The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index; none of the 25 sources its claims cite is checked for support yet.
The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data
Open accessAbstract
While experimental and observational studies suggest that sugar intake is associated with the development of type 2 diabetes, independent of its role in obesity, it is unclear whether alterations in sugar intake can account for differences in diabetes prevalence among overall populations. Using econometric models of repeated cross-sectional data on diabetes and nutritional components of food from 175 countries, we found that every 150 kcal/person/day increase in sugar availability (about one can of soda/day) was associated with increased diabetes prevalence by 1.1% (p <0.001) after testing for potential selection biases and controlling for other food types (including fibers, meats, fruits, oils, cereals), total calories, overweight and obesity, period-effects, and several socioeconomic variables such as aging, urbanization and income. No other food types yielded significant individual associations with diabetes prevalence after controlling for obesity and other confounders. The impact of sugar on diabetes was independent of sedentary behavior and alcohol use, and the effect was modified but not confounded by obesity or overweight. Duration and degree of sugar exposure correlated significantly with diabetes prevalence in a dose-dependent manner, while declines in sugar exposure correlated with significant subsequent declines in diabetes rates independently of other socioeconomic, dietary and obesity prevalence changes. Differences in sugar availability statistically explain variations in diabetes prevalence rates at a population level that are not explained by physical activity, overweight or obesity.
Overview
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Written from the paper’s full text.
TL;DR
Using econometric models of repeated cross-sectional data from 175 countries, this study found that higher sugar availability was associated with higher population-level diabetes prevalence, independent of obesity and other food types. The author concludes that sugar availability statistically explains some population variation in diabetes rates not explained by physical activity, overweight, or obesity.
Key findings
- Every 150 kcal/person/day increase in sugar availability (about one can of soda/day) was associated with a 1.1% increase in diabetes prevalence (95% CI: 0.48–1.7%; p<0.001) after controlling for other foods, total calories, overweight/obesity, period effects, and socioeconomic variables; total calorie availability was not significantly associated (0.1% rise per 150 kcal, not significant). No other food type had a significant individual association with diabetes prevalence after controls.
- The fraction of total calories from sugar was the only significant food fraction: a 1% rise corresponded to a 0.167% rise in diabetes prevalence. Each extra year of high sugar availability (≥300 kcal/person/day) was associated with a 0.053% increase in diabetes prevalence (p<0.05), and periods after a country lowered sugar availability showed a 0.074% reduction in diabetes prevalence (p<0.05).
- Diabetes prevalence rose 27% on average from 2000 to 2010, with just over one-fourth of the increase explained by rising sugar availability in the model. The sugar association remained after controlling for selection bias (magnified to 1.2% per 150 kcal/person/day, p<0.001), after removing outliers (1.2%, p<0.001), and in an autoregressive time-series model (0.4%, p<0.001).
Methods
- Econometric analysis of repeated cross-sectional panel data from 175 countries, 2000–2010. Diabetes prevalence (ages 20–79) came from the International Diabetes Federation; sugar and other food availability (kcal/person/day) came from UN FAO food supply data.
- Main models controlled for total calories, fibers, fruits, meats, cereals, oils, log GDP per capita, change in log GDP, urbanization, aging, obesity/overweight, period effects, and later physical inactivity, smoking, and heavy alcohol use. Food data were age-adjusted, regressions were population weighted, and robust standard errors were used.
- Analyses included Generalized Estimating Equations for model selection, a Hausman test, a Heckman-type selection model for high sugar availability, Granger-causality tests, and robustness checks (outlier removal, autoregressive time-series, fixed effects, direct survey data, and excluding the U.S.).
Limitations
- The paper states that cross-country ecological analysis risks ecological fallacy; food supply data measure availability, not actual consumption, and cannot account precisely for food wastage. It also cannot distinguish specific added sugars (e.g., HFCS vs. sucrose) or specific vehicles (e.g., soda vs. processed food).
- The paper states that ecological data limit statistical power and lose age, sex, and racial predictions; IDF diabetes prevalence data come from surveys of varying quality, likely underestimate diabetes, and do not distinguish type 1 from type 2 diabetes. FAO, IDF, and WHO data are described as imperfect, making findings exploratory.
- Evident from the text: the study is observational and country-level, so it cannot establish individual-level causation; despite extensive controls, unmeasured confounding remains possible, and sugar availability is a proxy for intake rather than a direct consumption measure.
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Claims the paper makes
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In countries like the Philippines, Romania, Sri Lanka, Georgia and Bangladesh, where high and rising diabetes rates were observed in the context of low obesity rates, sugar availability rose by over 20% during the study period.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
None of the sources cited for this claim have been checked yet.
