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Nutrients · 2026

Determinants of Folate and Vitamin B12 Deficiencies in Women of Reproductive Age: Insights from the 2018 National Nutrition Survey of Pakistan.

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Iqbal Junaid, Begum Kehkashan, Zuberi Rabia, Sajid Muhammad, Nausheen Sidrah, Chauhadry Imran A, Soofi Sajid Bashir, Bhutta Zulfiqar A

Аннотация

Background: Anemia is a major public health issue, particularly among women of reproductive age (WRA) in low- and middle-income countries (LMICs). Pakistan's National Nutrition Survey (NNS) 2011 showed a high prevalence of vitamin B12 (B12) and folate deficiency among WRA, necessitating further investigation in subsequent surveys. Methods: Blood samples from 31,828 WRA (15-49 years old) were collected using a stratified multi-stage sampling technique in NNS-2018. We conducted a secondary analysis using population-weighted logistic regression to assess the association of potential factors with B12 and folate deficiency. B12 (n = 4442) and folate (n = 12,662) samples were measured using an electrochemiluminescence immunoassay and a Centers for Disease Control and Prevention, USA (CDC)-approved microbiologic assay, respectively. Results: Folate deficiency was present in 44.7% WRA, and 20.2% had B12 deficiency. Provincial distribution was associated with folate deficiency, i.e., Sindh (OR = 1.140, 95% CI 1.018, 1.285), Baluchistan (OR = 1.237, 95% CI 1.052, 1.453), and Islamabad (OR = 1.524, 95% CI 1.109, 2.092), while B12 deficiency was prevalent in Islamabad (OR = 1.673, 95% CI 1.122, 2.497), Gilgit Baltistan (OR = 2.472, 95% CI 1.197, 5.106), and newly merged districts of KPK (OR = 1.584, 95% CI 0.977, 2.570). Rural residence (OR = 1.407, 95% CI 1.125, 1.760), obesity (OR = 1.649, 95% CI 1.282, 2.122), and overweight (OR = 1.560, 95% CI 1.262, 1.928) were associated with B12 deficiency. Conclusions: Our results show regional and demographic differences in the prevalence of folate and B12 deficiencies among WRA. This underscores the need for targeted nutritional interventions and further longitudinal studies to identify potentially associated factors.

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