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Vynckier P, Schmidt M, Nayani S, Guariguata L, Devleesschauwer B, Verhaeghe N. The economic burden of smoking in Belgium: incremental healthcare costs and lost productivity. Eur J Public Health 2025; 35:108-113. [PMID: 39844617 PMCID: PMC11832142 DOI: 10.1093/eurpub/ckae211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2025] Open
Abstract
Tobacco use is among the leading behavioural risk factors for morbidity and mortality. These high rates result in a high cost to society. Therefore, the aim of the current study was to provide a contemporary overview of the direct medical and indirect costs attributable to smoking tobacco in Belgium. Data from the Belgian Health Interview Survey (BHIS) was combined with health insurance claims data. Healthcare costs were calculated on individuals' cigarette smoking patterns (daily, former, and never smokers). Lost productivity costs were calculated by multiplying the number of absence days by the national average wage cost per day. Univariate and multivariable regression analyses with negative binomial distribution and log link were performed to evaluate the average healthcare costs and indirect costs in relation to tobacco use, socio-demographic characteristics, and (behavioural) risk factors. A total of 10 829 individuals were included in the analyses, of which 47.7% were men, with 15% being smokers. Men were more likely to be smokers than women (56.8% vs. 43.2%; P < 0.001). Compared to never smokers, significantly higher direct medical costs were found for daily (20%; P = 0.03) and former smokers (27%; P < 0.001). No significant differences were observed for the indirect costs for the smoking population compared to never smokers. Taking into account that 15% of the Belgian population were daily smokers in 2018, the national cost for daily smokers equates to €533.861.010. Results of our study show that cigarette smoking has higher direct medical costs compared with never smokers.
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Affiliation(s)
- Pieter Vynckier
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Masja Schmidt
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - Sarah Nayani
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - Leonor Guariguata
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
| | - Brecht Devleesschauwer
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
- Department of Translational Physiology, Infectiology and Public Health, Ghent University—Campus Merelbeke, Merelbeke, Belgium
| | - Nick Verhaeghe
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
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Schurz AP, Walter MM, Liechti M, Clijsen R, Deliens T, Taeymans J, Lutz N. Health economic evaluation of weight reduction interventions in individuals suffering from overweight or obesity and a musculoskeletal diagnosis-a systematic review. BMC Musculoskelet Disord 2024; 25:744. [PMID: 39285383 PMCID: PMC11406846 DOI: 10.1186/s12891-024-07861-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 09/09/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND Most of the worldwide population is overweight and suffers from the resulting musculoskeletal comorbidities such as knee osteoarthritis or back pain. Practice guidelines recommend weight loss interventions for individuals suffering from these conditions. This systematic review investigated whether including a weight loss intervention in the musculoskeletal therapy of these individuals was cost-effective compared to administering the musculoskeletal therapy alone. METHODS This study followed the PRISMA guidelines to systematically and independently search six databases and select full health economic evaluations published up to May 2024 from health care or societal perspectives according to predefined eligibility criteria. Cost data were standardised to 2023 Belgium Euros. The methodological quality was assessed using two health economic-specific checklists. RESULTS The searches produced 5'305 references, of which 8 studies were selected for a total of 1'726 participants. The interventions consisted of different exercise plans and nutritional targets. Six values were in the north-eastern; leading to increased quality-adjusted life year (QALY) and higher costs; and two in the south-eastern quadrant of the cost-utility plane; leading to increased QALYs and lower costs. Two studies observed no differences in QALYs. Incremental cost utility ratios (ICUR) ranged from €13'580.10 to €34'412.40 per additional QALY from a healthcare perspective. From a societal perspective, the ICUR was €30'274.84. The included studies fulfilled 86 percent of the criteria in trial-based economic evaluations and 57 percent in model-based economic evaluations. The most common limitations of the studies were related to appropriate cost measures' specifications, research questions, time horizon choices, and sensitivity analyses. CONCLUSIONS This systematic review showed weak but consistent evidence of cost-effectiveness for adding a weight loss intervention to musculoskeletal therapy for individuals with overweight, from either perspective. Further economic evaluations should evaluate the long-term cost-effectiveness of the intervention. TRIAL REGISTRATION International Platform of Registered Systematic Review and Meta-analysis Protocols INPLASY (2022,110,122).
