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Htet AS, Bjertness MB, Oo WM, Kjøllesdal MK, Sherpa LY, Zaw KK, Ko K, Stigum H, Meyer HE, Bjertness E. Changes in prevalence, awareness, treatment and control of hypertension from 2004 to 2014 among 25-74-year-old citizens in the Yangon Region, Myanmar. BMC Public Health 2017; 17:847. [PMID: 29073891 PMCID: PMC5659019 DOI: 10.1186/s12889-017-4870-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Accepted: 10/20/2017] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Hypertension is the leading risk factor for cardiovascular diseases, and little is known about trends in prevalence, awareness, treatment and the control of hypertension in Myanmar. This study aims at evaluating changes from 2004 to 2014 in the prevalence, awareness, treatment and control of hypertension in the Yangon Region, Myanmar, and to compare associations between hypertension and selected socio-demographic, behavioural- and metabolic risk factors in 2004 and 2014. METHODS In 2004 and 2014, household-based cross-sectional studies were conducted in urban and rural areas of Yangon Region using the WHO STEPS protocol. Through a multi-stage cluster sampling method, a total of 4448 and 1486 participated in 2004 and 2014, respectively, with the response rates above 89%. RESULTS From 2004 to 2014, there was a significant increase in the age-standardized prevalence of hypertension from 26.7% (95% CI:24.4-29.1) - 34.6% (32.2-37.1), as well as an awareness from 19.4% (17.2-21.9) to 27.8% (24.9-31.0), while treatment and control rates did not change. The age-standardized mean systolic blood pressure increased from 122.8 (SE) ± 0.82 mmHg in 2004 to 128.1 ± 0.53 mmHg in 2014, whereas diastolic blood pressure increased from 76.2 ± 0.35 mmHg to 80.9 ± 0.53 mmHg. In multivariate analyses, hypertension was significantly associated with age, alcohol consumption, overweight and diabetes in both 2004 and 2014, and additionally associated with low physical activity and hypercholesterolemia in 2004. Combining all data, a significant association between study-year and hypertension persisted in different models with an adjustment for socio-demographic variables and behavioural variables, but not when adjusting for a combination of socio-demographic variables, the metabolic variables, BMI and hypercholesterolemia. CONCLUSION The prevalence of hypertension has risen from 2004 to 2014 in both urban and rural areas of the Yangon Region, while, the awareness, treatment and control rate of hypertension remains low in urban and rural areas among both males and females. It is likely that changes in the metabolic variables, BMI and hypercholesterolemia have contributed to an increase in the prevalence of hypertension from 2004 to 2014. Factors associated with hypertension in both study years were age, alcohol consumption, overweight and diabetes. A national hypertension control programme should be implemented in order to reduce premature deaths in Myanmar.
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Affiliation(s)
- Aung Soe Htet
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
- International Relations Division, Ministry of Health, Nay Pyi Taw, Myanmar
| | - Marius B. Bjertness
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Win Myint Oo
- Faculty of Medicine, SEGi University, Petaling Jaya, Malaysia
| | - Marte Karoline Kjøllesdal
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Lhamo Y. Sherpa
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Ko Ko Zaw
- University of Public Health, Yangon, Myanmar
| | - Ko Ko
- Department of Diabetes and Endocrinology, University of Medicine 2, Yangon, Myanmar
| | - Hein Stigum
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Haakon E. Meyer
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Espen Bjertness
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
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Htet AS, Bjertness MB, Sherpa LY, Kjøllesdal MK, Oo WM, Meyer HE, Stigum H, Bjertness E. Urban-rural differences in the prevalence of non-communicable diseases risk factors among 25-74 years old citizens in Yangon Region, Myanmar: a cross sectional study. BMC Public Health 2016; 16:1225. [PMID: 27919240 PMCID: PMC5139102 DOI: 10.1186/s12889-016-3882-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2016] [Accepted: 11/25/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Recent societal and political reforms in Myanmar may upturn the socio-economy and, thus, contribute to the country's health transition. Baseline data on urban-rural disparities in non-communicable disease (NCD) risk factors are not thoroughly described in this country which has been relatively closed for more than five decades. We aim to investigate urban-rural differences in mean values and the prevalence of selected behavioral and metabolic risk factors for non-communicable diseases and 10-years risk in development of coronary heart diseases (CHD). METHODS Two cross-sectional studies were conducted in urban and rural areas of Yangon Region in 2013 