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      Mortality Trends in Colorectal Cancer in China During 2000–2015: A Joinpoint Regression and Age-Period-Cohort Analysis

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          Abstract

          Introduction

          As lifestyles have increasingly become westernized in China, public health strategies have increasingly focused on cancer prevention. The objective of this study was to describe trends in colorectal cancer (CRC) mortality and the age, period, and cohort effects of CRC mortality in urban and rural China from 2000 to 2015.

          Methods

          We collected CRC mortality data from the China Health Statistics Yearbook. We used joinpoint regression analysis to estimate the slope of mortality trends. We then used the age-period-cohort (APC) model with intrinsic estimator to estimate the age, period, and cohort effects of CRC mortality.

          Results

          CRC mortality was higher in urban areas than in rural areas, and the average annual percentage change was also larger in urban areas (4.1%) than in rural areas (3.7%). CRC mortality risk was higher among older adults than among adults aged 20 to 24: the relative risk among adults aged 60 to 64 was 31.09 times higher in urban China and 11.46 times higher in rural China. CRC mortality risk increased with period: compared with period 2000, the relative risk was 1.01 in period 2005, 1.36 in period 2010, and 1.42 in period 2015 in urban China and 1.12 in period 2005, 1.24 in period 2010, and 1.69 in period 2015 in rural China. More recent cohorts had lower CRC mortality risk: compared with the cohort born during 1920–1924, the relative risk of cohort 1950–1954 was 0.70 in urban China and 0.69 in rural China.

          Conclusion

          More interventions to reduce the burden of CRC should be conducted, and it is more necessary for older people and urban residents to adopt a healthy lifestyle in China.

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          Most cited references17

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          Permutation tests for joinpoint regression with applications to cancer rates.

          The identification of changes in the recent trend is an important issue in the analysis of cancer mortality and incidence data. We apply a joinpoint regression model to describe such continuous changes and use the grid-search method to fit the regression function with unknown joinpoints assuming constant variance and uncorrelated errors. We find the number of significant joinpoints by performing several permutation tests, each of which has a correct significance level asymptotically. Each p-value is found using Monte Carlo methods, and the overall asymptotic significance level is maintained through a Bonferroni correction. These tests are extended to the situation with non-constant variance to handle rates with Poisson variation and possibly autocorrelated errors. The performance of these tests are studied via simulations and the tests are applied to U.S. prostate cancer incidence and mortality rates. Copyright 2000 John Wiley & Sons, Ltd.
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            Maternal nutrition and birth outcomes.

            In this review, the authors summarize current knowledge on maternal nutritional requirements during pregnancy, with a focus on the nutrients that have been most commonly investigated in association with birth outcomes. Data sourcing and extraction included searches of the primary resources establishing maternal nutrient requirements during pregnancy (e.g., Dietary Reference Intakes), and searches of Medline for "maternal nutrition"/[specific nutrient of interest] and "birth/pregnancy outcomes," focusing mainly on the less extensively reviewed evidence from observational studies of maternal dietary intake and birth outcomes. The authors used a conceptual framework which took both primary and secondary factors (e.g., baseline maternal nutritional status, socioeconomic status of the study populations, timing and methods of assessing maternal nutritional variables) into account when interpreting study findings. The authors conclude that maternal nutrition is a modifiable risk factor of public health importance that can be integrated into efforts to prevent adverse birth outcomes, particularly among economically developing/low-income populations.
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              China's human resources for health: quantity, quality, and distribution.

              In this paper, we analyse China's current health workforce in terms of quantity, quality, and distribution. Unlike most countries, China has more doctors than nurses-in 2005, there were 1.9 million licensed doctors and 1.4 million nurses. Doctor density in urban areas was more than twice that in rural areas, with nurse density showing more than a three-fold difference. Most of China's doctors (67.2%) and nurses (97.5%) have been educated up to only junior college or secondary school level. Since 1998 there has been a massive expansion of medical education, with an excess in the production of health workers over absorption into the health workforce. Inter-county inequality in the distribution of both doctors and nurses is very high, with most of this inequality accounted for by within-province inequalities (82% or more) rather than by between-province inequalities. Urban-rural disparities in doctor and nurse density account for about a third of overall inter-county inequality. These inequalities matter greatly with respect to health outcomes across counties, provinces, and strata in China; for instance, a cross-county multiple regression analysis using data from the 2000 census shows that the density of health workers is highly significant in explaining infant mortality.
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                Author and article information

                Journal
                Prev Chronic Dis
                Prev Chronic Dis
                PCD
                Preventing Chronic Disease
                Centers for Disease Control and Prevention
                1545-1151
                2018
                13 December 2018
                : 15
                : E156
                Affiliations
                [1 ]Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, China
                [2 ]Global Health Institute, Wuhan University, Wuhan, China
                [3 ]Global Health Research Center, Duke Kunshan University, Kunshan, China
                [4 ]Duke Global Health Institute, Duke University, Durham, North Carolina
                Author notes
                Corresponding Author: Hao Xiang, PhD, Department of Global Health, School of Health Sciences, Wuhan University, 115# Donghu Rd, Wuhan, 430071, China. Telephone: +86-027-68759118. Email: xianghao@ 123456whu.edu.cn
                Article
                18_0329
                10.5888/pcd15.180329
                6307832
                30576278
                aa9a384c-7271-4bff-b2f8-9ad30099f1c0
                History
                Categories
                Original Research
                Peer Reviewed

                Health & Social care
                Health & Social care

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