Cancers Attributable to Infections in the US in 2017: A Meta-Analysis

Importance

Infections are largely modifiable causes of cancer. However, there remains untapped potential for preventing and treating carcinogenic infections in the US.

Objective

To estimate the percentage and number of incident cancers attributable to infections in the US among adults and children for the most recent year cancer incidence data were available (2017).

Data Sources

A literature search from 1946 onward was performed in MEDLINE on January 6, 2023, to obtain the data required to calculate population attributable fractions for 31 infection-cancer pairs. National Health and Nutrition Examination Survey data were used to estimate the population prevalence of hepatitis B and C viruses and Helicobacter pylori.

Study Selection

Studies conducted in the US or other Western countries were selected according to specific infection-cancer criteria.

Data Extraction and Synthesis

Data from 128 studies were meta-analyzed to obtain the magnitude of an infection-cancer association or prevalence of the infection within cancer cells.

Main Outcomes and Measures

The proportion of cancer incidence attributable to 8 infections.

Results

Of the 1 666 102 cancers diagnosed in 2017 among individuals aged 20 years or older in the US, 71 485 (4.3%; 95% CI, 3.1%-5.3%) were attributable to infections. Human papillomavirus (n = 38 230) was responsible for the most cancers, followed by H pylori (n = 10 624), hepatitis C virus (n = 9006), Epstein-Barr virus (n = 7581), hepatitis B virus (n = 2310), Merkel cell polyomavirus (n = 2000), Kaposi sarcoma-associated herpesvirus (n = 1075), and human T-cell lymphotropic virus type 1 (n = 659). Cancers with the most infection-attributable cases were cervical (human papillomavirus; n = 12 829), gastric (H pylori and Epstein-Barr virus; n = 12 565), oropharynx (human papillomavirus; n = 12 430), and hepatocellular carcinoma (hepatitis B and C viruses; n = 10 017). The burden of infection-attributable cancers as a proportion of total cancer incidence ranged from 9.6% (95% CI, 9.2%-10.0%) for women aged 20 to 34 years to 3.2% (95% CI, 2.4%-3.8%) for women aged 65 years or older and from 6.1% (95% CI, 5.2%-7.0%) for men aged 20 to 34 years to 3.3% (95% CI, 1.9%-4.4%) for men aged 65 years or older. Among those aged 19 years or younger, 2.2% (95% CI, 1.3%-3.0%) of cancers diagnosed in 2017 were attributable to Epstein-Barr virus.

Conclusions and Relevance

Infections were estimated to be responsible for 4.3% of cancers diagnosed among adults in the US in 2017 and, therefore, represent an important target for cancer prevention efforts.

Design and analysis of factorial clinical trials: The impact of one treatment's effectiveness on the statistical power and required sample size of the other

Factorial trials allow for the simultaneous evaluation of more than one treatment, by randomizing patients to their possible combinations, including control. However, the statistical power of one treatment can be influenced by the effectiveness of the other, a matter that has not been widely recognized. In this paper, we evaluate the relationship between the observed effectiveness of one treatment and the implied power for a second treatment in the same trial, under a range of conditions. We provide analytic and numerical solutions for a binary outcome, under the additive, multiplicative, and odds ratio scales for treatment interaction. We demonstrate how the minimum required sample size for a trial depends on the two treatment effects. Relevant factors include the event rate in the control group, sample size, treatment effect sizes, and Type-I error rate thresholds. We show that that power for one treatment decreases as a function of the observed effectiveness of the other treatment if there is no multiplicative interaction. A similar pattern is observed with the odds ratio scale at low control rates, but at high control rates, power may increase if the first treatment is moderately more effective than its planned value. When treatments do not interact additively, power may either increase or decrease, depending on the control event rate. We also determine where the maximum power occurs for the second treatment. We illustrate these ideas with data from two actual factorial trials. These results can benefit investigators in planning the analysis of factorial clinical trials, in particular, to alert them to the potential for losses in power when one observed treatment effect differs from its originally postulated value. Updating the power calculation and modifying the associated required sample size can then ensure sufficient power for both treatments.

Taking a chance: How likely am I to receive my preferred treatment in a clinical trial?

Researchers should ideally conduct clinical trials under a presumption of clinical equipoise, but in fact trial patients will often prefer one or other of the treatments being compared. Receiving an unblinded preferred treatment may affect the study outcome, possibly beneficially, but receiving a non-preferred treatment may induce 'reluctant acquiescence', and poorer outcomes. Even in blinded trials, patients' primary motivation to enrol may be the chance of potentially receiving a desirable experimental treatment, which is otherwise unavailable. Study designs with a higher probability of receiving a preferred treatment (denoted as 'concordance') will be attractive to potential participants, and investigators, because they may improve recruitment and hence enhance study efficiency. Therefore, it is useful to consider the concordance rates associated with various study designs. We consider this question with a focus on comparing the standard, randomised, two-arm, parallel group design with the two-stage randomised patient preference design and Zelen designs; we also mention the fully randomised and partially randomised patient preference designs. For each of these designs, we evaluate the concordance rate as a function of the proportions randomised to the alternative treatments, the distribution of preferences over treatments, and (for the Zelen designs) the proportion of patients who consent to receive their assigned treatment. We also examine the equity of each design, which we define as the similarity between the concordance rates for participants with different treatment preferences. Finally, we contrast each of the alternative designs with the standard design in terms of gain in concordance and change in equity.

A method was developed for correcting the bias in the usual study weights in meta-analyses

OBJECTIVES

Our goal was to evaluate the bias in the usual method of estimating study weights in a meta-analysis and to develop a suitable bias correction.

STUDY DESIGN AND SETTING

In meta-analyses, it is standard practice to weight studies by the inverse variance of their treatment effects. Weights are usually calculated by taking reciprocals of the estimated variances, but we show that this approach is biased. We established an exact expression for the bias with continuous data, yielding a correction factor for the study weights that yields improved estimation of the treatment effect.

RESULTS

With the usual method, the weight for each study is always overestimated, particularly with small samples; also, the variance of the summary treatment effect is underestimated. Our correction yields an unbiased estimate of the summary treatment effect with minimum variance. We illustrate the bias numerically for various scenarios and show how it can substantially affect actual meta-analyses in practice.

CONCLUSION

We recommend that the standard method of obtaining study weights should be modified by our bias correction factor. Our method is simple and straightforward to apply. Elimination of this bias will enhance the validity of conclusions from a meta-analysis, compared with the situation when the standard weights are used.

