Dataset Information

Modification of the Association between Visual Impairment and Mortality by Physical Activity: A Cohort Study among the Korean National Health Examinees.

ABSTRACT: The association between visual impairment and higher mortality remains unclear. In addition, evidence is lacking on the interaction between visual function and physical activity on mortality. We used data of individuals with no disability or with visual impairment among those who participated in the National Health Screening Program in Korea in 2009 or 2010. We constructed Cox proportional hazard models adjusted for potential confounders to evaluate the independent association between visual impairment and mortality. More severe visual impairment was associated with higher all-cause mortality (p-value for trend = 0.03) and mortality due to cardiovascular diseases (p-value for trend = 0.02) and that due to other diseases (p-value for trend = 0.01). We found an interaction on an additive scale between visual impairment and no physical activity on all-cause mortality (relative excess risk due to interaction = 1.34, 95% confidence interval: 0.37, 2.30, p-value = 0.01). When we stratified the study population by physical activity, the association between visual impairment and mortality was only found among individuals who did not engage in regular physical activity (p-value for trend = 0.01). We found an independent association between visual impairment and mortality and modification of this association by physical activity.

SUBMITTER: Kim KN

PROVIDER: S-EPMC6888179 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modification of the Association between Visual Impairment and Mortality by Physical Activity: A Cohort Study among the Korean National Health Examinees.

Kim Kyoung-Nam KN Park Sang Jun SJ Kim Woosung W Joo Jungmin J Kim Haebin H Kim Kyae Hyung KH Sohn Ji Hoon JH Kwon Yong Jin YJ

International journal of environmental research and public health 20191110 22

The association between visual impairment and higher mortality remains unclear. In addition, evidence is lacking on the interaction between visual function and physical activity on mortality. We used data of individuals with no disability or with visual impairment among those who participated in the National Health Screening Program in Korea in 2009 or 2010. We constructed Cox proportional hazard models adjusted for potential confounders to evaluate the independent association between visual imp ...[more]

PMID: 31717624

Similar Datasets

Project description:ImportanceIt is unclear whether, for the same amount of total physical activity, a higher proportion of vigorous physical activity (VPA) to total physical activity is associated with a greater reduction in mortality.ObjectiveTo examine the association of the proportion of VPA to total physical activity (defined as moderate to vigorous physical activity [MVPA]) with all-cause mortality, cardiovascular disease mortality, and cancer mortality.Design, setting, and participantsThis cohort study included 403 681 adults from the National Health Interview Survey 1997-2013 who provided data on self-reported physical activity and were linked to the National Death Index records through December 31, 2015. Statistical analysis was performed from May 15, 2018, to August 15, 2020.ExposuresProportion of VPA to total physical activity among participants performing any MVPA.Main outcomes and measuresAll-cause mortality, cardiovascular disease mortality, and cancer mortality. Cox proportional hazards regression models were performed to estimate hazard ratios (HRs) and 95% CIs, adjusted for sociodemographic characteristics, lifestyle risk factors, and total physical activity.ResultAmong the 403 681 individuals (225 569 women [51.7%]; mean [SD] age, 42.8 [16.3] years) in the study, during a median 10.1 years (interquartile range, 5.4-14.6 years) of follow-up (407.3 million person-years), 36 861 deaths occurred. Mutually adjusted models considering the recommendations of moderate physical activity (MPA; 150-299 vs 0 minutes per week) and VPA (≥75-149 vs 0 minutes per week) showed similar associations for all-cause mortality (MPA: HR, 0.83; 95% CI, 0.80-0.87; and VPA: HR, 0.80; 95% CI, 0.76-0.84) and cardiovascular disease mortality (MPA: HR, 0.75; 95% CI, 0.68-0.83; and VPA: HR, 0.79; 95% CI, 0.70-0.91). For the same contrasts, VPA (HR, 0.89; 95% CI, 0.80-0.99) showed a stronger inverse association with cancer mortality compared with MPA (HR, 0.94; 95% CI, 0.86-1.02). Among participants performing any MVPA, a higher proportion of VPA to total physical activity was associated with lower all-cause mortality but not with cardiovascular disease and cancer mortality. For instance, compared with participants with 0% of VPA (no vigorous activity), participants performing greater than 50% to 75% of VPA to total physical activity had a 17% lower all-cause mortality (hazard ratio, 0.83; 95% CI, 0.78-0.88), independent of total MVPA. The inverse association between proportion of VPA to total physical activity and all-cause mortality was consistent across sociodemographic characteristics, lifestyle risk factors, and chronic conditions at baseline.Conclusions and relevanceThis study suggests that, for the same volume of MVPA, a higher proportion of VPA to total physical activity was associated with lower all-cause mortality. Clinicians and public health interventions should recommend 150 minutes or more per week of MVPA but also advise on the potential benefits associated with VPA to maximize population health.