In the paper
“The coefficient of log Gross Domestic Product (GDP) per capita was 1.07, which means that a 1% increase in GDP levels corresponded to a 1.07% rise in diabetes prevalence (p<0.05), consistent with the notion that economic development is a powerful correlate to diabetes prevalence [35], [36].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
What the sources say
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We initially separated fruit from other vegetables/fibers given the potential glucose burden of fruit; when repeating the analysis combining fruits with vegetables and other fibers, the results did not change.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using econometric models of repeated cross-sectional data on diabetes and nutritional components of food from 175 countries, we found that every 150 kcal/person/day increase in sugar availability (about one can of soda/day) was associated with increased diabetes prevalence by 1.1% (p <0.001) after testing for potential selection biases and controlling for other food types (including fibers, meats,”
- Also stated in: § Correlates of diabetes prevalence · plain
“Each 150 kilocalorie/person/day increase in total calorie availability related to a 0.1% rise in diabetes prevalence (not significant), whereas a 150 kilocalories/person/day rise in sugar availability (one 12 oz. can of soft drink) was associated with a 1.1% rise in diabetes prevalence (95% CI: 0.48–1.7%; p<0.001) after all control variables were incorporated into the model.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
- Also stated in: § Correlates of diabetes prevalence · plain
None of the sources cited for this claim have been checked yet.
In the paper
“High diabetes yet low obesity prevalence are observed in countries with different ethnic compositions, such as the Philippines, Romania, France, Bangladesh and Georgia, although there are likely surveillance quality differences between nations [6], [7].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
What the sources say
- Not checked yetcites [6] International Diabetes Federation (2011) IDF Diabetes Atlas.
- Not checked yetcites [7] World Health Organization (2012) Global database on body mass index.
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We additionally tested whether sugar availability alone was a significant predictor of obesity rates independent of the other control variables (total consumption, urbanization, aging, income, other foods and period effects), and found the expected relationship between total calories and obesity, but not individually between sugar and obesity when total calories was accounted for—consistent with”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“each 150 kcal/person/day rise in sugar availability related to a 0.4% rise in diabetes prevalence (p<0.001).”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional robustness checks
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that in the periods after a country lowered its sugar availability (typically in the context of changes in trade agreements, discussed at length elsewhere, [38]), diabetes prevalence reduced by 0.074% (p<0.05), after correcting for changes in all other controls including the economic variables, socio-demographic variables, and changes in consumption of other food products as well as total”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional robustness checks
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At a population level, however, obesity does not fully explain variations and trends in diabetes prevalence rates observed in many countries.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In Table 1 , we see that sugar availability remained a significant correlate to diabetes prevalence independent of obesity and total calorie consumption.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
- It may state two separate claims as one. 32
- The quote only partly states this claim. 1
- Probably not a substantial claim. 11
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The impact of sugar on diabetes was independent of sedentary behavior and alcohol use, and the effect was modified but not confounded by obesity or overweight.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Trends in diabetes and obesity are also dyssynchronous within some nations; while Sri Lanka’s diabetes prevalence rate rose from 3% in the year 2000 to 11% in 2010, its obesity rate remained at 0.1% during that time period.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Incorporation of these factors (see Table S4) did not affect the sugar variable and did not themselves reach statistical significance as independent correlates of diabetes when the other control variables were included in the model.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional control variables
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As shown in Figure 1 , several countries with high diabetes prevalence rates have low obesity rates, and vice versa.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Duration and degree of sugar exposure correlated significantly with diabetes prevalence in a dose-dependent manner, while declines in sugar exposure correlated with significant subsequent declines in diabetes rates independently of other socioeconomic, dietary and obesity prevalence changes.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We tested the hypothesis that low-carbohydrate fibers (nuts and vegetables) might be protective against diabetes by individually including them in the regression (as opposed to all fiber-containing foods) but they had no significant effect, and did not change the impact of sugar on diabetes prevalence.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Each 150 kilocalorie/person/day increase in total calorie availability related to a 0.1% rise in diabetes prevalence (not significant)”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In all cases, the sugar variable maintained a similar association with diabetes prevalence.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional robustness checks
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe quote only partly states this claim.
- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Diabetes prevalence rates rose 27% on average from 2000 to 2010, with just over one-fourth of the increase explained by a rise in sugar availability in this model.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We identified a significant relationship between high sugar availability and subsequently higher diabetes prevalence rates, not vice versa.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional robustness checks
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As shown in Table 2 , the fraction of total calories arising from sugar was the only significant food fraction correlated with diabetes, with a 1% rise in the fraction of total food calories as sugar corresponding to a 0.167% rise in diabetes prevalence.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Tests of sugar exposure
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Conversely, diabetes prevalence in New Zealand declined from 8% in 2000 to 5% in 2010 while obesity rates in the country rose from 23% to 34% during that decade.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results were strengthened: a 150 kcal/person/day rise in sugar availability corresponded to a 1.2% rise in diabetes prevalence (p<0.001) as opposed to a 1.1% rise when outliers were included.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional robustness checks
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Similarly, in our analysis, many foods did not have significant correlations to diabetes prevalence at the population level, even though they are associated with diabetes in cohort or clinical trial studies.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Other societal factors associated with diabetes were those classically associated with metabolic syndrome; including income, urbanization and aging.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we identified that sugar availability appears to be uniquely correlated to diabetes prevalence independent of overweight and obesity prevalence rates, unlike other food types and total consumption, and independent of other changes in economic and social change such as urbanization, aging, changes to household income, sedentary lifestyles and tobacco or alcohol use.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
In the paper
“Similarly, variables capturing urbanization and aging populations were associated with diabetes prevalence; however these variables fell from significance as total food availability and obesity were incorporated into the model ( Table 1 ), suggesting that calorie consumption and obesity are among the pathways by which these other factors may contribute to diabetes, consistent with cross-sectional”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
What the sources say
- Not checked yetcites [37] KR Siegel, 2012, Societal correlates of diabetes prevalence: an analysis across 94 countries, Diabetes Res Clin Pract source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
In the paper
“We also modeled the hazard of having high sugar availability rates in each country, and used this constructed hazard variable to explicitly control for potential unobserved selection bias (a “Heckman selection model”, see Text S1) [29].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Methods
What the sources say
- Not checked yetcites [29] J Heckman, 2004, Using matching, instrumental variables and control functions to estimate economic choice models, Rev Econ Stat source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When obesity was removed from the model, the effect size of sugar was not significantly amplified (beta = 0.0081, p<0.001), suggesting that obesity does not appear to account for the major part of the impact of sugar on diabetes.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
In the paper
“First, a Hausman test [28] was performed to test whether factors that differ across countries such as the differing strength of diabetes surveillance systems would systematically affect our results, ensuring the available data were suitable to answer our research questions.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Methods
What the sources say
- Not checked yetcites [28] JA Hausman, 1978, Specification tests in econometrics, Econometrica source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Sugary foods have been significantly associated with the development of insulin resistance in laboratory-based studies [18], [19].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
What the sources say
- Not checked yetcites [18] KL Teff, 2009, Endocrine and metabolic effects of consuming fructose- and glucose-sweetened beverages with meals in obese men and women: influence of insulin resistance on plasma triglyceride responses, J Clin Endocrinol Metab source
- Not checked yetcites [19] AA Bremer, 2011, Fructose-fed rhesus monkeys: a nonhuman primate model of insulin resistance, metabolic syndrome, and type 2 diabetes, Clin Transl Sci source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Lastly, a high prevalence of smoking and heavy alcohol use have been associated with diabetes [5].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Additional control variables
What the sources say
- Not checked yetcites [5] FB Hu, 2011, Globalization of diabetes: the role of diet, lifestyle, and genes, Diab Care source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“For example, liver fructose metabolism in the fed state generates lipogenic substrates in an unregulated fashion, which drives hepatic de novo lipogenesis and reduced fatty acid oxidation, forming excessive liver fat and inflammation that inactivates the insulin signaling pathway, leading to hepatic insulin resistance [16], [17].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
What the sources say
- Not checked yetcites [16] AA Bremer, 2012, Toward a unifying hypothesis of metabolic syndrome, Pediatrics source
- Not checked yetcites [17] Y Nagai, 2009, The role of peroxisome proliferator-activated receptor gamma coactivator-1 beta in the pathogenesis of fructose-induced insulin resistance, Cell Metab source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Sugars added to processed food, in particular the monosaccharide fructose, can contribute to obesity [14], but also appear to have properties that increase diabetes risk independently from obesity [15].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
What the sources say
- Not checked yetcites [14] RJ Johnson, 2007, Potential role of sugar (fructose) in the epidemic of hypertension, obesity and the metabolic syndrome, diabetes, kidney disease, and cardiovascular disease, Am J Clin Nutr source
- Not checked yetcites [15] Malik VS, Hu FB (2012) Sweeteners and risk of obesity and type 2 diabetes: the role of sugar-sweetened beverages. Curr Diab Rep epub Jan 31.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“We also performed Granger-causality tests, which use the temporal nature of the data to test whether high sugar availability preceded an increase in diabetes (“precedence”) or whether high diabetes prevalence preceded high sugar availability [34] (see Text S1).”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Methods
What the sources say
- Not checked yetcites [34] CWJ Granger, 1969, Investigating causal relations by econometric models and cross-spectral methods, Econometrica
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“(It is possible that weight gain, rather than overt obesity, might account for some of the changes in diabetes, hence our models were repeated with overweight prevalence rather than obesity in Table S3, and with measures of physical inactivity rather than BMI in Table S4, but the results did not change).”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Results > Correlates of diabetes prevalence
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Food supply data on market availability accurately reflect population-level sugar intake or consumption.
- Rests on an assumption: International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that obesity appeared to exacerbate, but not confound, the impact of sugar availability on diabetes prevalence”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In all analyses, food availability data were age-adjusted, regressions were population weighted, and robust standard errors were computed to ensure stability of the results in the face of heteroskedasticity and intragroup correlations.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Methods
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
In the paper
“We conducted explicit model selection procedures using Generalized Estimating Equations (see results in Text S1) to ensure the model was an optimal choice for the given data [30].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Methods
What the sources say
- Not checked yetcites [30] Hardin JW, Hilbe JM (2003) Generalized estimating equations. Boca Raton: CRC Press. source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Reactive oxygen species are produced by the Maillard reaction [20], [21], damaging pancreatic beta cells, and leading to a subcellular stress response (the “unfolded protein response” in the endoplasmic reticulum) that drives insulin inadequacy [22], [23].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Introduction
What the sources say
- Not checked yetcites [20] CG Schalkwijk, 2004, Fructose-mediated non-enzymatic glycation: sweet coupling or bad modification, Diabetes Metab Res source
- Not checked yetcites [21] WL Dills, 1993, Protein fructosylation: fructose and the Maillard reaction, Am J Clin Nutr source
- Not checked yetcites [22] CX Santos, 2009, Mechanisms and implications of reactive oxygen species generation during the unfolded protein response: roles of endoplasmic reticulum oxidoreductases, mitochondrial electron transport, and NADPH oxidase, Antioxid Redox Signal source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The observed associations are biologically plausible, given the numerous mechanisms by which sugar foments pathophysiologic processes leading to diabetes [19], [40].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
What the sources say
- Not checked yetcites [19] AA Bremer, 2011, Fructose-fed rhesus monkeys: a nonhuman primate model of insulin resistance, metabolic syndrome, and type 2 diabetes, Clin Transl Sci source
- Not checked yetcites [40] JS Lim, 2010, The role of fructose in the pathogenesis of NAFLD and the metabolic syndrome, Nat Rev Gastroenterol Hepatol source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“It is thought that much of the FAO data on foods and nutrients in the food supply have limits to their reliability, and that IDF data and WHO data on obesity prevalence are difficult to validate independently.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“our ecological approach limits statistical power as one makes inferences about individuals based on aggregates; age, sex, and racial predictions are lost.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“the International Diabetes Federation database contains diabetes prevalence data based on multiple surveys of varying quality; as many diabetics go undiagnosed, these are likely underestimates, and do not distinguish between Type 1 (approximately 10%) and Type 2 diabetes (90%)”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“as with all cross-country analyses, the potential exists for ecological fallacies.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Strength:hedged· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the sugar-diabetes relationship appeared to meet criteria for temporal causality without being the result of selection biases or the effect of secular trends that may be artifacts of economic development or changes in surveillance.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“our analysis cannot distinguish between any specific added sugars, such as HFCS or sucrose, or between any specific vehicle, such as soda or processed food.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In other countries, supply and consumption are more closely aligned [41], and differential wastage among foodstuffs does not appear to occur [42].”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
What the sources say
- Not checked yetcites [41] Gustavsson J, Cederberg C, Sonesson U, van Otterdijk R, Meybeck A (2011) Global food losses and food waste. Rome: Food and Agriculture Organization.
- Not checked yetcites [42] Muth MK, Karns SA, Nielsen SJ, Buzby JC, Wells HF (2011) Consumer-level food loss estimates and their use in the ERS loss-adjusted food availability data. Washngton, D.C.: U.S. Dept. of Agriculture.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“these data are known to be highly imperfect.”
§ The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data > Discussion
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
The paper relies on this without support.
Food supply data on market availability accurately reflect population-level sugar intake or consumption.
