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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Public Health</journal-id>
<journal-title>Frontiers in Public Health</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Public Health</abbrev-journal-title>
<issn pub-type="epub">2296-2565</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpubh.2021.767151</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Public Health</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Relationship Between Lifestyle Habits and Health-Related Quality of Life of Recently Diagnosed Breast Cancer Patients: A Comparison Between Younger and Older Women in China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Zheng</surname> <given-names>Chao</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1576035/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Yu</surname> <given-names>Li-Xiang</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Jia</surname> <given-names>Hong-Ying</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1078739/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Cui</surname> <given-names>Shu-De</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Tian</surname> <given-names>Fu-Guo</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Fan</surname> <given-names>Zhi-Min</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1059343/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Geng</surname> <given-names>Cui-Zhi</given-names></name>
<xref ref-type="aff" rid="aff7"><sup>7</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Cao</surname> <given-names>Xu-Chen</given-names></name>
<xref ref-type="aff" rid="aff8"><sup>8</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1337902/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Yang</surname> <given-names>Zhen-Lin</given-names></name>
<xref ref-type="aff" rid="aff9"><sup>9</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Xiang</given-names></name>
<xref ref-type="aff" rid="aff10"><sup>10</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Liang</surname> <given-names>Hong</given-names></name>
<xref ref-type="aff" rid="aff11"><sup>11</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Shu</given-names></name>
<xref ref-type="aff" rid="aff12"><sup>12</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Jiang</surname> <given-names>Hong-Chuan</given-names></name>
<xref ref-type="aff" rid="aff13"><sup>13</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Duan</surname> <given-names>Xue-Ning</given-names></name>
<xref ref-type="aff" rid="aff14"><sup>14</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Hai-Bo</given-names></name>
<xref ref-type="aff" rid="aff15"><sup>15</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Guo-Lou</given-names></name>
<xref ref-type="aff" rid="aff16"><sup>16</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Qi-Tang</given-names></name>
<xref ref-type="aff" rid="aff17"><sup>17</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Jian-Guo</given-names></name>
<xref ref-type="aff" rid="aff18"><sup>18</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Jin</surname> <given-names>Feng</given-names></name>
<xref ref-type="aff" rid="aff19"><sup>19</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Tang</surname> <given-names>Jin-Hai</given-names></name>
<xref ref-type="aff" rid="aff20"><sup>20</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Liang</given-names></name>
<xref ref-type="aff" rid="aff21"><sup>21</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhu</surname> <given-names>Shi-Guang</given-names></name>
<xref ref-type="aff" rid="aff22"><sup>22</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Zuo</surname> <given-names>Wen-Shu</given-names></name>
<xref ref-type="aff" rid="aff23"><sup>23</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Fei</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhou</surname> <given-names>Fei</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Xiang</surname> <given-names>Yu-Juan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Guo</surname> <given-names>Ming-Ming</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname> <given-names>Yong-Jiu</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Huang</surname> <given-names>Shu-Ya</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1541557/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Liu</surname> <given-names>Li-Yuan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1459245/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Yu</surname> <given-names>Zhi-Gang</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/714820/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Breast Surgery, The Second Hospital, Cheeloo College of Medicine, Shandong University</institution>, <addr-line>Jinan</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University</institution>, <addr-line>Jinan</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Center of Evidence-Based Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University</institution>, <addr-line>Jinan</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>Department of Breast Surgery, Affiliated Tumor Hospital of Zhengzhou University</institution>, <addr-line>Zhengzhou</addr-line>, <country>China</country></aff>
<aff id="aff5"><sup>5</sup><institution>Department of Breast Surgery, Shanxi Cancer Hospital</institution>, <addr-line>Taiyuan</addr-line>, <country>China</country></aff>
<aff id="aff6"><sup>6</sup><institution>Department of Breast Surgery, The First Hospital of Jilin University</institution>, <addr-line>Changchun</addr-line>, <addr-line>Jilin</addr-line>, <country>China</country></aff>
<aff id="aff7"><sup>7</sup><institution>Breast Center, The Fourth Hospital of Hebei Medical University</institution>, <addr-line>Shijiazhuang</addr-line>, <country>China</country></aff>
<aff id="aff8"><sup>8</sup><institution>Department of Breast Surgery, Tianjin Medical University Cancer Institute and Hospital</institution>, <addr-line>Tianjin</addr-line>, <country>China</country></aff>
<aff id="aff9"><sup>9</sup><institution>Department of Thyroid and Breast Surgery, The First Affiliated Hospital of Binzhou Medical University</institution>, <addr-line>Binzhou</addr-line>, <country>China</country></aff>
<aff id="aff10"><sup>10</sup><institution>Department of Breast Surgery, Cancer Hospital, Chinese Academy of Medical Sciences</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff11"><sup>11</sup><institution>Department of General Surgery, Linyi People&#x00027;s Hospital</institution>, <addr-line>Linyi</addr-line>, <country>China</country></aff>
<aff id="aff12"><sup>12</sup><institution>Breast Disease Center, Peking University People&#x00027;s Hospital</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff13"><sup>13</sup><institution>Department of General Surgery, Beijing Chaoyang Hospital</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff14"><sup>14</sup><institution>Breast Disease Center, Peking University First Hospital</institution>, <addr-line>Beijing</addr-line>, <country>China</country></aff>
<aff id="aff15"><sup>15</sup><institution>Breast Center, Qingdao University Affiliated Hospital</institution>, <addr-line>Qingdao</addr-line>, <country>China</country></aff>
<aff id="aff16"><sup>16</sup><institution>Department of Breast and Thyroid Surgery, Weifang Traditional Chinese Hospital</institution>, <addr-line>Weifang</addr-line>, <country>China</country></aff>
<aff id="aff17"><sup>17</sup><institution>Department of Breast Surgery, The Second Affiliated Hospital of Qingdao Medical College, Qingdao Central Hospital</institution>, <addr-line>Qingdao</addr-line>, <country>China</country></aff>
<aff id="aff18"><sup>18</sup><institution>Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University</institution>, <addr-line>Harbin</addr-line>, <country>China</country></aff>
<aff id="aff19"><sup>19</sup><institution>Department of Breast Surgery, The First Affiliated Hospital of China Medical University</institution>, <addr-line>Shenyang</addr-line>, <country>China</country></aff>
<aff id="aff20"><sup>20</sup><institution>Department of General Surgery, Nanjing Medical University Affiliated Cancer Hospital, Cancer Institute of Jiangsu Province</institution>, <addr-line>Nanjing</addr-line>, <country>China</country></aff>
<aff id="aff21"><sup>21</sup><institution>Department of Breast and Thyroid Surgery, Zibo Central Hospital</institution>, <addr-line>Zibo</addr-line>, <country>China</country></aff>
