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Gong X, Tang Y, Zhang M, Yu Y, Hu W, Xu Y, Liu Y, Sun H, Yu G, Zhai C, Zong Q, Wang F, Zou Y. The Global Burden of Disease Attributable to Child and Maternal Malnutrition: 1990-2019. Pediatrics 2024:e2023064167. [PMID: 38832449 DOI: 10.1542/peds.2023-064167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 06/05/2024] Open
Abstract
OBJECTIVE With this study, we aimed to estimate the disease burden attributable to child and maternal malnutrition (CMM) throughout the world between 1990 and 2019. METHODS The number, age-standardized rate, population attributable fraction of deaths, disability-adjusted life-years, years of life lost, and years lived with disability associated with CMM were estimated using the Global Burden of Disease Study 2019 by age, sex, year, location, and sociodemographic index at the global level. The slope index of inequality and concentration index were employed to measure socioeconomic-related health inequalities across countries. RESULTS The number (million) of global deaths, disability-adjusted life-years, and years of life lost related to CMM were 2.9, 294.8, and 250.5 in 2019, showing decreases of 60.8, 57.4, and 60.7% since 1990. However, the number of years lived with CMM-related disability increased from 36.0 in 1990 to 44.3 in 2019. Additionally, the age-standardized rates of these 4 indicators showed varying degrees of decline. The global burden of CMM-related conditions differed with age and sex. The burden was the heaviest in western sub-Saharan Africa, especially in Chad. In terms of diseases, neonatal disorders represented the most significant burden attributed to CMM. Additionally, the CMM burden was more concentrated in regions with low sociodemographic indices, shown by the slope index of inequality and concentration index. CONCLUSIONS The findings of this study highlight the ongoing global burden of CMM, particularly in terms of years lived with disability. Population-wide actions targeting the effective treatment and relief of CMM may reduce the CMM-related disease burden.
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Affiliation(s)
- Xingyu Gong
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Yuqin Tang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Mingyi Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Yingying Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Wanqin Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Ying Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Yuqi Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Hongyu Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Guanghui Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Chunxia Zhai
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Qiqun Zong
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
| | - Fang Wang
- Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yanfeng Zou
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; and
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O'Hara HM. The Work, Play, and Worship Environments as Social Determinants of Health. Prim Care 2023; 50:621-631. [PMID: 37866835 DOI: 10.1016/j.pop.2023.04.009] [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] [Indexed: 10/24/2023]
Abstract
Consideration of the definition of the social determinants of health (SDOHs) requires health care to include work, play, and worship environments because they are important to the health of patients and communities. This article attempts to discuss the issues with limited focus on these areas and the importance of using multidisciplinary health-care teams during primary care visits. The expectation from this information is to advance the ability for primary care providers to support patients and the communities they work in to effect change toward decreasing health disparities and enhancing overall health outcomes.
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Affiliation(s)
- Heather M O'Hara
- Memorial Occupational Health Clinic, 2120 North 27th Street, Decatur, IL 62526, USA.
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Khosravi A, Mohamadi E, Sheidaei A, Shafiee G, Heshmat R, Olyaeemanesh A, Takian A. Child mortality inequalities and socioeconomic determinants of health in Iran, 2016-2018. J Public Health Policy 2023; 44:535-550. [PMID: 37898702 DOI: 10.1057/s41271-023-00448-z] [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] [Accepted: 10/03/2023] [Indexed: 10/30/2023]
Abstract
Measuring health inequalities is essential to inform policy making and for monitoring implementation to reduce avoidable and unfair differences in health status. We conducted a geospatial analysis of child mortality in Iran using death records from the Ministry of Health and Medical Education from 2016 to 2018 stratified by sex, age, province, and district, and household expenditure and income survey data from the Statistical Center of Iran collected in 2017. We applied multilevel mixed-effect models and detected significant inequality in child mortality and the impact of socioeconomic factors, especially household income. We advocate for using mortality rate for young children (< 5 years old) as an indicator for assessing the impact of interventions to reduce inequalities among various socioeconomic groups. We also recommend to design and implement comprehensive and longitudinal data collection systems for accurate, regular, and specific monitoring of health inequalities.
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Affiliation(s)
- Ardeshir Khosravi
- Health Equity Research Center (HERC), Tehran University of Medical Sciences (TUMS), Tehran, Iran
- Iranian Ministry of Health and Medical Education, Tehran, Iran
| | - Efat Mohamadi
- Health Equity Research Center (HERC), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Ali Sheidaei
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Gita Shafiee
- Chronic Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Ramin Heshmat
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
| | - Alireza Olyaeemanesh
- Health Equity Research Center (HERC), Tehran University of Medical Sciences (TUMS), Tehran, Iran
- National Institute of Health Research, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Amirhossein Takian
- Health Equity Research Center (HERC), Tehran University of Medical Sciences (TUMS), Tehran, Iran.
