Abstract
Objectives: Restrictive spirometric pattern (RSP) has a prevalence of 5.4–9.2% and is associated with various respiratory symptoms, comorbidities, and increased mortality. Breastfeeding has important effects on maternal health; however, the effects of breastfeeding on pulmonary function remain unclear. This study aimed to investigate the effects of breastfeeding on maternal pulmonary function, particularly the risk of RSP. Methods: Retrospective, cross-sectional observational study enrolling parous women aged >40 years who participated in the Korea National Health and Nutrition Examination Survey from 2013–2018. RSP was defined using the FEV1/FVC ratio and FVC outcomes of the pulmonary function test. The adjusted odds ratios (OR) for RSP were calculated using multivariate logistic regression. Results: Of 9261 parous women, 913 (9.9%) had RSP. Breastfeeding (≥1 month) was associated with a reduced risk of RSP (OR: 0.75 [0.60–0.92]) when adjusted for age, body mass index, smoking status, other diseases, socioeconomic status, and maternal risk factors. The adjusted ORs for RSP for women decreased further with increasing duration of breastfeeding (p for trend: 0.0004). The FEV1, FVC, and FVC% were higher in women who breastfed than in those who did not breastfeed (by 0.0390 L, 0.0521 L, 0.9540% p, respectively). Conclusions: There is an association between breastfeeding and pulmonary function in parous women. Breastfeeding was associated with a lower prevalence of RSP in parous women aged >40 years old, suggesting that breastfeeding may have a beneficial effect on maternal pulmonary function.
Keywords: breastfeeding, pulmonary function, restrictive lung disease, restrictive spirometric pattern, parous women
1. Introduction
Most diseases of the respiratory system are classified into three categories according to their patterns: restrictive lung diseases, obstructive lung diseases, and vascular diseases [1,2,3]. Restrictive lung disease is characterized by a decrease in total lung volume due to restricted lung expansion. This causes the patients’ breathing to become more difficult, leading to inefficient ventilation and oxygenation [2,4]. Restrictive lung disease can be classified into three types depending on its pathophysiology: parenchymal disease, neuromuscular weakness, and chest wall/pleural diseases [5]. Each heterogeneous set of diseases includes hundreds of specific diagnoses [1,2,3,4,5].
Restrictive lung disease can be diagnosed with a low total lung capacity (TLC) and a normal FEV1/FVC ratio. The threshold values for TLC and FEV1/FVC ratios are 80% of the reference value and 0.7, respectively [6,7]. However, TLC measurement is rarely used in clinical practice to diagnose restrictive lung disease due to the technical limitations of spirometry. Instead, a restrictive spirometric pattern (RSP), determined by FEV1/FVC ratio ≥ 70% and FVC% < 80%, is often used [6,7]. RSP is common in the general population, with a prevalence ranging from 5.4% to 9.2% in data from the US National Health and Nutrition Examination Survey (NHANES) [7,8]. Recently, RSP has been reported to be associated with an increased incidence of respiratory symptom burden [9,10], functional limitations, such as higher mMRC dyspnea scores [11], comorbidities (such as metabolic syndrome and diabetes mellitus [12,13]), and adverse outcomes, including increased mortality [7,9].
Breastfeeding is a major health concern worldwide. Previous studies have shown that breastfeeding is beneficial for both mothers and children [14,15]. In particular, breastfeeding has recently been shown to reduce the risk of chronic diseases such as cardiovascular disorders, including hypertension, type II diabetes mellitus, metabolic syndrome, NAFLD, and ovarian cancer in parous women [16,17]. However, to the best of our knowledge, no study has investigated the relationship of breastfeeding with RSP or pulmonary function in parous women. Therefore, this study aimed to identify the effects of breastfeeding on maternal pulmonary function, especially the risk of RSP, in women aged >40 years using representative nationwide survey data. Furthermore, this study investigated whether the duration of breastfeeding was related to the risk of RSP.
2. Methods
2.1. Data Source, Study Design, and Population
The Korean NHANES (KNHANES) is a nationwide cross-sectional survey conducted by the Korea Disease Control and Prevention Agency (KCDA) to assess the health and nutritional status of the Korean population [18].
