MATERIALS AND METHODS: This is a cross-sectional study on adolescents aged 13-18 years old. Upon ethical clearance obtained from UMMC Medical Ethics Committee, patients with colorectal, breast or lung cancer and their adolescent children were recruited from the Clinical Oncology Unit of University of Malaya Medical Centre. Respondents who gave consent completed a demographic questionnaire and the Pediatric Quality of Life Inventory, via the post, email, home visit or meetings at the clinics.
RESULTS: 95 adolescents from 50 families responded, giving a response rate of 88 percent. The adolescent's mean age was 16 years (ranging between 13-18 years). Adolescents with parental cancer had the lowest mean score in emotional functioning (p<0.05). Male adolescents had significantly higher quality of life overall and in physical functioning compared to female adolescents. Adolescents with a father with cancer had better school functioning compared to adolescents whose mothers had cancer. Families with household income of RM 5000 and above have significantly better quality of life compared to families with lower household income.
CONCLUSIONS: Adolescent sons and daughters of parents with a cancer diagnosis show lowered QOL, particularly with reference to emotional functioning and school performance. Addressing the needs of this young group has been slow and warrants special attention. Revisiting the risk and resilience factors of adolescents might also inform tailored programs to address the needs of this neglected adolescent population.
MATERIALS AND METHODS: A cross-sectional comparative study was performed on subjects from multiple dental centres in Malaysia using a questionnaire covering sociodemographics, OHRQoL using the Malaysian Oral Health Impact Profile questionnaire, OHIP-14(M) and self-reported symptoms. Participants with severe CP were age-and gender-matched with periodontally healthy/mild periodontitis (HMP) participants based on inclusion and exclusion criteria. Full mouth periodontal examination was performed on participants. Outcome measures were OHIP-14(M) prevalence of impact and severity of impact scores.
RESULTS: One hundred and thirty (130) participants comprising 65 severe CP and 65 HMP participants were included in the study. Prevalence of impact on OHRQoL was significantly higher in the severe CP than HMP group, with an odds ratio of 3. Mean OHIP-14(M) score was significantly higher in the severe CP (18.26 ± 10.22) compared to HMP (11.28± 8.09) group. The dimensions of psychological discomfort and functional limitation, and factors such as 'discomfort due to food stuck' and 'felt shy' were impacted more in severe CP compared to HMP group (p < 0.05). When compared with the HMP group, generalised severe CP participants showed higher prevalence of impact on OHRQoL [OR=5] (p < 0.05) compared to localised severe CP [OR=2] (p = 0.05). Participants who had experienced self-reported symptoms had statistically significant impacts on OHRQoL.
CONCLUSIONS: Severe CP had a greater impact on OHRQoL compared to HMP. Impacts were mainly for functional limitation and psychological discomfort dimensions. When considering extent of disease, the impact on OHRQoL was mostly in generalised severe CP subgroup.
METHODS: A cross-sectional study was conducted at two primary care clinics in Kuala Lumpur, Malaysia, recruiting 271 participants by utilizing the universal sampling method. Every patient who attended both the clinics during the study period and met the inclusion and exclusion criteria were approached and briefed about the study. Patients who gave consent were recruited as study participants. Information on sociodemographic, medical condition, and lifestyle behaviors were obtained. The Montreal Cognitive Assessment (MoCA) was used to screen for MCI at a score < 23. The World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire was used to evaluate QOL.
RESULTS: Prevalence of MCI was 27.3%. Lower QOL scores were found in the physical (67.3 ± 1.4), psychological (67.3 ± 1.4), social (66.9 ± 1.6) and environmental (71.3 ± 1.3) domains among participants with MCI. Among them, predictors of QOL were depression in the physical domain, age and stroke in the psychological domain, presence of other types of disorders in the social domain and diabetes and stroke in the environmental domain.
CONCLUSIONS: MCI was prevalent among study participants and were associated with poorer QOL in all domains of QOL. A better understanding of predictors of QOL in older people with MCI is deemed important.
CLINICAL IMPLICATION: Routine cognitive screening at primary care clinics will facilitate early recognition of MCI and facilitates referral to memory clinics for further assessment and treatment.
METHODS: The algorithm was developed using data from 345 TDT patients. Spearman's rank correlation was used to evaluate the conceptual overlap between the instruments. Model specifications were chosen using a stepwise regression. Both direct and response mapping methods were attempted. Six mapping estimation methods ordinary least squares (OLS), a log-transformed response using OLS, generalized linear model (GLM), two-part model (TPM), Tobit and multinomial logistic regression (MLOGIT) were tested to determine the root mean squared error (RMSE) and mean absolute error (MAE). Other criterion used were accuracy of the predicted utility score, proportions of absolute differences that was less than 0.03 and intraclass correlation coefficient. An in-sample, leave-one-out cross validation was conducted to test the generalizability of each model.
RESULTS: The best performing model was specified with three out of the four PedsQL GCS scales-the physical, emotional and social functioning score. The best performing estimation method for direct mapping was a GLM with a RMSE of 0.1273 and MAE of 0.1016, while the best estimation method for response mapping was the MLOGIT with a RMSE of 0.1597 and MAE of 0.0826.
CONCLUSION: The mapping algorithm developed using the GLM would facilitate the calculation of utility scores to inform economic evaluations for TDT patients when EQ-5D data is not available. However, caution should be exercised when using this algorithm in patients who have poor quality of life.
METHODS: We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs).
FINDINGS: In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505).
INTERPRETATION: Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
METHODS: A comprehensive literature search on October 1st, 2020, was performed in PubMed, Scopus, and Web of Science to retrieve original population-based studies on MS epidemiology in the Asian and Oceanian countries, published between January 1st, 1985 and October 1st, 2020. The designed search strategy was repeated for each country, and the relevant referenced articles were added to our database. A random-effect model was used to combine the epidemiological estimates, and subgroup analysis was also performed by continent, region, and country, when possible. Meta-regression analysis was done to evaluate the effects of Human Developmental Index (HDI), latitude, and study period on the epidemiologic parameters.
RESULTS: A total of 3,109 publications were found, of which 89 articles met the eligibility criteria and were included for data extraction. These articles provided data on prevalence, incidence, and mean age at disease onset in 18 countries in Asia and Oceania, including Iran, Turkey, Cyprus, Kuwait, Saudi Arabia, Qatar, UAE, Jordan, Israel, India, Malaysia, China, Hong Kong, Taiwan, Republic of Korea, Japan, Australia, and New Zealand. The pooled total prevalence, incidence, and mean age of onset in Asia and Oceania were 37.89/100000 (95% CI: 35.65 - 40.142), 2.40/100000 (95% CI: 2.22 - 2.58), and 28.21 (95% CI: 27.55 - 28.88), respectively. MS prevalence and incidence in the female gender (68.7/100000 and 4.42/100000, respectively) were infinitely higher than in the male gender (24.52/100000 and 2.06/100000, respectively). Our subgroup analysis showed that MS was much more prevalent in Australia and West Asia among the studied area. The meta-regression showed that the total incidence decreased with an increase in the HDI, and the total prevalence in Asia increased with increasing latitude gradients. Also, the study period had a positive effect on the total prevalence and incidence in Asia and Oceania.
CONCLUSION: MS prevalence and incidence have increased in recent decades. This study highlights the need for further studies to elucidate MS's geographical and temporal variations' exact etiologies.