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Fundamental social causes of inequalities in colorectal cancer mortality: A study of behavioral and medical mechanisms.

ABSTRACT: Background:Fundamental cause theory posits that social conditions strongly influence the risk of health risks. This study identifies risk mechanisms that social conditions associated with socioeconomic status (SES) and race/ethnicity shape in the production of colorectal cancer (CRC) mortality. Methods:Two large datasets in the United States examining behavioral and medical preventive factors (N = 4.63-million people) were merged with population-level mortality data observing 761,100 CRC deaths among 3.31-billion person-years of observation to examine trends in CRC mortality from 1999-2012. Analyses examined the changing role of medical preventions and health behaviors in catalyzing SES and racial/ethnic inequalities in CRC mortality. Results:Lower SES as well as Black, Hispanic, Asian/Pacific Islander, and Native American race/ethnicity were associated with decreased access to age-appropriate screening and/or increased prevalence of behavioral risk factors. Analyses further revealed that SES and racial/ethnic inequalities were partially determined by differences in engagement in two preventive factors: use of colonoscopy, and participation in physical activity. Discussion:Social inequalities were not completely determined by behavioral risk factors. Nevertheless, a more equitable distribution of preventive medicines has the potential to reduce both the risk of, and social inequalities in, CRC mortality.

SUBMITTER: Clouston SAP

PROVIDER: S-EPMC7068626 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Fundamental social causes of inequalities in colorectal cancer mortality: A study of behavioral and medical mechanisms.

Clouston Sean A P SAP Acker Julia J Rubin Marcie S MS Chae David H DH Link Bruce G BG

Heliyon 20200311 3

<h4>Background</h4>Fundamental cause theory posits that social conditions strongly influence the risk of health risks. This study identifies risk mechanisms that social conditions associated with socioeconomic status (SES) and race/ethnicity shape in the production of colorectal cancer (CRC) mortality.<h4>Methods</h4>Two large datasets in the United States examining behavioral and medical preventive factors (<i>N</i> = 4.63-million people) were merged with population-level mortality data observi ...[more]

PMID: 32190753

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Project description:Background During the coronavirus diseases 2019 (COVID-19) pandemic, population’s mortality has been affected not only by the risk of infection itself, but also through deferred care for other causes and changes in lifestyle. This study aims to investigate excess mortality by cause of death and socio-demographic context during the COVID-19 pandemic in South Korea. Methods Mortality data within the period 2015–2020 were obtained from Statistics Korea, and deaths from COVID-19 were excluded. We estimated 2020 daily excess deaths for all causes, the eight leading causes of death, and according to individual characteristics, using a two-stage interrupted time series design accounting for temporal trends and variations in other risk factors. Results During the pandemic period (February 18 to December 31, 2020), an estimated 663 (95% empirical confidence interval [eCI]: -2356–3584) excess deaths occurred in South Korea. Mortality related to respiratory diseases decreased by 4371 (3452–5480), whereas deaths due to metabolic diseases and ill-defined causes increased by 808 (456–1080) and 2756 (2021–3378), respectively. The increase in all-cause deaths was prominent in those aged 65–79 years (941, 88–1795), with an elementary school education or below (1757, 371–3030), or who were single (785, 384–1174), while a decrease in deaths was pronounced in those with a college-level or higher educational attainment (1471, 589–2328). Conclusion No evidence of a substantial increase in all-cause mortality was found during the 2020 pandemic period in South Korea, as a result of a large decrease in deaths related to respiratory diseases that offset increased mortality from metabolic disease and diseases of ill-defined cause. The COVID-19 pandemic has disproportionately affected those of lower socioeconomic status and has exacerbated inequalities in mortality. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-14785-3.

Project description:BackgroundTo more efficiently reduce social inequalities in mortality, it is important to establish which causes of death contribute the most to socioeconomic mortality differentials. Few studies have investigated which diseases contribute to existing socioeconomic mortality differences in specific age groups and none were in samples of the whole population, where selection bias is minimized. The aim of the present study was to determine which causes of death contribute the most to social inequalities in mortality in each age group in the whole population of Scania, Sweden.MethodsData from LOMAS (Longitudinal Multilevel Analysis in Skåne) were used to estimate 12-year follow-up mortality rates across levels of socioeconomic position (SEP) and workforce participation in 975,938 men and women aged 0 to 80 years, during 1991-2002.ResultsThe results generally showed increasing absolute mortality differences between those holding manual and non-manual occupations with increasing age, while there were inverted u-shaped associations when using relative inequality measures. Cardiovascular diseases (CVD) contributed to 52% of the male socioeconomic difference in overall mortality, cancer to 18%, external causes to 4% and psychiatric disorders to 3%. The corresponding contributions in women were 55%, 21%, 2% and 3%. Additionally, those outside the workforce (i.e., students, housewives, disability pensioners, and the unemployed) showed a strongly increased risk of future mortality in all age groups compared to those inside the workforce. Even though coronary heart disease (CHD) played a major contributing role to the mortality differences seen, stroke and other types of cardiovascular diseases also made substantial contributions. Furthermore, while the most common types of cancers made substantial contributions to the socioeconomic mortality differences, in some age groups more than half of the differences in cancer mortality could be attributed to rarer cancers.ConclusionCHD made a major contribution to the socioeconomic differences in overall mortality. However, there were also important contributions from diseases with less well understood mechanistic links with SEP such as stroke and less-common cancers. Thus, an increased understanding of the mechanisms connecting SEP with more rare causes of disease might be important to be able to more successfully intervene on socioeconomic differences in health.

Project description:BACKGROUND: The estimation of healthy life years (HLY) by socio-economic status (SES) requires two types of data: the prevalence of activity limitation by SES generally extracted from surveys and mortality rates by SES generally derived from a linkage between the SES information in population databases (census, register) and mortality records. In some situations, no population-wide databases are available to produce mortality rates by SES, and therefore some alternatives must be explored. This paper assesses the validity of calculating HLY by SES using mortality rates derived from a linkage between surveys and mortality records. METHODS: TWO SURVEYS WERE CHOSEN TO EXPLORE THE VALIDITY OF THE PROPOSED APPROACH: The Belgian Health Interview Survey (HIS) and the Belgian Survey on Income and Living Conditions (SILC). The mortality follow-up of these surveys were used to calculate HLY by educational level at age 25. These HLY were compared with HLY estimates calculated using the mortality follow-up of the 2001 census. The validity of this approach was evaluated against two criteria. First, the HLY calculated using the census and those calculated using the surveys must not be significantly different. Second, survey-based HLY must show significant social inequalities since such inequalities have been consistently reported with census-based HLY. RESULTS: Both criteria were met. First, for each educational category, no statistically significant difference was found when comparing census-based and survey-based HLY estimates. For instance, men in the lowest educational category have shown a HLY of 34 years according to the HIS, and while this figure was 35.5 years according to the census, this difference was not statistically significant. Second, the survey-based HLY have shown a significant social gradient. For instance, men in the highest educational category are expected to live 9.5 more HLY than their counterparts in the lowest educational category based on the HIS estimates, compared with 7.3 HLY based on the census estimates. CONCLUSIONS: This article suggests that using the mortality follow-up of a nationally representative cross-sectional survey is a valid approach to monitor social inequalities in HLY in the absence of population-wide data.

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Fundamental social causes of inequalities in colorectal cancer mortality: A study of behavioral and medical mechanisms.

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Fundamental social causes of inequalities in colorectal cancer mortality: A study of behavioral and medical mechanisms.

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