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. 2023 Oct 31;23:418. doi: 10.1186/s12890-023-02713-z

Lower socioeconomic status associated with higher tuberculosis rate in South Korea

Seong-Woo Choi 1,, Jeong-Ja Im 2, Sang-Eun Yoon 2, Seo-Hee Kim 2, Jun-Hwi Cho 2, So-Jung Jeong 2, Kyung-Ae Park 2, Young-Sung Moon 2
PMCID: PMC10619321  PMID: 37907868

Abstract

Background

Tuberculosis is an infectious disease influenced by social factors rather than a simple infectious disease. In this study, we investigated the relationship between tuberculosis rates and socioeconomic status.

Methods

This study was conducted using data of the 49,483 participants of the Korean National Health and Nutrition Examination Survey (KNHANES) VI–VIII (2013–2021). The relationships between tuberculosis rates and the quartiles of monthly household income and education level were examined using a multivariate logistic regression analysis.

Results

The KNHANES data revealed that the prevalence of tuberculosis as substantially related to monthly household income (odds ratio [OR], 6.0; 95% confidence interval [CI], 1.1–32.0 for lowest vs. highest incomes) and education level (OR, 3.8; 95% CI, 1.2–12.0 for 10–12 years vs. ≥13 years; OR, 4.1; 95% CI, 1.2–14.8 for ≤ 6 years vs. ≥13 years). Furthermore, current tuberculosis treatment was significantly related to monthly household income and education level.

Conclusion

There were substantial correlations between tuberculosis rates and socioeconomic status in South Korea.

Keywords: Income, Education, Socioeconomic status, Tuberculosis

Introduction

Tuberculosis (TB) is an infectious disease that is one of the leading causes of death throughout the world. Prior to the COVID-19 pandemic, TB had the highest mortality rate for a single infectious disease. According to the World Health Organization (WHO), there were  9.87 million tuberculosis cases and  1.49 million related deaths worldwide in 2020 [1]. In particular, multidrug-resistant TB has significantly increased the burden of the disease. Korea has one of the highest TB disease burdens among the Organization for Economic Co-operation and Development (OECD) countries. The TB mortality rate fell from 6.8 to 100,000 in 2001 to 2.8 per 100,000 in 2021, while the prevalence rate fell from 100.6 to 100,000 in 2001 to 29.7 per 100,000 in 2021 [2] (Fig. 1); however, these rates remain the highest among OECD countries.

Fig. 1.

Fig. 1

Age-standardized prevalence and mortality rate of tuberculosis in South Korea, 2001–2021

International organizations have attempted to break the transmission chains by identifying cases early and providing effective treatment through a TB control program [3]. However, these TB-treatment strategies have not proven to be sufficiently effective and, on a global scale, TB elimination remains a major challenge. This is because TB is not a simple infectious disease but an infectious disease influenced by social factors [3]. In other words, social determinants of health influence all aspects of TB, including exposure, diagnosis, treatment, and recovery [4]. Previous ecological studies have found links between high TB rates in different areas and low levels of education, high levels of poverty, and income inequality [57]. In individual-level studies, authors determined economic deprivation, homelessness, prison terms, injection of drugs, HIV/AIDS, and migration from high TB-rate countries as risk factors for TB [8, 9].

Korea has numerous distinct TB-related factors. Despite being a high-income country, it has a high incidence of TB and a few HIV/AIDS patients. Surprisingly, few studies have been conducted on the connection between socioeconomic status (SES) and TB in Korea. Therefore, we examined the relationship between TB and SES using the representative health data of Korea extracted from the Korea National Health and Nutrition Examination Survey (KNHANES) 2013–2021.