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Affiliation(s)
- Alexander P Schurz
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium.
- Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland.
- Faculty of Medicine, University of Bern, Murtenstrasse 10, Bern, CH-3008, Switzerland.
| | - Matthias M Walter
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Science and Research, Physio Insight, Haslach Im Kinzigtal, Baden-Württemberg, Germany
| | - Melanie Liechti
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland
| | - Ron Clijsen
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland
- Rehabilitation and Exercise Science Laboratory RESLab, Department of Business Economics, Health, and Social Care, University of Applied Sciences and Arts of Southern Switzerland, Landquart/Manno, Switzerland
- International University of Applied Sciences THIM, Landquart, Switzerland
| | - Tom Deliens
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Jan Taeymans
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland
| | - Nathanael Lutz
- Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland
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Łagowska K, Kuleta-Koberska A, Michalak M, Bajerska J. The effect of shift work on body mass index: A systematic review and meta-analysis of observational studies. Am J Hum Biol 2024; 36:e24041. [PMID: 38189567 DOI: 10.1002/ajhb.24041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 11/18/2023] [Accepted: 12/23/2023] [Indexed: 01/09/2024] Open
Abstract
CONTEXT Shift work involves working outside the standard working hours of 9 am to 5 pm Monday to Friday and may include working evening, night, weekend, or rotating shift patterns. Since shift workers sleep less and their circadian rhythms are disrupted, they are reported to have higher body weight than day workers. OBJECTIVE This meta-analysis aims to determine whether shift workers (SW) are more prone to higher body mass index (BMI) than their day workers (DW) counterparts. It also addresses the question of whether the duration of shift work exposure, sex, or occupational type affect BMI value. METHODS Four databases that is PubMed, EBSCO Host, Scopus, and Web of Science were searched for reports published up to October 2023. RESULTS Sixty-three studies involving a total of 693 449 participants met our inclusion criteria. Meta-analyses showed a significant effect of shift work on BMI value (standard mean difference; SMD: 0.10 kg/m2 [95% confidence interval; 95% CI: 0.07; 0.13; p < .001]) as compared with non-shift counterparts. Subgroup analysis revealed that shift work significantly increased BMI for studies where male working on this job schedule (SMD: 0.10 kg/m2 [95% CI: 0.04; 0.17; p = .0018]) for studies where shift workers worked ≥13 years (calculated as the median of shift work experience; SMD: 0.14 kg/m2 [95% CI: 0.10; 0.18; p < .001]) as well as for studies where industrial (SMD: 0.12 kg/m2 [95% CI: 0.05; 0.19; p = .0012]) and other type of occupations were dominated (0.12 kg/m2 [95% CI: 0.07; 0.16; p < .001]). CONCLUSIONS We found that in general working on a shift schedule increases BMI as compared with day workers, especially in case of male employed in this job schedule, for shift workers working for long periods of time (≥13 years), and for shift workers employed in industry and other type of occupations(e.g., airline workers, firefighters, police officers, blue collar, security personnel, bus drivers, garbage collectors, railway workers, postal, oil and gas workers).
