1
Appendix
2
References (AMERICA)
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http://www.abeso.org.br/uploads/downloads/70/553a23f27da68.pdf.
BRITISH VIRGIN ISLANDS: British Virgin Islands STEPS risk factor survey report 2009.
http://www.who.int/chp/steps/2009_BVI_STEPS_Report-VI.pdf?ua=1.
CANADA: Statistics Canada, http://www5.statcan.gc.ca/cansim/a47.
CAYMAN ISLANDS: The Cayman Islands Non-Communicable Disease STEPS Risk Factor Survey 2012. http://www.who.int/chp/steps/Cayman_Islands_NCD_RF_survey_2012.pdf?ua=1. [Economics and Statistics Office – pers. communication] CHILE: Encuesta Nacional de Consumo Alimentario. Informe Final. Universidad de Chile. http://web.minsal.cl/sites/default/files/ENCA-INFORME_FINAL.pdf. [E. Atalah – pers. communication] COLOMBIA: Ramírez-Vélez, R., Correa-Bautista, J. E., Martínez-Torres, J., Méneses-Echavez, J. F., González-Ruiz, K., González-Jiménez, E., et al. (2016). LMS tables for waist circumference and waist–height ratio in Colombian adults: Analysis of nationwide data 2010. Eur J Clin Nutr, 70(10): 1189-1196. doi: 10.1038/ejcn.2016.46.
COSTA RICA: Pan American Health Organization The Central America Diabetes Initiative (CAMDI): Survey of Diabetes, Hypertension and Chronic Disease Risk Factors. Belize, San José, San Salvador, Guatemala City, Managua and Tegucigalpa. Washington, D.C.: PAHO, 2011. [A. Barcelo – pers. communication]
CUBA: Bonet, M, Varona, P. (2015) Evaluación antropométrica. En: III Encuesta nacional de factores de riesgo y actividades preventivas de enfermedades no trasmisibles. Cuba 2010-2011. La Habana. Editorial Ciencias Médicas, 110-137. [M. Bonet – pers. communication] DOMINICA: Dominica STEPS survey 2008. [data provided by the Central Statistical Office].
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DOMINICAN REPUBLIC: Centro de Estudios Sociales y Demográficos (CESDEM) y ICF International, 2014. Encuesta Demográfica y de Salud 2013 [DHS survey 2013]. Santo Domingo, República Dominicana: CESDEM y ICF International. [datasets
obtained via http://www.dhsprogram.com/Data/]
ECUADOR: Freire WB, Ramírez-Luzuriaga MJ, Belmont P, Mendieta MJ, Silva-Jaramillo MK, Romero N, Sáenz K, Piñeiros P, Gómez LF, Monge R. (2014). Tomo I: Encuesta Nacional de Salud y Nutrición de la población ecuatoriana de cero a 59 años. ENSANUT-ECU 2012. inisterio de Salud Pública/Instituto Nacional de Estadísticas y Censos. Quito-Ecuador. http://www.ecuadorencifras.gob.ec/documentos/web-inec/Estadisticas_Sociales/ENSANUT/MSP_ENSANUT-ECU_06-10-2014.pdf. EL SALVADOR: Pan American Health Organization The Central America Diabetes Initiative (CAMDI): Survey of Diabetes, Hypertension and Chronic Disease Risk Factors. Belize, San José, San Salvador, Guatemala City, Managua and Tegucigalpa. Washington, D.C.: PAHO, 2011. [A. Barcelo – pers. communication]
GRENADA: Grenada STEPS 2010-2011. (WHO STEPS Chronic Disease Risk Factor Surveillance). http://www.who.int/chp/steps/Grenada_2010-11_STEPS_Report.pdf?ua=1. [Ministry of Health/CARPHA.org – pers. communication]
GUATEMALA: MSPAS. Encuesta Nacional de Salud Materno Childil 2008 (ENSMI-2008/09). Ministerio de Salud Pública y Asistencia Social (MSPAS)/Instituto Nacional de Estadística (INE)/Centros de Control y Prevención de Enfermedades (CDC). Guatemala (2011). https://www.ine.gob.gt/sistema/uploads/2014/01/22/LYk4A1kGJAO7lvfS0Aq6tezcUa9tQh35.pdf GUYANA: Ministry of Health (MOH), Bureau of Statistics (BOS), and ICF Macro. 2010. Guyana Demographic and Health Survey
2009. Georgetown, Guyana: MOH, BOS, and ICF Macro. [datasets obtained via https://www.dhsprogram.com/Data/]
HAITI: Mabchour, A. E., Delisle, H., Vilgrain, C., Larco, P., Sodjinou, R. (2016). Abdominal obesity and other cardiometabolic risk biomarkers: influence of socioeconomic status and lifestyle on two African-origin population groups, Cotonou (Benin) and Port-au-Prince (Haiti). Pan Afr Med J., 24, 306-306. [A. El Mabchour – pers. communication]
HONDURAS: Iniciativa Centroamericana de Diabetes (CAMDI). Encuesta de diabetes, hipertensión y factores de riesgo de enfermedades crónicas. Tegucigalpa, Honduras. PAHO & Fundacion Hondureña de Diabetes & Secretaria de Salud Honduras, 2009. www.paho.org/hon/index.php [A. Barcelo – pers. communication]. JAMAICA: National Survey 2007-2008. [T. S. Ferguson – pers. communication] MEXICO: Encuesta Nacional de Salud y Nutrición 2016 (ENSANUT 2016). [T. Sh. Levy – pers. communication] NETHERLANDS ANTILLES: Curacao Health Survey 2013. [S. Verstraeten – pers. communication] NICARAGUA: Iniciativa Centroamericana de Diabetes (CAMDI). Encuesta de Diabetes, Hipertensión y Factores de Riesgo de Enfermedades Crónicas. Managua, Nicaragua 2009. http://www1.paho.org/hq/dmdocuments/2010/Encuesta_CAMDI_Nicaragua.pdf [A. Barcelo – pers. communication]. PANAMA: Mc Donald, A Bradshaw, RA, Fontes, F, Mendoza, EA, Motta, JA, Cumbrera, A, Cruz, C. (2015). Prevalence of obesity in panama: some risk factors and associated diseases. BMC Public Health, 15(1), 1. [A. Mc Donald – pers. communication] PARAGUAY: Paraguay STEPS 2011. (Primera Encuesta Nacional de Factores de Riesgo de Enfermedades No Transmisibles), https://www.who.int/ncds/surveillance/steps/Paraguay_2011_STEPS_Report.pdf. [data provided by the Ministry of Health]. PERU: Ramirez, JP. El retardo del creciemento en le Perú. Universidad Nacional Mayor de San Marcos. Primera Edición: Enero 2016.https://www.nestle.com.pe/sites/g/files/pydnoa276/files/nestle-en-la-sociedad/para-las-personas-y-familias/nutricion-salud-y-
bienestar/nutrigroup/documents/publicaciones%20cientificas%20-%20libro%20dr%20pajuelo.pdf. PUERTO RICO: Pérez, C. M., Guzmán, M., Ortiz, A. P., Estrella, M., Valle, Y., Pérez, N., et al. (2008). Prevalence of the metabolic syndrome in San Juan, Puerto Rico. Ethn Dis., 18(4): 434.
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ST. KITTS AND NEVIS: St. Kitts and Nevis STEPS 2008 (2008 STEPwise Approach to Chronic Disease Risk Factor Survey Report). www.who.int/chp/steps/2007_Report_StKitts.pdf?ua=1.
ST. LUCIA: Databook for St. Lucia STEPS survey 2012. [requested from the Ministry of Health] ST. VINCENT & GRENADINES: STEPS 2013-2014. (National health & Nutrition Survey. Non-Communicable Disease Risk Factor Surveillance). https://www.who.int/ncds/surveillance/steps/StVincent_STEPS_Report_2013-14.pdf?ua=1. [data provided by the Ministry of Health]
SURINAME: Suriname STEPS 2013 (Nationaal gezondheidsonderzoek in Suriname 2013). [data provided by the Ministry of Health] TRINIDAD AND TOBAGO: Trinidad and Tobago STEPS 2011 (Trinidad and Tobago PANAM STEPS CNCD Risk Factor Survey. Final Report). http://www.who.int/chp/steps/TrinidadAndTobago_2011_STEPS_Report.pdf?ua=1. URUGUAY: Uruguay STEPS 2013 (2nd encuesta nacional de factores de riesgo de enfermedades no transmisibles). [data provided by the Ministry of Health] USA: Fryar, C. D., Gu, Q., Ogden, C. L., Flegal, K. M. (2016). Anthropometric Reference Data for Children and Adults: United States, 2011-2014. Vital Health Stat 3, (39): 1-46. https://www.cdc.gov/nchs/data/series/sr_03/sr03_039.pdf. VENEZUELA: Bermúdez, V, Salazar, J, Rojas, J, Calvo, M, Rojas, M, Chávez-Castillo, M. et al. (2016). Diabetes and Impaired Fasting Glucose Prediction Using Anthropometric Indices in Adults from Maracaibo City, Venezuela. Journal of community health, 41(6): 1223-1233. [J. Salazar – pers. communication]
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Appendix Table 1. Average male height in 48 European countries/regions. Rows with updated/newly added data are highlighted. Representative measured data were not available for Wales.
Country/region n Age Date Height Source
Netherlands 211 20-21 2009 183.8* Schönbeck et al., 2013 Montenegro A 981 17-20 2013 182.9 Popović, 2017 Iceland (Reykjavik area) 146 18 2008-2009 181.8±6.5 Arngrímsson et al., 2012 (pers. communication) Estonia 644 18-19 2006-2009 181.5* Salm et al., 2013 Sweden (Göteborg area) B 2,408 17-20 2008-2009 181.4 Sjöberg et al., 2012 Serbia 1,072 20-29 2013 181.2 National Health Survey 2013 (I. Ivanović – pers. comm.) Bosnia & Herzegovina 3,192 17-20 2015-2016 181.2 Grasgruber et al., 2017 Denmark (conscripts) 31,056 ~18-26 2015 180.7 Statistical Yearbook 2017 Czech Republic (schools in Brno) 1,239 18-19 2015-2016 180.6±6.8 Unpublished data of the authors Croatia 358 18 2006-2008 180.5 Juresa et al., 2012 Germany 317 18-24 2008-2011 180.2* DEGS1 (communication with authors) Latvia 342 20-29 2014 180.2 Latvia Health Behavior Among the Adult Population 2014 Norway (conscripts) 18,297 ~18-19 2011 180.0 Statistisk årbok 2011 Hungary 4,737 18-25 2016 179.9 Kiss et al., 2017 (E. Kekes – pers. communication) Slovenia 7,033 18-21 2012 179.8 G. Starc – pers. communication Austria 19 2009-2011 179.6 (m) Gleiss et al., 2013 Kosovo 830 18-20 2016 179.5 Popović et al., 2017 Lithuania C 302 18 2012 179.4±7.9 Venckunas et al., 2016 (T. Venckunas – pers. comm.) Belgium 215 18-30 2013 179.4±6.9 Vuylsteke et al., 2015 (M.E. Vuylsteke – pers. comm.) Slovakia 823 18 2011 179.3 L. Ševčíková - pers. communication Finland (conscripts) 14,939 20 2011 178.6 Defence Command Finland Ireland 162 18-29 2007 178.5 Harrington et al., 2008 (communication with authors) Poland 518 18 2007-2009 178.5±6.6 Kułaga et al., 2010 (Z. Kułaga – pers. communication) Northern Ireland 144 20-25 2010-2012 178.5 Northern Ireland Health Survey (comm. with authors) Switzerland (conscripts) 32,972 18-20 2014 178.4 Staub et al., 2016 Scotland 1,231 20-29 2008-2011 178.0 Scottish Health Survey 2008-11 (comm. with authors) Luxembourg 82 20-29 2007-2008 177.7±7.1 Alkerwi et al., 2011 (A.A. Alkerwi – pers. communication) United Kingdom E 20-34 2008-2017 177.7 a weighted mean of England, Scotland and Northern Ireland England 1,652 25-34 2014-2017 177.6 Health Survey for England, 2014-2017 (weighed mean) Belarus 331 18-29 2016-2017 177.5 Belarus STEPS 2016-2017 (North) Macedonia F 596 18 2012 177.4 Gontarev et al., 2012 (S. Gontarev – pers. communication) Russia 1,077 20-25 2004-2005 177.3 RLMS survey Spain 821 20-29 2008-2010 177.1±8.1 Rodriguez-Artalejo et al., 2011 (E. Garcia – pers. comm.) France (metropolitan areas) D 248 20-29 2014-2016 177.1 INCA 3 (2014-2015) & ESTEBAN (2014-2016) Ukraine 346 20-29 2009 176.6 World Bank 2009 (P. Paul – pers. communication) Italy 20 1999-2004 176.5 Cacciari et al., 2006 Greece 1,531 18 2010-2012 176.1±7.2 Grammatikopoulou et al., 2014 (D. Poulimeneas–pers.comm.) Georgia 247 18-24 2010 175.8 Georgia STEPS 2010 Bulgaria 135 18 2011 175.3 Petrova et al., 2012 Romania 11,683 18 2012 174.9 Cojocaru et al., 2015 (M. Stanescu – pers. communication) Moldova 314 18-29 2013 174.8 Moldova STEPS 2013 Albania 820 20-25 2017-2018 174.7±6.9 Albania DHS 2017-2018 Cyprus 339 17.5-18.5 2006-2007 174.6 Photiou, 2007 Portugal 696 18 2008 173.9±8.0 Sardinha et al., 2010 (D. Santos – pers. communication)
Turkey G 277 20-29 2017 173.7±7.2 Turkey STEPS 2017 (S. Üner – pers. communication) Azerbaijan 212 18-29 2017 173.4±6.4 Azerbaijan STEPS 2017 Malta 618 18-34 2014-2016 173.0 Cuschieri et al., 2016 (S. Cuschieri – pers. communication) Armenia 213 18-34 2016 172.7±7.5 Armenia STEPS 2016
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Appendix Table 2. Average female height in 45 European countries/regions. Representative measured data were not available for Bosnia & Herzegovina, Cyprus, Norway, and Wales.