We collected data from women aged over 40 years who participated in the KNHANES from January 2013 to December 2018 (n = 15,142). We excluded participants with no history of childbirth (n = 2097), during pregnancy or breastfeeding (n = 26), with missing information about breastfeeding (n = 179), pulmonary function test (PFT, n = 3442), or regarding other variables (n = 137). Finally, 9261 women aged over 40 years with a history of childbirth were analyzed (Figure 1).
Figure 1.
Flow chart of study population selection.
2.2. Study’s Main Variables
A restrictive spirometric pattern (RSP) was defined as a pre-bronchodilator FEV1/FVC ≥ 70% and FVC < 80% using the pulmonary function test, according to the ATS criteria (fixed-ratio criteria) [19]. Information on breastfeeding was extracted from the KNHANES survey. Experienced researchers investigated the history and total duration of breastfeeding through interviews. Based on the survey question, “Have you ever breastfed for more than 1 month?” those who answered “no” were defined as the non-breastfeeding group. For those in the breastfeeding group, the breastfeeding period was evaluated for at least one month of breastfeeding. The duration of breastfeeding was then categorized into 1–6 months, 7–12 months, 13–18 months, 19–24 months, and more than 24 months.
2.3. Covariates and Measurements
We extracted the following data from the KNHANES database for the analyses: duration of breastfeeding; FEV1, FVC, and FVC% in PFTs; RSP; COPD; age; height; body weight; smoking status; history of asthma, pulmonary tuberculosis, hypertension, and diabetes mellitus; region; employment status; education level; household income level; number of pregnancies; number of children breastfed; age at menarche; age at first delivery; and age at the last delivery.
The body mass index (BMI) was calculated as body weight per square of height (kg/m2), and participants were categorized into underweight (<18.5 kg/m2), normal (≥18.5 to <25 kg/m2), and obese (≥25 kg/m2) according to BMI values. Smoking status was classified as ever smoker, former smoker, or never smoker. An ever smoker refers to a person who smoked more than 100 cigarettes during their lifetime, and a former smoker is a person who smoked less than 100 cigarettes during their lifetime and now does not smoke. Never smoked was defined as an individual who had never smoked in their life. The region was categorized into capital (including Seoul, Incheon, and Gyeonggi-do) and non-capital regions. Employment status was classified into three categories: blue-collar (labor type workers), white-collar (administrative, managerial type workers), and unemployed workers. The educational level was categorized into four categories according to the highest level of education: elementary or lower, middle, high or secondary, and college or higher. Household income levels were categorized into quartiles: very low, low, high, and very high. Spirometry (PFT) was performed to measure the FEV1, FVC, and FVC%. Dry rolling seal spirometers, which were used until June 2016, were replaced with vyntus spiro in July 2016.
2.4. Statistical Analysis
All statistical analyses were performed using SAS software (version 9.4; SAS Institute, Cary, NC, USA). Categorical variables are expressed as numbers and proportions (%), and continuous variables are expressed as medians (interquartile ranges).
Differences in variables between participants with and without RSP and differences between participants who had breastfed and those who did not were evaluated using chi-square tests. The association between breastfeeding and RSP was calculated using multivariate logistic regression, which was adjusted for age, smoking status, asthma, pulmonary tuberculosis, hypertension, diabetes mellitus (diagnosed vs. never diagnosed), region of residence, employment, education level, house income level, parity, age at menarche, age at the first delivery, age at the last delivery, and examined year.
To assess whether a linear relationship existed between each categorical variable and RSP, it was defined as a continuous variable, and multiple logistic regression was performed (p for trend). The association between breastfeeding duration in six categories and RSP was also tested by multivariate logistic regression adjusted for the same covariables as presented above. The generalized linear method was used to determine the relationship between breastfeeding and secondary outcomes, including FEV1 (L), FVC (L), FVC percentage (%), and FEV1/FVC ratio, and a generalized linear method was used.
Finally, pre-specified subgroup analyses were performed to assess the consistency of the association between breastfeeding and RSP among various subgroups. Subgroups were defined using the same covariables used in multiple logistic regression, and interaction tests were used to determine the potential interaction effect between breastfeeding and the covariables (p for interaction). All variables with a p-value < 0.05 were considered statistically significant.
