Analysis of Forty Years of Geographic Disparity in Liver Cancer Mortality and the Influence of Risk Factors
Bibliographic Data
| ID | 3775385 |
|---|---|
| Authors | Xiaoping Shen (0000-0002-8125-5448, Central Connecticut State University), Limin Wang (0000-0001-9618-9239, National Center for Chronic and Noncommunicable Disease Control and Prevention), Xiulan Zhang (0000-0002-9288-0767, Beijing Normal University), Jiangmei Liu (0009-0000-5544-1266, National Center for Chronic and Noncommunicable Disease Control and Prevention), Lijun Wang (0000-0001-9782-6869, National Center for Chronic and Noncommunicable Disease Control and Prevention), Li Zhu (0000-0003-0179-6496, National Institutes of Health) |
| Year | 2022 |
| Volume | 112 |
| Issue | 2 |
| Pages | 563-580 |
| Publication date | 2022-02-17 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2021.1919501 |
| OpenAlex | W3169919684 |
| Language | EN |
| Citations received | 1 |
| References cited | 34 |
Regional disparities in cancer mortality rates are prevalent at all geographic scales. Area factors such as health conditions, behavior patterns, pollution, and socioeconomic status (SES) have significant impacts on cancer disparity. Efforts to determine the risk factors help to identify interventions that can lower disease burdens. In this study, we focus on liver cancer mortality (LCM), which is the second leading cause of cancer-related deaths in the world. Liver cancer rates have shown significant geographic disparities. We used a comprehensive database and applied innovative statistical models to investigate the influences of area factors on geographic disparities in LCM rates in China. To incorporate the long lag period between exposure and mortality, we integrated databases on LCM, other liver diseases, smoking and alcohol use, pollution, health care resources, censuses, and SES across four decades. Spatial random effect models were developed to address the effects of risk factors. Results showed that higher LCM is linked to less access to and lower availability of medical services and higher levels of water pollution. People in the high LCM area more likely worked in the industrial sector and had higher rates of smoking and alcohol use. Compared to Western countries where populations in high-LCM regions usually were those with the lowest SES, this study revealed that China’s high-LCM areas were the mostly rapidly industrializing regions with higher income, more severe water pollution, and a lack of access to medical services. Study results substantially inform potential policy on the allocation of resources for cancer prevention and control in developing countries
Cancer · China · Environmental health · Geography · Liver cancer · Population · Psychological intervention · Socioeconomic status · Data-Driven Disease Surveillance · Demography · Health disparities and outcomes · Healthcare Systems and Reforms · Medicine
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,25 |
| Citation span | 2022 - 2022 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |