This study examined the customers' perception on Home Meal Replacement (HMR) products. Specifically, there were three research objectives: 1. to identify the customers' HMR purchase patterns and preference of HMR product development; 2. to identify the attributes of the HMR products that the customers perceive; and 3. to examine the customers' level of expectation-confirmation toward HMR product attributes according to the demographic characteristics. This study employed a self-administered survey that was distributed online from November 21~24, 2017. The sample of the study was the customers who had purchased HMR products in the six months prior to taking the survey. A total of 553 respondents completed the survey, which was used for data analysis. The results revealed the customers' HMR purchase patterns. The major HMR product type of purchase was ready to heat (52.6%), while the main reason for purchasing HMR products was convenience (83.2%). For the differences in the level of expectation-confirmation toward HMR products in accordance with the demographic characteristics of customers, the results indicated that there was a difference in the expectation-confirmation level according to age, whereas the respondents aged 29 and under showed a significantly higher level of time-saving for the preparation and ease of cooking (P < 0.05) than the other age groups. In addition, there was a significant difference in the expectation-confirmation level for saving meal preparation time (P < 0.05) and convenience (P < 0.01) among the customer's occupation. These findings can provide the basis for a strategy for developing HMR products reflecting the rapidly changing customers' needs. HMR products should be developed according to the specific target market, as the study indicated that the respective customer segmentation resulted in a difference in their expectation toward HMR products.
Cooking ; Hot Temperature ; Humans ; Meals ; Occupations ; Statistics as Topic ; Surveys and Questionnaires

BACKGROUND: The main factor limiting the increase in brain dead organ donors is low consent rates for organ donation. METHODS: This study is a retrospective analysis of donor records of Korea Organ Donation Agency from 2013 to 2015. Factors related before providing information about organ donation and process of explaining organ donation were analyzed. RESULTS: Donor gender, marital status, religious affiliation, residence area, knowledge of patients' wishes, understanding of brain death status, and the referring system, providing initial information about donation and initial medical staff providing information about donation had a significant influence on decision to donate. Organ donation greatly increased when the donor family knew the patient's intent to donate. As the degree of family understanding of brain death status and the referring system increased, organ donation rate significantly increased. CONCLUSIONS: Providing sufficient information about brain death during the period of delivering medical services as well as activating campaign and public education are essential to improving the positive attitude toward organ donation.
Brain Death ; Education ; Humans ; Korea ; Marital Status ; Medical Staff ; Retrospective Studies ; Tissue and Organ Procurement* ; Tissue Donors

Although obesity is a risk factor for infection, whether it has the same effect on coronavirus disease 2019 (COVID-19) need confirming. We conducted a retrospective propensity score matched case-control study to examine the association between obesity and COVID-19. This study included data from the Nationwide COVID-19 Registry and the Biennial Health Checkup database, until May 30, 2020. We identified 2,231 patients with confirmed COVID-19 and 10-fold-matched negative test controls. Overweight (body mass index [BMI] 23 to 24.9 kg/m2; adjusted odds ratio [aOR], 1.16; 95% confidence interval [CI], 1.1.03 to 1.30) and class 1 obesity (BMI 25 to 29.9 kg/m2; aOR, 1.27; 95% CI, 1.14 to 1.42) had significantly increased COVID-19 risk, while classes 2 and 3 obesity (BMI ≥30 kg/m2) showed similar but non-significant trend. Females and those <50 years had more robust association pattern. Overweight and obesity are possible risk factors of COVID-19.

Purpose: Long-term safety of pregnancy after breast cancer (BC) remains controversial, especially with respect to BC biological subtypes. Methods: We analyzed a population-based retrospective cohort with BC from 2002 to 2017. Patient-level 1:1 matching was performed between pregnant and nonpregnant women. The study population was categorized into 6 biological subtypes based on the combination of prescribed therapies. Subanalyses were performed considering the time to pregnancy after BC diagnosis, systemic therapy, and pregnancy outcomes. Results: We identified 544 matched women with BC, who were assigned to the pregnant (cases, n = 272) or nonpregnant group (controls, n = 272) of similar characteristics, adjusted for guaranteed bias. These patients were followed up for 10 years, or disease and mortality occurrence after the diagnosis of BC. Survival estimates were calculated. The actuarial 10-year overall survival (OS) rates were 97.4% and 91.9% for pregnant and nonpregnant patients, respectively. The pregnant group showed significantly better OS (adjusted hazard ratio [aHR], 0.29; 95% confidence interval [CI], 0.12–0.68; P = 0.005) and did not have a significantly inferior disease-free survival (aHR, 1.10; 95% CI, 0.61–1.99; P = 0.760). Conclusion Consistent outcomes were observed in every subgroup analysis. Our observational data provides reassuring evidence on the long-term safety of pregnancy in young patients with BC regardless of the BC biological subtype.

