Global Population Aging, National Development Level, and Vulnerability to the Pandemic

Regional disparities, age-related changes and sex-related differences in knee osteoarthritis

BACKGROUND

The objective of the study is to analyse the regions, age and sex differences in the incidence of knee osteoarthritis (KOA).

METHODS

Data were extracted from the global burden of diseases (GBD) 2019 study, including incidence, years lived with disability (YLD), disability-adjusted life-years (DALYs) and risk factors. Estimated annual percentage changes (EAPCs) were calculated to quantify the temporal trends in age standardized rate (ASR) of KOA. Paired t-test, paired Wilcoxon signed-rank test and spearman correlation were performed to analyze the association of sex disparity in KOA and socio-demographic index (SDI).

RESULTS

There were significant regional differences in the incidence of knee osteoarthritis. In 2019, South Korea had the highest incidence of knee osteoarthritis (474.85,95%UI:413.34-539.64) and Thailand had the highest increase in incidence of knee osteoarthritis (EAPC = 0.56, 95%CI = 0.54-0.58). Notably, higher incidence, YLD and DALYs of knee osteoarthritis were associated with areas with a high socio-demographic index (r = 0.336, p < 0.001; r = 0.324, p < 0.001; r = 0.324, p < 0.001). In terms of age differences, the greatest increase in the incidence of knee osteoarthritis was between the 35-39 and 40-44 age groups. (EAPC = 0.52, 95%CI = 0.40-0.63; 0.47, 95%CI = 0.36-0.58). In addition, there were significant sex differences in the disease burden of knee osteoarthritis (P < 0.001).

CONCLUSIONS

The incidence of knee osteoarthritis is significantly different with regions, age and sex.

Evaluating the association between anthropometric parameters and successful aging in older adults

This study aimed to determine the relationship between successful aging (SA) and anthropometric parameters in older adults. We used body mass index (BMI), waist circumference, hip circumference, and calf circumference to reflect anthropometric parameters. SA was assessed by the following five aspects: self-rated health, self-rated psychological status or mood, cognitive function, activities of daily life, and physical activity. Logistic regression analyses were employed to examine the relationship between anthropometric parameters and SA. Results showed that larger BMI, waist circumference, and calf circumference are related to a higher prevalence of SA in older women; greater waist circumference and calf circumference are associated with a higher rate of SA in old-old adults. These findings suggest that the greater BMI, waist circumference, hip circumference, and calf circumference are associated with a higher rate of SA in older adults, and the associations are influenced to some extent by the sex and age.

Disparity in Occupational Health Risk During the Pandemic: Potential Misestimation and Its Implications for Health Policies

OBJECTIVE

This study clarifies potential misestimation of occupational risk caused by the dichotomy of frontline essential and nonessential occupations in prior studies.

METHODS

The linear regression is used to investigate the occupational risk in terms of incidence rate, hospitalization, and mortality on community level during the pandemic.

RESULTS

Overall, frontline essential occupations were positively associated with incidence rate, hospitalization, and mortality (156.06, 18.47, and 3.49; P < 0.01). Among essential occupations, however, education, training, and library occupations were negatively associated with them, whereas transportation, protective service, food preparation, and serving occupations were insignificantly associated with them. Moreover, among nonessential occupations, building and grounds cleaning, construction, and extraction occupations were positively associated with them.

CONCLUSION

The dichotomy of frontline essential and nonessential occupations can bring overestimation and underestimation of occupational risk during the COVID-19 pandemic.

Population distribution by ethnicities and the disparities in health risk and coping in the United States during the pandemic: the spatial and time dynamics

Background

As a multi-ethnic country, the US is increasingly concerned about ethnic minorities facing disproportionate health risks of the coronavirus disease 2019 (COVID-19) pandemic. This study attempted to provide a macro picture of the associations between population distribution by ethnicity and the vulnerability to COVID-19 in terms of infection risk and vaccination coverage in the US.

Methods

This study used multi-source data from New York Times, County Health Rankings & Roadmap Program (2020), and the Center for Disease Control and Prevention. Multiple linear regressions were performed at equidistant time points (May 2020-Jan 2021, with one-month interval between each time point) to reveal the association between population distribution by ethnicities and the infection risk and the dynamics over time. Besides, multiple linear regressions were also conducted at equidistant time points (Jan 2021-Aug 2021) to reveal whether health disparities between ethnicities would hold true for the COVID-19 vaccination coverage (in total population, and among those > 12, > 18, and > 65 years of age).

Results

Both the COVID-19 confirmed cases (population standardized) and the vaccination coverage (in total population, and among those > 12, > 18, and > 65 years of age) were significantly associated with the population distribution by ethnicity (e.g., population percentage of ethnic minorities). Above associations were statistically significant for non-Hispanic blacks and Hispanics, but not for Asian Americans.

Conclusions

A proportion of socioeconomically-disadvantageous population could be a key intuitive reflection of the risk level of this public health crisis. The policy focusing on the vulnerable population is important in this pandemic.