Country/region n Age Date Height Source
Netherlands 215 20-21 2009 170.5* Schönbeck et al., 2013 Montenegro A 1,107 17-20 2013 168.8 Popović, 2017 Lithuania C 255 18 2012 168.4±6.0 Venckunas et al., 2016 (T. Venckunas – pers. comm.) Estonia 927 18-19 2006-2009 168.2* Salm et al., 2013 Denmark H 315 18-24 2007-2008 168.1 (m) DANHES 2007-2008 Iceland (Reykjavik area) 129 18 2008-2009 167.9±5.6 Arngrímsson et al., 2012 (pers. communication) Sweden (Göteborg area) B 2,188 17-20 2008-2009 167.9±6.3 Sjöberg et al., 2012 Latvia 636 20-29 2014 167.3 Latvia Health Behavior Among the Adult Population 2014 Hungary 6,093 18-25 2016 166.9 Kiss et al., 2017 (E. Kekes – pers. communication) Serbia 1,017 20-29 2013 166.6 National Health Survey 2013 (I. Ivanović – pers. comm.) Belarus 344 18-29 2016-2017 166.6 Belarus STEPS 2016-2017 Slovenia 6,411 18-21 2012 166.5 G. Starc – pers. communication Czech Republic (schools in Brno) 1,213 18-19 2015-2016 166.5±6.2 Unpublished data of the authors Croatia 360 18 2006-2008 166.3 Juresa et al., 2012 Belgium 455 18-30 2013 166.2±6.8 Vuylsteke et al., 2015 (M.E. Vuylsteke – pers. comm.) Kosovo 793 18-20 2016 165.7 Popović et al., 2017 Romania 12,736 18 2012 165.4 Cojocaru et al., 2015 (M. Stanescu – pers. communication) Germany 312 18-24 2008-2011 165.4* DEGS1 (communication with authors) Austria 19 2009-2011 165.4 (m) Gleiss et al., 2013 Slovakia 824 18 2011 165.4±6.5 L. Ševčíková - pers. communication Finland 262 25-29 2012 165.4±6.4 FINRISK 2012 (H. Kennet – pers. communication) Switzerland I 202 18-29 2009 165.3±5.7 Volken et al., 2011 (T. Voken – pers. communication) Luxembourg 96 20-29 2007-2008 165.3±6.3 Alkerwi et al., 2011 (A.A. Alkerwi – pers. communication) Poland 643 18 2007-2009 165.1±6.1 Kułaga et al., 2010 (Z. Kułaga – pers. communication) Ukraine 358 20-29 2009 164.9±6.7 World Bank 2009 (P. Paul – pers. communication) (North) Macedonia F 552 18 2012 164.5±6.2 Gontarev et al., 2012 (S. Gontarev – pers. communication) Northern Ireland 224 20-25 2010-2012 164.3 Northern Ireland Health Survey (comm. with authors) Russia 1,343 20-25 2004-2005 164.2±6.5 RLMS survey Scotland 1,691 20-29 2008-2011 164.1 Scottish Health Survey 2008-11 (comm. with authors) Greece 1,641 18 2010-2012 164.1±6.2 Grammatikopoulou et al., 2014 (D. Poulimeneas–pers.comm.) United Kingdom E 20-34 2008-2017 164.0 a weighted mean of England, Scotland and Northern Ireland England 2,365 25-34 2014-2017 164.0 Health Survey for England, 2014 (weighed mean) France (metropolitan areas) D 283 20-29 2014-2016 163.8 INCA 3 (2014-2015) & ESTEBAN (2014-2016) Spain 940 20-29 2008-2010 163.7±6.3 Rodriguez-Artalejo et al., 2011 (E. Garcia – pers. comm.) Ireland 171 18-29 2007 163.5±6.7 Harrington et al., 2008 (communication with authors) Moldova 464 18-29 2013 163.4 Moldova STEPS 2013 Georgia 389 18-24 2010 163.4 Georgia STEPS 2010 Italy 20 1999-2004 162.6 Cacciari et al., 2006 Bulgaria 175 18 2011 162.4 Petrova et al., 2012 Azerbaijan 224 18-29 2017 161.3±6.3 Azerbaijan STEPS 2017 Albania 1,919 20-25 2017-2018 161.3±6.5 Albania DHS 2017-2018 Portugal 802 18 2008 161.1±6.8 Sardinha et al., 2010 (D. Santos – pers. communication) Turkey G 403 20-29 2017 160.6±6.6 Turkey STEPS 2017 (S. Üner – pers. communication) Armenia 414 18-34 2016 160.4±6.9 Armenia STEPS 2016 Malta 603 18-34 2014-2016 160.0 Cuschieri et al., 2016 (S. Cuschieri – pers. communication)
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Explanatory notes: (m) = median. * Pooled age categories. A The mean height measured in this survey from Montenegro is 183.4 cm in men and 169.4 cm in women, but due to large interregional differences, it was corrected for population size in the 13 examined regions. B Only men and women of Scandinavian origin. Other Swedish surveys do not separate ethnic Scandinavians from immigrants. C Data coming recently from Lithuania confirm a marked decrease in the height of young males. Tutkuviene (Anthropologischer Anzeiger, 2005, 63:29-44) reported a mean height of 181.3 cm in boys (n=195) and 167.5 cm in girls (n=278) aged 18 years measured in 2001. Similarly, a fitness survey conducted in 2002 found a mean height of 181.4 cm in boys (n=218) and 167.9 cm in girls (n=227) aged 18 years (T. Venckunas – pers. communication). However, Suchomlinov and Tutkuviene (Acta Medica Lituanica, 2013, 20:19-26) report only 179.7 cm in boys and 167.9 cm in girls aged 18 years from Vilnius measured in 2009-10. The retardation of growth that was documented in children aged 1-4 years in the early 1990s copied the era of the economic decline. Interestingly, the height of young females was not affected by these economic turmoils and may have continued to increase, as evidenced even by the study of Venckunas et al. (2016), which we use in the present study. D Anthropometric data from metropolitan (European) regions of France are conflicting and based on very limited samples. A small ENNS survey 2006-2007 reported an average height of 177.8 cm in men and 164.2 cm in women, but a subsequent ESTEBAN survey 2014-2016, performed by the same team, documented 178.0 cm in men (n=72) and only 163.2 cm in women (n=79) (B. Salanave – pers. communication). A concurrent INCA 3 survey 2014-2015 used larger samples but found a surprisingly short mean in men (176.7 cm, n=176) and a higher mean in women (164.0 cm, n=204) (A. Dufour – pers. communication). Apparently, the results were influenced by the small sample size and although the values are broadly similar, the discrepancies are too large to consider any of these surveys as sufficiently representative. Therefore, merging the participants of the ESTEBAN and the INCA 3 surveys seems to be the best option at this moment.
E A weighted mean taking into account the population size of England, Scotland and Northern Ireland. Measured data for Wales are not available.
F Only ethnic Macedonians, who make up ~64% of the population. G A much larger survey from Turkey performed in 2011 (Chronic Diseases and Risk Factor Survey in Turkey) reported an average height of 175.0 cm in men (n=1,454) and 161.3 cm in women (n=1,741) aged 20-29 years. Although these data may seem as far more representative at first glance, anthropometric measurements were not performed by the investigators but by family physicians, with an accuracy of 1 cm (E. Erkoyun – pers. communication), and are more similar to values of Turkish urban populations. These results are also in conflict with the Turkish DHS survey 2013 that reported a mean of 158.9 cm in women aged 20-29 years (n=2,497), and even with the Turkey Nutrition and Health Survey 2010 (Türkiye Beslenme ve Sağlık Araştırması 2010) in which men and women aged 19-30 years reached 173.2 cm (n=686) and 159.4 cm (n=893), respectively (after weighing urban and rural samples). When viewed from this perspective, the results of the STEPS survey 2017 are probably very close to the actual height in Turkey, and if anything, they may slightly overestimate it. H This study included even a sample of young men but it was relatively small (n=193), and their median height (181.8 cm) was substantially higher than the mean height of Danish recruits (180.7 cm), or a median reference value for 20 year olds (181.2 cm), based on a sample of 901 boys aged 20 years and calculated by Tinggaard et al. (Acta Paediatrica, 2014, 103: 214-224). I This Swiss study also included a sample of men but it was very small (179.5 cm, n=36).
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Appendix Table 3. Regional or less representative surveys including data on both sexes.
Country/territory Date Age Men Women
Source n Height n Height
Bosnia and Herzegovina (Federation) 2012 20-25 211 182.2 194 167.9 A. Pilav – pers. comm.
Finland 2012 25-29 203 178.3±5.6 262 165.4±6.4 FINRISK Study 1992-2012
Norway (Bergen) 2003-2006 19 125 181.0* 72 167.2* Júliússon et al., 2013
Note: * Results are normalized via the LMS method.
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HUNGARY: Kiss, I., Barna, I., Daiki, T., Dankovics, G., Kékes, E. (2017). Magyarország átfogó egészségvédelmi szûrôprogram”-jának (MÁESZ) 2016. évi és 2010-2016 közötti összefoglaló adatai. ICELAND: Arngrímsson, S. B., Richardsson, E. B., Jónsson, K., Ólafsdóttir, A. S. (2012). Holdafar, úthald, hreyfing og efnaskiptasnið meðal 18 ára íslenskra framhaldsskólanema [Body composition, aerobic fitness, physical activity and metabolic profile among 18 year old Icelandic high-school students]. Laeknabladid 98: 277-282. IRELAND: Harrington, J., Perry, I., Lutomski, J., Morgan, K., McGee, H., Shelley, E., et al. (2008). SLAN 2007: Survey of Lifestyle, Attitudes and Nutrition in Ireland. Dietary Habits of the Irish Population. Psychology Reports. Paper 6. http://epubs.rcsi.ie/psycholrep/6.
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KOSOVO: Popović S., Arifi, F., Bjelica, D. (2017). Standing Height and its Estimation Utilizing Foot Length Measurements in Kosovan Adults: National Survey. Int J Appl Exerc Physiol. 6(2): 1-7.
LATVIA: Latvia Health Behavior Among the Adult Population 2014. Centre for Disease Prevention and Control, https://www.spkc.gov.lv/lv/statistika-un-petijumi/petijumi-un-zinojumi/veselibu-ietekmejoso-paradumu-. LITHUANIA: Venckunas, T., Emeljanovas, A., Mieziene, B., Volbekiene, V. (2017). Secular trends in physical fitness and body size in Lithuanian children and adolescents between 1992 and 2012. J Epidemiol Community Health, 71(2): 181-187. LUXEMBOURG: Alkerwi, A. A., Donneau, A. F., Sauvageot, N., Lair, M. L., Scheen, A., Albert, A., Guillaume, M. (2011). Prevalence of the metabolic syndrome in Luxembourg according to the Joint Interim Statement definition estimated from the ORISCAV-LUX study. BMC Public Health, 11(1): 1. (NORTH) MACEDONIA: Gontarev, S., Zivkovic, V., Velickovska, L. A., Naumovski, M. (2014). First normative reference of standing long jump indicates gender difference in lower muscular strength of Macedonian school children. Health 6, 99-106.
MALTA: Cuschieri, S., Vassallo, J., Calleja, N., Camilleri, R., Borg, A., Bonnici, G, et al. (2016). Prevalence of Obesity in Malta. Obesity Science & Practice, 2(4): 466-470. (S. Cuschieri – pers. communication) MOLDOVA: Moldova STEPS 2013 (Prevalence of noncommunicable disease risk factors in the Republic of Moldova. STEPS 2013). https://www.who.int/ncds/surveillance/steps/Moldova_2013_STEPS_Report.pdf.
MONTENEGRO: Popovic, S. (2017). Local Geographical Differences in Adult Body Height in Montenegro. Monten J Sports Sci, 6(1): 81-87. NETHERLANDS: Schönbeck, Y., Talma, H., van Dommelen, P., Bakker, B., Buitendijk, S. E., HiraSing, R. A., van Buuren, S. (2012). The world's tallest nation has stopped growing taller: the height of Dutch children from 1955 to 2009. Pediatr Res, 73(3): 371-377.
NORTHERN IRELAND: Northern Ireland Health Survey, http://www.csu.nisra.gov.uk/surveyNIHS.asp5.htm.
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NORWAY (MALES): Statistisk årbok 2011 [Statistical Yearbook 2011]. Høyde, vekt og svømmeferdighet for vernepliktige, etter fylke. 2011 [Height, weight and swim capability of conscripts, by county. 2011]. pp. 126. https://www.ssb.no/a/histstat/aarbok/2011.pdf. NORWAY (FEMALES): Júlíusson, P. B., Roelants, M., Nordal, E., Furevik, L., Eide, G. E., Moster, D., et al. (2013). Growth references for 0–19 year-old Norwegian children for length/height, weight, body mass index and head circumference. Ann Hum Biol., 40(3): 220-227.
POLAND: Kułaga, Z., Litwin, M., Tkaczyk, M., Palczewska, I., Zajączkowska, M., Zwolińska, D., et al. (2011). Polish 2010 growth references for school-aged children and adolescents. Eur J Pediatr., 170(5): 599-609.
PORTUGAL: Sardinha, L. B., Santos, R., Vale, S., Silva, A. M., Ferreira, J. P., Raimundo, A. M., et al. (2011). Prevalence of overweight and obesity among Portuguese youth: A study in a representative sample of 10–18‐year‐old children and adolescents. Pediatr Obes., 6, e124-128.
ROMANIA: Cojocaru, V., Stanescu, M., Tudor, V., Ciolca, C., Stoicescu, M., Mujea, A. (2015) Raport privind evaluarea potentialului somatic, functional si motric al populatiei scolare din Romania. Editura Discobolul, Bucuresti, 392, 413 – 414. RUSSIA: RLMS (Russia Longitudinal Monitoring Survey), http://www.cpc.unc.edu/projects/rlms-hse.
SCOTLAND: Scottish Health Survey 2008-11, http://www.ucl.ac.uk/hssrg/studies/scottish.
SERBIA: National Health Survey 2013 (I. Ivanović, Institute of Public Health of Serbia "Dr Milan Jovanovic - Batut" – pers. communication). See also: Results of the National Health Survey of the Republic of Serbia 2013. http://www.batut.org.rs/download/publikacije/2013SerbiaHealthSurvey.pdf. SPAIN: Rodríguez-Artalejo, F., Graciani, A., Guallar-Castillón, P., León-Muñoz, L. M., Zuluaga, M. C., López-García, E., et al. (2011). Rationale and methods of the study on nutrition and cardiovascular risk in Spain (ENRICA). Rev Esp Cardiol (Engl Ed)., 64(10): 876-882. SWEDEN: Sjöberg, A., Barrenäs, M. L., Brann, E., Chaplin, J. E., Dahlgren, J., Mårild, S., et al. (2012). Body size and lifestyle in an urban population entering adulthood: the ‘Grow up Gothenburg’study. Acta Paediatr., 101(9): 964-972.
SWITZERLAND (MALES): Staub, K., Bender, N., Floris, J., Pfister, C., Rühli, F. J. (2016). From Undernutrition to Overnutrition: The Evolution of Overweight and Obesity among Young Men in Switzerland since the 19th Century. Obesity Facts, 9(4): 259-272.
SWITZERLAND (FEMALES): Volken, T., Schaffert, R., Rüesch, P. (2011). Need for weight management in Switzerland: findings from National Blood Pressure Week 2009. BMC Public Health, 11(1): 473.
TURKEY: Turkey STEPS 2017 (National Household Health Survey – Prevalence of Noncommunicable Disease Risk Factors in Turkey 2017 (STEPS). https://www.who.int/ncds/surveillance/steps/WHO-Turkey-Risk-Factors-A4_ENG.08_10_2018.pdf?ua=1
UKRAINE: World Bank. 2009. Ukraine Household Survey on Chronic Conditions, Lifestyle Factors and Health Care Utilization.
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Appendix Table 4. Average male height in 67 countries/territories of North Africa, Asia and Oceania.
