| Literature DB >> 25390898 |
Shaonong Dang1, Hong Yan1, Lingxia Zeng1, Quanli Wang1, Qiang Li1, Shengbin Xiao1, Xiaojing Fan1.
Abstract
OBJECTIVE: To assess the status of the vitamin B12 and folate of Chinese women living in northwest China.Entities:
Mesh:
Substances:
Year: 2014 PMID: 25390898 PMCID: PMC4229226 DOI: 10.1371/journal.pone.0112586
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of the female participants in the study.
| Variables | n | Outcome |
| Residence (%) | ||
| Rural | 794 | 67.9 |
| Urban | 376 | 32.1 |
| Geography (%) | ||
| North | 233 | 19.9 |
| Central | 741 | 63.3 |
| South | 196 | 16.8 |
| Age group (years) (%) | ||
| 10− | 276 | 23.6 |
| 15− | 280 | 23.9 |
| 20− | 117 | 10.0 |
| 30− | 267 | 22.8 |
| 40− | 230 | 19.7 |
| BMI by age | ||
| 10− | 276 | 18.4±2.75 |
| 15− | 264 | 19.8±2.24 |
| 20+ | 614 | 22.7±3.11 |
| Years of schooling by age | ||
| 10− | 274 | 7.44±1.42 |
| 15− | 261 | 9.21±1.45 |
| 20+ | 609 | 9.51±4.16 |
| Source of family income (%) | ||
| Farm only | 285 | 24.8 |
| Migrant working | 270 | 23.5 |
| Government institutions | 139 | 12.1 |
| State-owned Company | 214 | 18.7 |
| Private company | 239 | 20.8 |
| History of catching a cold within 2 weeks (%) | ||
| Yes | 197 | 16.8 |
| No | 956 | 81.7 |
| Anemia (%) | ||
| Yes | 317 | 27.1 |
| No | 847 | 72.4 |
*Few data were missing.
The median and distribution of vitamin B12 and folate by the residence, geographical environment and age.
| Vitamin B12 (pg/mL) | Folate (ng/mL) | |||||||||
| Median (P25, P75) | n(%) | Median (P25, P75) | n(%) | |||||||
| n | <100 | 100- | 200- | 300- | <3 | 3- | 6- | |||
| All women | 1170 | 214.5 | 125 | 407 | 315 | 323 | 4.6 | 172 | 694 | 304 |
| (148.1,311.4) | (10.7) | (34.8) | (26.9) | (27.6) | (3.5,6.0) | (14.7) | (59.3) | (26.0) | ||
| Residence | ||||||||||
| Rural | 794 | 195.9 | 105 | 308 | 208 | 173 | 4.7 | 109 | 468 | 217 |
| (137.4,283.2) | (13.2) | (38.8) | (26.2) | (21.8) | (3.6,6.1) | (13.7) | (58.9) | (27.3) | ||
| Urban | 376 | 254.1 | 20 | 99 | 107 | 150 | 4.4 | 63 | 226 | 87 |
| (182.2,359.9) | (5.3) | (26.3) | (28.5) | (39.9) | (3.4,5.9) | (16.8) | (60.1) | (23.1) | ||
| Geography | ||||||||||
| North | 233 | 188.7 | 40 | 87 | 64 | 42 | 4.5 | 34 | 147 | 52 |
| (126.5,274.1) | (17.2) | (37.3) | (27.5) | (18.0) | (3.5,5.7) | (14.6) | (63.1) | (22.3) | ||
| Central | 741 | 219.6 | 73 | 255 | 190 | 223 | 4.4 | 126 | 450 | 165 |
| (152.2,324.1) | (9.9) | (34.4) | (25.6) | (30.1) | (3.3,5.8) | (17.0) | (60.7) | (22.3) | ||
| South | 196 | 226.8 | 12 | 65 | 61 | 58 | 5.8 | 12 | 97 | 87 |
| (164.2,323.0) | (6.1) | (33.2) | (31.1) | (29.6) | (4.2,7.2) | (6.1) | (49.5) | (44.4) | ||
| Age group (years) | ||||||||||
| 10- | 276 | 233.7 | 23 | 85 | 84 | 84 | 4.4 | 39 | 175 | 62 |
| (163.3,329.6) | (8.3) | (30.8) | (30.4) | (30.4) | (3.4,5.7) | (14.1) | (63.4) | (22.5) | ||
| 15- | 280 | 197.7 | 37 | 110 | 59 | 74 | 4.0 | 57 | 183 | 40 |