Unified approach to optimal estimation of mean and standard deviation from sample summaries

Recently, various methods have been developed to estimate the sample mean and standard deviation when only the sample size, and other selected sample summaries are reported. In this paper, we provide a unified approach to optimal estimation that can be easily adopted when only some summary statistics are reported. We show that the proposed estimators have the lowest variance among linear unbiased estimators. We also show that in the most commonly reported cases, that is, when only a three-number or five-number summary is reported, the newly proposed estimators match the previously developed estimators. Finally, we demonstrate the performance of the estimators numerically.

The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI’s application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act swiftly and thereby enhance containment of outbreaks.

Estimation of standard deviations and inverse-variance weights from an observed range

A variety of methods have been proposed to estimate a standard deviation, when only a sample range has been observed or reported. This problem occurs in the interpretation of individual clinical studies that are incompletely reported, and also in their incorporation into meta-analyses. The methods differ with respect to their focus being either on the standard deviation in the underlying population or on the particular sample in hand, a distinction that has not been widely recognized. In this article, we contrast and compare various estimators of these two quantities with respect to bias and mean squared error, for normally distributed data. We show that unbiased estimators are available for either quantity, and recommend our preferred methods. We also propose a Taylor series method to obtain inverse-variance weights, for samples where only the sample range is available; this method yields very little bias, even for quite small samples. In contrast, the naïve approach of simply taking the inverse of an estimated variance is shown to be substantially biased, and can place unduly large weight on small samples, such as small clinical trials in a meta-analysis. Accordingly, this naïve (but commonly used) method is not recommended.

Impact of centre volume, surgeon volume, surgeon experience and geographic location on reoperation after intramedullary nailing of tibial shaft fractures

Background:

Tibial shaft fractures are the most common long-bone injury, with a reported annual incidence of more than 75 000 in the United States. This study aimed to determine whether patients with tibial fractures managed with intramedullary nails experience a lower rate of reoperation if treated at higher-volume hospitals, or by higher-volume or more experienced surgeons.

Methods:

The Study to Prospectively Evaluate Reamed Intramedullary Nails in Patients with Tibial Fractures (SPRINT) was a multicentre randomized clinical trial comparing reamed and nonreamed intramedullary nailing on rates of reoperation to promote fracture union, treat infection or preserve the limb in patients with open and closed fractures of the tibial shaft. Using data from SPRINT, we quantified centre and surgeon volumes into quintiles. We performed analyses adjusted for type of fracture (open v. closed), type of injury (isolated v. multitrauma), gender and age for the primary outcome of reoperation using multivariable logistic regression.

Results:

There were no significant differences in the odds of reoperation between high- and low-volume centres (p = 0.9). Overall, surgeon volume significantly affected the odds of reoperation (p = 0.03). The odds of reoperation among patients treated by moderate-volume surgeons were 50% less than those among patients treated by very-low-volume surgeons (odds ratio [OR] 0.50, 95% confidence interval [CI] 0.28–0.88), and the odds of reoperation among patients treated by high-volume surgeons were 47% less than those among patients treated by very-low-volume surgeons (OR 0.53, 95% CI 0.30–0.93).

Conclusion:

There appears to be no significant additional patient benefit in treatment by a higher-volume centre for intramedullary fixation of tibial shaft fractures. Additional research on the effects of surgical and clinical site volume in tibial shaft fracture management is needed to confirm this finding. The odds of reoperation were higher in patients treated by very-low-volume surgeons; this finding may be used to optimize the results of tibial shaft fracture management.

Clinical trial registration:

ClinicalTrials.gov, NCT00038129

Simulation study on the validity of the average risk approach in estimating population attributable fractions for continuous exposures

BACKGROUND

The population attributable fraction (PAF) is an important metric for estimating disease burden associated with causal risk factors. In an International Agency for Research on Cancer working group report, an approach was introduced to estimate the PAF using the average of a continuous exposure and the incremental relative risk (RR) per unit. This 'average risk' approach has been subsequently applied in several studies conducted worldwide. However, no investigation of the validity of this method has been done.

OBJECTIVE

To examine the validity and the potential magnitude of bias of the average risk approach.

METHODS

We established analytically that the direction of the bias is determined by the shape of the RR function. We then used simulation models based on a variety of risk exposure distributions and a range of RR per unit. We estimated the unbiased PAF from integrating the exposure distribution and RR, and the PAF using the average risk approach. We examined the absolute and relative bias as the direct and relative difference in PAF estimated from the two approaches. We also examined the bias of the average risk approach using real-world data from the Canadian Population Attributable Risk of Cancer study.

RESULTS

The average risk approach involves bias, which is underestimation or overestimation with a convex or concave RR function (a risk profile that increases more/less rapidly at higher levels of exposure). The magnitude of the bias is affected by the exposure distribution as well as the value of RR. This approach is approximately valid when the RR per unit is small or the RR function is approximately linear. The absolute and relative bias can both be large when RR is not small and the exposure distribution is skewed.

CONCLUSIONS

We recommend that caution be taken when using the average risk approach to estimate PAF.

Estimation of diagnostic test accuracy: A "Rule of Three" for data with repeated observations but without a gold standard

This article considers how to estimate the accuracy of a diagnostic test when there are repeated observations, but without the availability of a gold standard or reference test. We identify conditions under which the structure of the observed data is rich enough to provide sufficient degrees of freedom, such that a suitable latent class model can be fitted with identifiable accuracy parameters. We show that a Rule of Three applies, specifying that accuracy can be evaluated as long as there are at least three observations per individual with the given test. This rule also applies if the three observations arise from combinations of different test methods, or from a sequential design in which individuals are tested for a maximum number of times with the same test but stopping if a positive (or negative) result occurs. The rule pertains to tests having an arbitrary number of response categories. Accuracy is evaluated by parameters reflecting rates of misclassification among the response categories, and the model also provides estimates of the underlying distribution of the true disease state. These ideas are illustrated by data from two medical studies. Issues discussed include the advantages and disadvantages of analyzing the response variable as binary or multinomial, as well as the feasibility of testing goodness of fit when the model incorporates a large number of parameters. Comparisons are possible between models that do or do not assume equal accuracy rates for the observations, and between models where certain misclassification parameters are or are not assumed to be zero.

