Search Results (29)

Background: Suicide and self-injury are serious public health concerns, especially in young populations, owing to multiple social, cultural, and gender determinants. Qualitative evidence exploring narratives regarding the factors behind suicide among young women is rare in Pakistan. Objective: The present study aims to explore the complex dimensions of suicide or self-injury among young women of Southern Punjab. Methods: Semi-structured interviews were conducted in a marginalized district in South Punjab, with participants consenting to in-person meetings at their homes or phone interviews. We collected detailed accounts of fifteen deceased girls or self-harm survivors, with insights provided by close relatives of the victims. Results: Our findings identified several conducive factors to suicidality, including receiving insults in front of others, low self-esteem, household pressures, work burdens, unfulfilled romantic desires, feelings of worthlessness, cheating in love, marriage without choice, and engagement in risky behaviors. These causes could be categorized into personal (such as an inferiority complex), social (a lack of family support and frequent conflicts), and cultural factors (forced marriages). Conclusions: Our study advocates for empowering women through education and restricting access to suicide means, such as pesticides or Paraphenylenediamine (PPD). Moreover, the government should take strict measures to discourage the forced marriage of young females in rural contexts. This study highlights the importance of integrating suicide prevention initiatives with research efforts within Pakistan’s healthcare system. Full article

This study explored the prevalence and types of microplastic (MP) pollution in three fish species—Labeo rohita, Wallago attu, and Cirrhinus mrigala—collected from the Panjnad Barrage in South Punjab, Pakistan. MPs were analyzed from the gastrointestinal tracts (GITs), gills, and muscles of 90 fish samples. Advanced analytical techniques, including Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy/Energy-Dispersive X-Ray Spectroscopy (SEM/EDX), and Gas Chromatography/Mass Spectrometry (GC/MS), were deployed, confirming the polymeric composition and presence of various additives. Quantitative and qualitative analyses revealed significant variations in MP accumulation across tissues, with the GIT consistently showing the highest MP count, the gills having the highest concentration per gram, and the muscles exhibiting the lowest amount of accumulation. Wallago attu was found to have accumulated the highest concentration of microparticles among all three species due to its feeding habits and habitat. Fibers and fragments were the predominant types of MPs, with yellow and red being the most frequent colors. Polypropylene (PP) and polyethylene (PE) were the primary polymers identified, alongside other types like polyethylene terephthalate (PET) and polyvinyl chloride (PVC). The MP size distribution indicated that mid-sized particles (150–50 µm) were most abundant in the GIT and gills, while smaller particles (<50 µm) accumulated in the muscles, suggesting different levels of bioavailability and tissue penetration. Overall, the results suggest that agricultural activities are a major contributor to plastic pollution in the Panjnad Barrage. These findings highlight the ecological and health impacts of MP contamination, stressing the importance of targeted mitigation strategies to eliminate plastic waste in aquatic environments. Full article

Background: Anopheles stephensi, a primary malaria vector in South Asia, is expanding its geographic range, raising concerns about increased malaria transmission. However, critical aspects of its genetic diversity, population structure, and evolutionary dynamics remain poorly understood in Khyber Pakhtunkhwa (KP), Pakistan, an endemic malaria region where An. stephensi is adapting to urban settings, posing challenges for the development of targeted vector control strategies. This study addresses this gap by analyzing COI, COII (cytochrome oxidase subunit I and II), and ITS2 (internal transcribed spacer 2) sequences from An. stephensi populations in KP and comparing them with global isolates. Additionally, egg morphology analysis was conducted to identify the biological form. Methods: Mosquitoes were collected from malaria-endemic districts (Nowshera, Charsadda, and Peshawar) using ovitraps. Eggs were characterized morphologically, and DNA was extracted for PCR amplification of COI, COII, and ITS2 markers. Sequences from 17 Pakistani isolates, along with global sequences, were analyzed. Phylogenetic relationships, haplotype networks, genetic diversity, and neutrality tests (Tajima’s D and Fu’s Fs) were assessed. Results: Egg morphology confirmed the mysorensis form (13–15 ridges per egg) in KP. COI sequences clustered into two subclades (Punjab and KP), with >99% similarity to global isolates. COII and ITS2 sequences showed high similarity (99.46–100%) with populations from China, Iran, India, and Brazil, reflecting strong genetic connectivity rather than distinct regional clustering. Haplotype analysis identified six COI, ten COII, and ten ITS2 haplotypes, with Hap_2 (50.7%) and Hap_1 (43.3%) being the most prevalent in COI, Hap_7 (29.4%) in COII, and Hap_3 (80.8%) in ITS2. Population genetic analysis revealed higher COI diversity in Pakistan and India, with moderate diversity in COII. Neutrality tests suggested balancing selection in COI for both countries, while COII and ITS2 indicated population contraction in Iran. Conclusions: The findings reveal strong genetic connectivity within regions (e.g., Pakistan) and differentiation across global populations of An. stephensi, highlighting its potential for further expansion and adaptation. These insights are critical for informing global malaria control strategies, particularly in regions vulnerable to vector invasion. Full article

