Editorial
27 June 2023
Konstantinos Giannakou
, Maria Kyprianidou
, Stavri Chrysostomou
and
Costas A. Christophi
Editorial: The associations of lifestyle factors and behaviors with multimorbidity
Editors
3
Impact
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Original Research
05 May 2023
Qianqian Shen
, 7 more and
Yumei Zhang
3,232 views
1 citations
Original Research
04 May 2023
Yaoda Hu
, 11 more and
Guangliang Shan
3,690 views
2 citations
Original Research
03 May 2023
Christine Gaskell
, 2 more and
Ghizlane Bendriss
4,338 views
2 citations
Original Research
06 April 2023
Letícia Cristina Machado de Sousa
, 3 more and
Luciana Saraiva da Silva
Objective: The aim of this study was to identify patterns related to health and their association with chronic kidney disease (CKD) in the Brazilian population.
Methods: We used data from the National Health Survey (PNS), 2019. Participants were interviewed and answered questions related to socioeconomic and demographic information (gender, age, education, race/color), health conditions (presence of hypertension, diabetes mellitus, hyperlipidemia, cardiovascular disease, overweight and CKD) and lifestyle (smoking, alcohol consumption, physical activity and food consumption). To identify patterns, we used exploratory factor analysis. We performed logistic regression models to describe the association of CKD with each pattern in crude models and adjusted for gender, age group, education level and race/color.
Results: A total of 90,846 individuals were evaluated. The prevalence of CKD was 1.49% (95% CI: 1.3–1.6). Three health-related patterns – metabolic factors, behavioral risk factors and behavioral protective factors – were identified by factor analysis. Metabolic factors were determined by the presence of hypertension, diabetes mellitus, hyperlipidemia and cardiovascular diseases. Behavioral risk factors were determined by smoking, alcohol consumption, regular consumption of soft drinks, sweets and artificial juices, and high salt consumption. The protective behavioral factors were established by the practice of physical activity and regular consumption of vegetables and fruits. Participants of the highest tertile for metabolic factors were more likely to have CKD in the adjusted model (OR = 3.61, 95% CI: 2.69–4.85), when compared to those of the lower tertile.
Conclusion: The pattern referring to metabolic factors was associated with a higher chance of presenting CKD.
Original Research
27 March 2023
Ava Arshadipour
, 4 more and
Annette Peters
2,954 views
4 citations
Original Research
17 March 2023
Objectives: This study aimed to examine the cross-sectional and longitudinal association between multimorbidity and memory-related diseases (MDs) among Chinese middle-aged and older adults.
Methods: This study included 8,338 subjects who participated in the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression and Cox proportional hazards regression models were used to explore the association and effect of multimorbidity on MDs.
Results: The overall prevalence of MDs was 2.52%, and the mean multimorbidity number was 1.87. In a cross-sectional analysis, compared with the no multimorbidity group, groups of multimorbidity with four or more non-communicable diseases (NCDs) were more likely to have MDs (OR: 6.49, 95%CI: 4.35–9.68). Within 2.7 years of follow-up, 82 cases of MDs (1.12%) were reported, and participants with multimorbidity were more likely to have new-onset MDs than participants without multimorbidity (HR: 2.93, 95%CI: 1.74–4.96).
Conclusion: Multimorbidity is associated with MDs among Chinese middle-aged and older adults. This relationship gradually strengthens with the severity of multimorbidity, which indicates that early prevention for people with multimorbidity may reduce the risk of MDs.
Original Research
01 February 2023
Yuanjie Zheng
, 6 more and
Weiwei Liu
Original Research
20 February 2023
Mingjun Chen
, 11 more and
Siying Wu
3,887 views
4 citations
Original Research
09 January 2023
Changcong Wang
, 2 more and
Dongmei Mu
Objective: With advances in medical diagnosis, more people are diagnosed with more than one disease. The damage caused by different diseases varies, so relying solely on the number of diseases to represent multimorbidity is limited. The Charlson comorbidity index (CCI) is widely used to measure multimorbidity and has been validated in various studies. However, CCI's demographic and behavioral risk factors still need more exploration.
Methods: We conduct multivariate logistic regression analysis and restricted cubic splines to examine the influence factors of CCI and the relationship between covariates and risk of CCI, respectively. Our research employs the Multivariate Imputation by Chained Equations method to interpolate missing values. In addition, the CCI score for each participant is calculated based on the inpatient's condition using the International Classification of Diseases, edition 10 (ICD10). Considering the differences in the disease burden between males and females, the research was finally subgroup analyzed by sex.
Results: This study includes 5,02,411 participants (2,29,086 female) with CCI scores ranging from 0 to 98. All covariates differed between CCI groups. High waist-hip ratio (WHR) increases the risk of CCI in both males [OR = 19.439, 95% CI = (16.261, 23.241)] and females [OR = 12.575, 95% CI = (11.005, 14.370)], and the effect of WHR on CCI is more significant in males. Associations between age, Body Mass Index (BMI) and WHR, and CCI risk are J-shaped for all participants, males, and females. Concerning the association between Townsend deprivation index (TDI) and CCI risk, the U-shape was found in all participants and males and varied to a greater extent in males, but it is a J-shape in females.
Conclusions: Increased WHR, BMI, and TDI are significant predictors of poor health, and WHR showed a greater role. The impact of deprivation indices on health showed differences by sex. Socio-economic factors, such as income and TDI, are associated with CCI. The association of social status differences caused by these socioeconomic factors with health conditions should be considered. Factors might interact with each other; therefore, a comprehensive, rational, and robust intervention will be necessary for health.