Country/region n Age Date Height Source
France: French Polynesia 232 18-24 2010 178.6 French Polynesia STEPS 2010 Australia (total population) 975 18-24 2011-2012 177.8 Australian Health Survey New Zealand (total population) 19-30 2008-2009 177.6 New Zealand Adult Nutrition Survey 2008-09 Tonga 229 18-20 2008 176.7 Swinburn et al., 2011 (pers. communication) USA: American Samoa A 272 25-34 2004 175.9 American Samoa STEPS 2004 Lebanon 343 20-30 2009 175.5±6.6 Naja et al., 2011 (pers. communication) France: New Caledonia 56 18-24 2015 175.0 Baromètre Sante Adulte 2015 Israel (conscripts, Israeli-born only) 1,845 20-25 2010 174.5 IDF (R. Kayouf – pers. communication) South Korea 319 19-29 2013 174.4 KNHANES (S. Kweon – pers. communication) Libya 297 25-30 2009 174.3±7.4 Libya STEPS 2009 Algeria 527 20-29 2016-2017 174.3±7.8 Algeria STEPS 2016-2017 Tunisia B 456 18-20 2005 174.2±7.4 Aounallah-Skhiri et al. (2008) (B. Maire – pers. comm.) Kazakhstan 298 20-29 2014 174.0±7.8 Sharmanov et al. (unpublished) (Sh. Tazhibayev – pers. comm.) Fiji 289 18 2007-2008 174.1 Swinburn et al., 2011 (P. Kremer – pers. comm.) Samoa 186 24-30 2010 173.9±5.2 Hawley et al., 2014 (S. McGarvey – pers. comm.) United Arab Emirates (Dubai) 164 17-19 2009-2011 173.5±7.5 Al-Hazzaa et al., 2011 (pers. comm.) Palestine (incl. Gaza) 197 17-19 2013 173.5±7.0 PMS survey (2013) (A. Aburub – pers. comm.) Iran 3,316 20-29 2011 173.0 Bakshi et al., 2015 (A. Rafei – pers. comm.) China: Hong-Kong 212 20-29 2014-2015 173.0 Population Health Survey 2014-2015 Kuwait 506 18-29 2014 172.9 Kuwait STEPS 2014 Syria (refugees in Turkey) 863 18-29 2015 172.6 Turkey STEPS 2015 Bahrain 146 17-19 2009-2011 172.5±10.5 Al-Hazzaa et al., 2011 (pers. comm.) Taiwan 100 19-30 2005-2008 172.4±6.1 Nutrition and Health Survey 2005-08 (Min. of Health - pers.comm.) Egypt 833 20-24 2015 172.4 Egypt DHS 2015 Turkmenistan 287 18-24 2013-2014 172.3 Turkmenistan STEPS 2013-2014 (A. Boppyev – pers. comm..) China 3,853 19 2010 172.1 China: General Administration of Sport Iraq 732 18-39 2015 172.1 Iraq STEPS 2015 China: Macau 174 18 2014-2015 171.9±6.5 Lo et al., 2019 (W. W. S. Tam – pers. communication) Qatar 713 18-44 2012 171.7 Qatar STEPS 2012 Morocco 3,005 18-24 2011 171.7 K. El Rhazi - pers. communication Singapore 21-25 2010 171.5 Ministry of Health (pers. communication) Kyrgyzstan 235 25-34 2013 171.5±6.8 Kyrgyzstan STEPS 2013 Japan 1,200 20-29 2012-2014 171.5 National Health and Nutrition Survey (Ch.Shinsugi – pers.comm.) Uzbekistan 602 20-25 2002 171.1±5.6 Uzbekistan DHS 2002 Jordan 181 18-29 2009-2010 170.9±7.0 Y. S. Khader – pers. communication FSM/Fed. St. of Micronesia (Chuuk) 174 25-34 2006 169.9 FSM (Chuuk): STEPS 2006 USA: Guam 78 18-34 2011-2012 169.9 Y. C. Paulino – pers. communication Kiribati 163 25-34 2004-2006 169.8 Kiribati STEPS 2004-06 Oman (Muscat City) 224 17-19 2009-2011 169.6±7.8 Al-Hazzaa et al., 2011 (pers. comm.) Mongolia 677 25-34 2013 169.4 Mongolia STEPS 2013 USA: Northern Mariana Islands 98 18-34 2016 168.3 CNMI Hybrid Survey 2016 (H. Cash – pers. communication) Tajikistan 272 20-29 2016-2017 168.2±7.8 Tajikistan STEPS 2017 Saudi Arabia 1,062 20-29 2013 168.1 STEPS 2013 (Ministry of Health; M. Y. Saeedi – pers. comm.) Afghanistan C 18-29 2010-2011 167.9 Estimate (based on the Afghanistan MICS4 2010-2011) Vanuatu 698 25-34 2011 167.8 Vanuatu STEPS 2011 Pakistan D 20-24 2012-2013 167.8 Estimate (based on the Pakistan DHS 2012-13) Malaysia E 2,348 20-25 2011-2015 167.8 NHMS 2011 & NHMS 2015 Thailand 855 20-30 2009 167.6 Aekplakorn et al., 2014 (pers. communication) Sri Lanka 260 18-29 2015 167.5 Sri Lanka STEPS 2015 Solomon Islands 263 25-34 2006 167.4 Solomon Islands STEPS 2006 Brunei 473 20-25 2009-2011 166.9±6.0 Z. Bin Kamis – pers. communication Maldives 723 20-25 2016-2017 166.9±6.9 Maldives DHS 2016-2017 North Korea (refugees) 20-27 2000-2007 165.6±5.8 Pak et al., 2011 India 21,394 20-29 2005-2006 165.2±6.9 Mamidi et al., 2011 Nepal 1,513 20-25 2016 164.7±6.3 Nepal DHS 2016 Bhutan 499 18-39 2014 164.6 Bhutan STEPS 2014 Vietnam 22-26 2009-2010 164.4 Vietnam: General nutrition survey 2009-10 Myanmar/Burma 627 25-34 2014 164.2 Myanmar STEPS 2014 Marshall Islands 525 18-34 2018 164.0 RMI Hybrid Survey 2018 (H. Cash – pers. communication) Indonesia 1,275 20-25 2007-2008 163.9 Sohn, 2015 (pers. communication) Philippines 5,080 20-25 2013 163.9±6.6 8th National Nutrition Survey 2013 Laos (Vientiane City) 370 25-34 2008 163.6 Laos STEPS 2008 Yemen 374 20-25 2005-2006 163.1±10.4 World Bank, 2013 Papua New Guinea 334 25-34 2008-2009 163.1 PNG STEPS 2008-09 (P. van Maaren – pers. comm.) Bangladesh 1,172 25-34 2010 162.7 Bangladesh STEPS 2010 Cambodia 526 25-34 2010 162.4 Cambodia STEPS 2010 Timor-Leste 788 20-25 2016 160.0±7.3 Timor-Leste DHS 2016
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Appendix Table 5. Average female height in 67 countries/territories of North Africa, Asia and Oceania.
Country/region n Age Date Height Source
USA: American Samoa 330 25-34 2004 165.8 American Samoa STEPS 2004 France: French Polynesia 309 18-24 2010 165.5 French Polynesia STEPS 2010 Tonga 326 18-20 2008 165.2 Swinburn et al., 2011 (pers. communication) France: New Caledonia 90 18-24 2015 164.2 Baromètre Sante Adulte 2015 New Zealand (total population) 19-30 2008-2009 164.0 New Zealand Adult Nutrition Survey 2008-09 Australia (total population) 940 18-24 2011-2012 163.8 Australian Health Survey Israel (conscripts, Israeli-born only) 206 20-25 2010 162.6 IDF (R. Kayouf – pers. communication) Kazakhstan 537 20-29 2014 162.3±6.1 Sharmanov et al. (unpublished) (Sh. Tazhibayev – pers. comm.) Samoa 258 23-30 2010 162.2±5.3 Hawley et al., 2014 (S. McGarvey – pers. comm.) South Korea 398 19-29 2013 162.1 KNHANES (S. Kweon – pers. communication) Lebanon 408 20-30 2009 161.9±6.0 Naja et al., 2011 (pers. communication) Turkmenistan 438 18-24 2013-2014 161.8 Turkmenistan STEPS 2013-2014 (A. Boppyev – pers. comm..) Libya 330 25-30 2009 161.6±7.2 Libya STEPS 2017 Palestine (incl. Gaza) 182 17-19 2013 161.1 PMS survey (2013) (A. Aburub – pers. comm.) Algeria 667 20-29 2016-2017 161.1±7.2 Algeria STEPS 2016-2017 Tunisia B 594 18-20 2005 160.9±6.4 Aounallah-Skhiri et al. (2008) (pers. comm.) Singapore 21-25 2010 160.9 Ministry of Health (pers. communication) Fiji 348 18 2007-2008 160.8 Swinburn et al., 2011 (P. Kremer – pers. comm.) China 2,540 19 2010 160.1 China: General Administration of Sport Morocco 3,059 18-24 2011 159.8 K. El Rhazi - pers. communication Taiwan 100 19-30 2003-2008 159.8±5.7 Nutrition and Health Survey 2005-08 (Min. of Health - pers.comm.) China: Hong-Kong 251 20-29 2014-2015 159.7 Population Health Survey 2014-2015 Uzbekistan 1,041 20-25 2002 159.5 Uzbekistan DHS 2002 Kuwait 692 18-29 2014 159.4 Kuwait STEPS 2014 Bahrain 96 17-19 2009-2011 159.3±7.7 Al-Hazzaa et al., 2011 (pers. comm.) Iran 4,952 20-29 2011 159.2 Bakshi et al., 2015 (A. Rafei – pers. comm.) Egypt 1,157 20-24 2015 159.1 Egypt DHS 2015 Vanuatu 789 25-34 2011 159.0 Vanuatu STEPS 2011 FSM/Fed. St. of Micronesia (Chuuk) 343 25-34 2006 158.9 FSM (Chuuk): STEPS 2006 Kyrgyzstan 402 25-34 2013 158.8±6.6 Kyrgyzstan STEPS 2013 United Arab Emirates (Dubai) 187 17-19 2009-2011 158.7±6.8 Al-Hazzaa et al., 2011 (pers. comm.) Kiribati 225 25-34 2004-2006 158.6 Kiribati STEPS 2004-06 China: Macau 144 18 2014-2015 158.5±5.5 Lo et al., 2019 (W. W. S. Tam – pers. communication) Oman (Muscat City) 232 17-19 2009-2011 158.4±6.3 Al-Hazzaa et al., 2011 (pers. comm.) Qatar 994 18-44 2012 158.2 Qatar STEPS 2012 USA: Guam 56 18-34 2011-2012 158.2 Y. C. Paulino – pers. communication Mongolia 863 25-34 2013 158.1 Mongolia STEPS 2013 Saudi Arabia 1,395 20-29 2013 158.1 STEPS 2013 (Ministry of Health; M. Y. Saeedi – pers. comm.) Jordan 782 18-29 2009-2010 158.0±6.0 Y. S. Khader – pers. communication Japan 1,350 20-29 2012-2014 157.9 National Health and Nutrition Survey (Ch.Shinsugi – pers.comm.) Syria (refugees in Turkey) 1,000 18-29 2015 157.8 Turkey STEPS 2015 Iraq 1,132 18-39 2015 157.6 Iraq STEPS 2015 USA: Northern Mariana Islands 116 18-34 2016 157.4 CNMI Hybrid Survey 2016 (H. Cash – pers. communication) Tajikistan 355 20-29 2016-2017 156.9±6.2 Tajikistan STEPS 2017 Solomon Islands 424 25-34 2006 156.5 Solomon Islands STEPS 2006 Thailand 861 20-30 2009 156.0 Aekplakorn et al., 2014 (pers. communication) North Korea (refugees) 20-27 2000-2007 155.6±4.8 Pak et al., 2011 Malaysia E 2,185 20-25 2011-2015 155.6 NHMS 2011 & NHMS 2015 Afghanistan 3,821 18-29 2010-2011 155.2 Afghanistan MICS4 2010-2011 Papua New Guinea 370 25-34 2008-2009 155.0 PNG STEPS 2008-09 (P. van Maaren – pers. comm.) Sri Lanka 447 18-29 2015 155.0 Sri Lanka STEPS 2015 Brunei 607 20-25 2009-2011 154.6±5.1 Z. Bin Kamis – pers. communication Pakistan 1,292 20-24 2012-2013 154.4 Pakistan DHS 2012-13 Laos (Vientiane City) 698 25-34 2008 154.4 Laos STEPS 2008 Maldives 1,281 20-25 2016-2017 153.7±6.1 Maldives DHS 2016-2017 Myanmar/Burma 1,062 25-34 2014 153.6 Myanmar STEPS 2014 Vietnam 22-26 2009-2010 153.4 Vietnam: General nutrition survey 2009-10 Bhutan 906 18-39 2014 153.2 Bhutan STEPS 2014 Yemen 469 20-25 2005-2006 153.1±9.5 World Bank, 2013 Marshall Islands 632 18-34 2018 152.9 CMI Hybrid Survey 2018 (H. Cash – pers. communication) Philippines 5,040 20-25 2013 152.3±5.8 8th National Nutrition Survey 2013 Cambodia 883 25-34 2010 152.1 Cambodia STEPS 2010 Nepal 2,938 20-25 2016 152.1±5.5 Nepal DHS 2016 India 41,348 20-29 2005-2006 152.0±5.9 Mamidi et al., 2011 Indonesia 2,086 20-25 2007-2008 151.9 Sohn, 2015 (pers. communication) Timor-Leste 1,244 20-25 2016 151.7±5.7 Timor-Leste DHS 2016 Bangladesh 1,992 25-34 2010 150.9 Bangladesh STEPS 2010
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Explanatory notes: A A smaller, but somewhat more actual sample of young men from American Samoa aged 18-30 years (n=94), measured in 2002-03, reached 175.6 cm (S. McGarvey – pers. communication). B The true average height of this Tunisian sample was 173.4 cm in men and 160.6 cm in women but the authors recommended to use a mean corrected for the socio-economic characteristics of the sample. C The male average in Afghanistan was derived from female height in the Afghanistan MICS4 survey 2010-2011 (155.2 cm), using a rather arbitrary male/female ratio of 1.082 which was based on male/female ratios from nationwide surveys in Uzbekistan (1.073) and Iran (1.084), considering the proportion of Uzbeks and other genetically Turkic/Mongolian ethnicities (Turkmens and Hazaras) in the total population (~20%). Nevertheless, the estimated height (167.9 cm) is apparently plausible, being very similar to the mean height of Afghani men aged 25-30 years who were measured in 2012 in the border town of Jalalabad (168.2 cm, n=148) (K. M. I. Saeed - pers. communication). D The average height of 18-29-year olds in the recent Pakistan STEPS survey 2014 was 165.6 cm in men (n=958) and 154.3 cm in women (n=1,408) (M. Arif Nadeem Saqib - pers. communication). The survey was conducted in the most populous provinces of Punjab (165.3 cm in men, n=436; 154.4 cm in women, n=764) and Sindh (166.0 cm in men, n=522; 154.1 cm in women, n=644) comprising ~78% of the total population. However, the male mean is unexpectedly low and it would constitute an eccentric outlier in many graphic comparisons including nutrition.
According to Mamidi et al. (2011), the height of 20-29-year olds in the neighbouring Indian states of Jammu and Kashmir (168.0 cm in men, 154.7 cm in women), Punjab (168.4 cm in men, 154.7 cm in women), Rajasthan (167.2 cm in men, 154.5 cm in women) and Gujarat (166.2 cm in men, 152.7 cm in women) mostly agrees very well with the values of Pakistani women, but the men’s values are consistently higher than in Pakistani men, by as much as 3 cm. The male/female ratio in these four Indian states (1.082-1.089) is also strikingly higher than in Pakistan (1.073). Furthermore, the height of 25-30 year olds in the border town of Jalalabad in Afghanistan (168.2 cm in men, 154.1 cm in women), as well as the local male/female ratio (1.091), also resemble the values from India and not those from neighbouring Pakistan. In addition, there are numerous local health surveys from Pakistan which show a very similar picture, e.g. an urban survey by Khan et al. (Int J Cardiol., 2008, 124:259-262) from three provincial capitals (Karachi, Lahore, Quetta), in which men aged 20-29 years reached 169.0 cm (n=167) and women 154.0 cm (n=58) (data obtained from the authors).
Therefore, the results of the Pakistan STEPS survey 2014 seem somewhat suspect. Perhaps, the shorter height of Pakistani men is due to the unfinished growth of 18-19-year olds but this assumption cannot be confirmed because the average height of 20-29-year olds was not provided. Until this case is not clarified, an estimate of male height (167.8 cm) is preferred, based on the height of Pakistani women from the Pakistan DHS survey 2012-13 (154.4 cm), using the male/female ratio from the Indian nationwide survey 2005-2006 (1.087).
