Decomposition and comparative analysis of depressive symptoms between older adults living alone and with others in China.

Objective: This research dealt with investigating and measuring the contribution of the factors that impact depression in older adults living alone vs. those living with others (hereafter referred to as "not alone") in China. Design: This investigation adopts a cross-sectional research design. The dataset employed for this study comprises data from 2018 the Chinese Longitudinal Health Longevity Survey (CLHLS). Setting: The research involved data sourced from China, specifically from 23 of its provinces. From the 8th CLHLS, 12,197 older adults were selected who met the study requirements. Measures: Binary logistic regression models were established to delve into the primary factors impacting the depressive symptoms of the individuals. Furthermore, Fairlie models were employed to assess these factors between older adults living alone and those not living alone. This approach facilitated an in-depth analysis of their respective contributions. Results: It was observed that the demographic of Chinese older adults exhibited depressive symptoms at a rate of 11.92%. Older adults who resided alone (15.76%) exhibited a higher prevalence of depressive symptoms in comparison to their counterparts living in not-alone settings (11.15%). Employing Fairlie decomposition analysis, it was determined that this observed disparity in depressive symptoms, amounting to 55.33% of the overall difference, could be primarily attributed to distinct factors. This encompassed variance in marital status (20.55%), years of school (4.63%), self-reported local income status (7.25%), self-reported sleep status (17.56%), and self-reported health status (4.24%). Conclusion: The resulting data indicated that depressive symptoms exhibited an elevated prevalence in older adults living alone than in those living not alone. This discrepancy was predominantly attributed to variance in socioeconomic marital status, years of school, self-reported local income status, self-reported sleep status, and self-reported health status by living alone vs. not alone. Mitigating these influential factors could help develop targeted and meticulous intervention strategies, precisely tailored to improve the mental well-being of older adults at high risk.

Decomposition analysis of health inequalities between the urban and rural oldest-old populations in China: Evidence from a national survey.

The number of Chinese oldest-old (aged 80+) is growing rapidly and some studies have shown that the health status is unequal among older persons in different regions. However, to the best of our knowledge, no study to date has analyzed health inequalities among the oldest-old in urban and rural areas in China. This study therefore aimed to examine the correlation between health inequalities among the oldest-old in urban and rural areas of China. From the 8th wave of the Chinese Longitudinal Health Longevity Survey (CLHLS), we selected 8124 oldest-old participants who met the requirements of the study. Chi-square tests were used to analyze the distribution characteristics of indicators and a logistic model was performed to determine the factors associated with different self-rated health (SRH). The Fairlie model was adopted to decompose the causes and related contributions to health inequality. Our results found that of the Chinese oldest-old, 46.57% were in good health. Urban residents reported significantly better SRH than rural residents (50.17% vs. 45.13%). Variables associated with good and poor SRH had different distribution characteristics. The logistic model suggested that marital status, alcohol consumption, and annual income were important factors underlying the SRH differences. Our decomposition analysis indicated that 76.64% of the SRH differences were caused by observational factors, and validated that the difference in SRH between urban and rural areas was significantly (P<0.05) associated with exercise status (45.44%), annual income (37.64%), social activity status (3.75%), age (-5.27%), and alcohol consumption (-2.66%). Therefore, socioeconomic status and individual lifestyle status were the main factors underlying the health inequality between urban and rural Chinese oldest-old.

Decomposition and Comparative Analysis of the Prevalence of and Factors Associated With Smoking Between the Rural and Urban Elderly Population in China: A National Cross-Sectional Study.

This study aimed to compare and analyse the differences in smoking prevalence, and knowledge, attitudes, and factors associated with smoking between the rural and urban elderly population in China. In total, 6,966 participants aged 60 and above were included in this study, which assessed their smoking-related knowledge, attitudes, and perceptions toward tobacco control. The Chi-square test and logistic regression model were used for statistical analysis, and the Fairlie model was used for decomposition analysis. The overall prevalence of smoking was 25.6%; the rate was much higher in men than in women (overall: OR = 26.234; urban: OR = 31.260; rural: OR = 23.889). The rate of correct responses to all questions on smoking problems was significantly higher among the urban elderly than the rural elderly. Further, 64.18% of the participants supported printing photos of the health hazards of smoking on the cover of cigarette packs, and the rural elderly were more supportive of this. Moreover, only 36.52% of the participants supported increasing taxation and retail price of cigarettes; the urban elderly showed more support for this. Rules about smoking at home also played an important role, especially for families where smoking was not allowed at home, but with exceptions to the rule; however, this factor was only meaningful in urban families (urban: OR = 0.117). Through the Fairlie decomposition analysis, gender (-1.62%), age (-2.03%), region (13.68%), knowing about e-cigarettes (5.17%), rules about smoking at home (3.95%), and smoking-related knowledge scores (42.85%) were found to be associated with rural-urban disparities. This study focused on the differences in smoking between urban and rural areas in China. Smoking among the urban elderly was significantly less prevalent compared with the rural population. Factors including education, region, and smoking-related knowledge need to be addressed to reduce the gap between urban and rural health hazards in China.

