ARTICLE | doi:10.20944/preprints202006.0154.v1
Online: 12 June 2020 (12:39:49 CEST)
Aim: This study was designed to understand the changes in dietary and lifestyle behaviours that are major determinants of health during the COVID-19 outbreak. Methods: A cross-sectional study was conducted through an online questionnaire using a convenience sample of 415 adults living in Kuwait (age range 18-73 years). Results: The overall prevalence of being overweight and obesity among participants was 37.2% and 33.1% respectively. The study identified significant changes in the dietary habits and lifestyle behaviours of participants during COVID-19. In general, there was an increase in the percentage of participants that consumed four or more meals a day, skipped breakfast, and engaged in frequent late night snacking. Moreover, there was a drastic decrease in the frequency of fast food consumption and an increase in the percentage of participants who had their main meal freshly made. Furthermore, there was a great reduction in physical activity and an increase in the amount of screen time and sedentary behaviours. A notable increase was detected in day-time sleep and a decrease in night-time sleep among participants. Conclusion: This study indicates that due to the increased prevalence of habits conducive to increased rates of being overweight and obesity during the COVID-19 outbreak, there is a high likelihood that the pandemic will further exacerbate the already widespread problem of obesity and being overweight in Kuwait.
ARTICLE | doi:10.20944/preprints202202.0236.v1
Subject: Earth Sciences, Environmental Sciences Keywords: Kuwait; Covid-19; Air quality Index; GeoHealth; Kernel Density
Online: 18 February 2022 (12:27:48 CET)
Research have been conducted in many countries around the world to assess air quality during COVID-19 pandemic, especially during lockdown period, some of these studies found an increase or decrease in some pollutants. This paper investigates the impact of COVID-19 on seven air pollutants (i.e., PM2.5, PM10, NO2, O3, SO2, H2S, CO) from the period January 2020 to December 2020 in the State of Kuwait. Kuwait is a desert country located in the north-eastern part of the Arabian Peninsula, and the northeast of the Arabian Gulf (Persian as it is sometimes called). Several analytical methods were conducted, such as spatial analysis (spatial interpolation) to study the distribution of the studied variables. The data was also statistically analysed (time series analysis - Kernel density) to study the temporal changes. The analysis also included applying air quality index to the data. We found that concentrations for the pollutants decreased during the pandemic due to the decrease of anthropogenic sources including such as traffic and petroleum activities, but the concentration for PM2.5 increased, mostly because of the transported dust coming with the northwest winds prevailing in Kuwait from the Arabian deserts and Iraq.
ARTICLE | doi:10.20944/preprints202107.0232.v1
Subject: Earth Sciences, Atmospheric Science Keywords: Kuwait; Arabian Gulf; Remote Sensing; ChlorophyII-a; Marine Biogeography
Online: 9 July 2021 (15:49:04 CEST)
The concentration of chlorophyll-a (chlor-a) is an important indicator of marine water quality, as it is considered an indicator of the phytoplankton density in a specific area. Remote sensing techniques have been developed to measure the near-surface concentration of chlor-a in water across the correlation between spectral bands and in situ data. This algorithm applies to sensors of varying spatial, temporal and spectral resolutions. However, in this study, chlor-a level 2 and 3 products of SNPP – VIIRS spectrometer (Equation OC3) of NASA OceanColor suite was relied upon to study the spatial and temporal distribution of chlor-a concentration in the Arabian Gulf (also known as the Persian Gulf) and the State of Kuwait’s water (located to the north-eastern part of the Arabian Gulf) from 2012 to 2019. Ground truthing points (n = 192) matched to the level 2 products have been used to build an empirical model and cross-validate it. The correlation was positive where was 0.79 and the validation RMSE was = ± 0.64 mg/m-3. The derived algorithm was then applied to chlor-a level 3 seasonal products. Additionally, the chlor-a concentration values of Kuwaiti waters have been enhanced using the IDW algorithm to increase the spatial resolution, as it is considered as a small area compared to the spatial resolution of level 3 chlor-a products. The model derived from IDW was tested using the Mann Whitney test (Sig = 0.948 p > 0.01). However, the result showed that the chlor-a concentration is higher in Kuwait Bay compared to Kuwaiti water, and it is higher in Kuwaiti water compared to the Arabian Gulf. The coasts have higher concentrations too, when compared to the open water. Generally, the chlor-a increases in winter and makes a semi-regular cycle during the years of study; this cycle is more regular in the Gulf’s waters than in Kuwait’s.
REVIEW | doi:10.20944/preprints202108.0283.v1
Subject: Life Sciences, Molecular Biology Keywords: Type 1 diabetes; human leukocyte antigen; Kuwait Type 1 Diabetes Study; Islet autoantibodies; Insulin; prediction
Online: 13 August 2021 (08:19:26 CEST)
The incidence of Type 1 Diabetes (T1D) in the Arab world, particularly, oil and gas rich Gulf Cooperative Council (GCC) countries has more than doubled in the last twenty years. Therefore, there is a dire need for careful systematic familial cohort studies, especially in high-risk populations. Several immunogenetic factors affect the pathogenesis of the disease. Genes in the human leukocyte antigen (HLA) account for the major genetic susceptibility to the disease. The triggering agents initiate disease onset by destruction of pancreatic β-cells. The autoantibodies against glutamic acid decarboxylase (GADA), insulinoma antigen-2 (IA-2A), insulin (IAA), and zinc transporter-8 (ZnT-8A) comprise the most reliable biomarkers for T1D in both children and adults. Although three of the GCC countries, namely Kuwait, Saudi Arabia and Qatar are among the top 10 countries with high incidence rate of T1D, no proper diagnostic and prediction tools were applied in the region. Understanding the disease sequelae in a homogenous gene pool with high consanguinity in the GCC could help solve the challenges in understanding pathogenesis, as well as hasten the prevention of T1D. Arab states must incorporate T1D predictive and intervention policies on a war-footing basis to minimize the burden of this serious disease.
ARTICLE | doi:10.20944/preprints202007.0577.v1
Subject: Keywords: COVID-19; Coronavirus; SARS-CoV2; Random walks; Population dispersal; Diffusion; Lockdown; Confinement; Movement restrictions; Disease spread; Kuwait
Online: 24 July 2020 (10:57:04 CEST)
To mitigate the spread of the COVID-19 coronavirus, some countries have enforced more stringent non-pharmaceutical interventions in contrast to those widely adopted (for e.g. the state of Kuwait). In addition to standard practices such as enforcing curfews, social distancing, and closure of non-essential service industries, other non-conventional policies such as the total confinement of highly populated areas has also been implemented. In this paper, we model the movement of a host population using a mechanistic approach based on random walks, which are either diffusive or super-diffusive. Infections are realised through a contact process, whereby a susceptible host may be infected if in close spatial proximity of the infectious host. Our focus is only on the short-time scale prior to the infectious period, so that no further transmission is assumed. We find that the level of infection depends heavily on the population dynamics, and increases in the case of slow population diffusion, but remains stable for a high or super-diffusive population. Also, we find that the confinement of homogeneous or overcrowded sub-populations has minimal impact in the short term. Finally, we discuss the possible implications of our findings for total confinement in the context of the current situation in Kuwait.