Methods

Subjects

This study was conducted using data extracted from KNHANES VI–VIII (2013–2021). KNHANES data have previously been published [10]. The Korea Centers for Disease Control and Prevention (KCDCP) conducted KNHANES on an annual basis (VI, 2013–2015; VII, 2016–2018; and VIII, 2019–2021), employing a nationally representative cross-sectional design. A total of 69,776 subjects were enrolled in KNHANES VI–VIII (2013–2021) (VI [2013: 8,018; 2014: 7,550; 2015: 7,380], VII [2016: 8,150; 2017: 8,127; 2018: 7,992], and VIII [2019: 8,110; 2020: 7,359; 2021: 7,090]). A total of 20,293 people were excluded; 13,662 were under the age of 19, 6,207 did not have tuberculosis data, and 424 did not have sociodemographic or behavioral data. Finally, 49,483 participants were examined in this study. All participants gave their written permission for their data to be used. Our research was carried out following the guidelines of the Declaration of Helsinki. The KCDCP ethics committee authorized the study protocol (2013-07CON-03-4 C, 2014-12EXP-03-5 C, 2015-01-02-6 C, 2018-01-03-P-A, 2018-01-03-1 C-A, 2018-01-03-2 C-A).

Study measurements

Individual interviews were conducted by trained researchers using a structured questionnaire. A person who answered “yes” to the question “being prevalent with TB” was defined as a patient, and a person who answered “yes” to the question “being treated with TB” was defined as a currently-treated TB patient. The monthly household income was divided into four quartiles (highest, medium-highest, medium-lowest, and lowest). The education level was classified as ≤ 6, 7–9, 10–12, and ≥ 13 years. The participants’ weight (to the nearest 0.1 kg) and height (to the nearest 0.1 cm) were measured while wearing light clothing and socks. Body mass index (BMI) was calculated by dividing the weight in kilograms by the height in meter squared. The marital status was classified as unmarried or married, and the residential area was classified as urban or rural. Current smokers were those who smoked regularly or occasionally, and current drinkers were those who had one or more drinking experiences in the previous month. Walking for more than thirty minutes at a time and more than five times per week was characterized as a physical activity. A health checkup within the last two years was defined as a case in which a health checkup was performed within the last two years; a cancer examination within the last two years was defined as a case in which a cancer examination was performed within the last two years.

Statistical analysis

The survey responses were weighted using a multilevel, multiple, probability-sampling design to represent nationally representative prevalence estimates of the Korean population. The estimates were derived by considering the primary sampling unit, stratification variables, and sampling weights. The data were expressed as an estimated percentage, with a 95% confidence interval [CI]. The distributions of each variable according to the quartiles of monthly household income and education level were examined using cross tabulation. The relationships between TB and the quartiles of monthly household income and education level were examined using a multivariate logistic regression analysis. The crude odds ratio (OR) and adjusted OR for gender, age, BMI, survey year, marital status, residence area, current smoking, drinking, physical activity, health checkup, and cancer examination over the previous two years are presented herein. P-values < 0.05 were deemed statistically significant. Statistical analysis was conducted using SPSS ver. 22.0.

Results

Baseline characteristics

The TB prevalence rate (per 100,000) was 64.8 and the current TB-treatment rate (per 100,000) is 55.3. Monthly household income was in the range of 15.0% for the lowest, 23.8% for the medium-lowest, 29.3% for the medium-highest, and 31.9% for the highest. The education level was 14.4% for ≤ 6 years, 8.5 for 7–9 years, 36.8% for 10–12 years, and 40.3% for ≥ 13 years. 20.9% of all subjects currently smoked and 57.6% had consumed alcohol in the previous month; 65.4% had a health checkup in the previous 2 years and 52.8% had a cancer examination in the previous 2 years (Table 1).

Table 1.

