Low household income and income volatility increase risk of lung cancer: A nationwide retrospective cohort study

Abstract

Low socioeconomic conditions, including low education, low income, manual or unskilled work, and unemployment, have been associated with increased lung cancer risks [1, 2]. Although some studies have identified low household status as a risk factor for lung cancer, they had some limitations in terms of their study design, including limited covariates in multivariate models, and cross-sectional assessment of income status, thereby failing to describe the association between income status change over time and lung cancer [1, 2]. Therefore, we investigated the association between longitudinal low household income status and lung cancer in the South Korean general population. We collected information on income status for 5 years to determine the change in household income status and income volatility. We also designed multivariate regression models with covariates including demographics, lifestyle behaviors, and comorbidities. Consequently, this study investigated the relationship between economic vulnerability, such as income volatility, and lung cancer risk.

We sampled 40% (4,910,068) of individuals who underwent a national health examination in 2012 (the index year). Among them, we included 3,816,680 individuals aged 30-65 years (economically active population). Thereafter, we excluded individuals with insufficient income information, identified with any cancer (any insurance claim with the International Classification of Diseases 10th Revision [ICD-10] codes for cancer [C00-97] and the critical illness registration code for cancer [V193]) before their health examination (all cancer wash-out), with insufficient medical records, and identified with any cancer within 1 year after the index date (1-year lag period, to exclude over-detection of cancer after the health examination). Finally, the remaining 3,361,091 eligible individuals started follow-up 1 year after the index date, until December 2022. The follow-up was terminated upon lung cancer development, death, or censor.

Lung cancer was identified using the ICD-10 code (C33 and C34) and matched with the critical illness registration program code (V193). The household income level was estimated based on subscribers’ monthly national health insurance premium, which is a proxy for household income. We categorized household income into quartiles (Q1 = lowest and Q4 = highest). Individuals receiving medical aid benefits (public assistance, the lowest 3% income) were assessed as a separate income category. To evaluate the temporal changes in household income status, we evaluated (1) cumulative number of years receiving medical aid (sustained low-income status) and (2) income volatility, defined as the intraindividual standard deviation (SD) of the percentage change in income (Q1 = the lowest and Q4 = the highest, Supplementary Figure S1), predicts income uncertainty and may limit health behaviors.

Covariates were collected from the health examination and insurance claims data, which included age, sex, region, body mass index, cigarette smoking, alcohol consumption, regular exercise, diabetes, hypertension, dyslipidemia, and chronic kidney disease. The data source and statistical analysis are described in the Supplementary Materials and Methods.

During the mean follow-up of 9.28 ± 0.78 years, 20,692 individuals with newly developed lung cancer were identified in our cohort. The mean age of total participants was 46.9 ± 9.4 years, with males accounting for 56.5%. Medical aid beneficiaries were predominantly females (59.0%) and never smokers (63.9%), whereas the highest income group (Q4) was predominantly males (65.5%) and had smoking history (former, 21.8%; current, 25.6%, Supplementary Table S1).

Table 1 presents the association between household income and lung cancer. Comparing the baseline income status, medical aid beneficiaries had the highest risk of lung cancer (adjusted hazard ratio [aHR], 1.23; 95% confidence interval [CI], 1.12-1.36). The lower the income category, the higher the lung cancer risk. Regarding sustained low-income status, medical aid beneficiaries for 5 consecutive years had the highest risk of lung cancer (aHR, 1.19; 95% CI, 1.07-1.34). Regarding income volatility, individuals with the highest income volatility (Q4) had the highest risk of lung cancer (aHR, 1.08; 95% CI, 1.04-1.12). The cumulative incidence of lung cancer, as shown by the Kaplan-Meier analysis, increased with economic vulnerabilities (Supplementary Figure S2).

In the stratified analyses by smoking status, current smokers had an approximately two-fold increased risk of developing lung cancer than never or former smokers. The association between income status and lung cancer risk was significant in current smokers, but not in never or former smokers (Supplementary Table S2). Stratified analysis by age revealed that the effect of low income was more prominent among individuals aged < 45 years, whereas the effect of income volatility was more prominent among individuals aged 45-55 years (Supplementary Table S3).

