Dataset Information

Impact of follow-up time and analytical approaches to account for reverse causality on the association between physical activity and health outcomes in UK Biobank.

ABSTRACT:

Background

The advent of very large cohort studies (n?>?500 000) has given rise to prospective analyses of health outcomes being undertaken after short (<4?years) follow-up periods. However, these studies are potentially at risk of reverse causality bias. We investigated differences in the associations between self-reported physical activity and all-cause and cardiovascular disease (CVD) mortality, and incident CVD, using different follow-up time cut-offs and methods to account for reverse causality bias.

Methods

Data were from n?=?452 933 UK Biobank participants, aged 38-73?years at baseline. Median available follow-up time was 7 years (for all-cause and CVD mortality) and 6.1?years (for incident CVD). We additionally analysed associations at 1-, 2- and 4-year cut-offs after baseline. We fit up to four models: (1) adjusting for prevalent CVD and cancer, (2) excluding prevalent disease, (3) and (4) Model 2 excluding incident cases in the first 12 and 24?months, respectively.

Results

The strength of associations decreased as follow-up time cut-off increased. For all-cause mortality, Model 1 hazard ratios were 0.73 (0.69-0.78) after 1 year and 0.86 (0.84-0.87) after 7 years. Associations were weaker with increasing control for possible reverse causality. After 7-years follow-up, the hazard ratios were 0.86 (0.84-0.87) and 0.88 (0.86-0.90) for Models 1 and 4, respectively. Associations with CVD outcomes followed similar trends.

Conclusions

As analyses with longer follow-up times and increased control for reverse causality showed weaker associations, there are implications for the decision about when to analyse a cohort study with ongoing data collection, the interpretation of study results and their contribution to meta-analyses.

SUBMITTER: Strain T

PROVIDER: S-EPMC7124507 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Publications

Impact of follow-up time and analytical approaches to account for reverse causality on the association between physical activity and health outcomes in UK Biobank.

Strain Tessa T Wijndaele Katrien K Sharp Stephen J SJ Dempsey Paddy C PC Wareham Nick N Brage Søren S

International journal of epidemiology 20200201 1

<h4>Background</h4>The advent of very large cohort studies (n > 500 000) has given rise to prospective analyses of health outcomes being undertaken after short (<4 years) follow-up periods. However, these studies are potentially at risk of reverse causality bias. We investigated differences in the associations between self-reported physical activity and all-cause and cardiovascular disease (CVD) mortality, and incident CVD, using different follow-up time cut-offs and methods to account for rever ...[more]

PMID: 31651957

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Project description:BackgroundMultimorbidity, typically defined as having two or more long-term health conditions, is associated with reduced wellbeing and life expectancy. Understanding the determinants of multimorbidity, including whether they are causal, may help with the design and prioritisation of prevention interventions. This study seeks to assess the causality of education, BMI, smoking and alcohol as determinants of multimorbidity, and the degree to which BMI, smoking and alcohol mediate differences in multimorbidity by level of education.MethodsParticipants were 181,214 females and 155,677 males, mean ages 56.7 and 57.1 years respectively, from UK Biobank. We used a Mendelian randomization design; an approach that uses genetic variants as instrumental variables to interrogate causality.ResultsThe prevalence of multimorbidity was 55.1%. Mendelian randomization suggests that lower education, higher BMI and higher levels of smoking causally increase the risk of multimorbidity. For example, one standard deviation (equivalent to 5.1 years) increase in genetically-predicted years of education decreases the risk of multimorbidity by 9.0% (95% CI: 6.5 to 11.4%). A 5 kg/m2 increase in genetically-predicted BMI increases the risk of multimorbidity by 9.2% (95% CI: 8.1 to 10.3%) and a one SD higher lifetime smoking index increases the risk of multimorbidity by 6.8% (95% CI: 3.3 to 10.4%). Evidence for a causal effect of genetically-predicted alcohol consumption on multimorbidity was less strong; an increase of 5 units of alcohol per week increases the risk of multimorbidity by 1.3% (95% CI: 0.2 to 2.5%). The proportions of the association between education and multimorbidity explained by BMI and smoking are 20.4% and 17.6% respectively. Collectively, BMI and smoking account for 31.8% of the educational inequality in multimorbidity.ConclusionsEducation, BMI, smoking and alcohol consumption are intervenable causal risk factors for multimorbidity. Furthermore, BMI and lifetime smoking make a considerable contribution to the generation of educational inequalities in multimorbidity. Public health interventions that improve population-wide levels of these risk factors are likely to reduce multimorbidity and inequalities in its occurrence.

Dataset Information

Impact of follow-up time and analytical approaches to account for reverse causality on the association between physical activity and health outcomes in UK Biobank.

Background

Methods

Results

Conclusions

Publications

Impact of follow-up time and analytical approaches to account for reverse causality on the association between physical activity and health outcomes in UK Biobank.

Similar Datasets

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