3. Results
3.1. Demographic Characteristics of the Participants
The demographic characteristics of the participants are summarized in Table 1 and Supplementary Table S1. A total of 9261 participants were included in this study. Among them, 913 (9.9%) had RSP, and 1328 (14.3%) did not breastfeed. The mean (SD) values of participants were 57.5 (10.7) years for age, 24.0 (3.2) kg/m2 for BMI, 2.30 (0.45) L for FEV1, 2.91 (0.51) L for FVC, 92.76% (11.58%) for FVC%, and 0.79 (0.06) for FEV1/FVC ratio, respectively. Compared with the non-RSP group, the RSP group had a higher mean age (61.7 vs. 57.0 years), BMI (25.4 vs. 23.9 kg/m2), and age at menarche (14.8 vs. 14.5 years), and lower age at the first delivery (24.4 vs. 25.1 years) and at the last delivery (29.2 vs. 29.5 years).
Table 1.
Demographic characteristics of participants according to restrictive spirometric pattern.
| Variables | Total (n) | RSP | Non-RSP | p-Value | |||
|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | ||
| 9261 | 913 | 9.9 | 8348 | 90.1 | |||
| Breastfeeding duration (months) | 0.0006 | ||||||
| None | 1328 | 14.3 | 128 | 9.6 | 1200 | 90.4 | |
| Yes | 7933 | 85.7 | 785 | 9.9 | 7148 | 90.1 | |
| 1–6 | 1247 | 13.5 | 96 | 7.7 | 1151 | 92.3 | |
| 7–12 | 1051 | 11.3 | 87 | 8.3 | 964 | 91.7 | |
| 13–18 | 780 | 8.4 | 65 | 8.3 | 715 | 91.7 | |
| 19–24 | 1487 | 16.1 | 150 | 10.1 | 1337 | 89.9 | |
| 25- | 3368 | 36.4 | 387 | 11.5 | 2981 | 88.5 | |
| Age (years) | 57.5 (10.7) † | 61.7 (10.4) † | 57.0 (10.6) † | <0.0001 | |||
| 40–49 | 2519 | 27.2 | 126 | 5.0 | 2393 | 95.0 | |
| 50–59 | 2925 | 31.6 | 263 | 9.0 | 2662 | 91.0 | |
| 60–69 | 2306 | 24.9 | 269 | 11.7 | 2037 | 88.3 | |
| 70–79 | 1369 | 14.8 | 222 | 16.2 | 1147 | 83.8 | |
| 80+ | 142 | 1.5 | 33 | 23.2 | 109 | 76.8 | |
| BMI (kg/m2) | 24.0 (3.2) † | 25.4 (3.8) † | 23.9 (3.2) † | <0.0001 | |||
| Underweight | 189 | 2.0 | 20 | 10.6 | 169 | 89.4 | |
| Obese | 3127 | 33.8 | 466 | 14.9 | 2661 | 85.1 | |
| Normal | 5945 | 64.2 | 427 | 7.2 | 5518 | 92.8 | |
| FEV1 (L) | 2.30 (0.45) † | 1.81 (0.30) † | 2.36 (0.43) † | ||||
| FVC (L) | 2.91 (0.51) † | 2.27 (0.32) † | 2.98 (0.48) † | ||||
| FVC Percentage (%) | 92.76 (11.58) † | 74.22 (5.30) † | 94.79 (10.20) † | ||||
| FEV1/FVC | 0.79 (0.06) † | 0.80 (0.05) † | 0.79 (0.06) † | ||||
| Smoking status | 0.6915 | ||||||
| Ever (less than 100) | 76 | 0.8 | 8 | 10.5 | 68 | 89.5 | |
| Ever (more than 100) | 619 | 6.7 | 55 | 8.9 | 564 | 91.1 | |
| Never | 8566 | 92.5 | 850 | 9.9 | 7716 | 90.1 | |
| Asthma | 0.0580 | ||||||
| Diagnosed | 307 | 3.3 | 40 | 13.0 | 267 | 87.0 | |