<aff id="aff22"><sup>22</sup><institution>Department of Breast Surgery, Yantai Yuhuangding Hospital</institution>, <addr-line>Yantai</addr-line>, <country>China</country></aff>
<aff id="aff23"><sup>23</sup><institution>Breast Cancer Center, Shandong Cancer Hospital</institution>, <addr-line>Jinan</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Lei Si, University of New South Wales, Australia</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Simone Nardin, Universit&#x000E0; degli Studi del Piemonte Orientale, Italy; Ali Montazeri, Iranian Institute for Health Sciences Research, Iran</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Li-Yuan Liu <email>liuliyuan&#x00040;sdu.edu.cn</email>; <ext-link ext-link-type="uri" xlink:href="https://orcid.org/0000-0002-9862-7471">orcid.org/0000-0002-9862-7471</ext-link></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Aging and Public Health, a section of the journal Frontiers in Public Health</p></fn></author-notes>
<pub-date pub-type="epub">
<day>14</day>
<month>12</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>9</volume>
<elocation-id>767151</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>08</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>11</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 Zheng, Yu, Jia, Cui, Tian, Fan, Geng, Cao, Yang, Wang, Liang, Wang, Jiang, Duan, Wang, Li, Wang, Zhang, Jin, Tang, Li, Zhu, Zuo, Wang, Zhou, Xiang, Guo, Wang, Huang, Liu and Yu.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Zheng, Yu, Jia, Cui, Tian, Fan, Geng, Cao, Yang, Wang, Liang, Wang, Jiang, Duan, Wang, Li, Wang, Zhang, Jin, Tang, Li, Zhu, Zuo, Wang, Zhou, Xiang, Guo, Wang, Huang, Liu and Yu</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license> </permissions>
<abstract><p><bold>Objective:</bold> The aim of this study was to evaluate the relationship between lifestyle habits and health-related quality of life (HRQoL) among different ages who were initially diagnosed with breast cancer (within the first 2 weeks) and to determine the contribution of lifestyle habits factors on HRQoL.</p>
<p><bold>Methods:</bold> Patients with breast cancer were recruited from 22 hospitals in 11 provinces or municipalities in northern and eastern China. The Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B) was used to measure HRQoL. Chi-square test, ANOVA, and multivariable generalized linear models were conducted to identify the differences in HRQoL between two age groups (age &#x0003C;50 years and &#x02265;50 years) and to evaluate the contribution of lifestyle habits factors on HRQoL of patients with breast cancer.</p>
<p><bold>Results:</bold> About 1,199 eligible patients with breast cancer were used for analysis. Younger women (aged &#x0003C;50 years) appeared to show lower scores than older women (aged &#x02265;50 years) in HRQoL subscales, including emotional well-being (<italic>p</italic> = 0.003), functional well-being (<italic>p</italic> = 0.006), breast cancer subscale (<italic>p</italic> = 0.038), and FACT-B Total scores (<italic>p</italic> = 0.028). Tea and alcohol consumption and being very satisfied with sleep and current life were the strongest predictors of higher HRQoL in younger group. Meanwhile, no coffee consumption, frequent participation in physical activities, high sleep satisfaction, and current life satisfaction were the key predictors of higher HRQoL in older women with breast cancer.</p>
<p><bold>Conclusion:</bold> The relationship of the nine lifestyle habit items with HRQoL differed among younger and older women. The associated variable of low HRQoL can help clinicians take intervention early in order to improve the prognosis of patients with breast cancer.</p></abstract>
<kwd-group>
<kwd>quality of life</kwd>
<kwd>breast cancer</kwd>
<kwd>lifestyle habits</kwd>
<kwd>age-related differences</kwd>
<kwd>patient satisfaction</kwd>
<kwd>prognosis</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="6"/>
<equation-count count="0"/>
<ref-count count="49"/>
<page-count count="11"/>
<word-count count="7055"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Breast cancer is the most common cancer among women in China. According to the data released by the National Cancer Center of China, in 2020, there were 4,16,371 new cases of breast cancer among women in China (<xref ref-type="bibr" rid="B1">1</xref>). As evidenced by data on breast cancer with high incidence rates and relatively low mortality rates, it is the most prevalent cancer in China (<xref ref-type="bibr" rid="B2">2</xref>). It has been predicted that by 2021, there will be 2.2 million cases of breast cancer in China among women aged 35&#x02013;49 years in 2001, which is equivalent to more than 100 new cases per 1,00,000 women (<xref ref-type="bibr" rid="B3">3</xref>). Therefore, efforts to improve the health-related quality of life (HRQoL) of this growing population of women have thus become an issue of great public health importance (<xref ref-type="bibr" rid="B4">4</xref>&#x02013;<xref ref-type="bibr" rid="B6">6</xref>).</p>
<p>In 1993, the World Health Organization (WHO) defined quality of life (QoL) as &#x0201C;the comprehensive satisfaction of individuals in different cultures and value systems with their goals, expectations, standards, and life conditions related to their concerns, as well as their general sense of personal health&#x0201D; (<xref ref-type="bibr" rid="B7">7</xref>). The QoL reflects the overall physical and mental response and the sense of real self-worth from the heart when the individual suffers from the pain (<xref ref-type="bibr" rid="B8">8</xref>). This functional scale for a certain cancer can accurately evaluate the patient&#x00027;s condition and play an irreplaceable role (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>), and is now considered an important endpoint in cancer clinical trials (<xref ref-type="bibr" rid="B5">5</xref>).</p>
<p>As well-documented in previous studies, evaluating the HRQoL of patients with cancer could contribute to improved treatment and could even predict prognosis as medical factors can predict prognosis (<xref ref-type="bibr" rid="B11">11</xref>&#x02013;<xref ref-type="bibr" rid="B14">14</xref>). From a clinical point of view, patients with breast cancer perform poorly in terms of psychology, physiology, and sociology. Therefore, patients with breast cancer need more support and help in these aspects. It is very important to evaluate and study the HRQoL of patients with breast cancer, pay attention to their physical and mental condition, and take active measures and intervention methods to improve their HRQoL (<xref ref-type="bibr" rid="B6">6</xref>).</p>
<p>At present, many researchers are committed to exploring the influencing factors affecting the HRQoL of patients with breast cancer and hope to improve the overall health of patients with breast cancer by changing these factors. Psychosocial factors, sociodemographic variables, and medical variables have been identified as predictors of HRQoL in patients with cancer (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B12">12</xref>), but current research on the impact of various lifestyle habits factors on the HRQoL of patients with breast cancer is still controversial (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). Mosher and Danoff-Burg reviewed and analyzed the studies of age differences in breast cancer psychological adaptation and believed that age may be a risk factor for distress with other variables contributing to this demographic difference (<xref ref-type="bibr" rid="B17">17</xref>). Furthermore, previous studies have shown that younger women have a higher psychological incidence rate and poorer HRQoL after a breast cancer diagnosis than older women (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B18">18</xref>). However, the differences in the relationship between lifestyle habits and HRQoL in younger and older women in China have not been studied. More importantly, most studies on QoL after breast cancer are conducted at least 4 months to more than 5&#x02013;10 years after women are diagnosed with cancer and sometimes after the completion of treatment (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B15">15</xref>). Few studies have evaluated the HRQoL of women initially diagnosed with breast cancer in the first few weeks (<xref ref-type="bibr" rid="B19">19</xref>).</p>
