| Literature DB >> 34691209 |
Yijia Bao1, Jingyi Hu2, Yuenong Qin1.
Abstract
OBJECTIVE: The purpose of this study was to explore the relationship between acute mastitis and the constitution of traditional Chinese medicine (TCM) and the potential risk factors of acute mastitis in Chinese breastfeeding mothers.Entities:
Year: 2021 PMID: 34691209 PMCID: PMC8528590 DOI: 10.1155/2021/2255511
Source DB: PubMed Journal: Evid Based Complement Alternat Med ISSN: 1741-427X Impact factor: 2.629
Judging criteria of the constitution of TCM.
| Constitution of TCM | Score | Results |
|---|---|---|
| Balanced constitution | Conversion score ≥60 points | Yes |
| All biased constitution type's conversion score <30 points | ||
| Conversion score ≥60 points | Prone to be | |
| All biased constitution type's conversion score <40 points | ||
| All the above-mentioned conditions not satisfied | No | |
|
| ||
| Biased constitution type | Conversion score≥40 points | Yes |
| Conversion score 30–39 points | Prone to be | |
| Conversion score<30 points | No | |
Baseline demographic characteristics between the two groups.
| Variables | Case group | Control group |
| |
|---|---|---|---|---|
|
|
| |||
| Educational background | High school or below | 5 (2.7%) | 13 (6.5%) | 0.194 |
| University or college graduates | 142 (77.2%) | 153 (76.1%) | ||
| Master or doctor degree | 37 (20.1%) | 35 (17.4%) | ||
|
| ||||
| Previous history of benign breast diseases | Yes, with prenatal history of breast surgery | 8 (4.3%) | 6 (3.0%) | 0.332 |
| Yes and without a prenatal history of breast surgery | 28 (15.3%) | 22 (10.9%) | ||
| No | 148 (80.4%) | 173 (86.1%) | ||
|
| ||||
| Family history of acute mastitis | Yes | 4 (2.2%) | 0 (0%) | 0.051 |
| No | 180 (97.8%) | 201 (100%) | ||
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| ||||
| Previous history of breast tumors | Benign | 4 (1.6%) | 3 (1.5%) | 0.587 |
| Malignant | 4 (1.6%) | 2 (1%) | ||
Figure 1Distribution of the onset time of acute mastitis.
Distribution of maternity or lactation-related factors between the two groups.
| Variables | Case group | Control group |
| |
|---|---|---|---|---|
|
|
| |||
| Parity | Primipara | 157 (85.3%) | 188 (93.5%) | 0.008 |
| Multipara | 27 (14.7) | 13 (6.5%) | ||
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| ||||
| Primiparity age | 18–28 years old | 62 (33.7%) | 113 (56.2%) | <0.001 |
| 29–35 years old | 110 (59.8%) | 83 (41.3%) | ||
| 36–45 years old | 12 (6.5%) | 5 (2.5%) | ||
|
| ||||
| Mode of delivery | Vaginal delivery | 102 (55.4%) | 110 (54.7%) | 0.845 |
| Cesarean section | 80 (43.5%) | 90 (44.8%) | ||
| Delivery with forceps | 2 (1.1%) | 1 (0.5%) | ||
|
| ||||
| Fetal status | Fetal full-term | 149 (81.0%) | 193 (96.0%) | <0.001 |
| Preterm birth | 16 (8.7%) | 5 (2.5%) | ||
| Fetal overdue birth | 19 (10.3%) | 3 (1.5%) | ||
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| ||||
| Postpartum colostrum | ≤24 hours | 75 (40.8%) | 126 (62.7%) | <0.001 |
| 25–48 hours | 44 (23.9%) | 57(28.3%) | ||
| 49–72 hours | 46 (25%) | 13 (6.5%) | ||
| ≥72 hours | 19 (10.3%) | 5 (2.5%) | ||
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| First lactation time after delivery | ≤24 hours | 79 (42.9%) | 111(55.2%) | <0.001 |
| 25–48 hours | 40 (21.7%) | 62 (30.8%) | ||
| 49–72 hours | 35 (19.0%) | 19 (9.5%) | ||
| ≥72 hours | 30 (16.3%) | 9 (4.5%) | ||
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| Times of breastfeeding each day | ≤2 times | 7 (3.8%) | 1 (0.5%) | <0.001 |
| 3–6 times | 88 (47.8%) | 143 (71.1%) | ||
| ≥7 times | 89 (48.4%) | 57 (28.4%) | ||
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| Time of consecutive feeds with same breast | ≤10 minutes | 17 (9.2%) | 8 (4.0%) | <0.001 |
| 10–15 minutes | 80 (43.5%) | 61 (30.3%) | ||
| 16–30 minutes | 70 (38.0%) | 128 (63.7%) | ||
| ≥30 minutes | 17 (9.2%) | 4 (2.0%) | ||
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| Milk yield | Insufficient | 54 (29.4%) | 45 (22.4%) | 0.285 |
| Adequate or redundant | 111 (60.3%) | 135 (67.2%) | ||
| Surplus | 19 (10.3%) | 21 (10.4%) | ||
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| Milk pump damage | Yes | 152 (82.6%) | 174 (86.6%) | 0.281 |
| No | 32 (17.4%) | 27 (13.4%) | ||
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| Lactagogue food | Yes | 74 (40.2%) | 95 (47.3%) | 0.164 |
| No | 110 (59.8%) | 106 (52.7%) | ||
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| Crater nipple | Yes | 34 (18.5%) | 43 (21.4%) | 0.475 |
| No | 150 (81.5%) | 158 (78.6%) | ||
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| Times of nipple cleansing each day | ≤1 times | 79 (43.0%) | 35 (17.4%) | <0.001 |
| 2–3 times | 58 (31.5%) | 60 (29.9%) | ||
| ≥4 times | 47 (25.5%) | 106 (52.7%) | ||
∗∗ P < 0.001 between the groups.
