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Record W3143760019 · doi:10.1016/s2542-5196(20)30304-1

Changes in beverage purchases following the announcement and implementation of South Africa's Health Promotion Levy: an observational study

2021· article· en· W3143760019 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Lancet Planetary Health · 2021
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersCarolina Population Center, University of North Carolina at Chapel HillUniversity of North Carolina at Chapel HillEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversity of the Western CapeNational Center for Advancing Translational SciencesUniversity of North Carolina WilmingtonMedical Research CouncilUniversity of the Witwatersrand, JohannesburgSouth African Medical Research CouncilInternational Development Research CentreNational Institutes of HealthBloomberg Philanthropies
KeywordsTaxable incomePer capitaDemographyBusinessEconomicsDemographic economicsMedicineEnvironmental healthAccountingPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: In 2016, South Africa announced an intention to levy a tax on sugar-sweetened beverages (SSBs). In 2018, the country implemented an SSB tax of approximately 10%, known as the Health Promotion Levy (HPL). We aimed to assess changes in the purchases of beverages before and after the HPL announcement and implementation. METHODS: We used Kantar Europanel data on monthly household purchases between January, 2014, and March, 2019, among a sample of South African households (n=113 653 household-month observations) from all nine provinces to obtain per-capita sugar, calories, and volume from taxable and non-taxable beverages purchased before and after the HPL announcement and implementation. We describe survey-weighted means for each period, and regression-controlled predictions of outcomes and counterfactuals based on pre-HPL announcement trends, with bootstrapped 95% CIs, and stratify results by socioeconomic status. FINDINGS: Mean sugar from taxable beverage purchases fell from 16·25 g/capita per day (95% CI 15·80-16·70) to 14·26 (13·85-14·67) from the pre-HPL announcement to post-announcement period, and then to 10·63 g/capita per day (10·22-11·04) in the year after implementation. Mean volumes of taxable beverage purchases fell from 518·99 mL/capita per day (506·90-531·08) to 492·16 (481·28-503·04) from pre-announcement to post announcement, and then to 443·39 mL/capita per day (430·10-456·56) after implementation. Across these time periods, there was a small increase in the purchases of non-taxable beverages, from 283·45 mL/capita per day (273·34-293·56) pre-announcement to 312·94 (296·29-329·29) post implementation. When compared with pre-announcement counterfactual trends, reductions in taxable beverage purchase outcomes were significantly larger than the unadjusted survey-weighted observed reductions. Households with lower socioeconomic status purchased larger amounts of taxable beverages in the pre-announcement period than did households with higher socioeconomic status, but demonstrated bigger reductions after the tax was implemented. INTERPRETATION: The announcement and introduction of South Africa's HPL were followed by reductions in the sugar, calories, and volume of beverage purchases. FUNDING: Bloomberg Philanthropies, International Development Research Centre, South African Medical Research Council, and the US National Institutes of Health.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.037
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.200
GPT teacher head0.393
Teacher spread0.193 · 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