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Wang S, Miao Y, Feng Y, Zhao L, Wu X, Jia S, Zhao W, Tarimo CS, Zuo Y, Guo X, Ma M, Wu J. Mediation Effect of Obesity on the Association of Socioeconomic Status with Blood Pressure in the Elderly Hypertensive Population. Nutrients 2024; 16:2401. [PMID: 39125283 PMCID: PMC11314009 DOI: 10.3390/nu16152401] [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: 06/03/2024] [Revised: 07/16/2024] [Accepted: 07/16/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Socioeconomic status (SES) plays a crucial role in blood pressure (BP) control. SES may influence BP control through obesity indices, such as body mass index (BMI) and waist circumference (WC). This study aimed to understand the relationships between SES and BP control in the elderly hypertensive population, and to determine whether BMI and WC mediate the relationship between SES and BP control. METHODS The study was conducted in Jia County, Henan Province, China, from 1 July to 31 August 2023. The 18,963 hypertensive people over 65 years old who were included in the National Basic Public Health Service Program were investigated. The study utilized questionnaire surveys to collect data on participants' demographic characteristics, disease history, lifestyle behaviors, antihypertensive medication, and measured height, weight, and blood pressure. SES was indexed by participants' self-reported educational level, family income, and occupation, and categorized into low, medium, and high groups by using latent category analysis (LCA). Logistic regression models were used to analyze the associations between SES and BP control. Obesity indicators, represented by BMI and WC, were included in mediation models to examine the indirect effects of BMI/WC on the association between SES and BP control. RESULTS The mean age of 17,234 participants was 73.4 years and 9888 (57.4%) of the participants were female. The LCA results indicated the number of participants in low SES, middle SES, and high SES groups were 7760, 8347, and 1127, respectively. Compared with the low SES group, the odds ratios (ORs) and 95% confidence intervals (CIs) for the association of BP control with middle SES and high SES were 1.101 (1.031, 1.175), and 1.492 (1.312, 1.696). This association was similarly found in the subsequent subgroup analyses (p < 0.05). Compared with low SES, our findings further suggested that BMI (indirect effects: 95% CIs: -0.004--0.001; p < 0.001) and WC (indirect effects: 95% CIs: -0.003--0.001; p = 0.020) play a suppressing role in the association between high SES and BP control. CONCLUSIONS Our study indicated that the elderly hypertensive population with high SES may have a better result for BP control. However, we found that BMI/WC plays a suppressing role in this association. This indicated that despite the better BP control observed in elderly hypertensive populations with high SES, BMI and WC might undermine this beneficial relationship. Therefore, implementing strategies for obesity prevention is an efficient way to maintain this beneficial association between high SES and BP control.
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Affiliation(s)
- Saiyi Wang
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Yudong Miao
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Yifei Feng
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Lipei Zhao
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Xiaoman Wu
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Shiyu Jia
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Weijia Zhao
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Clifford Silver Tarimo
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
- Department of Science and Laboratory Technology, Dar es Salaam Institute of Technology, Dar es Salaam P.O. Box 2958, Tanzania
| | - Yibo Zuo
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Xinghong Guo
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Mingze Ma
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
| | - Jian Wu
- Department of Health Management, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin District, Zhengzhou 450001, China; (S.W.); (Y.M.); (Y.F.); (L.Z.); (X.W.); (S.J.); (W.Z.); (Y.Z.); (X.G.); (M.M.)
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Paár D, Pogátsa Z, Ács P, Szentei A. The Relationship between Inequalities in Household Sports Consumption Expenditures and Income Level. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15608. [PMID: 36497681 PMCID: PMC9736210 DOI: 10.3390/ijerph192315608] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 11/17/2022] [Accepted: 11/20/2022] [Indexed: 06/17/2023]
Abstract
Inequalities in income, wealth, quality of life, health and education are an intensively researched field of economics. In this study, we examine the inequality in sports expenditures of Hungarian households. We hypothesize that the development of income inequalities will also correlate significantly to inequalities in sports consumption, and this trend has been intensifying over the past two decades. The research is based on the Household Budget Survey database of Hungarian households for the period 2005-2017. The net income conditions of the population and the sports expenditure items recorded on the basis of the COICOP nomenclature are examined by income decile. Data is analysed using descriptive statistics, inequality indicators and correlation calculations. Aggregate household expenditures on passive sports consumption show a stagnant trend, while aggregate expenditures on active sports consumption follow a slightly upward trend among the Hungarian population. Inequality indicators show growing inequalities in terms of income and sports expenditure over the reviewed period. Income inequality and sports spending inequality move together. The Hungarian population is becoming polarised in terms of both income and level of sports expenditure.
