Background: Evidence of an effect of income on self-reported poor health (SRPH) is widely available in the literature. We compare this effect across age, different countries and between men and women using meta-analysis. Studies that report on an effect of income lack a homogenous effect size. To overcome this problem we propose a method to derive a homogenous effect size to enable us to compare the effect of income across groups.
Methods: We take a meta-analytical approach to examine the effect of income on SRPH. The data consists of reported and calculated odds ratios as a measure of effect for SRPH outcomes across different income categories. Self-reported health outcomes are dichotomised into 'good' and 'poor'. With least-squares techniques, we estimate the functional parameters that describe the log-linear association between income and SRPH. Subsequently, F-tests are performed to show variations between the groups.
Results: The relationship between income and SRPH is log-linear for most countries but not significantly for Sweden and the Netherlands. Our results show significant differences in the effect of income between countries. We find that men require a higher income than women to achieve comparable SRPH outcomes, and that the effect of income depends on age.
Conclusions: There is significant income related variation in SRPH between different countries even if the levels of income or the standards of living are comparable. For women income affects SRPH differently than for men. The effect of income on SRPH depends on the age of the individual respondent.
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http://dx.doi.org/10.1093/eurpub/ckq166 | DOI Listing |
J Multimorb Comorb
November 2023
Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA.
Purpose: Self-rated physical health (SRPH) and self-rated mental health (SRMH) are both linked to excess morbidity and premature mortality and can vary across rural and urban contexts. This can be particularly problematic for rural residents who have less access to important health care infrastructure. In this paper, we assess the prevalence of and rural-urban disparities at the intersection of SRPH and SRMH, specifically self-rated physical/mental multimorbidity (SRPMM) overall and across rural-urban contexts.
View Article and Find Full Text PDFBMC Public Health
July 2023
Department of Health Education and Behavioral Sciences, Faculty of Public Health, Mahidol University, Bangkok, Thailand.
Background: The aim of this study was to assess the self-reported physical health (SRPH) and self-reported mental health (SRMH) of older adults 80 years and older in Thailand.
Methods: We analyze national cross-sectional data from the Health, Aging and Retirement in Thailand (HART) in 2015. Physical and mental health status was assessed by self-report.
Diabetes Metab Syndr
December 2021
Division of General Medicine and Geriatrics. Emory University School of Medicine, Atlanta, GA, 30303, USA.
Aim: This study examined the associations of high allostatic load (h_ALS) and metabolic syndrome (MetS) with and self-rated poor health (SRPH) in overweight/obese non-Hispanic White (NHW), non-Hispanic Black (NHB), and Mexican American (MA) adults.
Methods: The 2015-16 and 2017-18 US National Health and Nutrition Examination Survey data (n = 4403) were used for this study.
Results: Rates of h_ALS in overweight/obese NHW, NHW, and MA participants were 56.
Int J Health Geogr
June 2014
1266 TAMU, Department of Health Promotion and Community Health Sciences, School of Rural Public Health, Texas A&M Health Science Center, College Station, TX 77843-1266, USA.
Background: Despite recommendations for cancer screening for breast and colorectal cancer among the Medicare population, preventive screenings rates are often lower among vulnerable populations such as the small but rapidly growing older American Indian and Alaska Native (AIAN) population. This study seeks to identify potential disparities in the availability of screening services, distance to care, and the utilization of cancer screening services for Medicare beneficiaries residing in areas with a higher concentration of AIAN populations.
Methods: Using the county (n =3,225) as the level of analysis, we conducted a cross-sectional analysis of RTI International's Spatial Impact Factor Data (2012) to determine the level of disparities for AIAN individuals.
Prev Sci
January 2015
Department of Epidemiology and Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, 219 SRPH Administration Building, TAMU 1266, College Station, TX, 77843-1266, USA,
Using multilevel analysis, this study investigated participant and site characteristics associated with participant retention in a multisite diabetes prevention translational project among American Indian and Alaska Native (AI/AN) people. We analyzed data from the Special Diabetes Program for Indians Diabetes Prevention Program (SDPI-DP), a lifestyle intervention to prevent diabetes implemented in 36 AI/AN grantee sites. A total of 2,553 participants were recruited and started the intervention between January 1, 2006 and July 31, 2008.
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