Global Burden of Double Malnutrition: Has Anyone Seen It?
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{"title"=>"Global burden of double malnutrition: Has anyone seen it?", "type"=>"journal", "authors"=>[{"first_name"=>"Daniel J.", "last_name"=>"Corsi", "scopus_author_id"=>"36815664100"}, {"first_name"=>"Jocelyn E.", "last_name"=>"Finlay", "scopus_author_id"=>"23008230900"}, {"first_name"=>"S. V.", "last_name"=>"Subramanian", "scopus_author_id"=>"55433328900"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"21980384", "issn"=>"19326203", "sgr"=>"80053274129", "pui"=>"362648541", "scopus"=>"2-s2.0-80053274129", "isbn"=>"1932-6203 (Electronic)\\n1932-6203 (Linking)", "doi"=>"10.1371/journal.pone.0025120"}, "id"=>"2e12ba69-78b4-38b3-934e-410f74fc4512", "abstract"=>"BACKGROUND: Low- to middle-income countries (LMICs) are believed to be characterized by the coexistence of underweight and overweight. It has also been posited that such coexistence is appearing among the low socioeconomic status (SES) groups.\\n\\nMETHODS: We conducted a cross-sectional analysis of nationally representative samples of 451,321 women aged 20-49 years drawn from 57 Demographic and Health Surveys conducted between 1994 and 2008. Body Mass Index (BMI in kg/m²), was used to define underweight and overweight following conventional cut-points. Covariates included age, household wealth, education, and residence. We estimated multinomial multilevel models to assess the extent to which underweight (BMI<18.5 kg/m²) and overweight (BM I≥ 25.0 kg/m²) correlate at the country-level, and at the neighborhood-level within each country.\\n\\nRESULTS: In age-adjusted models, there was a strong negative correlation between likelihood of being underweight and overweight at country- (r = -0.79, p<0.001), and at the neighborhood-level within countries (r = -0.51, P<0.001). Negative correlations ranging from -0.11 to -0.90 were observed in 46 of the 57 countries at the neighborhood-level and 29/57 were statistically significant (p ≤ 0.05). Similar negative correlations were observed in analyses restricted to low SES groups. Finally, the negative correlations across countries, and within-countries, appeared to be stable over time in a sub-set of 36 countries.\\n\\nCONCLUSION: The explicitly negative correlations between prevalence of underweight and overweight at the country-level and at neighborhood-level suggest that the hypothesized coexistence of underweight and overweight has not yet occurred in a substantial manner in a majority of LMICs.", "link"=>"http://www.mendeley.com/research/global-burden-double-malnutrition-anyone-seen-it", "reader_count"=>62, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>2, "Researcher"=>8, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>6, "Other"=>4, "Student > Master"=>12, "Student > Bachelor"=>7, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>3, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>2, "Researcher"=>8, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>6, "Other"=>4, "Student > Master"=>12, "Student > Bachelor"=>7, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>3, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>7, "Nursing and Health Professions"=>3, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>12, "Medicine and Dentistry"=>20, "Neuroscience"=>1, "Sports and Recreations"=>2, "Business, Management and Accounting"=>1, "Psychology"=>1, "Social Sciences"=>12, "Immunology and Microbiology"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>20}, "Neuroscience"=>{"Neuroscience"=>1}, "Social Sciences"=>{"Social Sciences"=>12}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Psychology"=>{"Psychology"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>12}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>7}}, "reader_count_by_country"=>{"Colombia"=>1, "Taiwan"=>1, "United Kingdom"=>2, "Malaysia"=>1}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/730105"], "description"=>"<p>Notes: Panel A adjusted for age, education, household wealth, and place of residence, Panel B adjusted for age and urban/rural place of residence. <b>Country abbreviations</b>: AL Albania, AM Armenia, AZ Azerbaijan, BD Bangladesh, BJ Benin, BO Bolivia, BR Brazil, BF Burkina Faso, KH Cambodia, CM Cameroon, CF Central African Republic, TD Chad, CO Colombia, KM Comoros, CD Congo, Dem. Rep., CG Congo, Rep., CI Cote d'Ivoire, DO Dominican Republic, EG Egypt, ET Ethiopia, GA Gabon, GH Ghana, GT Guatemala, GN Guinea, HT Haiti, HN Honduras, IN India, JO Jordan, KZ Kazakhstan, KE Kenya, KG Kyrgyz Republic, LS Lesotho, LR Liberia, MG Madagascar, MW Malawi, ML Mali, MD Moldova, MA Morocco, MZ Mozambique, NA Namibia, NP Nepal, NI Nicaragua, NE Niger, NG Nigeria, PE Peru, RW Rwanda, SN Senegal, SL Sierra Leone, SZ Swaziland, TZ Tanzania, TG Togo, TR Turkey, UG Uganda, UZ Uzbekistan, ZM Zambia, ZW Zimbabwe, ZA South Africa.