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Affiliation(s)
- Karolina Łagowska
- Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Wojska Polskiego, Poznań, Poland
| | - Agnieszka Kuleta-Koberska
- Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Wojska Polskiego, Poznań, Poland
| | - Michał Michalak
- Department of Computer Sciences and Statistics, Poznań University of Medical Sciences, Poznań, Poland
| | - Joanna Bajerska
- Department of Human Nutrition and Dietetics, Poznań University of Life Sciences, Wojska Polskiego, Poznań, Poland
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Tran PB, Nikolaidis GF, Abatih E, Bos P, Berete F, Gorasso V, Van der Heyden J, Kazibwe J, Tomeny EM, Van Hal G, Beutels P, van Olmen J. Multimorbidity healthcare expenditure in Belgium: a 4-year analysis (COMORB study). Health Res Policy Syst 2024; 22:35. [PMID: 38519938 PMCID: PMC10960468 DOI: 10.1186/s12961-024-01113-x] [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: 11/01/2023] [Accepted: 01/24/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND The complex management of health needs in multimorbid patients, alongside limited cost data, presents challenges in developing cost-effective patient-care pathways. We estimated the costs of managing 171 dyads and 969 triads in Belgium, taking into account the influence of morbidity interactions on costs. METHODS We followed a retrospective longitudinal study design, using the linked Belgian Health Interview Survey 2018 and the administrative claim database 2017-2020 hosted by the Intermutualistic Agency. We included people aged 15 and older, who had complete profiles (N = 9753). Applying a system costing perspective, the average annual direct cost per person per dyad/triad was presented in 2022 Euro and comprised mainly direct medical costs. We developed mixed models to analyse the impact of single chronic conditions, dyads and triads on healthcare costs, considering two-/three-way interactions within dyads/triads, key cost determinants and clustering at the household level. RESULTS People with multimorbidity constituted nearly half of the study population and their total healthcare cost constituted around three quarters of the healthcare cost of the study population. The most common dyad, arthropathies + dorsopathies, with a 14% prevalence rate, accounted for 11% of the total national health expenditure. The most frequent triad, arthropathies + dorsopathies + hypertension, with a 5% prevalence rate, contributed 5%. The average annual direct costs per person with dyad and triad were €3515 (95% CI 3093-3937) and €4592 (95% CI 3920-5264), respectively. Dyads and triads associated with cancer, diabetes, chronic fatigue, and genitourinary problems incurred the highest costs. In most cases, the cost associated with multimorbidity was lower or not substantially different from the combined cost of the same conditions observed in separate patients. CONCLUSION Prevalent morbidity combinations, rather than high-cost ones, made a greater contribution to total national health expenditure. Our study contributes to the sparse evidence on this topic globally and in Europe, with the aim of improving cost-effective care for patients with diverse needs.
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Affiliation(s)
- Phuong Bich Tran
- Department of Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium.
- Department of Epidemiology and public health, Brussels, Belgium.
| | | | - Emmanuel Abatih
- Department of Applied Mathematics, Computer Sciences and Statistics, Ghent University, Ghent, Belgium
| | - Philippe Bos
- Department of Sociology, University of Antwerp, Antwerp, Belgium
| | - Finaba Berete
- Department of Epidemiology and public health, Brussels, Belgium
| | - Vanessa Gorasso
- Department of Epidemiology and public health, Brussels, Belgium
| | | | - Joseph Kazibwe
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ewan Morgan Tomeny
- Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Guido Van Hal
- Department of Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), University of Antwerp, Antwerp, Belgium
| | - Josefien van Olmen
- Department of Family Medicine and Population Health, University of Antwerp, Antwerp, Belgium
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Hua Y, Xie D, Zhang Y, Wang M, Wen W, Sun J. Identification and analysis of key genes in adipose tissue for human obesity based on bioinformatics. Gene 2023; 888:147755. [PMID: 37659596 DOI: 10.1016/j.gene.2023.147755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 08/17/2023] [Accepted: 08/30/2023] [Indexed: 09/04/2023]
Abstract