- Department of Global Health & Public Policy, School of Public Health, Tehran University of Medical Sciences (TUMS), Poursina Avenue, Qods Street, Enqelab Square, Tehran, Iran.
- Department of Health Management, Policy & Economics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
- National Center for Health Insurance Research, Tehran, Iran.
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Olyaeemanesh A, Takian A, Mostafavi H, Mobinizadeh M, Bakhtiari A, Yaftian F, Vosoogh-Moghaddam A, Mohamadi E. Health Equity Impact Assessment (HEIA) reporting tool: developing a checklist for policymakers. Int J Equity Health 2023; 22:241. [PMID: 37980523 PMCID: PMC10657117 DOI: 10.1186/s12939-023-02031-0] [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: 07/10/2023] [Accepted: 10/03/2023] [Indexed: 11/20/2023] Open
Abstract
INTRODUCTION Health Equity Impact Assessment (HEIA) is a decision support tool that shows users how a new program, policy, or innovation affects health equity in different population groups. Various HEIA reporting and dissemination tools are available, nevertheless, a practical standard tool to present the results of HEIA in an appropriate period to policymakers is lacking. This work reports the development of a tool (a checklist) for HEIA reporting at the decision-making level, aiming to promote the application of HEIA evidence for improving health equity. METHODS This is a mixed-method study that was carried out over four stages in 2022-2023: 1) identifying HEIA models, checklists, and reporting instruments; 2) development of the initial HEIA reporting checklist; 3) checklist validation; and 4) piloting the checklist. We also analyzed the Face, CVR, and CVI validity of the tool. RESULTS We developed the initial checklist through analysis of 53 included studies and the opinions of experts. The final checklist comprised five sections: policy introduction (eight subsections), managing the HEIA of policy (seven subsections), scope of the affected population (three subsections), HEIA results (seven subsections), and recommendations (three subsections). CONCLUSION Needs assessment, monitoring during implementation, health impact assessment, and other tools such as monitoring outcome reports, appraisals, and checklists are all methods for assessing health equity impact. Other equity-focused indicators, such as the equity lens and equity appraisal, may have slightly different goals than the HEIA. Similarly, the formats for presenting and publishing HEIA reports might vary, depending on the target population and the importance of the report.
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Affiliation(s)
- Alireza Olyaeemanesh
- Health Equity Research Center (HERC), TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
- National Institute for Health Research, TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
| | - Amirhossein Takian
- Health Equity Research Center (HERC), TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
- Department of Global Health and Public Policy, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran
- Department of Health Management, Policy, and Economics, School of Public Health, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Hakimeh Mostafavi
- Health Equity Research Center (HERC), TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
| | - Mohammadreza Mobinizadeh
- National Institute for Health Research, TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
| | - Ahad Bakhtiari
- Health Equity Research Center (HERC), TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
| | - Fateme Yaftian
- Health Equity Research Center (HERC), TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
| | - Abbass Vosoogh-Moghaddam
- Governance and Health Training and Research Department, National Institute for Health Research, TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
- Secretariat for Health and Food Security, TehranUniversity of Medical Sciences (TUMS), Tehran, Iran
| | - Efat Mohamadi
- Health Equity Research Center (HERC), TehranUniversity of Medical Sciences (TUMS), Tehran, Iran.
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de Melo NP, de Souza JM, Cordeiro SM, Veríssimo MDLÓR. Clinical validation of the nursing diagnosis "Risk for delayed child development". Rev Esc Enferm USP 2022; 56:e20220229. [PMID: 36541418 PMCID: PMC10081643 DOI: 10.1590/1980-220x-reeusp-2022-0229en] [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: 06/02/2022] [Accepted: 09/15/2022] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE To validate clinically the risk factors of the nursing diagnosis "Risk for delayed child development". METHOD Cross-sectional quantitative study carried out in a specialty outpatient clinic and in family health units with 124 children. The data was collected through interviews with the children's guardians to investigate the risk factors for delay in child development. RESULTS The tested risk factors affected 108 of the evaluated children (87.1%). In the accuracy tests, most specificity values were above 80% and sensitivity values were lower than 30%. Most risk factors had odds ratio >1, three of which were noteworthy: genetic disorder (OR = 38, p < 0.05) and congenital disorder (OR = 4.4, p < 0.05), among child-related aspects, and impaired cognitive development in parents (OR = 27, p < 0.05), among caregiver-related aspects. CONCLUSION The study contributed to a refined diagnostic accuracy, identifying potential associated factors of the evaluated diagnosis.