</p>", "links"=>[], "tags"=>["plots", "country-level", "residuals", "underweight", "overweight", "women", "aged", "57", "low-", "middle-income", "countries", "low-socioeconomic", "groups"], "article_id"=>400450, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.g002", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatter_plots_of_country_level_residuals_for_underweight_and_overweight_among_women_aged_20_8211_49_in_57_low_to_middle_income_countries_overall_A_and_in_low_socioeconomic_status_groups_B_/400450", "title"=>"Scatter plots of country-level residuals for underweight and overweight among women aged 20–49 in 57 low- to middle-income countries overall (A), and in low-socioeconomic status groups (B).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-09-28 00:07:30"}
  • {"files"=>["https://ndownloader.figshare.com/files/729987"], "description"=>"<p>Prevalence of underweight (BMI<18.5 kg/m<sup>2</sup>) (A) and overweight (BMI≥25.0 kg/m<sup>2</sup>) (B) among women aged 20–49 in 57 low- to middle-income countries.</p>", "links"=>[], "tags"=>["underweight", "overweight", "women", "aged", "57", "low-", "middle-income"], "article_id"=>400340, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.g001", "stats"=>{"downloads"=>1, "page_views"=>22, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prevalence_of_underweight_BMI_2_A_and_overweight_BMI_8805_25_0_kg_m_2_B_among_women_aged_20_8211_49_in_57_low_to_middle_income_countries_/400340", "title"=>"Prevalence of underweight (BMI<18.5 kg/m<sup>2</sup>) (A) and overweight (BMI≥25.0 kg/m<sup>2</sup>) (B) among women aged 20–49 in 57 low- to middle-income countries.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-09-28 00:05:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/730520"], "description"=>"<p>Notes: Percent underweight represents the number of women with a BMI of less than 18.5 divided by the total number of women and then multiplied by 100; percent normal weight represent percent overweight represents the number of women with a BMI between 18.5 and 24.9 divided by the total number of and then multiplied by 100; percent overweight represents the number of women with a BMI of 25 and above divided by the total number of women and then multiplied by 100. Percentages are calculated as row percentages.</p>", "links"=>[], "tags"=>["nutritional", "women", "aged", "57", "low-", "middle-income"], "article_id"=>400867, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.t002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Survey_year_sample_size_number_of_neighborhoods_and_distribution_of_nutritional_status_for_women_aged_20_8211_49_in_57_low_to_middle_income_countries_/400867", "title"=>"Survey year, sample size, number of neighborhoods, and distribution of nutritional status for women aged 20–49 in 57 low- to middle-income countries.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-09-28 00:14:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/730375"], "description"=>"<p>Scatter plot of country-level residuals for underweight and overweight among men aged 15–54 in 7 low- to middle-income countries (<i>r</i> = −0.72, <i>P</i> = 0.28).</p>", "links"=>[], "tags"=>["country-level", "residuals", "underweight", "overweight", "men", "aged", "low-", "middle-income", "countries"], "article_id"=>400724, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.g005", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatter_plot_of_country_level_residuals_for_underweight_and_overweight_among_men_aged_15_54_in_7_low_to_middle_income_countries_r__0_72_P_0_28_/400724", "title"=>"Scatter plot of country-level residuals for underweight and overweight among men aged 15–54 in 7 low- to middle-income countries (<i>r</i> = −0.72, <i>P</i> = 0.28).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-09-28 00:12:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/730555"], "description"=>"<p>Notes:</p><p>*n = 7 countries; 10,746 neighborhoods; 119,786 individuals.</p><p>**(Age 15+ y).