Heavy Metals Contents of Commonly‐used Cosmetics at Ahmadu Bello University, Zaria, Nigeria
Notice bibliographique
Résumé
Cosmetics are preparations used in contact with various parts of the body such as epidermis, hair, nails, teeth, lips, genitalia; and mucous membrane of the oral cavity, for purpose of cleaning, perfuming, protecting, changing appearances for ‘better’, converting body odours to pleasant fragrances, and generally keeping body surfaces in good condition. Several studies have shown unacceptable levels of heavy metals in cosmetics, and which were linked to chronic toxicities. The aim of this study was to determine heavy metals contents of commonly‐used cosmetics at Ahmadu Bello University Zaria ‐ one of Nigeria’s 165 universities, which offers 520 programs by 98 academic departments housed in 16 faculties with total student and staff populations (and approximate female percent representation) of >60,000 (~35%) and >10,000 (~20%) respectively. A survey at its main campus, revealed 11 cosmetic shops while some of the other 415 on‐campus shops also sold diverse cosmetics. These included body creams/lotions/toners (150 different brands), perfumes/splashes (145), soaps (93), face powders (57), lipsticks/lip glosses (33), shampoos (30), toothpastes (9) and shaving creams/powders (7). Using purposive/convenient sampling techniques, students from all 6 departments in the Faculty of Pharmaceutical Sciences, were served a link to a questionnaire deployed on Survey Monkey TM platform; and the first 100 respondents‐indicated most‐commonly‐used cosmetics were identified, and analysed for 11 elements using flame atomic absorption spectrophotometer. Thus, 10 cosmetics used by the (stated percentage of participating) students, namely: oral‐B toothpaste (46%), veets shaving cream (32%), petals shampoo (19%), dettol medicated soap (19%), eva soap (19%), absolute lip gloss (16%), huda beauty pure matte lipstick (15%), iman makeup pressed powder (12%), dove lotion (7%) and jergen’s shea butter lotion (7%) were analysed; but not abraaj oud perfume (8%) due to the latter’s volatility. The concentrations in ppm were determined for the heavy metals; and compared where applicable, with standard limits set by the FDA, Health Canada, EU and WHO. The values obtained were: calcium (0.031–1.542), cadmium (0.001–0.067), cobalt (0.013–0.408), copper (0.004–0.178), iron (0.131–10.779), lead (0.00–0.590), magnesium (0.001–0.388), manganese (0.001–0.928), nickel (0.00–2.720), sodium (0.000–0.022) and zinc (0.000–0.736). None of the 11 heavy metals was undetected in all the 10 cosmetic samples studied; and the lipstick had the highest levels of 5 heavy metals ‐ cobalt, copper, magnesium, manganese and nickel. In addition, the concentration of nickel in the lipstick analysed, being 2.720 ppm, was several times higher than some nickel standard limits e.g. those specified by FDA (<0.6 ppm) and EU (<0.6 ppm), but not the standard limits specified by Health Canada (<10 ppm) and WHO (<10 ppm). While the vast majority of heavy metals contents of the cosmetics studied were below specified concentrations, possibilities of their accumulation in biological systems over time, constitute potential health risks. Absence of obvious standard limits for many heavy metals plus large disparities in those specified by various regulatory bodies complicate assessment of cosmetics toxicity.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».