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Soria-Reyes LM, Cerezo MV, Molina P, Blanca MJ. Life Satisfaction and Character Strengths in Women With Breast Cancer: Zest and Hope as Predictors. Integr Cancer Ther 2023; 22:15347354231197648. [PMID: 37799020 PMCID: PMC10559710 DOI: 10.1177/15347354231197648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/24/2023] [Accepted: 08/11/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND Empirical evidence shows that life satisfaction is positively related to character strengths, and although this association has been observed in different populations, it is scarce in breast cancer patients. This study analyzes the relationship between character strengths and life satisfaction in Spanish women diagnosed with breast cancer. METHODS A sample of 117 women completed the Satisfaction with Life Scale (SWLS) and the Spanish version of the VIA Inventory of Strengths (VIA-IS). Correlation analysis and regression modeling were performed to determine which strengths predict life satisfaction. RESULTS The results of the correlation analysis showed that 15 strengths were positively and significantly associated with life satisfaction, with the highest correlations corresponding to zest, hope, curiosity, social intelligence, love, gratitude, and judgment. Regression modeling indicated that of these, zest and hope were key strengths for predicting life satisfaction. CONCLUSIONS These findings suggest that intervention programs based on the development of zest and hope could help to improve life satisfaction and, therefore, the psychological well-being of women with breast cancer.
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Mei S, Yuan T, Liang L, Ren H, Hu Y, Qin Z, Fei J, Cao R, Li C, Hu Y. Effect of family stress on life satisfaction among female workers during the COVID-19 epidemic in China: Exploring the roles of anxiety symptoms and age. J Health Psychol 2022; 27:1484-1497. [PMID: 34658282 DOI: 10.1177/13591053211044824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
The study aimed to investigate the level of life satisfaction (LS) among Chinese female workers after resuming work during the COVID-19 epidemic, and to further explore the potential mediating and moderating roles in the association between family stress and LS. Self-reported questionnaires were completed by 10,175 participants. Results showed that the level of LS decreased. The family stress had a negative effect on LS, and the effect was mediated by anxiety symptoms. Additionally, age moderated the direct and indirect effects within this relationship. Interventions aiming to improve LS should consider these aspects and younger workers should be given special attention.
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Affiliation(s)
| | | | | | - Hui Ren
- Jilin University, Jilin Province, China
- The First Hospital of Jilin University, Changchun, China
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You W, Henneberg M. Large household reduces dementia mortality: A cross-sectional data analysis of 183 populations. PLoS One 2022; 17:e0263309. [PMID: 35239673 PMCID: PMC8893634 DOI: 10.1371/journal.pone.0263309] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 01/15/2022] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Large households/families may create more happiness and offer more comprehensive healthcare among the members. We correlated household size to dementia mortality rate at population level for analysing its protecting role against dementia mortality. METHODS This is a retrospective cross-sectional study. Dementia specific mortality rates of the 183 member states of World Health Organization were calculated and matched with the respective country data on household size, Gross Domestic Product (GDP), urban population and ageing. Scatter plots were produced to explore and visualize the correlations between household size and dementia mortality rates. Pearson's and nonparametric correlations were used to evaluate the strength and direction of the associations between household size and all other variables. Partial correlation of Pearson's approach was used to identify that household size protects against dementia regardless of the competing effects from ageing, GDP and urbanization. Multiple regression was used to identify significant predictors of dementia mortality. RESULTS Household size was in a negative and moderately strong correlation (r = -0.6034, p < 0.001) with dementia mortality. This relationship was confirmed in both Pearson r (r = - 0.524, p<0.001) and nonparametric (rho = -0.579, p < 0.001) analyses. When we controlled for the contribution of ageing, socio-economic status and urban lifestyle in partial correlation analysis, large household was still in inverse and significant correlation to dementia mortality (r = -0.331, p <0.001). This suggested that, statistically, large household protect against dementia mortality regardless of the contributing effects of ageing, socio-economic status and urban lifestyle. Stepwise multiple regression analysis selected large household as the variable having the greatest contribution to dementia mortality with R2 = 0.263 while ageing was placed second increasing R2 to 0.259. GDP and urbanization were removed as having no statistically significant influence on dementia mortality. CONCLUSIONS While acknowledging ageing, urban lifestyle and greater GDP associated with dementia mortality, this study suggested that, at population level, household size was another risk factor for dementia mortality. As part of dementia prevention, healthcare practitioners should encourage people to increase their positive interactions with persons from their neighbourhood or other fields where large household/family size is hard to achieve.
