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1.
One Health ; 13: 100281, 2021 Dec.
Article in English | MEDLINE | ID: mdl-34235243

ABSTRACT

Brucellosis is a zoonosis that has a devastating impact on the economy and public health, particularly in the Middle East, including Egypt. This study aimed to define risk factors associated with brucellosis in humans and in their cattle in Fayoum governorate - Upper Egypt. Also, molecular genotyping of recovered Brucella isolates from human cases and their cattle to assess the potential cross-species transmission in the study region. Data were obtained via double matched case-control studies for brucellosis in humans (106 cases and 160 controls) and in their cattle (78 cattle cases and 105 cattle controls). The results of multivariate regression analysis revealed that predictors of human brucellosis were animal-related occupations (OR 2.1, P 0.02), previous infection in other household members (OR 3.2, P 0.007), eating home-made soft cheese (OR 2.3, P 0.03), and exposure to cattle abortions (OR 6.9, P < 0.001). For cattle, predictors of brucellosis were maturity ≥2 years of age (OR 2.9, P 0.01), ≥2 animals reared by the same household (OR 3.7-6.9, P ≤ 0.001), and recent abortion (OR 15.2, P 0.01). Twelve Brucella isolates were recovered from eight human cases (7.5%, 8/106) and four cattle cases (6.2%, 4/65). All isolates were B. melitensis biovar 3. Analysis of the IS711 gene sequence revealed complete homology (100%) between isolates. Six virulence genes were utilized for virutyping: virB (100%), omp25 (100%), amiC (100%), ure (91.7%), wbkA (91.7%), and bvfA (75%). Virutyping revealed four virutypes: V1 (lack bvfA, 16.7%), V2 (harbored all genes, 66.7%), V3 (lack wbkA, 8.3%), and V4 (lack wbkA and ure, 8.3%). Repetitive extragenic palindromic PCR (REP-PCR) typing revealed two REP types. Combined REP-PCR/virulence genotyping revealed five different genotypes (G1-G5) for the detected isolates and a unique genotype for the reference strain (G6, B. melitensis bv3 Ether). Human and cattle isolates from the same household had matched genotypes. In conclusion, there were widespread risk factors among the cases studied. Health education for high-risk groups is essential for disease prevention, and combined REP-PCR/virulence genotyping is a quick tool for traceability, particularly in developing countries endemic with brucellosis as Egypt.

2.
J Environ Public Health ; 2017: 4783791, 2017.
Article in English | MEDLINE | ID: mdl-29201063

ABSTRACT

Malnutrition is an increasing health problem among children in developing countries. We assessed the level of malnutrition and associated factors among school children in a rural setting in Fayoum Governorate, Egypt. A school based cross-sectional survey was conducted on children (6-17 years) in Manshit El Gamal village in Tamia district of Fayoum Governorate. Weight, height, and age data were used to calculate z-scores of the three nutritional indicators using WHO anthroPlus. Sociodemographics and lifestyles Data were collected. Prevalence of stunting, underweight, and wasting was 34.2%, 3.4%, and 0.9%, respectively, while obesity was 14.9%. Prevalence of obesity was significantly higher in younger age group of 6-9 years in comparison with older age and was higher in males versus females in 10-13-year-age group. Increasing age, reduced poultry consumption, and escaping breakfast were associated factors for stunting with OR (95% CI) 1.27 (1.17-1.37), 2.19 (1.4-3.4), and 2.3 (1.07-5.03). Younger age and regular employment of the father were factors associated with obesity (OR = 0.753; 0.688-0.824 and OR = 2.217; 1.4-3.5). Malnutrition is highly prevalent in Fayoum in line with the national prevalence and associated with age, gender, regularity of father's employment, and dietary factors.


Subject(s)
Growth Disorders/epidemiology , Malnutrition/epidemiology , Obesity/epidemiology , Thinness/epidemiology , Wasting Syndrome/epidemiology , Adolescent , Anthropometry , Child , Cross-Sectional Studies , Egypt/epidemiology , Female , Growth Disorders/etiology , Humans , Life Style , Male , Obesity/etiology , Prevalence , Risk Factors , Rural Population , Socioeconomic Factors , Students/statistics & numerical data , Thinness/etiology , Wasting Syndrome/etiology
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