Is the disease risk associated with good self-reported health constant across the socio-economic spectrum?

Reliability and predictive validity of two scales of self-rated health in China: results from China Health and Retirement Longitudinal Study (CHARLS)

Background

Despite the widespread use of the single item self-rated health (SRH) question, its reliability has never been evaluated in Chinese population.

Methods

We used data from the China Health and Retirement Longitudinal Study, waves 1–4 (2011–2019). In wave 1, the same SRH question was asked twice, separated by other questions, on a subset of 4533 subjects, allowing us to examine the test–retest reliability of SRH. In addition, two versions of SRH questions (the WHO and US versions) were asked (n = 11,429). Kappa (κ), weighted kappa (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa}_{w}$$\end{document}κw), and polychoric correlation coefficient (ρ) were used for reliability assessment. Cox proportional-hazards models were estimated to assess the predictive validity of SRH measurement for mortality over 7 years of follow up. To do so, relative index of inequality (RII) and slope index of inequality (SII) were estimated for each SRH scale.

Results

There was moderate to substantial test–retest reliability (κ = 0.54, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa}_{w}$$\end{document}κw=0.63) of SRH; 31% of respondents who used the same scale twice changed their ratings after answering other questions. There was strong positive association between the two SRH measured by the two scales (ρ > 0.8). Compared with excellent/very good SRH, adjusted hazard ratios (HR) of death are 2.30 (95% CI, 1.70–3.13) for the US version and 1.86 (95% CI, 1.33–2.60) for the WHO version. Using slope indices of inequality, the WHO version estimated slightly larger mortality differences (RII = 3.50, SII = 15.53) than the US version (RII = 3.25, SII = 14.80).

Conclusions

In Chinese middle-aged and older population, the reliability of SRH is generally good, although the two commonly used versions of SRH scales could not be compared directly. Both indices predict mortality, with similar predictive validity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14218-1.

Cautionary tails of grip strength in health inequality studies: An analysis from the Canadian longitudinal study on aging

Self-rated health is widely used in studies of the socioeconomic gradient of health in community-based populations. Its subjectivity may lead to under- or over-estimation of a true underlying socioeconomic gradient and has increased interest in searching for alternative, objective measures of health. Grip strength has emerged as one such alternative for community-based older populations, yet no study has directly assessed the relationship between these two measures and compared their associations with socioeconomic status and health behaviours. Using 26,754 participants aged 45-85 years in the baseline data of the Canadian Longitudinal Study on Aging Comprehensive Cohort, we estimated adjusted-grip strength through indirect standardization using age, sex, height, weight, and their square terms and used ANOVA to assess the variance of adjusted-grip strength within and between each self-rated health category. We ran four separate logistic regression models, examining unhealthy tails (those reporting poor health vs. not and those at the bottom 8th percentile of adjusted-grip strength vs. above) and healthy tails (those reporting excellent health vs. not and those at the top 20th percentile of adjusted-grip strength vs. below). Stronger adjusted-grip strength correlated with better self-rated health, but only 2% of the total variance of adjusted-grip strength was explained by variance between the self-rated health categories. While self-rated health largely showed the expected socioeconomic gradients and positive relationships with health enhancing behaviours, adjusted-grip strength showed no clear, consistent associations with either socioeconomic or health behaviour variables. The results give caution about using grip strength as an objective alternative to self-rated health in studies of social inequalities in health. Empirical approaches demand careful considerations as to which dimensions of health and corresponding measures of health are most relevant to the context being studied.

Trends in socioeconomic inequalities in self-rated health in Germany: a time-trend analysis of repeated cross-sectional health surveys between 2003 and 2012

OBJECTIVES

This study assessed the extent of educational and income inequalities in self-rated health (SRH) in the German adult population between 2003 and 2012 and how these inequalities changed over time.

DESIGN

Repeated cross-sectional health interview surveys conducted in 2003, 2009, 2010 and 2012.

SETTING AND PARTICIPANTS

The study population was the German adult population aged 25-69, living in private households in Germany. In total 54 197 randomly selected participants (2003: 6890; 2009: 16 418; 2010: 17 145; 2012: 13 744) were included.

MAIN OUTCOME MEASURES

SRH was assessed with one single question. Five answer categories were dichotomised into good ('very good' and 'good') versus poor ('moderate', 'poor', 'very poor') SRH. To estimate the extent of the correlation between absolute and relative inequalities in SRH on the one hand, and income and education on the other; slope indices of inequality (SII) and relative indices of inequality (RII) were estimated using linear probability and log-binomial regression models.

RESULTS

There were considerable and persisting educational and income inequalities in SRH in every survey year. Absolute educational inequalities were largely stable (2003: SII=0.25, 95% CI 0.21 to 0.30; 2012: 0.29, 95% CI 0.25 to 0.33; p trend=0.359). Similarly, absolute income inequalities were stable (2003: SII=0.22, 95% CI 0.17 to 0.27; 2012: SII=0.26, 95% CI 0.22 to 0.30; p trend=0.168). RII by education (2003: 2.53, 95% CI 2.11 to 3.03; 2012: 2.72, 95% CI 2.36 to 3.13; p trend=0.531) and income (2003: 2.09. 95% CI 1.75 to 2.49; 2012: 2.53, 95% CI 2.19 to 2.92; p trend=0.051) were equally stable over the same period.

