Gender difference in psychogeriatric disorders

Association between retirement age and depressive symptoms among Korean retirees: Results from Korean Retirement and Income Panel Study

BACKGROUND

The effective age of retirement in South Korea is higher than the average of Organization for Economic Co-operation and Development (OECD) countries. Early retirement in Asia may affect mental health differently compared to western countries. Thus, we examined the association between retirement age and depressive symptoms among South Korean retirees.

METHODS

We used data from the 2011, 2013, 2015, 2017, and 2019 Korean Retirement and Income Panel Study, including a total of 2998, 3152, 3203, 3154, and 3055 participants, respectively. We excluded those younger than 50 years, non-retirees, those without information on the Center for Epidemiological Studies-Depression (CES-D) scale, and those with other missing values. We used a generalized estimating equation model to identify the association between retirement age and depressive symptoms measured using the CES-D.

RESULTS

Participants who retired at age < 50 years had significantly higher CES-D scores (β = 1.764, P = 0.0003) compared to those who retired at age ≥ 70 years. The negative effects of early retirement on depressive symptoms were greater among male participants, heads of households, young involuntary retirees, those who retired within the past 20 years, and those who had no difficulties in activities of daily living.

LIMITATIONS

Since we evaluated the association between retirement age and depressive symptoms in one direction, there is a possibility of reverse causality.

CONCLUSION

Our findings highlight the importance of managing depressive symptoms in early retirees, especially young involuntary retirees and those burdened with family care.

Informal caregiver's socio demographic profile for community-dwelling women and men with mild to moderate Alzheimer's disease, compliance, and satisfaction to treatment: A post-hoc analysis of the AXEPT study

In this post-hoc analysis of the AXEPT study, 855 patients were analyzed, 544 (63.6%) females. The mean (± SD) MMSE score in women vs men was 20.8 ± 2.6 vs. 21.2 ± 2.5; p = 0.0087, and women were more likely affected by psychiatric disorders (n = 76, 14.0% women vs. n = 21, 6.8% men; p = 0.0015). Men were mainly assisted by their wives (n = 207, 66.6%), women mainly by their daughters (n = 243, 44.7%) and only in a minority of cases by their husbands (n = 92, 16.9%). Women less frequently cohabited with their caregivers than men (n = 233, 43.1% vs. n = 240, 77.9%, p < 0.0001), and received less daily time of caregiving (mean (± SD): 10.0 ± 7.2 vs. 15.2 ± 8.2; p < 0.0001). No gender differences were highlighted in compliance to treatment and caregiver satisfaction, while gender differences in caregiving were found at disadvantage of women affected by more severe cognitive and psychiatric conditions.

Trends and Gender Differences in Mental Disorders in Hospitalized Patients in Thailand

Previous studies have shown that gender differences play a substantial role in the influence of mental disorders. This study was designed to investigate gender differences in mental disorders by presenting odd ratio (OR) trends and cumulative effects over a period of 13 years in Thailand. This observational study used hospital data from the Ministry of Public Health on selected patients admitted to inpatient departments in public hospitals with mental disorders, according to ICD-10 cause groups from 2007 to 2019, counting from more than 1,90,000 cases in 2007 to more than 4,00,000 cases in 2019. Data were collected from the Thailand Ministry of Public Health website. The results indicate that compared to women, men were positively related to five mental disorders revealed by the OR and the ratio per 100,000 population (mean and SD): psychoactive alcohol use (OR = 7.31-9.07, 271.19 (59.26)), substance abuse (OR = 5.06-7.82, 59.25 (33.71)), schizophrenia (OR = 1.64-1.93, 108.32 (19.62)), mental retardation (OR = 1.15-1.58, 10.64 (1.88)), and other mental and behavioral disorders (OR = 1.10-1.55, 70.67 (22.75)). Three mental disorders in men were found to be negatively related: neurotic and related disorders (OR=.34-.46, 27.98 (3.26)), mood (affective) disorders (OR = .44-.56, 31.91 (9.59)), and dementia (OR = .78-10.82, 13.75 (2.73)). Gender can become a key biological element that contributes to the dissimilarity of mental illness. Preventive care for men and women should, therefore, be prioritized for health conditions separately. More specifically, screening and detection, and providing appropriate intervention.

