Chronic Diseases and Translational Medicine最新文献

{"title":"Guide for Authors","authors":"","doi":"10.1002/cdt3.143","DOIUrl":"https://doi.org/10.1002/cdt3.143","url":null,"abstract":"","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 3","pages":"256-262"},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.143","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141639540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum: Effects of long-term blood pressure variability on renal function in community population","authors":"","doi":"10.1002/cdt3.144","DOIUrl":"https://doi.org/10.1002/cdt3.144","url":null,"abstract":"<p>In the article titled, “Effects of long-term blood pressure variability on renal function in community population” published in pages 149–152, vol. 10 of Chronic Diseases and Translational Medicine,<span>¹</span> the order of the first author's name is incorrect. The first author's name should be Feng Zhao.</p>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 4","pages":"351"},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.144","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of eating out of home and type 2 diabetes mellitus in Chinese urban workers: A nationwide study","authors":"Fangyan Chen,&nbsp;Sitong Wan,&nbsp;Jinjuan Hao,&nbsp;Ke Sun,&nbsp;Annan Liu,&nbsp;Ling Zhu,&nbsp;Shuyan Wang,&nbsp;Jingjing He,&nbsp;Ping Zeng","doi":"10.1002/cdt3.136","DOIUrl":"10.1002/cdt3.136","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The prevalence of type 2 diabetes mellitus (T2DM) has been rapidly growing in Chinese populations in recent decades, and the shift in eating habits is a key contributing factor to this increase. Eating out of home (EOH) is one of the major shifts in eating habits during this period. However, the influence of EOH on the incidence of T2DM among Chinese urban workers is unknown.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The cross-sectional study involved an analysis of 13,904 urban workers recruited from 11 health examination centers in the major cities of China to explore the relationship between EOH and T2DM between 2013 September and 2016 March.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Average weekly EOH frequency ≥10 times was positively associated with increased incidence of T2DM in the sampled population (OR: 1.31 [1.11–1.54], <i>p</i> &lt; 0.01), most notably in participants ≤45 years old (OR: 1.41[1.11–1.80], <i>p</i> &lt; 0.01]) and in males (OR:1.26 [1.06–1.51], <i>p</i> &lt; 0.01). An EOH frequency of 5 times/week appears as a threshold for a significant increase in the odds of T2DM. Weekly EOH frequency ≥5 times was associated with increased odds of T2DM in a dose–response manner in the total population and almost all subgroups (<i>p</i>_{overall association} &lt; 0.05 and <i>p</i>_nonlinearity ≤ 0.05).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study showed that a frequency of EOH (≥5 times/week) was associated with a frequency-dependent increase in the odds of T2DM urban workers in China. More nutrition promotion is needed to improve the eating behavior of Chinese urban workers to reduce T2DM risk.</p>\u0000 </section>\u0000 </div>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"11 1","pages":"69-77"},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141348353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guide for Authors","authors":"","doi":"10.1002/cdt3.140","DOIUrl":"https://doi.org/10.1002/cdt3.140","url":null,"abstract":"","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 2","pages":"159-165"},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.140","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improvement in oxygen dynamics after 3 months of home-based respiratory muscle rehabilitation in a patient with complex severe pulmonary hypertension: A case report","authors":"Xinxin Yan,&nbsp;Ya Song,&nbsp;Hongda Zhang,&nbsp;Tingting Guo,&nbsp;Xin Gao,&nbsp;Yan Wu,&nbsp;Lu Hua","doi":"10.1002/cdt3.138","DOIUrl":"10.1002/cdt3.138","url":null,"abstract":"&lt;p&gt;A 26-year-old woman with congenital heart disease, postatrial septal defect repair, postarterial catheter ligation, hypoxia-associated pulmonary hypertension, and reduced right heart function, which manifested as a severe decrease in activity tolerance, chest tightness and shortness of breath, and easy fatigue of breathing, was treated with oxygen, targeting medications such as anisentan, tadalafil, remodulin, and diuretic potassium supplementation to enhance cardiac function, and then her symptoms were slightly improved compared with the previous ones. She was guided with in-hospital respiratory training to the extent that the patient could tolerate it and then was discharged from the hospital to have a home-based respiratory rehabilitation for a period of 3 months. The training plan was as follows: (i) Respiratory muscle function test: the patient's resting maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) were assessed by the respiratory trainer equipment, and the respiratory muscle weakness/invulnerability was defined as a measured maximal pressure value less than 80 cmH&lt;sub&gt;2&lt;/sub&gt;O according to the ERS guidelines.