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Affiliation(s)
- Wenpeng You
- School of Biomedicine, The University of Adelaide, Adelaide, Australia
| | - Maciej Henneberg
- School of Biomedicine, The University of Adelaide, Adelaide, Australia
- Institute of Evolutionary Medicine, University of Zurich, Zürich, Switzerland
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Huang Y, Wang H, Lyu Z, Dai H, Liu P, Zhu Y, Song F, Chen K. Development and evaluation of the screening performance of a low-cost high-risk screening strategy for breast cancer. Cancer Biol Med 2021; 19:j.issn.2095-3941.2020.0758. [PMID: 34570443 PMCID: PMC9500221 DOI: 10.20892/j.issn.2095-3941.2020.0758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 04/06/2021] [Indexed: 01/31/2023] Open
Abstract
OBJECTIVE To develop and evaluate the screening performance of a low-cost high-risk screening strategy for breast cancer in low resource areas. METHODS Based on the Multi-modality Independent Screening Trial, 6 questionnaire-based risk factors of breast cancer (age at menarche, age at menopause, age at first live birth, oral contraceptive, obesity, family history of breast cancer) were used to determine the women with high risk of breast cancer. The screening performance of clinical breast examination (CBE), breast ultrasonography (BUS), and mammography (MAM) were calculated and compared to determine the optimal screening method for these high risk women. RESULTS A total of 94 breast cancers were detected among 31,720 asymptomatic Chinese women aged 45-65 years. Due to significantly higher detection rates (DRs) and suitable coverage of the population, high risk women were defined as those with any of 6 risk factors. Among high risk women, the DR for BUS [3.09/1,000 (33/10,694)] was similar to that for MAM [3.18/1,000 (34/10,696)], while it was significantly higher than that for the CBE [1.73/1,000 (19/10,959), P = 0.002]. Compared with MAM, BUS showed significantly higher specificity [98.64% (10,501/10,646) vs. 98.06% (10,443/10,650), P = 0.001], but no significant differences in sensitivity [68.75% (33/48) vs. 73.91% (34/46)], positive prediction values [18.54% (33/178) vs. 14.11% (34/241)], and negative prediction values [99.86% (10,501/10,516) vs. 99.89% (10,443/10,455)]. Further analyses showed no significant difference in the percentages of early stage breast cancer [53.57% (15/28) vs. 50.00% (15/30)], lymph node involvement [22.73% (5/22) vs. 28.00% (7/25)], and tumor size ≥ 2 cm [37.04% (10/27) vs. 29.03% (9/31)] between BUS and MAM. Subgroup analyses stratified by breast densities or age at enrollment showed similar results. CONCLUSIONS The low-cost high-risk screening strategy based on 6 questionnaire-based risk factors was an easy-to-use method to identify women with high risk of breast cancer. Moreover, BUS and MAM had comparable screening performances among high risk women.
