The authors have declared that no competing interests exist.
Conceived and designed the experiments: SJ MS. Analyzed the data: SJ YY. Wrote the paper: SJ MS.
Income disparities in mortality are profound in the United States, but reasons for this remain largely unexplained. The objective of this study was to assess the effects of health behaviors, and other mediating pathways, separately and simultaneously, including health insurance, health status, and inflammation, in the association between income and mortality.
This study used data from 9925 individuals aged 20 years or older who participated in the 1999–2004 National Health and Nutrition Examination Survey (NHANES) and were followed up through December 31, 2006 for mortality. The outcome measures were all-cause and CVD/diabetes mortality. During follow-up 505 persons died, including 196 deaths due to CVD or diabetes.
After adjusting for age, sex, education, and race/ethnicity, risk of death was higher in low-income than high-income group for both all-cause mortality (Hazard ratio [HR], 1.98; 95% confidence interval [CI]: 1.37, 2.85) and cardiovascular disease (CVD)/diabetes mortality (HR, 3.68; 95% CI: 1.64, 8.27). The combination of the four pathways attenuated 58% of the association between income and all-cause mortality and 35% of that of CVD/diabetes mortality. Health behaviors attenuated the risk of all-cause and CVD/diabetes mortality by 30% and 21%, respectively, in the low-income group. Health status attenuated 39% of all-cause mortality and 18% of CVD/diabetes mortality, whereas, health insurance and inflammation accounted for only a small portion of the income-associated mortality (≤6%).
Excess mortality associated with lower income can be largely accounted for by poor health status and unhealthy behaviors. Future studies should address behavioral modification, as well as possible strategies to improve health status in low-income people.
Income disparities in health outcomes remain profound despite national and local efforts
Several key risk factors of mortality are more common among individuals with low income. These include, first, unhealthy behaviors, such as consumption of a low-quality diet, physical inactivity, tobacco use, and heavy alcohol use
Previous studies used various measures of income to examine different hypotheses about the negative relation between income and health outcomes
Therefore, this study investigated the mediating effects of four pathways, separately and simultaneously, on the association between individual income and mortality, using data from a nationally representative sample of US civilians. Specifically, objectives of this study were to estimate the extent to which health behaviors, access to medical care, health status and systemic inflammation accounted for any observed association between low income and mortality.
This study used data from the National Health and Nutrition Examination Survey (NHANES) collected in 1999 through 2004
Information about deaths was obtained from the NHANES (1999–2004) Linked Mortality File, which was created by the National Center for Health Statistics (NCHS) by linking the NHANES data to the National Death Index (NDI). The public-use version of the linked data includes the mortality status of all respondents 18 years and older until December 31, 2006, as well as person-month follow-up, and underlying cause of death
Respondents completed questions on annual total family income and family size. NHANES, then, calculated a Poverty Income Ratio (PIR), the ratio of family income to the poverty threshold for the family size in the year of the interview, using tables on poverty that are published yearly by the U.S. Census Bureau. In contrast to family income, the PIR is an inflation-adjusted, and thus relatively stable, measure for analysis across years. PIR was categorized, according to NHANES guidelines
Health behaviors include diet quality, physical activity, alcohol use, body mass index (BMI), and cigarette smoking. Diet quality was assessed by the Healthy Eating Index-2005 (HEI-05), calculated from the reported dietary data. The HEI-05 ranges from 0 to 100, with higher scores indicating greater compliance with
Health status at the time of the interview was assessed by self-report and included: self-rated health, and disability. Self-assessment of health, including self-rated health and functional disability are considered to be valid and useful indicators of health status
All statistical analyses were performed using SAS 9.2 proc survey procedures (SAS Institute, Cary, NC). Data from NHANES cycles 1999–2000, 2001–2002 and 2003–2004 were combined. In all analyses sampling design and weights were used to account for the complex sampling design in NHANES, thereby generating nationally representative estimates. Differences between the income groups were assessed by χ2 tests. Cox proportional hazards analyses were used to estimate the hazard ratio (HR) and corresponding 95% confidence intervals (95% CI) for the association between income category (low, intermediate, and high) and either all-cause mortality (Model I) or CVD/diabetes mortality (Model II), adjusted for demographic covariates (age, sex, and race/ethnicity). To test the mediating effect, the mediators were added, separately and simultaneously, to Model I (for all-cause mortality) and Model II (for CVD/diabetes mortality) (
(β Model I - β Model I+mediator(s)) × 100/β Model I (all-cause mortality).
