Association between the household welfare index and Body Mass Index among 35–70 year old Algerian and Tunisian adults, by gender.

<p>Association between quintiles of the asset-based household welfare index and Body Mass Index among Algerian and Tunisian adults, by gender. Comparison of unadjusted or adjusted (for age, marital status, education, and profession) BMI means by general linear models taking into account sampling design: P-value for null hypothesis of no difference in unadjusted or adjusted BMI means between quintiles of household welfare. Trends interpolated by quadratic fit. Complete case analysis (Algeria women: n = 2678, men: n = 1944, Tunisia women: n = 2725, men: n = 2238).</p

Urban vs. rural contrasts of overall and abdominal adiposity among Algerian and Tunisian 35–70 year old adults, by gender.

<p>Urban vs. rural prevalence proportion odd-ratios weighted estimates for overall and abdominal adiposity, by gender and country (Women Algeria: urban n = 1735, rural: n = 1007; women Tunisia: urban n = 1638, rural: n = 1326; men Algeria: urban n = 1185, rural: n = 819; men Tunisia: urban n = 1423, rural: n = 956). BMI: Body Mass Index in kg/m², WHtR: Waist (cm) to Height (cm) Ratio. C.I.: 0.95 confidence interval adjusted for sampling design.</p

Area of residence and socio-economic factors among 35–70 year old Algerian and Tunisian adults, by gender.

a<p>Weighted proportions.</p>b<p>Null hypothesis of identical distribution in women vs. men (P-value adjusted for sampling design).</p>c<p>Asset-based household welfare index: increasing welfare from 1^st to 5^th quintile.</p

Association of obesity with socio-economic factors, among 35–70 year old Algerians and Tunisians, by gender.

a<p>Adjusted for age, marital status, education, profession and household welfare index.</p>b<p>Weighted proportion of obesity in each category.</p>c<p>Prevalence Odds-Ratio vs. reference category.</p>d<p>0.95 design based confidence interval.</p>e<p>Complete-case analysis.</p>f<p>Asset-based household welfare index: increasing welfare from 1^st to 5^th quintile.</p

Gender contrasts of overall and abdominal adiposity among Algerian and Tunisian 35–70 year old adults.

<p>Women vs. men prevalence proportion odd-ratios weighted estimates for overall and abdominal adiposity, by country (Algeria women: n = 2742, men: n = 2004; Tunisia women: n = 2964, men: n = 2379). BMI: Body Mass Index in kg/m², WHtR: Waist (cm) to Height (cm) Ratio. C.I.: 0.95 confidence interval adjusted for sampling design.</p

Inventory on the dietary assessment tools available and needed in africa: a prerequisite for setting up a common methodological research infrastructure for nutritional surveillance, research, and prevention of diet-related non-communicable diseases

<p><i>Objective:</i> To carry out an inventory on the availability, challenges, and needs of dietary assessment (DA) methods in Africa as a pre-requisite to provide evidence, and set directions (strategies) for implementing common dietary methods and support web-research infrastructure across countries. <i>Methods:</i> The inventory was performed within the framework of the “Africa's Study on Physical Activity and Dietary Assessment Methods” (AS-PADAM) project. It involves international institutional and African networks. An inventory questionnaire was developed and disseminated through the networks. Eighteen countries responded to the dietary inventory questionnaire. <i>Results:</i> Various DA tools were reported in Africa; 24-Hour Dietary Recall and Food Frequency Questionnaire were the most commonly used tools. Few tools were validated and tested for reliability. Face-to-face interview was the common method of administration. No computerized software or other new (web) technologies were reported. No tools were standardized across countries. <i>Conclusions:</i> The lack of comparable DA methods across represented countries is a major obstacle to implement comprehensive and joint nutrition-related programmes for surveillance, programme evaluation, research, and prevention. There is a need to develop new or adapt existing DA methods across countries by employing related research infrastructure that has been validated and standardized in other settings, with the view to standardizing methods for wider use.</p