Meta-Analyses of Low-risk Lifestyle Behaviours and Patient Important Outcomes

Rationale:

International health authorities universally recommend adherence to low-risk lifestyle behaviors for health promotion and prevention of chronic or non-communicable diseases (NCDs). Systematic reviews and meta-analyses of prospective cohort studies have shown that adherence to any one low-risk lifestyle behavior, including a healthy body weight, healthy diet, regular physical activity, smoking cessation, moderate alcohol intake, or adequate sleep, is associated with less risk of chronic disease. Although individual prospective cohort studies have shown that adherence to a combination of these low-risk lifestyle behaviors is associated with an even greater benefit, there are no systematic reviews and meta-analyses assessing whether it holds across different definitions of low-risk lifestyle behaviors, levels of exposure, populations, geographical regions, background risks, and chronic disease outcomes. To inform recommendations for the role of low-risk lifestyle behaviors in chronic disease prevention, the Canadian Cardiovascular Society (CCS), as part of the Dyslipidemia Guidelines Update, commissioned a series of systematic reviews and meta-analyses using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach of the association between adherence to a combination of low-risk lifestyle behaviors and (1) cardiovascular disease (CVD), (2) diabetes, (3) cancer, and (4) all-cause mortality outcomes.

Objectives:

1. To conduct a series of systematic reviews and meta-analyses of the association between adherene to a combination of low-risk lifestyle behaviors and 4 chronic disease outcomes (1) cardiovascular disease (cardiovascular disease (CVD) incidence and mortality, coronary heart disease [CHD] incidence and mortality, and stroke incidence and mortality), (2) diabetes, (3) cancer (cancer incidence and cancer mortality), and (4) all-cause mortality.
2. To assess the quality and strength of the evidence using GRADE.

Design:

The planning and conduct of the proposed systematic reviews and meta-analyses will follow the Cochrane handbook for systematic reviews of interventions. The reporting will follow the Meta-Analysis Of Observational Studies in Epidemiology (MOOSE) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements.

Data sources:

MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials (Clinical Trials; CENTRAL) will be searched using appropriate search terms. These searches will be supplemented by manual hand searches of the bibliographies of included studies and existing review articles.

Study selection:

Prospective cohort studies investigating the relation of at-least three low-risk lifestyle behaviors, one of which must include a healthy diet, with incident cardiovascular disease, diabetes, cancer or all-cause mortality will be included. Studies will be excluded if low-risk lifestyle behaviors are combined with biomarkers.

Data extraction:

Two independent reviewers or more will independently extract relevant information about study design, sample size, subject characteristics, low risk lifestyle behaviors, duration/person-years of follow-up, adjustments of models. Risk ratios for clinical outcomes will be extracted or derived from clinical event data across quantiles of exposure.

Risk of bias:

Two independent reviewers or more will assess risk of bias of (ROB) of each of the included prospective cohort studies using the Newcastle-Ottawa Scale (NOS) by . Up to 9 points can be awarded based on cohort selection (max 4 points), the comparability of cohort design and analysis (max 4 points), and adequacy of the outcome measures (max 3 points). Studies that receive ≥6 points will be considered as higher quality.

Outcomes:

Each of the four proposed systematic reviews and meta-analyses will assess a different chronic disease outcome: cardiovascular disease (CVD incidence and mortality, CHD incidence and mortality, and stroke incidence and mortality), (2) diabetes, (3) cancer (cancer and cancer mortality), and (4) all-cause mortality.

Data synthesis:

Risk estimates of extreme comparisons (all who adhered to low-risk behaviors versus none) will be pooled using inverse variance random effects models and expressed as risk ratios (RR) with 95% confidence intervals (CIs). Between-cohort heterogeneity will be assessed by the Cochran Q (chi-square) statistic and quantified by the I2 statistic. The significance level will be set at p<0.10 and an I2 ≥ 50% will be considered evidence of substantial heterogeneity. To explore sources of heterogeneity, the investigators will conduct sensitivity analyses, in which each study is systematically removed with recalculation of the summary estimates. If there are >=10 studies, then the investigators will also explore sources of heterogeneity using a priori subgroup analyses by underlying disease status, sex, number of lifestyle factors, follow-up (<10 years, ≥10 years), level of adjustment of models, NOS, ascertainment of outcome, and individual domains of NOS Meta-regression analyses will assess the significance of categorical and continuous subgroups analyses. Dose-response analyses will be undertaken using random-effects generalized least squares trend estimation models (GLST) to assess linear relationships and spline curve modeling (the MKSPLINE procedure) to assess non-linear relationships. If ≥10 cohort comparisons are available, then publication bias will be assessed by visual inspection of funnel plots and formally tested with the Egger and Begg tests at a significance level of p≤ 0.10. If publication bias is suspected, then the investigators will attempt to adjust for funnel plot asymmetry by imputing the missing study data using the Duval and Tweedie trim and fill method.

Quality of evidence:

Evidence profiles will be produced the overall strength and quality of the evidence will be assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. This system grades the evidence as "high quality", "moderate quality", "low quality", or "very low quality". The included prospective cohort studies will start at "low quality" by default and then be downgraded or upgraded based on pre-specified criteria. Criteria to downgrade will include study limitations (weight of studies show risk of bias by NOS), inconsistency (substantial unexplained inter-study heterogeneity, I2>50% and P<0.10), indirectness (presence of factors relating to the population, exposures, and outcomes that limit generalizability), imprecision (95% CI are wide or cross a minimally important difference of 10% [RR 0.9- 1.1]), and publication bias (significant evidence of small-study effects). Criteria to upgrade will include a large magnitude effect (RR>2 or RR<0.5 in the absence of plausible confounders), a dose-response gradient, and attenuation by plausible confounding effects.

Knowledge translation plan:

The results will be disseminated through interactive presentations at local, national, and international scientific meetings and publication in high impact factor journals. Target audiences will include the public health and scientific communities with interest in nutrition, physical activity, lifestyle modification, diabetes, cancer and cardiovascular disease. Feedback will be incorporated and used to improve the public health message and key areas for future research will be defined.

Significance:

The proposed project will aid in knowledge translation related to the effects of low-risk lifestyle behaviours on cardiovascular disease, diabetes, cancer, and all-cause mortality, strengthening the evidence-base for recommendations and improving health outcomes through informing consumers and public health policy makers, stimulating industry innovation, and guiding future research.

Role of the funding sources:

The funding source will have no role in the research question, design, analysis, results and interpretation of the results of this study.