) 3,965 (28.4) Anemia status Anemic 191 (11.0) 931 (53.4) 483 (27.7) 140 (8.0) 1,745 (12.5) < 0.0001 Non-anemic 606 (5.0) 5,665 (46.3) 4,383 (35.8) 1,588 (13.0) 12,242 (87.5) Note. 1The percentages in columns ‘underweight’, ‘normal weight’, ‘overweight’, ‘obesity’ are row percentages. The percentages in column ‘Total’ are column percentages within each subgrouping factor. 2Only subjects with both dietary intake data and hemoglobin/anemia records are included in this analysis. 3P-values are two-sided from non-parametric chi-squared tests. 4Living with others: others including sons/daughters/grandchildren/other relatives/caregivers. Table 2 presents the intakes of energy, macronutrients, and micronutrients, subgrouped by age and gender. Besides the energy imbalance-related underweight and overweight/obesity, micronutrient deficiency is another important component of malnutrition. Table 3 examines the prevalence of inadequate micronutrient intakes in the studied Chinese elderly sample, with subgroup comparisons by age and gender. The intake of numerous micronutrients was inadequate: > 75.0% of the elderly did not meet the Chinese DRIs for 10 out of the 17 micronutrients examined (vitamin A, vitamin B1, vitamin B2, folate, vitamin E, calcium, selenium, potassium, biotin, and choline). In general, the prevalence of dietary intake inadequacy for most nutrients increased with age. Female intakes were more inadequate in particular for magnesium, phosphorus, and selenium, while male intakes were more likely inadequate for zinc.
Table 2. Mean nutrient intakes per capita in Chinese elderly with different age, gender1
Nutrients Total Age (years) Gender 60–74 75– P-value2 Male Female P-value2 Mean SD Mean SD Mean SD Mean SD Mean SD Energy (kcal) 1848.8 634.9 1889.1 637.7 1653.8 583.3 < 0.0001 2005.9 658.6 1702.1 574.3 < 0.0001 Fat (g) 66.9 34.8 68.3 35.2 60.4 32.2 < 0.0001 72.3 36.7 61.9 32.1 < 0.0001 Fat (% En) 32.5 11.6 32.4 11.5 32.7 12.0 0.58 32.4 11.6 32.6 11.7 0.27 Protein (g) 55.9 22.8 57.0 22.8 50.9 22.0 < 0.0001 60.1 23.4 52.0 21.5 < 0.0001 Protein (% En) 12.3 3.3 12.2 3.3 12.4 3.4 0.006 12.2 3.2 12.4 3.4 0.0064 Carbohydrate (g) 257.2 106.5 263.0 107.4 228.8 97.0 < 0.0001 277.0 111.3 238.6 98.3 < 0.0001 Carbohydrate (% En) 55.8 12.1 55.8 12.0 55.5 12.3 0.3368 55.4 12.2 56.1 11.9 0.0025 Fiber 10.0 6.4 10.3 6.5 8.8 5.6 < 0.0001 10.6 6.6 9.5 6.1 < 0.0001 Vit A (μg RAE) 402.0 452.4 403.0 440.0 396.8 508.3 0.02 420.3 469.5 384.8 435.1 < 0.0001 Vit C (mg) 73.1 51.7 74.6 51.9 65.9 50.3 < 0.0001 76.2 53.8 70.3 49.4 < 0.0001 Vit B1 (mg) 0.8 0.4 0.8 0.4 0.7 0.3 < 0.0001 0.8 0.4 0.7 0.3 < 0.0001 Vit B2 (mg) 0.7 0.3 0.7 0.3 0.6 0.3 < 0.0001 0.7 0.3 0.6 0.3 < 0.0001 Niacin (mg NE) 12.1 6.1 12.4 6.2 10.9 5.5 < 0.0001 13.1 6.4 11.2 5.6 < 0.0001 Folate (μg DFE) 134.7 82.4 136.7 82.3 125.4 82.0 < 0.0001 143.3 86.5 126.8 77.5 < 0.0001 Biotin (mg) 27.0 16.4 27.6 16.6 24.0 14.8 < 0.0001 29.2 18.0 25.0 14.3 < 0.0001 Vit E (mg α-TE) 7.7 6.9 7.8 7.1 7.0 6.3 < 0.0001 8.3 7.5 7.1 6.3 < 0.0001 Choline (mg) 182.0 81.6 184.8 81.9 168.9 79.2 < 0.0001 196.2 85.0 168.8 76.0 < 0.0001 Ca (mg) 348.3 203.9 351.2 204.6 333.8 199.9 < 0.0001 