Baseline characteristics of subjects

Variables e%(95% CI)
TB prevalence (/100,000) 64.8 (44.9–93.4)
Current TB treatment (/100,000) 55.3 (36.7–83.2)
Gender
 Male 49.4 (49.0 − 49.8)
 Female 50.6 (50.2 − 51.0)
Age (years)
 ≤ 40 38.2 (37.4 − 38.9)
 41–64 45.5 (44.8 − 46.1)
 ≥ 65 16.4 (15.8 − 16.9)
Body mass index (kg/m2)
 < 18.5 4.4 (4.1 − 4.6)
 18.5–22.9 38.3 (37.7 − 38.8)
 23.0–24.9 22.6 (22.2 − 23.1)
 ≥ 25.0 34.7 (34.2 − 35.3)
Survey year
 KNHANES VI (2013–2015) 31.1 (30.4 − 31.9)
 KNHANES VII (2016–2018) 34.1 (33.3 − 35.0)
 KNHANES VIII (2019–2021) 34.8 (33.9 − 35.7)
Monthly household income
 Lowest 15.0 (14.4 − 15.6)
 Medium-lowest 23.8 (23.1 − 24.5)
 Medium-highest 29.3 (28.6 − 30.1)
 Highest 31.9 (30.8 − 32.9)
Education (year)
 ≤ 6 14.4 (13.9 − 15.0)
 7–9 8.5 (8.2 − 8.9)
 10–12 36.8 (36.1 − 37.4)
 ≥ 13 40.3 (39.4 − 41.2)
Marital status
 Single 34.0 (33.3 − 34.7)
 Married 66.0 (65.3 − 66.7)
Residential area
 Urban 84.3 (82.6 − 85.8)
 Rural 15.7 (14.2 − 17.4)
Number of household numbers
 1 10.1 (9.6–10.7)
 2–4 80.1 (79.5–80.8)
 ≥ 5 9.8 (9.2–10.3)
Current smoking 20.9 (20.4 − 21.4)
Alcohol intake 57.6 (57.0 − 58.2)
aPhysically active 45.9 (45.3 − 46.6)
bHealth examination during past 2 years 65.4 (64.8 − 65.9)
cCancer examination during past 2 years 52.8 (52.1 − 53.4)

All values are given as number and estimated percentage (95% confjdence interval).

CI; confidence interval, TB; tuberculosis, KNHANES; the Korea national health and nutrition examination survey

aPhysically active was indicated as ‘yes’ when the subject walked for more than 30 min at a time and more than five times per week.

bHealth examination during past 2 years was indicated as ‘yes’ when the subject had undergone health checkup within the prior 2 years.

cCancer examination during past 2 years was indicated as ‘yes’ when the subject had undergone screening within the prior 2 years for any kind of cancer such as lung cancer, stomach cancer, and breast cancer etc.

Characteristics of subjects by the quartile of monthly household income

The survey year, age, BMI, and current smoking differed significantly based on monthly household income quartiles. Furthermore, being a male, educated, urban dweller, alcohol intake, physical activity, health checkup, and cancer examination during the previous 2 years significantly increased with increasing monthly household income, whereas TB prevalence, current TB treatment, and being unmarried significantly decreased (Table 2).

Table 2.

Characteristics of subjects according to the quartile of monthly household income