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Affiliation(s)
- Yubei Huang
- Department of Cancer Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Huan Wang
- Department of Cancer Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Zhangyan Lyu
- Department of Cancer Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Hongji Dai
- Department of Cancer Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Peifang Liu
- Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Ying Zhu
- Department of Breast Imaging, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Fengju Song
- Department of Cancer Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
| | - Kexin Chen
- Department of Cancer Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Key Laboratory of Cancer Molecular Epidemiology of Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, Tianjin 300060, China
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Abstract
OBJECTIVE The present study tested preregistered predictions regarding the prospective associations between level and change in subjective well-being (SWB) and physical health. METHODS In two large longitudinal panel studies conducted in the United States (N = 3294) and Japan (N = 657), we used multilevel growth curve models to estimate level and change in components of SWB (i.e., life satisfaction, positive affect, and negative affect). Next, we used random intercepts and slopes to predict subsequent self-reported general health and number of chronic health conditions (in the United States and Japan) and mortality risk (in the United States). RESULTS Greater life satisfaction, higher positive affect, and lower negative affect were associated with better health (0.22 < |β values| < 0.46) and longer survival. Above and beyond SWB level, longitudinal increases in life satisfaction and positive affect and longitudinal decreases in negative affect were associated with better health (0.06 < |β values| < 0.20). Moreover, all three SWB components independently predicted health, and life satisfaction and negative affect independently predicted survival. The preregistration and analysis scripts are available at osf.io/mz9gy. CONCLUSIONS The present findings suggest that being happy and becoming happier across time are independently associated with better physical health in the United States and Japan.
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Martín-María N, Caballero FF, Moreno-Agostino D, Olaya B, Haro JM, Ayuso-Mateos JL, Miret M. Relationship between subjective well-being and healthy lifestyle behaviours in older adults: a longitudinal study. Aging Ment Health 2020; 24:611-619. [PMID: 30590962 DOI: 10.1080/13607863.2018.1548567] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Objectives: People who report better subjective well-being tend to be healthier in their daily behaviours. The objective of this study is to assess whether different components of subjective well-being are prospectively associated with different healthy lifestyle behaviours and to assess whether these associations differ by age.Method: A total of 1,892 participants aged 50+ living in Spain were interviewed in 2011-12 and 2014-15. Life satisfaction was measured with the Cantril Self-Anchoring Striving Scale. Positive and negative affect were assessed using the Day Reconstruction Method. Physical activity was assessed with the Global Physical Activity Questionnaire version 2. The remaining healthy lifestyle behaviours were self-reported. Generalised Estimating Equations (GEE) models were run.Results: Not having a heavy episodic alcohol drinking was the healthy lifestyle behaviour most fulfilled (97.97%), whereas the intake of five or more fruits and vegetables was the least followed (33.12%). GEE models conducted over the 50-64 and the 65+ age groups showed that a higher life satisfaction was significantly related to a higher physical activity in both groups. Relationships between a higher negative affect and presenting a lower level of physical activity, and a higher positive affect and following the right consumption of fruits and vegetables and being a non-daily smoker, were only found in the older group.Conclusion: The relationship between subjective well-being and healthy lifestyle behaviours was found fundamentally in those aged 65+ years. Interventions focused on incrementing subjective well-being would have an impact on keeping a healthy lifestyle and, therefore, on reducing morbidity and mortality.
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Affiliation(s)
- Natalia Martín-María
- Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM, Madrid, Spain.,Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Madrid, Spain
| | - Francisco Félix Caballero
- Department of Preventive Medicine, Public Health and Microbiology, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública. CIBERESP, Madrid, Spain
| | - Darío Moreno-Agostino
- Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM, Madrid, Spain.,Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Madrid, Spain
| | - Beatriz Olaya
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM, Madrid, Spain.,Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Sant Boi de Llobregat, Barcelona, Spain
| | - Josep Maria Haro
- Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM, Madrid, Spain.,Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Sant Boi de Llobregat, Barcelona, Spain
| | - José Luis Ayuso-Mateos
- Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM, Madrid, Spain.,Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Madrid, Spain
| | - Marta Miret
- Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain.,Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM, Madrid, Spain.,Department of Psychiatry, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Madrid, Spain
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You W, Rühli FJ, Henneberg RJ, Henneberg M. Greater family size is associated with less cancer risk: an ecological analysis of 178 countries. BMC Cancer 2018; 18:924. [PMID: 30257658 PMCID: PMC6156945 DOI: 10.1186/s12885-018-4837-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 09/19/2018] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Greater family size measured with total fertility rate (TFR) and with household size, may offer more life satisfaction to the family members. Positive psychological well-being has been postulated to decrease cancer initiation risk. This ecological study aims to examine the worldwide correlation between family size, used as the measure of positive psychological well-being, and total cancer incidence rates. METHODS Country specific estimates obtained from United Nations agencies on total cancer incidence rates (total, female and male rates in age range 0-49 years and all ages respectively), all ages site cancer incidence (bladder, breast, cervix uteri, colorectum, corpus uteri, lung, ovary and stomach), TFR, household size, life expectancy, urbanization, per capita GDP PPP and self-calculated Biological State Index (Ibs) were matched for data analysis. Pearson's, non-parametric Spearman's, partial correlations, independent T-test and multivariate regressions were conducted in SPSS. RESULTS Worldwide, TFR and household size were significantly and negatively correlated to all the cancer incidence variables. These correlations remained significant in partial correlation analysis when GDP, life expectancy, Ibs and urbanization were controlled for. TFR correlated to male cancer incidence rate (all ages) significantly stronger than it did to female cancer incidence rate (all ages) in both Pearson's and partial correlations. Multivariate stepwise regression analysis indicated that TFR and household size were consistently significant predictors of all cancer incidence variables. CONCLUSIONS Countries with greater family size have lower cancer risk in both females, and especially males. Our results seem to suggest that it may be worthwhile further examining correlations between family size and cancer risk in males and females through the cohort and case-control studies based on large samples.
