Measurement components of socioeconomic status in health-related studies in Iran

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Objective

The socioeconomic status (SES) is as a symbol of social determinants of health which has a dominant influence on population health. The purpose of this study was collecting, weighing, and determining the most relevant SES measurement items in Iran.

Results

The SES health studies conducted in Iran was searched from 2007 to 2017. First, the SES items were categorized. Then, each item was weighed based on its reliability and generalizability. Finally, the necessity of items was determined, weighed, and ranked. This is the two- round Delphi technique. After weighing 57 SES items, 37 items were selected with ≥ 1 weight and classified in 7 categories. According to the Delphi evaluation, 15 items were identified ≥ 3.5 for measuring SES of Iranian households: household size, head of household education, head of household job, household monthly income, type of school that children attend, house ownership, local value of residence, number of rooms in the house, house area, personal computer/laptop, smart cell phone, 3D TV, dishwasher, microwave, and car ownership. The SES items for the present society are categorized in 7 domains. The items collected in this study have the most comprehension of all studies related to income, life facilities, and assets.

Related collections

Most cited references 60

Record: found
Abstract: found
Article: not found

Measurement of socioeconomic status in health disparities research.

Vickie L Shavers (2007)

Socioeconomic status (SES) is frequently implicated as a contributor to the disparate health observed among racial/ ethnic minorities, women and elderly populations. Findings from studies that examine the role of SES and health disparities, however, have provided inconsistent results. This is due in part to the: 1) lack of precision and reliability of measures; 2) difficulty with the collection of individual SES data; 3) the dynamic nature of SES over a lifetime; 4) the classification of women, children, retired and unemployed persons; 5) lack of or poor correlation between individual SES measures; and 6) and inaccurate or misleading interpretation of study results. Choosing the best variable or approach for measuring SES is dependent in part on its relevance to the population and outcomes under study. Many of the commonly used compositional and contextual SES measures are limited in terms of their usefulness for examining the effect of SES on outcomes in analyses of data that include population subgroups known to experience health disparities. This article describes SES measures, strengths and limitations of specific approaches and methodological issues related to the analysis and interpretation of studies that examine SES and health disparities.

0 comments Cited 251 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Multimorbidity: Epidemiology and Risk Factors in the Golestan Cohort Study, Iran

Batoul Ahmadi, Masoomeh Alimohammadian, Mehdi Yaseri … (2016)

Abstract Advances in medicine and health policy have resulted in growing of older population, with a concurrent rise in multimorbidity, particularly in Iran, as a country transitioning to a western lifestyle, and in which the percent of the population over the age of 60 years is increasing. This study aims to assess multimorbidity and the associated risk factors in Iran. We used data from 50,045 participants (age 40–75 y) in the Golestan Cohort Study, including data on demographics, lifestyle habits, socioeconomic status, and anthropometric indices. Multimorbidity was defined as the presence of 2 or more out of 8 self-reported chronic conditions, including cardiovascular diseases, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, liver disease, gastroesophageal reflux disease, tuberculosis, and cancer. Multivariate logistic regression models were used to examine the associations between multiple different factors and the risk factors. Multimorbidity prevalence was 19.4%, with the most common chronic diseases being gastroesophageal reflux disease (76.7%), cardiovascular diseases (72.7%), diabetes (25.3%), and chronic obstructive pulmonary disease (21.9%). The odds of multimorbidity was 2.56-fold higher at the age of >60 years compared with that at <50 years (P < 0.001), and 2.11-fold higher in women than in men (P < 0.001). Other factors associated with higher risk of multimorbidity included non-Turkmen ethnicity, low education, unemployment, low socioeconomic status, physical inactivity, overweight, obesity, former smoking, opium and alcohol use, and poor oral health. Apart from advanced age and female sex, the most important potentially modifiable lifestyle factors, including excess body weight and opium use, and opium user, are associated with multimorbidity. Policies aiming at controlling multimorbidity will require a multidimensional approach to reduce modifiable risk factors in the younger population in developing countries alongside adopting efficient strategies to improve life quality in the older population.