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Affiliation(s)
- Dávid Paár
- Faculty of Health Sciences, Institute of Physiotherapy and Sport Sciences, University of Pécs, H-7621 Pecs, Hungary
| | - Zoltán Pogátsa
- Alexandre Lámfalussy Faculty of Economics, University of Sopron, H-9400 Sopron, Hungary
| | - Pongrác Ács
- Faculty of Health Sciences, Institute of Physiotherapy and Sport Sciences, University of Pécs, H-7621 Pecs, Hungary
| | - András Szentei
- Faculty of Health Sciences, Institute of Physiotherapy and Sport Sciences, University of Pécs, H-7621 Pecs, Hungary
- Faculty of Health Sciences, Doctoral School of Health Sciences, University of Pécs, H-7621 Pecs, Hungary
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Park S, Lee KS, Choi M, Lee M. Factors associated with quality of life in patients with benign prostatic hyperplasia, 2009-2016. Medicine (Baltimore) 2022; 101:e30091. [PMID: 36086750 PMCID: PMC9512327 DOI: 10.1097/md.0000000000030091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 06/29/2022] [Indexed: 11/25/2022] Open
Abstract
This study analyzed the factors affecting the health-related quality of life of patients with benign prostatic hyperplasia (BPH) according to age. We also aimed to determine appropriate strategies to improve their quality of life. Data from the Korea Health Panel Survey (2009-2016) were used in this study. A total of 3806 patients with BPH were divided into 2 groups: younger adults (aged under 65 years) and older adults (aged over 65 years). In addition, a logistic regression analysis was conducted to identify factors affecting the quality of life of young and older patients with BPH. In younger adult patients with BPH, the higher the level of education, the higher the quality of life by a factor of 1.379, and the more intense the physical activity, the lower the quality of life by a factor of 0.791. Also, the longer the sitting time, the lower the quality of life by a factor of 0.765. In contrast, for older adult patients with BPH, the quality of life improved by factors of 1.601 and 2.921, respectively, for health insurance and higher income level. In addition, it was found that the quality of life decreased by a factor of 0.754 in patients who drink alcohol. In order to improve the quality of life of the middle-aged adult population with BPH, it is necessary to reduce sitting time through constant physical activity. Moreover, the cost of medical care should be reduced and the quality of life increased through reductions in surgical treatment, as the burden of medical expenses will degrade the quality of life for older adults.
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Affiliation(s)
- Sewon Park
- Department of Medical Humanities and Social Medicine, Ajou University School of Medicine, Suwon, South Korea
| | - Kyu-Sung Lee
- Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Mankyu Choi
- Department of Health Policy & Management, College of Health Science, Korea University, Seoul, South Korea
- BK21 FOUR R&E Center for Learning Health Systems, Korea University, Seoul, South Korea
| | - Munjae Lee
- Department of Medical Humanities and Social Medicine, Ajou University School of Medicine, Suwon, South Korea
- Medical Research Collaborating Center, Ajou Research Institute for Innovative Medicine, Ajou University Medical Center, Suwon, South Korea
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Ford L, Chinta R, Fiedler A. Patient demographics as determinants of where they go for hospitalization, what inpatient care they get, and what they are charged: A national study. Health Mark Q 2021; 39:315-336. [PMID: 34436983 DOI: 10.1080/07359683.2021.1965814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
This study focuses on the impact of race, income, age, and gender on hospital charges in the US. The data include 28,133 discharge records for appendectomies from a stratified sample of 4,584 hospitals in the HCUP's (Hospital Cost and Utilization Project) NIS (National Inpatient Sample) database. Results show that race, income, and age were significant determinants of hospital charges. Gender was not significantly related to the variance in hospital charges. Additionally, hospital variables (ownership/control region, teaching status, size, and primary expected payer) had statistically significant effects on hospital charges. We conclude with implications for clinicians, hospital administrators, and policy makers.