and 2014 respectively, using the WHO STEPwise approach to surveillance of risk factors of NCDs. Through a multi-stage cluster sampling method, 1486 participants were recruited. RESULTS Age-standardized prevalence of the behavioral risk factors tended to be higher in the rural than urban areas for all included factors and significantly higher for alcohol drinking (19.9% vs. 13.9%; p = 0.040) and low fruit & vegetable consumption (96.7% vs. 85.1%; p = 0.001). For the metabolic risk factors, the tendency was opposite, with higher age-standardized prevalence estimates in urban than rural areas, significantly for overweight and obesity combined (40.9% vs. 31.2%; p = 0.023), obesity (12.3% vs.7.7%; p = 0.019) and diabetes (17.2% vs. 9.2%; p = 0.024). In sub-group analysis by gender, the prevalence of hypercholesterolemia and hypertriglyceridemia were significantly higher in urban than rural areas among males, 61.8% vs. 40.4%; p = 0.002 and 31.4% vs. 20.7%; p = 0.009, respectively. Mean values of age-standardized metabolic parameters showed higher values in urban than rural areas for both male and female. Based on WHO age-standardized Framingham risk scores, 33.0% (95% CI = 31.7-34.4) of urban dwellers and 27.0% (95% CI = 23.5-30.8) of rural dwellers had a moderate to high risk of developing CHD in the next 10 years. CONCLUSION The metabolic risk factors, as well as a moderate or high ten-year risk of CHD were more common among urban residents whereas behavioral risk factors levels were higher in among the rural people of Yangon Region. The high prevalences of NCD risk factors in both urban and rural areas call for preventive measures to reduce the future risk of NCDs in Myanmar.
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Affiliation(s)
- Aung Soe Htet
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway. .,International Relations Division, Ministry of Health, Nay Pyi Taw, Myanmar.
| | - Marius B Bjertness
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Lhamo Y Sherpa
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Marte Karoline Kjøllesdal
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Win Myint Oo
- Faculty of Medicine, SEGi University, Petaling Jaya, Malaysia
| | - Haakon E Meyer
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Hein Stigum
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Espen Bjertness
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
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Bjertness MB, Htet AS, Meyer HE, Htike MMT, Zaw KK, Oo WM, Latt TS, Sherpa LY, Bjertness E. Prevalence and determinants of hypertension in Myanmar - a nationwide cross-sectional study. BMC Public Health 2016; 16:590. [PMID: 27430560 PMCID: PMC4950687 DOI: 10.1186/s12889-016-3275-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 07/07/2016] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Non-communicable diseases (NCDs), malaria and tuberculosis dominate the disease pattern in Myanmar. Due to urbanization, westernized lifestyle and economic development, it is likely that NCDs such as cerebrovascular disease and ischemic heart disease are on a rise. The leading behavioral- and metabolic NCDs risk factors are tobacco smoke, dietary risks and alcohol use, and high blood pressure and body mass index, respectively. The study aimed at estimating the prevalence and determinants of hypertension, including metabolic-, behavioral- and socio-demographic risk factors. METHODS A nationwide, cross-sectional study of 7429 citizens of Myanmar aged 15-64 years were examined in 2009, using the WHO STEPS methodology. In separate analyses by gender, odds radios (ORs) and 95 % confidence intervals (CIs) for determinants of hypertension were estimated using logistic regression analyses. Confounders included in analyses were chosen based on Directed acyclic graphs (DAGs). RESULTS The prevalence of hypertension was 30.1 % (95 % CI: 28.4-31.8) in males and 29.8 % (28.5-31.1) in females. The mean BMI was 21.7 (SD 4.3) kg/m(2) for males and 23.0 (5.1) kg/m(2) for females. In fully adjusted analyses, we found in both genders increased OR for hypertension if the participants had high BMI (males: OR = 2.6; 95 % CI 2.1-3.3, females: OR = 2.3; 2.0-2.7) and high waist circumference (males: OR = 3.4; 1.8-6.8, females: OR = 2.7; 2.2-3.3). In both sexes, associations were also found between hypertension and low physical activity at work, or living in urban areas or the delta region. Being underweight and use of sesame oil in cooking was associated with lower odds for hypertension. CONCLUSIONS The prevalence of hypertension was high and associated with metabolic-, behavioral- and socio-demographic factors. Due to expected rapid economic growth in Myanmar we recommend similar studies in the future to follow up and describe trends in the risk factors, especially modifiable factors, which will most likely be on rise. Studies on effectiveness on interventions are needed, and policies to reduce the burden of NCD risk factors should be implemented if proven effective in similar settings.
