METHODS: Data for 91 countries were obtained from United Nations agencies. The response variable was life expectancy, and the determinant factors were demographic events (total fertility rate and adolescent fertility rate), socioeconomic status (mean years of schooling and gross national income per capita), and health factors (physician density and human immunodeficiency virus [HIV] prevalence rate). Path analysis was used to determine the direct, indirect, and total effects of these factors on life expectancy.
RESULTS: All determinant factors were significantly correlated with life expectancy. Mean years of schooling, total fertility rate, and HIV prevalence rate had significant direct and indirect effects on life expectancy. The total effect of higher physician density was to increase life expectancy.
CONCLUSIONS: We identified several direct and indirect pathways that predict life expectancy. The findings suggest that policies should concentrate on improving reproductive decisions, increasing education, and reducing HIV transmission. In addition, special attention should be paid to the emerging need to increase life expectancy by increasing physician density.
METHODS: This study was based on data obtained from 3716 Malaysians aged ≥60 years as part of the National Health and Morbidity Survey (NHMS) 2018. QoL was measured using the Control, Autonomy, Self-realization and Pleasure 19-item (CASP-19) questionnaire. UI was measured using the Questionnaire Urinary Incontinence Diagnosis (QUID) score. Association between UI and QoL were examined using linear regression analysis, after controlling socio-demographic variables and comorbidities.
RESULTS: Overall, the prevalence of UI was 5.2%. By subtypes, the prevalence of stress UI and urge UI were both 2.0%, while that of mixed UI was 1.3%. The UI group rated their lives more negatively in all four domains of QoL compared with non-UI group. Those who were incontinent had lower standardized scores on control and autonomy domains of CASP-19 as well as total score. Results from linear regression analysis indicated that UI had a significantly negative impact on control and autonomy domains of QoL after controlling for socio-demographic factors and comorbidities.
CONCLUSION: UI contributes to a significant reduction on QoL of older persons. Healthcare providers need to be sensitive in evaluating and discussing UI, particularly with their older patients. Geriatr Gerontol Int 2020; 20: 38-42.
Methods: Two hundred fifty-six patients with schizophrenia between the age of 18 and 65 years were randomly recruited. This cross-sectional study utilised the Calgary Depression Scale for Schizophrenia (CDSS), the Positive and Negative Syndrome Scale (PANSS) and the Psychotic Symptom Rating Scale (PSYRATS-AH). Univariate analysis was performed using an independent t-test or chi-square test, followed by binary logistic regression to determine the factors associated with increased suicidal risks.
Results: The socio-demographic factors associated with suicidal ideation included level of education (p=0.039); secondary-level education (OR=5.76, 95% CI:1.49, 22.34, p=0.011) and tertiary-level education (OR=9.30, 95% CI: 1.80, 48.12, p=0.008) posed a greater risk. A history of attempted suicide (OR=2.09, 95% CI: 1.01, 4.36, p=0.049) and the presence of co-morbid physical illnesses (OR=2.07, 95% CI: 1.02, 4.21, p=0.044) were also found to be associated with a suicidal ideation. Other significant factors associated with suicidal thoughts were concurrent depression (OR=9.68, 95% CI: 3.74, 25.05, p<0.001) and a higher PSYRATS score in emotional characteristics of auditory hallucinations (OR=1.13, 95% CI: 1.06, 1.21, p<0.001).
Conclusion: Suicide in schizophrenia appears to be more closely associated with certain socio-demographic factors and affective symptoms. Appropriate screening and treatment addressing these challenges must be emphasized if suicidal thoughts and actions are to be reduced.
Methods: We have selected a total of nine Asian nations, based on the strength of their economic output and long-term real GDP growth rates. The OECD members included Japan and the Republic of Korea, while the seven non-OECD nations were China, India, Indonesia, Malaysia, Pakistan, the Philippines, and Thailand. Healthcare systems efficiency was analyzed over the period 1996-2017. To assess the effectiveness of healthcare expenditure of each group of countries, the two-way fixed effects model (country- and year effects) was used.
Results: Quality of governance and current health expenditure determine healthcare system performance. Population density and urbanization are positively associated with a healthy life expectancy in the non-OECD Asian countries. In this group, unsafe water drinking has a statistically negative effect on healthy life expectancy. Interestingly, only per capita consumption of carbohydrates is significantly linked with healthy life expectancy. In these non-OECD Asian countries, unsafe water drinking and per capita carbon dioxide emissions increase infant mortality. There is a strong negative association between GDP per capita and infant mortality in both sub-samples, although its impact is far larger in the OECD group. In Japan and South Korea, unemployment is negatively associated with infant mortality.
Conclusion: Japan outperforms other countries from the sample in major healthcare performance indicators, while South Korea is ranked second. The only exception is per capita carbon dioxide emissions, which have maximal values in the Republic of Korea and Japan. Non-OECD nations' outcomes were led by China, as the largest economy. This group was characterized with substantial improvement in efficiency of health spending since the middle of the 1990s. Yet, progress was noted with remarkable heterogeneity within the group.
Methods: This observational study employs secondary data from various official sources of 12 states and one federal territory in Malaysia (2002-2014). Panel data of 78 observations (13 cross-sections at six points in time) were used in multivariate, fixed-effect, regressions to estimate the effects of socioeconomic variables on life expectancy at birth for male, female and both-gender.
Results: Poverty and income significantly determine female, male, and total life expectancies. Unemployment significantly determines female and total life expectancies, but not male. Income inequality and public spending on health (as a percentage of total health spending) do not significantly determine life expectancy. The coefficients of the multivariate regressions suggest that a 1% reduction in poverty, 1% reduction in unemployment, and around USD 23.20 increase in household monthly income prolong total life expectancy at birth by 17.9, 72.0, and 16.3 d, respectively. The magnitudes of the effects of the socioeconomic variables on life expectancy vary somewhat by gender.
Conclusion: Life expectancy in Malaysia is higher than the world average and higher than that in some developing countries in the region. However, it is far lower than the advanced world. Reducing poverty and unemployment and increasing income are three effective channels to enhance longevity.