(β Model II - β Model II+mediator(s)) × 100/β Model II (CVD/diabetes mortality).
Additionally, 95% confidence intervals were constructed for the estimates of the mediating effects, using bootstrapping re-sampling technique
Mediating effect was Calculated as: (β Model I – β Model I+mediator(s)) × 100/β Model I for all-cause mortality (β Model II - β Model II+mediator(s)) × 100/β Model II for CVD/diabetes mortality.
Because health status and health behaviors are interrelated
In addition to income, hazard ratios of mortality were estimated for education in the total population, also stratified by gender and race/ethnicity.
To evaluate whether a possible reverse causation between health and income, i.e. that low income caused by poor health, could affect the results, we conducted a sensitivity analysis excluding participants who were unemployed because of health reasons. Unemployment was define as reporting “looking for work” or “not working at a job/business” in the week before the interview. Among unemployed individuals, those who reported “unable to work for health reasons” or “disabled” were considered unemployed because of health reasons.
In addition, to examine the impact of mediating pathways among different age groups, age-stratified models were used, using three age groups: 20–44 years, 45–64 years, and 65 years and older.
Low income | Medium Income | High Income | ||
PIR ≤1.30 | 1.3 <PIR <3.5 | PIR ≥ 3.50 | ||
N = 2617 | N = 3855 | N = 3453 | ||
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Age, mean (SE) | 42.73 (0.46) | 45.75 (0.42) | 46.15 (36) | <.0001 |
Sex | <.0001 | |||
Female | 1440 (55) | 1986 (52) | 1693 (49) | |
Male | 1177 (45) | 1869 (48) | 1760 (51) | |
Race/ethnicity | <.0001 | |||
Non-Hispanic Black | 555 (21) | 744 (19) | 479 (14) | |
Mexican American | 884 (34) | 965 (25) | 381 (11) | |
Other | 259 (10) | 258 (7) | 177 (5) | |
Non-Hispanic White | 919 (35) | 1888 (49) | 2416 (70) | |
Education | <.0001 | |||
<High school | 1430 (55) | 1181 (31) | 300 (9) | |
High school/some college | 1060 (41) | 2183 (57) | 1759 (51) | |
≥ College graduate | 127 (5) | 491 (13) | 1394 (40) | |
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BMI (kg/m2) | <.0001 | |||
≥40.0 | 151 (6) | 182 (5) | 135 (4) | |
30.0–39.9 | 733 (28) | 1060 (27) | 892 (26) | |
25.0–29.9 | 891 (34) | 1421 (37) | 1289 (37) | |
18.5–24.9 | 797 (30) | 1134 (29) | 1094 (32) | |
<18.5 | 45 (2) | 58 (2) | 43 (1) | |
MET-hours/week of leisure-time physical activity | <.0001 | |||
Inactive (0) | 1450 (55) | 1701 (44) | 893 (26) | |
Somewhat active (>0 to <9) | 698 (27) | 1159 (30) | 1130 (33) | |
