The relationship between demands for lung cancer screening and the constructs of health belief model: a cross-sectional survey in Hefei, China.

The aim of investigation is to explore the relationship between demands for lung cancer screening (LCS) and the constructs derived from the health belief model (HBM) in Hefei. The study collected data about socio-demographics, health beliefs in and demands for LCS during early June to later July 2015. By constructing a LCS demands HBM constructs, it calculated indices of demands for LCS (DSI) and HBM constructs, which include perceived risk (PR) and seriousness (PS) of the cancers; and perceived effectiveness (PE), benefits (PB) and difficulties (PD) of the screening. It also performed descriptive and multivariate regression analysis of the demands and the HBM constructs. The amount of 823 respondents participated and completed the survey. 6.4% of them had ever undertaken LCS, whereas 60.1% of them expressed willingness to accept the service of LCS if it is free. In multiple regression analysis which used weights in calculating the HBM construct indices, education displayed significant positive associations with DSI (p = .044), and most of HBM constructs indices (PSI, PRI, PBI, and PDI) were statistically significant with DSI (p < .05). HBM-based constructs regarding LCS have important effects on demands for the service, and may provide effective paths to cancer screening promotion.

Pathways of healthcare and antibiotics use following reported gastrointestinal illness: a cross-sectional study in rural Anhui, China.

OBJECTIVE: To document the factors, and their pathways, that influence healthcare and antibiotics use following reported gastrointestinal illnesses in Anhui province, China. STUDY DESIGN: This study uses cross-sectional design, descriptive statistical analysis, pathway mapping and multivariate logistic regression modelling. SETTING: Households in 12 villages in Anhui province, China. PARTICIPANTS: A total of 3659 residents who: (1) held a registered rural residence and were actually living in the sampled villages when this study was conducted; (2) were aged 18 years and older and (3) were willing to participate and able to answer the survey questions. OUTCOME MEASURES: Planned and measured variables included the occurrence of gastrointestinal illness, professional care seeking and antibiotic use due to the illness and factors influencing these measures. RESULTS: Of the 3659 informants, 29.0% reported gastrointestinal illness episodes in the past year. Of these episodes, 50.2% led to professional care seeking and 65.4% of antibiotic use. Multivariate logistic modelling identifies that: (1) reported gastrointestinal illnesses were more frequent in north compared with middle (OR 0.569, 95% CI 0.472 to 0.686) and south (OR 0.588, 95% CI 0.492 to 0.702) Anhui, and were positively associated with age (B=0.123, p<0.05), knowledge concerning (B=0.248, p<0.05) and practice of (B=0.184, p<0.05) prevention; (2) seeking professional care and antibiotic use following the illness was linked to the severity of symptoms and geographical locations, rather than to specific pathogenic features. CONCLUSIONS: Reported gastrointestinal illnesses are quite prevalent in the sample population and a large proportion of these have resulted in professional care and antibiotics use. The factors associated with the reported illnesses and pathways of healthcare and antibiotic use, as identified in this study, should inform future research and intervention efforts.

Modeling age-specific cancer incidences using logistic growth equations: implications for data collection.

Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year- segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.

Association of risk of gastric cancer and consumption of tobacco, alcohol and tea in the Chinese population.