| Never diagnosed | 8954 | 96.7 | 873 | 9.7 | 8081 | 80.3 | |
| Pulmonary tuberculosis | 0.0937 | ||||||
| Diagnosed | 326 | 3.5 | 41 | 12.6 | 285 | 87.4 | |
| Never diagnosed | 8935 | 96.5 | 872 | 09.8 | 8063 | 90.2 | |
| Hypertension | <0.0001 | ||||||
| Diagnosed | 2515 | 27.2 | 368 | 14.6 | 2147 | 85.4 | |
| Never diagnosed | 6746 | 72.8 | 545 | 08.1 | 6201 | 91.9 | |
| Diabetes Mellitus | <0.0001 | ||||||
| Diagnosed | 860 | 9.3 | 153 | 17.8 | 707 | 82.2 | |
| Never diagnosed | 8401 | 90.7 | 760 | 9.0 | 7641 | 91.0 | |
| Region | 0.1346 | ||||||
| Capital | 4366 | 47.1 | 409 | 9.4 | 3957 | 90.6 | |
| Non-Capital | 4895 | 52.9 | 504 | 10.3 | 4391 | 89.7 | |
| Employment status | <0.0001 | ||||||
| Blue-collar worker | 1863 | 20.1 | 194 | 10.4 | 1669 | 89.6 | |
| White-collar worker | 2900 | 31.3 | 220 | 7.6 | 2680 | 92.4 | |
| Unemployed | 4498 | 48.6 | 499 | 11.1 | 3999 | 88.9 | |
| Education level | <0.0001 | ||||||
| Elementary or lower | 2863 | 30.9 | 366 | 12.8 | 2497 | 87.2 | |
| Middle school | 1334 | 14.4 | 149 | 11.2 | 1185 | 88.8 | |
| High school | 3054 | 33.0 | 263 | 8.6 | 2791 | 91.4 | |
| College or higher | 2010 | 21.7 | 135 | 6.7 | 1875 | 93.3 | |
| House income level | <0.0001 | ||||||
| Very low | 1940 | 20.9 | 253 | 13.0 | 1687 | 87.0 | |
| Low | 2340 | 25.3 | 233 | 10.0 | 2107 | 90.0 | |
| High | 2329 | 25.1 | 226 | 9.7 | 2103 | 90.3 | |
| Very high | 2652 | 28.6 | 201 | 7.6 | 2451 | 92.4 | |
| Parity | 0.0052 | ||||||
| Primipara | 347 | 3.7 | 19 | 5.5 | 328 | 94.5 | |
| Multipara | 8914 | 96.3 | 894 | 10.0 | 8020 | 90.0 | |
| Age at menarche | 14.6 (1.9) † | 14.8 (2.0) † | 14.5 (1.9) † | 0.0010 | |||
| <15 years | 4850 | 52.4 | 431 | 8.9 | 4419 | 91.1 | |
| ≥15 years | 4411 | 47.6 | 482 | 10.9 | 3929 | 89.1 | |
| Age at the first delivery | 25.0 (3.9) † | 24.4 (3.8) † | 25.1 (3.9) † | <0.0001 | |||
| <25 years | 4541 | 49.0 | 514 | 11.3 | 4027 | 88.7 | |
| ≥25 years | 4720 | 51.0 | 399 | 8.5 | 4321 | 91.5 | |
| Age at the last delivery | 29.5 (4.3) † | 29.2 (4.2) † | 29.5 (4.3) † | 0.2097 | |||
| <30 years | 5093 | 55.0 | 520 | 10.2 | 4573 | 89.8 | |
| ≥30 years | 4168 | 45.0 | 393 | 9.4 | 3775 | 90.6 | |
| Examined year | <0.0001 | ||||||
| 2013 | 1478 | 16.0 | 127 | 8.6 | 1351 | 91.4 | |
| 2014 | 1413 | 15.3 | 96 | 6.8 | 1317 | 93.2 | |
| 2015 | 1455 | 15.7 | 119 | 8.2 | 1336 | 91.8 | |
| 2016 | 1687 | 18.2 | 218 | 12.9 | 1469 | 87.1 | |
| 2017 | 1551 | 16.7 | 176 | 11.3 | 1375 | 88.7 | |
| 2018 | 1677 | 18.1 | 177 | 10.6 | 1500 | 89.4 | |
† Values are presented as mean (SE).