Estimating the future cancer management costs attributable to modifiable risk factors in Canada

OBJECTIVES

An estimated 33-37% of incident cancers in Canada are attributable to modifiable risk factors. Interventions targeting these risk factors would minimize the substantial health and economic burdens Canadians face due to cancer. We estimate the future health and economic burden of cancer in Canada by incorporating data from the Canadian Population Attributable Risk of Cancer (ComPARe) study into OncoSim, a web-based microsimulation tool.

METHODS

Using the integrated OncoSim population attributable risk and population impact measures, we evaluated risk factor-targeted intervention scenarios implemented in 2020, assuming the targeted risk factor prevalence reduction would be achieved by 2032 with a 12-year latency period.

RESULTS

We estimate that smoking will be the largest contributor to cancer-related costs, with a cost of CAD $44.4 billion between 2032 and 2044. An estimated CAD $3.3 billion of the cost could be avoided with a 30% reduction in smoking prevalence by 2022. Following smoking, the next highest cancer management costs are associated with inadequate physical activity and excess body weight, accounting for CAD $10.7 billion ($2.7 billion avoidable) and CAD $9.8 billion ($3.2 billion avoidable), respectively. Avoidable costs for other risk factors range from CAD $90 million to CAD $2.5 billion.

CONCLUSION

Interventions targeting modifiable cancer risk factors could prevent a substantial number of incident cancer cases and billions of dollars in cancer management costs. With limited budgets and rising costs in cancer care in Canada, these simulation models and results are valuable for researchers and policymakers to inform decisions and prioritize and evaluate intervention programs.

Shifting the focus away from binary thinking of statistical significance and towards education for key stakeholders: revisiting the debate on whether it's time to de-emphasize or get rid of statistical significance

There has been a long-standing controversy among scientists regarding the appropriate use of P-values and statistical significance in clinical research. This debate has resurfaced through recent calls to modify the threshold of P-value required to declare significance, or to retire statistical significance entirely. In this article, we revisit the issue by discussing: i) the connection between statistical thinking and evidence-based practice; ii) some history of statistical significance and P-values; iii) some practical challenges with statistical significance or P-value thresholds in clinical research; iv) the on-going debate on what to do with statistical significance; v) suggestions to shift the focus away from binary thinking of statistical significance and towards education for key stakeholders on research essentials including statistical thinking, critical thinking, good reporting, basic clinical research concepts and methods, and more. We then conclude with remarks and illustrations of the potential deleterious public health consequences of poor methods including selective choice of analysis approach and misguided reliance on binary use of P-values to report and interpret scientific findings.

Incorporating Portfolio Uncertainty in Decision Rules for Healthcare Resource Allocation

Cost-effectiveness analysis is widely adopted as a means to inform policy and decision makers in setting priorities for healthcare resource allocation. In resource-constrained settings, decision makers are confronted with healthcare resource reallocation decisions, e.g., moving funds from one or more existing healthcare programs to fund new healthcare programs. The decision-making plane (DMP) has been developed as a means to graphically present the results of reallocating available healthcare resources when healthcare program costs and effects are uncertain. Mapping a value function over the DMP allows the analyst to value all possible combinations of net costs and net effects that may result from reallocating available healthcare resources under conditions of uncertainty. In this paper, we extend this approach to include a change in portfolio risk, stemming from a change in the portfolios of funded healthcare programs, as an additional source of uncertainty, and demonstrate how this can be incorporated into the value function over net costs and net effects for a risk-averse decision maker. The methodology presented in this paper is of particular interest to decision makers who are risk averse, as it will help to better incorporate their preferences in the process of deciding how to best allocate scarce healthcare resources.

Effects of health literacy, screening, and participant choice on action plans for reducing unhealthy snacking in Australia: A randomised controlled trial

BACKGROUND

Low health literacy is associated with poorer health outcomes. A key strategy to address health literacy is a universal precautions approach, which recommends using health-literate design for all health interventions, not just those targeting people with low health literacy. This approach has advantages: Health literacy assessment and tailoring are not required. However, action plans may be more effective when tailored by health literacy. This study evaluated the impact of health literacy and action plan type on unhealthy snacking for people who have high BMI or type 2 diabetes (Aim 1) and the most effective method of action plan allocation (Aim 2).

METHODS AND FINDINGS

We performed a 2-stage randomised controlled trial in Australia between 14 February and 6 June 2019. In total, 1,769 participants (mean age: 49.8 years [SD = 11.7]; 56.1% female [n = 992]; mean BMI: 32.9 kg/m2 [SD = 8.7]; 29.6% self-reported type 2 diabetes [n = 523]) were randomised to 1 of 3 allocation methods (random, health literacy screening, or participant selection) and 1 of 2 action plans to reduce unhealthy snacking (standard versus literacy-sensitive). Regression analysis evaluated the impact of health literacy (Newest Vital Sign [NVS]), allocation method, and action plan on reduction in self-reported serves of unhealthy snacks (primary outcome) at 4-week follow-up. Secondary outcomes were perceived extent of unhealthy snacking, difficulty using the plans, habit strength, and action control. Analyses controlled for age, level of education, language spoken at home, diabetes status, baseline habit strength, and baseline self-reported serves of unhealthy snacks. Average NVS score was 3.6 out of 6 (SD = 2.0). Participants reported consuming 25.0 serves of snacks on average per week at baseline (SD = 28.0). Regarding Aim 1, 398 participants in the random allocation arm completed follow-up (67.7%). On average, people scoring 1 SD below the mean for health literacy consumed 10.0 fewer serves per week using the literacy-sensitive action plan compared to the standard action plan (95% CI: 0.05 to 19.5; p = 0.039), whereas those scoring 1 SD above the mean consumed 3.0 fewer serves using the standard action plan compared to the literacy-sensitive action plan (95% CI: -6.3 to 12.2; p = 0.529), although this difference did not reach statistical significance. In addition, we observed a non-significant action plan × health literacy (NVS) interaction (b = -3.25; 95% CI: -6.55 to 0.05; p = 0.054). Regarding Aim 2, 1,177 participants across the 3 allocation method arms completed follow-up (66.5%). There was no effect of allocation method on reduction of unhealthy snacking, including no effect of health literacy screening compared to participant selection (b = 1.79; 95% CI: -0.16 to 3.73; p = 0.067). Key limitations include low-moderate retention, use of a single-occasion self-reported primary outcome, and reporting of a number of extreme, yet plausible, snacking scores, which rendered interpretation more challenging. Adverse events were not assessed.