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Affiliation(s)
- Wenpeng You
- Adelaide Medical School, The University of Adelaide, Adelaide, SA 5005 Australia
| | - Frank J Rühli
- Institute of Evolutionary Medicine, University of Zurich, Zürich, Switzerland
| | - Renata J Henneberg
- Biological Anthropology and Comparative Anatomy Unit, Adelaide Medical School, The University of Adelaide, Adelaide, Australia
| | - Maciej Henneberg
- Adelaide Medical School, The University of Adelaide, Adelaide, SA 5005 Australia
- Institute of Evolutionary Medicine, University of Zurich, Zürich, Switzerland
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You W, Henneberg M. Prostate Cancer Incidence is Correlated to Total Meat Intake– a Cross-National Ecologic Analysis of 172 Countries. Asian Pac J Cancer Prev 2018; 19:2229-2239. [PMID: 30139230 PMCID: PMC6171413 DOI: 10.22034/apjcp.2018.19.8.2229] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 07/17/2018] [Indexed: 02/05/2023] Open
Abstract
Objective: To examine the association of total meat (animal flesh) consumption to prostate cancer incidence (PC61) at population level. Subjects and Methods: Data from 172 countries were extracted for analysis. Associations between country specific per capita total meat intake and PC61 incidence at country level were examined using Pearson’s r and Spearman rho, partial correlation, stepwise multiple linear regression analyses with ageing, GDP, Is (index of magnitude of prostate cancer gene accumulation at population level), obesity prevalence and urbanization included as the confounding factors. Countries were also grouped for regional association analysis. The data were log-transformed for analysis in SPSS. Microsoft Excel, and ANOVA Post hoc Scheffe tests were applied to calculate and compare mean differences between country groupings. Results: Worldwide, total meat intake was strongly and positively associated with PC61 incidence in Pearson’s r (r= 0.595, p<0.001) and Spearman rho (r= 0.637, p<0.001) analyses. This relationship remained significant in partial correlation (r= 0.295, p<0.001) when ageing, GDP, Is, obesity prevalence and urbanization were kept statistically constant. GDP was weakly and insignificantly associated with PC61 when total meat intake was kept statistically constant. Stepwise multiple linear regression identified that total meat was a significant predictor of PC61 with total meat intake and all the five confounders included as the independent variables (R2=0.417). Post hoc Scheffe tests revealed nine significant mean differences of PC61 between the six WHO regions, but all disappeared when the contributing effect of total meat on PC61 incidence rate was removed. GDP was not identified as the statistically significant predictor of PC61 in either of the models including or excluding total meat as the independent variable. Conclusions: Total meat intake is an independent predictor of PC61 worldwide, and the determinant of regional variation of PC61. The longitudinal cohort studies are proposed to explore the association further.
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Affiliation(s)
- Wenpeng You
- Adelaide Medical School, University of Adelaide, Australia.