3.2. Association between RSP and Breastfeeding
The result of logistic regression analysis on the association between RSP and the breastfeeding group showed a lower adjusted odds ratio (OR) for RSP among the breastfeeding group (OR: 0.75 [0.60–0.92], p = 0.007; Table 2). By classifying the duration of breastfeeding, adjusted ORs for RSP in participants with breastfeeding durations of 1–6 months, 7–12 months, 13–18 months, 19–24 months, and more than 24 months compared with the non-breastfeeding group were 0.86 [0.65–1.14], 0.79 [0.59–1.06], 0.82 [0.60–1.14], 0.74 [0.57–0.96], and 0.63 [0.49–0.81], respectively. The p-value for the trend according to breastfeeding was 0.0004.
Table 2.
Association of restrictive spirometric pattern according to breastfeeding or duration of breastfeeding.
| Variables | OR | 95% CI | p-Value | p-Value for Trend |
|---|---|---|---|---|
| Breastfeeding duration | ||||
| Yes | 0.75 | (0.60–0.92) | 0.0067 | 0.0004 |
| 1–6 | 0.86 | (0.65–1.14) | 0.2918 | |
| 7–12 | 0.79 | (0.59–1.06) | 0.1195 | |
| 13–18 | 0.82 | (0.60–1.14) | 0.2358 | |
| 19–24 | 0.74 | (0.57–0.96) | 0.0257 | |
| 25– | 0.63 | (0.49–0.81) | 0.0003 | |
| None | 1.00 | |||
| Age | <0.0001 | |||
| 40–49 | 0.22 | (0.13–0.36) | <0.0001 | |
| 50–59 | 0.39 | (0.25–0.63) | <0.0001 | |
| 60–69 | 0.51 | (0.33–0.79) | 0.0028 | |
| 70–79 | 0.74 | (0.48–1.14) | 0.1671 | |
| 80+ | 1.00 | |||
| BMI | <0.0001 | |||
| Underweight | 1.76 | (1.08–2.85) | 0.0224 | |
| Obese | 2.00 | (1.73–2.31) | <0.0001 | |
| Normal | 1.00 | |||
| Smoking status | 0.8768 | |||
| Ever (less than 100) | 1.40 | (0.66–2.98) | 0.3816 | |
| Ever (more than 100) | 0.96 | (0.71–1.29) | 0.7746 | |
| Never | 1.00 | |||
| Asthma | 0.5878 | |||
| Diagnosed | 1.10 | (0.78–1.57) | 0.5878 | |
| Never diagnosed | 1.00 | |||
| Pulmonary tuberculosis | 0.1737 | |||
| Diagnosed | 1.27 | (0.90–1.79) | 0.1737 | |
| Never diagnosed | 1.00 | |||
| Hypertension | 0.0437 | |||
| Diagnosed | 1.19 | (1.01–1.40) | 0.0437 | |
| Never diagnosed | 1.00 | |||
| Diabetes Mellitus | 0.0003 | |||
| Diagnosed | 1.46 | (1.19–1.79) | 0.0003 | |
| Never diagnosed | 1.00 | |||
| Region | 0.4792 | |||
| Capital | 0.95 | (0.82–1.10) | 0.4792 | |
| Non-Capital | 1.00 | |||
| Employment status | 0.7790 | |||
| Blue-collar worker | 1.01 | (0.84–1.21) | 0.9578 | |
| White-collar worker | 0.97 | (0.81–1.17) | 0.7492 | |
| Unemployed | 1.00 | |||
| Education level | 0.2958 | |||
| Elementary or lower | 0.91 | (0.68–1.21) | 0.5028 | |
| Middle school | 1.03 | (0.77–1.37) | 0.8614 | |
| High school | 1.08 | (0.86–1.36) | 0.5124 | |
| College or higher | 1.00 | |||
| House income level | 0.7543 | |||
| Very high | 1.00 | (0.79–1.26) | 0.9784 | |
| High | 1.16 | (0.93–1.44) | 0.1852 | |
| Low | 1.02 | (0.83–1.25) | 0.8766 | |
| Very low | 1.00 | |||
| Parity | 0.0912 | |||
| Primipara | 0.66 | (0.41–1.07) | 0.0912 | |
| Multipara | 1.00 | |||
| Age at menarche | 0.3458 | |||
| <15 years | 1.08 | (0.92–1.26) | 0.3458 | |
| ≥15 years | 1.00 | |||
| Age at the first delivery | 0.9210 | |||