367.8 214.0 330.0 192.3 < 0.0001 Fe (mg) 18.9 8.9 19.3 8.9 17.0 8.9 < 0.0001 20.3 9.5 17.7 8.2 < 0.0001 Mg (mg) 256.4 106.0 261.9 106.3 230.0 100.2 < 0.0001 274.2 109.9 239.8 99.4 < 0.0001 P (mg) 840.8 316.6 857.2 316.5 761.5 305.3 < 0.0001 902.6 327.6 783.2 294.7 < 0.0001 Zn (mg) 9.1 3.7 9.3 3.7 8.3 3.6 < 0.0001 9.9 3.9 8.5 3.4 < 0.0001 Se (μg) 38.4 22.9 39.2 23.3 34.7 20.3 < 0.0001 41.3 23.2 35.7 22.2 < 0.0001 K (mg) 1454.1 646.4 1482.6 648.1 1316.1 620.1 < 0.0001 1548.4 681.6 1366.0 598.5 < 0.0001 Na (mg) 5030.1 5081.2 5126.6 5342.4 4563.7 3521.9 < 0.0001 5368.2 4022.9 4714.5 5882.7 < 0.0001 Note. 1Abbreviations: RAE: retinol-activity equivalent; NE: niacin equivalent; DFE: dietary folate equivalent; α-TE: α-tocopherol equivalent. 2P-values are two-sided from non-parametric chi-squared tests. Table 3. Percentage of Chinese elderly with inadequate nutrient intakes among age and gender subgroups1
Nutrients Total
(%)Age (years) Gender 60–74 75– P-value2 Male Female P-value2 (%) (%) (%) (%) Vit A (μg RAE) 77.3 76.7 80.3 0.0001 78.5 76.1 0.0007 Vit C (mg) 69.0 67.8 74.7 < 0.0001 66.8 71.0 < 0.0001 Vit B1 (mg) 83.9 82.6 90.3 < 0.0001 84.9 83.0 0.0023 Vit B2 (mg) 91.5 91.1 93.3 0.0005 92.7 90.3 < 0.0001 Niacin (mg NE) 43.5 42.6 47.7 < 0.0001 45.1 42.0 0.0002 Folate (μg DFE) 96.5 96.4 96.9 0.29 95.9 97.1 0.0001 Biotin (mg) 86.3 85.5 90.0 < 0.0001 83.4 89.0 < 0.0001 Vit E (mg α-TE) 90.5 89.9 93.5 < 0.0001 88.3 92.6 < 0.0001 Choline (mg) 99.4 99.3 99.7 0.02 99.7 99.1 < 0.0001 Ca (mg) 96.9 96.9 96.9 0.89 96.1 97.6 < 0.0001 Fe (mg) 4.0 3.1 8.3 < 0.0001 2.1 5.7 < 0.0001 Mg (mg) 64.1 62.5 71.6 < 0.0001 57.3 70.4 < 0.0001 P (mg) 21.2 19.3 30.4 < 0.0001 14.8 27.3 < 0.0001 Zn (mg) 43.3 41.0 54.7 < 0.0001 63.3 24.7 < 0.0001 Se (μg) 78.5 77.5 83.2 < 0.0001 73.6 83.1 < 0.0001 K (mg) 83.8 82.8 88.7 < 0.0001 80.3 87.0 < 0.0001 Na (mg) 4.1 3.9 5.1 0.01 3.4 4.8 < 0.0001 Note. 1Abbreviations: RAE: retinol-activity equivalent; NE: niacin equivalent; DFE: dietary folate equivalent; α-TE: α-tocopherol equivalent. 2P-values are two-sided from non-parametric chi-squared tests. Then, we studied the food consumption patterns among subjects with different nutritional statuses. Table 4 shows the adjusted means of intakes for 27 major food groups across the 4 BMI categories, with adjustment for age, gender, urban/rural residence, income level, education level, living condition, area of residence, physical activity level, and total energy intake. Compared with underweight subjects, overweight and obese subjects consumed a significantly lower amount of rice, dark-colored vegetables, pork, animal viscera, poultry, and animal oils and a higher amount of wheat products, coarse cereals, and vegetable oils. It is worth noting that the population mean intakes of many food groups did not meet the Chinese Dietary Guideline recommendations regardless of their nutritional status. The biggest gaps exist in the food groups of dairy and fruits, with the recommendation of 300 g/d for dairy and 200–350 g/d for fruits in the Chinese Dietary Guideline. Such population-wide dietary patterns partly explained the numerous key nutrient inadequacies.
