Decomposition of socioeconomic inequalities in preterm deliveries in Tehran, Iran

Omani-Samani, Reza; Mansournia, Mohammad Alì; Almasi‐Hashiani, Amir; Sepidarkish, Mahdi; Safiri, Saeid; Morasae, Esmaeil Khedmati; Rarani, Mostafa Amini

doi:10.1002/ijgo.12347

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…This observation has been supported by several other studies conducted in both developed and developing nations 23–25 . However, it is important to note that one study presented conflicting results that contradicted our findings 26 …”

Section: Discussionsupporting

confidence: 73%

“…[23][24][25] However, it is important to note that one study presented conflicting results that contradicted our findings. 26 Upon conducting a decomposition analysis of the CI, it was revealed that certain factors made substantial positive contributions to the measured inequality in the occurrence of stillbirths in Tehran.…”

Section: Discussionmentioning

confidence: 99%

“… 23 , 24 , 25 However, it is important to note that one study presented conflicting results that contradicted our findings. 26 …”

Section: Discussionmentioning

confidence: 99%

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Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Mouseli,

Sharafi,

Mastaneh

et al. 2023

Health Science Reports

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BackgroundNoncommunicable diseases (NCDs) are the major causes of mortality across the globe, which impose a substantial burden on health care systems, particularly in low‐ and middle‐income countries. The present study aimed to determine socioeconomic inequality in the prevalence of NCDs using the concentration index (CI).MethodsThis cross‐sectional study was conducted on the baseline data of the Bandar Kong cohort. The principal component analysis was used to determine people's socioeconomic status (SES). The CI and Lorenz Curve were used for the assessment of socioeconomic inequality. Multivariate logistic regression was used to assess the relationship between SES and the prevalence of NCDs. A p Value less than 0.05 is considered significant.ResultsFrequency and prevalence of diabetes was 653 (16.22%), hypertension 848 (21.06%), chronic lung diseases 161 (4%), epilepsy 70 (1.74%), mental disorders 191 (4.74%), stillbirth 299 (13.94%), thyroid disorders 391 (9.71%) and depression 146 (3.63%). CI for the prevalence of diabetes was [−0.107, %95 CI: −0.146 to −0.068], hypertension [−0.122, %95 CI: −0.155 to −0.088], chronic lung disease [−0.116, %95 CI: −0.202 to −0.03], psychiatric disorders [−0.230, %95 CI: −0.304 to −0.155], depression [−0.132, %95 CI: −0.220 to−0.043] and stillbirth [−0.162, %95 CI: −0.220 to −0.105]. The Gini index was negative for all these diseases, indicating that these are significantly concentrated in people of poor SES.ConclusionsThe findings suggest that selected NCDs were concentrated among the poor and the low‐income. Particular attention may be necessary to address the problem of NCDs among these groups.

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Section: Discussionsupporting

confidence: 73%

Section: Discussionmentioning

confidence: 99%

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Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Mouseli,

Sharafi,

Mastaneh

et al. 2023

Health Science Reports

View full text Add to dashboard Cite

show abstract

“…Hence, the principal component analysis (PCA) was used to construct the economic status of the participants by using household assets. PCA has been widely used in previous studies to measure socioeconomic status [3,8,[23][24][25]. Two classes of variables, including the characteristic of housing (e.g., house ownership and floor area) and possession of assets (e.g., private car, motorcycle, personal computer, Internet access, kitchen, telephone, and central heating machine), were used to construct the wealth score.…”

Section: Measuring Healthcare Services Utilization and Definition Of mentioning

confidence: 99%

Tracking socio-economic inequalities in healthcare utilization in Iran: a repeated cross-sectional analysis

et al. 2020

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Background: Although some healthcare reforms such as Health Transformation Plan (HTP) were implemented in Iran to provide required healthcare services, few studies have been conducted to track the impacts of these reforms on socioeconomic inequality in healthcare utilization. This study aims to track socioeconomic inequalities in healthcare utilization and their changes between 2008 and 2016 in Iran. Methods: Required data were obtained from two of Iran's utilization of healthcare services survey conducted in 2008 and 2016. Erreygers concentration index (EI) was used to measure inequality in the utilization of outpatient and inpatient healthcare services (UOH and UIH). The decomposition of EI (DEI) was used to explain healthcare utilization inequality. Oaxaca decomposition (OD) was also employed to track the changes in EI in this period. Result: Inequality in UOH increased from 0.105 to 0.133 in the studied years, indicating the pro-rich distribution of UOH. Inequality in UIH decreased from 0.0558 to − 0.006. DEI showed that economic status was the main factor that contributed to inequality in the UOH and UIH. OD showed that residence in rural areas and supplementary insurance were the main contributing factors in the increased inequality of UOH. Moreover, OD also showed that economic status was the main contributing factor in the reduced inequality of UIH. Conclusion: While Iran still suffers from significant socioeconomic inequalities in UOH, it seems that healthcare reforms, especially HTP, have reduced UIH inequality. Expanding healthcare reforms into the outpatient sector and also implementing effective health financing policies could be recommended as a remedy against UOH inequality.

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Decomposing educational inequality in maternal mortality in Iran

2021

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Decomposition of socioeconomic inequalities in preterm deliveries in Tehran, Iran

Cited by 5 publications

References 25 publications

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Tracking socio-economic inequalities in healthcare utilization in Iran: a repeated cross-sectional analysis

Decomposing educational inequality in maternal mortality in Iran

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