BACKGROUND Obesity is a complex condition that is affected by a variety of factors, including the environment, behavior, and genetics. However, the genetic mechanisms underlying obesity remains poorly elucidated. Therefore, our study aimed at identifying key genes for human obesity using bioinformatics analysis. METHODS The microarray datasets of adipose tissue in humans were downloaded from the Gene Expression Omnibus (GEO) database. After the selection of differentially expressed genes (DEGs), we used Lasso regression and Support Vector Machine (SVM) algorithm to further identify the feature genes. Moreover, immune cell infiltration analysis, gene set variation analysis (GSVA), GeneCards database and transcriptional regulation analysis were conducted to study the potential mechanisms by which the feature genes may impact obesity. We utilized receiver operating characteristic (ROC) curve to analysis the diagnostic efficacy of feature genes. Finally, we verified the feature genes in cell experiments and animal experiments. The statistical analyses in validation experiments were conducted using SPSS version 28.0, and the graph were generated using GraphPad Prism 9.0 software. The bioinformatics analyses were conducted using R language (version 4.2.2), with a significance threshold of p < 0.05 used. RESULTS 199 DEGs were selected using Limma package, and subsequently, 5 feature genes (EGR2, NPY1R, GREM1, BMP3 and COL8A1) were selected through Lasso regression and SVM algorithm. Through various bioinformatics analyses, we found some signaling pathways by which feature genes influence obesity and also revealed the crucial role of these genes in the immune microenvironment, as well as their strong correlations with obesity-related genes. Additionally, ROC curve showed that all the feature genes had good predictive and diagnostic efficiency in obesity. Finally, after validation through in vitro experiments, EGR2, NPY1R and GREM1 were identified as the key genes. CONCLUSIONS This study identified EGR2, GREM1 and NPY1R as the potential key genes and potential diagnostic biomarkers for obesity in humans. Moreover, EGR2 was discovered as a key gene for obesity in human adipose tissue for the first time, which may provide novel targets for diagnosing and treating obesity.
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Affiliation(s)
- Yuchen Hua
- The Second School of Clinical Medicine, Southern Medical University, No.1023, South Shatai Road, Baiyun District, Guangzhou, Guangdong 510515, China
| | - Danyingzhu Xie
- Department of Endocrinology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, Guangdong Province 510282, China
| | - Yugang Zhang
- Department of Endocrinology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, Guangdong Province 510282, China
| | - Ming Wang
- Department of Traditional Chinese Medicine, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, Guangdong Province 510282, China.
| | - Weiheng Wen
- Department of Endocrinology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, Guangdong Province 510282, China.
| | - Jia Sun
- Department of Endocrinology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, Guangdong Province 510282, China.
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Vandevijvere S, De Pauw R, Djojosoeparto S, Gorasso V, Guariguata L, Løvhaug AL, Mialon M, Van Dam I, von Philipsborn P. Upstream Determinants of Overweight and Obesity in Europe. Curr Obes Rep 2023; 12:417-428. [PMID: 37594616 DOI: 10.1007/s13679-023-00524-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/20/2023] [Indexed: 08/19/2023]
Abstract
PURPOSE OF REVIEW To review the upstream determinants of overweight and obesity in Europe, including food and built environments, and political, commercial, and socioeconomic determinants. RECENT FINDINGS Overweight and obesity affect 60% of European adults, and one in three children, and are more common in individuals with low compared to high socioeconomic position (SEP). Individuals in low SEP groups are more exposed to unhealthy built and food environments, including higher exposure to unhealthy food marketing. Industries influencing the food system have much economic power, resulting in ignoring or silencing the role of ultra-processed foods and commercial practices in weight gain. Overall, effective policies to address overweight and obesity have been insufficiently implemented by governments. To accelerate implementation, strengthened political commitment is essential. Policies must also focus on the upstream, structural, and systemic drivers of overweight and obesity; be comprehensive; and target socioeconomic inequalities in diets and physical activity.