Background: Although coronavirus disease 2019 (COVID-19) is a viral infection, antibiotics are often prescribed due to concerns about accompanying bacterial infection. Therefore, we aimed to analyze the number of patients with COVID-19 who received antibiotic prescriptions, as well as factors that influenced antibiotics prescription, using the National Health Insurance System database. Methods: We retrospectively reviewed claims data for adults aged ≥ 19 years hospitalized for COVID-19 from December 1, 2019 to December 31, 2020. According to the National Institutes of Health guidelines for severity classification, we calculated the proportion of patients who received antibiotics and the number of days of therapy per 1,000 patient-days. Factors contributing to antibiotic use were determined using linear regression analysis. In addition, antibiotic prescription data for patients with influenza hospitalized from 2018 to 2021 were compared with those for patients with COVID-19, using an integrated database from Korea Disease Control and Prevention Agency-COVID19-National Health Insurance Service cohort (K-COV-N cohort), which was partially adjusted and obtained from October 2020 to December 2021. Results: Of the 55,228 patients, 46.6% were males, 55.9% were aged ≥ 50 years, and most patients (88.7%) had no underlying diseases. The majority (84.3%; n = 46,576) were classified as having mild-to-moderate illness, with 11.2% (n = 6,168) and 4.5% (n = 2,484) having severe and critical illness, respectively. Antibiotics were prescribed to 27.3% (n = 15,081) of the total study population, and to 73.8%, 87.6%, and 17.9% of patients with severe, critical, and mild-to-moderate illness, respectively. Fluoroquinolones were the most commonly prescribed antibiotics (15.1%; n = 8,348), followed by third-generation cephalosporins (10.4%; n = 5,729) and beta-lactam/beta-lactamase inhibitors (6.9%; n = 3,822). Older age, COVID-19 severity, and underlying medical conditions contributed significantly to antibiotic prescription requirement. The antibiotic use rate was higher in the influenza group (57.1%) than in the total COVID-19 patient group (21.2%), and higher in severe-to-critical COVID-19 cases (66.6%) than in influenza cases. Conclusion Although most patients with COVID-19 had mild to moderate illness, more than a quarter were prescribed antibiotics. Judicious use of antibiotics is necessary for patients with COVID-19, considering the severity of disease and risk of bacterial co-infection.

Despite the widespread impact of the severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019, COVID-19) and vaccination in South Korea, our understanding of kidney diseases following these events remains limited. We aimed to address this gap by investigating the characteristics of glomerular diseases following the COVID-19 infection and vaccination in South Korea. Methods: Data from multiple centers were used to identify de novo glomerulonephritis (GN) cases with suspected onset following COVID-19 infection or vaccination. Retrospective surveys were used to determine the COVID-19–related histories of patients who were initially not implicated. Bayesian structural time series and autoregressive integrated moving average models were used to determine causality. Results: Glomerular diseases occurred shortly after the infection or vaccination. The most prevalent postinfection GN was podocytopathy (42.9%), comprising primary focal segmental glomerulosclerosis and minimal change disease, whereas postvaccination GN mainly included immunoglobulin A nephropathy (IgAN; 57.9%) and Henoch-Schönlein purpura nephritis (HSP; 15.8%). No patient progressed to end-stage kidney disease. Among the patients who were initially not implicated, nine patients with IgAN/HSP were recently vaccinated against COVID-19. The proportion of glomerular diseases changed during the pandemic in South Korea, with an increase in acute interstitial nephritis and a decrease in pauci-immune crescentic GN. Conclusion: This study showed the characteristics of GNs following COVID-19 infection or vaccination in South Korea. Understanding these associations is crucial for developing effective patient management and vaccination strategies. Further investigation is required to fully comprehend COVID-19’s impact on GN.

Background: The coronavirus disease 2019 (COVID-19) pandemic is an emerging threat worldwide. It remains unclear how comorbidities affect the risk of infection and severity of COVID-19. Methods: This is a nationwide retrospective case-control study of 219,961 individuals, aged 18 years or older, whose medical costs for COVID-19 testing were claimed until May 15, 2020. COVID-19 diagnosis and infection severity were identified from reimbursement data using diagnosis codes and on the basis of respiratory support use, respectively. Odds ratios (ORs) were estimated using multiple logistic regression, after adjusting for age, sex, region, healthcare utilization, and insurance status. Results: The COVID-19 group (7,341 of 219,961) was young and had a high proportion of female. Overall, 13.0% (954 of 7,341) of the cases were severe. The severe COVID-19 group had older patients and a proportion of male ratio than did the non-severe group. Diabetes (odds ratio range [ORR], 1.206–1.254), osteoporosis (ORR, 1.128–1.157), rheumatoid arthritis (ORR, 1.207–1.244), substance use (ORR, 1.321–1.381), and schizophrenia (ORR, 1.614–1.721) showed significant association with COVID-19. In terms of severity, diabetes (OR, 1.247; 95% confidential interval, 1.009–1.543), hypertension (ORR, 1.245–1.317), chronic lower respiratory disease (ORR, 1.216–1.233), chronic renal failure, and end-stage renal disease (ORR, 2.052–2.178) were associated with severe COVID-19. Conclusion We identified several comorbidities associated with COVID-19. Health care workers should be more careful while diagnosing and treating COVID-19 when patients have the abovementioned comorbidities.