Income, Self-Rated Health, and Morbidity. A Systematic Review of Longitudinal Studies
Abstract
:1. Introduction
2. Materials and Methods
2.1. Inclusion Criteria
- Longitudinal data to investigate the relationship between income and health over time;
- income in an individual/absolute form, rather than as a measure of income inequality;
- health as:
- SRH or a similar measurement parameter for subjective general health OR
- several, but at least three, different chronic conditions for the variable of morbidity; and
- a wide age range with only adults included. The age of the working population (15–65 years old) was considered the best cohort.
2.2. Search Strategy
2.3. Dependent and Independent Variable
2.3.1. Income
2.3.2. Self-Rated Health (SRH)
2.3.3. Morbidity
2.4. Variations between the Papers
3. Results
3.1. China
3.2. Germany
3.3. Great Britain
3.4. New Zealand
3.5. Sweden
3.6. USA
3.7. Systematic Review by Imlach Gunasekara et al
4. Discussion
4.1. The Relationship between Income and Self-Rated Health
4.2. The Relationship between Income and Morbidity
4.3. The Effect of Exogenous Positive Income Shocks
5. Limitations
6. Conclusions
- ◦
- the multitude of possible disruptive factors,
- ◦
- the presumably different responses to exogenous income shocks and permanent income increases, and
- ◦
- the different research methods producing various results, it becomes clear that the association between income and health is very complex and needs further examination.
Author Contributions
Funding
ER/HHK/AH
Conflicts of Interest
References
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Author & Year | Country | Sample Size | Age | Percent Women | SRH (Self-Rated-Health) | Morbidity | Income | Survey & Statistical Methods | Time of Measurement | Results |
---|---|---|---|---|---|---|---|---|---|---|
Jiang et al. 2019 | China | NHSS (National Health Services Survey): N = 300,000 out of 93,600 households CHARLS (China Health and Retirement Longitudinal Study): N = 17.000 out of 10.000 households | NHSS: adults 15+ CHARLS: adults 45+ | N/A | N/A | Prevalence of chronic diseases →one of the 13 kinds, two-week incidence rate, the number of sick days per thousand people | Real income per capita (NHSS); average annual income per capita deflated (CHARLS) | National Health Services Survey (NHSS) and China Health and Retirement Longitudinal Study (CHARLS) data individual fixed effect regression model and individual random effect model, pooling (FGLS = feasible generalized least squares); pooling (OLS = ordinary least squares) | NHSS data from 1998, 2003, 2008 CHARLS data from wave 1–4 from 2011–2015 only using data from 2011, 2013, 2015 | There is a negative quadratic relationship between income per capita and morbidities. In addition, the relationship is found to be non-linear. At first morbidity decreases with growing per capita income. However, when income per capita reaches a specific turning-point level, morbidity begins to increase with continuing income growth. |
Frijters et al. 2005 | Germany | East: 46,953 person year observations on N = 6198 persons West: 176,770 person year observations on N = 20,617 persons | adults 18+ | 50–52% | Self-assessed health satisfaction scale 1–10 self-rated health (SRH) 1–5 scale | N/A | Equivalized pre-tax household income, relative household poverty | German Socio-Economic Panel (GSOEP); fixed effects ordered logit regression model | East Germans data: 13 waves from 1990–2002 West Germans data: 19 waves from 1984–2002 | There is a very small positive and statistically significant effect of large increase in real household income on the health satisfaction for East German males, but not females. A similar small effect for western males and females was also found. Studying the average health satisfaction over 13 years since reunification, a downward trend in health satisfaction for both East and West Germans was found. |
Lorgelly and Lindley 2008 | Great Britain | Annual N = 8645 Overall N = 71,598 | adults 16+ | 53% | Scale 1–5; recoded in a scale 1–4 with poor and very poor combined | N/A | Net total annual household income | The British Household Panel Survey (BHPS); ordered probit regression technique; pooled ordered probit (POP), random effects ordered probit (REOP), fixed effects ordered probit (FEOP) | First 12 waves from 1991–2004 | There is a significant, positive relationship between self-rated health and the absolute household income. |
