Association between Breastfeeding and Restrictive Spirometric Pattern in...

[Full title: Association between Breastfeeding and Restrictive Spirometric Pattern in Women Aged over 40 Years: A Cross-Sectional Study]

Citation: Jang, H.; Kwon, S.; Lee, B.; Kim, G.; Chae, W.; Jang, S.-I Association between Breastfeeding and Restrictive Spirometric Pattern in Women Aged over 40 Years: A Cross-Sectional Study Int. J. Environ Res. Public Health 2022 , 19 , 16291 https://doi.org/10.3390/ ijerph 192316291 Academic Editor: Paul B. Tchounwou Received: 7 November 2022 Accepted: 3 December 2022 Published: 5 December 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations Copyright: © 2022 by the authors Licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) International Journal of Environmental Research and Public Health Article Association between Breastfeeding and Restrictive Spirometric Pattern in Women Aged over 40 Years: A Cross-Sectional Study Hyeokjoo Jang 1,† , Sebin Kwon 1,† , Bumyeol Lee 1,† , Gahyeon Kim 1 , Wonjeong Chae 2,3, * ,‡ and Sung-In Jang 2,4, * ,‡ 1 College of Medicine, Yonsei University, Seoul 03722, Republic of Korea 2 Institute of Health Services Research, Yonsei University, Seoul 03722, Republic of Korea 3 Department of Health Policy and Management, Graduate School of Public Health, Yonsei University, Seoul 03722, Republic of Korea 4 Department of Preventive Medicine, Yonsei University, Seoul 03722, Republic of Korea * Correspondence: wjchae 0816@yuhs.ac (W.C.); jangsi@yuhs.ac (S.-I.J.) † These authors contributed equally to this work (Co-first authors) ‡ These authors contributed equally to this work (Co-correspondence authors) 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 FEV 1/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 FEV 1, 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 – 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 – 5 ]. Restrictive lung disease can be diagnosed with a low total lung capacity (TLC) and a normal FEV 1/FVC ratio. The threshold values for TLC and FEV 1/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 Int. J. Environ. Res. Public Health 2022 , 19 , 16291. https://doi.org/10.3390/ijerph 192316291 https://www.mdpi.com/journal/ijerph

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 2 of 13 of spirometry. Instead, a restrictive spirometric pattern (RSP), determined by FEV 1/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 ). 2.2. Study’s Main Variables A restrictive spirometric pattern (RSP) was defined as a pre-bronchodilator FEV 1/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; FEV 1, 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.

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 3 of 13 Int. J. Environ. Res. Public Health 2022 , 19 , x FOR PEER REVIEW 3 of 13 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 FEV 1/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 nonbreastfeeding 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; FEV 1, 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/m 2 ), and participants were categorized into underweight (<18.5 kg/m 2 ), normal (≥18.5 to <25 kg/m 2 ), and obese (≥25 kg/m 2 ) according to BMI values. Smoking status was Figure 1. Flow chart of study population selection The body mass index (BMI) was calculated as body weight per square of height (kg/m 2 ), and participants were categorized into underweight (<18.5 kg/m 2 ), normal ( ≥ 18.5 to <25 kg/m 2 ), and obese ( ≥ 25 kg/m 2 ) 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 noncapital 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 FEV 1, 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

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 4 of 13 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 FEV 1 (L), FVC (L), FVC percentage (%), and FEV 1/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 S 1. 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/m 2 for BMI, 2.30 (0.45) L for FEV 1, 2.91 (0.51) L for FVC, 92.76% (11.58%) for FVC%, and 0.79 (0.06) for FEV 1/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/m 2 ), 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

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 5 of 13 Table 1. Cont Variables Total (n) RSP Non-RSP p -Value n % n % n % 9261 913 9.9 8348 90.1 BMI (kg/m 2 ) 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 FEV 1 (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) † FEV 1/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

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 6 of 13 Table 1. Cont Variables Total (n) RSP Non-RSP p -Value n % n % n % 9261 913 9.9 8348 90.1 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 nonbreastfeeding 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

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 7 of 13 Table 2. Cont Variables OR 95% CI p -Value p -Value for Trend 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

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 8 of 13 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 FEV 1 (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 FEV 1/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 FEV 1, <0.0001 for FVC, 0.0002 for FVC%, and 0.1956 for the FEV 1/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 FEV 1 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 7 c 12 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) FEV 1/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).

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 9 of 13 Int. J. Environ. Res. Public Health 2022 , 19 , x FOR PEER REVIEW 9 of 13 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 Figure 2. Forest plot of subgroup analysis of the association between breastfeeding and restrictive spirometric pattern stratified by covariates.

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 10 of 13 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 nonbreastfeeding 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 FEV 1 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 – 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

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 11 of 13 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, α 1-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 Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijerph 192316291/s 1 , Table S 1: 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.