Active (≥9) | 469 (18) | 995 (26) | 1430 (41) | |
Diet (HEI-2005 quintiles) | <.0001 | |||
Q1 | 615 (24) | 784 (20) | 585 (17) | |
Q2 | 557 (21) | 774 (20) | 645 (19) | |
Q3 | 525 (20) | 806 (21) | 664 (19) | |
Q4 | 508 (19) | 774 (20) | 711 (21) | |
Q5 | 412 (16) | 717 (19) | 848 (24) | |
Current smoking | <.0001 | |||
Yes | 782 (30) | 866 (22) | 532 (15) | |
No | 1835 (70) | 2989 (78) | 2921 (85) | |
Alcohol use | <.0001 | |||
Non-drinker | 1347 (51) | 1702 (44) | 1035 (30) | |
Moderate drinker | 1117 (43) | 1899 (49) | 2150 (62) | |
Heavy drinker | 153 (6) | 254 (7) | 268 (8) | |
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Insurance coverage | <.0001 | |||
Yes | 1686 (64) | 3038 (79) | 3265 (95) | |
No | 931 (36) | 817 (21) | 188 (5) | |
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Self-rated health | <.0001 | |||
Good | 1753 (67) | 3085 (80) | 3155 (91) | |
Fair/poor | 864 (33) | 770 (20) | 298 (9) | |
Disabilities, Yes (vs. No) | ||||
ADL | 293 (11) | 225 (6) | 126 (4) | <.0001 |
IADL | 402 (15) | 309 (8) | 189 (5) | <.0001 |
LSA | 292 (11) | 217 (6) | 118 (3) | <.0001 |
LEM | 397 (15) | 352 (9) | 160 (5) | <.0001 |
GPA | 552 (21) | 552 (14) | 374 (11) | <.0001 |
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CRP, mg/L | <.0001 | |||
<1 | 610 (23) | 945 (25) | 1025 (30) | |
1–3 | 826 (32) | 1338 (35) | 1179 (34) | |
>3–10 | 826 (32) | 1154 (30) | 929 (27) | |
>10 | 355 (14) | 418 (11) | 320 (9) |
Abbreviations: ADL: Activities of daily living; BMI: Body mass index; CRP: C-reactive protein; CVD: Cardiovascular disease; GPA: General physical activities; HEI: Healthy eating index; IADL: Instrumental activities of daily living; LEM: Lower extremity mobility; LSA: Leisure and social activities; PIR: Poverty-income ratio.
Data are N (%) unless otherwise indicated. a χ2 (chi-square) analysis was used to compare frequencies and ANOVA was used to compare mean age between groups.
All-cause mortality | CVD/diabetes mortality | ||||||
Individual mediators | Person-years | Mortality rate |
HR |
Mortality rate |
HR |
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Diet (HEI-2005 quintiles) | |||||||
Q1 | 124462 | 10.32 | 1.46 (1.02, 2.10) | 3.57 | 1.28 (0.77, 2.13) | ||
Q2 | 117036 | 8.72 | 1.13 (0.74, 1.72) | 2.46 | 0.94 (0.44, 1.99) | ||
Q3 | 116052 | 9.31 | 1.06 (0.72, 1.54) | 4.55 | 1.51 (0.83, 2.74) | ||
Q4 | 111506 | 12.81 | 1.19 (0.88, 1.63) | 5.27 | 1.29 (0.70, 2.37) | ||
Q5 | 104883 | 11.90 | 1.00 | 4.81 | 1.00 | ||
MET-hours/week of leisure-time physical activity | |||||||
