Dataset Information

Urban/Rural Differences in Breast and Cervical Cancer Incidence: The Mediating Roles of Socioeconomic Status and Provider Density.

ABSTRACT: BACKGROUND:Breast and cervical cancer incidence vary by urbanicity, and several ecological factors could contribute to these patterns. In particular, cancer screening or other sociodemographic and health care system variables could explain geographic disparities in cancer incidence. METHODS:Governmental and research sources provided data on 612 counties in the Surveillance, Epidemiology, and End Results program for rural-urban continuum code, socioeconomic status (SES) quintile, percent non-Hispanic White residents, density of primary care physicians, cancer screening, and breast and cervical cancer incidence rates (2009-2013). Ecological mediation analyses used weighted least squares regression to examine whether candidate mediators explained the relationship between urbanicity and cancer incidence. RESULTS:As urbanicity increased, so did breast cancer incidence (?ˆ = 0.23; p < .001). SES quintile and density of primary care physicians mediated this relationship, whereas percent non-Hispanic White suppressed it (all p < .05); county-level mammography levels did not contribute to the relationship. After controlling for these variables, urbanicity and breast cancer incidence were no longer associated (?ˆ = 0.11; p > .05). In contrast, as urbanicity increased, cervical cancer incidence decreased (?ˆ = -0.33; p < .001). SES quintile and density of primary care physicians mediated this relationship (both p < .05); percent non-Hispanic White and Pap screening levels did not contribute to the relationship. After controlling for these variables, the relationship between urbanicity and cervical cancer incidence remained significant (?ˆ = -0.13; p < .05). CONCLUSIONS:County-level SES and density of primary care physicians explained the relationships between urbanicity and breast and cervical cancer incidence. Improving these factors in more rural counties could ameliorate geographic disparities in breast and cervical cancer incidence.

SUBMITTER: Moss JL

PROVIDER: S-EPMC5694385 | biostudies-literature | 2017 Nov - Dec

REPOSITORIES: biostudies-literature

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Urban/Rural Differences in Breast and Cervical Cancer Incidence: The Mediating Roles of Socioeconomic Status and Provider Density.

Moss Jennifer L JL Liu Benmei B Feuer Eric J EJ

Women's health issues : official publication of the Jacobs Institute of Women's Health 20171103 6

<h4>Background</h4>Breast and cervical cancer incidence vary by urbanicity, and several ecological factors could contribute to these patterns. In particular, cancer screening or other sociodemographic and health care system variables could explain geographic disparities in cancer incidence.<h4>Methods</h4>Governmental and research sources provided data on 612 counties in the Surveillance, Epidemiology, and End Results program for rural-urban continuum code, socioeconomic status (SES) quintile, p ...[more]

PMID: 29108988

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Project description:Background and objectivesUnderstanding the social determinants of health is a major goal in evolutionary biology and human health research. Low socioeconomic status (often operationalized as absolute material wealth) is consistently associated with chronic stress, poor health and premature death in high-income countries. However, the degree to which wealth gradients in health are universal-or are instead made even steeper under contemporary, post-industrial conditions-remains poorly understood.MethodologyWe quantified absolute material wealth and several health outcomes among a population of traditional pastoralists, the Turkana of northwest Kenya, who are currently transitioning toward a more urban, market-integrated lifestyle. We assessed whether wealth associations with health differed in subsistence-level versus urban contexts. We also explored the causes and consequences of wealth-health associations by measuring serum cortisol, potential sociobehavioral mediators in early life and adulthood, and adult reproductive success (number of surviving offspring).ResultsHigher socioeconomic status and greater material wealth predicts better self-reported health and more offspring in traditional pastoralist Turkana, but worse cardiometabolic health and fewer offspring in urban Turkana. We do not find robust evidence for either direct biological mediators (cortisol) or indirect sociobehavioral mediators (e.g. adult diet or health behaviors, early life experiences) of wealth-health relationships in either context.Conclusions and implicationsWhile social gradients in health are well-established in humans and animals across a variety of socioecological contexts, we show that the relationship between wealth and health can vary within a single population. Our findings emphasize that changes in economic and societal circumstances may directly alter how, why and under what conditions socioeconomic status predicts health.Lay summaryHigh socioeconomic status predicts better health and more offspring in traditional Turkana pastoralists, but worse health and fewer offspring in individuals of the same group living in urban areas. Together, our study shows that under different economic and societal circumstances, wealth effects on health may manifest in very different ways.

