1School of Nursing, Duke University, Durham, NC, USA
2Department of Economics, Seoul National University, Seoul, Korea
Copyright © 2019 The Korean Society for Preventive Medicine
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
CONFLICT OF INTEREST
The authors have no conflicts of interest associated with the material presented in this paper.
AUTHOR CONTRIBUTIONS
Conceptualization: LCY. Funding acquisition: None. Methodology: LCY, LYH. Writing-original draft: LCY. Writing-review & editing: LCY, LYH.
Category [Ref] | Main examples | Limitations | Suggestions |
---|---|---|---|
Compositional SEP measures [12-45] | Education, income, occupation, health insurance | Reliant on limited aspects of SEP, while depending on a few parameters | Use cluster analysis for socioeconomic classification |
Employ a composite measure based on social standing or prestige | |||
Hardly address time-varying features of SEP due to mostly being assessed cross-sectionally | Capture the dynamic and changing features of SEP | ||
Largely focus on objective SEP measures | More attention on subjective SEP measures that reflect an individual’s perception of socioeconomic standing | ||
Contextual SEP measures | |||
Organizational level [46-49] | Exposure to hazardous conditions, health resources in the workplace, workplace culture, physical exertion, welfare facilities | Only employ measures that describe the physical aspects of the working environment, without considering social or psychological aspects | Adopt a comprehensive set of work-related factors |
Community level [50-55] | Demographic, socioeconomic, behavioral, and health characteristics of the community according to county- or borough-level administrative boundaries | Crude proxies for the places in which people live their lives | More rigorous analysis of geographical differences in health (neighborhoods, townships, and towns) |
Societal level [25,50,56] | One’s welfare status | Lack a wide range of upstream factors that affect a society’s health status | Explore various upstream contextual forces that influence the population health appropriate to a country’s circumstances |
Multilevel analyses [46,48,50,55] | Combining compositional measures with either organizational-level or community-level measures | Rarely consider different SEP levels in the model | Focus on interactions between different levels of intertwined SEP factors to advance research design |
Composite SEP measures [50,52,55] | Material and social deprivation (Carstairs Index) | Limited statistical methods are used for analyzing area data | Use an originally developed and established area-deprivation index for the Korean context |
Reliant on an index more frequently used in Western cultures | Develop and test an index that can specifically predict cardiovascular health outcomes | ||
Life-course SEP measures [54,57-59] | Early-life SEP (indexed by the adult height or parental SEP during a childhood), changes in SEP from early life to adulthood | Using SEP measures when their concepts can only be captured in the sensitive period model or social mobility model in the life-course approach | Adopt more comprehensive life-course SEP measures related to 4 life-course models |
Viewing them as competing measures that should be examined independently | Consider SEP measures related to 4 models within the same analytic model |
Concepts | Search terms |
---|---|
Korea | “Korea”[MeSH] or “Republic of Korea”[MeSH] |
Cardiovascular health | “Cardiovascular Diseases”[MeSH] OR death OR mortality OR coronary OR cardiac OR heart OR cardiovascular OR “Myocardial Ischemia”[MeSH] OR “Myocardial Infarction”[MeSH] OR ”Stroke”[MeSH] OR “Cerebrovascular Disorders”[MeSH] OR “Heart Failure”[MeSH] OR “Metabolic Syndrome”[MeSH] “cardiovascular risk factor” OR “cardiovascular risk factors” OR ”Hypertension”[MeSH] OR “Blood Pressure”[MeSH] OR ”Hyperlipidemias”[MeSH] OR “Diabetes Mellitus”[MeSH] OR “Obesity”[MeSH] |
Disparities | “Socioeconomic Factors”[MeSH] OR socioeconomic OR social OR “Social Class”[MeSH] OR “Health Status Disparities”[MeSH] OR inequalit* OR disparit* OR inequit* OR “Social Environment”[MeSH] OR “Education”[MeSH] OR “Educational Status”[MeSH] OR “Income”[MeSH] OR ”Poverty”[MeSH] OR “Occupations”[MeSH] OR “Work”[MeSH] OR “Employment”[MeSH] OR “Geography”[MeSH] OR geographic |
Category [Ref] | Main examples | Limitations | Suggestions |
---|---|---|---|
Compositional SEP measures [12-45] | Education, income, occupation, health insurance | Reliant on limited aspects of SEP, while depending on a few parameters | Use cluster analysis for socioeconomic classification |
Employ a composite measure based on social standing or prestige | |||
Hardly address time-varying features of SEP due to mostly being assessed cross-sectionally | Capture the dynamic and changing features of SEP | ||
Largely focus on objective SEP measures | More attention on subjective SEP measures that reflect an individual’s perception of socioeconomic standing | ||
Contextual SEP measures | |||
Organizational level [46-49] | Exposure to hazardous conditions, health resources in the workplace, workplace culture, physical exertion, welfare facilities | Only employ measures that describe the physical aspects of the working environment, without considering social or psychological aspects | Adopt a comprehensive set of work-related factors |
Community level [50-55] | Demographic, socioeconomic, behavioral, and health characteristics of the community according to county- or borough-level administrative boundaries | Crude proxies for the places in which people live their lives | More rigorous analysis of geographical differences in health (neighborhoods, townships, and towns) |
Societal level [25,50,56] | One’s welfare status | Lack a wide range of upstream factors that affect a society’s health status | Explore various upstream contextual forces that influence the population health appropriate to a country’s circumstances |
Multilevel analyses [46,48,50,55] | Combining compositional measures with either organizational-level or community-level measures | Rarely consider different SEP levels in the model | Focus on interactions between different levels of intertwined SEP factors to advance research design |
Composite SEP measures [50,52,55] | Material and social deprivation (Carstairs Index) | Limited statistical methods are used for analyzing area data | Use an originally developed and established area-deprivation index for the Korean context |
Reliant on an index more frequently used in Western cultures | Develop and test an index that can specifically predict cardiovascular health outcomes | ||
Life-course SEP measures [54,57-59] | Early-life SEP (indexed by the adult height or parental SEP during a childhood), changes in SEP from early life to adulthood | Using SEP measures when their concepts can only be captured in the sensitive period model or social mobility model in the life-course approach | Adopt more comprehensive life-course SEP measures related to 4 life-course models |
Viewing them as competing measures that should be examined independently | Consider SEP measures related to 4 models within the same analytic model |
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