METHODS: A group of healthcare university students completed the RSES across three waves: baseline, 1-week follow-up, and 15-week follow-up. A total of 481 valid responses were collected through the three-wave data collection process. Exploratory factor analysis (EFA) was performed on the baseline data to explore the potential factorial structure, while confirmatory factor analysis (CFA) was performed on the follow-up data to determine the best-fit model. Additionally, the cross-sectional and longitudinal measurement invariances were tested to assess the measurement properties of the RSES for different groups, such as gender and age, as well as across different time points. Convergent validity was assessed against the Self-Rated Health Questionnaire (SRHQ) using Spearman's correlation. Internal consistency was examined using Cronbach's alpha and McDonald's omega coefficients, while test-retest reliability was assessed using intraclass correlation coefficient.
RESULTS: The results of EFA revealed that Items 5, 8, and 9 had inadequate or cross-factor loadings, leading to their removal from further analysis. Analysis of the remaining seven items using EFA suggested a two-factor solution. A comparison of several potential models for the 10-item and 7-item RSES using CFA showed a preference for the 7-item form (RSES-7) with two factors. Furthermore, the RSES-7 exhibited strict invariance across different groups and time points, indicating its stability and consistency. The RSES-7 also demonstrated adequate convergent validity, internal consistency, and test-retest reliability, which further supported its robustness as a measure of self-esteem.
CONCLUSIONS: The findings suggest that the RSES-7 is a psychometrically sound and brief self-report scale for measuring self-esteem in the Chinese context. More studies are warranted to further verify its usability.
METHODS: The Prospective Urban-Rural Epidemiology study is a large, longitudinal population study done in 21 countries of varying incomes and sociocultural settings. We enrolled an unbiased sample of households, which were eligible if at least one household member was aged 35-70 years. Height was measured in a standardized manner, without shoes, to the nearest 0.1 cm. During a median follow-up of 10.1 years (interquartile range 8.3-12.0), we assessed the risk of all-cause mortality, major cardiovascular events and cancer.
RESULTS: A total of 154 610 participants, enrolled since January 2003, with known height and vital status, were included in this analysis. Follow-up event data until March 2021 were used; 11 487 (7.4%) participants died, whereas 9291 (6.0%) participants had a major cardiovascular event and 5873 (3.8%) participants had a new diagnosis of cancer. After adjustment, taller individuals had lower hazards of all-cause mortality [hazard ratio (HR) per 10-cm increase in height 0.93, 95% confidence interval (CI) 0.90-0.96] and major cardiovascular events (HR 0.97, 95% CI 0.94-1.00), whereas the hazard of cancer was higher in taller participants (HR 1.23, 95% CI 1.18-1.28). The interaction p-values between height and country-income level for all three outcomes were <0.001, suggesting that the association with height varied by country-income level for these outcomes. In low-income countries, height was inversely associated with all-cause mortality (HR 0.88, 95% CI 0.84-0.92) and major cardiovascular events (HR 0.87, 95% CI 0.82-0.93). There was no association of height with these outcomes in middle- and high-income countries. The respective HRs for cancer in low-, middle- and high-income countries were 1.14 (95% CI 0.99-1.32), 1.12 (95% CI 1.04-1.22) and 1.20 (95% CI 1.14-1.26).
CONCLUSIONS: Unlike high- and middle-income countries, tall stature has a strong inverse association with all-cause mortality and major cardiovascular events in low-income countries. Improved childhood physical development and advances in population-wide cardiovascular treatments in high- and middle-income countries may contribute to this gap. From a life-course perspective, we hypothesize that optimizing maternal and child health in low-income countries may improve rates of premature mortality and cardiovascular events in these countries, at a population level.
OBJECTIVE: This systematic review aimed to review epidemiological reports to determine the prevalence of MCI and its associated risk factors in LMICs.
METHODS: Medline, Embase, and PsycINFO were searched from inception until November 2019. Eligible articles reported on MCI in population or community-based studies from LMICs and were included as long as MCI was clearly defined.
RESULTS: 5,568 articles were screened, and 78 retained. In total, n = 23 different LMICs were represented; mostly from China (n = 55 studies). Few studies were from countries defined as lower-middle income (n = 14), low income (n = 4), or from population representative samples (n = 4). There was large heterogeneity in how MCI was diagnosed; with Petersen criteria the most commonly applied (n = 26). Prevalence of amnesic MCI (aMCI) (Petersen criteria) ranged from 0.6%to 22.3%. Similar variability existed across studies using the International Working Group Criteria for aMCI (range 4.5%to 18.3%) and all-MCI (range 6.1%to 30.4%). Risk of MCI was associated with demographic (e.g., age), health (e.g., cardio-metabolic disease), and lifestyle (e.g., social isolation, smoking, diet and physical activity) factors.
CONCLUSION: Outside of China, few MCI studies have been conducted in LMIC settings. There is an urgent need for population representative epidemiological studies to determine MCI prevalence in LMICs. MCI diagnostic methodology also needs to be standardized. This will allow for cross-study comparison and future resource planning.