Inactive (0) | 238696 | 15.23 | 1.84 (1.34, 2.53) | 6.43 | 3.29 (1.64, 6.60) | ||
Somewhat active (>0 to <9) | 169797 | 10.32 | 1.26 (0.88, 1.81) | 3.89 | 2.04 (1.02, 4.05) | ||
Active (≥9) | 165446 | 4.06 | 1.00 | 0.94 | 1.00 | ||
Smoking | |||||||
Yes | 124304 | 10.23 | 1.96 (1.29, 2.97) | 3.57 | 2.19 (1.22, 3.93) | ||
No | 449635 | 10.65 | 1.00 | 4.24 | 1.00 | ||
Alcohol use | |||||||
Non-drinker | 235655 | 14.46 | 1.31 (0.97, 1.77) | 6.01 | 1.46 (0.96, 2.22) | ||
Moderate drinker | 298845 | 7.71 | 1.00 | 2.73 | 1.00 | ||
Heavy drinker | 39439 | 8.82 | 1.62 (0.96, 2.76) | 3.04 | 1.30 (0.62, 2.74) | ||
BMI, kg/m2 | |||||||
≥40.0 | 27190 | 7.06 | 1.42 (0.85, 2.37) | 2.21 | 2.12 (0.74, 6.09) | ||
30.0–39.9 | 156413 | 8.98 | 0.96 (0.68, 1.33) | 3.07 | 0.69 (0.40, 1.20) | ||
25.0–29.9 | 208468 | 10.48 | 0.69 (0.49, 0.96) | 4.37 | 0.72 (0.44, 1.19) | ||
18.5–24.9 | 173521 | 12.38 | 1.00 | 4.84 | 1.00 | ||
<18.5 | 8347 | 15.81 | 1.42 (0.52, 3.89) | 7.19 | 1.03 (0.29, 3.63) | ||
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Insurance coverage | |||||||
Yes | 460668 | 12.27 | 1.00 | 4.79 | 1.00 | ||
No | 113271 | 3.60 | 1.18 (0.70, 2.00) | 1.27 | 1.95 (0.79, 4.80) | ||
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Self-rated health | |||||||
Good | 464110 | 7.60 | 1.00 | 2.71 | 1.00 | ||
Fair/poor | 109829 | 23.05 | 2.61 (2.03, 3.36) | 9.94 | 2.50 (1.63, 3.84) | ||
Disabilities, Yes (vs. No) | |||||||
ADL | 33819 | 34.77 | 1.19 (0.84, 1.68) | 15.97 | 1.54 (0.89, 2.68) | ||
IADL | 48654 | 30.83 | 1.27 (0.83, 1.95) | 14.06 | 1.49 (0.84, 2.65) | ||
LSA | 33591 | 36.44 | 1.17 (0.84, 1.62) | 15.72 | 1.17 (0.74, 1.84) | ||
LEM | 48975 | 37.49 | 1.42 (0.91, 2.23) | 15.44 | 0.90 (0.40, 2.06) | ||
GPA | 79675 | 28.77 | 1.35 (0.89, 2.05) | 12.05 | 1.48 (0.69, 3.19) | ||
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CRP, mg/L | |||||||
<1 | 148784 | 5.00 | 1.00 | 1.94 | 1.00 | ||
1–3 | 191555 | 10.40 | 1.55 (1.07, 2.23) | 4.32 | 1.42 (0.70, 2.89) | ||
>3–10 | 170630 | 13.43 | 2.05 (1.47, 2.86) | 5.34 | 1.67 (0.77, 3.63) | ||
>10 | 62970 | 16.39 | 2.90 (1.95, 4.33) | 5.15 | 1.71 (0.80, 3.66) |
Abbreviations: ADL: Activities of daily living; BMI: Body mass index; CRP: C-reactive protein; CVD: Cardiovascular disease; GPA: General physical activities; HEI: Healthy eating index; IADL: Instrumental activities of daily living; LEM: Lower extremity mobility; LSA: Leisure and social activities; PIR: Poverty-income ratio.
The mortality rates are per 1,000 person-years;
Hazard ratio in separate models for each mediator, controlled for income, age, sex, education and race/ethnicity.