CONCLUSIONS

In our study we observed nominal improvements in effectiveness of action plans tailored to health literacy; however, these improvements did not reach statistical significance, and the costs associated with such strategies compared with universal precautions need further investigation. This study highlights the importance of considering differential effects of health literacy on intervention effectiveness.

TRIAL REGISTRATION

Australia and New Zealand Clinical Trial Registry ACTRN12618001409268.

Relative efficiencies of alternative preference-based designs for randomised trials

Recent work has shown that outcomes in clinical trials can be affected by which treatment the trial participants would select if they were allowed to do so, and if they do or do not actually receive that treatment. These influences are known as selection and preference effects, respectively. Unfortunately, they cannot be evaluated in conventional, parallel group trials because patient preferences remain unknown. However, several alternative designs have been proposed, to measure and take account of patient preferences. In this paper, we discuss three preference-based designs (the two-stage, fully randomised, and partially randomised designs). In conventional trials, only the treatment effect is estimable, while the preference-based designs have the potential to estimate some or all of the selection and preference effects. The relative efficiency of these designs is affected by several factors, including the proportion of participants who are undecided about treatments, or who are unable or unwilling to state a preference; the relative preference rate between the treatments being compared, among patients who do have a preference; and the ratio of patients randomised to each treatment. We also discuss the advantages and disadvantages of these designs under different scenarios.

Age-standardized cancer-incidence trends in Canada, 1971-2015

BACKGROUND

Although cancer incidence over time is well documented in Canada, trends by birth cohort and age group are less well known. We analyzed age- and sex-standardized incidence trends in Canada for 16 major cancer sites and all cancers combined.

METHODS

We obtained nationally representative population-based cancer incidence data in Canada between 1971 and 2015 from the National Cancer Incidence Reporting System (1969-1992) and the Canadian Cancer Registry (1992-2015). We analyzed cancer-incidence trends, reported as annual percent change (APC) for each 10-year group from age 20 to 89 years. We also estimated age-adjusted incidence rate ratios from fitted birth cohort models.

RESULTS

Across most age categories, the most recent trends show significant decreases in the incidence of cervical (APC -8.8% to -0.33%), lung (men: -7.42% to -0.36%; women: -6.27% to 1.07%), bladder (women: -4.12% to -0.07%; men: -5.13% to -0.38%) and prostate cancer (-11.11% to -1.11%). Significant increasing trends were observed for kidney, thyroid and uterine cancers. Overall incidence has increased among both sexes younger than 50 years of age, with recent increases in pancreatic cancer among men, breast cancer among women and colorectal cancer among both sexes. From the birth cohort analysis, we observed increasing trends in colorectal, liver and prostate cancers among men; kidney cancer and melanoma among women; and thyroid cancer among both sexes. We observed decreasing trends in cervical and ovarian cancers, and in bladder and lung cancers among men.

INTERPRETATION

Cancer incidence is decreasing at many sites targeted by primary-prevention efforts, such as smoking cessation and screening programs. Substantial increases in incidence among younger populations are driven by cancers possibly associated with obesity.

A systematic survey of randomised trials that stopped early for reasons of futility

Background

Randomised trial protocols may incorporate interim analyses, with the potential to stop the study for futility if early data show insufficient promise of a treatment benefit. Previously, we have shown that this approach will theoretically lead to mis-estimation of the treatment effect. We now wished to ascertain the importance of this phenomenon in practice.

Methods

We reviewed the methods and results in a set of trials that had stopped for futility, identified through an extensive literature search. We recorded clinical areas, interventions, study design, outcomes, trial setting, sponsorship, planned and actual treatment effects, sample sizes; power; and if there was a data safety monitoring board, or a published protocol. We identified: if interim analyses were pre-specified, and how many analyses actually occurred; what pre-specified criteria might define futility; if a futility analysis formed the basis for stopping; who made the decision to stop; and the conditional power of each study, i.e. the probability of statistically significant results if the study were to continue to its complete sample size.

Results

We identified 52 eligible trials, covering many clinical areas. Most trials had multiple centres, tested drugs, and 40% were industry sponsored. There were 75% where at least one interim analysis was planned a priori; a majority had only one interim analysis, typically with about half the target total sample size. A majority of trials did not pre-define a stopping rule, and a variety of reasons were given for stopping. Few studies calculated and reported low conditional power to justify the early stop. When conditional power could be calculated, it was typically low, especially under the current trend hypothesis. However, under the original design hypothesis, a few studies had relatively high conditional power. Data collection often continued after the interim analysis.

Conclusions

Although other factors will typically be involved, we conclude that, from the perspective of conditional power, stopping early for futility was probably reasonable in most cases, but documentation of the basis for stopping was often missing or vague. Interpretation of truncated trials would be enhanced by improved reporting of stopping protocols, and of their actual execution.

Total Hip Arthroplasty or Hemiarthroplasty for Hip Fracture

BACKGROUND

Globally, hip fractures are among the top 10 causes of disability in adults. For displaced femoral neck fractures, there remains uncertainty regarding the effect of a total hip arthroplasty as compared with hemiarthroplasty.

METHODS

We randomly assigned 1495 patients who were 50 years of age or older and had a displaced femoral neck fracture to undergo either total hip arthroplasty or hemiarthroplasty. All enrolled patients had been able to ambulate without the assistance of another person before the fracture occurred. The trial was conducted in 80 centers in 10 countries. The primary end point was a secondary hip procedure within 24 months of follow-up. Secondary end points included death, serious adverse events, hip-related complications, health-related quality of life, function, and overall health end points.

RESULTS

The primary end point occurred in 57 of 718 patients (7.9%) who were randomly assigned to total hip arthroplasty and 60 of 723 patients (8.3%) who were randomly assigned to hemiarthroplasty (hazard ratio, 0.95; 95% confidence interval [CI], 0.64 to 1.40; P = 0.79). Hip instability or dislocation occurred in 34 patients (4.7%) assigned to total hip arthroplasty and 17 patients (2.4%) assigned to hemiarthroplasty (hazard ratio, 2.00; 99% CI, 0.97 to 4.09). Function, as measured with the total Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score, pain score, stiffness score, and function score, modestly favored total hip arthroplasty over hemiarthroplasty. Mortality was similar in the two treatment groups (14.3% among the patients assigned to total hip arthroplasty and 13.1% among those assigned to hemiarthroplasty, P = 0.48). Serious adverse events occurred in 300 patients (41.8%) assigned to total hip arthroplasty and in 265 patients (36.7%) assigned to hemiarthroplasty.