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Affiliation(s)
- Lori Ford
- Huizenga College of Business and Entrepreneurship, Nova Southeastern University, Ft. Lauderdale, FL, USA
| | - Ravi Chinta
- Huizenga College of Business and Entrepreneurship, Nova Southeastern University, Ft. Lauderdale, FL, USA
| | - Anne Fiedler
- Huizenga College of Business and Entrepreneurship, Nova Southeastern University, Ft. Lauderdale, FL, USA
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Income Inequality and Outcomes in Heart Failure. JACC-HEART FAILURE 2019; 7:336-346. [DOI: 10.1016/j.jchf.2018.11.005] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 10/29/2018] [Accepted: 11/02/2018] [Indexed: 11/18/2022]
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Bojko MM, Kucejko RJ, Poggio JL. Racial Disparities and the Effect of County Level Income on the Incidence and Survival of Young Men with Anal Cancer. Health Equity 2018; 2:193-198. [PMID: 30283867 PMCID: PMC6110184 DOI: 10.1089/heq.2018.0018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Purpose: Prior studies have identified a racial disparity in incidence and survival of squamous cell carcinoma of the anus (SCCA) in the young African American male population. We aim to determine whether racial disparities are independent of income and urban location. Methods: The National Cancer Institute's Surveillance of Epidemiology and End Results database was queried for data on patients with SCCA for the years of 2000-2013. Cox regression was used to determine the effect of race, county median family income, rural-urban continuum, and stage of disease on overall survival. Results: The incidence rate of SCCA was significantly higher in black men <50 years old than in white men. Black race had a hazard ratio of 1.55 (confidence interval [CI] 1.33-1.81) when controlling for age, stage, income, and urban-rural status. Each $10,000 increase in county median family income was protective with a hazard ratio of 0.90 (CI 0.86-0.94). Residence in a metropolitan area did not significantly affect survival. Conclusions: The lower survival of black men <50 years old with SCCA is independent of income, urban location, and stage of disease. Further efforts are needed to target this at-risk population and the authors suggest wide application of previously validated screening programs for anal dysplasia.
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Affiliation(s)
- Markian M Bojko
- Department of Surgery, Drexel University College of Medicine, Philadelphia, Pennsylvania
| | - Robert J Kucejko
- Department of Surgery, Drexel University College of Medicine, Philadelphia, Pennsylvania
| | - Juan L Poggio
- Division of Colorectal Surgery, Department of Surgery, Drexel University College of Medicine, Philadelphia, Pennsylvania
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Tumin D, Menegay M, Shrider EA, Nau M, Tumin R. Local Income Inequality, Individual Socioeconomic Status, and Unmet Healthcare Needs in Ohio, USA. Health Equity 2018; 2:37-44. [PMID: 30283849 PMCID: PMC6071904 DOI: 10.1089/heq.2017.0058] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Purpose: Income inequality has been implicated as a potential risk to population health due to lower provision of healthcare services in deeply unequal countries or communities. We tested whether county economic inequality was associated with individual self-report of unmet healthcare needs using a state health survey data set. Methods: Adults residents of Ohio responding to the 2015 Ohio Medicaid Assessment Survey were included in the analysis. Ohio's 88 counties were classified into quartiles according to the Gini coefficient of income inequality. The primary outcome was a composite of self-reported unmet dental care, vision care, mental healthcare, prescription medication, or other healthcare needs within the past year. Unmet healthcare needs were compared according to county inequality quartile using weighted logistic regression. Results: The analytic sample included 37,140 adults. The weighted proportion of adults with unmet healthcare needs was 28%. In multivariable logistic regression, residents of counties in the highest (odds ratio [OR]=1.13, 95% confidence interval [CI]: 1.01-1.26; p=0.030) and second-highest (OR=1.16, 95% CI: 1.04-1.30; p=0.010) quartiles of income inequality experienced more unmet healthcare needs than residents of the most equal counties. Conclusion: Higher county-level income inequality was associated with individual unmet healthcare needs in a large state survey. This finding represents novel evidence for an individual-level association that may explain aggregate-level associations between community economic inequality and population health outcomes.