E There is a certain discrepancy between the Malaysian NHMS (National Health and Morbidity Survey) from 2011 (men: 168.4 cm, n=1,201; women: 156.0 cm, n=1,161) and from 2015 (men: 167.2 cm, n=1,147; women: 155.1 cm, n=1,024). Therefore, merging these surveys seems to be the best option.
15
References (NORTH AFRICA, ASIA AND OCEANIA)
AFGHANISTAN: Afghanistan MICS4 2010-2011. [datasets obtained via https://www.dhsprogram.com/Data/]
ALGERIA: Algeria STEPS 2016-2017. Unpublished. [datasets obtained from the WHO NCD Microdata Repository, https://extranet.who.int/ncdsmicrodata/index.php/catalog] AUSTRALIA (TOTAL POPULATION): Australian Health Survey 2011-12, http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4364.0.55.003Main+Features12011-2012?OpenDocument.
BANGLADESH: Bangladesh STEPS 2010 (Non-Communicable Disease Risk Factor Survey Bangladesh 2010), http://www.who.int/chp/steps/2010_STEPS_Report_Bangladesh.pdf?ua=1.
BHUTAN: Bhutan STEPS 2014 (National survey for noncommunicable disease risk factors and mental health using WHO STEPS
approach in Bhutan, 2014). http://www.who.int/chp/steps/Bhutan_2014_STEPS_Report.pdf?ua=1.
CAMBODIA: Cambodia STEPS 2010 (Prevalence of Non-Communicable Disease Risk Factors in Cambodia), http://www.who.int/chp/steps/2010_STEPS_Report_Cambodia.pdf?ua=1.
CHINA: China: General Administration of Sport, http://www.sport.gov.cn/n16/n1077/n297454/2052709.html.
CHINA: HONG-KONG: Population Health Survey 2014-2015, https://www.chp.gov.hk/en/static/51256.html (Department of Health - pers. communication)
CHINA: MACAU: Lo, K., Keung, V., Cheung, C., Tam, W., & Lee, A. (2019). Associations between Sleep Pattern and Quality and Cardiovascular Risk Factors among Macao School Students. Childhood Obesity. [published online ahead of print]
EGYPT: Egypt DHS 2015. Ministry of Health and Population [Egypt], El-Zanaty and Associates [Egypt], and ICF International. 2015. Egypt Health Issues Survey 2015. Cairo, Egypt and Rockville, Maryland, USA: Ministry of Health and Population and ICF International. https://dhsprogram.com/pubs/pdf/FR313/FR313.pdf.
FED. ST. OF MICRONESIA (CHUUK): FSM (Chuuk): STEPS 2006 (Federated States of Micronesia (Chuuk) NCD Risk Factors STEPS Report), http://www.who.int/chp/steps/2006_STEPS_Report_Micronesia.pdf?ua=1.
FIJI: Swinburn, B. A., Millar, L., Utter, J., Kremer, P., Moodie, M., Mavoa, H., et al. (2011). The Pacific Obesity Prevention in Communities project: project overview and methods. Obes Rev 12, Suppl 2: 3-11.
FRANCE: FRENCH POLYNESIA: French Polynesia STEPS 2010 (Enquête santé 2010 en Polynésie française), http://www.who.int/chp/steps/2010_STEPS_Report_FP.pdf?ua=1.
FRANCE: NEW CALEDONIA: Baromètre Sante Adulte 2015. Enquête sur la santé des Calédoniens de 18 à 60 ans. Résultats prelimaires. www.ass.nc/publication/doc_download/1151.
INDIA: Mamidi, R. S., Kulkarni B., Singh A. (2011). Secular trends in height in different states of India in relation to socioeconomic characteristics and dietary intake. Food Nutr Bull., 32: 23-34.
INDONESIA: Sohn K. (2015). The height premium in Indonesia. Econ Hum Biol. 16: 1-15.
IRAN: Bakhshi, E., Koohpayehzadeh, J., Seifi, B., Rafei, A., Biglarian, A., Asgari, F. (2015). Obesity and related factors in Iran: the STEPS Survey, 2011. Iran Red Crescent Med J., 17(6): e22479.
IRAQ: Iraq STEPS 2015 (Noncummunicable Diseases Risk Factors STEPS Survey Iraq 2015). http://www.who.int/chp/steps/Iraq_2015_STEPS_Report.pdf?ua=1.
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JAPAN: National Health and Nutrition Survey, http://www0.nih.go.jp/eiken/english/research/project_nhns.html.
KAZAKHSTAN: Sharmanov, T. Sh. Kompleksnaya profilaktika epidemii izbytochnoy massy tela i ozhireniya v Kazakhstane [Comprehensive prevention of the epidemic of overweight and obesity in Kazakhstan]. Unpublished. http://medscience.kz/2016/05/09/2012-2014_kaznmu_profil/ KIRIBATI: Kiribati STEPS 2004 (Kiribati NCD Risk Factors STEPS Report), http://www.who.int/chp/steps/kiribati_STEPS_report_2004-6.pdf?ua=1. KUWAIT: Kuwait STEPS 2014 (Survey of Risk Factors for Chronic Non Communicable Diseases State of Kuwait. http://www.who.int/chp/steps/Kuwait_2014_STEPS_Report.pdf?ua=1. KYRGYZSTAN: Kyrgyzstan STEPS 2013. Unpublished. [datasets obtained from the WHO NCD Microdata Repository, https://extranet.who.int/ncdsmicrodata/index.php/catalog] LAOS (VIENTIANE CITY): Laos STEPS 2008 (Report on STEPS Survey on Non Communicable Diseases Risk Factors in Vientiane Capital city, Lao PDR), http://www.who.int/chp/steps/2008_STEPS_Report_Laos.pdf?ua=1. LEBANON: Naja, F., Nasreddine L., Itani L., Chamieh M.C., Adra N., Sibai A.M., Hwalla N. (2011). Dietary patterns and their association with obesity and sociodemographic factors in a national sample of Lebanese adults. Public Health Nutr., 14, 1570-1578. LIBYA: Libya STEPS 2009. [datasets obtained from the WHO NCD Microdata Repository, https://extranet.who.int/ncdsmicrodata/index.php/catalog]
MALDIVES: Ministry of Health (MOH) [Maldives] and ICF. 2018. Maldives Demographic and Health Survey 2016-17. Malé,
Maldives, and Rockville, Maryland, USA: MOH and ICF. [datasets obtained via https://www.dhsprogram.com/Data/]
MALAYSIA: 1) Malaysia National Health and Morbidity Survey (NHMS) 2011, http://iku.moh.gov.my/index.php/research-eng/list-of-research-eng/iku-eng/nhms-eng/nhms-2011-eng (C. C. Kee - pers. communication). 2) Malaysia National Health and Morbidity Survey (NHMS) 2015, http://iku.moh.gov.my/index.php/research-eng/list-of-research-eng/iku-eng/nhms-eng/nhms-2015. (Sector for Biostatistics & Data Repository – pers. communication). MARSHALL ISLANDS: Ritz, S., Cash, H. Republic of the Marshall Islands Hybrid Survey 2018. Final report. MONGOLIA: Mongolia STEPS 2013 (Third national STEPS Survey on the Prevalence of Noncommunicable Disease and Injury Risk Factors-2013), http://www.who.int/chp/steps/Mongolia_2013_STEPS_Report.pdf?ua=1. MYANMAR/BURMA: Myanmar STEPS 2009 (Noncommunicable Disease Risk Factor Survey Myanmar 2009), http://www.who.int/chp/steps/2009_STEPS_Survey_Myanmar.pdf?ua=1. NEPAL: Ministry of Health, Nepal; New ERA; and ICF. 2017. Nepal Demographic and Health Survey 2016. Kathmandu, Nepal:
Ministry of Health, Nepal. [datasets obtained via https://www.dhsprogram.com/Data/]
NEW ZEALAND: New Zealand Adult Nutrition Survey 2008-09, https://www.health.govt.nz/system/files/documents/publications/a-focus-on-nutrition-ch8-v2.pdf. NORTH KOREA: Pak, S., Schwekendiek, D., Kim, H. K. (2011). Height and living standards in North Korea, 1930s–1980s. Econ Hist Rev., 64: 142-158. NORTHERN MARIANA ISLANDS: Dela Cruz, R., Cash, H. CNMI Non--‐Communicable Diseases & Risk Factor Hybrid Survey 2016 [final report].
17
PAKISTAN: Pakistan DHS 2012-13, http://dhsprogram.com/pubs/pdf/FR290/FR290.pdf. [datasets obtained via
https://www.dhsprogram.com/Data/]
PALESTINE: Palestinian micronutrient survey 2013.
PAPUA NEW GUINEA: Papua New GUinea STEPS 2007-2008 (Papua New Guinea NCD Risk Factors STEPS Report), http://www.who.int/chp/steps/PNG_2007-08_STEPS_Report.pdf?ua=1. PHILIPPINES: 8th National Nutrition Survey 2013. Anthropometric Survey Component. http://enutrition.fnri.dost.gov.ph/site/puf-preview.php?xx=201376 QATAR: Qatar STEPS 2012 (Chronic Disease Risk Factor Surveillance: Qatar STEPS Report 2012), http://www.qsa.gov.qa/eng/publication/STEPWISE-Report/STEPwise_Report.pdf.
SAMOA: Hawley, N. L., Minster, R. L., Weeks, D. E., Viali, S., Reupena, M. S., Sun, G., et al. (2014). Prevalence of adiposity and associated cardiometabolic risk factors in the samoan genome‐wide association study. Am J Hum Biol., 26, 491-501 (S. McGarvey – pers. communication). SOLOMON ISLANDS: Solomon Islands STEPS 2006 (Solomon Islands NCD Risk Factors STEPS Report), http://www.who.int/chp/steps/2006_Solomon_Islands_STEPS_Report.pdf?ua=1. SOUTH KOREA: Korea National Health and Nutrition Examination Survey (KNHANES), https://knhanes.cdc.go.kr/knhanes/eng/sub01/sub01_02.do. SRI LANKA: Sri Lanka STEPS 2015 (Non Communicable Disease Risk Factor Survey Sri Lanka 2015). http://www.who.int/chp/steps/STEPS-report-2015-Sri-Lanka.pdf?ua=1.
SYRIA: Turkey STEPS 2015 (Health Status Survey of Syrian Refugees in Turkey. Non-communicable Disease Risk Factors Surveillance among Syrian Refugees Living in Turkey), https://www.who.int/ncds/surveillance/steps/Turkey_2015_SyrianRefugees_STEPS_Report.pdf?ua=1. TAJIKISTAN: Tajikistan STEPS 2016-2017. Unpublished. [datasets obtained from the WHO NCD Microdata Repository, https://extranet.who.int/ncdsmicrodata/index.php/catalog] THAILAND: Aekplakorn, W., Inthawong, R., Kessomboon, P., Sangthong, R., Chariyalertsak, S., Putwatana, P., Taneepanichskul, S. (2014). Prevalence and trends of obesity and association with socioeconomic status in Thai adults: national health examination surveys, 1991–2009. J Obes., 2014:4102.. TIMOR-LESTE: General Directorate of Statistics (GDS). Ministry of Health and ICF. 2018. Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: GDS and ICF. [datasets obtained via
https://www.dhsprogram.com/Data/]
TONGA: Swinburn, B. A., Millar, L., Utter, J., Kremer, P., Moodie, M., Mavoa, H., et al. (2011). The Pacific Obesity Prevention in Communities project: project overview and methods. Obes Rev., 12, Suppl 2: 3-11. TUNISIA: Aounallah-Skhiri H, Romdhane HB, Traissac P, Eymard-Duvernay S, Delpeuch F, Achour N, Maire B (2008). Nutritional status of Tunisian adolescents: associated gender, environmental and socio-economic factors. Public Health Nutr 11(12):1306-1317. TURKMENISTAN: Turkmenistan STEPS 2013-2014. Unpublished.
USA: AMERICAN SAMOA: American Samoa STEPS 2004 (American Samoa NCD Risk Factors STEPS Report), http://www.who.int/chp/steps/Printed_STEPS_Report_American_Samoa.pdf?ua=1.
18
UZBEKISTAN: Analytical and Information Center, Ministry of Health of the Republic of Uzbekistan [Uzbekistan], State Department of Statistics, Ministry of Macroeconomics and Statistics [Uzbekistan], and ORC Macro. 2004. Uzbekistan Health Examination Survey 2002. Calverton, Maryland, USA: Analytical and Information Center, State Department of Statistics, and ORC Macro.,
http://www.dhsprogram.com/pubs/pdf/FR143/FR143.pdf. [datasets obtained via https://www.dhsprogram.com/Data/]
VANUATU: Vanuatu STEPS 2011 (Vanuatu NCD Risk Factors STEPS Report), http://www.who.int/chp/steps/vanuatu/en/. VIETNAM: Vietnam: General nutrition survey 2009-10 (Summary Report), http://www.unicef.org/vietnam/summary_report_gsn.pdf. YEMEN: World Bank. 2013. Yemen - Household Budget Survey Project. Washington DC; World Bank. http://documents.worldbank.org/curated/en/933951468181748580/Yemen-Household-Budget-Survey-Project.
19
Differences between the present study and the NCD Risk Factor Collaboration study
(eLIFE, 5:e13140, 2016, https://elifesciences.org/articles/13410)
The NCD Risk Factor Collaboration study (2016) collected data on the mean height in 200 countries or territories, and calculated estimates for adults born from 1896 to 1996 (people who had reached the age of 18 years between 1914-2014). In 77 cases (53.5%), the difference between male height in our study and estimated male height in the NCD Risk Factor Collaboration study (for the birth cohort 1996) was 0.0-1.0 cm. In other 40 cases (27.8%), it was 1.1-2 cm. In 16 cases (11.1%), it was 2.1-3.0 cm. The average difference in 144 populations was 1.2 cm. The most serious discrepancy was found in men from North Korea (6.4 cm), Egypt (5.7 cm), Bahrain (4.8 cm), Montenegro (4.6 cm), Saint Vincent and Grenadines (4.4 cm), and Algeria (4.2 cm). In all these cases, we believe that our data are based on more reliable and representative sources. The source for male height in North Korea (172.0 cm) is not listed in the dataset of the NCD Risk Factor Collaboration study and it was probably extrapolated from the height of South Korean men. Although the height of North Korean refugees, which we use in the current study (165.6 cm), may not accurately reflect the height of the general North Korean population, it is highly consistent in time, and corresponds with the economic and nutritional status of this country. The only known source that could resolve this situation, the North Korean STEPS survey 2005-2008, does not list any anthropometric data regarding height in the final report. Male height in Egypt (166.7 cm) is reportedly based on the DHS survey 2008 and the STEPS survey 2011. However, male height in the Egypt DHS survey 2008 (p. 195) is 170.3 cm for 20-24 year olds (n = 845) which is clearly very different from this value. The more actual DHS survey 2015 (p. 72) reported 172.4 cm for 20-24 year olds (n = 833). The STEPS survey 2011 (p. 41) lists only a rounded mean of “1.6 m” for 25-34 year olds. Either way, any value far below 170 cm is highly unlikely in this region because young men in neighbouring countries - Libya (174.3 cm), Sudan (173.2 cm), and Israel (174.5 cm) – are much taller. Male height in Bahrain (167.7 cm) is based on the National Nutrition Survey (1998-1999) which targeted people aged 19+ years. Our average (172.5 cm) is apparently more actual because it comes from a school survey performed between 2009-2011. Understandably, a secular trend of ~4 cm/decade is highly unlikely but the latter value accords very well with other data of wealthy Gulf countries such as neighbouring Qatar (171.7 cm), Kuwait (172.9 cm), and the Emirate of Dubai in the UAE (173.5 cm). The source for the height of Montenegrin males (178.3 cm) is not listed in the dataset, and the Montenegrin mean was probably estimated from the height of neighbouring countries. In any case, it is clearly far from the true height of young Montenegrin high schoolers measured in 2013 (182.9 cm). The dataset of the NCD Risk Factor Collaboration study again quotes no source for the mean height of men in Saint Vincent and Grenadines (172.8 cm). Our male average (177.2 cm) comes from the recent STEPS survey 2013-2014. Information coming from Algeria is more difficult to reconcile. The NCD Risk Factor Collaboration study reports a mean male height of 170.1 cm, quoting the STEPS survey 2003 (p. 69) in which men aged 25-34 years reached 170.0 cm (n = 508). Therefore, this mean relates to men born around 1973. The NCD Risk Factor Collaboration study further cites two other surveys, Transition and Health Impact in North Africa (2005)
20
and the ISOR (InSulino-resistance in ORan) study (2007-2009). Only the former is national but both targeted adults aged over 30 years, so again, the data would concern adults born in the early 1970s. A report from the ISOR survey (Houti et al., 2016) lists a mean height of 172.8 cm in 378 Algerian men from the city of Oran, aged 45.0±10.9 years. The value used in the present study (174.3 cm) comes from the STEPS survey 2016-2017 and relates to birth cohorts 1987-1997. Similar results were documented in several other recent surveys. Above all, a general population of young men aged 20-29 years from the ETHNA study (birth cohorts 1979-1989) was 173.1 cm tall (n = 509) (O. Kemmou – pers. communication). Urban boys aged 18 years from the city of Constantine, measured in 2008, were 174.1 cm tall (n = 379) (Bahchachi et al., 2015), and a small sample of Algerian boys aged 18 years reached 174.6 cm (n = 55) (ARAB-EAT-1 Project data, 2012; A.