Table 4. Adjusted means of food intakes in Chinese elderly with different nutritional status1
Item Underweight Normal Overweight Obesity P-trend Mean 95% CI Mean 95% CI Mean 95% CI Mean 95% CI Rice (g/d) 183.4 173.3 193.6 150.8 144.8 156.8 129.9 123.6 136.2 117.3 109.4 125.1 < 0.0001 Wheat (g/d) 88.7 79.6 97.9 111.3 105.9 116.8 126.8 121.1 132.5 141.4 134.2 148.5 < 0.0001 Coarse cereals (g/d) 15.0 11.5 18.4 17.2 15.2 19.2 20.0 17.9 22.2 20.6 17.9 23.2 < 0.0001 Tubers (g/d) 27.7 23.3 32.0 28.0 25.4 30.6 29.2 26.5 32.0 29.7 26.3 33.1 0.13 Legumes (g/d) 2.8 1.5 4.0 3.4 2.7 4.2 3.9 3.2 4.7 3.8 2.8 4.8 0.04 Soybean products (g/d) 9.9 8.3 11.6 10.4 9.4 11.3 10.1 9.1 11.1 10.6 9.4 11.9 0.71 Dark color vegetables (g/d) 84.6 77.5 91.6 80.6 76.5 84.8 74.3 69.9 78.7 67.1 61.6 72.6 < 0.0001 Light color vegetables (g/d) 145.8 135.8 155.8 152.0 146.1 157.9 152.8 146.6 159.1 154.5 146.8 162.3 0.17 Salted vegetables (g/d) 3.1 2.1 4.2 2.9 2.3 3.5 2.8 2.1 3.4 2.8 2.0 3.6 0.53 Fruits (g/d) 42.9 35.9 50.0 44.2 40.0 48.3 47.3 42.9 51.7 45.1 39.6 50.5 0.19 Nuts (g/d) 3.8 2.8 4.8 3.9 3.3 4.5 4.3 3.7 4.9 4.5 3.7 5.3 0.03 Pork (g/d) 51.8 47.6 56.0 51.1 48.6 53.6 49.3 46.7 51.9 46.8 43.6 50.1 0.001 Other livestock meats (g/d) 5.3 3.6 7.1 5.6 4.6 6.6 6.0 4.9 7.0 6.9 5.6 8.3 0.03 Animal viscera (g/d) 2.9 2.1 3.7 1.6 1.1 2.1 1.1 0.6 1.6 1.2 0.5 1.8 < 0.0001 Poultry (g/d) 10.8 8.7 12.9 10.0 8.7 11.2 9.3 8.0 10.6 7.6 5.9 9.2 0.0004 Milk (g/d) 43.3 36.4 50.1 42.3 38.3 46.3 47.6 43.4 51.8 45.2 39.9 50.5 0.02 Eggs (g/d) 23.3 21.1 25.6 24.0 22.6 25.3 25.6 24.2 27.0 23.8 22.1 25.6 0.12 Fish (g/d) 21.3 17.9 24.6 19.9 17.9 21.8 19.5 17.4 21.6 17.0 14.4 19.6 0.01 Vegetable oils (g/d) 30.2 28.2 32.1 31.9 30.8 33.1 33.9 32.6 35.1 34.2 32.7 35.8 < 0.0001 Animal oils (g/d) 5.8 4.9 6.7 4.1 3.5 4.6 3.0 2.5 3.6 2.7 2.0 3.4 < 0.0001 Cakes (g/d) 7.7 5.7 9.8 9.0 7.8 10.2 8.4 7.1 9.7 9.2 7.6 10.8 0.72 Sugar (g/d) 4.3 3.0 5.7 5.5 4.7 6.3 5.5 4.7 6.4 5.8 4.8 6.8 0.12 Salt (g/d) 8.8 7.9 9.7 8.8 8.3 9.4 9.1 8.5 9.7 8.9 8.2 9.7 0.37 Condiments (g/d) 15.6 13.6 17.7 14.3 13.1 15.5 14.5 13.2 15.8 14.6 13.0 16.2 0.83 Others (g/d) 7.8 5.6 10.1 8.8 7.4 10.1 9.2 7.8 10.6 10.6 8.8 12.3 0.01 Soft drinks (mL/d) 20.0 10.9 29.2 18.7 13.3 24.1 19.1 13.4 24.8 21.9 14.8 29.1 0.49 Alcoholic beverages (mL/d) 1.4 0.4 2.4 2.2 1.6 2.7 1.4 0.8 2.0 1.2 0.5 2.0 0.01 Note 1Mean and 95% CI are calculated from general linear model with adjustment for age, gender, urban/rural residence, income level, education level, living condition, area of residence, physical activity, and total energy intake. Abbreviations: CI: confidence interval. 2P-trend is calculated from general linear model using the median BMI values in each category as continuous variables.
