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Record W4289261010 · doi:10.1101/2022.07.28.22277961

Arterial hypertension and its covariates among nomadic Raute hunter-gatherers of Western Nepal: a mixed-method study

2022· preprint· en· W4289261010 on OpenAlexfundno aff
Tapendra Koirala, BC Udaya Bahadur, Carmina Shrestha, Ujjawal Paudel, Rolina Dhital, Sunil Pokharel, Madhusudan Subedi

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
FundersFaculty of Medicine and Dentistry, University of AlbertaUniversity of Alberta
KeywordsMedicineAnthropometryInterquartile rangeBlood pressureDemographyPopulationEnvironmental healthAlcohol consumptionSittingSurgeryAlcoholInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objectives To determine the prevalence of, and understand the factors associated with, hypertension among the nomadic Raute hunter-gatherers of Western Nepal. Design A mixed-method study. Setting The study was carried out at Raute temporary campsites in the Surkhet District of Karnali Province between May to September 2021. Participants The questionnaire-based survey included all males and non-pregnant females of the nomadic Raute group aged 15 years and above. In-depth interviews were conducted among purposively selected 15 Raute participants and four non-Raute key informants to help explain and enrich the quantitative findings. Outcome measures The prevalence of hypertension (defined as brachial artery blood pressure of systolic ≥ 140 mm Hg and/or diastolic ≥ 90 mm Hg) and its socio-demographic, anthropometric, and behavioral covariates. Results Of the 85 eligible participants, 81 [median age 35 years (interquartile range: 26–51), 46.9% female] were included in the final analysis. Hypertension was found in 10.5% of females, 48.8% of men, and 30.9% of the total population. Current alcohol and tobacco use were high (91.4% and 70.4%, respectively), with concerning high rates among youths. Males, older people, current drinkers, and current tobacco users were more likely to have hypertension. Our qualitative analysis suggests that the traditional forest-based Raute economy is gradually transitioning into a cash-based one that heavily relies on government incentives. Consumption of commercial foods, drinks, and tobacco products is increasing as their market involvement grows. Conclusion This study found a high burden of hypertension, alcohol, and tobacco use among nomadic Raute hunter-gatherers facing socioeconomic and dietary transitions. Further research is needed to assess the long-term impact of these changes on their health. This study is expected to help appraise concerned policymakers of an emerging health concern and formulate context-specific and culturally sensitive interventions to limit hypertension-related morbidities and mortalities in this endangered population. Strengths and limitations of this study This is the first study to report the prevalence of hypertension and its covariates among the nomadic Raute hunter-gatherers of Nepal. The major strengths of this study are the use of a mixed-method design to have both quantitative and qualitative perspectives, near total population enrollment, and robust methodology. The cross-sectional design of this study limits its ability to establish causal relationships between the variables. Several important factors, such as dietary fruits and vegetable consumption, salt intake, and level of physical activities, as well as the presence of diabetes mellitus, dyslipidemia, or central obesity, were not assessed, preventing this study from determining the community’s actual cardiovascular disease risk. Interviews taken in language non-native (Nepali) to the Raute may be subject to language bias.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.308
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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