CONCLUSIONS

We found considerable and persisting absolute and relative socioeconomic inequalities in SRH in the German adult population between 2003 and 2012, with those in lower socioeconomic position reporting poorer SRH. These findings should be a concern for both public health professionals and political decision makers.

The association between self-rated health and underlying biomarker levels is modified by age, gender, and household income: Evidence from Understanding Society - The UK Household Longitudinal Study

The goal of this study was to evaluate how self-rated health (SRH) and objective measures of health (biomarkers) are associated, and if this association varies by gender, age, and socioeconomic position (measured by household income). Data come from the UK Household Longitudinal Study nurse visit (2010–2012), including a representative sample of adults in Great Britain (N = 15 687 maximum sample). SRH was assessed by the question “In general, would you say your health is excellent, very good, good, fair, or poor?” and dichotomized into good or poor. Indices were created for four biomarker categories based on the aspects of health they are likely to reflect, including visible weigh-related, fitness, fatigue, and disease risk biomarkers. Logistic regression models were run with SRH as the outcome and each biomarker index as a predictor, adjusting by gender, age, and income. Further, interaction terms between each biomarker index and gender, age, and income (independently) were added to test for effect modification. All biomarker indices were associated with SRH in expected directions, with the fitness index most strongly predicting SRH. Gender, age, or income modified the associations between SRH and all biomarker indices to different extents. The association between the visible weight-related biomarker index (including body mass/fat variables) and SRH was stronger for women than men and for those in higher income groups than lower income groups. Income also modified the association between SRH and the fitness biomarker index, whereas age modified the association between SRH and the fatigue biomarker index. When using SRH to investigate health inequalities, researchers and policy makers should be clear that different social groups may systematically consider different dimensions of health when reporting their SRH.

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The association between self-rated global health and underlying objective health as measured by biomarkers varies by type of biomarker, age, sex and socioeconomic status.

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Biomarkers that measure different aspects of fitness most strongly predicting self-rated health.

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The association between the visible biomarkers (including body mass/fat variables) and self-rated health was stronger for women than men and for those in higher income groups than lower income groups.

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Income also modified the association between self-rated health and biomarkers of disease, with a stronger association for higher income groups.

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When rating own health individuals from different social groups may systematically consider different dimensions of health.

Associations of chronic conditions, APOE4 allele, stress factors, and health behaviors with self-rated health

Background

Self-rated health (SRH) has been widely used to measure the overall health status of older adults. Research has shown that SRH is determined by a large array of factors, such as chronic disease conditions, genetic markers (e.g., Apolipoprotein E, APOE, NM_000041), stress factors, and health behaviors. However, few studies have incorporated these factors simultaneously in the analytic framework of SRH. The aim of this study is to examine the associations of these four sets of factors with SRH.

Methods

Using a dataset from a population-based, random-cluster survey of 1,005 elderly respondents aged 54–91 conducted in Taiwan in 2000, we use logistic regressions to examine associations of chronic health conditions, the APOE4 allele stress factors, and health behaviors with SRH. The four disease conditions include diabetes, heart diseases, gastric ulcers, and chronic obstructive pulmonary disease. Stress factors are measured by traumatic events (having an earthquake-damaged house) and chronic life stress (financial difficulty). Health behaviors include smoking, drinking alcohol, vegetable and fruit intake, daily milk intake, and physical exercise.

Results

Diabetes, heart diseases, gastric ulcers, and chronic obstructive pulmonary disease are found to be associated with 2.63 (95 % CI: 1.75–3.95), 1.72 (95 % CI: 1.15–2.58), 1.94 (95 % CI: 1.35–2.80), and 2.54 (95 % CI: 1.66–3.92) odds ratios of poor SRH. The APOE4 allele is found to be significantly associated with poor SRH with odd ratio of 1.58 (95 % CI: 1.02–2.41). Financial difficulty is associated with increased likelihood of poor SRH, with odds ratios of 1.76 (95 % CI: 1.22–2.54) Doing exercise more than 5 times per week are associated with reduced likelihood of poor SRH by 44 % (odds ratio is 0.56, 95 % CI: 0.39–1.82). The interaction term between gender and gastric ulcer showed that the impact of gastric ulcer on SRH is more pronounced in women than in men, with an odds ratio of 2.63 (95 % CI: 1.24–5.58).

Conclusions

Chronic conditions and the APOE4 allele are significantly associated with increased likelihood of reporting poor health, and the associations appear differently among women and men. To better understand the mechanism of how people self-assess their overall health, chronic conditions and genetic components should be considered together with conventional factors such as life stress and health behaviors.