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Affiliation(s)
- Marius B. Bjertness
- />Section for Preventive Medicine and Epidemiology, Department of Community Medicine, University of Oslo, Oslo, Norway
| | - Aung Soe Htet
- />Section for Preventive Medicine and Epidemiology, Department of Community Medicine, University of Oslo, Oslo, Norway
- />International Health Department, Ministry of Health, Nay Pyi Taw, Myanmar
| | - Haakon E. Meyer
- />Section for Preventive Medicine and Epidemiology, Department of Community Medicine, University of Oslo, Oslo, Norway
- />Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
| | | | - Ko Ko Zaw
- />Department of Medical Research, Ministry of Health, Nay Pyi Taw, Myanmar
| | - Win Myint Oo
- />Department of Preventive and Social Medicine, University of Medicine 1, Yangon, Myanmar
| | | | - Lhamo Y. Sherpa
- />Section for Preventive Medicine and Epidemiology, Department of Community Medicine, University of Oslo, Oslo, Norway
| | - Espen Bjertness
- />Section for Preventive Medicine and Epidemiology, Department of Community Medicine, University of Oslo, Oslo, Norway
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Anderson I, Robson B, Connolly M, Al-Yaman F, Bjertness E, King A, Tynan M, Madden R, Bang A, Coimbra CEA, Pesantes MA, Amigo H, Andronov S, Armien B, Obando DA, Axelsson P, Bhatti ZS, Bhutta ZA, Bjerregaard P, Bjertness MB, Briceno-Leon R, Broderstad AR, Bustos P, Chongsuvivatwong V, Chu J, Gouda J, Harikumar R, Htay TT, Htet AS, Izugbara C, Kamaka M, King M, Kodavanti MR, Lara M, Laxmaiah A, Lema C, Taborda AML, Liabsuetrakul T, Lobanov A, Melhus M, Meshram I, Miranda JJ, Mu TT, Nagalla B, Nimmathota A, Popov AI, Poveda AMP, Ram F, Reich H, Santos RV, Sein AA, Shekhar C, Sherpa LY, Skold P, Tano S, Tanywe A, Ugwu C, Ugwu F, Vapattanawong P, Wan X, Welch JR, Yang G, Yang Z, Yap L. Indigenous and tribal peoples' health (The Lancet-Lowitja Institute Global Collaboration): a population study. Lancet 2016; 388:131-157. [PMID: 27108232 DOI: 10.1016/s0140-6736(16)] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
BACKGROUND International studies of the health of Indigenous and tribal peoples provide important public health insights. Reliable data are required for the development of policy and health services. Previous studies document poorer outcomes for Indigenous peoples compared with benchmark populations, but have been restricted in their coverage of countries or the range of health indicators. Our objective is to describe the health and social status of Indigenous and tribal peoples relative to benchmark populations from a sample of countries. METHODS Collaborators with expertise in Indigenous health data systems were identified for each country. Data were obtained for population, life expectancy at birth, infant mortality, low and high birthweight, maternal mortality, nutritional status, educational attainment, and economic status. Data sources consisted of governmental data, data from non-governmental organisations such as UNICEF, and other research. Absolute and relative differences were calculated. FINDINGS Our data (23 countries, 28 populations) provide evidence of poorer health and social outcomes for Indigenous peoples than for non-Indigenous populations. However, this is not uniformly the case, and the size of the rate difference varies. We document poorer outcomes for Indigenous populations for: life expectancy at birth for 16 of 18 populations with a difference greater than 1 year in 15 populations; infant mortality rate for 18 of 19 populations with a rate difference greater than one per 1000 livebirths in 16 populations; maternal mortality in ten populations; low birthweight with the rate difference greater than 2% in three populations; high birthweight with the rate difference greater than 2% in one population; child malnutrition for ten of 16 populations with a difference greater than 10% in five populations; child obesity for eight of 12 populations with a difference greater than 5% in four populations; adult obesity for seven of 13 populations with a difference greater than 10% in four populations; educational attainment for 26 of 27 populations with a difference greater than 1% in 24 populations; and economic status for 15 of 18 populations with a difference greater than 1% in 14 populations. INTERPRETATION We systematically collated data across a broader sample of countries and indicators than done in previous studies. Taking into account the UN Sustainable Development Goals, we recommend that national governments develop targeted policy responses to Indigenous health, improving access to health services, and Indigenous data within national surveillance systems. FUNDING The Lowitja Institute.