Low income | Intermediate income | |||
HR (95% CI) | % Attenuation |
HR (95% CI) | % Attenuation |
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Model I |
1.98 (1.37, 2.85) | – | 1.50 (1.10, 2.03) | - |
+Health behaviors (5 measures) | 1.61 (1.11, 2.33) | 30 (15, 64) | 1.33 (0.99, 1.79) | 30 (11, 131) |
Diet | 1.93 (1.33, 2.78) | 4 (−1, 13) | 1.48 (1.08, 2.01) | 4 (−2, 20) |
Physical activity | 1.78 (1.24, 2.57) | 15 (7, 34) | 1.43 (1.06, 1.92) | 12 (4, 48) |
Smoking | 1.85 (1.28, 2.67) | 10 (4, 24) | 1.44 (1.06, 1.94) | 10 (3, 43) |
Alcohol | 1.90 (1.32, 2.72) | 6 (−1, 19) | 1.46 (1.08, 1.96) | 7 (−2, 35) |
BMI | 1.94 (1.35, 2.79) | 1 (−2, 12) | 1.47 (1.09, 1.99) | 4 (−2, 19) |
+Health insurance | 1.93 (1.32, 2.83) | 3 (−6, 24) | 1.48 (1.09, 2.01) | 3 (−7, 30) |
+Health status (2 measures) | 1.51 (1.06, 2.17) | 39 (20, 76) | 1.38 (1.04, 1.84) | 20 (4, 70) |
Self-rated health | 1.68 (1.16, 2.42) | 24 (11, 50) | 1.44 (1.07, 1.95) | 9 (−3, 39) |
Disabilities | 1.63 (1.14, 2.33) | 28 (13, 55) | 1.42 (1.07, 1.89) | 13 (1, 43) |
+CRP | 1.94 (1.35, 2.79) | 3 (−4, 12) | 1.50 (1.11, 2.03) | −1 (−15, 10) |
Full model | 1.33 (0.91, 1.94) | 58 (28, 126) | 1.27 (0.95, 1.71) | 41 (11, 170) |
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Model II |
3.68 (1.64, 8.27) | – | 2.00 (1.11, 3.61) | – |
+Health behaviors (5 measures) | 2.79 (1.32, 5.92) | 21 (10, 39) | 1.71 (0.98, 2.98) | 22 (7, 90) |
Diet | 3.66 (1.61,8.30) | 0 (−4, 6) | 1.98 (1.08, 3.62) | 1 (−6, 14) |
Physical activity | 3.10 (1.44,6.72) | 13 (6, 25) | 1.84 (1.05, 3.24) | 12 (3, 48) |
Smoking | 3.42 (1.53,7.68) | 5 (1, 13) | 1.91 (1.08, 3.37) | 7 (1, 32) |
Alcohol | 3.41 (1.56,7.46) | 6 (0, 15) | 1.90 (1.07, 3.38) | 7 (−1, 31) |
BMI | 3.64(1.60, 8.26) | 1 (−3, 6) | 1.99 (1.09, 3.64) | 0 (−7, 11) |
+Health insurance | 3.41 (1.44, 8.07) | 6 (−2, 25) | 1.92 (1.05, 3.52) | 6 (−4, 34) |
+Health status (2 measures) | 2.92 (1.34, 6.40) | 18 (7, 34) | 1.90 (1.08, 3.34) | 8 (−7, 44) |
Self-rated health | 3.17 (1.44, 6.98) | 11 (4, 25) | 1.94 (1.09, 3.44) | 5 (−3, 25) |
Disabilities | 3.13 (1.41, 6.93) | 13 (4, 29) | 1.94 (1.08, 3.48) | 4 (−8, 27) |
+CRP | 3.65 (1.62,8.25) | 1 (−2, 5) | 1.99 (1.10, 3.61) | 0 (−6, 8) |
Full model | 2.33 (1.05, 5.16) | 35 (16, 68) | 1.61 (0.91, 2.87) | 31 (4, 150) |
age, sex, education, and race/ethnicity adjusted.
Calculated as: (β Model I – β Model I+mediator(s)) × 100/β Model I for all-cause mortality (β Model II - β Model II+mediator(s)) × 100/β Model II for CVD/diabetes mortality.