<p>The aim of this study was to evaluate the relationship of lifestyle habits with HRQoL among younger and older women who were initially diagnosed with breast cancer within the first 2 weeks and to determine the contribution of lifestyle habits factors on the HRQoL. The findings of this study can potentially help guide the training/initiatives that are organized for shaping lifestyle habits of patients with breast cancer after cancer diagnosis and may influence the future course and prognosis of breast cancer in women.</p></sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and Methods</title>
<sec>
<title>Recruitment</title>
<p>A multicenter, hospital-based case&#x02013;control study was conducted among breast cancer women from 22 hospitals in 11 provinces or municipalities in northern and eastern China from April 2012 to April 2013, as described previously (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>). Of these, Han Chinese women newly diagnosed with primary breast cancer confirmed by histology and aged from 25 to 70 years were included in this subgroup study. Exclusion criteria were as follows: (1) being &#x0003C;25 or &#x0003E;70 years of age; (2) being diagnosed with recurrent breast cancer; (3) being diagnosed with metastatic breast cancer; (4) patients with other malignant tumors; and (5) patients who refused to enroll. A self-designed structured questionnaire was used on the interview, as described previously (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>). The questionnaire mainly includes the following contents: demographic characteristics, female physiological and reproductive factors, medical and family history, lifestyle habits, and breast cancer-related knowledge. In this study, we only analyzed the lifestyle habits, including smoking (including passive smoking), alcohol consumption, dietary habits (tea and coffee consumption), sleep satisfaction, current life satisfaction, physical activity, and body mass index (BMI, kg/m<sup>2</sup>).</p></sec>
<sec>
<title>Assessment of HRQoL</title>
<p>The Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B)-simplified Chinese version 4 instrument is administered during the baseline interview to assess HRQoL. The FACT-B is a 36-item questionnaire that includes both 27 items of general HRQoL (FACT-G) associated with cancer and another nine items of HRQoL related to breast cancer, the breast cancer subscale (BCS). FACT-B consists of the following subscales: physical well-being (PWB) (seven items), social/family well-being (SWB) (seven items), emotional well-being (EWB) (six items), functional well-being (FWB) (seven items), and BCS. The simplified Chinese translation was performed using a standardized methodology by a series of forward and backward translations as well as review and field testing. The FACT-B uses a 5-point scale (0 = not at all; 1 = a little bit; 2 = somewhat; 3 = quite a bit; and 4 = very much) to indicate how true the statements were to the subjects over the previous 7 days. If more than half of the items that make up the subscale were answered, the missing values were calculated as an average of the observed items. Depending on the scale, higher scores may represent either a higher level of well-being or a lower level of well-being. The items that are expressed in the opposite direction were transformed before being summed up to calculate each subscale&#x00027;s score. Higher scores represent higher levels of well-being. The Cronbach &#x003B1; in this study was 0.881 for the FACT-B Total, 0.821 for PWB, 0.800 for SWB, 0.757 for EWB, 0.876 for FWB, and 0.653 for BCS.</p>
<p>Before the start of this study, the investigators were all trained and assessed. The baseline and FACT-B questionnaires were collected in a unified standard and unified manner to reduce information bias. Face-to-face interviews were conducted to collect the basic information and HRQoL information from the patients. And the baseline and FACT-B questionnaires were completed within 2 weeks after the diagnosis of breast cancer; none of the patients received surgery or neoadjuvant therapy and had not started further treatment when recruited into this study.</p></sec>
<sec>
<title>Statistical Analysis</title>
<p>Data entry, process, and analysis methods are the same as described previously (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>). Pearson&#x00027;s chi-square tests were used to compare the frequency distribution differences between women aged &#x0003C;50 years and &#x02265;50 years. Mean and SD were calculated for all HRQoL domains. One-way ANOVA was used to calculate the <italic>P</italic>-value. The multivariate generalized linear model (GLM) was used to estimate all the factors with statistical difference to determine the features most strongly associated with these HRQoL scores. A two-sided <italic>P</italic>-value &#x0003C;0.05 was considered to be statistically significant.</p></sec></sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>This study initially recruited 1,489 eligible patients with breast cancer as described previously, and 1,199 cases were used for analysis as appropriate. Of these women, the mean age was 47.66 years. In this study, the patients were divided into two groups: women aged &#x0003C;50 years and women aged &#x02265;50 years. Women aged &#x0003C;50 years constituted 62.0% of the entire dataset. <xref ref-type="fig" rid="F1">Figure 1</xref> presents the flow of patients in the study. The basic characteristics of the two groups are shown in <xref ref-type="table" rid="T1">Table 1</xref>. There were statistically significant differences between the two groups in education levels (&#x003C7;<sup>2</sup> = 43.845, <italic>P</italic> &#x0003C; 0.001), family average revenue (&#x003C7;<sup>2</sup> = 11.962, <italic>P</italic> = 0.018), and post-menopausal status (&#x003C7;<sup>2</sup> = 585.054, <italic>P</italic> &#x0003C; 0.001). No significant differences were found for location, economic status, social status, marriage, and family history of breast cancer between different age groups. In this study, no significant lifestyle habits differences existed based on age categories, except for BMI distribution. Women aged &#x0003C;50 years reported significantly lower BMI (&#x003C7;<sup>2</sup> = 19.080, <italic>P</italic> &#x0003C; 0.001).</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>Flowchart of patients eligible for this study.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpubh-09-767151-g0001.tif"/>
</fig>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Differences in the basic characteristics between younger and older breast cancer women.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Variable</bold></th>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>Age</bold></th>
<th valign="top" align="center"><bold>&#x003C7;<sup>2</sup></bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>Younger (&#x0003C;50) (<italic>n</italic> &#x0003D; 743)</bold></th>
<th valign="top" align="center"><bold>Older (&#x02265;50) (<italic>n</italic> &#x0003D; 456)</bold></th>
<th/>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="5">Basic demographic information</td>
</tr>
<tr>
<td valign="top" align="left">Location</td>
<td/>
<td/>
<td valign="top" align="center">0.893</td>
<td valign="top" align="center">0.345</td>
</tr>
<tr>
<td valign="top" align="left">Urban</td>
<td valign="top" align="center">336 (47.6%)</td>
<td valign="top" align="center">225 (50.4%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Rural</td>
<td valign="top" align="center">370 (52.4%)</td>
<td valign="top" align="center">221 (49.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Education</td>
<td/>
<td/>
<td valign="top" align="center">43.845</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Elementary or low</td>
<td valign="top" align="center">102 (14.1%)</td>
<td valign="top" align="center">122 (27.9%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Middle</td>
<td valign="top" align="center">274 (38.0%)</td>
<td valign="top" align="center">126 (28.8%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">High</td>
<td valign="top" align="center">220 (30.5%)</td>
<td valign="top" align="center">145 (33.1%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">College</td>
<td valign="top" align="center">120 (16.6%)</td>
<td valign="top" align="center">44 (10.0%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Postgraduate</td>
<td valign="top" align="center">6 (0.8%)</td>