Variables Monthly household income
Lowest Medium-lowest Medium-highest Highest P
TB prevalence (/100,000) 181.7(105.3-313.6) 63.0(30.7-129.6) 61.1(27.8-134.2) 14.3(4.1–49.5) < 0.001
Current TB treatment (/100,000) 140.2(73.5-267.3) 69.6(35.3–137.0) 52.8(22.0-126.9) 6.9(1.0-48.8) < 0.001
Gender < 0.001
 Male 42.8(41.6–43.9) 48.1(47.2–48.9) 50.9(50.1–51.7) 52.1(51.4–52.9)
 Female 57.2(56.1–58.4) 51.9(51.1–52.8) 49.1(48.3–49.9) 47.9(47.1–48.6)
Age (years) < 0.001
 ≤ 40 20.2(18.6–21.8) 37.4(36.1–38.7) 43.8(42.6–44.9) 42.2(41.1–43.3)
 41–64 30.2(29.0-31.5) 43.7(42.6–44.8) 47.2(46.1–48.3) 52.3(51.3–53.4)
 ≥ 65 49.7(48.0-51.3) 18.9(18.0-19.8) 9.0(8.5–9.6) 5.5(5.1-6.0)
Body mass index (kg/m2) < 0.001
 < 18.5 4.6(4.0-5.2) 4.7(4.2–5.2) 4.0(3.6–4.4) 4.4(4.0-4.8)
 18.5–22.9 36.2(34.9–37.5) 36.7(35.7–37.8) 38.6(37.7–39.6) 40.0(39.1–41.0)
 23.0–24.9 22.6(21.6–23.6) 22.7(21.8–23.6) 22.0(21.2–22.8) 23.1(22.4–23.9)
 ≥ 25.0 36.7(35.4–38.0) 35.9(34.8–37.0) 35.4(34.4–36.4) 32.5(31.5–33.4)
Survey year 0.039
 KNHANES VI (2013–2015) 31.7(29.9–33.5) 32.4(30.9–33.9) 31.3(29.8–32.7) 29.7(28.0-31.5)
 KNHANES VII (2016–2018) 35.8(33.9–37.7) 33.8(32.3–35.3) 34.3(32.8–35.8) 33.5(31.6–35.3)
 KNHANES VIII (2019–2021) 32.5(30.7–34.3) 33.9(32.4–35.4) 34.4(32.9–36.0) 36.8(34.8–38.8)
Education (year) < 0.001
 ≤ 6 45.3(43.7–47.0) 17.2(16.4–18.1) 8.0(7.5–8.5) 3.6(3.3-4.0)
 7–9 12.8(12.0-13.6) 11.7(11.0-12.4) 7.8(7.3–8.4) 4.7(4.4–5.2)
 10–12 28.8(27.3–30.3) 40.6(39.4–41.7) 40.4(39.3–41.5) 34.3(33.2–35.4)
 ≥ 13 13.1(12.1–14.1) 30.5(29.3–31.7) 43.8(42.6–45.1) 57.3(56.1–58.5)
Marital status < 0.001
 Single 51.5(49.9–53.0) 32.9(31.7–34.1) 30.3(29.2–31.4) 30.1(29.0-31.1)
 Married 48.5(47.0-50.1) 67.1(65.9–68.3) 69.7(68.6–70.8) 69.9(68.9–71.0)
Residential area < 0.001
 Urban 74.7(71.9–77.3) 82.1(80.0–84.0) 85.9(83.9–87.6) 88.9(87.1–90.4)
 Rural 25.3(22.7–28.1) 17.9(16.0–20.0) 14.1(12.4–16.1) 11.1(9.6–12.9)
Number of household numbers < 0.001
 1 29.2(27.7-3)0.7 9.6(8.9–10)0.4 6.4(5.7-7.)1 5.0(4.4-5.)5
 2–4 65.2(63.6-6)6.7 79.8(78.6–81.0) 82.6(81.5–83.7) 85.1(84.1–86.1)
 ≥ 5 5.7(4.8–6.7) 10.6(9.6-1)1.6 11.0(10.0–12.0) 9.9(9.0–10)0.9
Smoking 19.0(17.9–20.2) 21.6(20.7–22.6) 22.9(22.0-23.9) 19.5(18.6–20.3) < 0.001
Alcohol intake 41.1(39.7–42.5) 54.8(53.7–55.9) 60.6(59.5–61.7) 64.7(63.7–65.6) < 0.001
Physically activea 41.9(40.5–43.3) 45.5(44.4–46.6) 45.9(44.8–47.0) 48.3(47.2–49.4) < 0.001
Health examination during past 2 yearsb 57.0(55.7–58.3) 60.2(59.0-61.3) 66.1(65.1–67.1) 72.5(71.5–73.4) < 0.001
Cancer examination during past 2 yearsc 49.0(47.6–50.4) 50.1(48.9–51.3) 51.8(50.7–52.9) 57.5(56.5–58.6) < 0.001

All values are given as number and estimated percentage (95% confjdence interval).

TB; tuberculosis, KNHANES; the Korea national health and nutrition examination survey

aPhysically active was indicated as ‘yes’ when the subject walked for more than 30 min at a time and more than five times per week.

bHealth examination during past 2 years was indicated as ‘yes’ when the subject had undergone health checkup within the prior 2 years.

cCancer examination during past 2 years was indicated as ‘yes’ when the subject had undergone screening within the prior 2 years for any kind of cancer such as lung cancer, stomach cancer, and breast cancer etc.

Characteristics of subjects by educational level

TB prevalence, current TB treatment, BMI, survey years, marital status, current smoking, physical activity, health checkup, and cancer examination over the previous 2 years varied significantly based on education levels. Furthermore, being a male, having a monthly household income, urban dweller, and drinking alcohol increased significantly with increasing education level (Table 3).

Table 3.