doi: 10.3967/bes2021.045
Malnutrition in Relation with Dietary, Geographical, and Socioeconomic Factors among Older Chinese
-
Abstract:
Objective Nutrition is closely related to the health of the elderly population. This study aimed to provide a comprehensive picture of the nutrition status of elderly Chinese and its related dietary, geographical, and socioeconomic factors. Methods A total of 13,987 ≥ 60-year-old persons from the 2010–2013 Chinese National Nutrition and Health Survey were included to evaluate various aspects of malnutrition, including underweight, overweight or obesity, and micronutrient inadequacy. Results Overall, the prevalence of obesity, overweight, and underweight was 12.4%, 34.8%, and 5.7%, respectively, with disparities both geographically and socioeconomically. The prevalence of underweight was higher among the older old (≥ 75 years), rural residents and those with low income, with low education status, and residing in undeveloped West areas. More than 75% of the elderly do not meet the Dietary Reference Intakes for vitamins A, B1, B2, and E, folate, calcium, selenium, potassium, biotin, and choline, with the prevalence of inadequate intake increasing with age for most nutrients. At the population level, the mean intakes of numerous food groups did not meet the recommendations by the Chinese Dietary Guideline. Conclusions Obesity epidemic, inadequacy of micronutrient intake, and high prevalence of underweight and anemia in susceptible older people are the major nutrition challenges for the rapidly aging population in China. -
Key words:
- Malnutrition /
- Older Chinese /
- Food intake /
- Nutrients /
- National survey
-
Table 1. Prevalence of underweight, normal weight, overweight and obesity in demographic subgroups of Chinese elderly1
Item Underweight Normal weight Overweight Obesity Total2 P-value3 n (%) n (%) n (%) n (%) n (%) National 797 (5.7) 6,596 (47.2) 4,866 (34.8) 1,728 (12.4) 13,987 (100.0) Age (years) 60–74 564 (4.9) 5,394 (46.5) 4,134 (35.7) 1,497 (12.9) 11,589 (82.9) < 0.0001 75– 233 (9.7) 1,202 (50.1) 732 (30.5) 231 (9.6) 2,398 (17.1) Gender Male 404 (6.0) 3,418 (50.6) 2,269 (33.6) 661 (9.8) 6,752 (48.3) < 0.0001 Female 393 (5.4) 3,178 (43.9) 2,597 (35.9) 1,067 (14.8) 7,235 (51.7) Residence Urban 265 (3.4) 3,261 (41.8) 3,123 (40.0) 1,154 (14.8) 7,803 (55.8) < 0.0001 Rural 532 (8.6) 3,335 (53.9) 1,743 (28.2) 574 (9.3) 6,184 (44.2) Income Low 454 (6.4) 3,398 (47.9) 2,380 (33.6) 857 (12.1) 7,089 (50.7) < 0.0001 Middle 161 (6.1) 1,260 (48.1) 879 (33.5) 321 (12.3) 2,621 (18.7) High 156 (4.3) 1,642 (45.2) 1,365 (37.6) 472 (13.0) 3,635 (26.0) No response 26 (4.1) 296 (46.1) 242 (37.7) 78 (12.2) 642 (4.6) Education Primary or below 617 (7.2) 4,253 (49.7) 2,730 (31.9) 963 (11.3) 8,563 (61.2) < 0.0001 Junior high school 124 (3.8) 1,437 (44.4) 1,196 (37.0) 478 (14.8) 3,235 (23.1) Senior high or above 56 (2.6) 906 (41.4) 940 (42.9) 287 (13.1) 2,189 (15.7) Living condition Living alone 30 (3.8) 378 (47.4) 295 (37.0) 94 (11.8) 797 (5.7) < 0.0001 Living with spouse 335 (4.7) 3,213 (45.2) 2,608 (36.7) 946 (13.3) 7,102 (50.8) Living with others4 432 (7.1) 3,005 (49.4) 1,963 (32.2) 688 (11.3) 6,088 (43.5) Area East 275 (4.8) 2,459 (42.9) 2,184 (38.1) 809 (14.1) 5,727 (41.0) < 0.0001 Central 255 (5.9) 2,116 (49.3) 1,421 (33.1) 503 (11.7) 4,295 (30.7) West 267 (6.7) 2,021 (51.0) 1,261 (31.8) 416 (10.5) 3,965 (28.4) Anemia status Anemic 191 (11.0) 931 (53.4) 483 (27.7) 140 (8.0) 1,745 (12.5) < 0.0001 Non-anemic 606 (5.0) 5,665 (46.3) 4,383 (35.8) 1,588 (13.0) 12,242 (87.5) Note. 1The percentages in columns ‘underweight’, ‘normal weight’, ‘overweight’, ‘obesity’ are row percentages. The percentages in column ‘Total’ are column percentages within each subgrouping factor. 