Int. J. Environ. Res. Public Health 2022 , 19 , 16291 12 of 13 Funding: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2022 R 1 F 1 A 1062794) Institutional Review Board Statement: This study was approved by the KCDA Institutional Review Board (IRB; No. 2013-07 CON-03-4 C for 2013, 2013-12 EXP-03-5 C 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 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 References 1 Kasper, D.; Fauci, A.; Hauser, S.; Longo, D.; Jameson, J.; Loscalzo, J Harrison’s Principles of Internal Medicine , 11 th ed.; Mcgraw-Hill: New York, NY, USA, 2022; Volume 1 2 Meyer, K.B.; Wilbrey-Clark, A.; Nawijn, M.; Teichmann, S.A. The Human Lung Cell Atlas: A Transformational Resource for Cells of the Respiratory System. In Lung Stem Cells in Development, Health and Disease (ERS Monograph) ; European Respiratory Society: Sheffield, UK, 2021; pp. 158–174 3 Bartels, M.N.; Prince, D.Z. Acute Medical Conditions: Cardiopulmonary Disease, Medical Frailty, and Renal Failure Braddom’s Phys. Med. Rehabil 2021 , 511–534.e 515. [ CrossRef ] 4 Brack, T.; Jubran, A.; Tobin, M.J. Dyspnea and decreased variability of breathing in patients with restrictive lung disease Am. J Respir. Crit. Care Med 2002 , 165 , 1260–1264. [ CrossRef ] [ PubMed ] 5 Martinez-Pitre, P.J.; Sabbula, B.R.; Cascella, M Restrictive Lung Disease ; StatPearls Publishing: Treasure Island, FL, USA, 2022 6 Mannino, D.M.; Ford, E.S.; Redd, S.C. Obstructive and restrictive lung disease and markers of inflammation: Data from the Third National Health and Nutrition Examination Am. J. Med 2003 , 114 , 758–762. [ CrossRef ] [ PubMed ] 7 Mannino, D.M.; Holguin, F.; Pavlin, B.I.; Ferdinands, J.M. Risk factors for prevalence of and mortality related to restriction on spirometry: Findings from the First National Health and Nutrition Examination Survey and follow-up Int. J. Tuberc. Lung Dis 2005 , 9 , 613–621 8 Kurth, L.; Hnizdo, E. Change in prevalence of restrictive lung impairment in the U.S. population and associated risk factors: The National Health and Nutrition Examination Survey (NHANES) 1988–1994 and 2007–2010 Multidiscip. Respir. Med 2015 , 10 , 7 [ CrossRef ] 9 Guerra, S.; Sherrill, D.L.; Venker, C.; Ceccato, C.M.; Halonen, M.; Martinez, F.D. Morbidity and mortality associated with the restrictive spirometric pattern: A longitudinal study Thorax 2010 , 65 , 499–504. [ CrossRef ] 10 Soriano, J.B.; Miravitlles, M.; Garc í a-R í o, F.; Muñoz, L.; S á nchez, G.; Sobradillo, V.; Dur á n, E.; Guerrero, D.; Ancochea, J Spirometrically-defined restrictive ventilatory defect: Population variability and individual determinants Prim. Care Respir. J 2012 , 21 , 187–193. [ CrossRef ] 11 Mannino, D.M.; Ford, E.S.; Redd, S.C. Obstructive and restrictive lung disease and functional limitation: Data from the Third National Health and Nutrition Examination J. Intern. Med 2003 , 254 , 540–547. [ CrossRef ] 12 Nakajima, K.; Kubouchi, Y.; Muneyuki, T.; Ebata, M.; Eguchi, S.; Munakata, H. A possible association between suspected restrictive pattern as assessed by ordinary pulmonary function test and the metabolic syndrome Chest 2008 , 134 , 712–718 [ CrossRef ] 13 van den Borst, B.; Gosker, H.R.; Zeegers, M.P.; Schols, A.M. Pulmonary function in diabetes: A metaanalysis Chest 2010 , 138 , 393–406. [ CrossRef ] 14 Sattari, M.; Serwint, J.R.; Levine, D.M. Maternal Implications of Breastfeeding: A Review for the Internist Am. J. Med 2019 , 132 , 912–920. [ CrossRef ] [ PubMed ] 15 Koh, K. Maternal breastfeeding and children’s cognitive development Soc. Sci. Med 2017 , 187 , 101–108. [ CrossRef ] [ PubMed ]

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Chronic disease, Mortality, Causal effect, Diabetes mellitus, Informed consent, Respiratory system, Study population, General population, Body mass index, Clinical Practice, Type II Diabetes Mellitus, Metabolic syndrome, Study design, Cross-sectional study, Anti-inflammatory effect, Institutional review board, Spirometry, Prospective cohort study, Maternal health, Vascular disease, Pulmonary function, Odds ratio, Pulmonary function test, Protective effect, Regression analysis, Conflicts of interest, Statistical analyses, Negative correlation, Cardiovascular disorder, Systemic inflammation, Comorbidities, Linear Relationship, Lung function, Ovarian cancer, Parous Women, Education Level, Pro-inflammatory cytokine, Smoking status, Biological mechanism, Employment status, Breastfeeding, Beneficial effect, Multivariate Logistic Regression, Recall bias, Total Lung Capacity, Obstructive Lung Disease, Restrictive Lung Disease, Logistic regression analysis, Lung Volume, Health effect, FVC, Health data, Independent variable, Data source, National Research Foundation, Gonadotropin, Demographic characteristic, Covariate, Respiratory symptom, National health, Subgroup analyses, Study data, Data availability, Forest plot, FEV 1, Metabolic factor, Korean population, Neuroendocrine pathway, Nutrition Examination Survey, Korea National Health, Main variable, Interaction test, Health and nutritional status, Household income level.