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Affiliation(s)
- Ian Anderson
- The University of Melbourne, Melbourne, Australia.
| | - Bridget Robson
- Te Rōpū Rangahau Hauora a Eru Pōmare, University of Otago, Dunedin, New Zealand
| | | | - Fadwa Al-Yaman
- Indigenous and Children's Group, Australian Institute of Health and Welfare, Canberra, Australia
| | - Espen Bjertness
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway
| | | | | | | | - Abhay Bang
- Society for Education, Action and Research in Community Health, Gadchiroli, Maharashtra, India
| | - Carlos E A Coimbra
- Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Maria Amalia Pesantes
- Salud Sin Límites Perú, Lima, Peru; Center for Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | | | - Blas Armien
- The Gorgas Memorial Institute for Health Studies, Universidad Interamericana de Panamá, Panama City, Panama
| | | | - Per Axelsson
- Centre for Sami Research, Umeå University, Umeå, Sweden
| | - Zaid Shakoor Bhatti
- Department of Paediatrics and Child Health, The Aga Khan University, Karachi, Pakistan
| | - Zulfiqar Ahmed Bhutta
- Center of Excellence in Women and Child Health, The Aga Khan University, Karachi, Pakistan; SickKids Center for Global Child Health, Toronto, Canada
| | - Peter Bjerregaard
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Marius B Bjertness
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway
| | - Roberto Briceno-Leon
- LACSO, Social Science Laboratory, Central University of Venezuela, Caracas, Venezuela
| | - Ann Ragnhild Broderstad
- Centre for Sami Health Research, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway
| | | | | | - Jiayou Chu
- Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Jitendra Gouda
- International Institute for Population Sciences, Deemed University, Mumbai, India
| | - Rachakulla Harikumar
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | | | - Aung Soe Htet
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway; Ministry of Health, Nay Pyi Taw, Myanmar
| | - Chimaraoke Izugbara
- Population Dynamics and Reproductive Health Program, African Population and Health Research Center, Nairobi, Kenya
| | - Martina Kamaka
- Department of Native Hawaiian Health, John A Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Malcolm King
- CIHR-Institute of Aboriginal Peoples' Health, Simon Fraser University, Burnaby, BC, Canada
| | | | | | - Avula Laxmaiah
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | | | | | - Tippawan Liabsuetrakul
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand
| | - Andrey Lobanov
- Scientific Research Centre of the Arctic, Salekhard, Russia
| | - Marita Melhus
- Centre for Sami Health Research, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway
| | - Indrapal Meshram
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | - J Jaime Miranda
- Center for Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Balkrishna Nagalla
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | - Arlappa Nimmathota
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | | | | | - Faujdar Ram
- International Institute for Population Sciences, Deemed University, Mumbai, India
| | - Hannah Reich
- The University of Melbourne, Melbourne, Australia
| | - Ricardo V Santos
- Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | | | - Chander Shekhar
- International Institute for Population Sciences, Deemed University, Mumbai, India
| | - Lhamo Y Sherpa
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway
| | - Peter Skold
- Arctic Research Centre, Umeå University, Umeå, Sweden
| | - Sofia Tano
- School of Business and Economy, Umeå University, Umeå, Sweden
| | - Asahngwa Tanywe
- Cameroon Centre for Evidence-Based Health Care, Yaounde, Cameroon
| | - Chidi Ugwu
- Department of Sociology/Anthropology, University of Nigeria, Nsukka, Nigeria
| | - Fabian Ugwu
- Department of Psychology, Federal University, Ndufu-Alike, Nigeria
| | - Patama Vapattanawong
- Institute for Population and Social Research, Mahidol University Salaya, Phuttamonton, Nakhon Pathom, Thailand
| | - Xia Wan
- Institute of Basic Medical Sciences at Chinese Academy of Medical Sciences & School of Basic Medicine at Peking Union Medical College, Beijing, China