2Only subjects with both dietary intake data and hemoglobin/anemia records are included in this analysis. 3P-values are two-sided from non-parametric chi-squared tests. 4Living with others: others including sons/daughters/grandchildren/other relatives/caregivers. Table 2. Mean nutrient intakes per capita in Chinese elderly with different age, gender1
Nutrients Total Age (years) Gender 60–74 75– P-value2 Male Female P-value2 Mean SD Mean SD Mean SD Mean SD Mean SD Energy (kcal) 1848.8 634.9 1889.1 637.7 1653.8 583.3 < 0.0001 2005.9 658.6 1702.1 574.3 < 0.0001 Fat (g) 66.9 34.8 68.3 35.2 60.4 32.2 < 0.0001 72.3 36.7 61.9 32.1 < 0.0001 Fat (% En) 32.5 11.6 32.4 11.5 32.7 12.0 0.58 32.4 11.6 32.6 11.7 0.27 Protein (g) 55.9 22.8 57.0 22.8 50.9 22.0 < 0.0001 60.1 23.4 52.0 21.5 < 0.0001 Protein (% En) 12.3 3.3 12.2 3.3 12.4 3.4 0.006 12.2 3.2 12.4 3.4 0.0064 Carbohydrate (g) 257.2 106.5 263.0 107.4 228.8 97.0 < 0.0001 277.0 111.3 238.6 98.3 < 0.0001 Carbohydrate (% En) 55.8 12.1 55.8 12.0 55.5 12.3 0.3368 55.4 12.2 56.1 11.9 0.0025 Fiber 10.0 6.4 10.3 6.5 8.8 5.6 < 0.0001 10.6 6.6 9.5 6.1 < 0.0001 Vit A (μg RAE) 402.0 452.4 403.0 440.0 396.8 508.3 0.02 420.3 469.5 384.8 435.1 < 0.0001 Vit C (mg) 73.1 51.7 74.6 51.9 65.9 50.3 < 0.0001 76.2 53.8 70.3 49.4 < 0.0001 Vit B1 (mg) 0.8 0.4 0.8 0.4 0.7 0.3 < 0.0001 0.8 0.4 0.7 0.3 < 0.0001 Vit B2 (mg) 0.7 0.3 0.7 0.3 0.6 0.3 < 0.0001 0.7 0.3 0.6 0.3 < 0.0001 Niacin (mg NE) 12.1 6.1 12.4 6.2 10.9 5.5 < 0.0001 13.1 6.4 11.2 5.6 < 0.0001 Folate (μg DFE) 134.7 82.4 136.7 82.3 125.4 82.0 < 0.0001 143.3 86.5 126.8 77.5 < 0.0001 Biotin (mg) 27.0 16.4 27.6 16.6 24.0 14.8 < 0.0001 29.2 18.0 25.0 14.3 < 0.0001 Vit E (mg α-TE) 7.7 6.9 7.8 7.1 7.0 6.3 < 0.0001 8.3 7.5 7.1 6.3 < 0.0001 Choline (mg) 182.0 81.6 184.8 81.9 168.9 79.2 < 0.0001 196.2 85.0 168.8 76.0 < 0.0001 Ca (mg) 348.3 203.9 351.2 204.6 333.8 199.9 < 0.0001 367.8 214.0 330.0 192.3 < 0.0001 Fe (mg) 18.9 8.9 19.3 8.9 17.0 8.9 < 0.0001 20.3 9.5 17.7 8.2 < 0.0001 Mg (mg) 256.4 106.0 261.9 106.3 230.0 100.2 < 0.0001 274.2 109.9 239.8 99.4 < 0.0001 P (mg) 840.8 316.6 857.2 316.5 761.5 305.3 < 0.0001 902.6 327.6 783.2 294.7 < 0.0001 Zn (mg) 9.1 3.7 9.3 3.7 8.3 3.6 < 0.0001 9.9 3.9 8.5 3.4 < 0.0001 Se (μg) 38.4 22.9 39.2 23.3 34.7 20.3 < 0.0001 41.3 23.2 35.7 22.2 < 0.0001 K (mg) 1454.1 646.4 1482.6 648.1 1316.1 620.1 < 0.0001 1548.4 681.6 1366.0 598.5 < 0.0001 Na (mg) 5030.1 5081.2 5126.6 5342.4 4563.7 3521.9 < 0.0001 5368.2 4022.9 4714.5 5882.7 < 0.0001 Note. 1Abbreviations: RAE: retinol-activity equivalent; NE: niacin equivalent; DFE: dietary folate equivalent; α-TE: α-tocopherol equivalent. 2P-values are two-sided from non-parametric chi-squared tests. Table 3. Percentage of Chinese elderly with inadequate nutrient intakes among age and gender subgroups1
Nutrients Total