<td valign="top" align="center">1 (0.2%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Family average revenue (RMB)</td>
<td/>
<td/>
<td valign="top" align="center">11.962</td>
<td valign="top" align="center">0.018</td>
</tr>
<tr>
<td valign="top" align="left">&#x0003C;1,000</td>
<td valign="top" align="center">48 (6.6%)</td>
<td valign="top" align="center">47 (10.5%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">1,000&#x02013;1,999</td>
<td valign="top" align="center">119 (16.4%)</td>
<td valign="top" align="center">92 (20.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">2,000&#x02013;2,999</td>
<td valign="top" align="center">208 (28.7%)</td>
<td valign="top" align="center">117 (26.2%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">3,000&#x02013;4,999</td>
<td valign="top" align="center">175 (24.1%)</td>
<td valign="top" align="center">105 (23.5%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x02265;5,000</td>
<td valign="top" align="center">176 (24.2%)</td>
<td valign="top" align="center">85 (19.1%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Economic status</td>
<td/>
<td/>
<td valign="top" align="center">4.939</td>
<td valign="top" align="center">0.176</td>
</tr>
<tr>
<td valign="top" align="left">High</td>
<td valign="top" align="center">19 (2.6%)</td>
<td valign="top" align="center">13 (2.7%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Good</td>
<td valign="top" align="center">159 (21.8%)</td>
<td valign="top" align="center">97 (21.7%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Average</td>
<td valign="top" align="center">461 (63.2%)</td>
<td valign="top" align="center">262 (58.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Poor</td>
<td valign="top" align="center">90 (12.3%)</td>
<td valign="top" align="center">75 (16.8%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Social status</td>
<td/>
<td/>
<td valign="top" align="center">1.999</td>
<td valign="top" align="center">0.573</td>
</tr>
<tr>
<td valign="top" align="left">High</td>
<td valign="top" align="center">23 (3.2%)</td>
<td valign="top" align="center">13 (3.0%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Good</td>
<td valign="top" align="center">163 (22.5%)</td>
<td valign="top" align="center">103 (23.4%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Average</td>
<td valign="top" align="center">499 (68.9%)</td>
<td valign="top" align="center">292 (66.4%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Poor</td>
<td valign="top" align="center">39 (5.4%)</td>
<td valign="top" align="center">32 (7.3%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Menopause</td>
<td/>
<td/>
<td valign="top" align="center">585.054</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">56 (7.7%)</td>
<td valign="top" align="center">340 (76.9%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">667 (92.3%)</td>
<td valign="top" align="center">102 (23.1%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Marriage</td>
<td/>
<td/>
<td valign="top" align="center">1.376</td>
<td valign="top" align="center">0.241</td>
</tr>
<tr>
<td valign="top" align="left">Ever</td>
<td valign="top" align="center">722 (97.2%)</td>
<td valign="top" align="center">448 (98.2%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Never</td>
<td valign="top" align="center">21 (2.8%)</td>
<td valign="top" align="center">8 (1.8%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Family history of breast cancer</td>
<td/>
<td/>
<td valign="top" align="center">0.444</td>
<td valign="top" align="center">0.505</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">45 (6.3%)</td>
<td valign="top" align="center">23 (5.3%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">668 (93.7%)</td>
<td valign="top" align="center">407 (94.7%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="5">Lifestyle habits characteristics</td>
</tr>
<tr>
<td valign="top" align="left">Cigarette smoking</td>
<td/>
<td/>
<td valign="top" align="center">1.465</td>
<td valign="top" align="center">0.226</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">20 (2.7%)</td>
<td valign="top" align="center">18 (4.0%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">721 (97.3%)</td>
<td valign="top" align="center">436 (96.0%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Second-hand smoking</td>
<td/>
<td/>
<td valign="top" align="center">0.880</td>
<td valign="top" align="center">0.348</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">277 (60.5%)</td>
<td valign="top" align="center">174 (64.0%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">181 (39.5%)</td>
<td valign="top" align="center">98 (36.0%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Alcohol drinking</td>
<td/>
<td/>
<td valign="top" align="center">0.109</td>
<td valign="top" align="center">0.742</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">96 (13.0%)</td>
<td valign="top" align="center">56 (12.3%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">643 (87.0%)</td>
<td valign="top" align="center">398 (87.7%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Tea</td>
<td/>
<td/>
<td valign="top" align="center">1.640</td>
<td valign="top" align="center">0.200</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">141 (19.3%)</td>
<td valign="top" align="center">100 (22.4%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">589 (80.7%)</td>
<td valign="top" align="center">346 (77.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Coffee</td>
<td/>
<td/>
<td valign="top" align="center">0.035</td>
<td valign="top" align="center">0.853</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">31 (4.3%)</td>
<td valign="top" align="center">20 (4.5%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">694 (95.7%)</td>
<td valign="top" align="center">424 (95.5%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Sleep satisfaction</td>
<td/>
<td/>
<td valign="top" align="center">2.436</td>
<td valign="top" align="center">0.296</td>
</tr>
<tr>
<td valign="top" align="left">Very satisfied</td>
<td valign="top" align="center">90 (12.3%)</td>
<td valign="top" align="center">48 (10.8%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Satisfied</td>
<td valign="top" align="center">514 (70.4%)</td>
<td valign="top" align="center">305 (68.2%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Dissatisfied</td>
<td valign="top" align="center">126 (17.3%)</td>
<td valign="top" align="center">92 (20.7%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Current life satisfaction</td>
<td/>
<td/>
<td valign="top" align="center">4.565</td>
<td valign="top" align="center">0.102</td>
</tr>
<tr>
<td valign="top" align="left">Very satisfied</td>
<td valign="top" align="center">82 (11.0%)</td>
<td valign="top" align="center">39 (8.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Satisfied</td>
<td valign="top" align="center">493 (66.4%)</td>
<td valign="top" align="center">329 (72.1%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Dissatisfied</td>
<td valign="top" align="center">168 (22.6%)</td>
<td valign="top" align="center">88 (19.3%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Physical activity</td>
<td/>
<td/>
<td valign="top" align="center">2.142</td>
<td valign="top" align="center">0.343</td>
</tr>
<tr>
<td valign="top" align="left">Often</td>
<td valign="top" align="center">210 (28.5%)</td>
<td valign="top" align="center">129 (28.5%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Occasionally</td>
<td valign="top" align="center">311 (42.3%)</td>
<td valign="top" align="center">175 (38.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Never</td>
<td valign="top" align="center">215 (29.2%)</td>
<td valign="top" align="center">149 (32.9%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">BMI (kg/m<sup>2</sup>)</td>
<td/>
<td/>
<td valign="top" align="center">19.080</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">&#x0003C;24.0</td>
<td valign="top" align="center">373 (51.9%)</td>
<td valign="top" align="center">183 (42.6%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">24.0&#x02013;28.0</td>
<td valign="top" align="center">275 (38.2%)</td>
<td valign="top" align="center">169 (39.3%)</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x0003E;28.0</td>
<td valign="top" align="center">71 (9.9%)</td>
<td valign="top" align="center">78 (18.1%)</td>
<td/>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