| | - James R Welch
- Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Gonghuan Yang
- Institute of Basic Medical Sciences at Chinese Academy of Medical Sciences & School of Basic Medicine at Peking Union Medical College, Beijing, China
| | - Zhaoqing Yang
- Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Leslie Yap
- Native Hawaiian Center of Excellence, John A Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
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5
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Anderson I, Robson B, Connolly M, Al-Yaman F, Bjertness E, King A, Tynan M, Madden R, Bang A, Coimbra CEA, Pesantes MA, Amigo H, Andronov S, Armien B, Obando DA, Axelsson P, Bhatti ZS, Bhutta ZA, Bjerregaard P, Bjertness MB, Briceno-Leon R, Broderstad AR, Bustos P, Chongsuvivatwong V, Chu J, Gouda J, Harikumar R, Htay TT, Htet AS, Izugbara C, Kamaka M, King M, Kodavanti MR, Lara M, Laxmaiah A, Lema C, Taborda AML, Liabsuetrakul T, Lobanov A, Melhus M, Meshram I, Miranda JJ, Mu TT, Nagalla B, Nimmathota A, Popov AI, Poveda AMP, Ram F, Reich H, Santos RV, Sein AA, Shekhar C, Sherpa LY, Skold P, Tano S, Tanywe A, Ugwu C, Ugwu F, Vapattanawong P, Wan X, Welch JR, Yang G, Yang Z, Yap L. Indigenous and tribal peoples' health (The Lancet-Lowitja Institute Global Collaboration): a population study. Lancet 2016; 388:131-57. [PMID: 27108232 DOI: 10.1016/s0140-6736(16)00345-7] [Citation(s) in RCA: 513] [Impact Index Per Article: 64.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND International studies of the health of Indigenous and tribal peoples provide important public health insights. Reliable data are required for the development of policy and health services. Previous studies document poorer outcomes for Indigenous peoples compared with benchmark populations, but have been restricted in their coverage of countries or the range of health indicators. Our objective is to describe the health and social status of Indigenous and tribal peoples relative to benchmark populations from a sample of countries. METHODS Collaborators with expertise in Indigenous health data systems were identified for each country. Data were obtained for population, life expectancy at birth, infant mortality, low and high birthweight, maternal mortality, nutritional status, educational attainment, and economic status. Data sources consisted of governmental data, data from non-governmental organisations such as UNICEF, and other research. Absolute and relative differences were calculated. FINDINGS Our data (23 countries, 28 populations) provide evidence of poorer health and social outcomes for Indigenous peoples than for non-Indigenous populations. However, this is not uniformly the case, and the size of the rate difference varies. We document poorer outcomes for Indigenous populations for: life expectancy at birth for 16 of 18 populations with a difference greater than 1 year in 15 populations; infant mortality rate for 18 of 19 populations with a rate difference greater than one per 1000 livebirths in 16 populations; maternal mortality in ten populations; low birthweight with the rate difference greater than 2% in three populations; high birthweight with the rate difference greater than 2% in one population; child malnutrition for ten of 16 populations with a difference greater than 10% in five populations; child obesity for eight of 12 populations with a difference greater than 5% in four populations; adult obesity for seven of 13 populations with a difference greater than 10% in four populations; educational attainment for 26 of 27 populations with a difference greater than 1% in 24 populations; and economic status for 15 of 18 populations with a difference greater than 1% in 14 populations. INTERPRETATION We systematically collated data across a broader sample of countries and indicators than done in previous studies. Taking into account the UN Sustainable Development Goals, we recommend that national governments develop targeted policy responses to Indigenous health, improving access to health services, and Indigenous data within national surveillance systems. FUNDING The Lowitja Institute.