(%)Age (years) Gender 60–74 75– P-value2 Male Female P-value2 (%) (%) (%) (%) Vit A (μg RAE) 77.3 76.7 80.3 0.0001 78.5 76.1 0.0007 Vit C (mg) 69.0 67.8 74.7 < 0.0001 66.8 71.0 < 0.0001 Vit B1 (mg) 83.9 82.6 90.3 < 0.0001 84.9 83.0 0.0023 Vit B2 (mg) 91.5 91.1 93.3 0.0005 92.7 90.3 < 0.0001 Niacin (mg NE) 43.5 42.6 47.7 < 0.0001 45.1 42.0 0.0002 Folate (μg DFE) 96.5 96.4 96.9 0.29 95.9 97.1 0.0001 Biotin (mg) 86.3 85.5 90.0 < 0.0001 83.4 89.0 < 0.0001 Vit E (mg α-TE) 90.5 89.9 93.5 < 0.0001 88.3 92.6 < 0.0001 Choline (mg) 99.4 99.3 99.7 0.02 99.7 99.1 < 0.0001 Ca (mg) 96.9 96.9 96.9 0.89 96.1 97.6 < 0.0001 Fe (mg) 4.0 3.1 8.3 < 0.0001 2.1 5.7 < 0.0001 Mg (mg) 64.1 62.5 71.6 < 0.0001 57.3 70.4 < 0.0001 P (mg) 21.2 19.3 30.4 < 0.0001 14.8 27.3 < 0.0001 Zn (mg) 43.3 41.0 54.7 < 0.0001 63.3 24.7 < 0.0001 Se (μg) 78.5 77.5 83.2 < 0.0001 73.6 83.1 < 0.0001 K (mg) 83.8 82.8 88.7 < 0.0001 80.3 87.0 < 0.0001 Na (mg) 4.1 3.9 5.1 0.01 3.4 4.8 < 0.0001 Note. 1Abbreviations: RAE: retinol-activity equivalent; NE: niacin equivalent; DFE: dietary folate equivalent; α-TE: α-tocopherol equivalent. 2P-values are two-sided from non-parametric chi-squared tests. Table 4. Adjusted means of food intakes in Chinese elderly with different nutritional status1
Item Underweight Normal Overweight Obesity P-trend Mean 95% CI Mean 95% CI Mean 95% CI Mean 95% CI Rice (g/d) 183.4 173.3 193.6 150.8 144.8 156.8 129.9 123.6 136.2 117.3 109.4 125.1 < 0.0001 Wheat (g/d) 88.7 79.6 97.9 111.3 105.9 116.8 126.8 121.1 132.5 141.4 134.2 148.5 < 0.0001 Coarse cereals (g/d) 15.0 11.5 18.4 17.2 15.2 19.2 20.0 17.9 22.2 20.6 17.9 23.2 < 0.0001 Tubers (g/d) 27.7 23.3 32.0 28.0 25.4 30.6 29.2 26.5 32.0 29.7 26.3 33.1 0.13 Legumes (g/d) 2.8 1.5 4.0 3.4 2.7 4.2 3.9 3.2 4.7 3.8 2.8 4.8 0.04 Soybean products (g/d) 9.9 8.3 11.6 10.4 9.4 11.3 10.1 9.1 11.1 10.6 9.4 11.9 0.71 Dark color vegetables (g/d) 84.6 77.5 91.6 80.6 76.5 84.8 74.3 69.9 78.7 67.1 61.6 72.6 < 0.0001 Light color vegetables (g/d) 145.8 135.8 155.8 152.0 146.1 157.9 152.8 146.6 159.1 154.5 146.8 162.3 0.17 Salted vegetables (g/d) 3.1 2.1 4.2 2.9 2.3 3.5 2.8 2.1 3.4 2.8 2.0 3.6 0.53 Fruits (g/d) 42.9 35.9 50.0 44.2 40.0 48.3 47.3 42.9 51.7 45.1 39.6 50.5 0.19 Nuts (g/d) 3.8 2.8 4.8 3.9 3.3 4.5 4.3 3.7 4.9 4.5 3.7 5.3 0.03 Pork (g/d) 51.8 47.6 56.0 51.1 48.6 53.6 49.3 46.7 51.9 46.8 43.6 50.1 0.001 Other livestock meats (g/d) 5.3 3.6 7.1 5.6 4.6 6.6 6.0 4.9 7.0 6.9 5.6 8.3 0.03 Animal viscera (g/d) 2.9 2.1 3.7 1.6 1.1 2.1 1.1 0.6 1.6 1.2 0.5 1.8 < 0.0001 Poultry (g/d) 10.8 8.7 12.9 10.0 8.7 11.2 9.3 8.0 10.6 7.6 5.9 9.2 0.0004 Milk (g/d) 43.3 36.4 50.1 42.3 38.3 46.3 47.6 43.4 51.8 45.2 39.9 50.5 0.02 Eggs (g/d) 23.3 21.1 25.6 24.0 22.6 25.3 25.6 24.2 27.0 23.8 22.1 25.6 0.12 Fish (g/d) 21.3 17.9 24.6 19.9 17.9 21.8 19.5 17.4 21.6 17.0 14.4 19.6 0.01 Vegetable oils (g/d) 30.2 28.2 32.1 31.9 30.8 33.1 33.9 32.6 35.1 34.2 32.7 35.8 < 0.0001 Animal oils (g/d) 5.8 4.9 6.7 4.1 3.5 4.6 3.0 2.5 3.6 2.7 2.0 3.4 < 0.0001 Cakes (g/d) 7.7 5.7 9.8 9.0 7.8 10.2 8.4 7.1 9.7 9.2 7.6 10.8 0.72 Sugar (g/d) 4.3 3.0 5.7 5.5 4.7 6.3 5.5 4.7 6.4 5.8 4.8 6.8 0.12 Salt (g/d) 8.8 7.9 9.7 8.8 8.3 9.4 9.1 8.5 9.7 8.9 8.2 9.7 0.37 Condiments (g/d) 15.6 13.6 17.7 14.3 13.1 15.5 14.5 13.2 15.8 14.6 13.0 16.2 0.83 Others (g/d) 7.8 5.6 10.1 8.8 7.4 10.1 9.2 7.8 10.6 10.6 8.8 12.3 0.01 Soft drinks (mL/d) 20.0 10.9 29.2 18.7 13.3 24.1 19.1 13.4 24.8 21.9 14.8 29.1 0.49 Alcoholic beverages (mL/d) 1.4 0.4 2.4 2.2 1.6 2.7 1.4 0.8 2.0 1.2 0.5 2.0 0.01 Note 1Mean and 95% CI are calculated from general linear model with adjustment for age, gender, urban/rural residence, income level, education level, living condition, area of residence, physical activity, and total energy intake. Abbreviations: CI: confidence interval. 2P-trend is calculated from general linear model using the median BMI values in each category as continuous variables. -