Trypanosomes are parasitic protozoa that cause severe diseases in humans and animals. The most important species of Trypanosmes include Trypanosoma evansi and Trypanosoma brucei gambiense. The most well-known human diseases are sleeping sickness in Africa and Chagas disease in South America. The most identified animal diseases include Nagana in the African tsetse fly belt and Surra in South Asia, North Africa, and the Middle East. Surra is caused by Trypanosoma evansi. Diminazene resistance is an emerging threat caused by T. evansi infecting animals. The underlying mechanism of diminazene resistance is poorly understood. Trypanosoma brucei gambiense causes African sleeping sickness. The development of diminazene resistance in Trypanosoma brucei gambiense is associated with the alterations in the corresponding P2 adenosine transporter-1 (AT-1) gene. In the present study, by extrapolating the findings from Trypanosoma brucei gambiense, we analyzed genetic diversity in the P2 adenosine transporter-1 gene (AT-1) from T. evansi to explore a potential link between the presence of mutations in this locus and diminazene treatment in ruminants. We examined T. evansi-infected blood samples collected from goats, sheep, camels, buffalo, and cattle in seven known endemic regions of the Punjab province of Pakistan. Heterozygosity (H_e) indices indicated a high level of genetic diversity between seven T. evansi field isolates that had resistance-type mutations at codons 178E/S, 239Y/A/E, and 286S/H/I/D/T of the P2 adenosine transporter-1 (AT-1) locus. A low level of genetic diversity was observed in 19 T. evansi field isolates with susceptible-type mutations at codons A178, G181, D239, and N286 of the P2 adenosine transporter-1 (AT-1) locus. Our results on T. evansi warrant further functional studies to explore the relationship between diminazene resistance and the mutations in AT-1. Full article

Land use and land cover (LULC) changes are significantly impacting the natural environment. Human activities and population growth are negatively impacting the natural environment. This negative impact directly relates to climate change, sustainable agriculture, inflation, and food security at local and global levels. Remote sensing and GIS tools can provide valuable information about change detection. This study examines the correlation between population growth rate and LULC dynamics in three districts of South Punjab, Pakistan—Multan, Bahawalpur, and Dera Ghazi Khan—over a 30-year period from 2003 to 2033. Landsat 7, Landsat 8, and Sentinel-2 satellite imagery within the Google Earth Engine (GEE) cloud platform was utilized to create 2003, 2013, and 2023 LULC maps via supervised classification with a random forest (RF) classifier, which is a subset of artificial intelligence (AI). This study achieved over 90% overall accuracy and a kappa value of 0.9 for the classified LULC maps. LULC was classified into built-up, vegetation, water, and barren classes in Multan and Bahawalpur, with an additional “rock” class included for Dera Ghazi Khan due to its unique topography. LULC maps (2003, 2013, and 2023) were prepared and validated using Google Earth Engine. Future predictions for 2033 were generated using the MOLUSCE model in QGIS. The results for Multan indicated substantial urban expansion as built-up areas increased from 8.36% in 2003 to 25.56% in 2033, with vegetation and barren areas displaying decreasing trends from 82.96% to 70% and 7.95% to 3.5%, respectively. Moreover, areas containing water fluctuated and ultimately changed from 0.73% in 2003 to 0.9% in 2033. In Bahawalpur, built-up areas grew from 1.33% in 2003 to 5.80% in 2033, while barren areas decreased from 79.13% to 74.31%. Dera Ghazi Khan expressed significant increases in built-up and vegetation areas from 2003 to 2033 as 2.29% to 12.21% and 22.53% to 44.72%, respectively, alongside reductions in barren and rock areas from 32.82% to 10.83% and 41.23% to 31.2%, respectively. Population projections using a compound growth model for each district emphasize the demographic impact on LULC changes. These results and findings focus on the need for policies to manage unplanned urban sprawl and focus on environmentally sustainable practices. This study provides critical awareness to policy makers and urban planners aiming to balance urban growth with environmental sustainability. Full article