| <25 years | 0.99 | (0.84–1.17) | 0.921 | |
| ≥25 years | 1.00 | |||
| Age at the last delivery | 0.1757 | |||
| <30 years | 1.11 | (0.95–1.30) | 0.1757 | |
| ≥30 years | 1.00 | |||
| Examined year | 0.0002 | |||
| 2013 | 0.83 | (0.65–1.06) | 0.1403 | |
| 2014 | 0.63 | (0.49–0.83) | 0.0007 | |
| 2015 | 0.75 | (0.58–0.96) | 0.0232 | |
| 2016 | 1.20 | (0.96–1.49) | 0.1056 | |
| 2017 | 1.06 | (0.85–1.33) | 0.6027 | |
| 2018 | 1.00 | |||
| Values are presented as adjusted odds ratio (95% confidence interval). | ||||
For other independent variables, underweight and obese participants had higher ORs for RSP than those of normal participants. (OR: 1.76 [1.08–2.85], 2.00 [1.73–2.31], respectively); and participants with hypertension and diabetes mellitus had higher ORs for RSP compared with participants without hypertension and diabetes mellitus. (OR: 1.19 [1.01–1.40], 1.46 [1.19–1.79], respectively)
3.3. Correlation between Breastfeeding and the Results of the Respiratory Function Test
In reference to the non-breastfeeding group, the breastfeeding group had a higher FEV1 (by 0.0390 L, p = 0.0001), FVC (by 0.0521 L, p < 0.0001), and FVC percentage (by 0.9540% p, p = 0.0051). The FEV1/FVC ratio showed no statistically significant difference (p = 0.1956). The p-values for the trend by the duration of breastfeeding were 0.0004 for FEV1, <0.0001 for FVC, 0.0002 for FVC %, and 0.1956 for the FEV1/FVC ratio (Table 3).
Table 3.
Coefficients of pulmonary function test results according to breastfeeding or duration of breastfeeding.
| FT Results | Variables | Coefficient | p-value | p-Value for Trend |
|---|---|---|---|---|
| FEV1 | Breastfeeding | |||
| Ever | 0.0390 | 0.0001 | 0.0004 | |
| 1–6 | 0.0303 | 0.0213 | ||
| 7–12 | 0.0421 | 0.0023 | ||
| 13–18 | 0.0296 | 0.0498 | ||
| 19–24 | 0.0385 | 0.0033 | ||
| 25– | 0.0506 | <0.0001 | ||
| Never | (reference) | |||
| FVC | Breastfeeding | |||
| Ever | 0.0521 | <0.0001 | <0.0001 | |
| 1–6 | 0.0407 | 0.0112 | ||
| 7c12 | 0.0461 | 0.0062 | ||
| 13–18 | 0.0422 | 0.0219 | ||
| 19–24 | 0.0521 | 0.0011 | ||
| 25– | 0.0732 | <0.0001 | ||
| Never | (reference) | |||
|
FVC
percentage (%) |
Breastfeeding | |||
| Ever | 0.9540 | 0.0051 | 0.0002 | |
| 1–6 | 0.7174 | 0.1007 | ||
| 7–12 | 0.6514 | 0.1552 | ||
| 13–18 | 0.3390 | 0.4989 | ||
| 19–24 | 1.0267 | 0.0181 | ||
| 25– | 1.6906 | <0.0001 | ||
| Never | (reference) | |||
| FEV1/FVC | Breastfeeding | |||
| Ever | −0.0006 | 0.7038 | 0.1956 | |
| 1–6 | −0.0002 | 0.9264 | ||
| 7–12 | 0.0015 | 0.4928 | ||
| 13–18 | −0.0012 | 0.6094 | ||
| 19–24 | −0.0007 | 0.7334 | ||
| 25– | −0.0023 | 0.2588 | ||
| Never | (reference) | |||
3.4. Subgroup Analyses
Figure 2 shows a forest plot of subgroup analyses. In pre-specified subgroup analyses, subgroups defined by employment status (unemployed vs. white-collar worker vs. blue-collar worker) showed statistically significant interactions with breastfeeding years (p = 0.0218).
Figure 2.
Forest plot of subgroup analysis of the association between breastfeeding and restrictive spirometric pattern stratified by covariates.