<p>The mean FACT-B scores for each individual HRQoL domain and overall scores are shown in <xref ref-type="table" rid="T2">Table 2</xref>. The mean FACT-B overall score of younger women was 83.63, while in the older women group, it was 85.88. Younger women (aged &#x0003C;50 years) at the diagnosis of breast cancer appeared to be related to lower scores than older women (aged &#x02265;50 years) in all of the HRQoL subscales except PWB and SWB. EWB (<italic>p</italic> = 0.003), FWB (<italic>p</italic> = 0.006), BCS (<italic>p</italic> = 0.038), and FACT-B Total (<italic>p</italic> = 0.028) were significantly related to age.</p>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>Health-related quality of life differences by age group.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>Age</bold></th>
<th valign="top" align="center"><bold><italic>t</italic></bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>Younger (&#x0003C;50) (<italic>n</italic> &#x0003D; 734)</bold></th>
<th valign="top" align="center"><bold>Older (&#x02265;50) (<italic>n</italic> &#x0003D; 456)</bold></th>
<th/>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">PWB</td>
<td valign="top" align="center">19.45 &#x000B1; 4.385</td>
<td valign="top" align="center">19.32 &#x000B1; 4.798</td>
<td valign="top" align="center">0.217</td>
<td valign="top" align="center">0.614</td>
</tr>
<tr>
<td valign="top" align="left">SWB</td>
<td valign="top" align="center">16.14 &#x000B1; 5.519</td>
<td valign="top" align="center">16.28 &#x000B1; 5.214</td>
<td valign="top" align="center">0.182</td>
<td valign="top" align="center">0.670</td>
</tr>
<tr>
<td valign="top" align="left">EWB</td>
<td valign="top" align="center">13.92 &#x000B1; 4.416</td>
<td valign="top" align="center">14.67 &#x000B1; 4.475</td>
<td valign="top" align="center">8.623</td>
<td valign="top" align="center">0.003</td>
</tr>
<tr>
<td valign="top" align="left">FWB</td>
<td valign="top" align="center">12.80 &#x000B1; 5.515</td>
<td valign="top" align="center">13.72 &#x000B1; 5.746</td>
<td valign="top" align="center">7.656</td>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">BCS</td>
<td valign="top" align="center">21.32 &#x000B1; 4.622</td>
<td valign="top" align="center">21.90 &#x000B1; 4.849</td>
<td valign="top" align="center">4.337</td>
<td valign="top" align="center">0.038</td>
</tr>
<tr>
<td valign="top" align="left">Total</td>
<td valign="top" align="center">83.63 &#x000B1; 16.211</td>
<td valign="top" align="center">85.88 &#x000B1; 17.244</td>
<td valign="top" align="center">5.215</td>
<td valign="top" align="center">0.023</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>PWB, physical well-being; SWB, social well-being; EWB, emotional well-being; FWB, functional well-being; BCS, breast cancer subscale (Higher scores represent better health-related quality of life)</italic>.</p>
</table-wrap-foot>
</table-wrap>
<p>As shown in <xref ref-type="table" rid="T3">Table 3</xref>, in order to more specifically examine which items in lifestyle habits were correlated with HRQoL among younger and older women diagnosed with breast cancer within 2 weeks, we compared the mean scores of the FACT-B Total between two age groups. The relationships of the nine lifestyle habit items with HRQoL were different between younger and older women. First, very satisfied with sleep and current life at diagnosis were criteria associated with higher scores in all the women with breast cancer. Second, tea (<italic>p</italic> = 0.009) and alcohol-drinking (<italic>p</italic> = 0.001) women showed a significantly higher score in the younger age group, while drinking coffee (<italic>p</italic> = 0.009) showed a significantly lower score in the older age group. Third compared to the younger age group, frequent participation in physical activities in the older age group was associated with higher HRQoL overall (<italic>p</italic> = 0.002). And smoking showed worse HRQoL in the older age group (<italic>p</italic> = 0.045). No other significant items of lifestyle habits were observed in association with FACT-B Total scores.</p>
<table-wrap position="float" id="T3">
<label>Table 3</label>
<caption><p>Comparison of mean FACT-B Total scores of lifestyle habit items between the two age groups.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Variable</bold></th>
<th valign="top" align="center" colspan="3" style="border-bottom: thin solid #000000;"><bold>Younger (&#x0003C;50)</bold></th>
<th valign="top" align="center" colspan="3" style="border-bottom: thin solid #000000;"><bold>Older (&#x02265;50)</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>Scores</bold></th>
<th valign="top" align="center"><bold><italic>t</italic></bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
<th valign="top" align="center"><bold>Scores</bold></th>
<th valign="top" align="center"><bold><italic>t</italic></bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Cigarette smoking</td>
<td/>
<td valign="top" align="center">3.838</td>
<td valign="top" align="center">0.050</td>
<td/>
<td valign="top" align="center">4.026</td>
<td valign="top" align="center">0.045</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">91.10 &#x000B1; 17.029</td>
<td/>
<td/>
<td valign="top" align="center">77.67 &#x000B1; 15.080</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">83.80 &#x000B1; 16.418</td>
<td/>
<td/>
<td valign="top" align="center">85.79 &#x000B1; 16.894</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Second-hand smoking</td>
<td/>
<td valign="top" align="center">3.614</td>
<td valign="top" align="center">0.058</td>
<td/>
<td valign="top" align="center">0.127</td>
<td valign="top" align="center">0.722</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">82.59 &#x000B1; 16.531</td>
<td/>
<td/>
<td valign="top" align="center">85.61 &#x000B1; 16.851</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">85.67 &#x000B1; 17.577</td>
<td/>
<td/>
<td valign="top" align="center">86.43 &#x000B1; 18.928</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Alcohol drinking</td>
<td/>
<td valign="top" align="center">10.498</td>
<td valign="top" align="center">0.001</td>
<td/>
<td valign="top" align="center">0.191</td>
<td valign="top" align="center">0.662</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">89.06 &#x000B1; 19.729</td>
<td/>
<td/>
<td valign="top" align="center">86.23 &#x000B1; 17.958</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">83.26 &#x000B1; 15.820</td>
<td/>
<td/>
<td valign="top" align="center">85.17 &#x000B1; 16.834</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Tea</td>
<td/>
<td valign="top" align="center">6.788</td>
<td valign="top" align="center">0.009</td>
<td/>
<td valign="top" align="center">3.775</td>
<td valign="top" align="center">0.053</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">87.22 &#x000B1; 16.178</td>
<td/>
<td/>
<td valign="top" align="center">88.31 &#x000B1; 18.895</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">83.21 &#x000B1; 16.510</td>
<td/>
<td/>
<td valign="top" align="center">84.55 &#x000B1; 16.447</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Coffee</td>
<td/>
<td valign="top" align="center">2.758</td>
<td valign="top" align="center">0.097</td>
<td/>
<td valign="top" align="center">6.955</td>
<td valign="top" align="center">0.009</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">88.81 &#x000B1; 18.541</td>
<td/>
<td/>
<td valign="top" align="center">75.50 &#x000B1; 10.081</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">83.77 &#x000B1; 16.444</td>
<td/>
<td/>
<td valign="top" align="center">85.70 &#x000B1; 17.150</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Sleep satisfaction</td>
<td/>
<td valign="top" align="center">7.275</td>
<td valign="top" align="center">0.001</td>
<td/>
<td valign="top" align="center">4.438</td>
<td valign="top" align="center">0.012</td>
</tr>
<tr>
<td valign="top" align="left">Very satisfied</td>
<td valign="top" align="center">89.63 &#x000B1; 17.633</td>
<td/>
<td/>
<td valign="top" align="center">89.69 &#x000B1; 18.659</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Satisfied</td>
<td valign="top" align="center">82.67 &#x000B1; 15.894</td>
<td/>
<td/>
<td valign="top" align="center">83.68 &#x000B1; 15.668</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Dissatisfied</td>
<td valign="top" align="center">84.89 &#x000B1; 16.878</td>
<td/>
<td/>
<td valign="top" align="center">88.15 &#x000B1; 18.804</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Current life satisfaction</td>
<td/>
<td valign="top" align="center">11.823</td>