Soil contamination with potentially toxic elements (PTEs) in the Malwa region belt of Punjab, India, can be a serious concern as a result of intensive agricultural practices and overuse of agrochemicals. The main objectives of the present study were to evaluate the spatial distribution, geochemical signature, and contamination level/health risk of PTEs in 76 soil samples (0–10 cm) collected from the three districts viz. Muktar, Faridkot, and Moga of Punjab, India. The result shows that PTEs concentrations vary widely in the region, with Fe and Mn distribution patterns being mostly coherent with each other. When compared to the Indian natural soil background values, the average concentration of Pb and Zn were higher than the limit, only Pb exceeded the average values of the world background and upper continental crust (UCC). Spatial autocorrelation plotted with a local indicator of spatial association (LISA) in GeoDa software version 1.18 was used to identify hotspots. A positive spatial autocorrelation (>0.2) was indicated with Moran’s I values for Pb, V, Mn, Cu, and Cr, being highest for Pb. A principal component analysis (PCA) identified the major geo-chemical patterns of Fe-Al-V-Cr and TOC-Mn-Zn-HCO₃⁻, which were positively loaded on PC1. This indicates that Fe/Al-oxyhydroxides and organic matter play a dominant role in controlling metal mobility in soils. This can be further substantiated with the Spearman’s rank correlation values. The contamination factor (CF) indicates that only Pb and Zn (15.7% and 3.9% samples, respectively) were under high risk. This could be due to the excessive application of chemical fertilizers. The large range of degree of contamination (C_deg) values suggests that there are variations in the degree of soil pollution due to PTEs. A little over 3.9% of samples had significant contamination, compared to 72.3% of samples with low contamination and 23.6% of samples with moderate contamination. Human non-carcinogenic and carcinogenic risk levels were investigated. The hazard index (HI) values for adult ranged from 0.00 to 0.2, and values for children ranged from 0.009 to 1.2. These findings suggest that both children and adults are not at potential risk, except in a few locations. Overall, the results of this study provide the current baseline status of toxic elements in agricultural soil. This would be helpful for developing strategies for sustainable management of the soil resources in the region, as well as for future monitoring programs of the soil quality in the Malwa region as a whole, to track any changes in the contamination levels over time. Full article

Climate variability and change pose a substantial threat to agricultural practices and livelihoods in the Punjab province of Pakistan, a region of agricultural significance in South Asia. In particular, farmers residing in vulnerable parts of Punjab will be affected by a combination of high exposure to the impacts of climate events, the innate sensitivity of agricultural systems, and constraints on farmers’ adaptive capacity. The situation requires closer engagement with vulnerable farming communities of Punjab to assess their vulnerability and build their capacity for adaptation actions. Through qualitative analysis of semi-structured interviews with farmers from four highly vulnerable districts of Punjab (Rajanpur, Muzaffargarh, Chakwal, Dera Ghazi Khan), we explored farmers’ perceptions of climate change, their adaptation strategies, and enablers and limitations on adaptation options imposed by the enabling environment. We found issues around water governance, knowledge exchange, and market arrangements for crops as key limitations to farmers’ local adaptation action in highly resource-constrained settings. Moreover, the results indicated the need to address equity issues for small-scale compared to large-scale farmers. Farmers valued their experience-based local knowledge and peer-to-peer sharing networks as pivotal resources in pursuit of their practice-based learning. The research findings highlighted the necessity of directed institutional assistance to empower adaptation by vulnerable small-scale farmers. This study emphasizes the critical significance of the enabling environment that facilitates vulnerable farmers to implement adaptation strategies, thereby promoting the adoption of Vulnerable-Smart Agriculture. Full article