Project description:ObjectiveTo characterize health disparities in common chronic diseases among adults by socioeconomic status (SES) and ethnicity in a mixed rural-urban community of the United States.Patients and methodsWe conducted a cross-sectional study to assess the association of the prevalence of the 5 most burdensome chronic diseases in adults with SES and ethnicity and their interaction. The Rochester Epidemiology Project medical records linkage system was used to identify the prevalence of coronary heart disease, asthma, diabetes, hypertension, and mood disorder using International Classification of Diseases, Ninth Revision codes recorded from January 1, 2005, through December 31, 2009, among all adult residents of Olmsted County, Minnesota, on April 1, 2009. For SES measurements, an individual HOUsing-based index of SocioEconomic Status (HOUSES) derived from real property data was used. Logistic regression models were used to examine the association of the prevalence of chronic diseases with ethnicity and HOUSES score and their interaction.ResultsWe identified 88,010 eligible adults with HOUSES scores available, of whom 48,086 (54.6%) were female and 80,699 (91.7%) were non-Hispanic white; the median (interquartile range) age was 45 years (30-58 years). Overall and in the subgroup of non-Hispanic whites, SES measured by HOUSES was inversely associated with the prevalence of all 5 chronic diseases independent of age, sex, and ethnicity (P<.001). While an association of ethnicity with disease prevalence was observed for all the chronic diseases, SES modified the effect of ethnicity for clinically less overt conditions (interaction P<.05 for each condition [diabetes, hypertension, and mood disorder]) but not for coronary heart disease, a clinically more overt condition.ConclusionIn a mixed rural-urban setting with a predominantly non-Hispanic white population, health disparities in chronic diseases still exist across SES. The extent to which SES modifies the effect of ethnicity on the risk of chronic diseases may depend on the nature of the disease.

Project description:Atmospheric particulate matter (PM) is a recognized risk factor for the global burden of disease in human populations. We are presenting here the application of toxicogenomics in the evaluation of the toxic effects of organic content of atmospheric particle matter (PM), from urban and rural environments (city of Barcelona and village of La Pobla, NE Spain), using the developing zebrafish embryo. The main goal is to identify the metabolic pathways involved in the adverse effects observed in zebrafish embryos exposed to PM organic content from urban and rural environments, also allowing the selection of genes of interest that are differentially expressed. The relevance of particle size to the PM toxicity is also addressed. Indeed, the zebrafish embryos were exposed to PM of aerodynamic diameter larger than 7.2 Î¼m and smaller than 0.5 Î¼m (PM10 and PM0.5, respectively). PM0.5 concentrated biological and toxic activities linked to organic substances. Transcriptomic analyses showed strong induction of the AhR signalling pathway (a.k.a. dioxin-like activity) for embryos exposed to both rural and urban extracts, correlating with the concentrations of PAHs. Urban extracts, with strong contribution of traffic emissions, specifically de-regulated oxidative stress-related genes, as well as pancreatic and eye-lens specific genes, two organs known to be affected by air pollution in humans. Exposure to rural extracts, with high contribution of wood burning emissions, affected genes implicated in basic cellular functions, in agreement with their strong embryotoxicity. Extracts from rural and urban samples elicited both common and specific transcriptome responses, suggesting different potentially adverse outcomes depending on PM source and composition. The authors thank the financial support of the Spanish Ministry (project TEA-PARTICLE, grant number CGL2011-29621) and the Portuguese Foundation for Science and Technology for the doctoral grant of Sofia R. Mesquita (SFRH/BD/80710/2011) funded by the Program POPH-QREN through the Portuguese Ministry of Education and Science and the European Social Fund, and support through project PEst-C/MAR/LA0015/2013. The PM filter samples used in the present study were PM10 and PM0.5 from the urban site - total of 4 samples from 2 sampling months; and PM0.5 from the rural site - total of 2 samples from 2 sampling months (PM10 samples from the rural site were not tested due to their very low concentration in organic compounds, and insignificant biological activity, previously measured). Sampling occurred during the cold periods of the year 2012/2013. The organic fraction of PM samples was extracted by sonication using a mixture of dichloromethane:methanol. Then, the extracts were filtered, evaporated and re-dissolved in Dimethyl sulfoxide (DMSO). Zebrafish fertilized eggs were exposed to PM organic extracts (0.2% DMSO) from the urban and rural sites from 24 to 120h post-fertilization. Total RNA was isolated from whole embryos (pools of 20 individuals), using Trizol reagent protocol (Invitrogen Life Technologies, Carlsberg, CA). The microarray study was performed using the Agilent Two-colour D. rerio Oligo Microarray v3 platform, following the Agilent Microarray â?? Based Gene Expression Analysis protocol. Three biological replicates were performed for each PM sample and controls. Biological replicates, a technical replicate and a self-to-self, were simultaneously amplified and labelled using Cyanine 3 (Cy3) and Cyanine 5 (Cy5) dye. After cRNA purification (RNeasy Kit, Quiagen GmbH, Hilden, Germany), the cRNA concentration and labelling were quantified in the NanoDrop spectrophotometer, obtaining incorporation rates in the range of 15-20pmol of cyanide dye/Âµl cRNA and yield values > 0.825ug, as recommended. cRNA was fragmented and hybridized in 4x44K arrays, for 17h at 65oC. After the hybridization the array slides were washed, and immediately scanned using Microarray Scanner Agilent G2505C system. Data was extracted using Agilent Feature Extraction Software v10.5.1.1, and the quality of microarray data was evaluated using the Quality Control report provided by Agilent Software. Based on the microarray data analysis, 22 primers were selected and designed using Primer Express 2.0 software (Applied Biosystems, Foster City, CA). Genes were quantified by real-time PCR to validate the microarray data, and a subset of 13 genes were further selected by their robust behaviour in the validation assays, allowing to differentiate the toxic potential of PM from urban and rural sources.

Dataset Information

Urban/Rural Differences in Breast and Cervical Cancer Incidence: The Mediating Roles of Socioeconomic Status and Provider Density.

Publications

Urban/Rural Differences in Breast and Cervical Cancer Incidence: The Mediating Roles of Socioeconomic Status and Provider Density.

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