Jones and Wildman 2008 | Great Britain | Annual N = 10,000 Overall N = 113,310 | adults 16+ | ca. 54% | Scale 1–5 Recoded in 1 = good or excellent and 0 = fair, poor, very poor | N/A | Equivalized and deflated annual household income | BHPS (The British Household Panel Survey); parametric and semiparametric panel data models | First 11 waves starting in 1991 | There is a clear evidence of income having a significant, positive but small effect on self-assessed health. Large changes in income cause small changes in health. It is shown, that there is a non-linear relationship between income and health. |
Apouey and Clark 2015 | Great Britain | Annual: N = 10,000–16,000 out of 5500–9000 households Overall: N = 110,000 | adults 16+ | ca. 54% | Scale 1–5 | Health problems with arms, legs, hands; sight; hearing; skin conditions/allergy; chest/breathing; heart/blood pressure; stomach or digestion; diabetes | Positive income shocks as lottery prizes | BHPS (The British Household Panel Survey); three models with individual fixed effects regression models | Health data from wave 6–18 from 1996–2008 lottery prizes data from wave 7–18 from 1997–2008 | The coefficients on any prize are insignificant. In other words, there is no evidence of a positive correlation between exogenous income and general health. In addition, there is no significant relationships between lottery winnings and physical health problems. It was found, that there is a significant positive effect on mental health. |
Imlach Gunasekara et al. 2012 | New Zealand | N = 22,165 out of 11,500 households | Adults 15+; middle age ca. 41 | 54.5% | Scale 1–5 | N/A | Household income (employment earnings, government benefits, pensions, investments and interest) | NZ Survey of Family, Income and Employment (SoFIE); fixed-effects ordinal logistic regression model | Four waves from 2002–2005 | An increase in income of $10,000 over one year increased the odds of reporting better SRH by 1% (OR 1.01, 95% CI 1.00 to 1.02). Poor baseline health significantly modified the association between income and SRH while poverty or deprivation did not modify the association. |
Pega et al. 2013 | New Zealand | N = 6900 out of 11,500 households | Adults 15 + | 56.3% | Scale 1–5 | N/A | Equivalized gross total annual family income;the dollar amount of IWTC (In-Work Tax Credit) | NZ Survey of Family, Income and Employment (SoFIE); fixed effects regression analyses | Seven waves from 2002–2009 | A $1000 increase in the IWTC amount increased SRH by 0.003 units (no significance). Becoming eligible for IWTC or a substantial increase in the IWTC amount was not associated with a difference in SRH over the short term. |
Pega et al. 2014 | New Zealand | N = 6900 | Working age 19–65 | 56.3% | Scale 1–5 | N/A | Equivalized gross total annual family income; the dollar amount of FTC (Family Tax Credit) | NZ Survey of Family, Income and Employment (SoFIE); unadjusted and fully adjusted fixed effects regression analyses | Seven waves from 2002–2009 | The unconditional tax credit for families had no short-term effect on SRH. There is no difference between the impact of unconditional and employment-conditional tax-credit on SRH. |
Lindahl 2003 | Sweden | N = 2948 | Adults middle age 53.3 | 56% | Number of poor mental health symptoms | 48 health symptoms combined to the Standardized Index of Bad Health | Income including sources as work, capital, and government transfers | Swedish Level of Living Surveys (SLLS) Poisson as well as OLS regression | Three waves from 1968, 1974, 1981 | Winning 100,000 Swedish kronor (SEK) on lotteries in a 13-year period (almost 8000 per year) increases general health by 3 percent. Income shocks are negatively associated with poor mental health, cardiovascular diseases and headaches. Furthermore, the income change reduces the chance of being overweight. |