The accumulation of salt through natural causes and human artifice, such as saline inundation or mineral weathering, is marked as salinization, but the hindrance toward spatial mapping of soil salinity has somewhat remained a consistent riddle despite decades of efforts. The purpose of the current study is the spatial mapping of soil salinity in Kot Addu (situated in the south of the Punjab province, Pakistan) using Landsat 8 data in five advanced machine learning regression models, i.e., Random Forest Regressor, AdaBoost Regressor, Decision Tree Regressor, Partial Least Squares Regression and Ridge Regressor. For this purpose, spectral data were obtained between 20 and 27 of January 2017 and a field survey was carried out to gather a total of fifty-five soil samples. To evaluate and compare the model’s performances, the coefficient of determination (R²), Mean Squared Error (MSE), Mean Absolute Error (MAE) and the Root-Mean-Squared Error (RMSE) were used. Spectral data of band values, salinity indices and vegetation indices were employed to study the salinity of soil. The results revealed that the Random Forest Regressor outperformed the other models in terms of prediction, achieving an R² of 0.94, MAE of 1.42 dS/m, MSE of 3.58 dS/m and RMSE of 1.89 dS/m when using the Differential Vegetation Index (DVI). Alternatively, when using the Soil Adjusted Vegetation Index (SAVI), the Random Forest Regressor achieved an R² of 0.93, MAE of 1.46 dS/m, MSE of 3.90 dS/m and RMSE of 1.97 dS/m. Hence, remote sensing technology with machine learning models is an efficient method for the assessment of soil salinity at local scales. This study will contribute to mitigating osmotic stress and minimizing the risk of soil erosion by providing early warnings regarding soil salinity. Additionally, it will assist agriculture officers in estimating soil salinity levels within a shorter time frame and at a reduced cost, enabling effective resource allocation. Full article

(1) Background: Physical literacy (PL) is a multidimensional concept, since it fosters lifetime engagement in physical activities and reduces obesity; however, empirical evidence is lacking to support this association. This study first aimed to establish PL levels stratified by normal weight children and children with overweight and obesity. Furthermore, this study determined a correlation between PL domains and BMI by weight status among South Punjab school children. (2) Methods: This cross-sectional study involved 1360 (Boys: 675 and Girls: 685) children aged 8 to 12, and was conducted using CAPL-2. T-tests and chi-square were used to determine the difference between categorical variables, with MANOVA used to compare weight statuses. Spearman correlation was employed to determine the correlation between variables; p < 0.05 was considered significant. (3) Results: Normal weight children had significantly higher PL and domain scores, except for the knowledge domain. Most children with normal weights were at the achieving and excelling levels, while children with overweight and obesity were at the beginning and progressing levels. The correlation among PL domains in normal and overweight and obese children ranged from weak to strong (r = 0.001 to 0.737), and the knowledge domain was inversely correlated with the motivation domain (r = −0.023). PL and domain scores were inversely correlated to BMI, except for the knowledge domain. (4) Conclusions: Children with normal weight tend to have higher PL and domain scores, while those with overweight or obesity tend to have lower scores. There was a positive relationship between normal weight and higher PL and domain scores, and an inverse relationship was observed between BMI and higher PL scores. Full article

A substantial drop in atmospheric visibility or visual range (VR) is documented in several parts of the world. We examined the long-term spatiotemporal variability in ground-based VR data for ten airports in Pakistan from 1980 to 2020. Average VR time series analysis was performed using nonparametric tests of Mann–Kendall (MK), Modified Mann–Kendall (MMK), Sen’s Slope (SS), and Sequential Mann–Kendall (SMK), followed by spatiotemporal mapping. Bad VR (<5 km) conditions prevailed over more than 60% of the study period. Noticeably, VR was better during 1991–2000 due to the high average annual rainfall (905 mm) during the 1990s. Plain areas such as Faisalabad experienced the greatest number of bad VR days with hourly (92.85%), daily (95.35%), monthly (90.97%), and seasonal (90.97%) measurements, followed by Sialkot and Multan. The VR of lowlands in central, southern, and eastern Punjab and northern, central, and eastern Sindh showed decreasing trends. In contrast, the VR in coastal areas of south and southwestern Sindh, in the western highlands, and parts of Khyber Pakhtunkhwa (KPK) province, have indicated positive trends. The results of this study will support policymakers in catering to the issue of declining VR in the region by supporting and developing strategies to limit the factor associated with VR. Full article

