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Original Articles
- Identifying, Measuring, and Ranking Social Determinants of Health for Health Promotion Interventions Targeting Informal Settlement Residents
- Farhad Nosrati Nejad, Mohammad Reza Ghamari, Seyed Hossein Mohaqeqi Kamal, Seyed Saeed Tabatabaee
- J Prev Med Public Health. 2023;56(4):327-337. Published online June 26, 2023
- DOI: https://doi.org/10.3961/jpmph.23.059
- 1,461 View
- 121 Download
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Abstract
PDF - Objectives
Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health promotion interventions targeting informal settlement residents in a metropolitan area in Iran.
Methods
Using a hybrid method, this study was conducted in 3 phases from 2019 to 2020. SDHs were identified by reviewing studies and using the Delphi method. To examine the SDHs among informal settlement residents, a cross-sectional analysis was conducted using researcher-made questionnaires. Multilayer perceptron analysis using an artificial neural network was used to rank the SDHs by priority.
Results
Of the 96 determinants identified in the first phase of the study, 43 were examined, and 15 were identified as high-priority SDHs for use in health-promotion interventions for informal settlement residents in the study area. They included individual health literacy, nutrition, occupational factors, housing-related factors, and access to public resources.
Conclusions
Since identifying and addressing SDHs could improve health justice and mitigate the poor health status of settlement residents, ranking these determinants by priority using artificial intelligence will enable policymakers to improve the health of settlement residents through interventions targeting the most important SDHs. -
Summary
- Inequality in Private Health Care Expenditures: A 36-Year Trend Study of Iranian Households
- Ehsan Aghapour, Mehdi Basakha, Seyed Hossein Mohaqeqi Kamal, Abolghasem Pourreza
- J Prev Med Public Health. 2022;55(4):379-388. Published online June 27, 2022
- DOI: https://doi.org/10.3961/jpmph.22.123
- 2,324 View
- 76 Download
- 1 Crossref
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Abstract
PDF
- Objectives
Throughout history, societies have been impacted by inequality. Many studies have been conducted on the topic more broadly, but only a few have investigated inequalities in out-of-pocket health payments (OHP). This study measures OHP inequality trends among the Iranian households.
Methods
This study used data from the Iranian Statistics Center on Iranian household income and expenditures. The analysis included a total of 995 300 households during the 36 years from 1984 to 2019. The Gini coefficient, Atkinson index, and Theil index were calculated for Iranian OHP.
Results
Average Iranian household OHP increased from 33 US dollar (USD) in 1984 to 47 USD in 2019. During this 36-year span, the average±standard deviation Gini coefficient for OHP was 0.73±0.04, and the Atkinson and Theil indexes were 0.68±0.05 and 1.14±0.29, respectively. The Gini coefficients for the subcategories of OHP of outpatient diagnostic services, medical assistant accessories, hospital inpatient services, and addiction cessation were 0.70, 0.61, 0.84, and 0.64, respectively.
Conclusions
In this study, we scrutinized trends of inequality in the OHP of Iranian households. Inequality in OHP decreased slightly over the past four decades. An analysis of trends among different subgroups revealed that affluent households, such as households with insurance coverage and households in higher income deciles, experienced higher inequality. Therefore, lower inequality in health care expenditures may be related to restricted access to health care services in Iran. -
Summary
Citations
Citations to this article as recorded by
- Decomposition of Healthcare Utilization Inequality in Iran: The Prominent Role of Health Literacy and Neighborhood Characteristics
Neda Soleimanvandiazar, Seyed Hossein Mohaqeqi Kamal, Mehdi Basakha, SalahEddin Karim, Sina Ahmadi, Gholamreza Ghaedamini Harouni, Homeira Sajjadi, Ameneh Setareh Forouzan
INQUIRY: The Journal of Health Care Organization, Provision, and Financing.2024;[Epub] CrossRef
Scoping Review- The Most Important Social Determinants of Slum Dwellers’ Health: A Scoping Review
- Farhad Nosrati Nejad, Mohammad Reza Ghamari, Seyed Hossein Mohaqeqi Kamal, Seyed Saeed Tabatabaee, Raheleh Ganjali
- J Prev Med Public Health. 2021;54(4):265-274. Published online July 8, 2021
- DOI: https://doi.org/10.3961/jpmph.21.073
- 4,565 View
- 220 Download
- 4 Crossref
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Abstract
PDF
- Objectives
Given the importance of social determinants of health in promoting the health of slum residents, this study was conducted with the aim of identifying the main dimensions and components of these determinants.
Methods
This scoping review study was conducted according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). A comprehensive search was performed of PubMed, ProQuest, Scopus, and Web of Science for articles conducted from 2010 to the end of 2019. Studies were selected based on inclusion criteria, with a special focus on studies dealing with the social determinants of physical and mental health or illness.
Results
Thirty-three articles were selected to extract information on the social determinants of health. After reviewing the articles, 7 main dimensions (housing, socioeconomic status of the family, nutrition, neighborhood characteristics, social support and social capital, occupational factors, and health behaviors) and 87 components were extracted as social determinants of health among slum dwellers.
Conclusions
This framework could be used by planners, managers, and policy-makers when making decisions affecting the health of these settlements’ residents due to the common characteristics of slums around the world, especially in developing countries. -
Summary
Citations
Citations to this article as recorded by- Deprivation and Its Association with Child Health and Nutrition in the Greater Kampala Metropolitan Area of Uganda
Rornald Muhumuza Kananura, Peter Waiswa, Ronald Wasswa, Ties Boerma, Cauane Blumenberg, Abdoulaye Maiga
Journal of Urban Health.2024;[Epub] CrossRef - “For my safety and wellbeing, I always travel to seek health care in a distant facility”—the role of place and stigma in HIV testing decisions among GBMSM – BSGH 002
Edem Yaw Zigah, Gamji Rabiu Abu-Ba'are, Osman Wumpini Shamrock, Henry Delali Dakpui, Amos Apreku, Donte T. Boyd, LaRon E. Nelson, Kwasi Torpey
Health & Place.2023; 83: 103076. CrossRef - Identifying, Measuring, and Ranking Social Determinants of Health for Health Promotion Interventions Targeting Informal Settlement Residents
Farhad Nosrati Nejad, Mohammad Reza Ghamari, Seyed Hossein Mohaqeqi Kamal, Seyed Saeed Tabatabaee
Journal of Preventive Medicine and Public Health.2023; 56(4): 327. CrossRef - Do Community-based Livelihood Interventions Affect Sexual and Reproductive Health and Rights of Young People in Slum Areas of Uganda: a Difference-in-difference with Kernel Propensity Score Matching Analysis
Andre M. N. Renzaho, Joseph K. Kamara, Daniel Doh, Paul Bukuluki, Rashidul A. Mahumud, Moses Galukande
Journal of Urban Health.2022; 99(1): 164. CrossRef
Original Article- Contextual and Individual Determinants of Mental Health: A Cross-sectional Multilevel Study in Tehran, Iran
- Homeira Sajjadi, Gholamreza Ghaedamini Harouni, Hassan Rafiey, Mohammadreza Vaez-Mahdavi, Meroe Vameghi, Seyed Hossein Mohaqeqi Kamal
- J Prev Med Public Health. 2020;53(3):189-197. Published online April 14, 2020
- DOI: https://doi.org/10.3961/jpmph.19.150
- 3,535 View
- 148 Download
- 4 Crossref
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Abstract
PDF
- Objectives
Our aim was to answer the following questions: (1) Can mental health variance be partitioned to individual and higher levels (e.g., neighborhood and district); (2) How much (as a percentage) do individual-level determinants explain the variability of mental health at the individual-level; and (3) How much do determinants at the neighborhood- or district-level explain the variability of mental health at the neighborhood- or district-level?
Methods
We used raw data from the second round of the Urban Health Equity Assessment and Response Tool in Tehran (in 2012-2013, n=34 700 samples nested in 368 neighborhoods nested in 22 districts) and the results of the official report of Tehran’s Center of Studies and Planning (in 2012-2013, n=22 districts). Multilevel linear regression models were used to answer the study questions.
Results
Approximately 40% of Tehran residents provided responses suggestive of having mental health disorders (30-52%). According to estimates of residual variance, 7% of mental health variance was determined to be at the neighborhood-level and 93% at the individual-level. Approximately 21% of mental health variance at the individual-level and 49% of the remaining mental health variance at the neighborhood-level were determined by determinants at the individual-level and neighborhood-level, respectively.
Conclusions
If we want to make the most effective decisions about the determinants of mental health, in addition to considering the therapeutic perspective, we should have a systemic or contextual view of the determinants of mental health. -
Summary
Citations
Citations to this article as recorded by- Multidimensional poverty index: a multilevel analysis of deprivation among Iranian older adults
Seyed Hossein Mohaqeqi Kamal, Mehdi Basakha, Sabina Alkire
Ageing and Society.2024; 44(2): 337. CrossRef - Parental Objective, Subjective, and Contextual Socioeconomic Status and Children's Mental Health in Iran: The Mediating Effect of the Subjective Measure
Ardavan Mohammad Aghaei, Lawrence Wissow, Ramin Mojtabai, Hadi Zarafshan, Zahra Shahrivar, Amir Hossein Nikzad, Vandad Sharifi
Iranian Journal of Psychiatry and Behavioral Sciences.2023;[Epub] CrossRef - This is the place: a multi-level analysis of neighbourhood correlates of adolescent wellbeing
Jose Marquez, Neil Humphrey, Louise Black, Sophie Wozmirska
Social Psychiatry and Psychiatric Epidemiology.2023;[Epub] CrossRef - Measuring and exploring mental health determinants: a closer look at co-residents’ effect using a multilevel structural equations model
Hend Gabr, Mohammed Baragilly, Brian H. Willis
BMC Medical Research Methodology.2022;[Epub] CrossRef
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