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Fulltext Effect of diet on type 2 diabetes mellitus: A review

Sami W, Ansari T, Butt NS, Hamid MRA

Int J Health Sci (Qassim), 2017 Apr-Jun;11(2):65-71.
PMID: 28539866

Globally, type 2 diabetes mellitus (T2DM) is considered as one of the most common diseases. The etiology of T2DM is complex and is associated with irreversible risk factors such as age, genetic, race, and ethnicity and reversible factors such as diet, physical activity and smoking. The objectives of this review are to examine various studies to explore relationship of T2DM with different dietary habits/patterns and practices and its complications. Dietary habits and sedentary lifestyle are the major factors for rapidly rising incidence of DM among developing countries. In type 2 diabetics, recently, elevated HbA1c level has also been considered as one of the leading risk factors for developing microvascular and macrovascular complications. Improvement in the elevated HbA1c level can be achieved through diet management; thus, the patients could be prevented from developing the diabetes complications. Awareness about diabetes complications and consequent improvement in dietary knowledge, attitude, and practices lead to better control of the disease. The stakeholders (health-care providers, health facilities, agencies involved in diabetes care, etc.) should encourage patients to understand the importance of diet which may help in disease management, appropriate self-care and better quality of life.
Fulltext Dietary Knowledge among Adults with Type 2 Diabetes-Kingdom of Saudi Arabia

Sami W, Alabdulwahhab KM, Ab Hamid MR, Alasbali TA, Alwadani FA, Ahmad MS

Int J Environ Res Public Health, 2020 01 30;17(3).
PMID: 32019083 DOI: 10.3390/ijerph17030858

Dietary management is considered as a major step in assessing a patient's knowledge related to nutritional aspects, treatment, and complications of diabetes. Diabetes patients frequently face difficulty in identifying the recommended diet, including its quality and quantity. In the Kingdom of Saudi Arabia (KSA), sedentary lifestyle, along with food choices and portion sizes, have increased considerably and this has resulted in the soaring risk of diabetes. In addition, there is paucity of literature focusing on the Dietary Knowledge (DK) of type 2 diabetics in KSA. The study aimed to assess and evaluate the DK of type 2 diabetics. An analytical cross-sectional study was conducted among 350 type 2 diabetics using a valid and reliable self-prepared questionnaire comprising of 21 questions. Results showed that type 2 diabetics had an overall poor DK (28.57%). Sub-group analysis further revealed that diabetes patients had poor knowledge related to the consumption of carbohydrates and food choices, whereas they had good knowledge related to lipids and fats, proteins and food types. The role of diet in controlling of diabetes is considered imperative, but still, diabetes patients are unaware how they should approach this issue. The patient empowerment approach can be used to counsel patients with a poor DK. Primary care physicians and dietitians should work together and carry out individualized, tailored and patient-centered dietary education sessions.
Fulltext Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches

Sajid MR, Almehmadi BA, Sami W, Alzahrani MK, Muhammad N, Chesneau C, et al.

Int J Environ Res Public Health, 2021 11 29;18(23).
PMID: 34886312 DOI: 10.3390/ijerph182312586

Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low-middle-income countries (LMICs). Further, conventional logistic regression analysis (LRA) does not consider non-linear associations and interaction terms in developing these RPMs, which might oversimplify the phenomenon. This study aims to develop alternative machine learning (ML)-based RPMs that may perform better at predicting CVD status using nonlaboratory features in comparison to conventional RPMs. The data was based on a case-control study conducted at the Punjab Institute of Cardiology, Pakistan. Data from 460 subjects, aged between 30 and 76 years, with (1:1) gender-based matching, was collected. We tested various ML models to identify the best model/models considering LRA as a baseline RPM. An artificial neural network and a linear support vector machine outperformed the conventional RPM in the majority of performance matrices. The predictive accuracies of the best performed ML-based RPMs were between 80.86 and 81.09% and were found to be higher than 79.56% for the baseline RPM. The discriminating capabilities of the ML-based RPMs were also comparable to baseline RPMs. Further, ML-based RPMs identified substantially different orders of features as compared to baseline RPM. This study concludes that nonlaboratory feature-based RPMs can be a good choice for early risk assessment of CVDs in LMICs. ML-based RPMs can identify better order of features as compared to the conventional approach, which subsequently provided models with improved prognostic capabilities.
Fulltext Elevating athletic performance: Maximizing strength and power in long jumpers through combined low-intensity blood flow restriction and high-intensity resistance training

Sarfabadi P, Rizvi MR, Sharma A, Sami W, Sajid MR, Arora S, et al.