Among the three subpopulations, the OR of having RSP in the breastfeeding group compared with the non-breastfeeding group was lowest in the subpopulation who were unemployed (OR: 0.60 [0.45–0.80]), middle in the subpopulation of blue-collar workers (OR: 0.78 [0.45–1.36]), and highest in the subpopulation of white-collar workers (OR: 1.00 [0.67–1.49]). However, the subgroups defined by other variables did not show significant interaction effects with breastfeeding.
4. Discussion
In this study, we demonstrated a negative correlation between breastfeeding and RSP in parous women, despite adjusting for all possible confounder variables. According to our main analysis, the risk of RSP in women with a history of breastfeeding was approximately 25% lower than in those with no history of breastfeeding. (OR: 0.75 [0.60–0.92], p:0.007) This protective effect of breastfeeding against RSP was also consistently observed in most of the subgroups. The subpopulation diagnosed with diabetes mellitus (OR: 1.08 [0.55–2.10]) and those with a lower BMI (OR: 1.66 [0.34–8.09]) were the only exceptions; however, the relationship between breastfeeding and RSP was not statistically significant in these two subgroups. Additionally, the adjusted OR decreased further with increasing the duration of breastfeeding. (p for trend: 0.0004) The risk of RSP in women who breastfed for 19–24 months and more than 24 months was significantly lower compared with the non-breastfeeding group (OR: 0.74 [0.57–0.96], 0.63 [0.49–0.81], respectively), while women who did for 1–6 months, 7–12 months, 13–18 months were not (0.86 [0.65–1.14], 0.79 [0.59–1.06], 0.82 [0.60–1.14]). This suggests that the protective effect of breastfeeding against RSP may be strengthened by increasing the duration of breastfeeding. Other factors independently associated with an increased risk of RSP were age, BMI, doctor-diagnosed hypertension, and doctor-diagnosed diabetes mellitus. These risk factors have already been identified in previous studies based on KHANES and US NHANES. [12,13,20]
Many recent studies have shown the health effects of breastfeeding on mothers. As breastfeeding suppresses gonadotropins, breastfeeding probably has protective effects against ovarian cancer. [17] Additionally, breastfeeding activates central neuroendocrine pathways, including oxytocin and prolactin, and lactation itself positively affects glucose and insulin homeostasis. These findings may explain the protective effects of breastfeeding against hypertension and type 2 diabetes mellitus. Breastfeeding has also been reported to be associated with a lower incidence of other diseases, including metabolic syndrome, obesity [16,17], Alzheimer’s disease [21], gall bladder disease [22], rheumatoid arthritis [23], hip fractures, and osteoporosis [24]. However, before this study, the association between breastfeeding and pulmonary function had not been investigated.
Since spirometry cannot measure TLC, restrictive lung disease cannot be diagnosed by spirometry alone, whereas RSP can be defined by FEV1 and FVC. Although RSP does not reflect the actual lung volume, studies have reported that it is also meaningful [25]. First, RSP is associated with a higher burden of chronic respiratory symptoms and functional limitations [9,10,11]. According to Soriano et al., the patient group with RSP showed more phlegm, dyspnea, and wheezing than the normal group and reported a significant worsening of the mMRC dyspnea score, which is comparable to the COPD group [10]. Second, RSP is related to comorbidities, such as obesity, metabolic syndrome, and diabetes mellitus [12,13]. Third, RSP is associated with adverse outcomes, such as lung cancer, cardiovascular disease, and increased mortality. According to a large study in Sweden, RSP is an independent predictor of lung cancer, especially squamous cell carcinoma and small cell carcinoma, but not adenocarcinoma [26]. Finally, it has been reported that RSP is associated with increased mortality [7,9].
Although the biological mechanisms underlying the protective effects of breastfeeding against RSP are unclear, one possible key mechanism that could explain the relationship between the two is systemic inflammation. Mannino et al. showed that the presence of RSP was associated with higher levels of systemic CRP and fibrinogen and that the levels of markers were comparable with those of moderate COPD [6]. Additionally, previous studies have shown that systemic inflammation is associated with impaired lung function, especially lower FVC. Several studies have shown that decreased FVC is associated with higher levels of CRP [27], fibrinogen [28], and other inflammation-sensitive plasma proteins (haptoglobin, ceruloplasmin, α1-antitrypsin, and orosomucoid) [29]. According to a prospective cohort study conducted by Ahn et al., the level of the pro-inflammatory cytokine IL-6 at 6 months postpartum was lower in women who primarily practiced breastfeeding than in women who practiced bottle feeding [30]. Groer et al. also showed that exclusively breastfeeding mothers were more likely to have lower IFN-γ levels and IFN-γ/IL-10 ratios at weeks 4 to 6 postpartum than exclusively formula-feeding mothers [31]. Together, these findings suggest that systemic inflammation may explain the link between breastfeeding and a lower prevalence of RSP. However, further studies are needed to identify the association between systemic inflammation and breastfeeding and whether the anti-inflammatory effects of breastfeeding last until the later period of life. Furthermore, systemic inflammation may not be the only explanation for the lower prevalence of RSP in breastfeeding mothers. For instance, breastfeeding may affect factors involved in the pathogenesis of restrictive lung disease. Metabolic factors known to be related to breastfeeding and restrictive lung disease may also play a role. Therefore, further studies are required to identify the mechanisms underlying the protective effects of breastfeeding against RSP.
This study has several strengths. This was the first study to determine the association between breastfeeding and maternal pulmonary function, particularly the prevalence of RSP. We hope that this study serves as a meaningful first step in investigating the relationship between breastfeeding and maternal pulmonary function. Second, we used data from the KNHANES data, which is sufficiently large to represent the entire Korean population. Third, the effects of any known risk factors for maternal RSP or potentially confounding factors were corrected using multivariate logistic regression.
However, this study also has some limitations. First, this was a cross-sectional study that is not suitable for evaluating the causal effect of breastfeeding on RSP, despite the significant association between breastfeeding and the prevalence of RSP. Second, we used RSP instead of restrictive lung disease due to the lack of information about TLC. Third, a standard definition of RSP has not yet been established. RSP is defined in two ways: by the fixed ratio criterion and by the lower limit normal (LLN) criterion [25,32]. We used a fixed ratio criterion instead of the LLN criterion to define RSP, although using a fixed ratio criterion can lead to overdiagnosis of obstructive lung disease in older age groups [33]. Fourth, the data were collected in the form of a survey, which could have caused recall bias. However, it has been reported that information about the breastfeeding of the respondent can be precisely recalled [34]. The KHANES survey data contains general health data in a large population that does not include viral or bacterial infection history, which we could not include in the study. Nevertheless, we used a diagnosis history of asthma and pulmonary tuberculosis to potential factors related to spirometry; we suggest further study using data with detailed health information.
5. Conclusions
In conclusion, this study showed that breastfeeding is associated with a reduced prevalence of RSP, which means that breastfeeding can have beneficial effects on maternal lung function. Further studies should be conducted to evaluate restrictive lung disease in terms of TLC and focus on causal effects or pathophysiology.
Abbreviations
| BMI | body mass index |
| KNHANES | Korean National Health and Nutrition Examination Survey |
| KCDA | Korea Disease Control and Prevention Agency |
| PFT | pulmonary function test |
| RSP | restrictive spirometric pattern |
| TLC | total lung capacity |
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijerph192316291/s1, Table S1: Demographic characteristics of participants according to Breastfeeding.
Author Contributions
Conceptualization, H.J., S.K., B.L. and S.-I.J. Data curation, H.J., S.K., B.L., G.K. and S.-I.J. Formal analysis, H.J., S.K., B.L. and G.K. Writing-original draft, H.J., S.K. and B.L. Writing-review & editing, W.C. and S.-I.J. Supervision, W.C. and S.-I.J. All authors had full access to all study data. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
This study was approved by the KCDA Institutional Review Board (IRB; No. 2013-07CON-03-4C for 2013, 2013-12EXP-03-5C for 2014, 2018-01-03-P-A for 2018). The KNHANES was implemented without an IRB review in 2015–2017, according to the Bioethics Act and Enforcement Rules.
Informed Consent Statement
Informed consent was obtained from all participants involved in the study.
Data Availability Statement
The data are available from the KCDA and Prevention database on the following webpage https://knhanes.kdca.go.kr/knhanes/eng/index.do (accessed on 4 December 2022).
Conflicts of Interest
The authors declare no conflict of interest.
Funding Statement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2022R1F1A1062794).
Footnotes
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data are available from the KCDA and Prevention database on the following webpage https://knhanes.kdca.go.kr/knhanes/eng/index.do (accessed on 4 December 2022).