Musaiger - pers. communication). Because young men in Morocco (171.7 cm), Tunisia (174.2 cm), and Libya (174.3 cm) stand very close to these values, the height of contemporary young Algerians must definitely be in the 173-174 cm range.
These examples show that most of the problematic cases result from missing or old data in the NCD Risk Factor Collaboration study. The methodology used in this study also isn’t always clear, as demonstrated by the large difference between the height in Egypt and the height measured in the DHS survey 2008. On the other hand, some data in this study seem to be more accurate, e.g. the estimated male height in Laos (160.5 cm), based on the general population from the STEPS survey 2013. Because results from this survey are not publicly avalaible and the local ministry of health did not respond to repeated requests, we had to use an urban population from Vientiane City (163.6 cm) which was measured during the STEPS survey 2008. The position of this sample on graphic comparisons indicates that it overestimates the true height of males in Laos.
21
Appendix Figure 1. Updated values of male height in Europe.
22
Appendix Figure 2. Male height in America.
23
Appendix Figure 3. Relationship between the GDP per capita (by purchasing power parity, current international USD; 1995-2013) in 128 populations and the GNI per capita (by purchasing power parity, current international USD; 1995-2013).
Braz Ecu
Guat
Jam
St Kitts
Surin
USA
P.Rico
Aut
Bos
Cro
Cyp
Cze
Fra
Ger
Hun
Irel Ita
Lux
Malta
Neth
Nor
Pol
Port
Svk
Slo
Spain
Switz
UK
Isr
Kuw
Oman
S.Arabia
Bahr
H Kong
Macau
Jap
S.Korea
Brunei
Malay
Singapore
NZL
r=0.99 (p<0.001) [n=119] r=0.99 (p<0.001) [n=128]
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
55000
60000
65000
70000
75000
80000
GN
I per
cap
ita
(cu
rren
t in
t. U
SD
)
GDP per capita (current int. USD)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
24
Appendix Figure 4. Relationship between the GDP per capita (by purchasing power parity, current international USD; 1995-2013) in 128 populations and health expenditure per capita (by purchasing power parity, constant 2011 international USD; 1995-2013).
Bah
Barb
Braz
Can
Cuba
St Kitts
Trin
USA
Aut
Belg
Cro
Cyp Cze
Den
Fin
Fra
Ger
Gre
Hun
Isl
Irel Ita
Lux
Malta
Neth
Nor
Port
Serb
Svk
Slo
Spain
Swe
Switz
UK
Isr
Kuw
Oman
S.Arabia
UAE
Bahr
Austr
NZL
Marsh.Isl.
Jap
Kaz
S.Korea
Brunei
Indon
Malay
Thai
Singapore
r = 0.83 (p<0.001) [n = 119] r = 0.81 (p<0.001) [n = 128]
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
5500
6000
6500
Hea
lth
exp
end
itu
re p
er c
apit
a (c
on
stan
t 20
11 in
t. U
SD
)
GDP per capita (current int. USD)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
25
Appendix Figure 5. Relationship between the Human Development Index (HDI) (2013) in 135 populations and child mortality under 5 years (per 1,000 live births; 1995-2013).
Arg
Cuba
Dom
Guat
Haiti
Trin
USA
Aut
Azerb
Belg
Bos Cro
Den Isl
Irel Neth
Nor
Port
Mold
Rus Switz
Mac
S.Arabia
Qatar
Palest
Solom.Isl.
FSM
Tonga
Afgh
Jap
Kaz
S.Korea
Camb
Indon
Mald
Timor
Egypt Mor
Yemen
Syria
Kyrg
Mong
Tajik Turkm
Uzb
Bangl
India
Laos
Myan
Nepal
Pak
Philip
Viet
Bhutan
Kiribati
Van
Papua
Bol
Dom.Rep. Guy
Hond Nic
Pan
r = -0.84 (p<0.001) [n = 119] r = -0.83 (p<0.001) [n= 135]
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
Ch
ild m
ort
alit
y u
nd
er 5
yea
rs (
per
1,0
00 li
ve b
irth
s)
Human Development Index
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
26
Appendix Figure 6. Relationship between health expenditure per capita (by purchasing power parity, constant 2011 international USD; 1995-2013) in 133 populations and child mortality under 5 years (per 1,000 live births; 1995-2013).
Arg
Bah
Braz
Can
Ecu
Guat
Haiti
Surin Trin
USA
Aut
Azerb
Belar
Bos Cro Cyp
Cze Den
Fin
Fra Ger Gre
Isl
Irel Lux
Neth Nor
Rus
Swe
Switz
Kuw Oman
S.Arabia
UAE Bahr
Qatar
NZL
Solom.Isl.
FSM
Tonga
Afgh
Jap
Kaz
S.Korea
Brunei
Indon
Singapore
Egypt
Syria
Kyrg
Mong
Kiribati
Turkm
Uzb
India
Laos
Yemen
Myanmar
Nepal
Pak
Philip
Bhutan
Van
Papua
Bol
Dom.Rep.
r = -0.59 (p<0.001) [n = 119] r = -0.57 (p<0.001) [n = 133]
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
Ch
ild m
ort
alit
y u
nd
er 5
yea
rs (
per
1,0
00 li
ve b
irth
s)
Health expenditure per capita (constant 2011 int. USD)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
27
Appendix Figure 7. Relationship between child mortality under 5 years (per 1,000 live births; 1995-2013) in 135 populations and total fertility rate (total births per woman; 1995-2013).
Arg
Bah
Barb
Braz
Can
Chile
Ecu
Gren
Guat
Haiti
Jam Mex
Pan Peru
Surin
Trin
USA
Ven
Alb
Arm
Azerb
Bul
Fra
Geo
Isl
Lat
Lux Mont
Mold Rom
Rus Mac
Tur
Ukr
Isr
Kuw
Oman S.Arabia
UAE
Bahr
Qatar
Palest
Fiji
Solom.Isl.
Marsh.Isl.
FSM
Papua Tonga
N.Korea
Kaz
S.Korea
Brunei
Camb
Indon Malay
Mald
Thai
Timor
Singapore
Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb Bangl
India
Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Bhutan
Kirib
Samoa
Van
Belize
Bol
Col C.Rica
Dom. Rep.
Guy
Hond
Nic
Par
r =0.70 (p<0.001) [n = 119] r =0.71 (p<0.001) [n = 135]
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
0 10 20 30 40 50 60 70 80 90 100 110 120
To
tal f
erti
lity
rate
(to
tal b
irth
s p
er w
om
an)
Child mortality under 5 years (per 1,000 live births)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
28
Appendix Figure 8. Relationship between male height in 136 populations and the mean supply of dairy proteins (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah Barb
Berm Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam Mex
Neth Ant
Pan
Peru
St Kitts
St.Vincent
Surin
Trin
USA
Ven
Alb
Arm
Aut
Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux
Malta
Mont Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai Timor
Alg
Egypt Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm Uzb
Bangl
India
Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Kirib Samoa Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic Par
Urug
r = 0.75 (p<0.001) [n = 136]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Dai
ry p
rote
ins
(g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
29
Appendix Figure 9. Relationship between male height in 136 populations and the mean supply of total protein (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan Peru
St Kitts
St.Vincent
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux Malta
Mont
Neth Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz S.Korea Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Egypt
Iraq
Israel
Jord
Kuw
Leb
Mor
Oman
S. Arabia
Tun
UAE
Yemen
Libya
Syria
Palestine
Afgh
China
Kyrg
Mong
Tajik
Uzb
Bangl
India
Laos
Myan Nepal Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Par
St.Lucia Urug
r = 0.71 (p<0.001) [n = 136]
40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
To
tal p
rote
in (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
30
Appendix Figure 10. Relationship between male height in 136 populations and the mean supply of total energy (kcal/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru St Kitts
St.Vincent
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel Ita
Lat
Lith
Lux
Malta Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji Fr.Polyn N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl India
Laos
Myan
Nepal Pak
Philip
S.Lanka
Viet
Kirib Samoa Van
Belize
Bol
Col C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Par St.Lucia
Urug
r = 0.70 (p<0.001) [n = 136]
1800
1900
2000
2100
2200
2300
2400
2500
2600
2700
2800
2900
3000
3100
3200
3300
3400
3500
3600
3700
3800
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
To
tal e
ner
gy
(kca
l/day
per
cap
ita)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
31
Appendix Figure 11. Relationship between male height in 136 populations and the mean supply of potato protein (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm Braz
Can
Chile
Cuba
Dom
Ecu
Gren Guat
Haiti Jam
Mex
Neth Ant
Peru
St.Vincent
Surin
Trin
USA
Ven
Alb
Arm Aut
Azerb
Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux
Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia UAE
Palest
Austr
Fiji
Fr.Polyn N.Caled
NZL
Solom.Isl.
N.Korea
Kaz
S.Korea Brunei
Camb Taiwan Indon
Malay
Mald
Thai Timor
Alg
Iran
Iraq
Leb
Mor Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik Turkm
Uzb
Bangl
India
Laos Myan
Nepal
Pak
Philip S.Lanka
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep. Nic
Par
St.Lucia
Urug
r = 0.58 (p<0.001) [n =136]
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
8
8.5
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Po
ota
to p
rote
in (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
32
Appendix Figure 12. Relationship between male height in 136 populations and the mean supply of pork protein (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba Dom
Ecu
Gren
Guat Haiti Jam
Mex
Neth Ant
Pan
Peru
St Kitts
St.Vincent
Surin Trin
USA
Ven
Alb
Arm
Aut
Belar
Belg
Bos
Bul Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux
Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr
Austr
Fiji
Fr.Polyn N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Jord
Leb
Yemen
China
Kyrg
Uzb
Bangl India
Laos
Myan
Nepal
Philip
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond Nic
Par
St.Lucia
Urug
r = 0.57 (p<0.001) [n =136]
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Po
rk p
rote
in (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
33
Appendix Figure 13. Relationship between male height in 136 populations and the mean supply of egg protein (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah Barb
Berm
Braz
Can
Chile Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts
St.Vincent Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl Irel
Ita Lat Lith
Lux
Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Uzb
Bangl India
Laos
Myan
Nepal
Pak
Philip
S.Lanka Viet
Kirib
Samoa Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Par
St.Lucia
Urug
r = 0.52 (p<0.001) [n =136]
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Eg
g p
rote
in (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
34
Appendix Figure 14. Relationship between male height in 136 populations and the mean supply of proteins from dairy and pork (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts St.Vincent
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro Cyp
Cze
Den Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl Irel
Ita Lat
Lith
Lux
Malta
Mont Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai Timor Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong Turkm
Uzb
Bangl
India
Laos
Myan Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy Hond
Nic
Par
St.Lucia
Urug
r = 0.78 (p<0.001) [n =136]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Pro
tein
s fr
om
dai
ry a
nd
po
rk (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
35
Appendix Figure 15. Relationship between male height in 136 populations and the mean supply of proteins from dairy, pork and eggs (g/day per capita, FAOSTAT 1995-2013).
Arg Bah
Barb
Berm Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro Cyp
Cze
Den
Est
Fin Fra
Geo
Ger
Gre
Hun
Isl Irel
Ita Lat
Lith
Lux
Malta
Mont
Neth
Nor Pol
Port
Mold
Rom
Rus Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea Brunei
Camb
Taiwan
Indon
Malay Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm Uzb
Bangl
India
Laos
Myan Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv Guy
Hond
Nic
Par
St.Lucia
St.Vincent
Urug
r = 0.79 (p<0.001) [n =136]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Pro
tein
s fr
om
dai
ry,
po
rk, a
nd
eg
gs
(g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
36
Appendix Figure 16. Relationship between male height in 136 populations and the mean supply of rice protein (g/day per capita, FAOSTAT 1995-2013).
Bah
Braz
Chile
Cuba
Ecu
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts
Surin
Trin Ven
Geo
Isl
Mont
Neth
Port
Ukr
Kuw
Oman
S.Arabia
UAE Fiji
Fr.Polyn N.Caled
Solom.Isl.
H Kong Macau
N.Korea
Jap
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Iran Iraq
Jord
Leb
Mor Tun
Yemen Libya Syria Afgh
China
Kyrg
Mong
Tajik
Turkm Uzb
Bangl
India
Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Van
Belize
Bol Col
C.Rica Dom.Rep.
El Salv
Guy
Hond
Nic
Par
r = -0.67 (p<0.001) [n =136]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Ric
e p
rote
in (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
37
Appendix Figure 17. Relationship between male height in 136 populations and the mean supply of total legume protein (g/day per capita, FAOSTAT 1995-2013).
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux
Malta
Mont
Neth
Pol
Port
Mold
Rom Rus
Serb
Slo
Spain
Swe Switz
Mac
Tur
Ukr
UK
Isr Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
NZL
Solom.Isl.
H Kong Macau
N.Korea
Jap
S.Korea
Brunei Camb
Taiwan
Indon Malay
Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Afgh
China
Kyrg
Mong Tajik
Uzb
Bangl
India
Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Par
St.Lucia
Urug
r = -0.31 (p<0.001) [n =136]
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
To
tal l
egu
me
pro
tein
(g
/day
per
cap
ita)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
38
Appendix Figure 18. Relationship between male height in 136 populations and the mean supply of maize protein (g/day per capita, FAOSTAT 1995-2013).
Arg
Barb
Braz
Can
Chile Cuba
Ecu
Guatemala
Haiti
Mexico
Pan
Peru
Trin
USA
Ven
Aut
Azerb
Bosnia
Bul
Cro
Cze
Den Est Fra
Geo
Ger
Gre
Isl
Irel
Ita
Mont
Neth
Port
Mold
Rom
Serb
Slo
Swe
Mac
Tur
Ukr
UK
Isr Oman
S.Arabia
Solom.Isl.