Characteristics of subjects according to the quartile of education level

Variables Education (year)
≤ 6 7–9 10–12 ≥ 13 P
TB prevalence (/100,000) 176.2(107.0-290.2) 68.7(22.7-207.8) 74.4(37.9-145.6) 15.4(6.2–38.2) < 0.001
Current TB treatment (/100,000) 147.6(84.2-258.6) 47.2(11.8-188.2) 68.0(33.3-138.6) 12.5(4.3–36.5) < 0.001
Gender < 0.001
 Male 31.8(30.8–32.8) 47.1(45.6–48.7) 52.4(51.5–53.2) 53.4(52.7–54.2)
 Female 68.2(67.2–69.2) 52.9(51.3–54.4) 47.6(46.8–48.5) 46.6(45.8–47.3)
Age (years) < 0.001
 ≤ 40 1.3(1.0–1.)7 7.7(6.7-8.)8 42.7(41.7–43.7) 53.7(52.5–54.9)
 41–64 33.7(32.5–34.9) 62.9(61.2–64.5) 49.4(48.5–50.4) 42.3(41.2–43.5)
 ≥ 65 65.0(63.8–66.2) 29.5(28.0–31.0) 7.9(7.4-8.)3 4.0(3.7-4.)3
Body mass index (kg/m2) < 0.001
 < 18.5 2.7(2.4-3.)1 2.5(2.0–3.)1 4.7(4.4-5.)1 5.0(4.6-5.)4
 18.5–22.9 31.2(30.1–32.3) 33.6(32.1–35.2) 39.2(38.4–40.1) 40.9(40.1–41.7)
 23.0–24.9 25.4(24.5–26.5) 25.6(24.1–27.1) 22.4(21.6–23.1) 21.2(20.5–21.9)
 ≥ 25.0 40.6(39.5–41.8) 38.3(36.7–39.9) 33.7(32.8–34.6) 32.9(32.1–33.7)
Survey year 0.039
 KNHANES VI (2013–2015) 36.5(34.8–38.2) 33.0(31.2–34.9) 32.3(31.1–33.5) 27.7(26.5–29.0)
 KNHANES VII (2016–2018) 34.6(32.9–36.3) 35.1(33.2–37.1) 32.7(31.5–33.9) 35.1(33.6–36.6)
 KNHANES VIII (2019–2021) 28.9(27.3–30.6) 31.9(30.0-33.8) 35.0(33.7–36.3) 37.2(35.7–38.8)
Monthly household income < 0.001
 Lowest 47.3(45.9–48.7) 22.5(21.2–24.0) 11.8(11.0-12.6) 4.9(4.5-5.)3
 Medium-lowest 28.5(27.3–29.7) 32.8(31.2–34.4) 26.3(25.3–27.3) 18.0(17.1–18.9)
 Medium-highest 16.2(15.2–17.3) 27.0(25.4–28.6) 32.2(31.2–33.3) 31.9(30.8–32.9)
 Highest 8.0(7.3-8.)8 17.7(16.4–19.1) 29.7(28.5–31.0) 45.3(43.9–46.6)
Marital status < 0.001
 Single 36.5(35.2–37.7) 22.0(20.7–23.5) 38.9(37.8–40.0) 31.2(30.1–32.4)
 Married 63.5(62.3–64.8) 78.0(76.5–79.3) 61.1(60.0-62.2) 68.8(67.6–69.9)
Residential area < 0.001
 Urban 70.5(67.5–73.3) 78.3(75.7–80.7) 85.3(83.4–87.0) 89.5(87.9–90.9)
 Rural 29.5(26.7–32.5) 21.7(19.3–24.3) 14.7(13.0-16.6) 10.5(9.1-1)2.1
Number of household numbers < 0.001
 1 20.9(19.8-2)1.9 11.6(10.7–12.7) 8.0(7.3-8.)8 7.9(7.2-8.)7
 2–4 72.3(71.1-7)3.4 79.8(78.4–81.2) 81.0(80.1–82.0) 82.2(81.2–83.1)
 ≥ 5 6.8(6.1–7.6) 8.5(7.5-9.)7 10.9(10.2–11.8) 10.0(9.3-1)0.7
Smoking 12.7(11.9–13.6) 21.4(20.0-22.8) 25.6(24.7–26.5) 19.5(18.7–20.2) < 0.001
Alcohol intake 35.6(34.4–36.8) 50.8(49.1–52.4) 61.3(60.3–62.2) 63.5(62.7–64.4) < 0.001
Physically activea 37.3(36.0-38.5) 42.7(41.1–44.3) 48.4(47.4–49.3) 47.5(46.6–48.5) < 0.001
Health examination during past 2 yearsb 66.2(65.1–67.3) 69.1(67.5–70.6) 60.5(59.5–61.4) 68.8(67.9–69.6) < 0.001
Cancer examination during past 2 yearsc 61.5(60.3–62.6) 63.9(62.2–65.6) 46.9(46.0-47.8) 52.7(51.6–53.8) < 0.001