Of the 31,126 individuals who participated in the 1999–2004 NHANES, 14213 (46%) were aged 20 years or older and attended the mobile examination center. Of these, 9925 were included in this analysis after listwise deletion of those with missing data on mortality (n = 20), income (n = 1252), or other variables (n = 3016); missing data on each variable was less than 10%. Compared to the study sample, those who were excluded were on average 4.0 years older (95% CI: 2.9, 5.1), more likely to have low-income (38% vs. 26%), be non-Hispanic Black (23% vs. 18%), and had higher mortality rates for all-cause mortality (19.48 vs. 10.56 per 1000 person-years) and CVD/diabetes mortality (7.97 vs. 4.10 per 1000 person-years) (each
Example of calculation for all-cause mortality, low-income group: Mediating effect of Health Behaviors and Health Status = 57% Mediating effect of Health Behaviors = 30%; Mediating effect of Health Status = 39% Combined effect = 30%+39% = 69% Overlap = 69% –57% = 12% Health Behaviors, independent Effect = 30%–12% = 18% Health Status, Independent Effect = 39%–12% = 27%.
Total | Gender | Race/ethnicity | ||||
Women | Men | Non-Hispanic Black | Mexican American | Non-Hispanic White | ||
HR (95% CI) | HR (95% CI) | HR (95% CI) | HR (95% CI) | HR (95% CI) | HR (95% CI) | |
Person-years | 47828.25 | 24914.92 | 22913.33 | 8442.17 | 11324.58 | 24538.25 |
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N. of deaths | 505 | 201 | 304 | 98 | 79 | 309 |
Mortality rate | 10.56 | 8.07 | 13.27 | 11.61 | 6.98 | 12.59 |
Income | ||||||
Low, PIR ≤1.30 | 1.98 (1.37, 2.85) | 1.81 (0.97, 3.37) | 2.01 (1.23, 3.30) | 4.53 (2.10, 9.78) | 1.22 (0.28, 5.32) | 1.98 (1.30, 3.00) |
Medium, 1.3<PIR<3.5 | 1.50 (1.10, 2.03) | 1.25 (0.71, 2.20) | 1.68 (1.22, 2.33) | 3.32 (1.58, 6.96) | 0.61 (0.18, 2.14) | 1.46 (1.04, 2.04) |
High, PIR ≥3.50 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Education | ||||||
<High school | 1.68 (1.12, 2.51) | 2.11 (1.04, 4.27) | 1.53 (0.87, 2.66) | 1.22 (0.59, 2.53) | 0.35 (0.07, 1.62) | 1.92 (1.30, 2.82) |
High school/some college | 1.60 (1.09, 2.34) | 2.05 (0.98, 4.26) | 1.44 (0.86, 2.42) | 1.30 (0.59, 2.85) | 0.37 (0.10, 1.36) | 1.78 (1.23, 2.58) |
≥ College graduate | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
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N. of deaths | 196 | 80 | 116 | 34 | 34 | 120 |
Mortality rate | 4.10 | 3.21 | 5.06 | 4.03 | 3.00 | 4.89 |
Income | ||||||
Low, PIR ≤1.30 | 3.68 (1.64, 8.27) | 1.98 (0.82, 4.77) | 5.43 (1.95, 15.10) | 22.04 (2.58, 188.50) | 1.47 (0.05, 47.77) | 3.29 (1.39, 7.76) |
Medium, 1.3<PIR<3.5 | 2.00 (1.11, 3.61) | 0.96 (0.52, 1.78) | 3.34 (1.46, 7.64) | 17.70 (2.27, 137.76) | 0.49 (0.03, 9.49) | 1.62 (0.87, 3.01) |
High, PIR ≥3.50 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Education | ||||||
<High school | 0.97 (0.43, 2.16) | 1.29 (0.37, 4.45) | 0.91 (0.38, 2.15) | 2.19 (0.22, 22.41) |
|
1.11 (0.49, 2.50) |
High school/some college | 0.91 (0.46, 1.79) | 1.59 (0.53, 4.73) | 0.63 (0.26, 1.51) | 2.83 (0.32, 25.41) |
|
0.98 (0.48, 2.00) |
≥ College graduate | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
1370320 (67885.83, 27660815);
1773536 (695560.1, 4522152).
