Sociodemographic and lifestyle determinants of multimorbidity among community-dwelling older adults: findings from 346,760 SHARE participants

Ni, Wenqing; Yuan, Xiaojie; Zhang, Yan; Zhang, Hongmin; Zheng, Yijing; Xu, Jian

doi:10.1186/s12877-023-04128-1

Cited by 11 publications

(5 citation statements)

References 42 publications

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“…The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, which recruited participants aged 65 years and older who had attended the Older Adult Health Management Project of the National Basic Public Health Service in Shenzhen since 2018 [ 12 ]. New recruitment and follow-up surveys take place every year.…”

Section: Methodsmentioning

confidence: 99%

“…Detailed items and data collection methods of comprehensive health assessment have been described in previous publications [ 12 , 13 ]. In brief, sociodemographic characteristics, lifestyle, and health-related parameters were collected by a structured questionnaire [ 13 ], including sex (male, female), age, educational level (illiteracy, primary school, junior high school and above), marital status (unmarried, divorced, widowed, married), occupation, drinking status (never, occasionally, often), smoking status (never a smoker, ex-smoker, current smoker), exercise (no exercise, occasional exercise, regular exercise), self-assessment of health status (unsatisfactory, satisfactory), self-care ability (good, poor), emotional status screening (negative, positive), and the total scores of the AD8 scale and category of each question, namely A1–A8 (negative, positive).…”

Section: Methodsmentioning

confidence: 99%

“…Body mass index (BMI) was calculated by dividing the participants’ body weight by the square of their height. Electrocardiography measurements were taken to measure the heart rate and check for heart abnormalities [ 12 ]. A fasting blood sample of the participants was collected to obtain information on the levels of hemoglobin (HB), white blood cells (WBCs), platelets, serum uric acid, serum creatinine, alanine aminotransferase, glutamic oxalacetic minotransferase, total bilirubin, total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, fasting plasma glucose and carcinoembryonic antigen [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

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Community screening for dementia among older adults in China: a machine learning-based strategy

Zhang,

Xu,

Zhang

et al. 2024

BMC Public Health

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Background Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). Methods The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models. Results The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference. Conclusions The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Community screening for dementia among older adults in China: a machine learning-based strategy

Zhang,

Xu,

Zhang

et al. 2024

BMC Public Health

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“…As reported by Ghazi et al, a patient's socioeconomic status and type of healthcare are independently associated with CKD prevalence regardless of the patient's age [10]. However, socioeconomic status can strongly impact lifestyle [11,12] and disease awareness, especially in older people [13]. Theoretically, more accessible access to nephrological care without cost should reduce care disparity, at least in the more symptomatic phase of CKD.…”

Section: Introductionmentioning

confidence: 91%

Stage 5 Chronic Kidney Disease: Epidemiological Analysis in a NorthEastern District of Italy Focusing on Access to Nephrological Care

Martino,

Fanton,

Zanetti

et al. 2024

JCM

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Background: We conducted a retrospective epidemiological study about the prevalence of stage 5 chronic kidney disease (CKD) in a high-income district, comparing some demographic characteristics and outcomes of those patients who had nephrological consultations and those who had not. Results: In a district of 400,000 adult subjects in 2020, 925 patients had an estimated glomerular filtration rate (eGFR) under 15 mL/min and CKD. In the same period, 747 (80.4%) patients were assessed by nephrologists, while 178 (19.6%) were not. Age (88 vs. 75, p < 0.0001), female gender (66.3% vs. 47%, p < 0.001), and eGFR (12 vs. 9 mL/min, p < 0.001) were significantly different in the patients assessed by a nephrologist as compared those who did not have nephrological care. Furthermore, unfollowed CKD patients had a significantly higher death rate, 83.1% versus 14.3% (p < 0.0001). Conclusions: About 20% of ESKD patients did not receive a nephrologist consultation. Older people and women were more likely not to be referred to nephrology clinics. Unfollowed patients with stage 5 CKD had a significantly higher death rate.

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“…Poor lifestyle habits are pervasive among community-dwelling seniors and their caregivers. 26 , 27 At preoperative visit, questionnaires aimed at stratifying older patients on the basis of their risk for perioperative complications contain questions on nutrition, physical function, and mental health, 28 , 29 with the ERAS team comprising dietitians and physiotherapists to deliver evidence-based practice. The habits to promote are therefore those pertaining the HEPAS.…”

Section: Conceptual Scenariomentioning

confidence: 99%

Why Treat Patients with a Major Orthopaedic Surgery Only to Send Them Back to the Vulnerable Conditions That Made Them Sick in the First Place? A Conceptual Scenario to Improve Patient’s Journey

Briguglio,

Cordani,

Langella

et al. 2023

IJGM

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Individuals with severe cartilage degeneration of the hip or knee or collapsed vertebrae that cause spine deformities can suffer from joint and neuropathic pain in the back, disuse of the affected limb, and restriction of movements. Surgical intervention is the most widespread and successful solution to date. There is a general belief that eating healthy and staying physically and mentally active might have a preventive role against musculoskeletal disease occurrence, while instead, we are more certain of the benefits deriving from a healthy diet and exercise therapy after major orthopaedic procedures. These aspects are in fact vital components in enhanced recovery after surgery programmes. However, they are applied in hospital settings, are often centre-dependent, and lack primary and tertiary preventive efficacy since end once the patient is discharged. There is the lack of initiatives at the territorial level that ensure a continuum in the patient’s journey towards orthopaedic surgery, home transition, and a healthy and long-lasting life. The expert panel advocates the integration of an intermediate lifestyle clinic that promotes healthy eating, physical activity, and sleep hygiene. In this facility directed by professionals in enhancing recovery after surgery, patients can be referred after the surgical indication and before home discharge. Surgery is in fact a moment when individuals are more curious to do their best to heal and stay healthy, representing a timepoint and opportunity for educating patients on how lifestyle changes may optimise not only their surgical recovery but also long-term future health state.

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Sociodemographic and lifestyle determinants of multimorbidity among community-dwelling older adults: findings from 346,760 SHARE participants

Cited by 11 publications

References 42 publications

Community screening for dementia among older adults in China: a machine learning-based strategy

Community screening for dementia among older adults in China: a machine learning-based strategy

Stage 5 Chronic Kidney Disease: Epidemiological Analysis in a NorthEastern District of Italy Focusing on Access to Nephrological Care

Why Treat Patients with a Major Orthopaedic Surgery Only to Send Them Back to the Vulnerable Conditions That Made Them Sick in the First Place? A Conceptual Scenario to Improve Patient’s Journey

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