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Affiliation(s)
- Stefanie Vandevijvere
- Department of Epidemiology and Public Health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium.
| | - Robby De Pauw
- Department of Epidemiology and Public Health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - Sanne Djojosoeparto
- Consumption and Healthy Lifestyles Chair Group, Wageningen University and Research, Wageningen, The Netherlands
| | - Vanessa Gorasso
- Department of Epidemiology and Public Health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - Leonor Guariguata
- Department of Epidemiology and Public Health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - Anne Lene Løvhaug
- Department of Nursing and Health Promotion, OsloMet-Oslo Metropolitan University, Oslo, Norway
| | | | - Iris Van Dam
- Department of Epidemiology and Public Health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - Peter von Philipsborn
- Pettenkofer School of Public Health, Ludwig-Maximilians-Universität München, Munich, Germany
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Berete F, Demarest S, Charafeddine R, De Ridder K, Van Oyen H, Van Hoof W, Bruyère O, Van der Heyden J. Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium. Arch Public Health 2023; 81:198. [PMID: 37968754 PMCID: PMC10648729 DOI: 10.1186/s13690-023-01213-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 11/03/2023] [Indexed: 11/17/2023] Open
Abstract
In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.
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Affiliation(s)
- Finaba Berete
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium.
- Department of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium.
| | - Stefaan Demarest
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
| | - Rana Charafeddine
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
| | - Karin De Ridder
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
| | - Herman Van Oyen
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
- Department of Public Health and Primary Care, Ghent University, Ghent, Belgium
| | - Wannes Van Hoof
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
| | - Olivier Bruyère
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Ageing, Research Unit in Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
| | - Johan Van der Heyden
- Department of Epidemiology and Public Health, Sciensano, Juliette Wytsmanstraat 14, Brussels, 1050, Belgium
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Zhao S, Xu X, You H, Ge J, Wu Q. Healthcare costs attributable to abnormal weight in China: evidence based on a longitudinal study. BMC Public Health 2023; 23:1927. [PMID: 37798694 PMCID: PMC10552200 DOI: 10.1186/s12889-023-16855-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 09/28/2023] [Indexed: 10/07/2023] Open
Abstract
BACKGROUND The prevalence of abnormal weight is on the rise, presenting serious health risks and socioeconomic problems. Nonetheless, there is a lack of studies on the medical cost savings that can be attained through the mitigation of abnormal weight. The aim of this study was to estimate the impact of abnormal weight on healthcare costs in China. METHODS The study employed a 4-wave panel data from China Family Panel Studies (CFPS) between 2012 and 2018 (11,209 participants in each wave). Inpatient, non-inpatient and total healthcare costs were outcome variables. Abnormal weight is categorized based on body mass index (BMI). Initially, the two-part model was employed to investigate the impact of overweight/obesity and underweight on healthcare utilisation and costs, respectively. Subsequently, the estimated results were utilised to calculate the overweight/obesity attributable fraction (OAF) and the underweight attributable fraction (UAF). RESULTS In 2018, healthcare costs per person for overweight and obese population were estimated to be $607.51 and $639.28, respectively, and the underweight population was $755.55. In comparison to people of normal weight, individuals who were overweight/obese (OR = 1.067, p < 0.05) was more likely to utilise healthcare services. Overweight/obesity attributable fraction (OAF) was 3.90% of total healthcare costs and 4.31% of non-inpatient costs. Overweight/obesity does not result in additional healthcare expenditures for young people but increases healthcare costs for middle-aged adults (OAF = 7.28%) and older adults (OAF = 6.48%). The non-inpatient cost of underweight population was significantly higher than that of normal weight population (β = 0.060,p < 0.1), but the non-inpatient health service utilisation was not significantly affected. CONCLUSIONS Abnormal weight imposes a huge economic burden on individuals, households and the society. Abnormal weight in Chinese adults significantly increased healthcare utilisation and costs, particular in non-inpatient care. It is recommended that government and relevant social agencies provide a better social environment to enhance individual self-perception and promote healthy weight.
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Affiliation(s)
- Shiqi Zhao
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, Jiangsu, P.R. China
| | - Xinpeng Xu
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, Jiangsu, P.R. China.
- Institute of Healthy Jiangsu Development, Nanjing Medical University, Nanjing, China.
| | - Hua You
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, Jiangsu, P.R. China.
- Institute of Healthy Jiangsu Development, Nanjing Medical University, Nanjing, China.
| | - Jinjin Ge
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, Jiangsu, P.R. China
| | - Qifeng Wu
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, Jiangsu, P.R. China
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