All values are given as number and estimated percentage (95% confjdence interval).

CI; confidence interval, TB; tuberculosis, KNHANES; the Korea national health and nutrition examination survey

aPhysically active was indicated as ‘yes’ when the subject walked for more than 30 min at a time and more than five times per week.

bHealth examination during past 2 years was indicated as ‘yes’ when the subject had undergone health checkup within the prior 2 years.

cCancer examination during past 2 years was indicated as ‘yes’ when the subject had undergone screening within the prior 2 years for any kind of cancer such as lung cancer, stomach cancer, and breast cancer etc.

The ORs for tuberculosis prevalence and treatment based on quartiles of monthly household income and educational level

Based on the adjustment for covariates, such as gender, age, BMI, survey year, marital status, residential area, number of household members, current smoking, alcohol intake, physical activity, health checkup, and cancer examination over the previous 2 years, TB prevalence was significantly correlated with monthly household income (OR, 6.0; 95% CI, 1.1–32.0 for lowest vs. highest) and education level (OR, 3.8; 95% CI, 1.2–12.0 for 10–12 years vs. ≥13 years; OR, 4.1; 95% CI, 1.2–14.8 for ≤ 6 years vs. ≥13 years). Moreover, current TB treatment was significantly correlated with monthly household income (OR, 8.1; 95% CI, 1.0–68.2 for medium-lowest vs. highest; OR, 12.3; 95% CI, 1.2–128.9 for lowest vs. highest) and education level (OR, 4.4; 95% CI, 1.2–16.4 for 10–12 years vs. ≥13 years; OR, 5.7; 95% CI, 1.3–24.4 for ≤ 6 years vs. ≥13 years) (Table 4).

Table 4.

The ORs for tuberculosis by monthly household income and education level

Crude Adjusted*
OR(95%CI) OR (95%CI)
TB prevalence Monthly household income
 medium- highest/highest 4.3(1.0-18.7) 3.6(0.8–16.3)
 medium-lowest/highest 4.4(1.0-18.6) 3.1(0.7–14.1)
 lowest/highest 12.8(3.3–49.6) 6.0(1.1–32.0)
Education (year)
 10–12/≥13 4.8(1.5–15.1) 3.8(1.2–12.0)
 7–9/≥13 4.5(1.1–18.8) 2.6(0.5–12.8)
 ≤ 6/≥13 11.5(4.0-32.6) 4.1(1.2–14.8)
Current TB treatment Monthly household income
 medium- highest/highest 7.7(0.9–66.1) 6.6(0.7–60.0)
 medium-lowest/highest 10.1(1.3–80.9) 8.1(1.0-68.2)
 lowest/highest 20.5(2.6-161.6) 12.3(1.2-128.9)
Education (year)
 10–12/≥13 5.5(1.5–19.9) 4.4(1.2–16.4)
 7–9/≥13 3.8(0.7–21.9) 2.8(0.4–20.5)
 ≤ 6/≥13 11.9(3.5–40.2) 5.7(1.3–24.4)

*Adjusted by gender, age, BMI, survey year, marital status, residential area, number of household members, current smoking, alcohol intake, physically active, health checkup during the previous 2 years and cancer examination during the previous 2 years

Discussion

This study assessed the relationship between SES and TB using KNHANES, a representative health dataset for Korea. Based on this study, we observed that the lower the monthly household income and education level, the greater the TB prevalence and the greater the TB treatment rate.