CONCLUSIONS

Among independently ambulating patients with displaced femoral neck fractures, the incidence of secondary procedures did not differ significantly between patients who were randomly assigned to undergo total hip arthroplasty and those who were assigned to undergo hemiarthroplasty, and total hip arthroplasty provided a clinically unimportant improvement over hemiarthroplasty in function and quality of life over 24 months. (Funded by the Canadian Institutes of Health Research and others; ClinicalTrials.gov number, NCT00556842.).

The crossover design for studies of infertility employing in-vitro fertilization: A methodological survey

Background

Infertility has become increasingly common worldwide. There is a need for the infertility literature to evaluate new interventions with IVF. The crossover design presents many methodological advantages for IVF trials. In addition to providing a within-person comparison of outcomes, it offers participants the opportunity to potentially benefit from more than one available treatment. However, infertility studies present a unique challenge in terms of bias: successful participants do not cross over to the second treatment group.

Objectives

The main objective of our study was to survey the methodological features of crossover trials for infertility with in-vitro fertilization (IVF) based interventions. A secondary focus was reporting key results.

Study design & setting

We conducted a methodological survey by systematically searching Medline and Embase databases. The capture-recapture technique was used to estimate the number of relevant studies that were not retrieved by our search strategy. We employed the Cochrane risk of bias tool to assess methodological rigour. Crossover-specific methods features were summarized. Treatment effects for pregnancy outcomes across studies are also presented.

Results

15 studies met inclusion criteria. Most studies were deemed to have high or unclear risks of bias, usually because of incomplete reporting of outcome data and assessment procedures. 13 studies did not employ crossover-specific methods to analyze outcome data by period, which may bias treatment effect estimates. Four studies reported pregnancy outcome data with sample sizes from both treatment periods. Of these four studies, three reported that the control intervention was favoured.

Conclusions

The main limitation of our survey was the small sample size of studies. Future reviews should be larger and seek to encompass a broader range of the infertility literature. Despite the issues identified in the included trials, consideration should still be given to using the crossover design in future infertility research. Employing crossover-specific analysis methods, such as accounting for participant non-completion, along with strict adherence to CONSORT reporting guidelines, may significantly reduce the risk of bias in individual studies.

Accounting for health literacy and intervention preferences when reducing unhealthy snacking: protocol for an online randomised controlled trial

INTRODUCTION

Health literacy describes the cognitive and social skills that individuals use to access, understand and act on health information. Health literacy interventions typically take the 'universal precautions approach' where all consumers are presented with simplified materials. Although this approach can improve knowledge and comprehension, its impact on complex behaviours is less clear. Systematic reviews also suggest that health literacy interventions underuse volitional strategies (such as planning) that play an important role in behaviour change. A recent study found volitional strategies may need to be tailored to the participant's health literacy. The current study aims to replicate these findings in a sample of people who have diabetes and/or are overweight or obese as measured by body mass index, and to investigate the most effective method of allocating an action plan to a participant to reduce unhealthy snacking.

METHODS AND ANALYSIS

We plan to recruit approximately 2400 participants at baseline. Participants will receive one of two alternative online action plans intended to reduce unhealthy snacking ('standard' action plan or 'literacy-sensitive' action plan). Participants will be randomised to a method of allocation to an action plan: (1) random allocation; (2) allocation by health literacy screening tool or (3) allocation by participant selection. Primary outcome is self-reported serves of unhealthy snacks during the previous month. Multiple linear regression will evaluate the impact of health literacy on intervention effectiveness. The analysis will also identify independent contributions of each action plan, method of allocation, health literacy and participant selections on unhealthy snacking at 4-week follow-up.

ETHICS AND DISSEMINATION

This study was approved by the University of Sydney Human Research Ethics Committee (2017/793). Findings will be disseminated through peer-reviewed international journals, conferences and updates with collaborating public health bodies (Diabetes New South Wales (NSW) & Australian Capital Territory (ACT), and Western Sydney Local Health District).

TRIAL REGISTRATION NUMBER

ACTRN12618001409268; Pre-results.

Estimates of the current and future burden of melanoma attributable to ultraviolet radiation in Canada

Exposure to ultraviolet radiation (UVR) is an established cause of cutaneous melanoma. The purpose of this study was to estimate the current attributable and future avoidable burden of melanoma related to exposure to UVR and modifiable UVR risk behaviors (sunburn, sunbathing, and indoor tanning). The population attributable risk (PAR) associated with UVR in 2015 was estimated by comparing Canadian melanoma incidence rates in 2015 to estimated incidence rates of a 1920 birth cohort. Rates were adjusted for changes in reporting and ethnicity. We estimated PARs for modifiable UVR risk behaviors using Caucasian prevalence data from the Second National Sun Survey and relative risks that are generalizable to Canada from meta-analyses of relevant studies. Attributable cases apply to 98.9% of melanomas in Canada that occur in Caucasians. We also estimated the future burden of UVR risk behaviors using the potential impact fraction framework and potential reductions in prevalence of 10% to 50% from 2018 to 2042. Adult sunburn and sunbathing were associated with increased risks of melanoma of 1.28 (95% CI: 1.15, 1.43) and 1.44 (95% CI: 1.18, 1.76), respectively. In 2015, we estimate that 62.3% of melanomas in Canada were attributable to exposure to UVR and that 29.7% were attributable to the combination of sunburn (7.4%), sunbathing (17.8%), and indoor tanning (7.0%). A 50% reduction in modifiable UVR behaviors could avoid an estimated 11,980 melanoma cases by 2042. Prevention strategies aimed at modifiable UVR behaviors are crucial to reduce the growing burden of melanoma in Canada.