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Affiliation(s)
- Ian Anderson
- The University of Melbourne, Melbourne, Australia.
| | - Bridget Robson
- Te Rōpū Rangahau Hauora a Eru Pōmare, University of Otago, Dunedin, New Zealand
| | | | - Fadwa Al-Yaman
- Indigenous and Children's Group, Australian Institute of Health and Welfare, Canberra, Australia
| | - Espen Bjertness
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway
| | | | | | | | - Abhay Bang
- Society for Education, Action and Research in Community Health, Gadchiroli, Maharashtra, India
| | - Carlos E A Coimbra
- Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Maria Amalia Pesantes
- Salud Sin Límites Perú, Lima, Peru; Center for Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | | | - Blas Armien
- The Gorgas Memorial Institute for Health Studies, Universidad Interamericana de Panamá, Panama City, Panama
| | | | - Per Axelsson
- Centre for Sami Research, Umeå University, Umeå, Sweden
| | - Zaid Shakoor Bhatti
- Department of Paediatrics and Child Health, The Aga Khan University, Karachi, Pakistan
| | - Zulfiqar Ahmed Bhutta
- Center of Excellence in Women and Child Health, The Aga Khan University, Karachi, Pakistan; SickKids Center for Global Child Health, Toronto, Canada
| | - Peter Bjerregaard
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Marius B Bjertness
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway
| | - Roberto Briceno-Leon
- LACSO, Social Science Laboratory, Central University of Venezuela, Caracas, Venezuela
| | - Ann Ragnhild Broderstad
- Centre for Sami Health Research, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway
| | | | | | - Jiayou Chu
- Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Jitendra Gouda
- International Institute for Population Sciences, Deemed University, Mumbai, India
| | - Rachakulla Harikumar
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | | | - Aung Soe Htet
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway; Ministry of Health, Nay Pyi Taw, Myanmar
| | - Chimaraoke Izugbara
- Population Dynamics and Reproductive Health Program, African Population and Health Research Center, Nairobi, Kenya
| | - Martina Kamaka
- Department of Native Hawaiian Health, John A Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Malcolm King
- CIHR-Institute of Aboriginal Peoples' Health, Simon Fraser University, Burnaby, BC, Canada
| | | | | | - Avula Laxmaiah
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | | | | | - Tippawan Liabsuetrakul
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand
| | - Andrey Lobanov
- Scientific Research Centre of the Arctic, Salekhard, Russia
| | - Marita Melhus
- Centre for Sami Health Research, Faculty of Health, UiT The Arctic University of Norway, Tromsø, Norway
| | - Indrapal Meshram
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | - J Jaime Miranda
- Center for Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Balkrishna Nagalla
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | - Arlappa Nimmathota
- National Institute of Nutrition, Indian Council of Medical Research, Hyderabad, India
| | | | | | - Faujdar Ram
- International Institute for Population Sciences, Deemed University, Mumbai, India
| | - Hannah Reich
- The University of Melbourne, Melbourne, Australia
| | - Ricardo V Santos
- Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | | | - Chander Shekhar
- International Institute for Population Sciences, Deemed University, Mumbai, India
| | - Lhamo Y Sherpa
- University of Oslo, Institute of Health and Society, Department of Community Medicine, Oslo, Norway
| | - Peter Skold
- Arctic Research Centre, Umeå University, Umeå, Sweden
| | - Sofia Tano
- School of Business and Economy, Umeå University, Umeå, Sweden
| | - Asahngwa Tanywe
- Cameroon Centre for Evidence-Based Health Care, Yaounde, Cameroon
| | - Chidi Ugwu
- Department of Sociology/Anthropology, University of Nigeria, Nsukka, Nigeria
| | - Fabian Ugwu
- Department of Psychology, Federal University, Ndufu-Alike, Nigeria
| | - Patama Vapattanawong
- Institute for Population and Social Research, Mahidol University Salaya, Phuttamonton, Nakhon Pathom, Thailand
| | - Xia Wan
- Institute of Basic Medical Sciences at Chinese Academy of Medical Sciences & School of Basic Medicine at Peking Union Medical College, Beijing, China
| | - James R Welch
- Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Gonghuan Yang
