2025
Air Pollution and Cognitive Impairment Among the Chinese Elderly Population: An Analysis of the Chinese Longitudinal Healthy Longevity Survey (CLHLS)
Zhu Q, Lyu Y, Huang K, Zhou J, Wang W, Steenland K, Chang H, Ebelt S, Shi X, Liu Y. Air Pollution and Cognitive Impairment Among the Chinese Elderly Population: An Analysis of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). GeoHealth 2025, 9: e2024gh001023. PMID: 39776607, PMCID: PMC11705411, DOI: 10.1029/2024gh001023.Peer-Reviewed Original ResearchChinese Longitudinal Health Longevity SurveyWarm-season O<sub>3</sub>Chinese elderly populationAssociated with cognitive impairmentLongevity SurveyCognitive impairmentLinear mixed-effects modelsChinese Longitudinal Healthy Longevity SurveyAir pollutionAssociation of air pollutionMixed-effects modelsAverage NO<sub>2</sub>Average PM<sub>2.5</sub>Elderly populationSingle-pollutant modelsMulti-pollutant modelsLogistic regression modelsCMMSE scoresControl Action PlanAir pollution preventionStudy participantsGaseous air pollutantsFollow-up visitRandom interceptPositive association
2024
[Exploring implementation strategies for healthy longevity among the elderly population in China based on the delphi method].
Chai X, Cui J, Ye L, Lyu Y, Shao R, Zhang J, Shi X. [Exploring implementation strategies for healthy longevity among the elderly population in China based on the delphi method]. Chinese Preventive Medicine 2024, 58: 883-890. PMID: 38955737, DOI: 10.3760/cma.j.cn112150-20230804-00056.Peer-Reviewed Original ResearchConceptsHarmony coefficientsImplementation strategiesHealthy longevityAuthority coefficientPromote healthy longevityExpert active coefficientElderly populationChinese elderly populationDelphi methodDelphi consultationConsultation questionnaireElderly care service industryPublic healthFeasibility scoreScore of feasibilityAverage scoreConsultationExpert discussionScoresLiterature reviewClinical medicine
2022
Machine learning prediction of exposure to acrylamide based on modelling of association between dietary exposure and internal biomarkers
Wan X, Zhang Y, Gao S, Shen X, Jia W, Pan X, Zhuang P, Jiao J, Zhang Y. Machine learning prediction of exposure to acrylamide based on modelling of association between dietary exposure and internal biomarkers. Food And Chemical Toxicology 2022, 170: 113498. PMID: 36328216, DOI: 10.1016/j.fct.2022.113498.Peer-Reviewed Original ResearchConceptsDietary exposureElderly populationInternal exposureTotal energy intakeDietary acrylamide exposureChinese elderly populationAverage dietary intakeN-acetylExposure assessmentRegression modelsUrinary biomarkersDietary intakeUrinary contentAcrylamide exposureChinese cohortPhysical activityAccurate exposure assessmentEnergy intakeElderly participantsPotential health risksL-cysteineImportant covariatesLinear regression modelsHealth risksExposure
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