Hepatitis C virus (HCV) is a major public health concern globally, resulting in liver-related complications. Approximately 6% population of Pakistan is infected with HCV. HCV is error prone, due to which it is classified into 7 genotypes and 67 subtypes. HCV genotype determination is critical for treatment and therapy response. In this study, 3,539 samples were collected from 2015 to 2019 from all over Punjab. RNA was extracted from samples using QIA Amp Viral RNA MINI kit (Qiagen, Germany) and viral genotyping was performed. Furthermore, a systemized literature search (2009-2018) was done to analyze the HCV genotype distribution pattern in Pakistan. In Punjab, genotype 3a (86.46%) is most prevalent, followed by untypable (7.17%) and genotype 1a (3.84%) and 3b (1.04%). Mixed genotype constitutes only 0.67% of total infections. Genotype 2a, 2b, 3c, and 4 were found to be rare. Data available from literature review when compiled showed that HCV genotype 3a (58.16%) was predominant in Pakistan, followed by genotypes 3b (9.05%), 2a (6.70%), 1a (6.22%), and 1b (2.39%). The frequency of mixed genotypes was found to be 4% and 12% of untypable HCV variants. This study highlights the HCV genotype distribution pattern in different regions of Pakistan. Therapy response and disease management depend on genotype, so HCV genotype determination is crucial. In Pakistan, the most prevalent genotype is 3a, followed by untypable genotype. Both interferon and sofosbuvir are effective against genotype 3a, but treatment with sofosbuvir has comparatively high sustained virological response, less adverse effects, and more tolerability.

Recently it has been highlighted by ESPEN Council that the COVID-19 pandemic is posing unprecedented challenges worldwide. There is significant correlation between age and polymorbidity and these factors are independently associated with malnutrition and its negative impact on patient survival [1]. The COVID-19 outbreak has shattered the world's economic giants with an estimated loss of $1 trillion during year 2020. This economic dent could have drastic effects on people living in extreme poverty [2]. As in year 2019 top donor countries of humanitarian aid and world food program were United States of America (USA), Germany, United Kingdom, and European Commission respectively (Fig. 1). Unfortunately these countries were badly hit by the COVID-* Corresponding author.

Previous studies have reported increased prevalence of coronary heart disease (CHD) in Indians and South Asian settlers in North America. This increased burden of CHD among South Asians is mainly caused by dyslipidemia. To the best of our knowledge, none of the previous works has studied the patterns and prevalence of dyslipidemia in the Pakistani population. The present work aimed to study the plasma lipid trends and abnormalities in a population-based sample of urban and rural Pakistanis. The study included 238 participants (108 males,130 females). Plasma lipid profiles of the participants were determined using standard protocols. We observed that 63% of the study population displayed irregularities in at least one major lipid-fraction including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), or triglycerides (TG). The most common form of isolated-dyslipidemia was low HDL-C (17.3%) followed by high TG (11.2%). Several overlaps between high TC, LDL-C, TG and low HDL-C were also noted. Gender, urbanization, and occupational class were all observed to have an impact on lipid profiles. Briefly, male, urban, and blue-collar participants displayed higher prevalence of dyslipidemia compared to female, rural, and white-collar participants, respectively. In comparison to normal subjects, dyslipidemic subjects displayed significantly higher values for different anthropometric variables including body mass index (BMI), body fat percentage, and waist circumference. The present work provides a comprehensive estimation of the prevalence of dyslipidemia and CHD risk in the Pakistani population. This information will be helpful for better healthcare planning and resource allocation in Pakistan.

BackgroundIt has been shown that obesity is associated with increased rates of dyslipidemia. The present work revisits the association between plasma lipid levels and classical indicators of obesity including body mass index (BMI). The significance of various anthropometric/metabolic variables in clinical assessment of type and severity of dyslipidemia was also determined. Recently described body indices, a body shape index (ABSI) and body roundness index (BRI), were also assessed in this context.MethodsFor the present cross-sectional analytical study, the participants (n = 275) were recruited from the patients visiting different health camps. Participants were anthropometrically measured and interviewed, and their fasting intravenous blood was collected. Plasma lipid levels were accordingly determined.ResultsThe values for different anthropometric parameters are significantly different between dyslipidemic and non-dyslipidemic participants. Receiver operating characteristics curve analyses revealed that all the tested variables gave the highest area under the curve (AUC) values for predicting hypertriglyceridemia in comparison to other plasma lipid abnormalities. BRI gave slightly higher AUC values in predicting different forms of dyslipidemia in comparison to BMI, whereas ABSI gave very low values.ConclusionsSeveral anthropometric/metabolic indices display increased predictive capabilities for detecting hypertriglyceridemia in comparison to any other form of plasma lipid disorders. The capacity of BRI to predict dyslipidemia was comparable but not superior to the classical indicators of obesity, whereas ABSI could not detect dyslipidemia.Electronic supplementary materialThe online version of this article (doi:10.1186/s40101-017-0134-x) contains supplementary material, which is available to authorized users.