- Institute of Basic Medical Sciences at Chinese Academy of Medical Sciences & School of Basic Medicine at Peking Union Medical College, Beijing, China
| | - Zhaoqing Yang
- Institute of Medical Biology, Chinese Academy of Medical Sciences, Kunming, China
| | - Leslie Yap
- Native Hawaiian Center of Excellence, John A Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
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Sherpa LY, Deji, Stigum H, Chongsuvivatwong V, Nafstad P, Bjertness E. Prevalence of metabolic syndrome and common metabolic components in high altitude farmers and herdsmen at 3700 m in Tibet. High Alt Med Biol 2013; 14:37-44. [PMID: 23537259 DOI: 10.1089/ham.2012.1051] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVES To estimate the prevalence of metabolic syndrome, its associated factors and components in 30-80-year-old Tibetans living at high altitude. METHOD Multistage sampling of 692 participants. We used IDF criteria for estimation of the metabolic syndrome, and a questionnaire based on the WHO MONICA protocol. RESULTS The prevalence of metabolic syndrome was 8.2% (Confidence interval (CI):6.1-10.2) while the common components were: fasting hyperglycemia 57.5% (53.8-61.1); abdominal obesity 46% (42.2-49.7); and high blood pressure 37% (33.4-40.5). Metabolic syndrome was significantly lower for males, those with higher education and physical activity >2000 Kcal/week. Self awareness, treatment and control were low for both diabetes and lipid abnormality. CONCLUSION The overall prevalence of metabolic syndrome in high altitude farmers and herdsmen in Tibet was lower compared to other high altitude natives, while its components (hyperglycemia, obesity, and high blood pressure) were higher than in other high altitude communities. Implications of the findings of high prevalence of smoking (among men), obesity, and hypertension and low rates of awareness, treatment, and control of the components of the metabolic syndrome among rural highlanders propels the need for health programs targeting risk factors.
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Affiliation(s)
- Lhamo Y Sherpa
- Section for Preventive Medicine and Epidemiology, Department of Community Medicine, Institute of Health and Society, University of Oslo, Oslo, Norway.
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Sherpa LY, Deji, Stigum H, Chongsuvivatwong V, Luobu O, Thelle DS, Nafstad P, Bjertness E. Lipid profile and its association with risk factors for coronary heart disease in the highlanders of Lhasa, Tibet. High Alt Med Biol 2011; 12:57-63. [PMID: 21452966 DOI: 10.1089/ham.2010.1050] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to determine the prevalence of abnormal lipid levels and its association with selected coronary heart disease (CHD) risk factors in the Tibetan population living at 3660 meters above sea level in Lhasa, Tibet. Three hundred seventy one randomly selected male and female, aged 30 to 70 yr took part in the study. Based on the National Cholesterol Education Programme (NCED) adult treatment panel ATP-III 2004 criteria, the age-adjusted prevalence of hypertriglyceridemia was 12.0%; high triglycerides (TG), 33.4%; high low-density lipoprotein cholesterol (LDL-C), 4.8%; and low high-density lipoprotein cholesterol (HDL-C); 24.3%. After adjusting for age, sex, smoking, alcohol, physical activity, diet, hemoglobin (Hb) concentration, and systolic and diastolic blood pressure (BP), an increase in waist-to-hip ratio (WHR) by 0.1 unit was associated with a statistically significant increase in TG, total cholesterol (TC) and LDL-C by 0.25 mmol/L, 0.24 mmol/L, and 0.18 mmol/L, respectively. Female gender increased HDL-C by 0.18 mmol/L when compared with males. Age-adjusted prevalences of Framingham CHD risk score for males and females were 16.3% and 0.6%, respectively. This study demonstrated a high prevalence of hypertriglyceridemia in males, a higher prevalence of low HDL-C in females, and a high hypercholesterolemia prevalence in both genders. However, further longitudinal studies assessing CHD risk factors in high altitude natives are required.
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Affiliation(s)
- Lhamo Y Sherpa
- Section for Preventive Medicine and Epidemiology, Institute of Health and Society, University of Oslo, Oslo, Norway.
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