Soft Drinks & Non-Alcoholic Beverages Data: Consumption, Intake, Prices and Product Records · Head-to-head
BLS Consumer Price Data Tools (Nonalcoholic Beverages CPI) vs WHO Global Health Observatory Indicators
Which soft drinks & non-alcoholic beverages data: consumption, intake, prices and product records data fits your job: BLS Consumer Price Data Tools, or WHO Global Health Observatory Indicators. API, files, or your warehouse. Daily, weekly, or hourly.
BLS Consumer Price Data Tools (Nonalcoholic Beverages CPI)
WHO Global Health Observatory Indicators
Coverage, side by side
| BLS Consumer Price Data Tools | WHO Global Health Observatory Indicators | |
|---|---|---|
| Geographic | Area code carried inside `series_id`; US city average plus regional and area indexes | `SpatialDim` - ISO3 country code (GIN), with `ParentLocation` giving the WHO region |
What each contains
Pick by fit, not by loyalty.
| BLS Consumer Price Data Tools | WHO Global Health Observatory Indicators | |
|---|---|---|
| Documented fields | 5 | 11 |
| Period stamp | `year` (calendar year, 1947 onward) plus `period` M01-M13, where M13 is the annual average | `TimeDim` - integer reference year of the observation |
| Geography | Area code carried inside `series_id`; US city average plus regional and area indexes | `SpatialDim` - ISO3 country code (GIN), with `ParentLocation` giving the WHO region |
| Series descriptor | `series_id` combining seasonal-adjustment prefix (CUUR/CUSR), area code and item code (SAF114, SEFN01) | `IndicatorCode` - short code distinguishing obesity measures (NCD_BMI_30C) from policy registers (NCD_CCS_SSBTAX) |
| Measured value | `value` - index number relative to the 1982-84=100 base period (11.4 in January 1947) | `NumericValue` point estimate with `Low`/`High` uncertainty bounds, plus `Value` string formatted with interval or Yes/No |
| Segment dimension | None beyond the adjustment prefix and area - no population subgroup axis | `Dim1` - disaggregation by sex, age or wealth quintile where the survey supports it |
| Provenance columns | `footnote_codes` - flags such as `X` marking values unavailable after the 2025 appropriations lapse | `DataSourceDim`, `Comments` and the `Date` timestamp recording when the fact entered the observatory |
What each does better
the BLS nonalcoholic beverages CPI
Depth. Nothing else in the beverage catalog reaches 1947. The verified item codes in the CPI cu database read like a shelf plan: SAF114 (Nonalcoholic beverages and beverage materials), SEFN (Juices and nonalcoholic drinks), SEFN01 (Carbonated drinks), SEFN02 (Frozen noncarbonated juices and drinks), SEFN03 (Nonfrozen noncarbonated juices and drinks) and SEFP (Beverage materials including coffee and tea). Each code combines with an area code and a seasonal-adjustment prefix into a full series ID such as CUUR0000SAF114, indexed to the 1982-84=100 base.
A single-item series spans roughly 950 monthly rows from January 1947 to the present, and extraction this August found the data current through July 2026 - with October through December 2025 flagged X, marked unavailable after the federal appropriations lapse. The sample row proves the vintage: CUUR0000SAF114 reads 11.4 for January 1947. Seasonally adjusted (CUSR) and unadjusted (CUUR) variants ride alongside each other, and regional area indexes sit behind the US city average.
It also saves you from a trap. Two frequently circulated series IDs look like beverage codes and are not: CUUR0000SAF113 resolves to fruits and vegetables, and CUUR0000SEFJ resolves to dairy and related products. The beverage family is SAF114 and the SEFN block - verified directly against the item-code dictionary rather than copied from a forum post.
the WHO Global Health Observatory
Breadth. Where the BLS table covers one deep market, the observatory covers the map. Crude adult obesity (NCD_BMI_30C, BMI 30 kg/m2 and above) holds about 28,350 facts across 199 countries spanning 1980 to 2024, with an age-standardized companion in NCD_BMI_30A and an overweight-plus-obesity measure in EQ_OVERWEIGHTADULT. Every modeled prevalence estimate ships with Low and High uncertainty bounds, and the Dim1 dimension splits facts by sex where the survey supports it.
The policy shelf is the one beverage strategists actually ask about. NCD_CCS_SSBTAX records whether a country levies a tax on sugar-sweetened beverages: 582 records across 194 countries, captured in three waves - 2017, 2019 and 2021. Its sibling NCD_CCS_FOOD_TAX covers taxes on foods high in fat, sugar or salt, and an oral-health indicator tracks national policies aimed at cutting sugars intake. A sample fact shows the grain: Guinea (GIN), 2019, SSB tax - "No", filed under the WHO African region.
That wave structure is also the trade: tax answers arrive as two-to-three-year snapshots rather than a continuous series, so the observatory maps regulatory direction better than it times month-to-month change.
Or take both in one feed
Yes - the observatory supplies the demand weather and the regulatory forecast; the CPI supplies the register receipt from the world's largest beverage market.
The 1947 starting line matters here: it lets you compare today's pricing behavior against decades that predate sugar politics entirely.
Three cautions from the field dictionary. Treat the observatory as the map and the CPI as the seismograph, and neither will mislead you.
API, files, or your warehouse. Daily, weekly, or hourly.
Fair questions
Is the BLS nonalcoholic beverages CPI better than WHO GHO indicators?
They answer different questions. WHO wins on reach: obesity, overweight and sugar-tax indicators across roughly 194 to 199 countries, also scoring 8/10.
Which dataset covers more geography?
The WHO observatory, decisively: 194 countries for the sugar-sweetened beverage tax register and 199 for crude adult obesity, all under one ISO3 code system. The BLS tools stay inside the United States - city average plus regional area indexes - but compensate with depth, carrying monthly index readings back to 1947.
Which goes further back in time?
The BLS series run continuously from January 1947 - about 950 monthly rows for a single-item series, indexed to 1982-84=100. WHO depth depends on the indicator: modeled adult obesity reaches back to 1980, while sugar-tax answers exist only for the 2017, 2019 and 2021 waves.
Can I combine BLS CPI data with WHO obesity and tax indicators?
Yes. Bridge the two deliberately - there is no shared key, and index levels need converting before any currency comparison.
Can I get both BLS and WHO beverage data from Datadory?
Yes - sample both and pick by fit, or take both in one feed. Datadory normalizes each to its documented field dictionary, attaches sample rows for validation, and ships them alongside the rest of the soft drinks and non-alcoholic beverages catalog, delivered daily, weekly, or hourly - your call.