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; (ii) Respiratory muscle training impedance progression: first month, 30% of the MIP and MEP of this test, 30 repetitions/day, 5–7 days/week for 1 month; second month, reassessment of respiratory muscle strength with impedance of 35% of the MIP and MEP of this test, 30 repetitions/day, 5–7 days/week for 1 month; and month 3, reassessment of respiratory muscle strength with impedance of MIP and 40% of MEP, 30 times/day, 5–7 days/week for 1 month. During the period of home respiratory rehabilitation, this patient did not experience any adverse hazardous events. (1) After 3 months of training, this patient's respiratory muscle strength improved, including a significant increase in MIP from 43 to 53 cmH&lt;sub&gt;2&lt;/sub&gt;O and a slight increase in MEP from 53 to 57 cmH&lt;sub&gt;2&lt;/sub&gt;O; peak inspiratory flow rate decreased from 2.77 to 3.50 L/s, and peak expiratory flow rate decreased from 3.01 to 2.57 L/s. (2) This patient's oxygen saturation improved with oxygen (91% vs. 94%) and her heart rate decreased significantly without oxygen (102 vs. 90 bpm) compared to before training (91% vs. 94%). Additionally, her heart rate was significantly lower (102 vs. 90 bpm), and oxygen saturation was significantly better (83% vs. 89%) without oxygen than it was 3 months prior. (3) Subjective symptoms improved, with the patient initially completing a training session with a Borg score of up to 12/20. After training, she completed the same session with a Borg score of 9–10/20. (4) Weakness improved. Before training, the patient experienced more than moderate shortness of breath with minimal activity and needed a wheelchair while in an oxygenated state. After the training, she could go up and down three staircases or walk on the flat ground for 3–4 min with much less perceived dyspnea.&lt;/p&gt;&lt;p&gt;Respiratory muscle ","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"11 1","pages":"78-80"},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.138","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141366864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges","authors":"Ebenezer Afrifa-Yamoah,&nbsp;Eric Adua,&nbsp;Emmanuel Peprah-Yamoah,&nbsp;Enoch O. Anto,&nbsp;Victor Opoku-Yamoah,&nbsp;Emmanuel Acheampong,&nbsp;Michael J. Macartney,&nbsp;Rashid Hashmi","doi":"10.1002/cdt3.137","DOIUrl":"10.1002/cdt3.137","url":null,"abstract":"<p>Chronic diseases such as heart disease, cancer, and diabetes are leading drivers of mortality worldwide, underscoring the need for improved efforts around early detection and prediction. The pathophysiology and management of chronic diseases have benefitted from emerging fields in molecular biology like genomics, transcriptomics, proteomics, glycomics, and lipidomics. The complex biomarker and mechanistic data from these “omics” studies present analytical and interpretive challenges, especially for traditional statistical methods. Machine learning (ML) techniques offer considerable promise in unlocking new pathways for data-driven chronic disease risk assessment and prognosis. This review provides a comprehensive overview of state-of-the-art applications of ML algorithms for chronic disease detection and prediction across datasets, including medical imaging, genomics, wearables, and electronic health records. Specifically, we review and synthesize key studies leveraging major ML approaches ranging from traditional techniques such as logistic regression and random forests to modern deep learning neural network architectures. We consolidate existing literature to date around ML for chronic disease prediction to synthesize major trends and trajectories that may inform both future research and clinical translation efforts in this growing field. While highlighting the critical innovations and successes emerging in this space, we identify the key challenges and limitations that remain to be addressed. Finally, we discuss pathways forward toward scalable, equitable, and clinically implementable ML solutions for transforming chronic disease screening and prevention.</p>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"11 1","pages":"1-21"},"PeriodicalIF":0.0,"publicationDate":"2024-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141367147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in the prevalence and incidence of chronic obstructive pulmonary disease among adults aged ≥50 years in the United States, 2000–2020","authors":"Yaxian Meng,&nbsp;Qianqian Ji,&nbsp;Aijie Zhang,&nbsp;Yiqiang Zhan","doi":"10.1002/cdt3.135","DOIUrl":"https://doi.org/10.1002/cdt3.135","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Understanding the trends of the prevalence and incidence rate of chronic obstructive pulmonary disease (COPD) is vital for improving the control and prevention of COPD. We aimed to examine the trends in the prevalence and incidence rate of COPD among adults aged 50 years or older in the United States during 2000–2020.