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Taghizade S, Mahmoodi Z, Zandifar A, Qorbani M, Mohamadi F, Mehrafzoun N. The relationship model among parent-child relationship, coping responses and behavioral problems in children with attention deficit hyperactivity disorder. BMC Psychiatry 2022; 22:596. [PMID: 36076206 PMCID: PMC9453719 DOI: 10.1186/s12888-022-04224-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 08/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Attention Deficit Hyperactivity Disorder (ADHD) constitutes a prevalent behavioral problem. The present study examined the parent-child relationship model and investigated strategies to cope with behavioral problems in children with ADHD. METHODS This descriptive study selected 300 children with ADHD using convenience sampling. The data collected using the child behavior checklist, the parent-child relationship scale (PCRS), the Billings and Moos Coping Checklist, the socioeconomic status questionnaire, the general health questionnaire-28 (GHQ-28) and a demographic checklist were analyzed in SPSS-25 and LISREL 8.8. RESULTS According to the results of the path analysis on the relationship model among parent-child relationship domains, coping responses and children's behavioral problems, parent-child dependency domain (B = 0.22) in the direct path, disease duration (B = 0.085) in the indirect path, and conflicts in the domain of parent-child relationship (B = 0.366) in both direct and indirect paths had the most positive causal effect on behavioral problems. Furthermore, intimacy in the said domain (B = -0.42) had the most negative causal effect in both direct and indirect paths. The extent to which parents used coping responses via the direct path had a positive causal effect on behavioral problems (B = 0.12). Based on the path analysis test findings in the relationship model among positive parent-child relationship, coping responses and children's behavioral problems, the positive parent-child relationship score had the most negative causal effect via the direct path (B = -0.56). Conversely, the child's age had the highest positive causal effect via the indirect path (B = 0.1) on behavioral problems in children. CONCLUSION Based on findings, there is a causal and significant relationship between the parent-child relationship and the extent to which coping responses are used. It is recommended that training programs be developed to strengthen communication skills, coping responses and problem-solving techniques in parents.
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Affiliation(s)
- Soulmaz Taghizade
- grid.411705.60000 0001 0166 0922Student Research Committee, Alborz University of Medical Sciences, Karaj, Iran
| | - Zohreh Mahmoodi
- Social Determinants of Health Research Center, Alborz University of Medical Sciences, Karaj, Iran.
| | - Atefeh Zandifar
- grid.411705.60000 0001 0166 0922Social Determinants of Health Research Center, Alborz University of Medical Sciences, Karaj, Iran
| | - Mostafa Qorbani
- grid.411705.60000 0001 0166 0922Non-Communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran ,grid.411705.60000 0001 0166 0922Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farima Mohamadi
- grid.411600.2Social Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Niloufar Mehrafzoun
- grid.412112.50000 0001 2012 5829Kermanshah University of Medical Sciences, Kermanshah, Iran
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Melo NPD, Souza JMD, Cordeiro SM, Veríssimo MDLÓR. Validação clínica do diagnóstico de enfermagem “Risco de atraso no desenvolvimento infantil”. Rev Esc Enferm USP 2022. [DOI: 10.1590/1980-220x-reeusp-2022-0229pt] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
RESUMO Objetivo: Realizar a validação clínica dos fatores de risco do diagnóstico de Enfermagem “Risco de atraso no desenvolvimento infantil”. Método: Estudo transversal, de abordagem quantitativa, realizado em um ambulatório de especialidades e em unidades de saúde da família, com 124 crianças. A coleta de dados ocorreu por meio de entrevistas com os responsáveis pelas crianças e investigou os fatores de risco para atraso no desenvolvimento infantil. Resultados: Os fatores de risco sob teste estiveram presentes em 108 crianças avaliadas (87,1%). Nos testes de acurácia, a maioria dos valores de especificidade foi acima de 80%, e os de sensibilidade, inferiores a 30%. A maioria dos fatores de risco teve odds ratio >1, com destaque para três: distúrbio genético (OR = 38, p < 0,05) e distúrbio congênito (OR = 4,4, p < 0,05), entre os aspectos relativos à criança, e o desenvolvimento cognitivo dos pais prejudicado (OR = 27, p < 0,05), entre os aspectos dos cuidadores. Conclusão O estudo contribuiu para o refinamento da acurácia diagnóstica, identificando fatores potencialmente associados ao diagnóstico avaliado.
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