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Affiliation(s)
- Dmitry Tumin
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio
| | - Michelle Menegay
- The Ohio Colleges of Medicine Government Resource Center, Columbus, Ohio.,Division of Epidemiology, The Ohio State University College of Public Health, Columbus, Ohio
| | - Emily A Shrider
- Department of Sociology, The Ohio State University, Columbus, Ohio
| | - Michael Nau
- The Ohio Colleges of Medicine Government Resource Center, Columbus, Ohio
| | - Rachel Tumin
- The Ohio Colleges of Medicine Government Resource Center, Columbus, Ohio
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Lago S, Cantarero D, Rivera B, Pascual M, Blázquez-Fernández C, Casal B, Reyes F. Socioeconomic status, health inequalities and non-communicable diseases: a systematic review. ZEITSCHRIFT FUR GESUNDHEITSWISSENSCHAFTEN = JOURNAL OF PUBLIC HEALTH 2017; 26:1-14. [PMID: 29416959 PMCID: PMC5794817 DOI: 10.1007/s10389-017-0850-z] [Citation(s) in RCA: 82] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 09/25/2017] [Indexed: 11/07/2022]
Abstract
AIM A comprehensive approach to health highlights its close relationship with the social and economic conditions, physical environment and individual lifestyles. However, this relationship is not exempt from methodological problems that may bias the establishment of direct effects between the variables studied. Thus, further research is necessary to investigate the role of socioeconomic variables, their composition and distribution according to health status, particularly on non-communicable diseases. SUBJECTS AND METHODS To shed light on this field, here a systematic review is performed using PubMed, the Cochrane Library and Web of Science. A 7-year retrospective horizon was considered until 21 July 2017. RESULTS Twenty-six papers were obtained from the database search. Additionally, results from "hand searching" were also included, where a wider horizon was considered. Five of the 26 studies analyzed used aggregated data compared to 21 using individual data. Eleven considered income as a study variable, while 17 analyzed the effect of income inequality on health status (2 of the studies considered both the absolute level and distribution of income). The most used indicator of inequality in the literature was the Gini index. CONCLUSION Although different types of analysis produce very different results concerning the role of health determinants, the general conclusion is that income distribution is related to health where it represents a measure of the differences in social class in the society. The effect of income inequality is to increase the gap between social classes or to widen differences in status.
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Affiliation(s)
- Santiago Lago
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Applied Economics, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
| | - David Cantarero
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Economics, Faculty of Business and Economics University of Cantabria, Avda. de los Castros, S/N, 39005 Santander, Spain
| | - Berta Rivera
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Applied Economics, Faculty of Business and Economics University of A Coruña, Campus de Elviña, 15071 A Coruña, Spain
| | - Marta Pascual
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Economics, Faculty of Business and Economics University of Cantabria, Avda. de los Castros, S/N, 39005 Santander, Spain
| | - Carla Blázquez-Fernández
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Economics, Faculty of Business and Economics University of Cantabria, Avda. de los Castros, S/N, 39005 Santander, Spain
| | - Bruno Casal
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Applied Economics, Faculty of Business and Economics University of A Coruña, Campus de Elviña, 15071 A Coruña, Spain
| | - Francisco Reyes
- GEN Governance and Economics Network-Spain, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
- Department of Applied Economics, Faculty of Business and Tourism University of Vigo, Campus Universitario As Lagoas s/n, 32004 Ourense, Spain
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Tumin D, Horan J, Shrider EA, Smith SA, Tobias JD, Hayes D, Foraker RE. County socioeconomic characteristics and heart transplant outcomes in the United States. Am Heart J 2017; 190:104-112. [PMID: 28760203 DOI: 10.1016/j.ahj.2017.05.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 05/27/2017] [Indexed: 11/25/2022]
Abstract
BACKGROUND Geographic disparities in survival after heart transplantation have received mixed support in prior studies, and specific geographic characteristics that might be responsible for these differences are unclear. We tested for differences in heart transplant outcomes across United States (US) counties after adjustment for individual-level covariates. Our secondary aim was to evaluate whether specific county-level socioeconomic characteristics explained geographic disparities in survival. METHODS Data on patients aged ≥18 years undergoing a first-time heart transplant between July 2006 and December 2014 were obtained from the United Network for Organ Sharing. Residents of counties represented by <5 patients were excluded. Patient survival (censored in March 2016) was analyzed using multivariable Cox regression. Shared frailty models were used to test for residual differences in overall all-cause mortality across counties after adjusting for recipient and donor characteristics. Measures of county economic disadvantage, inequality, and racial segregation were obtained from US Census data and coded into quintiles. A likelihood ratio test determined whether adjusting for each county measure improved the fit of the Cox model. RESULTS Multivariable analysis of 10,879 heart transplant recipients found that, adjusting for individual-level characteristics, there remained statistically significant variation in mortality hazard across US counties (P=.004). Adjusting for quintiles of community disadvantage, economic inequality, or racial segregation did not significantly improve model fit (likelihood ratio test P=.092, P=.273, and P=.107, respectively) and did not explain residual differences in patient survival across counties. CONCLUSIONS Heart transplantation outcomes vary by county, but this difference is not attributable to county-level socioeconomic disadvantage.
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