</p><p>Correlations are based on the neighborhood-level covariance in underweight and overweight from age-adjusted models.</p>", "links"=>[], "tags"=>["within-country", "age-adjusted", "underweight", "overweight", "men", "aged", "dhs", "surveys", "low-", "middle-income"], "article_id"=>400898, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.t003", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_country_and_neighborhood_level_and_within_country_neighborhood_age_adjusted_correlation_of_underweight_and_overweight_among_men_aged_15_8211_54_from_DHS_surveys_in_seven_low_to_middle_income_countries_/400898", "title"=>"Global (country and neighborhood level) and within-country (neighborhood) age-adjusted correlation of underweight and overweight among men aged 15–54 from DHS surveys in seven low- to middle-income countries.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-09-28 00:14:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/368790", "https://ndownloader.figshare.com/files/368894", "https://ndownloader.figshare.com/files/368977"], "description"=>"<div><h3>Background</h3><p>Low- to middle-income countries (LMICs) are believed to be characterized by the coexistence of underweight and overweight. It has also been posited that such coexistence is appearing among the low socioeconomic status (SES) groups.</p> <h3>Methods</h3><p>We conducted a cross-sectional analysis of nationally representative samples of 451321 women aged 20–49 years drawn from 57 Demographic and Health Surveys conducted between 1994 and 2008. Body Mass Index (BMI in kg/m<sup>2</sup>), was used to define underweight and overweight following conventional cut-points. Covariates included age, household wealth, education, and residence. We estimated multinomial multilevel models to assess the extent to which underweight (BMI<18.5 kg/m<sup>2</sup>) and overweight (BMI≥25.0 kg/m<sup>2</sup>) correlate at the country-level, and at the neighborhood-level within each country.</p> <h3>Results</h3><p>In age-adjusted models, there was a strong negative correlation between likelihood of being underweight and overweight at country- (<em>r</em> = −0.79, <em>p</em><0.001), and at the neighborhood-level within countries (<em>r</em> = −0.51, <em>P</em><0.001). Negative correlations ranging from −0.11 to −0.90 were observed in 46 of the 57 countries at the neighborhood-level and 29/57 were statistically significant (<em>p</em>≤0.05). Similar negative correlations were observed in analyses restricted to low SES groups. Finally, the negative correlations across countries, and within-countries, appeared to be stable over time in a sub-set of 36 countries.</p> <h3>Conclusion</h3><p>The explicitly negative correlations between prevalence of underweight and overweight at the country-level and at neighborhood-level suggest that the hypothesized coexistence of underweight and overweight has not yet occurred in a substantial manner in a majority of LMICs.</p> </div>", "links"=>[], "tags"=>["seen"], "article_id"=>132879, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0025120.s001", "https://dx.doi.org/10.1371/journal.pone.0025120.s002", "https://dx.doi.org/10.1371/journal.pone.0025120.s003"], "stats"=>{"downloads"=>2, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Global_Burden_of_Double_Malnutrition_Has_Anyone_Seen_It_/132879", "title"=>"Global Burden of Double Malnutrition: Has Anyone Seen It?", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-09-28 00:47:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/730195"], "description"=>"<p>Notes: Panel A adjusted for age, education, household wealth, and place of residence, Panel B adjusted for age and place of residence; *<i>P</i><0.05.</p>", "links"=>[], "tags"=>["underweight", "overweight", "women", "aged", "57", "low-", "middle-income", "low-socioeconomic", "groups"], "article_id"=>400541, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Within_country_neighborhood_level_correlation_of_underweight_and_overweight_among_women_aged_20_8211_49_in_57_low_to_middle_income_countries_overall_A_and_in_low_socioeconomic_status_groups_B_/400541", "title"=>"Within country (neighborhood-level) correlation of underweight and overweight among women aged 20–49 in 57 low- to middle-income countries, overall (A), and in low-socioeconomic status groups (B).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-09-28 00:09:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/730432"], "description"=>"<p>*Notes: Study sample includes all non-pregnant women aged 20–49 and included women with and without children of any age.