[1] Cederholm T, Jensen GL, Correia M, et al. GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community. J Cachexia Sarcopenia Muscle, 2019; 10, 207−17. doi: 10.1002/jcsm.12383 [2] Roust LR, DiBaise JK. Nutrient deficiencies prior to bariatric surgery. Curr Opin Clin Nutr Metab Care, 2017; 20, 138−44. doi: 10.1097/MCO.0000000000000352 [3] Wells JC, Sawaya AL, Wibaek R, et al. The double burden of malnutrition: aetiological pathways and consequences for health. Lancet, 2020; 395, 75−88. doi: 10.1016/S0140-6736(19)32472-9 [4] Collaborators GBDD. Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet, 2019; 393, 1958−72. doi: 10.1016/S0140-6736(19)30041-8 [5] United Nations Department of Economic and Social Affairs Population Division (2015) World Population Ageing 2015 (ST/ESA/SER. A/390). [6] The State Council of the People’s Republic of China (2017) National Nutrition Plan (2017−2030). [7] Zhao L, Ma G, Piao J, et al. Scheme of the 2010-2012 Chinese nutrition and health surveillance. Chin J Prevent Med, 2016; 50, 204−7. (In Chinese) [8] Yang Y, Wang G, Pan X. China Food Composition Table. 2nd ed. Beijing: Peking University Medical Press. 2009. [9] China Nutrition Society (2014) China Dietary Reference Intakes Handbook (2013). Beijing: China Standard Press. [10] China Statistical Yearbook In 2010. Beijing: National Bureau of Statistics of China. [11] World Health Organization. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. [Vitamin and Mineral Nutrition Information System, editor]. Geneva: World Health Organization. 2011. [12] National Health and Family Planning Commission of the People’s Republic of China (2013) Health Standard of the People’s Republic of China. No. WS/T 428-2013: Criteria of Weight for Adults. Beijing. [13] State Government of China China National Census 2010. [14] Hu L, Huang X, You C, et al. Prevalence of overweight, obesity, abdominal obesity and obesity-related risk factors in southern China. PLoS One, 2017; 12, e0183934. doi: 10.1371/journal.pone.0183934 [15] Liu X, Wu W, Mao Z, et al. Prevalence and influencing factors of overweight and obesity in a Chinese rural population: the Henan Rural Cohort Study. Sci Rep, 2018; 8, 13101. doi: 10.1038/s41598-018-31336-2 [16] Song N, Liu F, Han M, et al. Prevalence of overweight and obesity and associated risk factors among adult residents of northwest China: a cross-sectional study. BMJ Open, 2019; 9, e028131. doi: 10.1136/bmjopen-2018-028131 [17] Collaboration NCDRF. Rising rural body-mass index is the main driver of the global obesity epidemic in adults. Nature, 2019; 569, 260−4. doi: 10.1038/s41586-019-1171-x [18] Jaacks LM, Gordon-Larsen P, Mayer-Davis EJ, et al. Age, period and cohort effects on adult body mass index and overweight from 1991 to 2009 in China: the China Health and Nutrition Survey. Int J Epidemiol, 2013; 42, 828−37. doi: 10.1093/ije/dyt052 [19] Popkin BM. Global nutrition dynamics: the world is shifting rapidly toward a diet linked with noncommunicable diseases. Am J Clin Nutr, 2006; 84, 289−98. doi: 10.1093/ajcn/84.2.289 [20] Chye L, Wei K, Nyunt MSZ, et al. Strong Relationship between Malnutrition and Cognitive Frailty in the Singapore Longitudinal Ageing Studies (SLAS-1 and SLAS-2). J Prev Alzheimers Dis, 2018; 5, 142−8. [21] Wei K, Nyunt MS, Gao Q, et al. Association of Frailty and Malnutrition With Long-term Functional and Mortality Outcomes Among Community-Dwelling Older Adults: Results From the Singapore Longitudinal Aging Study 1. JAMA Netw Open, 2018; 1, e180650. doi: 10.1001/jamanetworkopen.2018.0650 [22] Jones N, Bartlett HE. Comparison of the eating behaviour and dietary consumption in older adults with and without visual impairment. Br J Nutr, 2019; 1−25. [23] Culleton BF, Manns BJ, Zhang J, et al. Impact of anemia on hospitalization and mortality in older adults. Blood, 2006; 107, 3841−6. doi: 10.1182/blood-2005-10-4308 [24] Yang G, Wang Y, Zeng Y, et al. Rapid health transition in China, 1990-2010: findings from the Global Burden of Disease Study 2010. Lancet, 2013; 381, 1987−2015. doi: 10.1016/S0140-6736(13)61097-1 [25] Seitz AE, Eberhardt MS, Lukacs SL. Anemia Prevalence and Trends in Adults Aged 65 and Older: U. S. National Health and Nutrition Examination Survey: 2001−2004 to 2013−2016. J Am Geriatr Soc, 2018; 66, 2431−2. doi: 10.1111/jgs.15530 [26] Gaskell H, Derry S, Andrew Moore R, et al. Prevalence of anaemia in older persons: systematic review. BMC Geriatr, 2008; 8, 1. doi: 10.1186/1471-2318-8-1 [27] den Elzen WP, Westendorp RG, Frolich M, et al. Vitamin B12 and folate and the risk of anemia in old age: the Leiden 85-Plus Study. Arch Intern Med, 2008; 168, 2238−44. doi: 10.1001/archinte.168.20.2238 [28] Shi Z, Zhen S, Wittert GA, et al. Inadequate riboflavin intake and anemia risk in a Chinese population: five-year follow up of the Jiangsu Nutrition Study. PLoS One, 2014; 9, e88862. doi: 10.1371/journal.pone.0088862 [29] Powers HJ. Riboflavin (vitamin B-2) and health. Am J Clin Nutr, 2003; 77, 1352−60. doi: 10.1093/ajcn/77.6.1352 [30] Xu X. Introduction to Food Culture: Dongnan University Press: Nanjing, China. 2008. [31] Song F, Cho MS. Geography of Food Consumption Patterns between South and North China. Foods, 2017; 6, 34. doi: 10.3390/foods6050034 [32] Huang L, Wang H, Wang Z, et al. Regional Disparities in the Association between Cereal Consumption and Metabolic Syndrome: Results from the China Health and Nutrition Survey. Nutrients, 2019; 11, 764. doi: 10.3390/nu11040764 [33] Zhou M, Wang H, Zhu J, et al. Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013. Lancet, 2016; 387, 251−72. doi: 10.1016/S0140-6736(15)00551-6 [34] Xu G, Ma M, Liu X, et al. Is there a stroke belt in China and why? Stroke, 2013; 44, 1775−83. [35] Li Y, Wang L, Feng X, et al. Geographical variations in hypertension prevalence, awareness, treatment and control in China: findings from a nationwide and provincially representative survey. J Hypertens, 2018; 36, 178−87. doi: 10.1097/HJH.0000000000001531 [36] Azzolino D, Passarelli PC, De Angelis P, et al. Poor Oral Health as a Determinant of Malnutrition and Sarcopenia. Nutrients, 2019; 11. [37] Nifli AP. Appetite, Metabolism and Hormonal Regulation in Normal Ageing and Dementia. Diseases, 2018; 6. [38] Remond D, Shahar DR, Gille D, et al. Understanding the gastrointestinal tract of the elderly to develop dietary solutions that prevent malnutrition. Oncotarget, 2015; 6, 13858−98. doi: 10.18632/oncotarget.4030 [39] ter Borg S, Verlaan S, Hemsworth J, et al. Micronutrient intakes and potential inadequacies of community-dwelling older adults: a systematic review. Br J Nutr, 2015; 113, 1195−206. doi: 10.1017/S0007114515000203 [40] Hu L, Huang X, You C, et al. Prevalence and Risk Factors of Prehypertension and Hypertension in Southern China. PLoS One, 2017; 12, e0170238. doi: 10.1371/journal.pone.0170238