Our findings revealed a link between lower education levels and higher TB rates. In a study using data from the United States National TB Surveillance System from 1996 to 2005 [11], TB rates were highest among those with the least education. In a case-control study in England using the 2003–2012 UK Enhanced TB surveillance data, researchers found a link between higher education and lower TB rates [9], similar to our results. Education is known to be a strong predictor of future employment and earnings [12] as well as of increased awareness and/or increased ability to act on existing knowledge regarding healthy behavior [13, 14].

Our findings revealed a link between lower household income and higher TB rates. Previous research in low-income countries had yielded contradictory results. According to a case-control study conducted in Malawi, higher asset indexes is associated with lower TB rates [15]. However, other studies have not found a significant relationship between income and TB rates (5-glynn). High-income studies identified vulnerable groups of TB as economically disadvantaged people, the homeless, prisoners, and HIV/AIDS patients [3, 9]. The current global TB strategy focuses primarily on medical technologies, such as early case detection and effective treatment for the high-risk populations [16]. However, according to our findings, TB is a problem that is not limited to the vulnerable and marginalized groups. TB-related risks increase at a relatively constant rate with decreasing SES across the entire SES spectrum, similar to coronary heart disease, hypertension, cancer, and many chronic diseases [17]. This suggests that tuberculosis is not only a problem for high-risk groups but also a widespread societal health issue. In a 2006 Indian demographic health survey, TB prevalence increased linearly with the wealth quintile [18], similar to our findings.

There are several plausible explanations for the link between socioeconomic factors and TB. First, socioeconomic factors may expose people to TB, such as crowded and poorly ventilated work environments and housing. Second, malnutrition is a source of increased vulnerability. Third, increased risk factors include smoking, alcoholism, and comorbidities. Fourth, lack of access to health care results in delayed diagnosis and treatment.

Korea is a high-income country with a high TB incidence. The Korean government has implemented various tuberculosis eradication policies to reduce the prevalence of tuberculosis. The 2030 TB eradication plan was established in 2006, and the public private mix was expanded and implemented nationally in 2011. Furthermore, the government subsidized out-of-pocket TB-treatment costs in 2011 and the health coverage of latent TB-infected people was expanded in 2020, nearly eliminating the burden of out-of-pocket costs for tuberculosis testing and treatment [19]. Nonetheless, in this study, we observed differences in TB treatment rates based on SES. This is because, despite the free TB-treatment service provided by the public sector, patients bear direct costs associated with health seeking, indirect costs associated with lost income, and dissaving during illness, diagnosis, and treatment [20, 21]. These early costs are widespread, frequently severe, and have been linked to negative TB-treatment outcomes such as treatment failure, no follow-ups, or death.

Our research was based on extensive national health data. Despite the extensive register data of this study, it has some limitations. First, its cross-sectional design precludes drawing conclusions about the direction of the observed association between the TB rates and SES. Second, confounding effects may remain due to uncontrolled factors such as diabetes or cancer. Third, while KNHANES is a household-visit survey, it can under report cases of TB because it excludes high-risk populations, such as the homeless, inmates, and foreign workers. In conclusion, there were significant associations between TB rates and SES in South Korea.

Acknowledgements

Not applicable.

Authors’ contributions

SW and YS analyzed the samples and wrote the manuscript. JJ and SE was responsible for designing the study, and revising the manuscript. SH and JH were responsible for data interpretation. SJ and KA was responsible for analyzing the samples and revising the manuscript. All authors reviewed and approved the manuscript.

Funding

This study was supported by research fund from Chosun University (2022).

Data availability

The datasets generated and/or analysed during the current study are available in the KNHANES web site, https://knhanes.kdca.go.kr/knhanes/sub03/sub03_02_05.do.

Declarations

Ethics approval and consent to participate

Our research was carried out following the guidelines of the Declaration of Helsinki. The KCDCP ethics committee authorized the study protocol (2013-07CON-03-4 C, 2014-12EXP-03-5 C, 2015-01-02-6 C, 2018-01-03-P-A, 2018-01-03-1 C-A, 2018-01-03-2 C-A).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets generated and/or analysed during the current study are available in the KNHANES web site, https://knhanes.kdca.go.kr/knhanes/sub03/sub03_02_05.do.


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