| (140.9,304.4) | (13.2) | (39.3) | (21.1) | (26.4) | (3.1,5.3) | (20.4) | (65.3) | (14.3) | ||
| 20- | 117 | 229.8 | 8 | 41 | 33 | 35 | 4.3 | 22 | 71 | 24 |
| (154.4,333.9) | (6.8) | (35.0) | (28.3) | (29.9) | (3.2,5.5) | (18.8) | (60.7) | (20.5) | ||
| 30- | 267 | 216.8 | 29 | 88 | 83 | 67 | 5.0 | 30 | 134 | 103 |
| (144.3,302.4) | (10.9) | (33.0) | (31.1) | (25.1) | (3.9,6.7) | (11.2) | (50.2) | (38.6) | ||
| 40- | 230 | 204.9 | 28 | 83 | 56 | 63 | 5.1 | 24 | 131 | 75 |
| (144.2,309.2) | (12.2) | (36.1) | (24.3) | (27.4) | (4.0,6.6) | (10.4) | (57.0) | (32.6) | ||
*Compared with rural women, urban women had higher vitamin B12 (P<0.001) and lower folate (P = 0.029).
The vitamin B12 in south and central Shaanxi was not different statistically (P = 0.379) but higher than that of north Shaanxi (P<0.001). The folate in north and central Shaanxi was not different statistically (P = 0.576) but lower than that of south Shaanxi (P<0.001).
There were significantly lower vitamin B12 and folate among the women aged 15-19.99 years (P<0.001).
Figure 1Distribution of vitamin B12 and folate by age among Chinese women in Shaanxi province.
Figure 2Prevalence of deficiency in vitamin B12 and folate among Chinese women in Shaanxi province.
Figure 3The relationship between the vitamin B12 and folate among Chinese women in Shaanxi province.
Figure 4Quantile regression and ordinary least squares (OLS) estimates by residence (urban vs rural): folate deficiency and vitamin B12.
Circles represent quantile regression estimates, and the shaded areas around the quantile regression estimates were the 95% confidence intervals. The dashed line was OLS estimate, and the dash-dotted lines showed the OLS 95% confidence interval. Estimates shown here compared folate deficiency with no-deficiency.
Estimated coefficients from and multiple liner regression quantile regression for selected quantiles: vitamin B12 and folate status by residence.*
| Quantile | ||||||||||
| Folate deficiency | 0.05 | 0.10 | 0.25 | 0.45 | 0.50 | 0.75 | 0.85 | 0.95 | OLS | |
| Rural | ||||||||||
| Coefficient | −15.00 | −27.19 | −47.36 | −57.98 | −60.69 | −88.24 | −85.34 | −125.08 | −65.74 | |
|
| 0.011 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.037 | <0.001 | |
| Urban | ||||||||||
| Coefficient | −22.40 | −26.97 | −48.40 | −48.17 | −58.87 | −88.65 | −83.95 | −85.53 | −65.61 | |
|
| 0.136 | 0.013 | 0.026 | 0.006 | <0.001 | 0.01 | 0.065 | 0.458 | 0.018 | |
*Quantile regression model and ordinary least squares (OLS) were used for estimates. In the models the dependent variable was vitamin B12 concentration and folate status (deficiency or not) were regarded as the independent variable controlling for potential affecting factors including age, BMI, education level, geographical region, source of family income and morbidity of cold.
The coefficient here meant the change of vitamin B12 of women with folate deficiency compared with those with normal status of folate.