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Utilizing data from the Health and Retirement Study, we analyzed COPD prevalence across survey waves and calculated COPD incidence rates between consecutive interview waves, stratified by gender and race. We employed joinpoint regression models to investigate trends in COPD prevalence and incidence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The individuals reporting COPD are more likely to be women and Caucasians. The age-adjusted prevalence of COPD among adults aged 50 years and over showed an increasing trend throughout the study period, spanning from 9.02% in 2000 to 9.88% in 2020 (average biennial percent change [ABPC] = 0.41, 95% confidence interval [CI]: 0.10, 0.71; <i>p</i> = 0.01). The age-adjusted incidence rate of COPD among adults aged 50 and over showed a decreasing trend throughout the study period 1031.1 per 100,000 person-years in 2000 to 700.5 per 100,000 person-years in 2020 (ABPC = −1.63, 95% CI: −2.88, −0.36; <i>p</i> = 0.02).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our findings indicate a rising prevalence of COPD among older adults in the United States since 2000, while the incidence rate of COPD has shown a declining trend.</p>\u0000 </section>\u0000 </div>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 4","pages":"302-311"},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.135","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bayesian network for estimating hypertension risk due to occupational aluminum exposure","authors":"Le Zhao,&nbsp;Jinzhu Yin,&nbsp;Jiaping Huan,&nbsp;Xiao Han,&nbsp;Dan Zhao,&nbsp;Jing Song,&nbsp;Linping Wang,&nbsp;Huifang Zhang,&nbsp;Baolong Pan,&nbsp;Qiao Niu,&nbsp;Xiaoting Lu","doi":"10.1002/cdt3.134","DOIUrl":"https://doi.org/10.1002/cdt3.134","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The correlation between metals and hypertension, such as sodium, zinc, potassium, and magnesium, has been confirmed, while the relationship between aluminum and hypertension is not very clear. This study aimed to evaluate the correlation between plasma aluminum and hypertension in electrolytic aluminum workers by the Bayesian networks (BN).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In 2019, 476 male workers in an aluminum factory were investigated. The plasma aluminum concentration of workers was measured by inductively coupled plasma mass spectrometry. The influencing factors on the prevalence of hypertension were analyzed by the BN.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The prevalence of hypertension was 23.9% in 476 male workers. The risk of hypertension from plasma aluminum in the Q2, Q3, and Q4 groups was 5.20 (1.90–14.25), 6.92 (2.51–19.08), and 7.33 (2.69–20.01), respectively, compared with that in the Q1 group. The risk of hypertension from the duration of exposure to aluminum of &gt;10 years was 2.23 (1.09–4.57), compared without aluminum exposure. Area under the curve was 0.80 of plasma aluminum and the duration of exposure to aluminum was based on covariates, indicating that aluminum exposure had important predictive value in the prevalence of hypertension in the occupational population. The results of the study using the BN model showed that if the plasma aluminum of all participants was higher than Q4 (≥47.86 µg/L) and the participants were drinking, smoking, diabetes, central obesity, dyslipidemia, and aged &gt;50 years, the proportion of hypertension was 71.2%.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The prevalence of hypertension increased significantly with the increase of plasma aluminum level.</p>\u0000 </section>\u0000 </div>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 2","pages":"130-139"},"PeriodicalIF":0.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.134","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hypertension and human health: Evidence and prospects","authors":"Fangchao Liu,&nbsp;Xiangfeng Lu","doi":"10.1002/cdt3.129","DOIUrl":"https://doi.org/10.1002/cdt3.129","url":null,"abstract":"<p>High blood pressure is a major public health issue and a leading risk factor for death worldwide, with the number of attributable deaths increased from 6.8 million in 1990 to 10.8 million in 2019.<span>^{1, 2}</span> According to the World Health Organization, the age-standardized prevalence of hypertension was estimated to be 33%, affecting approximately 1.3 billion adults aged 30–79 years in 2019 worldwide, doubling from 1990.