A cross-sectional analysis of the differences in anthropometry parameters and body composition was carried out in two populations of kiwchas, natives from Ecuador.
This study was carried out in Ecuador in two geographically different areas, the Andes and the Amazon Basin. The research work began in January 2017 and concluded in August 2019.
Ecuador with an area of more than 283,000 Km2 is the smallest country in the Andean mountainous region in South America. The country is divided into 4 geographical regions, the coast, the highlands, the Amazon region, and the Galapagos Islands. The political division encloses 24 provinces, 10 from the highlands, 7 from the coast, 6 from the Amazon region and 1 from the insular region of Galapagos. Every province has several political divisions called cantons and they are comparable to cities elsewhere. The country has 141 cantons at low altitude, 28 at moderate altitude, 41 at high altitude and 11 at very high altitude. Limoncocha is located at low altitude while Oyacachi is located at very high altitude (Figure 1).
All the participants who voluntarily agreed are members of the Kiwcha indigenous group from Ecuador. The high-altitude group came from Oyacachi, a small Kiwcha community located at 3,800 m of elevation while the low-altitude group came from Limoncocha, located at 230 m of elevation.
The study will be carried out in healthy volunteers of both sexes without any type of comorbidity or chronic disease, between the ages of 18 and 85 who were born and currently residing in Oyacachi (high-altitude group) and in Limoncocha (low altitude group).
Volunteers who are under 18 years of age, who were born in another community and those who does not habitually reside in the parishes were excluded from the study. Those volunteers who did not complete the anthropometric measurements were excluded from the analysis.
Variables and outcomes
Sociodemographic variables, such as age, sex, marital status, and place of residence were recorded. We included the following anthropometric measurements Weight (Kg), Height (cm), Body Mass Index (BMI), Shoulder height (cm), Hip height (cm), Buttock height (cm), Lateral arm length (cm), Shoulder height (cm)- median (IQR), Biacromial Shoulder Width (cm), Biiliac width (cm), Arm length (cm), Chest circumference (cm), Waist circumference (cm), Head circumference (cm) ,Body composition grease (%), Body composition Muscle (%),Corporal Age (years), Real Age (years).
The main outcome is to determine the possible anthropometric differences between genotype-matched Kiwcha indigenous people who live at high altitudes versus their counterparts who live at low altitudes
Individual-level socio-demographic information, place of residence and past medical history was obtained in-situ in both communities. A complete physical examination including body weight, height, and t anthropometric variables recording was performed.
Study size and sample size calculation:
In terms of the number of patients required to achieve significance the sample size (n) and margin of error (E) were given by the following formula:
||N x/((N-1)E2 + x)
||Sqrt[(N - n)x/n(N-1)]
Where N is the population size (n=570 in Oyacachi and n=890 in Limoncocha), (r) is the fraction of expected responses (50%), and Z(c/100) is the critical value for the confidence level (c). The total number of medical and physical evaluations required to achieve statistical significance was 82 for the high-altitude group and 96 for the low-altitude control group. Through a non-probability convenience-based sampling technique 117 patients were included in Limoncocha and 95 for Oyacachi.
DNA extraction and analysis of ancestry ratios
To compare the ancestry of the two populations, a subsample of 47 unrelated individuals (30 Oyacachi vs 17 Limoncocha) was selected. We looked for a subsample among all the individuals to identify those subjects who did not have any first order degree of consanguinity, condition that is based on our laboratory protocol for ancestry analysis. DNA extraction was performed from FTA cards (GE Healthcare) by the Chelex method, then the extracts were diluted to a concentration of 5 ng / ul using the NanoDrop 2000 UV-Vis spectrophotometer (Thermo Scientific, Waltham, MA)(25). 46-plex autosomal ancestry informative deletion-insertion markers (46-plex AIMs-InDel) were amplified. Fluorescent amplicons were sized by capillary electrophoresis in Pop-7 polymer using a genetic analyzer ABI 3130 (Applied Biosystems, Austin, TX). Alleles were named by the software Genemapper V 3.1 (Life Technologies, Carlsbad, CA) following nomenclature described by Pereira et al, 2012(26). Taking into account tri-hybrid historic mixture in Ecuador(27–29), Inference of ancestry proportions were obtained considering the admixture model with K = 3 (based in Runs consisted of 100,000 burnin steps, followed by 100,000 Markov Chain Monte Carlo (MCMC) using STRUCTURE V2.3.4 software(30).
All runs were made without any prior information on the origin of samples and only considered the genetic background for the ancestral continental populations based on reference samples: European, EUR (n = 158), African, AFR (n = 105), and Native American, NAM (n = 64). Reference genotypes were extracted from the diversity panel of the Human Genome Diversity Project-Center d'Etude du Polymorphisme Humain (HGDP-CEPH). The populations selected as comparative groups for Africa were: Angola (n = 1), Botswana (n = 4), Central African Republic (n = 23), Congo (n = 13), Kenya (n = 11), Lesotho (n = 1), Namibia (n = 6), Nigeria (n = 22), Senegal (n = 22) and, South Africa (n = 2), for South America: Brazil (n = 22), Colombia (n = 7), and Mexico (n = 35), and for Europe were: France (n = 52), Italy (n = 49), Orkney Islands (n = 15) and Russia (n = 42).
Descriptive statistics were used to analyze and visualize differences between the two populations. Student’s t-test was used to analyze differences between continue variables and Chi square test was performed to check the association or independence of categorical variables. When the expected values were less than 5 in any of the categories, Fisher's exact test or Spearman's test were used when the variable had evident asymmetries with histograms prior to the selection of the test. The strength of association between categorical variables was performed using the V-Cramer test.
All statistical analysis accepted significance for a p-value <0.05. Calculations were completed using the IBM Corp. Released 2014. IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: and R Core Team software 2018 version 3.5.1. Cartography was generated using QGIS Development Team 2.8 and all the references were managed using the open source software Zotero 5.0.85
A full ethical approval was obtained (#MED.EOP.17.01) thought out the Universidad de las Americas bioethics committee (CEISH). All patients voluntarily signed an informed consent. For people who could not read or write, an official community translator and a family member capable of understanding what was described in the document were used to explain the entire context of the project and ensure that there were no doubts about it. To protect the identity and autonomy of patients, all personal information was coded to ensure anonymity