1.Classifying Sources of Nitrate Contamination in an Alluvial Deposit Aquifer System Using Hydrogeochemical Properties and Multivariate Statistical Techniques
Aida Soraya SHAMSUDDIN ; Sharifah Norkhadijah Syed Ismail ; Emilia Zainal ABIDIN ; Ho Yu BIN
Malaysian Journal of Medicine and Health Sciences 2018;14(SP1):30-39
Introduction: This study determined nitrate concentration and identify the classifying sources of nitrate pollution in the alluvial deposit aquifer system in Bachok, Kelantan. Materials and Methods: A total of 300 groundwater samples were collected in two different areas; agricultural area (150 samples) and non-agricultural area (150 samples). The samples were analyzed for nitrate and other parameters such as pH, EC, NH4+, TDS, turbidity and salinity. The multivariate analyses were used to identify factors that govern the groundwater quality and potential nitrate sources in the study area. Results: Samples in the agricultural area were slightly acidic (5.89 ± 0.67), contained high nitrate (15.10 ± 15.90 mg/L NO3-N), NH4+ (0.82 ± 1.24 mg/L) and turbidity (3.25 ± 2.78 NTU). The principal component analysis (PCA) have identified the groundwater quality in the study area was influenced by the natural processes and anthropogenic activities. Based on the hierarchal cluster analysis (HCA), Cluster II in the agricultural area was identified to be most heavily nitrate contamination, while Cluster III in the non-agricultural area was identified to be strongly affected by seawater intrusion. Conclusion: The findings of this study are useful for developing protection alternatives of private well waters to prevent further deterioration of groundwater quality by nitrate such as control of nitrogen fertilizer use, manure applications and other agricultural practices in the agricultural area. In order to reduce the health risk of nitrate, private well water users in this area should be advised to treat their water or find alternative sources for drink
2.Prevalence of Mental Health Problems Among University Students and Association With Body Mass Index (BMI) and Diet Quality
Nur Nadhira Khairul Azhar ; Muhamad Ariff Ibrahim ; Mohd Radzi Tarmizi A Halim ; Aida Soraya Shamsuddin ; Nuraniza Azahari ; Mohd Ahsani A. Malek
Malaysian Journal of Medicine and Health Sciences 2023;19(No.3):82-90
Introduction: Numerous factors contributed to the susceptibility of university students to develop mental health
issues. Objective: This study aimed to assess the prevalence of mental health problems among International Islamic
University Malaysia (IIUM) students and their relationships with diet quality and body mass index (BMI). Methods: A
cross-sectional study was conducted among 104 students. The Depression, Anxiety, and Stress Scale (DASS-21) was
used to assess students’ depression, anxiety, and stress levels. The Malaysian Healthy Eating Index (M-HEI) was used
to assess diet quality. Spearman Rho was used to determine the relationships between variables. Results: Approximately 69.4% (n = 34), 71.4% (n = 35), and 48.9% (n = 34) of male students experienced moderate to extremely
severe symptoms of depression, anxiety, and stress, respectively. In contrast, 85.4% (n = 47), 89.1% (n = 49), and
54.6% (n = 30) of female students had moderate to extremely severe symptoms of depression, anxiety, and stress,
respectively. No correlations were found between diet quality and BMI with students’ mental health problems. For
male students, there were negative significant associations reported between fat-rich foods (r = -0.447, p-value =
0.001) and sugar-rich foods (r = -0.332, p-value = 0.020) intake with depression; a positive significant relationship
between fruit intake and anxiety (r = 0.284, p-value = 0.048); a positive relationship between fruit intake and stress (r
= 0.300, p-value = 0.036); and a negative relationship between fat-rich foods and stress (r = -0.293, p-value = 0.041).
Female students only had a significant negative correlation between fish intake and anxiety (r = -0.376, p-value =
0.005). Conclusion: No associations were found between diet quality, BMI, and mental health problems. A more
profound comprehension of the connections between risk factors and mental health could lead to new intervention
strategies.