Project description:BackgroundAlmost all Koreans are covered by mandatory national health insurance and are required to undergo health screening at least once every 2 years. We aimed to develop a machine learning model to predict the risk of developing hepatocellular carcinoma (HCC) based on the screening results and insurance claim data.MethodsThe National Health Insurance Service-National Health Screening database was used for this study (NHIS-2020-2-146). Our study cohort consisted of 417,346 health screening examinees between 2004 and 2007 without cancer history, which was split into training and test cohorts by the examination date, before or after 2005. Robust predictors were selected using Cox proportional hazard regression with 1000 different bootstrapped datasets. Random forest and extreme gradient boosting algorithms were used to develop a prediction model for the 9-year risk of HCC development after screening. After optimizing a prediction model via cross validation in the training cohort, the model was validated in the test cohort.ResultsOf the total examinees, 0.5% (1799/331,694) and 0.4% (390/85,652) in the training cohort and the test cohort were diagnosed with HCC, respectively. Of the selected predictors, older age, male sex, obesity, abnormal liver function tests, the family history of chronic liver disease, and underlying chronic liver disease, chronic hepatitis virus or human immunodeficiency virus infection, and diabetes mellitus were associated with increased risk, whereas higher income, elevated total cholesterol, and underlying dyslipidemia or schizophrenic/delusional disorders were associated with decreased risk of HCC development (p < 0.001). In the test, our model showed good discrimination and calibration. The C-index, AUC, and Brier skill score were 0.857, 0.873, and 0.078, respectively.ConclusionsMachine learning-based model could be used to predict the risk of HCC development based on the health screening examination results and claim data.

Project description:BackgroundThere is not enough evidence regarding how information obtained from general health check-ups can predict individual mortality based on long-term follow-ups and large sample sizes. This study evaluated the applicability of various health information and measurements, consisting of self-reported data, anthropometric measurements and laboratory test results, in predicting individual mortality.MethodsThe National Health Screening Cohort included 514,866 participants (aged 40-79 years) who were randomly selected from the overall database of the national health screening program in 2002-2003. Death was determined from causes of death statistics provided by Statistics Korea. We assessed variables that were collected at baseline and repeatedly measured for two consecutive years using traditional and time-variant Cox proportional hazards models in addition to random forest and boosting algorithms to identify predictors of 10-year all-cause mortality. Participants' age at enrollment, lifestyle factors, anthropometric measurements and laboratory test results were included in the prediction models. We used c-statistics to assess the discriminatory ability of the models, their external validity and the ratio of expected to observed numbers to evaluate model calibration. Eligibility of Medicaid and household income levels were used as inequality indexes.ResultsAfter the follow-up by 2013, 38,031 deaths were identified. The risk score based on the selected health information and measurements achieved a higher discriminatory ability for mortality prediction (c-statistics = 0.832, 0.841, 0.893, and 0.712 for Cox model, time-variant Cox model, random forest and boosting, respectively) than that of the previous studies. The results were externally validated using the community-based cohort data (c-statistics = 0.814).ConclusionsIndividuals' health information and measurements based on health screening can provide early indicators of their 10-year death risk, which can be useful for health monitoring and related policy decisions.

Dataset Information

Modification of the Association between Visual Impairment and Mortality by Physical Activity: A Cohort Study among the Korean National Health Examinees.

Publications

Modification of the Association between Visual Impairment and Mortality by Physical Activity: A Cohort Study among the Korean National Health Examinees.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets