| Literature DB >> 31664922 |
Zhewen Ren1, Fei Zhao1,2, Hui Chen1, Dongmei Hu1, Wentao Yu3, Xiaoli Xu3, Dingwen Lin4, Fuyi Luo5, Yueling Fan6, Haijun Wang7, Jun Cheng8, Liyun Zhao9.
Abstract
BACKGROUND: The objectives of this study were to examine nutrient intakes of tuberculosis (TB) patients and to identify their associated factors.Entities:
Keywords: Behavioral factors; Nutrient intakes; Socio-demographic factors; Tuberculosis patients
Mesh:
Substances:
Year: 2019 PMID: 31664922 PMCID: PMC6819533 DOI: 10.1186/s12879-019-4481-6
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Socio-demographic and behavioral characteristics for 300 TB patients
| Characteristics | N | N% | |
|---|---|---|---|
| Socio-demographic factors | |||
| Age group | 18–49 | 161 | 53.7 |
| 50–64 | 86 | 28.7 | |
| ≥65 | 53 | 17.7 | |
| Mean (±SD) | 45.5 (±18.7) | ||
| Gender | Male | 206 | 68.7 |
| Female | 94 | 31.3 | |
| Education | Primary school and below | 161 | 53.7 |
| Junior middle school and above | 139 | 46.3 | |
| Marital status | Married | 209 | 69.7 |
| Other marital status | 91 | 30.3 | |
| Occupation | Employed | 178 | 59.3 |
| Unemployed | 122 | 40.7 | |
| Annual household incomea | < 20,000 | 136 | 45.3 |
| 20,000-40,000 | 79 | 26.3 | |
| ≥40,000 | 20 | 6.7 | |
| Refusal or unknown | 65 | 9.7 | |
| Mean (±SD) | 18,203.1 (±17,622.2) | ||
| Behavioral factors | |||
| Alcohol consumption | Yes | 119 | 39.7 |
| No | 181 | 60.3 | |
| Smoking status | Smoker | 140 | 46.7 |
| Non-smoker | 160 | 53.3 | |
| Eating out-of-home | Yes | 58 | 19.3 |
| No | 242 | 80.7 | |
a65 patients who refused or with missing data were excluded from this analysis
Daily energy and macronutrient intakes of TB patients compared with DRIs
| Energy and macronutrient intakes | Males ( | Females ( | ||||
|---|---|---|---|---|---|---|
| RNI/AI | Mean (SD) | Below RNI/AI(%) | RNI/AI | Mean (SD) | Below RNI/AI(%) | |
| Calories (Kcal) | 2250 | 1655.0 (619.3) | 180 (87.4) | 1800 | 1360.3 (552.1) | 78 (83.0) |
| Total Protein (g) | 65 | 44.6 (18.2) | 187 (90.8) | 55 | 35.9 (12.3) | 86 (91.5) |
| Total Fat (g) | – | 73.0 (50.5) | – | – | 68.9 (48.3) | – |
| Total Carbohydrates (g) | – | 212.1 (117.2) | – | – | 154.8 (58.0) | – |
| Total fiber (g) | – | 7.6 (4.3) | – | – | 5.7 (2.6) | – |
Daily micronutrient intakes of TB patients compared with DRIs
| Micronutrient intakes | Males (n = 206) | Females (n = 94) | ||||
|---|---|---|---|---|---|---|
| RNI/AI | Mean (SD) | Below RNI/AI(%) | RNI/AI | Mean (SD) | Below RNI/AI(%) | |
| Retinol (μg) | 800 | 807.5 (994.0) | 135 (65.5) | 700 | 603.9 (626.7) | 68 (72.3) |
| Thiamin (mg) | 1.4 | 0.9 (0.5) | 180 (87.4) | 1.2 | 0.7 (0.3) | 88 (93.6) |
| Riboflavin (mg) | 1.4 | 0.6 (0.3) | 203 (98.5) | 1.2 | 0.5 (0.2) | 94 (100) |
| Niacin (mg) | 12 | 12.6 (5.3) | 94 (45.6) | 15 | 10.3 (4.7) | 78 (83.0) |
| Vitamin E (mg) | 14 | 53.6 (39.6) | 13 (6.3) | 14 | 57.1 (40.0) | 4 (4.3) |
| Vitamin C (mg) | 100 | 96.6 (75.3) | 130 (63.1) | 100 | 70.2 (55.8) | 74 (78.7) |
| Potassium (mg) | 2000 | 1309.2 (636.7) | 180 (87.4) | 2000 | 1011.7 (351.0) | 94 (100) |
| Sodium (mg) | 1500 | 2204.4 (1204.8) | 67 (35.5) | 1500 | 2054.5 (1123.4) | 28 (29.8) |
| Calcium (mg) | 800 | 216.3 (126.2) | 205 (99.5) | 800 | 176.9 (86.5) | 94 (100) |
| Magnesium (mg) | 330 | 221.0 (112.0) | 174 (84.5) | 330 | 166.0 (56.6) | 92 (97.9) |
| Iron (mg) | 12 | 14.2 (6.8) | 86 (41.8) | 20 | 10.8 (3.7) | 92 (97.9) |
| Manganese (mg) | 4.5 | 4.7 (2.3) | 126 (61.2) | 4.5 | 3.5 (1.3) | 83 (88.3) |
| Zinc (mg) | 12.5 | 5.5 (2.9) | 196 (95.2) | 7.5 | 4.1 (1.5) | 90 (95.7) |