Miething and Åberg Yngwe 2014 | Sweden | N = 5142 (SRH Data) N = 3377 (Income Data) | Working age 30–64 | ca. 50% | Good, bad and something in between; recoded in good and poor (= bad and something in between) | N/A | Individual disposable income (income after taxation and welfare transfers) = net income | The Swedish Level of Living Survey (SLLS); the income register; logistic regression models | SRH-data from 2000 (cross sectional) income-data from 1995–2000 (longitudinal data) | Decreases in absolute income have a greater effect on self-rated health than income gains have over time. Loss of income is a threat for health whereas increases in income shows inconsistent results. Income instability in either way shows an adverse association with health. |
Fiscella and Franks 2000 | USA | N = 14,407 | Adults 25–74 | N/A | Scale 1–5 | Physical examination: laboratory, EKG, pulmonary function, radiologic test results; severity of conditions: minimum, moderate, severe | Total annual family income; 12 income categories ranging from under $1000 to $25,000 and over | The first National Health and Nutrition Examination Survey and Epidemiologic Follow-up Study; cumulative logistic regression models | Three waves from 1982–1984 | Individual income has a much stronger relationship with biomedical morbidity and baseline and follow-up self-rated health than income inequality has. |
Halliday 2007 | USA | N = 13,800 | Working-aged people 30–60 | ca. 53% | Scale 1–5, recoded in good = 1 or 2, bad = 4 or 5 and 3 is omitted | N/A | Individual labor income; adverse income shocks (less income or unemployment) | Panel study of income dynamics (PSID); individual-specific fixed-effects regression analyses | Health data from 1984–1997 labor income data from 1978–1994 | Positive income shocks tend to improve health outcomes. Movements from the bottom and the top of the income distribution to the middle leads to better health. The transition from income below the 75%-percentile to above this percentile causes an adverse effect on health (turning point). Adverse income shocks have negative effects on self-rated health. |
Ryder et al. 2011 | Houston, USA | N = 4162 | Middle age 42.85 ± 14.87 | 87.3% | Scale 1–5, recoded in 0 (fair or poor) and 1 (good, very good or excellent) | N/A | Gross annual household income; four different methods to impute missing income data | The Mexican American Cohort Study (MACS); logistic regression analysis | Four waves from 1 July. 2002–31 December 2005 | The “yearly income” was a good predictor of SRH outcome. The odds of SRH as good or better increased by 11% for each $5000 increment in yearly income. People with a good or better SRH have a significantly greater yearly income than the people with fair or poor SRH. |
Imlach Gunasekara et al. 2011 Systematic review | Great Britain, USA, Germany, Australia | five longitudinal surveys in 13 studies | Often adults 15+ | Various | Scale 1–5 | N/A | BHPS, GSEOP, HRS (Health and Retirement Study): annual equivalized household income PSID (Panel Study of Income Dynamics): change in income-to-needs ratio; labor income HILDA (Household, Income and Labour Dynamics in Australia): income less than 50% of median income = poverty | British Household Panel Survey (five studies); Panel Study of Income Dynamics (four studies); German Socioeconomic Panel (three studies); Health and Retirement Study (one study); Household, Income and Labour Dynamics in Australia (HILDA) Survey (one study) | In total from 1967–2005 | Most studies (ten of 13) found that income change had a small, statistically significant positive association with SRH. Three studies out of these 10 found no significant relationship among women. |
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Reche, E.; König, H.-H.; Hajek, A. Income, Self-Rated Health, and Morbidity. A Systematic Review of Longitudinal Studies. Int. J. Environ. Res. Public Health 2019, 16, 2884. https://doi.org/10.3390/ijerph16162884
Reche E, König H-H, Hajek A. Income, Self-Rated Health, and Morbidity. A Systematic Review of Longitudinal Studies. International Journal of Environmental Research and Public Health. 2019; 16(16):2884. https://doi.org/10.3390/ijerph16162884
Chicago/Turabian StyleReche, Elena, Hans-Helmut König, and André Hajek. 2019. "Income, Self-Rated Health, and Morbidity. A Systematic Review of Longitudinal Studies" International Journal of Environmental Research and Public Health 16, no. 16: 2884. https://doi.org/10.3390/ijerph16162884