Estimates of the current and future burden of cancer attributable to red and processed meat consumption in Canada

Red meat and processed meat have been consistently associated with an increased risk of colorectal, stomach, pancreatic cancer and esophageal cancer (processed meat only). The purpose of this analysis was to estimate the current attributable and future avoidable burden of cancer related to red and processed meat consumption in Canada. We estimated the population attributable risk of cancer separately for red meat consumption (beef, lamb, and pork, excluding processed meat) and processed meat consumption (sausage and bacon) incorporating current cancer incidence data, relative risks, and exposure prevalence. We also estimated the future avoidable burden of cancer from 2015 to 2042 for Canada and by province using the potential impact fraction associated with various potential intervention scenarios intended to reduce consumption, ranging from a decrease of 0.2 servings/week to 2.0 servings/week among the adult Canadian population aged 20 and over. The estimated mean red meat consumption in the Canadian population in 2007 to 2011 was approximately 3.2 times per week. In addition, Canadians consume an average of 1.2 times of processed meat per week. In 2015, an estimated 5.9% of associated cancers and 0.9% of all cancers were attributable to red meat consumption. An estimated 4.5% of associated cancers and 0.7% of all cancers were attributable to processed meat consumption. A mean decrease of 0.5 servings/week of red meat or processed meat could prevent about 8700 or 16,600 cancer cases, respectively, between 2015 and 2042. In conclusion, a small but meaningful cancer burden is associated with red and processed meat consumption. Interventions aimed at reducing consumption at the population level have the potential in the prevention of many cancers in Canada.

Estimates of the current and future burden of cancer attributable to lack of physical activity in Canada

Physical activity reduces the risk of many cancers, yet the prevalence of inadequate physical activity among Canadians remains high. Here we estimated the current attributable and future avoidable burden of cancer related to inadequate physical activity among Canadian adults. Population attributable risk (PAR) for all cancers associated with inadequate physical activity were estimated using relative risks obtained from comprehensive reports, meta-analyses and pooled analyses. Cancer incidence data were acquired from the Canadian Cancer Registry. Physical activity data were taken from Canadian Community Health Survey (Cycle 2.1, 2003), in which respondents were classified as "physically inactive" (<1.5 kcal/kg/day), "moderately active" (1.5-2.9 kcal/kg/day) or "physically active (≥3.0 kcal/kg/day). We defined "inadequate physical activity" as being either "physically inactive" or "moderately active" to determine the PAR of cancer due to inadequate physical activity. We estimated the future burden of inadequate physical activity using potential impact fractions and a series of intervention scenarios, including 10% to 50% reductions in inadequate physical activity from 2015 to 2042. For 2015, the total attributable burden due to inadequate physical activity for associated cancers was 10.6% and 4.9% for all cancers. A 50% reduction in inadequate physical activity could avoid 39,877 cumulative cases of cancer by 2042. Over 9000 cancer cases in 2015 were estimated to be attributable to inadequate physical activity and 5170 incident cases of cancer could be prevented with increases in physical activity levels by 2042. Policies aimed at increasing physical activity among Canadian could have a meaningful impact for cancer prevention.

Estimates of the current and future burden of cancer attributable to excess body weight and abdominal adiposity in Canada

The increasing prevalence of obesity among Canadians has important implications for newly diagnosed cases of cancer given that excess body weight and abdominal adiposity are known to increase the risk of several cancers. The purpose of this analysis was to estimate the current attributable and future avoidable burden of cancer related to excess body weight and abdominal adiposity among Canadian adults. We estimated the population attributable risk (PAR) for all cancers associated with excess body weight and abdominal adiposity using contemporary cancer incidence, relative risk and exposure prevalence data for body mass index (BMI), waist circumference and waist-to-hip-ratio. Using the partial impact fraction (PIF), we also estimated the future avoidable burden of cancer from 2015 to 2042 in Canada, and by province, through various hypothetical intervention scenarios. In 2003, approximately half (50.5%) of the Canadian population was estimated to be overweight (BMI 25.0-29.9) or obese (BMI ≥30.0), 56.5% to have excess abdominal adiposity and 56.8% with a high waist-to-hip ratio. In 2015, the estimated PARs of all incident cancers associated with excess body weight, excess abdominal adiposity and high waist-to-hip ratio were 7.2%, 8.9% and 10.0%, respectively. If the population BMI could revert to its 1994 distribution, 72,157 associated cancer cases could be prevented cumulatively by 2042. A reduction in excess body weight and abdominal adiposity has the potential to decrease the future cancer burden in Canada substantially, and hence efforts to reverse increasing trends in obesity should be prioritized.

Estimates of the current and future burden of cancer attributable to alcohol consumption in Canada

Alcohol consumption is associated with elevated risk of oropharyngeal, laryngeal, esophageal, colon, rectal, breast, liver, pancreatic and stomach cancers. The purpose of this analysis was to provide national and provincial estimates of the number and proportion of cancers attributable to alcohol consumption in Canada and to project the numbers of potentially avoidable cancers using possible intervention scenarios. We estimated the population attributable risk (PAR) for cancers associated with alcohol consumption levels (drinks/day) using: i) relative risks obtained from the World Cancer Research Fund/(WCRF) reports or meta-analyses, ii) alcohol consumption (prevalence) data from the 2003 Canadian Community Health Survey, and iii) cancer incidence data from the 2015 Canadian Cancer Registry. We used potential impact fractions (PIFs) to estimate the future avoidable cancer burden under four counterfactual scenarios: (1) lowering alcohol consumption to meet the WCRF low risk guidelines, (2) meeting the Canada's Low-Risk Drinking Guidelines, (3) reducing daily intake by one drink/day, and (4) decreasing consumption to 50% of the 2003 levels by 2032. We estimated that 3282 incident cancer cases (5.2% of alcohol-associated cancers and 1.8% of all cancers) diagnosed in Canada in 2015 were attributable to alcohol consumption. At the current consumption levels, alcohol-attributable cancers are expected to increase to 10,122 (8.8% of cases among alcohol-associated cancers) by 2042. Under the best case scenario, reducing alcohol consumption to 50% of 2003 levels by 2032, could prevent 70,261 cases by 2042. Strategies that effectively reduce alcohol consumption at a population level can have a meaningful impact on reducing the cancer burden in Canada.