0 comments Cited 49 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Understanding determinants of socioeconomic inequality in mental health in Iran's capital, Tehran: a concentration index decomposition approach

Esmaeil Khedmati Morasae, Ameneh Setareh Forouzan, Reza Majdzadeh … (2012)

Background Mental health is of special importance regarding socioeconomic inequalities in health. On the one hand, mental health status mediates the relationship between economic inequality and health; on the other hand, mental health as an "end state" is affected by social factors and socioeconomic inequality. In spite of this, in examining socioeconomic inequalities in health, mental health has attracted less attention than physical health. As a first attempt in Iran, the objectives of this paper were to measure socioeconomic inequality in mental health, and then to untangle and quantify the contributions of potential determinants of mental health to the measured socioeconomic inequality. Methods In a cross-sectional observational study, mental health data were taken from an Urban Health Equity Assessment and Response Tool (Urban HEART) survey, conducted on 22 300 Tehran households in 2007 and covering people aged 15 and above. Principal component analysis was used to measure the economic status of households. As a measure of socioeconomic inequality, a concentration index of mental health was applied and decomposed into its determinants. Results The overall concentration index of mental health in Tehran was -0.0673 (95% CI = -0.070 - -0.057). Decomposition of the concentration index revealed that economic status made the largest contribution (44.7%) to socioeconomic inequality in mental health. Educational status (13.4%), age group (13.1%), district of residence (12.5%) and employment status (6.5%) also proved further important contributors to the inequality. Conclusions Socioeconomic inequalities exist in mental health status in Iran's capital, Tehran. Since the root of this avoidable inequality is in sectors outside the health system, a holistic mental health policy approach which includes social and economic determinants should be adopted to redress the inequitable distribution of mental health.

0 comments Cited 33 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Sediqe Shafiei: s_shafiei@sbmu.ac.ir

Shahram Yazdani: shahram.yazdani@yahoo.com

Mohammad-Pooyan Jadidfard: pooyan_mj@yahoo.com

A. Hamid Zafarmand: +98 (21) 22 42 18 13 , zafarmand@alum.bu.edu

Journal

Journal ID (nlm-ta): BMC Res Notes

Journal ID (iso-abbrev): BMC Res Notes

Title: BMC Research Notes

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-0500

Publication date (Electronic): 31 January 2019

Publication date PMC-release: 31 January 2019

Publication date Collection: 2019

Volume: 12

Electronic Location Identifier: 70

Affiliations

[1 ]GRID grid.411600.2, Department of Community Oral Health, , Shahid Beheshti University of Medical Sciences, ; 19839, Tehran, Islamic Republic of Iran

[2 ]GRID grid.411600.2, School of Medical Education, , Shahid Beheshti University of Medical Sciences, ; Tehran, Islamic Republic of Iran

[3 ]GRID grid.411600.2, Department of Orthodontics, , Shahid Beheshti University of Medical Sciences, ; Tehran, 19839, Islamic Republic of Iran

Article

Publisher ID: 4101

DOI: 10.1186/s13104-019-4101-y

PMC ID: 6357485

PubMed ID: 30704521

SO-VID: 75753faa-e56c-4ff1-b6a1-5f944662b35f

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 10 October 2018

Date accepted : 19 January 2019

Custom metadata

ScienceOpen disciplines: Medicine

Keywords: social determinant of health (sdh),socioeconomic factors,socioeconomic status (ses),family characteristics,household head,household equipment,iran

Data availability:

ScienceOpen disciplines: Medicine

Keywords: social determinant of health (sdh), socioeconomic factors, socioeconomic status (ses), family characteristics, household head, household equipment, iran

Measurement components of socioeconomic status in health-related studies in Iran

Read this article at

Abstract

Objective

Results

Related collections

Measurement of Glucocorticoid Receptor Signaling in Major Depression

Most cited references 60

Measurement of socioeconomic status in health disparities research.

Multimorbidity: Epidemiology and Risk Factors in the Golestan Cohort Study, Iran

Understanding determinants of socioeconomic inequality in mental health in Iran's capital, Tehran: a concentration index decomposition approach

Author and article information

Contributors

Journal

Affiliations

Article

History

Categories

Custom metadata

Comments

Comment on this article

Similar content 760

Cited by 10

Most referenced authors 572