Multivariable Logistic Regression analysis of risk factors for acute mastitis.
| Variables |
| Wald |
| OR | 95% CI for EXP (B) | |
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| Primiparity age | 0.126 | 10.306 | 0.001 | 1.135 | 1.050 | 1.226 |
| Mode of delivery | −0.613 | 5.365 | 0.021 | 0.541 | 0.322 | 0.910 |
| Postpartum colostrum | 0.555 | 12.680 | <0.001 | 1.742 | 1.283 | 2.364 |
| Times of breastfeeding each day | 0.389 | 4.653 | 0.031 | 1.475 | 1.036 | 2.100 |
| Frequency of nipple cleansing | −0.725 | 19.059 | <0.001 | 0.484 | 0.350 | 0.671 |
| Nipple infection | 1.964 | 37.573 | <0.001 | 7.128 | 3.804 | 13.357 |
| Improper diet | 1.273 | 17.500 | <0.001 | 3.573 | 1.967 | 6.488 |
| Emotional stimulation | 0.658 | 4.606 | 0.032 | 1.930 | 1.059 | 3.519 |
| Parity | 1.620 | 13.177 | <0.001 | 5.053 | 2.107 | 12.118 |
| Constants | −4.735 | 12.903 | <0.001 | 0.009 | — | — |
∗∗ P < 0.001 between the groups.
Logistic regression subgroup analysis for nipple infection, improper diet, and emotional stimulation.
| Variances | b | Wald |
| OR | 95% CI for EXP (B) | ||
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| Nipple infection | Infant bite | 1.052 | 9.375 | 0.002 | 2.863 | 1.460 | 5.615 |
| Milk pump damage | 2.605 | 11.973 | 0.001 | 13.529 | 3.094 | 59.159 | |
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| Improper diet | Spicy food | 1.690 | 6.642 | 0.010 | 5.420 | 1.499 | 19.598 |
|
| 1.690 | 6.642 | 0.010 | 5.420 | 1.499 | 19.598 | |
|
| 1.112 | 15.181 | <0.001 | 3.042 | 1.738 | 5.323 | |
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| |||||||
| Emotional stimulation | Melancholy | 1.113 | 13.355 | <0.001 | 3.043 | 1.675 | 5.526 |
Warm food was defined as food having “warm, bright, or outward” attributes, such as spicy food, fatty meat, or broth and fruits like orange, dates, and bayberries, according to traditional Chinese medicine (TCM). ∗∗P < 0.001 between the groups.
Binary logistic regression analysis of risk factors for acute mastitis in the constitution of TCM.
| Variances |
| Wald |
|
| 95% CI for EXP (B) | |
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| BC | −1.021 | 9.558 | 0.002 | 0.360 | 0.189 | 0.688 |
| QDC | 0.931 | 7.519 | 0.006 | 2.536 | 1.304 | 4.933 |
| YADC | 0.061 | 0.038 | 0.845 | 1.063 | 0.575 | 1.966 |
| YIDC | −0.028 | 0.007 | 0.935 | 0.973 | 0.500 | 1.893 |
| PDC | 0.132 | 0.116 | 0.734 | 1.141 | 0.534 | 2.440 |
| DHC | 0.562 | 1.481 | 0.224 | 1.755 | 0.709 | 4.341 |
| BSC | 0.027 | 0.004 | 0.949 | 1.027 | 0.451 | 2.341 |
| QSC | −0.056 | 0.031 | 0.861 | 0.945 | 0.505 | 1.769 |
| ISC | 0.295 | 0.222 | 0.638 | 1.343 | 0.394 | 4.575 |
| Constants | 0.913 | 2.364 | 0.124 | 2.491 | — | — |
Multivariable logistic regression analysis of risk factors for acute mastitis in the constitution of TCM.
| Variances |
| Wald |
|
| 95% CI for EXP (B) | |
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| BC | −1.158 | 26.701 | <0.001 | 0.314 | 0.202 | 0.487 |
| QDC | 0.958 | 8.992 | 0.003 | 2.605 | 1.393 | 4.871 |
| Constants | 1.190 | 11.354 | 0.001 | 3.286 | — | — |
∗∗ P < 0.001 between the groups.
Figure 2Icicle plots of constitution types in traditional Chinese medicine in the case and the control group. The horizontal axis represents nine types of TCM constitution types clustered, while the vertical axis indicates that these nine types of constitution are clustered into several categories, which demonstrated the classification results of TCM constitution types when clustered into different categories.
Figure 3Dendrogram of constitution of TCM in the case and the control group. The horizontal axis represents the relative distances of various categories after clustering, which is a general change of the distances between categories; the vertical axis is the object of clustering.
Figure 4Distribution of biased physical symptoms in postpartum whose symptoms were aggravated.
Figure 5Distribution of biased physical symptoms in postpartum whose symptoms were relieved.