<td valign="top" align="center">&#x0003C;0.001</td>
<td/>
<td valign="top" align="center">15.430</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Very satisfied</td>
<td valign="top" align="center">89.10 &#x000B1; 19.505</td>
<td/>
<td/>
<td valign="top" align="center">93.05 &#x000B1; 20.578</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Satisfied</td>
<td valign="top" align="center">84.75 &#x000B1; 15.735</td>
<td/>
<td/>
<td valign="top" align="center">86.57 &#x000B1; 16.390</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Dissatisfied</td>
<td valign="top" align="center">79.24 &#x000B1; 15.840</td>
<td/>
<td/>
<td valign="top" align="center">77.41 &#x000B1; 14.562</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Physical activity</td>
<td/>
<td valign="top" align="center">2.915</td>
<td valign="top" align="center">0.055</td>
<td/>
<td valign="top" align="center">6.345</td>
<td valign="top" align="center">0.002</td>
</tr>
<tr>
<td valign="top" align="left">Often</td>
<td valign="top" align="center">83.93 &#x000B1; 17.145</td>
<td/>
<td/>
<td valign="top" align="center">89.51 &#x000B1; 19.928</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Occasionally</td>
<td valign="top" align="center">85.53 &#x000B1; 17.023</td>
<td/>
<td/>
<td valign="top" align="center">84.97 &#x000B1; 16.064</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">Never</td>
<td valign="top" align="center">82.01 &#x000B1; 14.887</td>
<td/>
<td/>
<td valign="top" align="center">82.36 &#x000B1; 14.589</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">BMI (kg/m<sup>2</sup>)</td>
<td/>
<td valign="top" align="center">1.991</td>
<td valign="top" align="center">0.137</td>
<td/>
<td valign="top" align="center">1.435</td>
<td valign="top" align="center">0.239</td>
</tr>
<tr>
<td valign="top" align="left">&#x0003C;24.0</td>
<td valign="top" align="center">84.73 &#x000B1; 16.417</td>
<td/>
<td/>
<td valign="top" align="center">85.97 &#x000B1; 17.516</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">24.0-28.0</td>
<td valign="top" align="center">82.25 &#x000B1; 15.859</td>
<td/>
<td/>
<td valign="top" align="center">84.52 &#x000B1; 15.862</td>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x0003E;28.0</td>
<td valign="top" align="center">84.82 &#x000B1; 17.045</td>
<td/>
<td/>
<td valign="top" align="center">88.41 &#x000B1; 17.180</td>
<td/>
<td/>
</tr>
</tbody>
</table>
</table-wrap>
<p>Meanwhile, we also analyzed the mean FACT-B scores for each individual HRQoL domain of the nine items in lifestyle habits in <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables 1&#x02013;5</xref>. Each individual domain with statistical differences is summarized in <xref ref-type="table" rid="T4">Table 4</xref>.</p>
<table-wrap position="float" id="T4">
<label>Table 4</label>
<caption><p>The summary of each individual HRQoL domain with statistical differences in nine lifestyle habit items.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Variable</bold></th>
<th valign="top" align="center"><bold>Younger (&#x0003C;50)</bold></th>
<th valign="top" align="center"><bold>Older (&#x02265;50)</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Cigarette smoking</td>
<td valign="top" align="center">SWB(&#x0002B;)</td>
<td valign="top" align="center">EWB(-)</td>
</tr>
<tr>
<td valign="top" align="left">Alcohol drinking</td>
<td valign="top" align="center">SWB(&#x0002B;), EWB(&#x0002B;), BCS(&#x0002B;)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Tea</td>
<td valign="top" align="center">PWB(&#x0002B;), SWB(&#x0002B;), BCS(&#x0002B;)</td>
<td valign="top" align="center">BCS(&#x0002B;)</td>
</tr>
<tr>
<td valign="top" align="left">Coffee</td>
<td valign="top" align="center">PWB(&#x0002B;)</td>
<td valign="top" align="center">EWB(&#x02013;), BCS(&#x02013;)</td>
</tr>
<tr>
<td valign="top" align="left">Sleep satisfaction</td>
<td valign="top" align="center">PWB(&#x0002B;), SWB(&#x0002B;), EWB(&#x0002B;), FWB(&#x0002B;), BCS(&#x0002B;)</td>
<td valign="top" align="center">PWB(&#x0002B;), EWB(&#x0002B;), BCS(&#x0002B;)</td>
</tr>
<tr>
<td valign="top" align="left">Current life satisfaction</td>
<td valign="top" align="center">PWB(&#x0002B;), SWB(&#x0002B;), EWB(&#x0002B;), BCS(&#x0002B;)</td>
<td valign="top" align="center">PWB(&#x0002B;), SWB(&#x0002B;), EWB(&#x0002B;), FWB(&#x0002B;), BCS(&#x0002B;)</td>
</tr>
<tr>
<td valign="top" align="left">Physical activity</td>
<td valign="top" align="center">FWB(&#x0002B;)</td>
<td valign="top" align="center">PWB(&#x0002B;), EWB(&#x0002B;), BCS(&#x0002B;)</td>
</tr>
<tr>
<td valign="top" align="left">BMI (&#x0003E;28)</td>
<td/>
<td valign="top" align="center">BCS(&#x0002B;)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>&#x0002B;: Higher score</italic>.</p>
<p><italic>&#x02013;: Lower score</italic>.</p>
<p><italic>PWB, physical well-being; SWB, social well-being; EWB, emotional well-being; FWB, functional well-being; BCS, breast cancer subscale (Higher scores represent better health-related quality of life)</italic>.</p>
</table-wrap-foot>
</table-wrap>
<p>The relationship of lifestyle habits with HRQoL was further analyzed using GLM, as shown in <xref ref-type="table" rid="T5">Tables 5</xref>, <xref ref-type="table" rid="T6">6</xref>. Tea and alcohol drinking, being very satisfied with sleep and with current life, were again the strongest predictors of higher HRQoL in the younger age group. Meanwhile, no coffee consumption, frequent participation in physical activities, and being very satisfied with sleep and current life were the key predictors of higher HRQoL in the older age group.</p>
<table-wrap position="float" id="T5">
<label>Table 5</label>
<caption><p>Multivariable generalized linear models examining the health-related quality of life scores in relation to lifestyle habits in the younger group (aged &#x0003C;50 years).</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="left"><bold>B</bold></th>
<th valign="top" align="center"><bold>S.E</bold>.</th>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>95% C.I</bold>.</th>
<th valign="top" align="center"><bold>Wald</bold></th>
<th valign="top" align="center"><bold>df</bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
</tr>
<tr>
<th/>
<th/>
<th/>
<th valign="top" align="center"><bold>Lower</bold></th>
<th valign="top" align="center"><bold>Upper</bold></th>
<th/>
<th/>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Alcohol drinking (yes)</td>
<td valign="top" align="center">6.030</td>
<td valign="top" align="center">1.7843</td>
<td valign="top" align="center">2.533</td>
<td valign="top" align="center">9.527</td>
<td valign="top" align="center">11.423</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">Tea (yes)</td>
<td valign="top" align="center">3.524</td>
<td valign="top" align="center">1.5218</td>
<td valign="top" align="center">0.541</td>
<td valign="top" align="center">6.507</td>
<td valign="top" align="center">5.363</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.021</td>
</tr>
<tr>
<td valign="top" align="left">Sleep satisfaction (very satisfied)</td>
<td valign="top" align="center">4.604</td>
<td valign="top" align="center">2.2634</td>
<td valign="top" align="center">0.168</td>
<td valign="top" align="center">9.040</td>
<td valign="top" align="center">4.137</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.042</td>
</tr>
<tr>
<td valign="top" align="left">Current life satisfaction (very satisfied)</td>
<td valign="top" align="center">9.376</td>
<td valign="top" align="center">2.2459</td>
<td valign="top" align="center">4.974</td>
<td valign="top" align="center">13.778</td>
<td valign="top" align="center">17.429</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Intercept</td>
<td valign="top" align="center">84.119</td>
<td valign="top" align="center">2.2748</td>
<td valign="top" align="center">79.661</td>
<td valign="top" align="center">88.578</td>
<td valign="top" align="center">1367.426</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap position="float" id="T6">
<label>Table 6</label>
<caption><p>Multivariable generalized linear models examining the health-related quality of life scores in relation to lifestyle habits in the older group (aged &#x02265;50 years).</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>B</bold></th>
<th valign="top" align="center"><bold>S.E</bold>.</th>
<th valign="top" align="center" colspan="2" style="border-bottom: thin solid #000000;"><bold>95% C.I</bold>.</th>