This study aimed at summarizing epidemiological research findings on associations between tobacco, alcohol and tea consumption and risk of gastric cancer (GC) in the Chinese population. The review searched PubMed, Embase, China National Knowledge Infrastructure (CNKI) and China Biology Medicine (CBM) databases and reference lists of review papers for all studies published in English or Chinese languages. Information extracted, via two independent researchers, from retrieved articles included first author, year of publication, study design, sample size, source of controls and adjusted odds ratio (OR) or relative risk (RR) with the corresponding 95% confidence intervals (CIs) for each category. Statistical analyses used software STATA version 12.0. The systematic search found 89 articles containing 25,821 GC cases and 135,298 non-cases. The overall random effects in terms of pooled OR and 95%CI for tobacco, alcohol and tea consumption were 1.62 (95%CI: 1.50-1.74), 1.57 (95%CI: 1.41-1.76) and 0.67 (95%CI: 0.59-0.76) respectively; while the heterogeneity among included studies ranged from 80.1% to 87.5%. The majority of subgroup analyses revealed consistent results with the overall analyses. All three behavioral factors showed statistically significant dose-dependent effects on GC (P<0.05). The study revealed that tobacco smoking and alcohol drinking were associated with over 1/2 added risk of GC, while tea drinking conferred about 1/3 lower risk of GC in the Chinese population. However, these results should be interpreted with caution given the fact that most of the included studies were based on a retrospective design and heterogeneity among studies was relatively high.

Association between pancreatitis and subsequent risk of pancreatic cancer: a systematic review of epidemiological studies.

This study aimed to summarize published epidemiological evidence for the relationship between pancreatitis and subsequent risk of pancreatic cancer (PC). We searched Medline and Embase for epidemiological studies published by February 5th, 2014 examining the risk of PC in pancreatitis patients using highly inclusive algorithms. Information about first author, year of publication, country of study, recruitment period, type of pancreatitis, study design, sample size, source of controls and attained age of subjects were extracted by two researchers and Stata 11.0 was used to perform the statistical analyses and examine publication bias. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated with the random effects model. A total of 17 articles documenting 3 cohort and 14 case-control studies containing 14,667 PC cases and 17,587 pancreatitis cases were included in this study. The pooled OR between pancreatitis and PC risk was 7.05 (95%CI: 6.42-7.75). However, the pooled ORs of case-control and cohort studies were 4.62 (95%CI: 4.08-5.22) and 16.3 (95%CI: 14.3-18.6) respectively. The risk of PC was the highest in patients with chronic pancreatitis (pooled OR=10.35; 95%CI: 9.13-11.75), followed by unspecified type of pancreatitis (pooled OR=6.41; 95%CI: 4.93-8.34), both acute and chronic pancreatitis (pooled OR=6.13; 95%CI: 5.00-7.52), and acute pancreatitis (pooled OR=2.12; 95%CI: 1.59-2.83). The pooled OR of PC in pancreatitis cases diagnosed within 1 year was the highest (pooled OR=23.3; 95%CI: 14.0-38.9); and the risk in subjects diagnosed with pancreatitis for no less than 2, 5 and 10 years were 3.03 (95%CI: 2.41-3.81), 2.82 (95%CI: 2.12-3.76) and 2.25 (95%CI: 1.59-3.19) respectively. Pancreatitis, especially chronic pancreatitis, was associated with a significantly increased risk of PC; and the risk decreased with increasing duration since diagnosis of pancreatitis.

Refining and validating a two-stage and web-based cancer risk assessment tool for village doctors in China.

The big gap between efficacy of population level prevention and expectations due to heterogeneity and complexity of cancer etiologic factors calls for selective yet personalized interventions based on effective risk assessment. This paper documents our research protocol aimed at refining and validating a two-stage and web- based cancer risk assessment tool, from a tentative one in use by an ongoing project, capable of identifying individuals at elevated risk for one or more types of the 80% leading cancers in rural China with adequate sensitivity and specificity and featuring low cost, easy application and cultural and technical sensitivity for farmers and village doctors. The protocol adopted a modified population-based case control design using 72, 000 non-patients as controls, 2, 200 cancer patients as cases, and another 600 patients as cases for external validation. Factors taken into account comprised 8 domains including diet and nutrition, risk behaviors, family history, precancerous diseases, related medical procedures, exposure to environment hazards, mood and feelings, physical activities and anthropologic and biologic factors. Modeling stresses explored various methodologies like empirical analysis, logistic regression, neuro-network analysis, decision theory and both internal and external validation using concordance statistics, predictive values, etc..