Socio-Economic Differences in the Association between Self-Reported and Clinically Present Diabetes and Hypertension: Secondary Analysis of a Population-Based Cross-Sectional Study

Background

Diabetes and hypertension are key risk factors for coronary heart disease. Prevalence of both conditions is socio-economically patterned. Awareness of presence of the conditions may influence risk behaviour and use of preventative services. Our aim was to examine whether there were socio-economic differences in awareness of hypertension and diabetes in a UK population.

Method

Data from the Scottish Health Survey was used to compare self-reported awareness of hypertension and diabetes amongst those found on examination to have these conditions, by socioeconomic position (SEP) (measured by occupation, education and income). Odds ratios of self-reported awareness against presence, and the sensitivity, specificity and predictive value of self-reporting as a measure of the presence of the condition, were calculated.

Results

Presence and self-reported awareness of both conditions increased as SEP decreased, on most measures. There was only one significant difference in awareness by SEP once other factors had been taken into account. Sensitivity showed that those in the most disadvantaged groups were most likely to self-report awareness of their hypertension, and specificity showed that those in the least disadvantaged groups were most likely to self-report awareness of its absence. There were few differences of note for diabetes.

Conclusion

We found no consistent pattern in the associations between SEP and the presence and self-reported awareness of hypertension and diabetes amongst those with these conditions. Without evidence of differences, it is important that universal approaches continue to be applied to the identification and management of those at risk of these and other conditions that underpin cardiovascular disease.

SRH and HrQOL: does social position impact differently on their link with health status?

Background

Self-rated Health (SRH) and health-related quality of life (HRQoL) are used to evaluate health disparities. Like all subjective measures of health, they are dependent on health expectations that are associated with socioeconomic characteristics. It is thus needed to analyse the influence played by socioeconomic position (SEP) on the relationship between these two indicators and health conditions if we aim to use them to study health disparities. Our objective is to assess the influence of SEP on the relationship between physical health status and subjective health status, measured by SRH and HRQoL using the SF-36 scale.

Methods

We used data from the French National Health Survey. SEP was assessed by years of education and household annual income. Physical health status was measured by functional limitations and chronic low back pain.

Results

Regardless of their health status, people with lower SEP were more likely than their more socially advantaged counterparts to report poor SRH and poorer HRQoL, using any of the indicators of SEP. The negative impact of chronic low back pain on SRH was relatively greater in people with a high SEP than in those with a low SEP. In contrast, chronic low back pain and functional limitations had less impact on physical and mental component scores of quality of life for socially advantaged men and women.

Conclusions

Both SRH and HRQoL were lower among those reporting functional limitations or chronic low back pain. However, the change varied according SEP and the measure. In relative term, the negative impact of a given health condition seems to be greater on SRH and lower on HRQoL for people with higher SEP in comparison with people with low SEP. Using SRH could thus decrease socioeconomic differences. In contrast using HRQoL could increase these differences, suggesting being cautious when using these indicators for analyzing health disparities.

Does self-rated health mean the same thing across socioeconomic groups? Evidence from biomarker data

PURPOSE

Self-rated health (SRH) is widely used to study health inequalities by socioeconomic status (SES), but concern has arisen that SRH may not correspond to objective health in the same way for different SES groups. We test whether levels of biological risk differ by SES for those with the same SRH.

METHODS

We analyzed a U.S. nationally representative sample of 13,877 adults aged 25 to 80 years. We tested whether education modifies the association between SRH and 14 biomarkers representing metabolic, cardiovascular, inflammatory, and organ function using both interaction models and models stratified by four levels of SRH. Estimated education coefficients in the stratified models indicated whether biomarker levels varied by educational attainment within a given self-rated health category.

RESULTS

Significant variation in biological risk by education within the same self-rated health category was found, especially at higher levels of SRH. In general, respondents with more education had healthier levels of biomarkers for the same level of SRH.

CONCLUSIONS

The results suggest that the relation of self-reported health to objective health, as measured by biological risk factors, differs by socioeconomic status. Caution should be exercised when using SRH to compare health risks across SES groups.

Does the predictive power of self-rated health for subsequent mortality risk vary by socioeconomic status in the US?

BACKGROUND

The purpose of this study is to test whether the predictive power of an individual's self-rated health (SRH) on subsequent mortality risk differs by socioeconomic status (SES) in the United States.

METHODS

We use the National Health Interview Survey 1986-94 linked to Multiple Cause of Death Files 1986-97 (NHIS-MCD). Analyses are based on non-Hispanic Black and White adults 25 and older (n = 358,388). Cox proportional hazard models are used to estimate the effect of SRH on mortality risk during follow-up. Interactions of SRH and level of education and SRH and level of income are used to assess differences in the predictive power of SRH for subsequent mortality risk.

RESULTS

The effect of SRH on subsequent mortality risk differs by level of education and level of income. Lower health ratings are more strongly associated with mortality for adults with higher education and/or higher income relative to their lower SES counterparts.

CONCLUSIONS

Our findings suggest that individuals with different education or income levels may evaluate their health differently with respect to the traditional five-point SRH scale, and hence their subjective health ratings may not be directly comparable. These results have important implications for research that tries to quantify and explain socioeconomic inequalities in health based on self-rated health.