Association between diet quality and obesity indicators among the working-age adults in Inner Mongolia, Northern China: a cross-sectional study.

BACKGROUND: Obesity is a major risk factor for the global burden of disease in countries that are economically developed or not. This study aimed to investigate the association between diet quality and obesity indicators applying DASH and aMed. METHODS: This cross-sectional study on adult nutrition and chronic disease in Inner Mongolia (n = 1320). Dietary data were collected using 24-h diet recall for 3 consecutive days and weighing method. DASH and aMed were used to assess the dietary quality. WC, BMI and WC-BMI were used as obesity indicators. Logistic regression models were used to examine the associations between diet quality and obesity indicators. RESULTS: Higher diet quality, assessed by DASH, was only associated with WC. The odds ratio (OR) for abdominal obesity in the highest tertile of DASH scores compared with the lowest was 0.71 (95% confidence interval (CI) 0.53, 0.96; Ptrend = 0.03). Furthermore, aMed was inversely associated with obesity indicators. OR for abdominal obesity in the highest tertile of aMed score compared with the lowest were 0.63 (95% CI 0.47, 0.87; Ptrend = 0.005) and 0.57 (95% CI 0.41, 0.77; Ptrend = 0.02) for overweight and obesity, respectively, and 0.60 (95% CI 0.44, 0.81; Ptrend = 0.02) for high obesity risk. CONCLUSIONS: Our findings suggest that dietary quality assessed using aMed is more closely associated with obesity than assessment using DASH in working-age adults in Inner Mongolia. The Mediterranean diet can be recommended as a healthy diet to control weight.

The Association between Socioeconomic Status, Smoking, and Chronic Disease in Inner Mongolia in Northern China.

The interactive associations of socioeconomic status (SES) and smoking with chronic disease were investigated with a view to expanding the evidence to inform tobacco policies and interventions in Northern China. The fifth NHSS (National Health Service Survey) 2013 in Inner Mongolia was a population-based survey of national residents, aged 15 years and older, in which multi-stage stratified cluster sampling methods were used to survey 13,554 residents. The SES was measured by scores derived from levels of education level and household annual income. Multivariate logistic regression models were performed to determine the association between SES, smoking, and chronic disease adjusted by confounders. Three thousand nine hundred and thirty-seven residents (32.29%) were identified as current smokers and 3520 residents (26.01%) had been diagnosed with chronic diseases. In the males, former smoking with low SES had the highest risk of one chronic disease, with an odds ratio (OR) of 2.505 (95% confidence interval [95% CI] (OR = 2.505, 95% CI: 1.635⁻3.837) or multiple chronic diseases (OR = 2.631, 95% CI: 1.321⁻5.243). In the females, current smoking with low SES had the highest risk of one chronic disease (OR = 3.044, 95% CI: 2.158⁻4.292). The conclusion of this study was that residents with combined ever-smoking and low SES deserved more attention in the prevention and control of chronic disease.

Prevalence of and factors associated with daily smoking among Inner Mongolia medical students in China: a cross-sectional questionnaire survey.

BACKGROUND: To date, no study on smoking behavior of medical students in Inner Mongolia has been reported. The aim of the present study was to determine the 1-month prevalence of and factors associated with daily smoking among medical students in Inner Mongolia of China, to assist interventions designed to reduce the smoking behavior of medical college students in this region. METHODS: During December 2010 and January 2011 a cross-sectional survey was conducted among medical students at the Inner Mongolia Medical College using a self-administered questionnaire. The questionnaire consisted of three sections: students' basic information, attitude on smoking behavior, and smoking status of the student daily smokers. Students who smoked every day in the last 30 days were regarded as daily smokers. Factors associated with smoking were identified using binary logistic regression analysis. RESULTS: A total of 6044 valid surveys were returned. The overall prevalence of daily smoking was 9.8% while the prevalence of daily smoking among males and females were 29.4% and 1.7%, respectively. Males in the Faculty of Medicine Information Management had the highest daily smoking rate (48.9%). Logistic regression models found that the main factors associated with daily smoking among male medical students were highest year of study (OR = 3.62; CI: 1.18-11.05); attitude towards smoking behavior Do not care about people smoking around you (OR = 2.75; CI: 2.08-3.64); and Smoking is harmful to their health (OR = 4.40; CI: 2.21-8.75). The main factor associated with daily smoking among female medical students was attitude towards smoking behavior Eliminate smoking on campus (OR = 0.11; CI: 0.06-0.23). Both for male and female medical students, there was no association between ethnicity and cigarette daily smoking. In regard to smoking status, more than 60% of daily smokers began smoking in high school, 61.3% smoked less than 5 cigarettes per day, 62.9% of the daily smokers' families opposed their smoking behavior, and after an hour of not smoking 74.6% daily smokers did not feel uncomfortable. CONCLUSIONS: Antismoking education should be further promoted in Inner Mongolia medical students, with consideration given to the factors associated with daily smoking behavior found in the present study.