Previous studies have linked low household income to an increased risk of lung cancer [1, 2]. In our data, both low income at baseline and sustained status were associated with increased lung cancer risks in a dose-response manner, even after adjusting for smoking. Economic vulnerability is associated with other potential socioeconomic risk factors of lung cancer, including alcohol consumption and cigarette smoking, related to emotional stress owing to poor economic status [3, 4]. However, medical aid beneficiaries had a higher proportion of never-smokers and non-alcohol drinkers. Low income is also associated with air pollution, such as biomass fuel and ambient particulate matter [5]. Additionally, low income is related to less healthy foods (e.g., fewer vegetables and more frozen desserts) [6]. Low income is linked to anxiety and depression, which may aggravate poor economic conditions in a vicious cycle [7].

More importantly, our results demonstrated that income volatility was also associated with an increased lung cancer risk. Almost half of the individuals with the highest income volatility were categorized into baseline low-income categories (medical aid, 1.6%; Q1, 43.7%), thereby supporting the economic vulnerability at longitudinal aspects. Regarding liquidity-constrained households, a one SD increase in income volatility during 24 months can cause a 1.3%-4.3% increase in the probability of deteriorated health [8]. Income volatility was linked to poor health and well-being, such as depression [9]. Additionally, psychological stress may lead to frequent or heavy cigarette smoking and alcohol consumption [4].

The association between household income and lung cancer risk was more prominent in current smokers than in never or former smokers. Cigarette smoking is the most important cause of lung cancer, having a synergistic effect with other potential risk factors of lung cancer (e.g., alcohol, diet, occupational exposures, and air pollution) related to poor socioeconomic status, which could be modifiable through social support programs [10].

This study has some limitations. First, subscribers’ national health insurance premium is a proxy for estimating household income, and the health insurance premium was determined differently by employment type (employee-insured and self-employed), which might have caused income estimation inaccuracies. Second, loss of household income may reflect preceding poor health conditions (reverse causality), which may mitigate the effect of income on lung cancer. Third, voluntary participation and self-reported questionnaire responses (especially regarding smoking and alcohol consumption) in health examinations may lead to selection bias or recall bias. Fourth, there was limited information regarding potential risk factors, including air pollution, occupational exposure, secondhand smoke, and other health behaviors linked to economic vulnerability.

In conclusion, low-income status, particularly sustained low income and income volatility, was associated with an increased risk for lung cancer development in a dose-response manner. These associations were more prominent in current smokers. Our data requires public awareness of national healthcare policies (e.g. lung cancer screening or smoking cessation programs) for economically vulnerable individuals. Social safety net and stable employment opportunities may help economically vulnerable populations.

Chiwook Chung, Dong Wook Shin, Kyu Na Lee, Sei Won Lee, and Kyungdo Han conceived and designed the study. Kyu Na Lee and Kyungdo Han contributed to the data collection and analysis. The data were interpreted by Chiwook Chung, Dong Wook Shin, Kyu Na Lee, Sei Won Lee, and Kyungdo Han. Chiwook Chung and Dong Wook Shin drafted the manuscript. All authors revised and approved the final manuscript. All authors accept responsibility for the accuracy of the content in the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The funder did not have any role in the design of the study, in the collection, analysis, and interpretation of data, and in writing the manuscript.

This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-NR077159), the Bio&Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (No. RS-2022-NR067421 and No. RS-2023-00222687), the “National Institute of Health” (NIH) research project (No. 2024ER080600), and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (No. HI23C0679).

This study protocol was approved by the Institutional Review Board of Asan Medical Center, Seoul, Republic of Korea (approval No.: 2024-0990). The requirement for informed consent was waived, as it was a retrospective study, and the data used were anonymized. This study complied with the guidelines stipulated in the Declaration of Helsinki, and all methods were performed in accordance with the relevant guidelines.