The burden of cancer attributable to modifiable risk factors in Canada: Methods overview

Up-to-date estimates of current and projected future cancer burden attributable to various exposures are essential for planning and implementing cancer prevention initiatives. The Canadian Population Attributable Risk of Cancer (ComPARe) study was conducted to: i) estimate the number and proportion of cancers diagnosed among adults in Canada in 2015 that are attributable to modifiable risk factors and ii) project the future avoidable cancers by 2042 under various intervention targets. We estimated the population attributable risk (with 95% confidence intervals) and the potential impact fraction of cancers associated with selected lifestyle, environmental, and infectious factors. Exposure-specific sensitivity analyses were also completed where appropriate. Several exposures of interest included active and passive smoking, obesity and abdominal adiposity, leisure-time physical inactivity, sedentary behaviour, alcohol consumption, insufficient fruit and vegetable intake, red and processed meat consumption, air pollution (PM2.5, NO₂), indoor radon gas, ultraviolet radiation (UVR), hepatitis B and C virus, Helicobacter pylori, Epstein-Barr virus, human papillomavirus, human herpesvirus type 8 and human T-cell lymphotropic virus type 1. We used the 2015 cancer incidence data for 35 cancer sites from the Canadian Cancer Registry and projected cancer incidence to 2042 using historical data from 1983 to 2012. Here, we provide an overview of the data sources and methods used in estimating the current and future cancer burden in Canada. Specific methodologic details for each exposure are included in the individual articles included as part of this special issue.

Estimates of the current and future burden of cancer attributable to low fruit and vegetable consumption in Canada

Low fruit and vegetable consumption is associated with colorectal cancer and may be associated with lung, breast, bladder, pancreatic, ovarian, liver, stomach, esophageal, head and neck cancers. We estimated the current attributable and future avoidable burden of cancer associated with low fruit and vegetable consumption in Canada. Using data on cancer incidence, exposure prevalence and risk effects, we estimated the population attributable risk (PAR) for cancers associated with low fruit and vegetable consumption as well as the future avoidable burden. The prevalence of fruit and vegetable consumption was projected to 2032 and cancer incidence was projected to 2042 to estimate the future potential impact fraction of cancer attributable to low fruit and vegetable consumption. Based on estimates from the Canadian Community Health Survey, the prevalence of low fruit (<4 servings/day) and vegetable (<4 servings/day) consumption in the Canadian population was 80.5% and 86.6%, respectively. The PARs for colorectal cancer associated with low fruit and vegetable consumption were 6.1% (1, 371 cases) and 2.2% (487 cases), respectively. For all incident cancers in 2015, 0.7% and 0.3% were attributable to low fruit and vegetable consumption, respectively. An increase of one serving/week of fruit could prevent 20,710 colorectal cancer cases cumulatively by 2042, and the same increase in vegetable consumption could prevent 10,185 cases. Although more research on the association between fruit and vegetable consumption and cancer risk is needed, our results demonstrate that with reasonable increases in current fruit and vegetable consumption by Canadians, over 30,000 colorectal cancer cases could be prevented by 2042.

Estimates of the current and future burden of cancer attributable to active and passive tobacco smoking in Canada

Although previous studies have examined the burden of cancer attributable to tobacco smoking, updated estimates are needed given the dramatic changes in smoking behaviours over the last 20 years. In this study, we estimate the proportion of cancer cases in 2015 attributable to past tobacco smoking and passive exposure in Canada and the proportion of cancers in the future that could be prevented through the implementation of interventions targeted at reducing tobacco use. Data from the Canadian Community Health Survey (2003) were used to estimate the prevalence of active tobacco smoking and passive exposure. Population attributable risk estimates were employed to estimate the proportion of cancers attributable to tobacco in 2015. The prevalence of active tobacco smoking and passive exposure was projected to 2032 and cancer incidence was projected from 2016 to 2042 to estimate the future burden of cancer attributable to tobacco. In 2003, 30% and 24% of Canadians were former and current smoker, respectively and 24% had been exposed to tobacco smoke in the past. We estimated that 17.5% (32,655 cases; 95% CI: 31,253-34,034) of cancers were attributable to active tobacco smoking and 0.8% (1408 cases; 95% CI: 1048-1781) to passive tobacco exposure in never smokers. Between 41,191 and 50,696 cases of cancer could be prevented by 2042 under various prevention scenarios. By decreasing passive tobacco exposure by 10-50%, between 730 and 3650 cancer cases could be prevented by 2042. Strategies focused on reducing the prevalence of tobacco smoking are crucial for cancer control in Canada.

Optimising the two-stage randomised trial design when some participants are indifferent in their treatment preferences

Outcomes in a clinical trial can be affected by any underlying preferences that its participants have for the treatments under comparison and by whether they actually receive their preferred treatment. These effects cannot be evaluated in standard trial designs but are estimable in the alternative two-stage randomised trial design, in which some patients can choose their treatment, while the rest are randomly assigned. We have previously shown that, when all two-stage trial participants have a preferred treatment, the preference effects can be evaluated, in addition to the usual direct effect of treatment. We also determined criteria by which to optimise how many participants should be given a choice of treatment vs being randomised. More recently, we extended our methodology to allow for participants who are unable or unwilling to express a treatment preference if they are assigned to the choice group. In this paper, we show how to optimise the two-stage design when some participants are undecided about their treatment. We demonstrate that the undecided group should be regarded as distinct in the analysis, to obtain valid estimates of the preference effects. We derive the optimal proportion of participants who should be offered a choice of treatment, which in many cases will be close to 50%. More generally, the optima depend on the preference rates for treatments and the proportion of undecided participants, and the parameters of primary interest. We discuss some advantages and disadvantages of the two-stage trial design in this situation and describe a practical example.

Estimation of the benefit and harms of including clinical breast examination in an organized breast screening program

BACKGROUND

There is controversy about the value of clinical breast examination (CBE) in addition to mammography for breast screening. The study investigates the associations between risk factors such as mammographic density, hormone therapy use and family history and the effectiveness of screening mammography with or without CBE.

METHODS

The cohort consists of women 50-69 years old screened at the Ontario Breast Screening Program. The associations of the risk factors were investigated using a joint logistic regression model that accommodates the partially unobserved disease status, clustered data structures, individual risk factors, and the dependence between true and false detection.

RESULTS

Having high mammographic density, a first degree relative with breast cancer and using hormone therapy generally increased a woman's probability of being referred correctly. For low risk group (defined as without dense breasts, family history, and not currently using hormone therapy), the average loss of specificity ranged from 3.6% to 5.7% and the gain of sensitivity was between 10.6% and 21.2% with the addition of CBE.

CONCLUSIONS

The addition of CBE to mammography would increase the overall sensitivity and decrease the specificity. CBE can be targeted to those women in which it has the highest net benefit.