| Copper (mg) | 0.8 | 1.2 (1.2) | 72 (35.0) | 0.8 | 0.9 (0.3) | 53 (56.4) |
| Phosphorus (mg) | 720 | 745.7 (382.1) | 116 (56.3) | 720 | 571.8 (173.0) | 74 (78.7) |
| Selenium (μg) | 60 | 26.3 (15.3) | 200 (97.1) | 60 | 20.2 (10.2) | 93 (98.9) |
Factors associated with low energy and low protein intakes using univariate regression analysis in 300 TB patients
| Associated factors | Energy | Protein | |||
|---|---|---|---|---|---|
| OR (95%CI) |
| OR (95%CI) |
| ||
| Socio-demographic factors | |||||
| Age | 18–49 | 1.0 | 1.0 | ||
| 50–64 | 1.032 (0.498, 2.138) | 0.9319 | 2.039 (0.730, 5.698) | 0.1741 | |
| ≥65 | 2.252 (0.746, 6.797) | 0.1499 | 1.542 (0.498, 4.778) | 0.4530 | |
| Area | Lin county | 1.0 | 1.0 | ||
| Linyun county | 0.639 (0.329, 1.240) | 0.1856 | 1.509 (0.676, 3.369) | 0.3158 | |
| Gender | male | 1.0 | 1.0 | ||
| female | 0.704 (0.358, 1.386) | 0.3098 | 1.092 (0.460, 2.593) | 0.8415 | |
| Severity | mild | 1.0 | 1.0 | ||
| severe | 0.851 (0.425, 1.704) | 0.6486 | 0.859 (0.370, 1.911) | 0.7224 | |
| Education | Primary school and below | 1.0 | 1.0 | ||
| Junior middle school and above | 1.503 (0.547, 2.207) | 0.8780 | 0.923 (0.418, 2.037) | 0.8429 | |
| Marriage | Married | 1.0 | 1.0 | ||
| unmarried | 1.708 (0.781, 3.735) | 0.1797 | 0.859 (0.370, 1.991) | 0.7224 | |
| Occupation | Employed | 1.0 | 1.0 | ||
| Unemployed | 3.364 (1.499, 7.550) | 0.0033 | 1.412 (0.612, 3.257) | 0.4181 | |
| Annual household income | < 20,000 | 1.0 | 1.0 | ||
| 20,000-40,000 | 0.766 (0.333, 1.762) | 0.5311 | 0.905 (0.336, 2.438) | 0.8437 | |
| ≥40,000 | 0.289 (0.097, 0.866) | 0.0266 | 0.499 (0.126, 1.969) | 0.3207 | |
| Behaviroral factors | |||||
| Alcohol consumption | No | 1.0 | 1.0 | ||
| Yes | 1.372 (0.690, 2.731) | 0.3670 | 1.350 (0.585, 3.113) | 0.4821 | |
| Smoking status | Non-smoker | 1.0 | 1.0 | ||
| Smoker | 0.766 (0.399, 1.472) | 0.4243 | 0.482 (0.213, 1.092) | 0.0802 | |
| Eating out-of-home | No | 1.0 | 1.0 | ||
| Yes | 0.628 (0.294, 1.228) | 0.2280 | 0.302 (0.132, 0.693) | 0.0047 | |
Note: Intake above RNI/AI was assigned as 0, intake below RNI/AI was assigned as 1. The sample size of analysis of annual household income was 235
Factors associated with low energy and low protein intakes using multivariate regression analysis in 300 TB patients
| Associated factors | OR (95% CI) |
| ||
|---|---|---|---|---|
| Energy | Age | 18–49 | 1.0 | |
| 50–64 | 1.010 (0.452, 2.260) | 0.9800 | ||
| ≥65 | 1.916 (0.560, 6.555) | 0.3002 | ||
| Gender | Male | 1.0 | ||
| female | 0.512 (0.246, 1.067) | 0.0741 | ||
| Area | Lin county | 1.0 | ||
| Linyun county | 0.631 (0.286, 1.394) | 0.2550 | ||
| Severity | mild | 1.0 | ||
| severe | 1.192 (0.546, 2.605) | 0.6595 | ||
| Occupation | Employed | 1.0 | ||
| Unemployed | 3.542 (1.471, 8.530) | 0.0048 | ||
| Annual household income | < 20,000 | 1.0 | ||
| 20,000-40,000 | 1.242 (0.536, 2.877) | 0.6132 | ||
| ≥40,000 | 0.366 (0.115, 1.163) | 0.0885 | ||
| Protein | Age | 18–49 | 1.0 | |
| 50–64 | 1.460 (0.490, 4.353) | 0.4927 | ||
| ≥65 | 0.985 (0.285, 3.401) | 0.9813 | ||
| Gender | Male | 1.0 | ||
| female | 1.133 (0.468, 2.741) | 0.7817 | ||
| Area | Lin county | 1.0 | ||
| Linyun county | 1.284 (0.489, 3.370) | 0.6122 | ||
| Severity | mild | 1.0 | ||
| severe | 0.690 (0.266, 1.792) | 0.4461 | ||
| Eating out-of-home | No | 1.0 | ||
| Yes | 0.328 (0.133, 0.809) | 0.0155 | ||
Note: Intake above RNI/AI was assigned as 0, intake below RNI/AI was assigned as 1. The sample size of analysis of annual household income was 235