Eating habits and risk of esophageal cancers: a population-based case–control study

Objective  

Eating behaviors, such as the timing, speed of eating, and frequently consuming hot drinks, fried, spicy, or barbecued foods may be associated with increased risks of esophageal cancer. We analyzed data from a population-based case–control study to examine whether eating behaviors are associated with risk of esophageal cancer.     

Long-term increase in sunscreen use in an Australian community after a skin cancer prevention trial

BACKGROUND: Given the public health burden of skin cancer in white populations, an increase in sun protective behavior is needed. In a high-risk community, we assessed long-term sunscreen use among people who had participated in a randomized trial of daily sunscreen application for prevention of skin cancer. METHODS: In 1992, 1621 residents of the subtropical Australian township of Nambour were randomly allocated to either daily or discretionary sunscreen use until 1996. From 1997 to 2002, we monitored by questionnaires their ongoing sunscreen use. RESULTS: People who had never or irregularly used sunscreen when in summer sun before the trial were more likely (P < 0.0001) to be sustaining regular application especially to their face (20% vs. 11%) and forearms (14% vs. 5%) if they had been allocated to daily, not discretionary, use of sunscreen for 5 years. CONCLUSIONS: Regular voluntary sunscreen use for skin cancer prevention can be sustained by sun-sensitive people in the long term. Habit formation appears to be an important goal for sun protection programs among those living, or on vacation, in sunny places.     

Risk of attrition in a longitudinal study of skin cancer: logistic and survival models can give different results

ObjectivesLongitudinal studies are a major tool for public health research, but their value can be undermined by attrition. Identification of factors associated with attrition through modeling depends on the efficient use of data and is conditional on modeling assumptions being met. The primary aim of this study was to compare the performance of four models in analyzing attrition risk.Study Design and SettingData from participants who were lost to follow-up from The Nambour Skin Cancer Study between 1992 and 2000 were analyzed using logistic and survival models, for all-cause and nondeath attritions.ResultsDuring follow-up, 321 (19.8%) of 1,621 participants were lost to follow-up; 70 (4.3%) because of death and 251 (15.5%) for other reasons. Using survival models showed skin cancer diagnosis to be associated with increased all-cause attrition (hazard ratio: 2.3; 95% confidence interval [95% CI]: 1.5, 3.4) and nondeath attrition (subhazard ratio: 1.9; 95% CI: 1.0, 3.3). Using logistic regression resulted in inverse associations being observed for both all-cause attrition (odds ratio [OR]: 0.7; 95% CI: 0.5, 1.1) and nondeath attrition (OR: 0.5; 95% CI: 0.3, 1.0).ConclusionThese results demonstrate the relative inadequacy of a logistic as opposed to a survival approach when analyzing attrition risk in the presence of time-varying covariates and multiple timepoints.     

Use of support services in a sample of patients with high‐risk primary melanomas in urban,regional and rural Queensland

Objective: To characterise use of support services in patients diagnosed with high‐risk primary melanoma by their location of residence. Methods: In a cross‐sectional study of 787 patients with histologically‐confirmed clinical stage 1B‐2 melanoma, we estimated odds ratios (ORs) using regression models to assess the association of support service use with residence in rural, regional or urban areas. We also evaluated demographic and clinical correlates of support service use. Results: Among 113 rural patients, 33 (29%) used support services around time of diagnosis compared to 88 (39%) of 224 regional participants and 164 of 448 (37%) urban participants. Regional participants more commonly used support services compared to rural participants (OR 1.84; CI 1.09–3.10), but there was no association with urban versus rural residence (OR 1.32; CI 0.82–2.13). As well, females (OR 1.58; CI 1.15–2.18), those <65 years (OR 1.96; CI 1.42–2.71), or with higher education (OR 2.30; CI 1.53–3.44), or those with T‐stage 4B (OR 2.69; CI 1.36–5.32) were more likely to use support services than other patients. Conclusion: Use of support services is lower among rural patients and other sub‐groups of primary melanoma patients who have poorer prognoses than others. Implications for public health: Appropriate triage to support services is required for rural and other vulnerable patient groups to ensure optimal patient care.     

Regression to the mean: what it is and how to deal with it

BACKGROUND: Regression to the mean (RTM) is a statistical phenomenon that can make natural variation in repeated data look like real change. It happens when unusually large or small measurements tend to be followed by measurements that are closer to the mean. METHODS: We give some examples of the phenomenon, and discuss methods to overcome it at the design and analysis stages of a study. RESULTS: The effect of RTM in a sample becomes more noticeable with increasing measurement error and when follow-up measurements are only examined on a sub-sample selected using a baseline value. CONCLUSIONS: RTM is a ubiquitous phenomenon in repeated data and should always be considered as a possible cause of an observed change. Its effect can be alleviated through better study design and use of suitable statistical methods.