</p><p>**Adjusted for age, education, household wealth, and place of residence.</p>", "links"=>[], "tags"=>["adjusted", "underweight", "overweight", "women", "younger", "groups", "57", "low-", "middle-income"], "article_id"=>400782, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.t004", "stats"=>{"downloads"=>3, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_country_level_age_and_fully_adjusted_correlation_of_underweight_and_overweight_among_women_with_and_without_children_and_among_women_of_younger_and_middle_age_groups_in_57_low_to_middle_income_countries_/400782", "title"=>"Global (country level) age and fully adjusted correlation of underweight and overweight among women with and without children, and among women of younger and middle age groups in 57 low- to middle-income countries.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-09-28 00:13:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/730288"], "description"=>"<p>Notes: Models adjusted for age; <b>Country abbreviations</b>: AM Armenia, BD Bangladesh, BJ Benin, BO Bolivia, BF Burkina Faso, KH Cambodia, CM Cameroon, TD Chad, CO Colombia, CI Cote d'Ivoire, EG Egypt, ET Ethiopia, GH Ghana, GN Guinea, HT Haiti, IN India, JO Jordan, KZ Kazakhstan, KE Kenya, MG Madagascar, MW Malawi, ML Mali, MA Morocco, MZ Mozambique, NA Namibia, NP Nepal, NI Nicaragua, NE Niger, NG Nigeria, PE Peru, RW Rwanda, TZ Tanzania, TR Turkey, UG Uganda, ZM Zambia, ZW Zimbabwe, GC Global (country-level), GE Global (neighborhood-level).</p>", "links"=>[], "tags"=>["age-adjusted", "underweight", "overweight", "women", "aged", "dhs", "36", "low-", "middle-income", "countries", "repeated"], "article_id"=>400633, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.g004", "stats"=>{"downloads"=>2, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Within_country_neighborhood_and_global_country_and_neighborhood_level_age_adjusted_correlation_of_underweight_and_overweight_among_women_aged_20_49_at_the_first_DHS_survey_median_year_1996_vs_the_most_recent_DHS_survey_median_year_2005_in_36_low_to_middl/400633", "title"=>"Within-country (neighborhood) and global (country and neighborhood level) age-adjusted correlation of underweight and overweight among women aged 20–49 at the first DHS survey (median year: 1996) <i>vs.</i> the most recent DHS survey (median year: 2005) in 36 low- to middle-income countries with repeated surveys.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-09-28 00:10:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/730475"], "description"=>"<p>\n <b>Notes:</b></p><p>*Study sample includes all non-pregnant women aged 20–49 and included women with and without children of any age.</p><p>**<b>Correlations adjusted for age, education, household wealth, and place of residence.</b></p>", "links"=>[], "tags"=>["correlations", "underweight", "overweight", "women", "older", "groups", "colombia"], "article_id"=>400823, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.t005", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Within_country_correlations_between_underweight_and_overweight_among_women_of_younger_middle_and_older_age_groups_in_Colombia_and_South_Africa_/400823", "title"=>"Within country correlations between underweight and overweight among women of younger, middle, and older age groups in Colombia and South Africa.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-09-28 00:13:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/730591"], "description"=>"<p>Notes:</p><p>*Male and Female populations combined.</p>", "links"=>[], "tags"=>["nutrition", "adults", "low-", "middle-income"], "article_id"=>400952, "categories"=>["Immunology", "Medicine", "Mathematics", "Biotechnology"], "users"=>["Daniel J. Corsi", "Jocelyn E. Finlay", "S. V. Subramanian"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0025120.t001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Studies_reporting_a_double_burden_of_nutrition_among_adults_in_low_to_middle_income_countries_/400952", "title"=>"Studies reporting a double burden of nutrition among adults in low- to middle-income countries.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-09-28 00:15:52"}

PMC Usage Stats | Further Information

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Relative Metric

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