GRADE approach to rate the certainty from a network meta-analysis: avoiding spurious judgments of imprecision in sparse networks

When direct and indirect estimates of treatment effects are coherent, network meta-analysis (NMA) estimates should have increased precision (narrower confidence or credible intervals compared with relying on direct estimates alone), a benefit of NMA. We have, however, observed cases of sparse networks in which combining direct and indirect estimates results in marked widening of the confidence intervals. In many cases, the assumption of common between-study heterogeneity across the network seems to be responsible for this counterintuitive result. Although the assumption of common between-study heterogeneity across paired comparisons may, in many cases, not be appropriate, it is required to ensure the feasibility of estimating NMA treatment effects. This is especially the case in sparse networks, in which data are insufficient to reliably estimate different variances across the network. The result, however, may be spuriously wide confidence intervals for some of the comparisons in the network (and, in the Grading of Recommendations Assessment, Development, and Evaluation approach, inappropriately low ratings of the certainty of the evidence through rating down for serious imprecision). Systematic reviewers should be aware of the problem and plan sensitivity analyses that produce intuitively sensible confidence intervals. These sensitivity analyses may include using informative priors for the between-study heterogeneity parameter in the Bayesian framework and the use of fixed effects models.

Estimating the current and future cancer burden in Canada: methodological framework of the Canadian population attributable risk of cancer (ComPARe) study

INTRODUCTION

The Canadian Population Attributable Risk of Cancer project aims to quantify the number and proportion of cancer cases incident in Canada, now and projected to 2042, that could be prevented through changes in the prevalence of modifiable exposures associated with cancer. The broad risk factor categories of interest include tobacco, diet, energy imbalance, infectious diseases, hormonal therapies and environmental factors such as air pollution and residential radon.

METHODS AND ANALYSIS

Using a national network, we will use population-attributable risks (PAR) and potential impact fractions (PIF) to model both attributable (current) and avoidable (future) cancers. The latency periods and the temporal relationships between exposures and cancer diagnoses will be accounted for in the analyses. For PAR estimates, historical exposure prevalence data and the most recent provincial and national cancer incidence data will be used. For PIF estimates, we will model alternative or 'counterfactual' distributions of cancer risk factor exposures to assess how cancer incidence could be reduced under different scenarios of population exposure, projecting incidence to 2042.

DISSEMINATION

The framework provided can be readily extended and applied to other populations or jurisdictions outside of Canada. An embedded knowledge translation and exchange component of this study with our Canadian Cancer Society partners will ensure that these findings are translated to cancer programmes and policies aimed at population-based cancer risk reduction strategies.

Wound irrigation does not affect health-related quality of life after open fractures: results of a randomized controlled trial

AIMS

The Fluid Lavage in Open Fracture Wounds (FLOW) trial was a multicentre, blinded, randomized controlled trial that used a 2 × 3 factorial design to evaluate the effect of irrigation solution (soap versus normal saline) and irrigation pressure (very low versus low versus high) on health-related quality of life (HRQL) in patients with open fractures. In this study, we used this dataset to ascertain whether these factors affect whether HRQL returns to pre-injury levels at 12-months post-injury.

PATIENTS AND METHODS

Participants completed the Short Form-12 (SF-12) and the EuroQol-5 Dimensions (EQ-5D) at baseline (pre-injury recall), at two and six weeks, and at three, six, nine and 12-months post-fracture. We calculated the Physical Component Score (PCS) and the Mental Component Score (MCS) of the SF-12 and the EQ-5D utility score, conducted an analysis using a multi-level generalized linear model, and compared differences between the baseline and 12-month scores.

RESULTS

We found no clinically important differences between irrigating solutions or pressures for the SF-12 PCS, SF-12 MCS and EQ-5D. Irrespective of treatment, participants had not returned to their pre-injury function at 12-months for any of the three outcomes (p < 0.001).

CONCLUSION

Neither the composition of the irrigation solution nor irrigation pressure applied had an effect on HRQL. Irrespective of treatment, patients had not returned to their pre-injury HRQL at 12 months post-fracture. Cite this article: Bone Joint J 2018;100-B:88-94.

Dupuytren's contracture and handwork: A case-control study

OBJECTIVE

The objective of this study was to examine the association between Dupuytren's contracture (DC), repetitive handwork (RHW), heavy handwork (HHW), and/or vibration exposure.

METHODS

Frequency and intensity of the three types of handwork were collected and compared between DC patients and controls. Hours of work were weighted by average "frequency," for RHW, and average "intensity," for HHW and use of vibrating tool. Logistic regression was used to evaluate risk of developing DC associated with the above-mentioned factors.

RESULTS

Data from 129 cases (74 clinical, 106 controls) was analyzed. Family history, male gender and age (decades) were associated with increased risk of DC. Results indicate that the risk becomes substantial after about 30 years of steady RHW. Independent effects of intensity-weighted HHW and vibrating exposure were not established.

CONCLUSIONS

Frequency-weighted RHW increases DC risk. Additionally, a strong association between DC, male gender and heredity was found.

Prevalence and predictors of low serum 25-hydroxyvitamin D levels in rural Canadian children

Objectives

Studies in Canada have reported varying prevalences of low serum 25-hydroxyvitamin D (25(OH)D) levels, but none have been conducted in rural paediatric populations. The purpose of this study was to determine the prevalence and predictors of low vitamin D levels in rural communities.

Methods

We conducted a cross-sectional study of children aged 3 to 15 living in Canadian Hutterite communities. Serum 25(OH)D levels were measured between October 2008 and April 2009 using a chemiluminescence assay. Predictors of vitamin D levels were evaluated using multivariable linear regression. A multilevel model was used to evaluate the impact of individual, household and colony factors on the variation in vitamin D levels.

Results

Serum 25(OH)D levels were available on 743 children/adolescents. The median was 62.0 nmol/L (interquartile range 51.0, 74.0). Levels lower than 50 nmol/L and 75 nmol/L were found in 152 (20.5%) and 565 (76%) children, respectively. Adolescents were at highest risk for levels <75 nmol/L (odds ratio 3.38, 95% confidence interval 2.00, 5.80). Age and latitude were negatively correlated with serum 25(OH)D level. In the multilevel model, most of the variation in levels was associated with individual children.

Conclusion

Low vitamin D levels are a significant problem in rural Hutterite communities in Canada. Adolescents were at greatest risk for low levels and represent an important target group for supplementation. Variation in serum 25(OH)D levels was explained mostly at the individual level. Additional studies are needed to explore factors associated with individuals (e.g., genetics) leading to lower 25(OH)D levels.