Objective  To explore the effects of daily mean temperature (℃), average daily air pressure (hPa), humidity (%), wind speed (m/s), particulate matter (PM) 2.5 (μg/m³) and PM10 (μg/m³) on the admission rate of chronic kidney disease (CKD) patients admitted to the Second Affiliated Hospital of Harbin Medical University in Harbin and to identify the indexes and lag days that impose the most critical influence.  Methods  The R language Distributed Lag Nonlinear Model (DLNM), Excel, and SPSS were used to analyze the disease and meteorological data of Harbin from 01 January 2010 to 31 December 2019 according to the inclusion and exclusion criteria.  Results  Meteorological factors and air pollution influence the number of hospitalizations of CKD to vary degrees in cold regions, and differ in persistence or delay. Non-optimal temperature increases the risk of admission of CKD, high temperature increases the risk of obstructive kidney disease, and low temperature increases the risk of other major types of chronic kidney disease. The greater the temperature difference is, the higher its contribution is to the risk. The non-optimal wind speed and non-optimal atmospheric pressure are associated with increased hospital admissions. PM2.5 concentrations above 40 μg/m³ have a negative impact on the results.  Conclusion  Cold region meteorology and specific environment do have an impact on the number of hospital admissions for chronic kidney disease, and we can apply DLMN to describe the analysis.

Because of the overbearing low temperature, cold areas increase the morbidity and mortality of chronic non-communicable diseases (chronic diseases) in exposed populations. With the growth of the aging population and the superposition of lifestyle risk factors, the number of people with chronic diseases in cold areas is climbing, and the family and social burdens are rising. These health-threatening circumstances in the cold areas render the general practitioners to face serious challenges and difficulties in the community management of chronic diseases. This paper summarizes the current situation of chronic disease management in cold areas and explores the relevant management models so as to provide a useful reference for regional health construction, graded diagnosis and treatment, and prevention and control of chronic diseases in China.

Osteoarthritis is a common chronic irreversible joint disease characterized by degenerative changes of articular cartilage and secondary hyper osteogeny. Knee osteoarthritis(KOA) affects not only the articular cartilage, but also the entire joint, including subchondral bone, joint capsule, synovial membrane, meniscus, ligaments, periarticular muscles, and tendons. The primary aim of treatment is to relieve symptoms, delay joint degeneration, and maximally maintain patient's quality of life. There are many risk factors contributing to the development of KOA, including climate. This review will discuss the relationship between climate in cold region and KOA and the possibility of modifying risk factors such as the environment for the prevention and treatment of KOA.

  Background   Previous studies have established a link between fluctuations in climate and increased mortality due to coronary artery disease (CAD). However, there remains a need to explore and clarify the evidence for associations between meteorological changes and hospitalization incidences related to CAD and its subtypes, especially in cold regions. This study aimed to systematically investigate the relationship between exposure to meteorological changes, air pollutants, and hospitalization for CAD in cold regions.   Methods   We conducted a cross-sectional study using hospitalization records of 86, 483 CAD patients between January 1, 2009, and December 31, 2019. Poisson regression analysis, based on generalized additive models, was applied to estimating the influence of hospitalization for CAD.   Results   Significant associations were found between low ambient temperature [-10℃, RR= 1.65; 95% CI: (1.28–2.13)] and the incidence of hospitalization for CAD within a lag of 0–14 days. Furthermore, O₃ [95.50 μg/m³, RR = 12; 95% CI: (1.03–1.21)] and NO₂ [48.70 μg/m³, RR = 1.0895% CI: (1.01–1.15)] levels were identified as primary air pollutants affecting the incidence of CAD, ST-segment-elevation myocardial infarction (STEMI), and non-STEMI (NSTEMI) within the same lag period. Furthermore, O₃ [95.50 μg/m³, RR = 1.12; 95% CI: (1.03–1.21)] and NO₂ [48.70 μg/m³, RR = 1.0895% CI: (1.01–1.15)] levels were identified as primary air pollutants affecting the incidence of CAD, ST-segment-elevation myocardial infarction (STEMI), and non-STEMI (NSTEMI) within the same lag period. The effect curve of CAD hospitalization incidence significantly increased at lag days 2 and 4 when NO₂ and O₃ concentrations were higher, with a pronounced effect at 7 days, dissipating by lag 14 days. No significant associations were observed between exposure to PM, SO₂, air pressure, humidity, or wind speed and hospitalization incidences due to CAD and its subtypes.   Conclusion   Our findings suggest a positive correlation between short-term exposure to low ambient temperatures or air pollutants (O₃ and NO₂) and hospitalizations for CAD, STEMI, and NSTEMI. These results could aid the development of effective preparedness strategies for frequent extreme weather events and support clinical and public health practices aimed at reducing the disease burden associated with current and future abnormal weather events.