The unadjusted all-cause mortality rates per 1000 person-years among the low-, intermediate-, and high-income groups were 13.61, 12.85, and 5.77, respectively. The unadjusted CVD/diabetes mortality rates per 1000 person-years among the three income groups were 6.00, 4.97 and 1.72, respectively. After controlling for age, sex, education and race/ethnicity, the risk of all-cause mortality was higher in the low-income (HR: 1.98, 95% CI: 1.37, 2.85) and the intermediate-income (HR: 1.50, 95% CI: 1.10, 2.03), compared to the high-income group. The adjusted risk of CVD/diabetes mortality was 3.68 (95% CI: 1.64, 8.27) in the low-income and 2.00 (95% CI: 1.11, 3.61) in the intermediate-income group compared to the high-income group.
As shown in
Similarly, for CVD/diabetes mortality, health behaviors and health status had the largest mediating effects, 21% and 18%, respectively, while health insurance and CRP each accounted for only a small portion of the low-income disparity. Of all mediators, physical activity and disabilities accounted for the largest proportion of the effect of income on mortality. Overall, the full model attenuated 35% of the CVD/diabetes mortality in the low-income group and 31% in the intermediate income group.
As depicted in
When hazard ratios were estimated for education, the results showed that low-education was associated with all-cause mortality, but not with CVD/diabetes mortality (
The results of the sensitivity analysis excluding participants who were unemployed because of health reasons (N = 249), were similar to the original models; the combination of the four pathways attenuated 60% of the association between low income and all-cause mortality and 37% of that of CVD/diabetes mortality. In addition, results of the age stratified models showed that among individuals aged 20–44 years, unlike the older age groups, income was not associated with mortality. Moreover, in the age groups 45–64 and ≥65 years, respectively, the combination of the four pathways attenuated 66% and 48% of the association between income and all-cause mortality and 44% and 41% of that of CVD/diabetes mortality.
This nationally representative study of US adults assessed the mediating effects of health behaviors, health insurance coverage, health status and CRP on the association between income and all-cause and CVD/diabetes mortality. The combination of the four groups of factors accounted for the vast majority of why persons with low- and those with intermediate incomes were more likely to die compared to those with higher incomes. The results provide new insight into the pathways that mediate income disparities in health by demonstrating that besides unhealthy behaviors, poor health status also plays an important role in income disparities in health.
Consistent with previous studies, health behaviors accounted for only part of the reason for socioeconomic disparity in mortality. In particular, health behaviors attenuated 30% of all-cause mortality in this study compared to 12% in a previous US study
A more complete picture of socioeconomic disparities in mortality involves several other factors besides health behaviors, such as access to medical care, biological factors, and health status. Among these factors, poor health status was an important mediator in this study. One possible explanation is that worse health status is a consequence of unhealthy behaviors. However, a longitudinal nationally representative US study showed that unhealthy behaviors, including smoking, physical inactivity, alcohol use, and overweight, accounted for only a small proportion of the subsequent socioeconomic disparities in health status, measured by physical functioning and self-rated health
Contrary to health behaviors and health status, access to health care and biological factors had negligible contributions to income related mortality. Given that the proportion of people who were uninsured was greater in the low-income group, the reason for the small mediating effect may be partly related to the income related differences in types of insurance. In the US, public insurance has been associated with a greater risk of mortality than private insurance
This study has some limitations. First, the models did not include some potential mediators such as environmental factors. However, it is likely that these factors exert their effect through the more proximate mediators included in the statistical models. Second, mediators were measured only at one time point. Because some of the mediators may change differentially over time
In summary, this study supports the findings from previous studies that health behaviors are important mechanisms mediating income disparities in risk of death. The present study extends previous findings by showing that income disparities in mortality are also the result of poor health status. To reduce mortality in low income people, more emphasis may be needed in improving health status. Future studies should address behavioral modification, as well as possible strategies to improve health status in low-income people.