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Original Articles
Open Access

Obesity as a public health problem among adult women in rural Tanzania

Gudrun B Keding, John M Msuya, Brigitte L Maass and Michael B Krawinkel
Global Health: Science and Practice November 2013, 1(3):359-371; https://doi.org/10.9745/GHSP-D-13-00082
Gudrun B Keding
aJustus Liebig University Giessen, Institute of Nutritional Sciences, Department of International Nutrition, Giessen, Germany
bBioversity International, Nairobi, Kenya
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  • For correspondence: g.keding@cgiar.org
John M Msuya
cSokoine University of Agriculture (SUA), Department of Food Science & Technology, Nutrition and Development Economics, Morogoro, Tanzania
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Brigitte L Maass
dInternational Center for Tropical Agriculture, Nairobi, Kenya
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Michael B Krawinkel
aJustus Liebig University Giessen, Institute of Nutritional Sciences, Department of International Nutrition, Giessen, Germany
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Figures & Tables

Figures

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  • Figure1
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    A portable scale and measuring board allowed the researchers to collect anthropometric measurements from study participants during all 3 household surveys.

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    Interviewers showed study participants 3 different-sized containers to help them estimate portion sizes of the foods they ate.

  • Figure 1.
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    Figure 1.

    Association Between Body Mass Index (BMI) and Food Variety Score (FVS) (N = 210; ρ = 0.204; P = .003)

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    Figure 2.

    Association Between Body Mass Index (BMI) and Dietary Diversity Score (DDS) (N = 210; ρ = 0.147; P = .03)

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    Figure 3.

    Proportion of Women From 3 Districts in Tanzania Associating Positive Characteristics With a Corpulent Person (multiple answers possible)

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    Figure 4.

    Proportion of Women From 3 Districts in Tanzania Associating Negative Characteristics With a Corpulent Person (multiple answers possible)

Tables

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    Table 1. Characteristics of the Women Interviewed in 3 Districts of Tanzania
    CharacteristicsAll DistrictsDistrict 1 (Kongwa)District 2 (Muheza)District 3 (Singida)
    N210526989
    Age, mean, y33.730.834.634.8
    Ethnic group (%)
    Bondei7.60.023.20.0
    Gogo13.353.80.00.0
    Kaguru7.128.80.00.0
    Nyaturu41.93.80.096.6
    Shambaa11.413.534.80.0
    Other18.60.042.03.4
    Education (%)
    Illiterate7.67.78.76.7
    Primary school90.088.588.492.1
    More than primary2.43.82.91.1
    Wealth statusa (%)
    Low26.730.833.319.1
    Medium29.036.529.024.7
    High44.332.737.756.2
    DDS (median across seasons)b6584
    FVS (mean across seasons)c8.47.210.97.2
    Cultivating/collecting indigenous vegetables (%)98.198.199.097.4
    Cultivating exotic vegetables (%)31.112.216.953.2
    • ↵a According to number of possessions, setting of the house, number of livestock, type of occupation, and whether vegetables were sold.

    • ↵b DDS, Dietary Diversity Score, calculated by summing the number of food groups consumed by an individual over a 24-hour recall period.

    • ↵c FVS, Food Variety Score, counting single foods over a 24-hour recall period.

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    Table 2. Median Body Mass Index (BMI) Values and Percent Distribution in 4 BMI Categories of Interviewed Women, by District and Season, Rural Tanzania
    Distribution by weight category (%)
    NMedian (kg/m2)Range (kg/m2)Underweight (<18.5 kg/m2)Normal (18.5–24.9 kg/m2)Overweight (25.0–29.9 kg/m2)Obese (≥30 kg/m2)
    All districts/seasons21021.714.9–37.77.171.015.76.2
     Kongwa5221.617.7–34.71.975.019.23.8
     Muheza6922.514.9–37.78.766.714.510.1
     Singida8921.416.4–35.29.071.914.64.5
    June/July (dry season)21021.714.3–37.36.771.915.26.2
    November/December (short rains)21021.915.3–37.78.170.015.76.2
    March/April (long rains)21021.712.3–37.210.068.614.86.7
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    Table 3. Results of Multiple Regression Analysis With ln(BMI) as Dependent Variable, 210 Women from 3 Districts of Tanzania, Mean Across 3 Seasons if Applicable
    Unstandardized coefficientsStandardized coefficients
    BSEβtP-valueeB
    (Constant)2.8980.07936.486.000
    Age0.0030.0020.1211.748.081.003
    Low education0.0680.0410.1121.642.101.070
    High education−0.0920.072−0.086−1.277.200.912
    Kongwa0.0200.0290.0530.692.491.020
    Muheza−0.0320.034−0.093−0.935.350.969
    Dietary Pattern 20.0220.0130.1391.682.091.022
    FVS0.0140.0070.2042.008.0461.014
    • Abbreviations: BMI, body mass index; FVS, Food Variety Score; ln, natural logarithm of; SE, standard error.

    • eB  =  inverse of the natural logarithm of B.

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Global Health: Science and Practice: 1 (3)
Global Health: Science and Practice
Vol. 1, No. 3
November 01, 2013
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Obesity as a public health problem among adult women in rural Tanzania
Gudrun B Keding, John M Msuya, Brigitte L Maass, Michael B Krawinkel
Global Health: Science and Practice Nov 2013, 1 (3) 359-371; DOI: 10.9745/GHSP-D-13-00082

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Obesity as a public health problem among adult women in rural Tanzania
Gudrun B Keding, John M Msuya, Brigitte L Maass, Michael B Krawinkel
Global Health: Science and Practice Nov 2013, 1 (3) 359-371; DOI: 10.9745/GHSP-D-13-00082
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