Browsing by Person "Ismail, Roshidi"

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Diabetes Treatment and Mental Illness: A Call for an Integrated Health Care System in Underserved Semi-Rural Malaysia
(MDPI, 2022-08-14) Thangiah, Govindamal; Johar, Hamimatunnisa; Ismail, Roshidi; Reininghaus, Ulrich; Bärnighausen, Till; Thurairajasingam, Sivakumar; Reidpath, Daniel; Su, Tin Tin
Diabetes mellitus (DM) management imposes a tremendous psychological burden on patients. The study investigates the association between DM treatment with blood glucose (BG) control and common mental health conditions. A cross-sectional study was conducted among 1821 individuals with DM in a community-based survey conducted in 2013. Information on respondents’ sociodemographic, mental health, DM treatment, and BG levels was collected. Multinomial logistic regression was employed to examine the association of diabetes treatment with controlled BG levels (11.1 mmol/L) (42.5%, n = 774) or uncontrolled BG levels (34.3%, n = 625) compared with those not undergoing treatment (23.2%, n = 422) on depression anxiety, and stress. Having DM treatment and controlled BG was associated with high depressive symptoms (Relative Risk Ratio, RRR: 2.42; 95% CI 1.33−4.41) and high anxiety symptoms (1.66; 1.08−2.56) but not with perceived stress. However, treated DM with uncontrolled BG was associated with anxiety (high: 1.64; 1.05−2.56; low: 2.59; 1.10−6.09) but not depression or perceived stress. Our results suggest that being treated for DM, regardless of glucose control status, was associated with anxiety symptoms, whereas being treated with controlled BG was associated with high depressive symptoms. This situation highlights the need for integrative, multidisciplinary care for DM patients with mental health comorbidities.
Frequent Eating Out and 10-Year Cardiovascular Disease Risk: Evidence from a Community Observatory in Malaysia
(Hindawi, 2022-03-07) Ang, Chiew Way; Ismail, Roshidi; Kassim, Zaid; Ghazali, Ahmad Nizal Mohd; Reidpath, Daniel; Su, Tin Tin; Siemianowicz, Krzysztof
Despite increasing mortality rates from cardiovascular diseases (CVDs) in low- and middle-income countries, information on the estimation of 10-year CVD risk remains to be sparse. Therefore, this study was aimed at predicting the 10-year CVD risk among community dwellers in Malaysia and at identifying the association of distal (socioeconomic characteristics) and proximal (lifestyle practices) factors with 10-year CVD risk. We calculated the 10-year CVD risk score among 11,897 eligible respondents from the community health survey conducted by the South East Asia Community Observatory (SEACO) using the Framingham risk score (FRS). The findings indicate that 28% of respondents have a high chance of having CVD within the next ten years. After adjusting for the age of respondents, demographic and socioeconomic factors such as gender, ethnicity, marital status, education, income, and occupation had an association with the 10-year CVD risk. In addition, frequent eating out had an association with 10-year CVD risk, while physical activity was found to have no association with predicted CVD risk. CVD remained among the top five mortality causes in Malaysia. Health promotion strategies should emphasize the importance of having home-cooked meals as a healthy dietary behavior, to reduce the mortality rate among Malaysians due to CVDs.
Multimorbidity latent classes in relation to 11-year mortality, risk factors and health-related quality of life in Malaysia: a prospective health and demographic surveillance system study
(BioMed Central, 2025-01-06) Tan, Michelle M. C.; Hanlon, Charlotte; Muniz-Terrera, Graciela; Benaglia, Tatiana; Ismail, Roshidi; Mohan, Devi; Konkoth, Ann Breeze Joseph; Reidpath, Daniel; Pinho, Pedro José M. Rebello; Allotey, Pascale; Kassim, Zaid; Prina, Matthew; Su, Tin Tin
Background: We aimed to identify specific multimorbidity latent classes among multi-ethnic community-dwelling adults aged ≥ 18 years in Malaysia. We further explored the risk factors associated with these patterns and examined the relationships between the multimorbidity patterns and 11-year all-cause mortality risk, as well as health-related quality of life (HRQoL). Methods: Using data from 18,101 individuals (aged 18–97 years) from the baseline Census 2012, Health Round 2013, and Verbal Autopsies 2012–2023 of the South East Asia Community Observatory (SEACO) health and demographic surveillance system, latent class analysis was performed on 13 chronic health conditions to identify statistically and clinically meaningful groups. Multinomial logistic regression and Cox proportional hazards regression models were conducted to investigate the adjusted association of multimorbidity patterns with the risk factors and mortality, respectively. HRQoL was analyzed by linear contrasts in conjunction with ANCOVA adjusted for baseline confounders. Results: Four distinct multimorbidity latent classes were identified: (1) relatively healthy (n = 10,640); (2) cardiometabolic diseases (n = 2428); (3) musculoskeletal, mobility and sensory disorders (n = 2391); and (4) complex multimorbidity (a group with more severe multimorbidity with combined profiles of classes 2 and 3) (n = 699). Significant variations in associations between socio-demographic characteristics and multimorbidity patterns were discovered, including age, sex, ethnicity, education level, marital status, household monthly income and employment status. The complex multimorbidity group had the lowest HRQoL across all domains compared to other groups (p < 0.001), including physical health, psychological, social relationships and environment. This group also exhibited the highest mortality risk over 11 years even after adjustment of confounders (age, sex, ethnicity, education and employment status), with a hazard of death of 1.83 (95% CI 1.44–2.33), followed by the cardiometabolic group (HR 1.42, 95% CI 1.18–1.70) and the musculoskeletal, mobility and sensory disorders group (HR 1.29, 95% CI 1.04–1.59). Conclusions: Our study advances the understanding of the complexity of multimorbidity and its implications for health outcomes and healthcare delivery. The findings suggest the need for integrated healthcare approaches that account for the clusters of multiple conditions and prioritize the complex multimorbidity cohort. Further longitudinal studies are warranted to explore the underlying mechanisms and evolution of multimorbidity patterns.
Prevalence of and factors associated with multimorbidity among 18 101 adults in the South East Asia Community Observatory Health and Demographic Surveillance System in Malaysia: a population-based, cross-sectional study of the MUTUAL consortium
(BMJ Publishing Group, 2022-12-23) Tan, Michelle M C; Prina, A Matthew; Muniz-Terrera, Graciela; Mohan, Devi; Ismail, Roshidi; Assefa, Esubalew; Keinert, Ana Á M; Kassim, Zaid; Allotey, Pascale; Reidpath, Daniel; Su, Tin Tin
Objectives: To assess the prevalence and factors associated with multimorbidity in a community-dwelling general adult population on a large Health and Demographic Surveillance System (HDSS) scale. Design: Population-based cross-sectional study. Setting: South East Asia Community Observatory HDSS site in Malaysia. Participants: Of 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18–97 years (mean age 47 years, 55.6% female) were included. Main outcome measures: The main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed. Results: Of the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001). Conclusions: The current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies.