METHODS: This was a prospective cohort study of 133,137 individuals between the ages of 20 and 80 from 24 countries. Country-specific validated questionnaires documented baseline and follow-up medication use. Participants were followed up prospectively at least every 3 years. The main outcome was the development of IBD, including Crohn's disease (CD) and ulcerative colitis (UC). Short-term (baseline but not follow-up use) and long-term use (baseline and subsequent follow-up use) were evaluated. Results are presented as adjusted odds ratios (aORs) with 95% CIs.
RESULTS: During a median follow-up period of 11.0 years (interquartile range, 9.2-12.2 y), there were 571 incident IBD cases (143 CD and 428 UC). Incident IBD was associated significantly with baseline antibiotic (aOR, 2.81; 95% CI, 1.67-4.73; P = .0001) and hormonal medication use (aOR, 4.43; 95% CI, 1.78-11.01; P = .001). Among females, previous or current oral contraceptive use also was associated with IBD development (aOR, 2.17; 95% CI, 1.70-2.77; P < .001). Nonsteroidal anti-inflammatory drug users also were observed to have increased odds of IBD (aOR, 1.80; 95% CI, 1.23-2.64; P = .002), which was driven by long-term use (aOR, 5.58; 95% CI, 2.26-13.80; P < .001). All significant results were consistent in direction for CD and UC with low heterogeneity.
CONCLUSIONS: Antibiotics, hormonal medications, oral contraceptives, and long-term nonsteroidal anti-inflammatory drug use were associated with increased odds of incident IBD after adjustment for covariates.
METHODS: This prospective observational study was conducted at a a PMDT unit in Multan, Punjab, Pakistan. A total of 271 eligible culture positive DR-TB patients enrolled for treatment at the study site between January 2016 and May 2017 were followed till their treatment outcomes were recorded. World Health Organization's (WHO) defined criteria was used for categorizing treatment outcomes. The outcomes of cured and treatment completed were collectively placed as successful outcomes, while death, lost to follow-up (LTFU) and treatment failure were grouped as unsuccessful outcomes. Multivariable binary logistic regression analysis was employed for getting predictors of unsuccessful treatment outcomes. A p-value <0.05 was considered statistically significant.
RESULTS: Of the 271 DR-TB patients analysed, nearly half (51.3%) were males. The patient's (Mean ± SD) age was 36.75 ± 15.69 years. A total of 69% patients achieved successful outcomes with 185 (68.2%) patients being cured and 2 (0.7%) completed therapy. Of the remaining 84 patients with unsuccessful outcomes, 48 (17.7%) died, 2 (0.7%) were declared treatment failure, 34 (12.5%) were loss to follow up. After adjusting for confounders, patients' age > 50 years (OR 2.149 (1.005-4.592) with p-value 0.048 and baseline lung cavitation (OR 7.798 (3.82-15.919) with p-value <0.001 were significantly associated with unsuccessful treatment outcomes.
CONCLUSIONS: The treatment success rate (69%) in the current study participants was below the target set by WHO (>75%). Paying special attention and timely intervention in patients with high risk of unsuccessful treatment outcomes may help in improving treatment outcomes at the study site.
OBJECTIVES: To determine the incidence and prevalence of GPP in the Malaysian population and characterize its flares and trigger factors.
METHODS: We conducted a population-based cohort study using the Teleprimary Care database between January 2010 and December 2020. We identified 230 dermatologist-confirmed GPP cases using International Classification of Diseases, 10th revision, diagnostic codes. Annual prevalence and incidence rates were stratified by age, sex and ethnicity. We compared data regarding flares and trigger factors for patients with GPP who had associated psoriasis vulgaris (PV) with those who did not have associated PV.
RESULTS: The prevalence of GPP was 198 per million (267 women, 127 men) and incidence was 27.2 per million person-years [95% confidence interval (CI) 22.8-31.6]; 35.3 (28.4-42.2) per million person-years for women and 18.3 (13.1-23.5) per million person-years for men. Rates were higher in Chinese individuals [prevalence 271 per million; incidence 41.6 per million person-years (28.9-54.3)] than in the Malay population [prevalence 186; incidence 24.6 (19.4-29.7)] or the Indian ethnic group [prevalence 179; incidence 25.0 (13.8-36.3)]. Annual prevalence was consistently higher in women than in men and highest among the Chinese population, followed by the Indian and Malay populations. Overall, 67% of patients with GPP had associated PV. The prevalence and incidence of GPP without PV were lower than GPP with PV at 66 vs. 132 per million and 19.3 (95% CI 15.6-23.0) vs. 8.0 (95% CI 5.6-10.3) per million person-years, respectively. The mean age at GPP onset was 42.7 years (SD 18.4). A bimodal trend in the age of GPP onset was observed, with first and second peaks at age 20-29 years and age 50-59 years, respectively. Disease onset was significantly earlier in patients with GPP without PV than in those with PV [mean age 37.5 years (SD 20.7) vs. 44.9 years (SD 17.0), P = 0.026]. Flares occurred more frequently in patients without PV than in those with PV [mean number of flares per patient per year was 1.35 (SD 0.77) vs. 1.25 (SD 0.58), P = 0.039]. Common triggers of flares in patients with GPP who did not have PV were infections, pregnancy, menstruation and stress, whereas withdrawal of therapy, particularly systemic corticosteroids, was a more frequent trigger in patients with GPP who also had PV.