N.Korea
Brunei
Camb
Indon
Mald
Thai
Timor
Egypt
Mor
Yemen
China
Kyrg
Tajik
Bangl
India
Laos
Myan
Nepal
Pak
Philip S.Lanka
Viet
Belize
Bol Col
C.Rica Dom.Rep.
El Salvador
Guy
Hond
Nicaragua
Paraguay
Urug
r = -0.29 (p=0.001) [n =136]
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Mai
ze p
rote
in (
g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
39
Appendix Figure 19. Relationship between male height in 136 populations and the mean proportion of protein energy in the diet (% total energy intake) (FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant Pan
Peru
St Kitts
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel Ita
Lat
Lith
Lux
Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain Swe
Switz
Mac
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl
India
Laos
Myan
Nepal
Pak
Philip S.Lanka
Viet Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond Nic
Par
St.Lucia
Urug
r = 0.49 (p<0.001) [n =136]
8.5
9
9.5
10
10.5
11
11.5
12
12.5
13
13.5
14
14.5
15
15.5
16
16.5
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Pro
po
rtio
n o
f p
rote
in e
ner
gy
in t
he
die
t (%
)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
40
Appendix Figure 20. Relationship between male height in 136 populations and the mean supply of poultry proteins (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts
St.Vincent
Surin
Trin
USA
Ven
Alb Arm
Aut
Azerb
Belar
Belg
Bos
Bul
Cro
Cyp
Cze
Den
Est Fin
Fra
Geo
Ger Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom Rus
Serb
Svk
Slo
Spain
Swe Switz
Mac Tur Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald Thai
Timor Alg
Egypt
Iran
Iraq
Jord
Leb
Mor Tun
Yemen
Libya
Syria
Afgh
China
Kyrg Mong
Uzb
Bangl
India Laos
Myan
Pak
Philip
S.Lanka Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Par
St.Lucia
Urug
r = 0.30 (p<0.001) [n =136]
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Po
ult
ry p
rote
ins
(g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
41
Appendix Figure 21. Relationship between male height in 136 populations and the mean supply of beef proteins (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Dom
Ecu
Gren Guat
Haiti
Jam
Mex
Pan
Peru
Trin
USA
Ven Alb
Arm
Aut
Azerb
Belar
Belg
Bos Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux
Malta
Mont
Neth Nor
Pol
Port
Mold
Rus
Serb Svk
Slo
Spain
Swe
Switz
Mac Ukr
UK
Isr
Kuw Oman
Palest
Austr
Fr.Polyn
N.Caled
NZL
H Kong
China
N.Korea
Jap
Kaz
Brunei
Camb
Indon
Mald
Timor
Egypt
Leb
Mor Tun
Yemen Syria
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl India
Laos
Myan
Nepal Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van Belize
Bol
Col
C.Rica
Guy
Hond
Nic
Par
Urug
r = 0.39 (p<0.001) [n =136]
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Bee
f p
rote
ins
(g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
42
Appendix Figure 22. Relationship between male height in 136 populations and the mean supply of fish & seafood proteins (g/day per capita, FAOSTAT 1995-2013).
Bah
Barb Berm
Braz
Cuba
Dom
Ecu
Gren
Guat Haiti
Jam
Mexico
Pan
Peru
St Kitts
Surin Trin Aut
Belar
Belg
Bosnia
Cro Cze
Den
Est
Fin
Fra
Geo
Ger
Hun
Isl
Irel Lat
Lith
Malta
Mont
Neth
Nor
Pol
Port
Serb Svk Slo
Spain
Swe
Switz
Mac
Ukr Kuw
Oman
S.Arabia
UAE
Fiji
Fr.Polyn
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
S.Korea
Brunei
Camb Taiwan
Indon
Malay
Mald
Thai
Timor
Egypt
Leb Tun Yemen
Libya
China
Kyrg Mong
Bangl
India
Laos
Myan
Nepal
Philip
S.Lanka Viet
Kirib
Samoa
Van
Belize
Bol Col
Guy
St.Lucia
r = 0.04 (p=0.65) [n =136]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Fis
h &
Sea
foo
d p
rote
ins
(g/d
ay p
er c
apit
a)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
43
Appendix Figure 23. Relationship between male height in 136 populations and the mean supply of wheat protein (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren Guatemala
Haiti
Jam
Mexico
Neth Ant
Pan
Peru
St Kitts St. Vincent
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg Bosnia
Bul
Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl Irel
Ita
Lat
Lith
Lux
Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom Rus
Serb Svk
Slo
Spain
Swe Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong Macau
N.Korea
Jap
Kaz
S.Korea Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl
India
Laos Myan
Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salvador
Guy
Hond
Nicaragua
Paraguay
St.Lucia
Urug
r = 0.42 (p<0.001) [n =136]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Wh
eat
pro
tein
(g
/day
per
cap
ita)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
44
Appendix Figure 24. Relationship between male height in 136 populations and the mean supply of plant proteins (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu Gren
Guat
Haiti
Jam
Mexico
Neth Ant
Pan
Peru
St Kitts
St.Vinc
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bosnia
Bul
Cro
Cyp
Cze Den
Est Fin
Fra
Geo
Ger
Gre
Hun Isl
Irel
Ita Lith
Lux
Malta
Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn N.Caled
NZL
Solom.Isl.
H Kong Macau
N.Korea
Jap
Kaz
S.Korea
Brunei Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl
India Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van
Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Paraguay
St.Lucia
Urug
r = 0.03 (p=0.75) [n =136]
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60
62
64
66
68
70
72
74
76
78
80
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
Pla
nt
pro
tein
s (g
/day
per
cap
ita)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
45
Appendix Figure 25. Relationship between male height in 136 populations and the mean supply of animal proteins (g/day per capita, FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Dom
Ecu
Gren
Guat
Haiti
Jam
Mexico
Neth Ant
Pan
Peru
St Kitts
St.Vincent
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Belar
Belg
Bosnia
Bul Cro
Cyp
Cze
Den
Est
Fin
Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita
Lat
Lith
Lux
Malta Mont
Neth
Nor
Pol
Port
Mold
Rom Rus
Serb Svk
Slo
Spain
Swe
Switz
Mac Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl
India Laos
Myan
Nepal
Pak Philip
S.Lanka
Viet
Kirib
Samoa
Van Belize
Bol
Col
C.Rica
Dom.Rep.
El Salvador
Guy
Hond
Nicaragua
Paraguay
St.Lucia
Urug
r = 0.68 (p<0.001) [n =136]
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
An
imal
pro
tein
s (g
/day
per
cap
ita)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
46
Appendix Figure 26. Relationship between male height in 136 populations and the proportion of animal proteins in the diet (% total protein supply) (FAOSTAT 1995-2013).
Arg
Bah
Barb
Berm
Braz
Can
Chile
Cuba
Ecu
Gren
Guat
Haiti
Jam
Mexico
Neth Ant
Pan
Peru
St Kitts
Surin
Trin
USA
Ven Alb
Arm
Aut
Azerb
Belar
Belg
Bosnia
Bul
Cro
Cyp
Cze
Den
Est
Fin Fra
Geo
Ger
Gre Hun
Isl
Irel
Ita
Lat Lith
Lux
Malta Mont
Neth
Nor
Pol
Port
Mold
Rom
Rus
Serb
Svk
Slo
Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor
Alg
Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Libya
Syria
Afgh
China
Kyrg
Mong
Tajik
Turkm
Uzb
Bangl
India Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa
Van Belize
Bol
Col
C.Rica
Dom.Rep.
El Salv
Guy
Hond
Nic
Parag
St.Lucia
Urug
r = 0.59 (p<0.001) [n =136]
10
15
20
25
30
35
40
45
50
55
60
65
70
75
158 160 162 164 166 168 170 172 174 176 178 180 182 184 186
% A
nim
al p
rote
ins
(as
% t
ota
l pro
tein
su
pp
ly)
Average male height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
47
Appendix Table 6. Relationship between male height and food consumption (supply), within tertiles of the GDP per capita (126 populations with available data).
1st tertile (≥ 19 460 USD per capita)
2nd tertile (7184-17 078 USD per capita)
3rd tertile (≤ 7147 USD per capita)
TOTAL SAMPLE
Populations (n) 40 (mean: 176.1 cm) 46 (mean: 174.1 cm) 40 (mean: 169.0 cm) 136 (mean: 173.1 cm)
Mean r p Mean r p Mean r p Mean r p
PROTEIN SUPPLY (g/day per capita)
Dairy total 17.2 0.78 < 0.001 11.4 0.59 < 0.001 7.0 0.59 < 0.001 11.7 0.75 < 0.001 Cheese 7.7 0.74 < 0.001 2.9 0.57 < 0.001 0.7 0.44 0.005 3.7 0.67 < 0.001 Milk 6.6 0.34 0.033 7.1 0.27 0.073 5.5 0.63 < 0.001 6.3 0.46 < 0.001 Eggs 3.3 0.23 0.152 2.4 0.23 0.117 1.3 0.42 0.007 2.3 0.52 < 0.001 Meat total 28.4 0.21 0.198 17.6 0.32 0.033 10.1 0.40 0.010 18.6 0.58 < 0.001 Beef 7.2 0.35 0.027 5.2 -0.04 0.784 3.2 0.40 0.011 5.1 0.39 < 0.001 Mutton & Goat meat 1.8 -0.08 0.622 0.8 0.04 0.771 1.4 0.21 0.187 1.3 0.09 0.297 Pork 7.7 0.52 < 0.001 4.0 0.57 < 0.001 1.9 0.12 0.452 4.5 0.57 < 0.001 Poultry 10.6 -0.49 0.001 7.3 0.08 0.616 3.3 0.25 0.125 7.1 0.30 < 0.001 Fish & Seafood 8.4 -0.07 0.662 5.2 -0.23 0.124 4.4 -0.13 0.437 5.8 0.04 0.649 Pelagic marine fish 2.5 0.11 0.488 2.7 -0.22 0.143 2.0 0.09 0.598 2.4 0.02 0.816 Freshwater fish 0.9 0.19 0.242 0.5 -0.13 0.393 0.9 -0.46 0.003 0.7 -0.17 0.046 Pelagic & Freshwater fish 3.4 0.16 0.322 3.2 -0.23 0.118 2.9 -0.13 0.416 3.1 -0.02 0.776 Offals 2.1 0.03 0.841 1.5 0.34 0.021 1.1 0.24 0.130 1.5 0.31 < 0.001 ANIMAL PROTEINS 59.8 0.61 < 0.001 38.3 0.33 0.025 23.9 0.59 < 0.001 40.2 0.68 < 0.001 Cereals total 25.6 -0.11 0.512 29.7 0.05 0.740 31.8 0.19 0.235 29.0 -0.10 0.258 Wheat 19.6 0.36 0.024 21.0 0.33 0.028 16.6 0.59 < 0.001 19.2 0.42 < 0.001 Rice 3.4 -0.71 < 0.001 4.1 -0.70 < 0.001 9.4 -0.64 < 0.001 5.6 -0.67 < 0.001 Maize 1.2 -0.26 0.103 3.0 -0.31 0.035 4.5 0.07 0.679 2.9 -0.29 < 0.001 Fruits 1.5 -0.22 0.177 1.4 -0.17 0.273 0.9 0.11 0.487 1.2 0.18 0.037 Oilcrops 1.8 -0.32 0.045 1.1 -0.28 0.061 1.7 -0.14 0.400 1.6 -0.19 0.027 Legumes (excl. Soybeans) 2.2 -0.28 0.078 3.3 -0.24 0.102 3.1 -0.21 0.198 2.9 -0.26 0.002 Legumes total 2.8 -0.46 0.003 3.6 -0.28 0.057 3.6 -0.24 0.131 3.4 -0.31 < 0.001 Starchy roots 2.1 0.72 < 0.001 2.5 0.63 < 0.001 2.4 0.25 0.117 2.3 0.34 < 0.001 Potatoes 2.1 0.73 < 0.001 2.0 0.58 < 0.001 1.3 0.46 0.003 1.8 0.58 < 0.001 Treenuts 0.7 0.20 0.215 0.4 0.03 0.861 0.2 0.26 0.107 0.4 0.29 < 0.001 Vegetables 3.9 -0.27 0.097 2.8 0.28 0.062 2.5 0.41 0.008 3.1 0.30 < 0.001 PLANT PROTEINS 40.6 -0.12 0.447 43.0 0.11 0.463 43.6 0.33 0.039 42.5 0.03 0.752 TOTAL PROTEIN 100.3 0.49 0.001 81.2 0.40 0.006 67.5 0.70 < 0.001 82.7 0.71 < 0.001 ENERGY SUPPLY (kcal/day) TOTAL ENERGY 3218.9 0.48 0.002 2884.0 0.37 0.010 2511.1 0.63 < 0.001 2865.3 0.70 < 0.001 % PROTEIN ENERGY 12.8 0.20 0.210 11.5 0.24 0.109 11.0 0.48 0.002 11.7 0.49 < 0.001 COMBINATIONS OR RATIOS OF PROTEIN SUPPLY
Rice & Legumes total 6.2 -0.68 < 0.001 7.7 -0.66 < 0.001 13.0 -0.66 < 0.001 9.0 -0.68 < 0.001 Rice, Maize & Legumes total 7.3 -0.71 < 0.001 10.7 -0.67 < 0.001 17.5 -0.58 < 0.001 11.9 -0.71 < 0.001 Rice & Maize 4.6 -0.73 < 0.001 7.1 -0.72 < 0.001 13.9 -0.59 < 0.001 8.5 -0.73 < 0.001 Dairy, Pork, Fish & Seafood 33.3 0.72 < 0.001 20.6 0.34 0.021 13.2 0.52 < 0.001 22.1 0.68 < 0.001 Dairy & Beef 24.3 0.76 < 0.001 16.6 0.37 0.011 10.1 0.60 < 0.001 16.8 0.71 < 0.001 Dairy & Potatoes 19.2 0.80 < 0.001 13.4 0.62 < 0.001 8.3 0.62 < 0.001 13.5 0.76 < 0.001 Dairy, Pork, Eggs & Beef 35.4 0.80 < 0.001 23.1 0.52 < 0.001 13.4 0.66 < 0.001 23.6 0.77 < 0.001 Dairy & Eggs 20.5 0.78 < 0.001 13.9 0.58 < 0.001 8.3 0.63 < 0.001 14.0 0.77 < 0.001 Dairy, Pork, Eggs, Beef & Potat. 37.4 0.82 < 0.001 25.1 0.55 < 0.001 14.7 0.67 < 0.001 25.4 0.78 < 0.001 Dairy & Pork 24.9 0.82 < 0.001 15.5 0.67 < 0.001 8.9 0.64 < 0.001 16.2 0.78 < 0.001 Dairy, Pork & Eggs 28.2 0.81 < 0.001 17.9 0.65 < 0.001 10.2 0.66 < 0.001 18.5 0.79 < 0.001 Dairy, Pork, Eggs & Potatoes 30.2 0.83 < 0.001 19.9 0.66 < 0.001 11.5 0.68 < 0.001 20.3 0.79 < 0.001 ... / Rice & Maize 17.1 0.73 < 0.001 14.1 0.54 < 0.001 3.0 0.43 0.006 11.08 0.57 < 0.001 Dairy & Pork / Wheat 1.32 0.48 0.002 1.04 -0.18 0.228 1.15 -0.38 0.015 1.15 -0.11 0.206 Dairy & Pork / Cereals 1.01 0.76 < 0.001 0.57 0.56 < 0.001 0.29 0.58 < 0.001 0.62 0.73 < 0.001 % ANIMAL PROTEINS 59.3 0.49 0.001 46.9 0.16 0.295 34.2 0.43 0.005 46.5 0.59 < 0.001
Positive relationships Negative relationships
r≥0.700 p < 0.001 p < 0.01 p < 0.05 p < 0.05 p < 0.01 p < 0.001 r≥0.700
48
Appendix Table 7. Residuals of the multiple regression model (3c) in Table 6. Country Observed
male height Predicted
male height Residual
(cm) Country Observed
male height Predicted
male height Residual
(cm) Bosnia and Herzegovina 181.2 173.5 7.7 United Kingdom 177.7 177.9 -0.2 Haiti 170.4 164.8 5.6 Oman 169.6 169.9 -0.3 Serbia 181.2 176.1 5.1 Russia 177.3 177.6 -0.3 Egypt 172.4 167.7 4.7 Ireland 178.5 178.8 -0.3 Saint Vincent & Grenad. 177.2 172.6 4.6 Saint Lucia 174.7 175.1 -0.4 Netherlands 183.8 179.6 4.2 Bolivia 166.6 167.0 -0.4 Iceland 181.8 177.8 4.0 Nepal 164.7 165.1 -0.4 Jamaica 176.1 172.3 3.8 China 172.1 172.5 -0.4 Laos 163.6 160.2 3.4 Austria 179.6 180.2 -0.6 Samoa 173.9 170.5 3.4 Tunisia 174.2 174.9 -0.7 Grenada 177.0 173.7 3.3 Switzerland 178.4 179.1 -0.7 Fiji 174.1 170.9 3.2 Guyana 168.9 169.7 -0.8 Croatia 180.5 177.4 3.1 Bulgaria 175.3 176.1 -0.8 El Salvador 171.2 168.1 3.1 Pakistan 167.8 168.6 -0.8 Estonia 181.5 178.7 2.8 Ukraine 176.6 177.4 -0.8 Venezuela 172.4 169.7 2.7 Tajikistan 168.2 169.1 -0.9 Dominican Republic 172.1 169.5 2.6 Bangladesh 162.7 163.7 -1.0 (North) Macedonia 177.4 174.9 2.5 Saudi Arabia 168.1 169.1 -1.0 Sweden 181.4 179.0 2.4 Cuba 171.0 172.1 -1.1 New Zealand 177.6 175.2 2.4 Turkey 173.7 174.9 -1.2 Denmark 180.7 178.4 2.3 Poland 178.5 179.8 -1.3 Nicaragua 169.0 166.7 2.3 USA 176.8 178.1 -1.3 South Korea 174.4 172.4 2.0 Belarus 177.5 178.9 -1.4 Paraguay 171.7 169.8 1.9 France 177.1 178.5 -1.4 Moldova 174.8 172.9 1.9 Indonesia 163.9 165.4 -1.5 Georgia 175.8 173.9 1.9 Luxembourg 177.7 179.3 -1.6 Slovenia 179.8 177.9 1.9 Uzbekistan 171.1 172.7 -1.6 Kiribati 169.8 167.9 1.9 Sri Lanka 167.5 169.2 -1.7 Slovakia 179.3 177.5 1.8 Spain 177.1 178.8 -1.7 Norway 180.0 178.3 1.7 Vanuatu 167.8 169.6 -1.8 Trinidad and Tobago 175.3 173.7 1.6 Cyprus 174.6 176.5 -1.9 Latvia 180.2 178.6 1.6 Panama 167.8 169.7 -1.9 Suriname 170.9 169.4 1.5 Costa Rica 170.9 172.8 -1.9 Hungary 179.9 178.5 1.4 Kazakhstan 174.0 176.0 -2.0 Australia 177.8 176.4 1.4 Bahamas 171.5 173.5 -2.0 Algeria 174.3 173.0 1.3 Yemen 163.1 165.2 -2.1 Czechia 180.6 179.3 1.3 Japan 171.5 173.7 -2.2 Honduras 167.6 166.7 0.9 Kyrgyzstan 171.5 173.8 -2.3 Brazil 173.0 172.2 0.8 Thailand 167.6 169.9 -2.3 Jordan 170.9 170.2 0.7 Armenia 172.7 175.0 -2.3 Lebanon 175.5 174.8 0.7 Albania 174.7 177.0 -2.3 Uruguay 174.8 174.2 0.6 Philippines 163.9 166.3 -2.4 UAE 173.5 172.9 0.6 Chile 171.5 174.0 -2.5 Germany 180.2 179.7 0.5 Malaysia 167.8 170.3 -2.5 Canada 177.7 177.2 0.5 Viet Nam 164.4 167.0 -2.6 Belgium 179.4 178.9 0.5 Italy 176.5 179.1 -2.6 Kuwait 172.9 172.7 0.2 India 165.2 167.9 -2.7 Solomon Islands 167.4 167.2 0.2 Romania 174.9 177.6 -2.7 Iran 173.0 172.8 0.2 Colombia 168.8 171.5 -2.7 Mexico 168.2 168.1 0.1 Guatemala 161.9 164.7 -2.8 Cambodia 162.4 162.4 0.0 Mongolia 169.4 172.5 -3.1 Barbados 174.7 174.7 0.0 Peru 165.5 168.8 -3.3 Lithuania 179.4 179.4 0.0 Greece 176.1 179.5 -3.4 Morocco 171.7 171.7 0.0 Belize 167.0 170.6 -3.6 Turkmenistan 172.3 172.4 -0.1 Maldives 166.9 170.8 -3.9 Israel 174.5 174.6 -0.1 Brunei Darussalam 166.9 171.0 -4.1 Argentina 174.3 174.4 -0.1 Ecuador 166.2 170.5 -4.3 Azerbaijan 173.4 173.6 -0.2 Portugal 173.9 178.4 -4.5 Myanmar 164.2 164.4 -0.2 Malta 173.0 177.8 -4.8 Finland 178.6 178.8 -0.2
49
Appendix Table 8. Correlation between female height and socio-economic factors (a sample of 116 populations for which all variables are available).
Europe North Africa, Asia & Oceania
America WORLD TOTAL
Populations (n) 37 48 31 116
Mean r p Mean r p Mean r p Mean r p
GDP per capita 22,117 0.37 0.022 13,495 0.27 0.061 11,415 0.48 0.006 15,689 0.42 <0.001 GNI per capita 21,516 0.40 0.014 13,418 0.26 0.074 11,061 0.47 0.007 15,371 0.41 <0.001 Health expenditure 1,821 0.39 0.018 641 0.47 <0.001 878 0.37 0.039 1,076 0.55 <0.001 Child mortality 11.4 -0.50 0.002 38.7 -0.56 <0.001 27.7 -0.32 0.077 27.1 -0.63 <0.001 Total fertility rate 1.58 -0.20 0.244 2.91 -0.30 0.037 2.61 -0.67 <0.001 2.40 -0.65 <0.001 Urban population (%) 69.2 0.32 0.054 50.3 0.57 <0.001 62.0 -0.04 0.85 59.5 0.47 <0.001
Human Development Index 0.84 0.52 0.001 0.70 0.63 <0.001 0.73 0.45 0.011 0.75 0.70 <0.001
Positive relationships Negative relationships
r≥0.700 p < 0.001 p < 0.01 p < 0.05 p < 0.05 p < 0.01 p < 0.001 r≥0.700
50
Appendix Table 9. Relationship between female height and food consumption (supply) in 133 populations.
Europe North Africa. Asia & Oceania America TOTAL SAMPLE
Populations (n) 41 (mean: 165.0 cm) 56 (mean: 157.9 cm) 36 (mean: 159.5 cm) 133 (mean: 160.5 cm)
Mean r p Mean r p Mean r p Mean r p
PROTEIN SUPPLY (g/day per capita)
Dairy total 19.5 0.47 0.002 6.9 0.51 <0.001 10.0 0.43 0.009 11.6 0.72 <0.001 Cheese 7.7 0.40 0.009 1.2 0.51 <0.001 2.9 0.50 0.002 3.7 0.66 <0.001 Milk 9.1 -0.02 0.901 4.5 0.43 0.001 5.9 -0.01 0.939 6.3 0.43 <0.001 Eggs 3.3 0.35 0.027 1.9 0.37 0.004 1.8 -0.15 0.384 2.3 0.47 <0.001 Meat total 22.5 0.28 0.079 14.8 0.64 <0.001 20.2 0.66 <0.001 18.6 0.61 <0.001 Beef 5.9 0.00 0.982 3.7 0.67 <0.001 6.4 0.24 0.154 5.1 0.39 <0.001 Mutton & Goat meat 1.0 -0.13 0.404 1.9 0.37 0.005 0.7 0.42 0.011 1.3 0.09 0.301 Pork 8.4 0.48 0.001 2.5 0.19 0.171 3.2 0.42 0.010 4.5 0.58 <0.001 Poultry 6.4 0.05 0.758 6.0 0.49 <0.001 9.7 0.71 <0.001 7.1 0.34 <0.001 Fish & Seafood 5.5 0.20 0.204 6.8 -0.05 0.739 4.6 0.58 <0.001 5.8 0.04 0.682 Pelagic marine fish 2.2 0.29 0.063 2.9 -0.01 0.951 1.8 0.48 0.003 2.4 0.04 0.686 Freshwater fish 0.7 0.27 0.086 1.0 -0.38 0.004 0.4 0.06 0.744 0.7 -0.19 0.033 Pelagic & Freshwater fish 2.9 0.33 0.036 3.8 -0.11 0.436 2.2 0.50 0.002 3.1 -0.01 0.885 Offals 2.0 0.13 0.426 1.4 0.38 0.004 1.2 -0.05 0.761 1.5 0.32 <0.001 ANIMAL PROTEINS 53.2 0.40 0.009 31.7 0.57 <0.001 38.1 0.69 <0.001 40.1 0.69 <0.001 Cereals total 30.2 -0.58 <0.001 31.9 -0.03 0.841 23.4 -0.45 0.006 29.0 -0.15 0.092 Wheat 25.1 -0.62 <0.001 19.3 0.48 <0.001 12.0 0.55 <0.001 19.1 0.38 <0.001 Rice 0.8 -0.44 0.004 9.6 -0.64 <0.001 5.2 -0.28 0.104 5.7 -0.65 <0.001 Maize 1.8 -0.17 0.278 2.0 -0.32 0.015 5.4 -0.61 <0.001 2.8 -0.35 <0.001 Fruits 1.2 -0.13 0.414 1.1 0.33 0.012 1.5 0.24 0.162 1.2 0.18 0.039 Oilcrops 0.8 0.05 0.735 2.4 0.11 0.404 1.4 -0.02 0.916 1.6 -0.17 0.050 Legumes (excl. Soybeans) 1.7 -0.24 0.139 2.7 -0.14 0.305 4.6 -0.30 0.075 2.9 -0.32 <0.001 Legumes total 1.8 -0.23 0.156 3.7 -0.08 0.547 5.0 -0.31 0.068 3.5 -0.35 <0.001 Starchy roots 3.3 0.32 0.042 1.8 0.19 0.152 1.9 0.24 0.152 2.3 0.39 <0.001 Potatoes 3.3 0.32 0.042 1.0 0.41 0.002 1.2 0.02 0.918 1.8 0.58 <0.001 Treenuts 0.6 -0.04 0.823 0.5 0.28 0.038 0.2 0.27 0.106 0.4 0.23 0.009 Vegetables 3.7 -0.50 <0.001 3.3 0.43 <0.001 1.9 0.40 0.014 3.0 0.28 0.001 PLANT PROTEINS 44.0 -0.54 <0.001 45.0 0.16 0.231 36.8 -0.26 0.131 42.4 -0.03 0.714 TOTAL PROTEIN 97.1 0.15 0.347 76.7 0.67 <0.001 74.9 0.57 <0.001 82.5 0.68 <0.001 ENERGY SUPPLY (kcal/day) TOTAL ENERGY 3193.0 0.07 0.649 2723.2 0.67 0.000 2699.5 0.47 0.004 2861.6 0.65 <0.001 % Protein energy 12.4 0.17 0.283 11.5 0.43 0.001 11.3 0.48 0.003 11.7 0.49 <0.001 COMBINATIONS OR RATIOS OF PROTEIN SUPPLY
Rice & Legumes total 2.6 -0.33 0.034 13.3 -0.61 <0.001 10.1 -0.37 0.027 9.1 -0.67 <0.001 Rice. Maize & Legumes total 4.4 -0.32 0.040 15.3 -0.65 <0.001 15.5 -0.69 <0.001 12.0 -0.73 <0.001 Rice & Maize 2.6 -0.25 0.112 11.6 -0.69 <0.001 10.6 -0.77 <0.001 8.5 -0.74 <0.001 Dairy. Pork. Fish & Seafood 33.4 0.51 <0.001 16.1 0.31 0.021 17.8 0.66 <0.001 21.9 0.66 <0.001 Dairy & Beef 25.3 0.36 0.020 10.6 0.62 <0.001 16.4 0.39 0.020 16.7 0.69 <0.001 Dairy & Potatoes 22.8 0.53 <0.001 7.9 0.52 <0.001 11.2 0.40 0.016 13.4 0.73 <0.001 Dairy. Pork. Eggs & Beef 37.1 0.50 0.001 14.9 0.68 <0.001 21.4 0.40 0.016 23.5 0.75 <0.001 Dairy & Eggs 22.8 0.51 <0.001 8.7 0.56 <0.001 11.9 0.37 0.028 13.9 0.73 <0.001 Dairy. Pork. Eggs. Beef & Potat. 40.3 0.53 <0.001 15.9 0.69 <0.001 22.6 0.38 0.021 25.2 0.76 <0.001 Dairy & Pork 27.9 0.57 <0.001 9.3 0.58 <0.001 13.2 0.50 0.002 16.1 0.76 <0.001 Dairy. Pork & Eggs 31.2 0.59 <0.001 11.2 0.60 <0.001 15.0 0.44 0.007 18.4 0.76 <0.001 Dairy. Pork. Eggs & Potatoes 34.5 0.62 <0.001 12.2 0.62 <0.001 16.2 0.42 0.011 20.1 0.77 <0.001 ... / Rice & Maize 27.6 0.46 0.003 3.4 0.39 0.003 3.2 0.51 0.002 10.8 0.58 <0.001 Dairy & Pork / Wheat 1.2 0.67 <0.001 1.0 -0.31 0.019 1.2 -0.12 0.489 1.2 -0.07 0.436
Dairy & Pork / Cereals 1.0 0.63 <0.001 0.3 0.53 <0.001 0.6 0.58 <0.001 0.6 0.73 <0.001 % ANIMAL PROTEINS 53.8 0.54 <0.001 39.1 0.49 <0.001 49.3 0.64 <0.001 46.4 0.62 <0.001
Positive relationships Negative relationships
r≥0.700 p < 0.001 p < 0.01 p < 0.05 p < 0.05 p < 0.01 p < 0.001 r≥0.700
51
Arg
Bah
Barb
Berm Braz
Can
Chile
Cuba
Dom
Ecu Gren
Guat
Haiti
Jam
Mex
Neth Ant
Pan
Peru
St Kitts St.Vincent
Surin
Trin
USA
Ven
Alb
Aut
Belar
Belg
Bul
Cro
Cze Den Est
Fin Fra
Geo
Ger
Gre
Hun
Isl
Irel
Ita Lat
Lith
Lux
Malta
Mont
Neth
Pol
Port
Mold
Rom
Rus
Serb Svk
Slo Spain
Swe
Switz
Mac
Tur
Ukr
UK
Isr
Kuw
Oman
S.Arabia
UAE
Palest
Austr
Fiji
Fr.Polyn
N.Caled
NZL
Solom.Isl.
