The Prevalence of Cardio-Metabolic Conditions (Diabetes, Hypertension, and Obesity) Before and During COVID-19 and Association with Health and Sociodemographic Factors

Cardiometabolic conditions, including hypertension, diabetes, and obesity are associated with adverse health outcomes, including increased rates of hospitalization and deaths in patients who are diagnosed with COVID-19. However, little to no evidence is known currently on the cardiometabolic conditions before and during the COVID-19 pandemic. This study utilizes a nationally representative sample of adults in the United States (U.S.) to estimate the prevalence of cardiometabolic conditions, focusing on diabetes, hypertension, and obesity, and determine their prevalence and absolute and relative rates before and during COVID-19 pandemic declaration. Furthermore, the study aims to determine the association between these cardiometabolic conditions and physical activity, tobacco use, anxiety/depression, and sociodemographic characteristics among U.S. adults during the COVID-19 pandemic. Data from the 2019 (N = 5359) and 2020 (N = 3830) Health Information National Trends Surveys (HINTS) on adults were utilized. Dependent variable was cardiometabolic conditions and the main explanatory variable was response before and during the COVID-19 pandemic. We conducted weighted descriptive and multivariable logistic regression controlling for confounders such as age, sex, and intensity of physical activity. While there was a slight increase in the prevalence of cardiometabolic conditions during the pandemic (56.09%) compared to before (54.96%), there was only a slight increase in the prevalence of diabetes (18.10% vs 17.28%) and obesity (34.68% vs 34.18%) and a slight decrease in the prevalence of hypertension (36.38% vs 36.36%). Results showed an increase in the prevalence of cardiometabolic conditions among former smokers (67.91% vs 63.86%), and current cigarette smokers (59.39% vs 55.43%), current e-cigarette users (37.24% vs 28.66%), individuals with mild (59.62% vs 55.43%), or moderate (61.98% vs 57.83%) anxiety/depression, sexual minority (53.50% vs 51.12%) and heterosexual (56.45% vs 54.96%) individuals during the pandemic, compared to before the pandemic. Additionally, people with mild anxiety/depression had higher odds of cardiometabolic conditions during the pandemic (AOR = 1.55, 95% CI = 1.01, 2.38), compared to before (AOR = 1.52, 95% CI =1.06, 2.19), relative to those without anxiety/depression. Similarly, former smokers had higher odds of cardiometabolic outcomes before and during the pandemic (AOR = 1.38, 95% CI = 1.01, 1.87 vs AOR = 1.57, 95% CI = 1.10, 2.25), when compared to never smokers. Odds were lower for current e-cigarette users (AOR = 0.44, 95% CI = 0.23, 0.85) compared to never e-cigarette users before the pandemic. There were no significant differences in odds of cardiometabolic conditions between sexual minorities and heterosexual individuals before and during the pandemic. In conclusion, increased risk for adverse cardiometabolic conditions was higher for individuals with cigarette use and mental health diagnoses during the COVID-19 pandemic, suggesting the critical need for smoking cessation and programs to support behavioral health

Prevalence and Predictors of Human Immunodeficiency Virus (HIV) Testing Amongst Women of Reproductive Age in Zimbabwe

Introduction: HIV remains a leading cause of death globally, with over two-thirds of the cases in sub-Saharan Africa. Zimbabwe, a country located in East Africa, part of Sub-Saharan Africa, ranks in the top five countries with the highest prevalence of HIV in Africa (HIV prevalence in Zimbabwe estimated as 21.4% in 2019). Previous studies demonstrated HIV testing prevalence of 66.9% in East Africa. This study aimed to assess the prevalence of HIV testing amongst women of reproductive age in Zimbabwe, alongside some predictors of HIV testing amongst this population. Methods: Cross-sectional study design using the 2015 Demographic and Health Surveys (DHS) data for women aged 15-49. The prevalence of HIV testing as the outcome variable and the highest educational level, age at first sex, current marital status, and condom use as the predictor variables of interest were assessed. Descriptive statistics (frequencies, percents) and test of significance (using Chi-squared test)were conducted. Bivariate and multivariate logistic regression were completed to assess for the independent relationship between each predictor variable and HIV testing prevalence and, all predictor variables and HIV testing prevalence, respectively. Odds ratio estimates, 95% confidence intervals and p-values werereported. All analyses were performed using the Statistical Analysis System (SAS) version 9.4. The initial sample size included 9955 women. However, the effective sample size used in the statistical analysis was 7130 after accounting for missing variables. Results: About 9 in 10 women in the sample had ever been tested for HIV. Secondary education was the most prevalent highest level of education (64%). About 67% women had their first sex at age 15-19; peak incidence seen at ages 17 and 18 (15.3%). Multivariate analysis showed statistically significant associations between all independent variables and HIV testing (P-value Conclusion: Increasing highest educational level, age at first sex and condom use in Zimbabwe would likely increase the prevalence of HIV testing further. Focused education on the importance of HIV testing before the age of 15 will be beneficial in ensuring HIV testing as soon as sexual intercourse is established. Policy efforts are needed to address these HIV testing predictors. Causality is not implied

Predictors of HIV testing among reproductive-aged women in South Africa – The Demographic and Health Survey (DHS) 2016