CONCLUSIONS: Our findings contribute to the global mapping of GPP, which will help inform the management of this rare condition.
METHODS: MyBFF@home intervention was a quasi-experimental study which involved 328 overweight and obese housewives aged 18-59 years old (Control group: 159, Intervention group: 169). Data of the control and intervention group (pre and post intervention who completed the body composition and blood pressure measurements were analysed. Body compositions were measured using the Body Impedance Analyser (InBody 720) and blood pressure (Systolic and Diastolic) was taken using the blood pressure monitoring device (Omron HEM 907) at baseline, 6 month and 12 month. Data analyses (Pearson's correlation test and ANOVA) were performed and analysed using SPSS Statistics for Windows, version 22.0.
RESULTS: Visceral fat area, fat mass and body fat percentage, were all significantly decreased in the intervention group compared to the control group after 6 month intervention (p
METHODS: Data of 328 eligible housewives who participated in the MyBFF@Home study was used. Intervention group of 169 subjects were provided with an intervention package which includes physical activity (brisk walking, dumbbell exercise, physical activity diary, group exercise) and 159 subjects in control group received various health seminars. Physical activity level was assessed using short-International Physical Activity Questionnaire. The physical activity level was then re-categorized into 4 categories (active intervention, inactive intervention, active control and inactive control). Physical activity, blood glucose and lipid profile were measured at baseline, 3rd month and 6th month of the study. General Linear Model was used to determine the effect of physical activity on glucose and lipid profile.
RESULTS: At the 6th month, there were 99 subjects in the intervention and 79 control group who had complete data for physical activity. There was no difference on the effect of physical activity on the glucose level and lipid profile except for the Triglycerides level. Both intervention and control groups showed reduction of physical activity level over time.
CONCLUSION: The effect of physical activity on blood glucose and lipid profile could not be demonstrated possibly due to physical activity in both intervention and control groups showed decreasing trend over time.
METHODS: A validated self-administered questionnaire was used in this cross-sectional study to collect data from final-year BPharm students enrolled at 3 government-funded universities and 1 private university in Malaysia. Both descriptive and inferential statistics were used for data analysis.
RESULTS: Three hundred fourteen students responded (213 from public universities and 101 from the private university). Approximately 32% of public university students and 37% of private university students ranked their own interest in pharmacy as the reason for undertaking pharmacy degree studies; 40.4% of public and 19.8% of private university respondents stated that they would enter a nonpharmacy-related career upon graduation if given the choice. Public university students ranked hospital pharmacy as their choice of first career setting (4.39, p = 0.001), while private students ranked community pharmacy first (4.1, p = 0.002). On a scale of 1 to 5, salary received the highest mean score (3.9 and 4.0, p = 0.854) as the extrinsic factor most influencing their career choice.
CONCLUSIONS: Final-year students at Malaysian public universities were most interested in hospital pharmacy practice as their first career step upon graduation, while private university students were most interested in community pharmacy. The top 3 extrinsic factors rated as significant in selecting a career destination were salary, benefits, and geographical location.
OBJECTIVES: We examined trajectories across adolescence and early adulthood for 2 major dietary patterns and their associations with childhood and parental factors.
METHODS: Using data from the Western Australian Pregnancy Cohort (Raine Study), intakes of 38 food groups were estimated at ages 14, 17, 20 and 22 y in 1414 participants using evaluated FFQs. Using factor analysis, 2 major dietary patterns (healthy and Western) were consistently identified across follow-ups. Sex-specific group-based modeling assessed the variation in individual dietary pattern z scores to identify group trajectories for each pattern between ages 14 and 22 y and to assess their associations with childhood and parental factors.
RESULTS: Two major trajectory groups were identified for each pattern. Between ages 14 and 22 y, a majority of the cohort (70% males, 73% females) formed a trajectory group with consistently low z scores for the healthy dietary pattern. The remainder had trajectories showing either declining (27% females) or reasonably consistent healthy dietary pattern z scores (30% males). For the Western dietary pattern, the majority formed trajectories with reasonably consistent average scores (79% males, 81% females) or low scores that declined over time. However, 21% of males had a trajectory of steady, marked increases in Western dietary pattern scores over time. A lower maternal education and higher BMI (in kg/m2) were positively associated with consistently lower scores of the healthy dietary pattern. Lower family income, family functioning score, maternal age, and being in a single-parent family were positively related to higher scores of the Western dietary pattern.
CONCLUSIONS: Poor dietary patterns established in adolescence are likely to track into early adulthood, particularly in males. This study highlights the transition between adolescence and early adulthood as a critical period and the populations that could benefit from dietary interventions.
OBJECTIVES: We sought to establish the effects of 1 mo of intermittent fasting on the gut microbiome.
METHODS: We took advantage of intermittent fasting being voluntarily observed during the Islamic faith-associated Ramadan and sampled feces and blood, as well as collected longitudinal physiologic data in 2 cohorts, sampled in 2 different years. The fecal microbiome was determined by 16S sequencing. Results were contrasted to age- and body weight-matched controls and correlated to physiologic parameters (e.g., body mass and calorie intake).
RESULTS: We observed that Ramadan-associated intermittent fasting increased microbiome diversity and was specifically associated with upregulation of the Clostridiales order-derived Lachnospiraceae [no fasting 24.6 ± 13.67 compared with fasting 39.7 ± 15.9 in relative abundance (%); linear discriminant analysis = 4.9, P