Anthropometric Markers With Specific Cut-Offs Can Predict Anemia Occurrence Among Malaysian Young Adults

Objective: Anemia bears a high global prevalence with about 1.6 billion people living with this affliction. Malaysia carries the burden of 13.8% anemia prevalence which urges for extensive research directed to its prediction and amelioration. This is the first study that aims to (a) propose simple non-invasive predictive anthropometric markers and their specific cut-off values for early prediction of anemia among the young adults in Malaysia, (b) provide anemia prevalence based on both gender and ethnicity among young adults of Malaysia.

Method: The present cross-sectional study included 245 participants (113 men and 132 women) aged between 18 and 30 years. Anthropometric parameters were measured following the standard protocols. Blood samples were collected and hemoglobin levels were determined using the HemoCue haemoglobinometer (Hb 201+ System, Angelhom, Sweden) to detect the presence of anemia. The receiver operating characteristics (ROC) curve was employed to assess and compare the efficacy of anthropometric indices in the prediction of anemia. Data were analyzed using SPSS (v. 22.0, IBM, Chicago, IL, USA) and MedCalc (v. 19.05, Ostend, Belgium).

Result: The ROC analysis indicates that body mass index (BMI) is the best anthropometric marker with the highest area under the curve (AUC) and specificity (SP) for predicting the presence of anemia in young adults in Malaysia. Thus, the study proposes the optimal cut-off value of BMI for young men of Malaysia as 20.65 kg/m² (AUC: 0.889) and young women of Malaysia as 19.7 kg/m² (AUC: 0.904). The study also reports that Malaysian Indians have the highest prevalence of anemia (26.22%) followed by Malays (21.54%), “Others” (indigenous ethnic group) (20%), and Chinese (14.5%), with an overall higher prevalence of anemia in young adult women (21.96%) than in men (18.6%) of Malaysia.

Conclusion: The proposed anemia-predictive anthropometric markers with optimal cut-off values will aid early detection of anemia among young adults in Malaysia, and given its simple, inexpensive, and intelligible approach, it can be widely used. The ease of anemia prediction together with the reported distribution of anemia prevalence based on gender and ethnicity will facilitate in gauging the necessary extent of strategies of anemia management in the young adult population of Malaysia.

Identification of Hemoglobin Levels Based on Anthropometric Indices in Elderly Koreans

OBJECTIVES

Anemia is independently and strongly associated with an increased risk of mortality in older people and is also strongly associated with obesity. The objectives of the present study were to examine the associations between the hemoglobin level and various anthropometric indices, to predict low and normal hemoglobin levels using combined anthropometric indices, and to assess differences in the hemoglobin level and anthropometric indices between Korean men and women.

METHODS

A total of 7,156 individuals ranging in age from 53-90 years participated in this retrospective cross-sectional study. Binary logistic regression (LR) and naïve Bayes (NB) models were used to identify significant differences in the anthropometric indices between subjects with low and normal hemoglobin levels and to assess the predictive power of these indices for the hemoglobin level.

RESULTS

Among all of the variables, age displayed the strongest association with the hemoglobin level in both men (p < 0.0001, odds ratio [OR] = 0.487, area under the receiver operating characteristic curve based on the LR [LR-AUC] = 0.702, NB-AUC = 0.701) and women (p < 0.0001, OR = 0.636, LR-AUC = 0.625, NB-AUC = 0.624). Among the anthropometric indices, weight and body mass index (BMI) were the best predictors of the hemoglobin level. The predictive powers of all of the variables were higher in men than in women. The AUC values for the NB-Wrapper and LR-Wrapper predictive models generated using combined anthropometric indices were 0.734 and 0.723, respectively, for men and 0.649 and 0.652, respectively, for women. The use of combined anthropometric indices may improve the predictive power for the hemoglobin level.

DISCUSSION

Among the various anthropometric indices, with the exception of age, we did not identify any indices that were better predictors than weight and BMI for low and normal hemoglobin levels. In addition, none of the ratios between pairs of indices were good indicators of the hemoglobin level. Finally, the Korean men tended to have higher associations between the anthropometric indices and anemia than the women.