Heliyon, 2023 Aug;9(8):e19068.
PMID: 37636460 DOI: 10.1016/j.heliyon.2023.e19068

PURPOSE: This study aimed to evaluate the effects of low-intensity blood flow restriction (BFR) training and high-intensity resistance training (HI-RT) on the leaping performance of long-jumpers.
MATERIALS AND METHODS: Long jump players were divided into two groups; one group (group A) receiving HI-RT (n = 8) and the other group (group B) receiving combined low-intensity BFR training plus HI-RT (n = 8). Muscle power and knee muscle strength was assessed at baseline, 3 weeks and 6 weeks of intervention.
RESULTS: 1-RM was found to be significantly different between Group A and Group B at 3 and 6 weeks. Further, IKDQR, IKDHR and IKDQL was significantly improved in group B as compared to group A both at 3 and 6 weeks. There was significant time effect, group effect and time-group interaction in the strength of quadriceps and hamstring of both left and right leg measured through isokinetic device. Post-hoc analysis for 1-RM in group B showed a significant improvement at baseline and 6 weeks and the broad jump was significant at baseline and 3 weeks and at baseline and 6 weeks.
CONCLUSION: The combined effects of low-intensity BFR training and HI-RT is effective in improving the muscle strength and power of lower limbs in long jumpers.
Hesitancy in COVID-19 vaccine uptake and its associated factors among the general adult population: a cross-sectional study in six Southeast Asian countries

Marzo RR, Sami W, Alam MZ, Acharya S, Jermsittiparsert K, Songwathana K, et al.

Trop Med Health, 2022 Jan 05;50(1):4.
PMID: 34983692 DOI: 10.1186/s41182-021-00393-1

BACKGROUND: Vaccines are effective and reliable public health interventions against viral outbreaks and pandemics. However, hesitancy regarding the Coronavirus disease (COVID-19) vaccine is evident worldwide. Therefore, understanding vaccination-related behavior is critical in expanding the vaccine coverage to flatten the infection curve. This study explores the public perception regarding COVID-19 vaccination and identifies factors associated with vaccine hesitancy among the general adult populations in six Southeast Asian countries.
METHODS: Using a snowball sampling approach, we conducted a descriptive cross-sectional study among 5260 participants in Indonesia, Malaysia, Myanmar, Philippines, Thailand, and Vietnam between February and May 2021. Binary logistic regression analysis with a backward conditional approach was applied to identify factors associated with COVID-19 vaccine hesitancy.
RESULTS: Of the total, 50.6% were female, and the median age was 30 years (range: 15-83 years). The majority of the participants believed that vaccination effectively prevents and controls COVID-19 (81.2%), and 84.0% would accept COVID-19 vaccines when they become available. They agreed that health providers' advice (83.0%), vaccination convenience (75.6%), and vaccine costs (62.8%) are essential for people to decide whether to accept COVID-19 vaccines. About half (49.3%) expressed their hesitancy to receive the COVID-19 vaccines. After adjustment for other covariates, COVID-19 vaccine hesitancy was significantly associated with age, residential area, education levels, employment status, and family economic status. Participants from Indonesia, Myanmar, Thailand, and Vietnam were significantly more likely to express hesitancy in receiving COVID-19 vaccines than those from Philippines.
CONCLUSIONS: In general, participants in this multi-country study showed their optimistic perception of COVID-19 vaccines' effectiveness and willingness to receive them. However, about half of them still expressed their hesitancy in getting vaccinated. The hesitation was associated with several socioeconomic factors and varied by country. Therefore, COVID-19 vaccination programs should consider these factors essential for increasing vaccine uptake in the populations.
Fine root dynamics across pantropical rainforest ecosystems

Huaraca Huasco W, Riutta T, Girardin CAJ, Hancco Pacha F, Puma Vilca BL, Moore S, et al.

Glob Chang Biol, 2021 08;27(15):3657-3680.
PMID: 33982340 DOI: 10.1111/gcb.15677

Fine roots constitute a significant component of the net primary productivity (NPP) of forest ecosystems but are much less studied than aboveground NPP. Comparisons across sites and regions are also hampered by inconsistent methodologies, especially in tropical areas. Here, we present a novel dataset of fine root biomass, productivity, residence time, and allocation in tropical old-growth rainforest sites worldwide, measured using consistent methods, and examine how these variables are related to consistently determined soil and climatic characteristics. Our pantropical dataset spans intensive monitoring plots in lowland (wet, semi-deciduous, and deciduous) and montane tropical forests in South America, Africa, and Southeast Asia (n = 47). Large spatial variation in fine root dynamics was observed across montane and lowland forest types. In lowland forests, we found a strong positive linear relationship between fine root productivity and sand content, this relationship was even stronger when we considered the fractional allocation of total NPP to fine roots, demonstrating that understanding allocation adds explanatory power to understanding fine root productivity and total NPP. Fine root residence time was a function of multiple factors: soil sand content, soil pH, and maximum water deficit, with longest residence times in acidic, sandy, and water-stressed soils. In tropical montane forests, on the other hand, a different set of relationships prevailed, highlighting the very different nature of montane and lowland forest biomes. Root productivity was a strong positive linear function of mean annual temperature, root residence time was a strong positive function of soil nitrogen content in montane forests, and lastly decreasing soil P content increased allocation of productivity to fine roots. In contrast to the lowlands, environmental conditions were a better predictor for fine root productivity than for fractional allocation of total NPP to fine roots, suggesting that root productivity is a particularly strong driver of NPP allocation in tropical mountain regions.