<th valign="top" align="center"><bold>Wald</bold></th>
<th valign="top" align="center"><bold>df</bold></th>
<th valign="top" align="center"><bold><italic>P</italic></bold></th>
</tr>
<tr>
<th/>
<th/>
<th/>
<th valign="top" align="center"><bold>Lower</bold></th>
<th valign="top" align="center"><bold>Upper</bold></th>
<th/>
<th/>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Coffee (no)</td>
<td valign="top" align="center">9.462</td>
<td valign="top" align="center">3.6877</td>
<td valign="top" align="center">16.609</td>
<td valign="top" align="center">2.234</td>
<td valign="top" align="center">6.583</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.010</td>
</tr>
<tr>
<td valign="top" align="left">Physical activity (often)</td>
<td valign="top" align="center">7.116</td>
<td valign="top" align="center">1.9780</td>
<td valign="top" align="center">3.239</td>
<td valign="top" align="center">10.993</td>
<td valign="top" align="center">12.943</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Sleep satisfaction (very satisfied)</td>
<td valign="top" align="center">4.095</td>
<td valign="top" align="center">1.9618</td>
<td valign="top" align="center">0.250</td>
<td valign="top" align="center">7.940</td>
<td valign="top" align="center">4.358</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">0.037</td>
</tr>
<tr>
<td valign="top" align="left">Current life satisfaction (very satisfied)</td>
<td valign="top" align="center">15.438</td>
<td valign="top" align="center">3.2623</td>
<td valign="top" align="center">8.954</td>
<td valign="top" align="center">21.742</td>
<td valign="top" align="center">22.134</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Intercept</td>
<td valign="top" align="center">78.109</td>
<td valign="top" align="center">4.2783</td>
<td valign="top" align="center">69.724</td>
<td valign="top" align="center">86.494</td>
<td valign="top" align="center">333.311</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
</tbody>
</table>
</table-wrap></sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>In this study, we examined the HRQoL among patients with breast cancer in Chinese populations and investigated their relationship with specific lifestyle habits factors. To the best of our knowledge, this is the first report on the relationship between ages and the specific lifestyle habits factors and HRQoL in Chinese patients with breast cancer using the FACT-B questionnaires. The FACT-B is an international scale developed by Rush-Presbyterian-St. Luke&#x00027;s Medical Center, Chicago, United States, which is widely used to assess the HRQoL of patients with breast cancer (<xref ref-type="bibr" rid="B22">22</xref>). It has been translated into many languages, such as (simplified) Chinese, Malayalam, and Korean (<xref ref-type="bibr" rid="B23">23</xref>). Previous studies have demonstrated that Chinese versions of the FACT-B (version 4) are effective, sensitive, and reliable in evaluating the HRQoL of patients with breast cancer in China (<xref ref-type="bibr" rid="B23">23</xref>&#x02013;<xref ref-type="bibr" rid="B25">25</xref>), which was also confirmed in this study. Using this internationally consistent and effective scale to assess the QoL of Chinese patients is important to improve our understanding of the prognosis of breast cancer.</p>
<p>Previous studies have mostly performed HRQoL tests on female patients for at least 4 months after a breast cancer diagnosis (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B15">15</xref>). By this time, these patients with breast cancer have begun their initial treatment process and have had some time to adapt to their condition. There are few studies that conducted HRQoL tests within a few weeks of a woman being newly diagnosed with breast cancer (<xref ref-type="bibr" rid="B19">19</xref>). In this study, all the newly diagnosed patients have not received surgery or neoadjuvant therapy and have not started further treatment when recruited into this study. As previous studies have demonstrated, the diagnosis of cancer will directly impact a person&#x00027;s mental health immediately, and the ability to cope with the diagnosis will subsequently change greatly (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B26">26</xref>). The early psychosocial adaptation to a diagnosis of breast cancer may have important effects on some survivorship issues, such as receiving and adhering to treatment (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B28">28</xref>), coping mechanisms (<xref ref-type="bibr" rid="B28">28</xref>), and long-term prognosis (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). In this study, 1,199 patients came from 22 different hospitals, and the formulation and decision-making process of each patient&#x00027;s treatment plan was different. Therefore, the completion time of FACT-B questionnaire ranged from 1 day to 14 days after diagnosis. Hence, we set the time point as within 2 weeks of breast cancer diagnosis to analyze the early factors affecting HRQoL of patients with breast cancer in China.</p>
<p>Moreover, the age group with the highest incidence of breast cancer in women is 45&#x02013;59 years old, and some independent studies have reported that the peak age of breast cancer was between 45 and 55 years in China (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B20">20</xref>). In this study, as an approximate indicator of menopausal status, we divided the age into two groups of &#x0003C;50 years old and &#x02265;50 years old; this cutoff point was used for epidemiological studies and HRQoL studies of large-scale breast cancer as well as clinical practice. The results of this study suggested that older patients with breast cancer showed better HRQoL than younger women in most of the HRQoL domains except SWB and PWB, which was supported in previous studies (<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>). Compared to older women, the younger women are more susceptible to suffering from psychosocial influences (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B31">31</xref>), may receive more aggressive treatment than older groups, and are more likely to receive chemotherapy, while older patients have more resources or skills to deal with breast cancer and maintain economic stability.</p>
<p>This study complements the very limited number of research studies that access the impact of lifestyle habits [i.e., smoking (including passive smoking), alcohol intake, dietary habits (tea and coffee), sleep satisfaction, current life satisfaction, physical activity, and BMI] on HRQoL in Chinese women who were diagnosed with breast cancer within 2 weeks. The results suggest that patients with breast cancer who adopted different lifestyle behaviors had different HRQoL between ages, as shown in <xref ref-type="table" rid="T3">Table 3</xref> and <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables 1&#x02013;5</xref>. In this study, cigarette smoking in younger women showed a better SWB while being associated with worse EWB in the older age group, and alcohol drinking was significantly related to better SWB, EWB, and BCS in the younger age group. Previous studies have demonstrated that women who drunk more alcohol daily reported fewer disturbing vasomotor symptoms (<xref ref-type="bibr" rid="B33">33</xref>), which are considered to be the most specific symptom of menopause (<xref ref-type="bibr" rid="B34">34</xref>), while women who smoked cigarettes daily had more symptoms of depression than non-smokers, except for the menstrual symptoms domain (<xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B35">35</xref>). These observations are in agreement with the results of this study, which show worse EWB in older smokers and high HRQoL (including SWB, EWB, and BCS) in younger alcohol consumers.</p>
<p>Clinically significant premenstrual syndrome (PMS) affects 15&#x02013;20% of premenopausal women and significantly reduces QoL (<xref ref-type="bibr" rid="B36">36</xref>). Rossignol et al. (<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B38">38</xref>), along with three other similar studies (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B40">40</xref>), found a strong positive correlation between caffeine and coffee intake and premenstrual syndrome. Women with severe premenstrual symptoms appear to be able to alter caffeine intake, increasing caffeine intake to treat symptoms such as fatigue. These observations support our result that younger women with tea and coffee intake have higher HRQoL (87.22 and 88.81, respectively). In contrast, tea in China has thousands of years of cultural heritage, and older Chinese women prefer to drink traditional tea but refuse coffee, which causes no coffee to have a higher HRQoL. However, this explanation should be provided with discretion and needs more study. But it is worth noting that tea intake was associated with higher HRQoL in both younger and older women. Some studies have shown that tea or its constituents (<xref ref-type="bibr" rid="B41">41</xref>), particularly, epigallocatechin-3-gallate as the most abundant and biologically active tea catechins (<xref ref-type="bibr" rid="B42">42</xref>), suppress mammary tumorigenesis <italic>via</italic> effects on antioxidant activity (<xref ref-type="bibr" rid="B43">43</xref>), sex hormones (<xref ref-type="bibr" rid="B44">44</xref>), or different molecular pathways (<xref ref-type="bibr" rid="B45">45</xref>), which may also have a potential impact on QoL.</p>
<p>It is important to note that the frequency of physical activity was positively associated with higher HRQoL of patients with breast cancer in older group, while there was no statistical difference in the younger group. Angenete et al. found that the preoperative physical activity is positively associated with an enhanced physical recovery after breast cancer surgery (<xref ref-type="bibr" rid="B46">46</xref>). More importantly, evidence from observational studies shows a statistically significant positive correlation between inactivity and sedentary behavior and breast cancer risk and poorer health outcomes (<xref ref-type="bibr" rid="B47">47</xref>, <xref ref-type="bibr" rid="B48">48</xref>). In patients with breast cancer, higher levels of physical activity have been shown to be associated with fewer adverse treatment-related side effects, higher HRQoL, and improved disease-specific prognoses, including longer survival and reduced risk of recurrence and mortality (<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B49">49</xref>). With this evidence, guidelines for physical activity for breast cancer survivors recommend that physical activity should be an integral and ongoing part of the care of all patients with breast cancer.</p>
<p>A population-based survey of HRQoL conducted by Katainen et al. suggested that BMI was a risk factor for lower HRQoL (<xref ref-type="bibr" rid="B33">33</xref>). Women with normal BMI had more physical and vasomotor symptoms than women with BMI lower than 25 kg/m<sup>2</sup>. Women with BMI higher than 30 kg/m<sup>2</sup> had more physical and depressive symptoms than women with a BMI lower than 25 kg/m<sup>2</sup> and have more cognitive impairments than women with lower BMI. In our study, though the distribution of BMI between the younger and older women in China with breast cancer showed significant differences, the BMI showed no influence on HRQoL in all the women. The remaining factors, very satisfied with sleep and current life at diagnosis, were associated with higher HRQoL scores in all the women with breast cancer, as expected.</p>
<p>Finally, the inherent limitations of this study should not be neglected. The most important limitations of this study include that the study was descriptive and cross-sectional, and some factors were collected retrospectively, which may have influenced our results; in our study, all the newly diagnosed patients were enrolled to complete the FACT-B questionnaire before receiving surgery or neoadjuvant therapy and further treatment, so the exact stage of the disease has not been determined, which may be an important factor affecting the HRQoL of patients. Notwithstanding its limitations, the results of this large population-based study may help guide interventions to improve QoL. It is believed that this study can provide reference and a basis for future research and also pave the road for finding patient-centered solutions for evidence-based selection of optimal treatments, decision-making process, psychosocial interventions, patient&#x02013;physician communications, etc.</p></sec>
<sec sec-type="conclusions" id="s5">
<title>Conclusion</title>
<p>In summary, we found that younger patients &#x0003C;50 years showed significantly lower HRQoL than older patients &#x02265;50 years. The relationship of the nine lifestyle habit items with HRQoL was different between younger and older women. The associated variable of QoL can help clinicians identify patients at risk for low QoL. When these characteristics or situations can be balanced, changing them through intervention can improve a patient&#x00027;s QoL, and as women gradually receive treatment and then enter into their long-term survivorship period, their effects may change subsequent adjustments and functions regarding breast cancer, consequently improving the prognosis of patients with breast cancer.</p></sec>
<sec sec-type="data-availability" id="s6">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary Material</xref>, further inquiries can be directed to the corresponding author/s.</p></sec>
<sec id="s7">
<title>Ethics Statement</title>
<p>All procedures performed involving human participants were in accordance with the Ethical Standards of the Second Hospital of Shandong University Research Committee with the approval number 2010004. The patients/participants provided their written informed consent to participate in this study.</p></sec>
<sec id="s8">
<title>Author Contributions</title>
<p>Z-GY conceived the study. CZ, H-YJ, and LL contributed to the study design and performed statistical analyses. CZ and LL wrote the manuscript. L-YL, FW, FZ, Y-JX, M-MG, Y-JW, and S-YH contributed to manuscript revision and statistical analyses. S-DC, F-GT, Z-MF, C-ZG, X-CC, Z-LY, XW, HL, SW, H-CJ, X-ND, H-BW, G-LL, Q-TW, J-GZ, FJ, J-HT, LL, S-GZ, and W-SZ contributed to the collection of the data and biological samples. All authors contributed to the article and approved the submitted version.</p></sec>
<sec sec-type="funding-information" id="s9">
<title>Funding</title>
<p>This research was primarily granted funding from the Minister-affiliated hospital key project of the Ministry of Health of the People&#x00027;s Republic of China (establishment and improvement of high-risk populations screening and evaluation system for breast cancer), the Major Scientific and Technological Innovation Project of Shandong Province (2017CXGC1212), the National Key Research and Development Program of China (2016YFC0901304), the National Natural Science Foundation of China (81702603), the Taishan Scholars Program of Shandong Province (tsqn201812135), and the China Postdoctoral Science Foundation (2021T140408 and 2021M691934).</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec sec-type="disclaimer" id="s10">
<title>Publisher&#x00027;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec> </body>
<back>
<ack><p>The authors gratefully thank Santosh Kumar Paidi from Johns Hopkins University, USA, for useful comments, suggestions, and language editing for improving the manuscript. We would like to thank all participants involved in the study for their cooperation.</p>
</ack>
<sec sec-type="supplementary-material" id="s11">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpubh.2021.767151/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpubh.2021.767151/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/></sec>
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</ref-list>
<glossary>
<def-list>
<title>Abbreviations</title>
<def-item><term>HRQoL</term>
<def><p>Health-related quality of life</p></def></def-item>
<def-item><term>WHO</term>
<def><p>World Health Organization</p></def></def-item>
<def-item><term>QoL</term>
<def><p>Quality of life</p></def></def-item>
<def-item><term>FACT-B</term>
<def><p>Functional Assessment of Cancer Therapy-Breast Cancer</p></def></def-item>
<def-item><term>BCS</term>
<def><p>Breast cancer subscale</p></def></def-item>
<def-item><term>PWB</term>
<def><p>Physical well-being</p></def></def-item>
<def-item><term>SWB</term>
<def><p>Social/family well-being</p></def></def-item>
<def-item><term>EWB</term>
<def><p>Emotional well-being</p></def></def-item>
<def-item><term>FWB</term>
<def><p>Functional well-being</p></def></def-item>
<def-item><term>PMS</term>
<def><p>Premenstrual syndrome</p></def></def-item>
<def-item><term>ANOVA</term>
<def><p>Analysis of variance.</p></def></def-item>
</def-list>
</glossary> 
</back>
</article> 