Work

Quantification of Heavy Metals in Ready-To-Drink Milk Tea Samples Collected from Markets of Multan, Pakistan

Year: 2025
Type: article
Abstract: This study investigates the quantification of heavy metals in milk tea prepared in various restaurants in Multan, Pakistan, assessing the associated health risks and performing a proximate analysis of its key components. A total of 75 tea samples were collected from lower-, middle-, and upper-class restaurants and analyzed for heavy metal content using Atomic Absorption Spectroscopy (AAS) after a rigorous sample preparation and wet digestion process. Toxic metals, including arsenic, lead, and cadmium, were evaluated alongside essential minerals such as iron, zinc, copper, and cobalt. Results revealed arsenic concentrations exceeding WHO permissible limits in 65% of water samples, while lead and cadmium levels surpassed thresholds in 40% and 38% of cases, respectively. Additionally, proximate analyses of black tea and milk were conducted to measure moisture, protein, fat, fiber, and ash contents using established AOAC methods. Statistical analyses (ANOVA and LSD) highlighted significant differences in heavy metal concentrations across the sampled restaurant classes, with lower-class establishments showing the highest contamination levels. Heavy metal contamination poses a serious risk to food safety and public health. This study measured arsenic, cadmium, cobalt, copper, iron, lead, and zinc in milk, tea, water, and sugar from restaurants of different classes. Contamination was highest in lower-class restaurants due to inadequate facilities, while upper-class establishments had the lowest levels. Middle-class restaurants showed moderate contamination, with higher iron and zinc in milk. The findings highlight the health risks of heavy metal exposure and the urgent need for stricter contamination controls to improve food safety standards in Pakistan.
Authors: Ghulam Husnain, Iqra Kanwal, Danish Kamal, Faraz Hussain, Zuha Fatima, Fraz Ahmad, Farhad Alam, Qamar Sajjad, Muhammad Suleman Najib
Language: English
Subfield: Pollution
Open Access status: hybrid
OpenAlex ID: W4408952867
FWCI:
Cites: 25
Cited by:
Related to: 10