<span>³</span> In addition to the heavy disease burden, the economic burden associated with hypertension is also substantial, accounting for approximately 10% of the global healthcare expenditure.<span>⁴</span> Furthermore, despite improvements in diagnostic and treatment capacities, the status of hypertension care remains suboptimal, especially in low- and middle-income countries. For instance, in China, in 2019, the awareness, treatment, and control rates of hypertension were 38.3%, 34.6%, and 12.0%, respectively.<span>⁵</span> Accumulating evidence calls for more comprehensive and effective prevention and management of hypertension.</p><p>Multiple risk factors for hypertension have been well established, including genetic background, high sodium intake, smoking, physical inactivity, obesity, and alcohol intake.<span>^{6, 7}</span> Other potential risk factors (e.g., air pollution, psychological disorders, sleep habits, and noise exposure) have received increasing attention in recent years.<span>⁴</span> To enhance the efficacy of prevention, identifying the potential risk factors for hypertension within specific populations and developing advanced tools to improve adherence to interventions remain imperative. In addition to lifestyle modifications, pharmacological treatment is essential for managing hypertension. Moreover, hypertension may cause other diseases such as cardiovascular disease, chronic kidney disease, and dementia.<span>^{8, 9}</span> Additionally, hypertension during pregnancy is associated with adverse consequences for offspring, including preterm birth, vascular dysfunction, and cognitive impairment.<span>^{10, 11}</span> Therefore, it is important to systematically understand the current research status of hypertension and related diseases.</p><p>In this special issue, authors from the United States, United Kingdom, China, India, and Pakistan report the latest research findings on hypertension and related diseases. The issue comprises eight publications, including four original articles, two brief reports, one study protocol, and one correspondence. In summary, the aforementioned studies employed different epidemiological designs to assess the risk factors for hypertension, identify molecular biomarkers for pre-eclampsia (PE), depict the adverse impact of blood pressure on various outcomes, and provide potential evidence for hypertension management and treatment.</p><p>Zhang et al.<span>¹²</span> offered valuable ","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 2","pages":"89-91"},"PeriodicalIF":0.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.129","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical activity, long-term fine particulate matter exposure and type 2 diabetes incidence: A prospective cohort study","authors":"Qian Li,&nbsp;Fangchao Liu,&nbsp;Keyong Huang,&nbsp;Fengchao Liang,&nbsp;Chong Shen,&nbsp;Jian Liao,&nbsp;Jianxin Li,&nbsp;Chenxi Yuan,&nbsp;Xueli Yang,&nbsp;Jie Cao,&nbsp;Shufeng Chen,&nbsp;Dongsheng Hu,&nbsp;Jianfeng Huang,&nbsp;Yang Liu,&nbsp;Xiangfeng Lu,&nbsp;Dongfeng Gu","doi":"10.1002/cdt3.128","DOIUrl":"https://doi.org/10.1002/cdt3.128","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Despite the adverse effects of ambient fine particulate matter (PM_2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM_2.5 on the relationship between PA and type 2 diabetes remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long-term PM_2.5 exposure was calculated using 1-km resolution satellite-based PM_2.5 estimates. PM_2.5 exposure and PA's effect on type 2 diabetes were assessed by cohort-stratified Cox proportional hazards models, individually and in combination.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In 488,166 person-years of follow-up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM_2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM_2.5 stratification (≤65.02 µg/m³) other than in high PM_2.5 stratification (&gt;65.02 µg/m³), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66–0.85) and 1.10 (95% CI: 0.99–1.22), respectively. Similar results were observed for PA intensity. High PM_2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR = 1.79, 95% CI: 1.59–2.01 for PA volume; HR = 1.82, 95% CI: 1.64–2.02 for PA intensity).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>PA could reduce type 2 diabetes risk in low-pollution areas, but high PM_2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long-term polluted residents.</p>\u0000 </section>\u0000 </div>","PeriodicalId":32096,"journal":{"name":"Chronic Diseases and Translational Medicine","volume":"10 3","pages":"205-215"},"PeriodicalIF":0.0,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cdt3.128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141639646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}