The lockdown after the COVID-19 pandemic not only caused public health crises and income stress but also put millions at risk of food insecurity and malnutrition across the globe, especially in low and middle-income countries [LMICs]. This study evaluated the effects of financial stress and household socio-economic deprivation on the nutritional status of 1551 children under the age of five during COVID-19 in Pakistan. A self-administered questionnaire was used between November 2020 and April 2021 to collect information on age, height, children’s weight, and socio-economic status from 1152 rural households from underdeveloped regions in Punjab, Pakistan. With the help of the proportionate simple random sampling method, this study employed a model (binary logistic regression) to calculate the likelihood of malnourishment. The findings showed that the stunting, underweight, and wasting prevalence rates during COVID-19 were 58.86%, 41.89%, and 8.11%, respectively, in the Bahawalpur region. According to the binary logistic regression analysis, among the household deprivation status (HDS) categories, the risks of childhood malnutrition were lesser in HDS-2 (OR = 0.05, 95% CI: 0. 005–0.879) and HDS-3 (OR = 0.04, 95% CI: 0.008–0.193). Similar to this, within the financial stress index (FSI) categories, the children in homes with medium financial stress had reduced odds of malnutrition (OR = 0.10, 95% CI: 0.018–0.567), and the children in households with low financial stress had reduced risks of malnutrition (OR = 0.006, 95% CI: 0.005–0.061). The proposed research found that stunting and underweight increased by 17.26% and 12.29% during the COVID-19 lockdown in the Bahawalpur region. Additionally, financial stress and socio-economic deprivation strongly affected children’s nutritional statuses during the COVID-19 lockdown in the Bahawalpur region of Southern Punjab. Full article

Pakistan and other South Asian countries rely on wheat for human nutrition. However, wheat yield is declining in the region due to several biotic and abiotic constraints. Weeds are among the major factors responsible for yield decrease and farmers manage them by intensive tillage practices. Several studies have investigated the impact of various tillage practices on weed management in wheat. However, weed suppression abilities of different mulch types are rarely tested. This three-year (2019–20, 2020–21 and 2021–22) study investigated the impact of different mulch types (prepared from different crops) on weed infestation, soil properties and productivity of wheat under conventional and conservation production systems at three locations (Multan, Hafizabad and Faisalabad) in Punjab, Pakistan. The mulches included in the study were cotton sticks mulch, mungbean straw mulch, sorghum straw mulch, rice straw mulch, sunflower straw mulch, plastic mulch, and no mulch (as control). The production systems opted for wheat cultivation were conventionally tilled wheat (CTW), zero-tilled wheat (ZTW) and zero-tilled wheat sown with happy seeder machine (HSW). The CTW resulted in the lowest soil bulk density and the highest soil porosity after wheat harvest, while ZTW behaved oppositely. Similarly, incorporation of crop mulches resulted in the highest soil porosity and the lowest soil bulk density, while no-mulch incorporation and plastic mulch recorded the highest bulk density and the lowest soil porosity. Regarding mulches by production systems’ interaction, CTW with sorghum straw- and plastic mulches recorded the lowest weed density and biomass, while ZTW with no-mulch recorded the highest weed density and biomass at all locations. The CTW with mungbean straw- and plastic mulches resulted in the highest yield due to significant improvement in yield-related traits. However, ZTW with sorghum straw mulch and no-mulch resulted in the lowest wheat yield. Although sorghum straw mulch suppressed weed infestation, it negatively affected wheat growth. Economic analysis revealed that CTW with mungbean straw mulch resulted in the highest gross and net incomes and benefit:cost ratio (BCR), while the ZTW with rice straw- and sorghum straw mulches produced the lowest gross and net incomes and BCR at all locations. Therefore, mungbean straw mulch is a viable option to improve wheat productivity and net economic returns under different agro-climatic conditions of Punjab, Pakistan. Full article