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You W, Symonds I, Henneberg M. Low fertility may be a significant determinant of ovarian cancer worldwide: an ecological analysis of cross- sectional data from 182 countries. J Ovarian Res 2018; 11:68. [PMID: 30115095 PMCID: PMC6097201 DOI: 10.1186/s13048-018-0441-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2018] [Accepted: 08/07/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Ageing, socioeconomic level, obesity, fertility, relaxed natural selection and urbanization have been postulated as the risk factors of ovarian cancer (OC56). We sought to identify which factor plays the most significant role in predicting OC56 incidence rate worldwide. METHODS Bivariate correlation analysis was performed to assess the relationships between country-specific estimates of ageing (measured by life expectancy), GDP PPP (Purchasing power parity), obesity prevalence, fertility (indexed by the crude birth rate), opportunity for natural selection (Ibs) and urbanization. Partial correlation was used to compare contribution of different variables. Fisher A-to-Z was used to compare the correlation coefficients. Multiple linear regression (Enter and Stepwise) was conducted to identify significant determinants of OC56 incidence. ANOVA with post hoc Bonferroni analysis was performed to compare differences between the means of OC56 incidence rate and residuals of OC56 standardised on fertility and GDP respectively between the six WHO regions. RESULTS Bivariate analyses revealed that OC56 was significantly and strongly correlated to ageing, GDP, obesity, low fertility, Ibs and urbanization. However, partial correlation analysis identified that fertility and ageing were the only variables that had a significant correlation to OC56 incidence when the other five variables were kept statistically constant. Fisher A-to-Z revealed that OC56 had a significantly stronger correlation to low fertility than to ageing. Stepwise linear regression analysis only identified fertility as the significant predictor of OC56. ANOVA showed that, between the six WHO regions, multiple mean differences of OC56 incidence were significant, but all disappeared when the contributing effect of fertility on OC56 incidence rate was removed. CONCLUSIONS Low fertility may be the most significant determining predictor of OC56 incidence worldwide.
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Affiliation(s)
- Wenpeng You
- Adelaide Medical School, The University of Adelaide, Adelaide, SA Australia
| | - Ian Symonds
- Adelaide Medical School, The University of Adelaide, Adelaide, SA Australia
| | - Maciej Henneberg
- Adelaide Medical School, The University of Adelaide, Adelaide, SA Australia
- Institute of Evolutionary Medicine, University of Zürich, 8057 Zurich, Switzerland
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Wang SQ, Ying J, Zhang ML, Shi Y, Li Y, Xing ZJ, Li HH, Sun J. Health-related life satisfaction and its influencing factors: A cross-sectional study in China. Jpn J Nurs Sci 2018; 15:285-297. [PMID: 29363255 DOI: 10.1111/jjns.12201] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 09/27/2017] [Indexed: 11/29/2022]
Abstract
AIM With the rapid development of science and technology, the pace of life has accelerated. Health and life satisfaction issues of persons are gaining more attention. China, Japan, Malaysia, and Taiwan conducted international cooperative research on health of four regional populations. This research was a part of the study in mainland China, which aimed to explore health-related life satisfaction and its influencing factors on large samples in mainland China. METHODS A random group of 1404 persons from universities, factories, companies, and elderly centers in Changchun completed a structured questionnaire. This study centered on life satisfaction indicators, which included the current whole life, income, family relationships, peer relationships, relationships with the neighbors, living environment, personal health, family health, spare time, and housework share. Other collected data included the Body Mass Index, blood pressure, self-rated health, Breslow's seven health practices, medical treatment within the past 6 months, physical examinations, General Health Questionnaire (GHQ)-12 Scale, social activities, networking relationships with persons around the community, social support, and sociodemographic variables. Associations between life satisfaction, demographics, and health-related variables were analyzed through a multiway ANOVA. RESULTS The living environment and income of Chinese persons were related to their low life satisfaction. The multiway ANOVA showed that the independent relationship of self-rated health, regular physical examinations, GHQ-12 Scale, trust in the community, communication with the neighbors, education, and age related with life satisfaction accounting for 20.3% of the variance. Education and age showed interactive effects on life satisfaction. CONCLUSION This study identified seven factors that influenced the life satisfaction of persons in mainland China. Life satisfaction can be enhanced through interventions to improve self-rated health, regular physical examinations, mental health, trust in the community, communication with the neighbors, education, and improvement in the health service.
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Affiliation(s)
- Shou-Qi Wang
- College of Nursing, Jilin University, Changchun, China
| | - Jie Ying
- College of Nursing, Jilin University, Changchun, China
| | | | - Ying Shi
- College of Nursing, Jilin University, Changchun, China
| | - Yuan Li
- College of Nursing, Jilin University, Changchun, China
| | | | - Huan-Huan Li
- College of Nursing, Jilin University, Changchun, China
| | - Jiao Sun
- College of Nursing, Jilin University, Changchun, China
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Dong H, Huang Y, Song F, Dai H, Liu P, Zhu Y, Wang P, Han J, Hao X, Chen K. Improved Performance of Adjunctive Ultrasonography After Mammography Screening for Breast Cancer Among Chinese Females. Clin Breast Cancer 2017; 18:e353-e361. [PMID: 28887010 DOI: 10.1016/j.clbc.2017.07.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2017] [Revised: 07/13/2017] [Accepted: 07/17/2017] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Until now, no studies have investigated whether women other than those with dense breasts are suitable for adjunctive ultrasonography after negative mammography, and investigated whether all women with negative mammography are suitable for adjunctive ultrasonography. METHODS Based on the Multi-modality Independent Screening Trial in China, a total of 31,918 women aged 45 to 65 years underwent both ultrasonography and mammography. Physicians performed ultrasonography and mammography separately and were blinded to each other's findings until their interpretations had been recorded. For both ultrasonography and mammography, suspicious results and those highly suggestive of a malignancy were confirmed by pathologic examination, whereas other results were confirmed by 1-year follow-up after initial screening. RESULTS Based on Breast Imaging Reporting and Data System (BIRADS) assessments, 84 (84.8%) of 99 cancers were identified on mammography (detection rate, 2.6/1000), and 61 (61.6%) of 99 cancers were identified on ultrasonography (detection rate, 1.9/1000). Integrated mammography with ultrasonography identified 94 (95.0%) of 99 cancers, with an increment of 11.9% in cancer detection rate (from 2.6/1000 to 2.9/1000) (P < .05). Moreover, among women with BIRADS 3, adjunctive ultrasonography detected no cancers. All 10 additional cancers detected by adjunctive ultrasonography were from women with BIRADS 0 to 2, at a cost of 207 women with false positives. Additionally, dense breasts and benign breast disease were significantly associated with positive ultrasonography after BIRADS 0 to 2 (all P values < .05). CONCLUSIONS After negative mammography, adjunctive ultrasonography should only be recommended for BIRADS 0 to 2 but not BIRADS 3, especially for women with dense breasts or benign breast disease.
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Affiliation(s)
- Henglei Dong
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Yubei Huang
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Peifang Liu
- Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Ying Zhu
- Department of Breast Imaging, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Peishan Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China
| | - Jiali Han
- Department of Epidemiology, Fairbanks School of Public Health, Simon Cancer Center, Indiana University, Indianapolis, IN
| | - Xishan Hao
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China; Chinese Anti-Cancer Association, Tianjin, China.