South Africa has the highest global burden of HIV/AIDS with over 7.9 million people living with HIV/AIDS. Women and girls bear a disproportionate burden of the disease, which is potentially driven by low levels of correct HIV knowledge and high levels of gender-based violence. Our study aimed to determine the factors that influence uptake of HIV testing among reproductive aged women between 15-49 years in South Africa. Data from the 2016 (N=8514) iteration of the Demographic and Health Survey was utilized. Our outcome variable was HIV testing (yes/no) and our predictor variables were age at first sex, highest educational level, marital status, and recent condom use. We conducted descriptive statistics, chi-square analysis and T-test for our categorical and continuous variables (age at first sex), respectively. We further conducted multiple logistic regression to determine predictors of HIV testing. Frequencies, mean age at first sex, p-values, odds ratios, and 95% confidence intervals with alpha set to 0.05 were reported. Of 6489 women included in the final analysis, 5915 (91.15%) of women had ever been tested for HIV, 4964 (76.50%) and 746 (11.50%) had secondary and higher education as their highest educational level The mean age at first sex for women who had ever tested for HIV was 17.55 + 2732.7 years compared to 17.17 + 3119.7 years for women who had never tested for HIV (P\u3c0.0001). The majority of respondents were never married (N=3415,52.63%) and 1746 women (26.91%) were married. Women who used condom during the last sex were 2883 (44.43%) compared to 3606 (55.57%) women who did not. The relationship between marital status and HIV testing (P=0.0009) and condom use and HIV testing (P=0.0471) were all statistically significant. After adjusting for confounders, we found that women with primary education had a 44.4% decrease in the odds of HIV testing and women with no education had a 61% decrease, compared to women to women who had secondary education (OR = 0.556, CI= 0.429-0.719, P\u3c0.0001), (OR = 0.394, CI= 0.251-0.620, p\u3c0.0001)., Women who had higher education had a 46% increase in the odds of HIV testing compared to women who had secondary education (OR = 1.460, CI= 1.049-2.033, P=0.0249). Being married and living with partner were associated with a 59.6% and 90% increase in the odds of having been tested HIV (OR = 1.596, CI= 1.276-1.996, P\u3c0.0001) and (OR = 1.907, CI= 1.441-2.524, P\u3c0.0001) compared to women who had never been married. No longer living together/separated was associated with a 4.5 times higher odds of HIV testing (OR = 4.491, CI= 1.826-11.045, P=0.0011) among women compared to never been married. Age at first sex was not significantly associated with HIV testing in the final model (OR = 1.028, CI= 0.995-1.062, P= 0.1020). Our study suggests the need to increase basic education up to secondary level and beyond among women in South Africa to increase uptake of HIV testing and reduce the burden of HIV/AIDS

Comorbidities Predict Length of Stay Among Patients Admitted with Peripheral Artery Disease– An Analysis of The National Inpatient Sample.

The global prevalence of peripheral artery disease (PAD) is estimated to be about 120 million, making up about 25.6% of the worldwide burden of cardiovascular diseases (CVD). In the United States (U.S.), the prevalence of PAD is about 7%, representing nearly 8 million adults. There is a higher prevalence of disease in Blacks and non-Hispanic Whites, with approximately 30% of Blacks and 20% of non-Hispanic Whites developing PAD in their lifetime. The strong risk factors associated with PAD include smoking, diabetes, hypertension, age, and male sex. Our study aimed to estimate the effects of obesity, alcohol abuse, renal failure, and hypertension on patients’ length of stay (LOS) among patients admitted with a diagnosis of PAD. Using the 2012 U.S. National Inpatient Sample database, we included 336,790 patients with PAD as a separate comorbidity during their index admission. Our main outcome variable was patients’ total length of stay (LOS) during the index admission. We categorized LOS \u3c 1 into next day discharge (NDD) and LOS \u3e 1 into non-NDD. Our predictor variables were hypertension, obesity, alcohol abuse and renal failure. We ran descriptive statistics to delineate the baseline characteristics of our sample population, and bivariate analysis with t-test and chi-square analysis. Multivariable logistic regression was used to estimate odds of non-NDD given our comorbidities; obesity, hypertension, alcohol abuse, renal failure while adjusting for age, race, and sex. We reported frequencies, p-values, and odd ratios (ORs) at a 95% significance level with alpha at 0.05. Of our final sample, 54.8% were males while 45.2% were females and the mean age of patients was 71.7 + 12.8. Hypertension, obesity, alcohol abuse and renal failure were present in 75%, 12%, 3.4%, and 30.9% of patients, respectively. Majority (75%) of the patients were white, while Black and Hispanic patients made up 13.3% and 7.1%, respectively. In our adjusted model, we found that patients with hypertension had 12% lower odds of non-NDD (OR = 0.88, CI= 0.86-0.90, P\u3c0.0001) compared to those without hypertension, females had 20% increase in the odds of non-NDD compared to males (OR = 1.20, CI= 1.18-1.23, P\u3c0.0001), patients with obesity, alcohol abuse and renal failure had 39%, 43% and 45% increase in odds of non-NDD compared to those without these comorbidities. (OR = 1.39, CI= 1.34-1.44, P\u3c0.0001), (OR = 1.43, CI= 1.35-1.52, P\u3c0.0001), (OR = 1.45, CI= 1.42-1.49, P\u3c0.0001). Given the significant association between obesity, alcohol abuse, and renal failure with prolonged hospital stay in patients admitted to hospital with PAD, our study highlights the importance of adequate management of pre-existing patients\u27 comorbidities. This is expected to improve overall length of stay and total healthcare utilization and costs, among patients with PAD