H Kong
Macau
N.Korea
Jap
Kaz
S.Korea
Brunei
Camb
Taiwan
Indon
Malay Mald
Thai
Timor Egypt
Iran
Iraq
Jord
Leb
Mor
Tun
Yemen
Syria
Afgh
China
Kyrg
Tajik
Uzb
Bangl
India
Laos
Myan Nepal
Pak
Philip
S.Lanka
Viet
Kirib
Samoa Van
Belize Bol
Col
C.Rica
Dom.Rep.
El Salv Guy
Hond
Nic
Par
St.Lucia
Urug
r = 0.77 (p<0.001) [n =133]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
146 148 150 152 154 156 158 160 162 164 166 168 170 172 174
Pro
tein
s fr
om
dai
ry,
po
rk, e
gg
s, a
nd
po
tato
es (
g/d
ay p
er c
apit
a)
Average female height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
Appendix Figure 27. Relationship between female height in 133 populations and the mean combined supply of proteins from dairy, pork, eggs, and potatoes (g/day per capita, FAOSTAT 1995-2013).
52
Appendix Figure 28. Relationship between female height in 133 populations and the mean combined supply of proteins from rice and maize (g/day per capita, FAOSTAT 1995-2013).
Arg
Berm
Braz
Can
Chile
Cuba
Ecu
Guat
Haiti
Jam
Mex
Neth Ant
Pan Peru
7.4
Surin
Trin
USA
Ven
Alb
Arm
Aut
Azerb
Cro
Cze Den
Est
Geo
Mont
Neth
Port
Mold
Rom
Serb
Slo
Swe
Mac
Kuw
Oman
S.Arabia
Fiji
Fr.Polyn
N.Caled
Macau
N.Korea
Jap
S.Korea Brunei
Camb
Taiwan
Indon
Malay
Mald
Thai
Timor Egypt
Iran
Iraq
Jord
Mor
Tun
Yemen
Syria
Afgh
China
Kyrg
Mong
Tajik Uzb
Bangl
India
Laos
Myan
Nepal
Pak
Philip
S.Lanka
Viet
Belize
Bol
Col
Dom.Rep.
El Salv
Guy
Hond Nic
Par
Urug
r = -0.74 (p<0.001) [n =133]
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
146 148 150 152 154 156 158 160 162 164 166 168 170 172 174
Pro
tein
s fr
om
ric
e an
d m
aize
(g
/day
per
cap
ita)
Average female height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
53
Appendix Table 10. Correlation between female height and nine socio-economic & three nutritional factors.
Seven socio-economic variables & Nutrition
...& Gini index ...& IHDI ...Gini index & IHDI
Populations (n) 110 98 93 90
Mean r p Mean r p Mean r p Mean r p
SOCIO-ECONOMIC FACTORS
GDP per capita 15,599 0.43 <0.001 14,161 0.62 <0.001 14,766 0.64 <0.001 14,699 0.63 <0.001
GNI per capita 15,297 0.42 <0.001 13,799 0.63 <0.001 14,402 0.65 <0.001 14,340 0.65 <0.001
Health expenditure 1,096 0.56 <0.001 1,098 0.59 <0.001 1,153 0.60 <0.001 1,164 0.60 <0.001
Child mortality 26.6 -0.62 <0.001 26.5 -0.61 <0.001 26.7 -0.66 <0.001 26.2 -0.65 <0.001
Total fertility rate 2.36 -0.68 <0.001 2.34 -0.69 <0.001 2.32 -0.71 <0.001 2.31 -0.70 <0.001
Urban population (%) 60.2 0.49 <0.001 60.3 0.53 <0.001 61.2 0.59 <0.001 61.5 0.58 <0.001
Human Development Index 0.76 0.71 <0.001 0.76 0.73 <0.001 0.76 0.76 <0.001 0.76 0.75 <0.001
Gini index 38.1 -0.53 <0.001 37.8 -0.53 <0.001
Inequality-adjusted HDI 0.63 0.81 <0.001 0.63 0.80 <0.001
PROTEIN SUPPLY (g/day per capita)
Dairy 11.9 0.72 <0.001 12.3 0.74 <0.001 12.6 0.75 <0.001 12.8 0.75 <0.001
Dairy, Pork, Eggs & Potatoes 20.4 0.78 <0.001 21.2 0.81 <0.001 21.6 0.82 <0.001 21.9 0.82 <0.001
Rice & Maize 8.9 -0.75 <0.001 8.5 -0.73 <0.001 8.8 -0.75 <0.001 8.6 -0.74 <0.001
Positive relationships Negative relationships
r≥0.700 p<0.001 p<0.01 p<0.05 p<0.05 p<0.01 p<0.001 r≥0.700
54
Appendix Figure 29. Relationship between female height in 103 populations and the inequality-adjusted Human Developmnent Index (IHDI) (2013). Populations with incomplete data that were not included in the joint analysis of nine socio-economic and three nutritional factors (90 populations; Appendix Table 10) are shown in matt colors.
Bah
Braz
Chile
Ecu
Guat
Haiti
Jam
Mex
Pan Peru
Trin
USA
Alb
Arm
Belar
Belg
Cro
Cze Den
Est
Fin Fra
Geo
Ger
Gre
Isl
Ita
Lat
Lith
Lux
Malta
Mont
Neth
Port
Mold
Rom Rus
Serb
Svk
Slo
Spain
Swe
Maced
Tur
Ukr
UK
Iran
Yem
Fiji
Kiribati
Solom.Isl.
Jap
Kaz
Mong
Camb
India
Indon
Mald
Thai
Timor
Egypt
Isr
Mor
Afgh
Taj
Uzb
Bangl
Laos
Nepal Pak
Philip
S.Lanka
Viet
Bhutan
Austr
Arg
Bol
Can
Col
C.Rica
Dom.Rep.
El Salv
Guyana
Hond
Nicar
Urug
Ven
r = 0.80 (p<0.001) [n =90] r = 0.81 (p<0.001) [n =103]
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
146 148 150 152 154 156 158 160 162 164 166 168 170 172 174
IHD
I (20
13)
Average female height (cm)
Europe North Africa & Near East Temperate Asia Tropical Asia Oceania America
55
Appendix Table 11. Multiple regression models of female height (total sample of 116 populations). Models Socio-economic variables only Nutrition only All 9 variables
(1a) (1b) (1c) (2a) (2b) (3a) (3b) (3c)
Parsimonious All Optimal Parsimonious Optimal Parsimonious All Optimal
Dairy, Pork,
Eggs & Potato
protein
b* = 0.50 r = 0.59 p < 0.001
b* = 0.42 r = 0.45 p < 0.001
b* = 0.31 r = 0.36 p < 0.001
b* = 0.28 r = 0.27 p = 0.004
b* = 0.28 r = 0.30 p = 0.001
Rice & Maize
protein
b* = -0.43 r = -0.53 p < 0.001
b* = -0.42 r = -0.52 p <0.001
b* = -0.45 r = -0.57 p < 0.001
b* = -0.43 r = -0.53 p < 0.001
b* = -0.45 r = -0.57 p < 0.001
Total energy b* = 0.13 r = 0.17 p = 0.076
b*= 0.11 r = 0.13 p = 0.17
b* = 0.12 r = 0.15 p = 0.11
GDP per capita b* = -0.26 r = -0.22 p = 0.023
b* = -0.27 r = -0.23 p = 0.015
b* = -0.07 r = -0.08 p = 0.41
Health
expenditure
per capita
b* = 0.19 r = 0.15 p = 0.12
b* = 0.19 r = 0.15 p = 0.11
b* = -0.01 r = -0.01 p = 0.95
Child mortality b* = -0.03 r = -0.03 p = 0.78
b* = -0.04 r = -0.05 p = 0.63
Total fertility rate b* = -0.32 r = -0.31 p < 0.001
b* = -0.27 r = -0.26 p = 0.008
b* = -0.28 r = -0.27 p = 0.004
b* = -0.27 r = -0.37 p < 0.001
b* = -0.22 r = -0.26 p = 0.007
b* = -0.27 r = -0.36 p < 0.001
Urban
population (%)
b* = -0.08 r = -0.08 p = 0.40
b* = -0.10 r = -0.13 p = 0.17
b* = -0.09 r = -0.14 p = 0.13
HDI b* = 0.47 r = 0.43 p < 0.001
b* = 0.58 r = 0.29 p = 0.002
b* = 0.54 r = 0.35 p < 0.001
b* = 0.09 r = 0.06 p = 0.56
Variables (n) 2 6 4 2 3 3 9 5
Adj. R2 0.533 0.545 0.550 0.713 0.718 0.750 0.748 0.753
p-values p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001 p < 0.001
Note: b* = beta coefficients; r = partial correlations; p = probability values.
Positive relationships Negative relationships
p < 0.001 p < 0.01 p < 0.05 p < 0.05 p < 0.01 p < 0.001
56
Appendix Table 12. Multiple regression models of female height (regions).
Europe North Africa, Asia, Oceania America
Models (1) (2a) (2b) Models (1a) (1b) Models (1a) (1b)
Parsim. Parsim. Optimal Parsimonious Optimal Parsim. Optimal
Populations (n) 40 39 39 Populations (n) 44 44 Populations (n) 32 32
Dairy & Pork / Wheat
protein
b* = 0.85 r = 0.65 p < 0.001
b* = 0.69 r = 0.75 p < 0.001
b* = 0.48 r = 0.50 p = 0.002
Dairy, Pork, Eggs,
Beef & Potato
protein
b* = 0.23 r = 0.34 p = 0.033
Poultry protein b* = 0.23 r = 0.32 p = 0.099
Rice & Maize
protein
b* = -0.49 r = -0.66 p < 0.001
b* = -0.36 r = -0.53 p < 0.001
Rice & Maize
protein
b* = -0.75 r = -0.75 p < 0.001
b* = -0.53 r = -0.61 p < 0.001
Total energy b* = 0.54 r = 0.69 p < 0.001
b* = 0.56 r = 0.63 p < 0.001
Genetics (Y
haplogroup I-M170)
b* = 0.30 r = 0.44 p = 0.008
Genetics (Y
haplogroup R1a-M420)
b* = 0.38 r = 0.53 p < 0.001
b* = 0.28 r = 0.39 p = 0.018
Genetics (Neolithic Y
haplogroups E, G, J)
b* = -0.13 r = -0.14 p = 0.41
GDP per capita GDP per capita b* = -0.25 r = -0.36 p = 0.024
GDP per capita
Health
expenditure
per capita
b* = -0.72 r = -0.47 p = 0.003
Health
expenditure
per capita
Health
expenditure
per capita
b* = 0.19 r = 0.27 p = 0.16
Child mortality Child mortality
Child mortality
Total fertility rate Total fertility rate Total fertility
rate
Urban
population (%)
Urban population
(%)
b* = 0.18 r = -0.18 p = 0.28
Urban
population (%)
HDI b* = 0.47 r = 0.32 p = 0.053
HDI b* = 0.26 r = 0.29 p = 0.068
HDI b* = -0.58 r = -0.50 p = 0.007
Variables (n) 3 2 4 Variables (n) 2 6 Variables (n) 1 5
Adj. R2 0.545 0.604 0.674 Adj. R2 0.722 0.785 Adj. R2 0.553 0.720
p-value p < 0.001 p < 0.001 p < 0.001 p-value p < 0.001 p < 0.001 p-value p < 0.001 p < 0.001
Note: b* = beta coefficients; r = partial correlations; p = probability values.
Positive relationships Negative relationships
p < 0.001 p < 0.01 p < 0.05 p < 0.05 p < 0.01 p < 0.001
57
Appendix Table 13. Correlations between male height in 28 American populations and 57 variables, including partial correlations in 53 variables adjusted for genetic factors.
Variables
Correlations Adjustment for Nat. American & East Asian
genetic ancestry Mean r p partial correlations (r)
PROTEIN SUPPLY (g/day per capita)
Dairy total 9.8 0.53 0.004 0.51
Cheese 2.8 0.57 0.002 0.52
Milk 6.2 0.18 0.350 0.27
Eggs 2.0 0.05 0.796 0.23
Meat total 19.6 0.61 < 0.001 0.50
Beef 6.9 0.34 0.076 0.37
Mutton & Goat meat 0.6 0.34 0.079 0.16
Pork 3.1 0.37 0.051 0.22
Poultry 8.6 0.60 < 0.001 0.42
Fish & Seafood 3.8 0.56 0.002 0.39
Pelagic marine fish 1.7 0.34 0.080 0.25
Freshwater fish 0.4 0.18 0.350 0.09
Pelagic & Freshwater fish 2.1 0.39 0.041 0.28
Offals 1.4 -0.12 0.538 0.08
ANIMAL PROTEINS 36.7 0.67 < 0.001 0.59
Cereals total 23.8 -0.30 0.126 0.11
Wheat 11.6 0.61 < 0.001 0.62
Rice 4.8 -0.31 0.106 -0.49
Maize 6.6 -0.56 0.002 -0.27
Fruits 1.4 0.12 0.531 -0.12
Oilcrops 1.4 0.25 0.194 0.09
Legumes (excl. Soybeans) 5.0 -0.19 0.333 -0.35
Legumes total 5.4 -0.19 0.342 -0.34
Starchy roots 1.9 0.20 0.298 0.36
Potatoes 1.3 0.09 0.634 0.44
Treenuts 0.2 0.34 0.078 0.37
Vegetables 1.8 0.35 0.069 0.18
PLANT PROTEINS 37.2 -0.09 0.638 0.08
TOTAL PROTEIN 74.0 0.60 < 0.001 0.57
ENERGY SUPPLY (kcal/day)
TOTAL ENERGY 2683.1 0.57 0.002 0.48
% PROTEIN ENERGY 11.2 0.42 0.025 0.50
COMBINATIONS OR RATIOS OF PROTEIN SUPPLY
Rice & Legumes total 10.2 -0.30 0.124 -0.49
Rice. Maize & Legumes total 16.8 -0.61 < 0.001 -0.52
Rice & Maize 11.4 -0.73 < 0.001 -0.57
Dairy. Pork. Fish & Seafood 16.7 0.70 < 0.001 0.60
Dairy & Beef 16.7 0.47 0.011 0.49
Dairy & Potatoes 11.1 0.50 0.006 0.56
Dairy. Pork. Eggs & Beef 21.8 0.48 0.009 0.48
Dairy & Eggs 11.8 0.48 0.010 0.49
Dairy. Pork. Eggs. Beef & Potat. 23.1 0.47 0.011 0.50
Dairy & Pork 12.9 0.57 0.002 0.50
Dairy. Pork & Eggs 14.9 0.52 0.005 0.48
Dairy. Pork. Eggs & Potatoes 16.2 0.51 0.006 0.52
... / Rice & Maize 2.6 0.67 < 0.001 0.61
Dairy & Pork / Wheat 1.3 -0.10 0.613 -0.11
Dairy & Pork / Cereals 0.6 0.57 0.002 0.40
% ANIMAL PROTEINS 48.0 0.59 0.001 0.51
SOCIO-ECONOMIC FACTORS
GDP per capita 12.048 0.55 0.002 0.39
Health expenditure 928 0.47 0.011 0.35
Child mortality 26.7 -0.43 0.022 -0.45
Total fertility 2.55 -0.68 < 0.001 -0.51
% Urban population 64.7 0.04 0.820 0.18
HDI 2013 0.74 0.55 0.002 0.57
GENETIC FACTORS
Genetics (European) 42.3 0.27 0.16
Genetics (African) 28.5 0.40 0.036
Genetics (European & African) 70.9 0.76 < 0.001
Genetics (Nat. American & East Asian) 28.6 -0.77 < 0.001
Positive relationships Negative relationships
r≥0.700 p < 0.001 p < 0.01 p < 0.05 p < 0.05 p < 0.01 p < 0.001 r≥0.700