Analyzing the efficiency of the water, energy, and food (WEF) nexus is critical for effective governance strategies. Therefore, three-stage data envelopment analysis (DEA) was used to measure the efficiency level of WEF in the 36 districts of Punjab, Pakistan, for the period from 2015 to 2021. Furthermore, the stochastic frontier was used to analyze the effect of external environmental factors on these efficiency scores of the WEF nexus. The results of the DEA showed that the number of frontier efficiency districts decreased, and most districts experienced rank change over time. Overall, the performance of 50% of the districts declined over time. The relative decline in efficiency was found to be higher in districts Bahwalnaghar and Rahim Yar Khan. The performance of districts Multan and Sheikhupura increased over time, while districts Vehari and Sargodha were the most complete and efficient in actual performance. According to the SFA’s findings, the WEF nexus efficiency of South Punjab districts was negatively impacted by external environmental factors (urbanization rate, manufactured industry output, population), leading to severe stress across WEF sectors. Districts in central and southern Punjab, however, were more likely to have lower rankings because of the positive impact of external environmental factors on the efficiency of the WEF nexus. The substantial rise of external environmental variables focused on scale expansion rather than quality improvement, which created a wide gap in WEF inputs and, hence, reduced the efficiency of the WEF nexus in the districts. The findings of this study provide valuable insights for developing governance strategies based on external environmental factors and WEF resource endowment, and they complement the efficiency calculation of WEF nexus research. Future research should focus on the Baluchistan region, the most deprived area in terms of water, energy, and food. Full article

The sustenance of marginal and small farm households is a pertinent question given that their number is on the rise in South-Asia. The study aims to assess their present socio-economic profile and the challenges faced in order to draw a roadmap of development for these underprivileged households. The study pertains to Indian Punjab and data from the Situation Assessment Survey of the 70th Round of NSSO are used. The concepts of economic surplus, occupational diversity, farm productivity and vertical and horizontal inequalities are used to achieve the objectives. This study reveals that marginal farm households faced food insecurity as they failed to meet consumption expenditure from the income earned. In fact, small farm households are left with an annual economic surplus of Rs 8890 per capita only, after meeting consumption needs. Income is unevenly distributed among farm households with a Gini coefficient of 0.48. The majority of the marginal and small farm households fall in lower-income quintiles and are occupationally more diversified than their larger counterparts. Horizontal inequalities are lower between the farm-size categories (0.14) than within farm-size categories (0.27). The Gini coefficient within each farm-size category is the highest among marginal farm households (0.50), followed by small farm households (0.45), highlighting their economic stress and tug-of-war survival. Further, the farm households belonging to socially lower castes falls only in the marginal farm-size category and represent the lowest income. Development must be sustainable and inclusive, hence, policies to develop marginal farmers’ centric farming systems and high value crops such as potato, cotton, sugarcane and oilseeds, providing high yielding livestock breeds, value addition through farmer-producer organizations, non-farm employment through MGNREGA, provision of institutional credit at subsidised rate of interest and quality health and education facilities in the public sector are recommended to uplift the affected households. Full article

Background: Adults in South Asian countries have high chances of developing coronary artery disease (CAD) as compared to the developed nations. CAD is among the primary non-communicable causes of death in this region. Dyslipidemia, obesity, smoking hypertension, diabetes are considered as important risk factors for CVD. Methods: A case-control study was conducted, with data was collected from the Punjab Institute of Cardiology in Lahore and the University of Lahore Teaching Hospital. A total of 500 subjects were selected, of which 250 were coronary artery disease patients and 250 were healthy controls. The CAD patients were selected from the outpatient department (OPD) and emergency unit of the Punjab Institute of Cardiology and the University of Lahore Teaching Hospital. Results: The mean age of CAD patients was 57.83 ± 7.51 years and that of the controls was 55.32 ± 6.40 years. There was a significant difference in the mean values of biochemical parameters among cases and controls except for fasting blood sugar levels while there was a significant difference (p-value: 0.000) in the mean values of systolic blood pressure among cases and controls. Similarly, the values of diastolic blood pressure were also significantly different (p-value: 0.000) among cases and controls. The values of total blood cholesterol, LDL, triglycerides and HDL were also significantly different among cases and controls. There was a significant relationship between consumption of chicken, eggs, beef, yogurt, junk food, fresh vegetables, and fruits, and incidence of CAD. Consuming milk every day, and consuming fish weekly and consuming ghee had no significant association with the risk of coronary artery disease. On the other hand, from the findings of the unadjusted model, there was a significant association between CAD risk and intake of chicken, beef, egg, yogurt, junk food, fish, vegetables, and fruits. Conclusions: Diet is a risk factor for coronary artery disease and can be adjusted to reduce the risk of CAD. A key finding is that consumption of chicken, beef, eggs and junk food are associated with a high risk of CAD whereas consumption of ghee is not associated with the risk of CAD. Full article