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Key Laboratory of Breast Cancer Prevention and Therapy, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
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12
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Olsson M, Nilsson M, Fugl-Meyer K, Petersson LM, Wennman-Larsen A, Kjeldgård L, Alexanderson K. Life satisfaction of women of working age shortly after breast cancer surgery. Qual Life Res 2017; 26:673-684. [PMID: 28070803 PMCID: PMC5309315 DOI: 10.1007/s11136-016-1479-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2016] [Indexed: 12/21/2022]
Abstract
Purpose To explore, among women of working age, satisfaction with life as a whole and with different life domains, and its associations with social and health variables, shortly after breast cancer surgery. Methods This cross-sectional study included 605 women, aged 20–63 years, who had had breast cancer surgery with no distant metastasis, pre-surgical chemotherapy, or previous breast cancer. Associations between LiSat-11 and demographic and social factors as well as health- and treatment-related variables were analysed by multivariable logistic regression. Results Compared with Swedish reference levels, the women were, after breast cancer surgery, less satisfied with life, particularly sexual life. Women working shortly after breast cancer surgery were more often satisfied with life in provision domains compared with the reference population. Although most included variables showed associations with satisfaction, after adjustment for all significantly associated variables, only six variables—having children, being in work, having emotional and informational social support, and having good physical and emotional functioning—were positively associated with satisfaction with life as a whole. The odds ratios for satisfaction were higher in most life domains if the woman had social support and good emotional and cognitive functioning. Conclusions One month after breast cancer surgery, satisfaction with different life domains was associated primarily with social support and health-related functioning. However, this soon after surgery, treatment-related variables showed no significant associations with life satisfaction. These results are useful for planning interventions to enhance e.g. social support and emotional as well as cognitive functioning.
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Affiliation(s)
- Mariann Olsson
- Division of Social Work, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
| | - Marie Nilsson
- Division of Social Work, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Social Work, Karolinska University Hospital, Stockholm, Sweden.,Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Kerstin Fugl-Meyer
- Division of Social Work, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Social Work, Karolinska University Hospital, Stockholm, Sweden
| | - Lena-Marie Petersson
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Agneta Wennman-Larsen
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Sophiahemmet University, Stockholm, Sweden
| | - Linnea Kjeldgård
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Kristina Alexanderson
- Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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13
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Bai A, Li H, Huang Y, Liu X, Gao Y, Wang P, Dai H, Song F, Hao X, Chen K. A survey of overall life satisfaction and its association with breast diseases in Chinese women. Cancer Med 2015; 5:111-9. [PMID: 26640035 PMCID: PMC4708902 DOI: 10.1002/cam4.565] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Revised: 09/16/2015] [Accepted: 09/21/2015] [Indexed: 12/17/2022] Open
Abstract
To investigate the association between overall life satisfaction and healthy lifestyle, knowledge of breast cancer, physical examination, and detection rate of breast cancer and benign breast disease in Chinese women. In a multicentered breast disease screening program in China, we enrolled 33,057 women aged 45-65 years without prior diagnosis of breast cancer. After completing an epidemiological questionnaire, all participants were examined by clinical breast examination, breast ultrasound, and mammography independently. All breast cancer cases and a selected sample of benign breast diseases were confirmed pathologically. Univariate and multivariate odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the association between life satisfaction and lifestyle, knowledge of breast cancer, physical examination, and detection rate of breast diseases. Overall life satisfaction was positively associated with women's healthy lifestyle. Compared with less satisfied women, satisfied women were less likely to be smokers (OR = 0.54; 95% CI: 0.47-0.62), have more exercise (OR = 1.49; 95% CI: 1.26-1.75), eat less fried (OR = 0.60; 95% CI: 0.50-0.71), smoked (OR = 0.54, 95% CI: 0.47-0.63), pickled (OR = 0.66, 95% CI: 0.55-0.79), and grilled (OR = 0.63, 95% CI: 0.54-0.74) foods. Satisfied women were more likely to have knowledge of breast cancer (OR = 1.48, 95% CI: 1.29-1.70), and have regular physical examinations (OR = 1.11, 95% CI: 1.01-1.12). Compared to less satisfied women, we found significantly lower detection rate of benign breast diseases (OR = 0.90, 95% CI: 0.82-0.99), and lower but nonsignificant detection rate of breast cancer (OR = 0.66, 95% CI: 0.35-1.25) in satisfied women. Women with a higher overall life satisfaction are more likely to have healthy lifestyle, knowledge of breast cancer, and regular physical examination, thus resulting in a lower detection rate of breast diseases in screening.
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Affiliation(s)
- Aili Bai
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Haixin Li
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Yubei Huang
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Xueou Liu
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Ying Gao
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Peishan Wang
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Hongji Dai
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Fengju Song
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Xishan Hao
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
| | - Kexin Chen
- Departments of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin, National Clinical Research Center of Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China
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