“We used United Nations Food and Agricultural Organization food supply data [26] to capture market availability of different food items (sugars, fibers, fruits, meats, cereals, oils, and total food) in kilocalories per person per day in each country for each year of the analysis.”
The paper relies on this without support.
International Diabetes Federation diabetes prevalence estimates are valid and comparable across countries and years.
“The dependent variables in the analysis were International Diabetes Federation estimates of diabetes prevalence among persons aged 20 to 79 years old from 2000 through 2010 [6].”
The paper relies on this without support.
No direct measures of actual human consumption that account for food wastage and provide precise measures of food consumption internationally exist.
“as there are no direct measures of actual human consumption that can account for food wastage and provide precise measures of food consumption internationally.”
Claims other papers make about this one
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“In the 1985 to 2005 period extensive added sugar intake occurred across HIC (55) but more recently large increases have occurred in LMIC, particularly in consumption of sugar-sweetened beverages and processed foods (56–59).”
From Food Consumption and its Impact on Cardiovascular Disease: Importance of Solutions Focused on the Globalized Food System (2015) · cites this paper as [56]
Citations
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“First, a Hausman test [28] was performed to test whether factors that differ across countries such as the differing strength of diabetes surveillance systems would systematically affect our results, ensuring the available data were suitable to answer our research questions.”
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“Nearly 1 in 10 adults worldwide are now affected by diabetes [1].”
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“Lastly, a high prevalence of smoking and heavy alcohol use have been associated with diabetes [5].”
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“About 20% of obese individuals appear to have normal insulin regulation and normal metabolic indices (no indication of diabetes) and normal longevity [8], while up to 40% of normal weight people in some populations manifest aspects of the ‘‘metabolic syndrome’’ [9–12].”
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“05), consistent with the notion that economic development is a powerful correlate to diabetes prevalence [35,36].”
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“…parameters identified in the literature as risk factors for diet-related non-communicable diseases with worrying prevalence in the population, such as obesity, diabetes, hypertension and cardiovascular diseases (Boniface and Tefft 2002; Basu et al. 2013; Romieu et al. 2017; Wang et al. 2020).”
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“Second, sugar consumption is strongly linked to the development of obesity and a number of diseases associated with metabolic syndrome (Basu et al. 2013; Castro 2016; Lustig 2009b, 2010, 2016; Malhotra 2013; Nguyen and Lustig 2010; Ivancic 2018).”
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“Although this message has been reverberating for some time now, it gained additional momentum with the publication in February 2013 of an ecological study linking increasing availability of dietary sugar to an increasing prevalence of diabetes (7).”
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“These are two health conditions commonly linked to excessive sugar consumption (Yudkin, 1988; Basu et al., 2013; Lustig et al, 2012; Lustig, 2013).”
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“Ecological data support an association (not necessarily causal) between average sugar use and diabetes prevalence [6], but the relationship is potentially confounded by more frequent overweight and obesity in countries with more diabetes: attempting to correct this for average BMI will not remove the influence of fatn…”
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“The main cause for this increase is linked to population growth, financial development, and expanding urbanization that result in a greater degree of sedentary behavior and higher intake of sugar and unhealthy foods associated with obesity [7].”
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“Two recent ecologic studies have linked the rise in fructose availability (either from HFCS or sucrose) to increased prevalence of obesity both in the United States and around the world [14] [15].”
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“Moreover, habitual sugar intake is known to lead to elevated blood glucose levels, increased risk of diabetes, and the accumulation of visceral fat contributing to metabolic syndrome [4], [5], [6].”
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Is there really a link between diabetes and the ingestion of fructose?
Livesey, G. (2013) · Nutrition Bulletin · doi:10.1111/nbu.12045 · Cited by 4
“A recent cross-country ecological study that included data from 136 to 141 countries (the number dependent on the model used to analyse the data) from all continents observed a positive association between sugar availability and the prevalence of type 2 diabetes (Basu et al. 2013).”
BackgroundRippe, J. M. (2014) · American Journal of Lifestyle Medicine · doi:10.1177/1559827613520527 · Cited by 4
“Several recent ecologic studies have suggested an association between sugar consumption and diabetes.(37,38)”
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Harahap, A. S., Herman, R. B., & Yerizel, E. (2015) · Jurnal Kesehatan Andalas · doi:10.25077/jka.v4i1.179 · Cited by 4
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“Increasing sugar consumption is associated with an increased risk of metabolic diseases such as NAFLD and T2D (an increase of ~38 grams of sugar/ day is associated with a 1% increase in T2D prevalence) [20, 47].”
BackgroundFamily physicians’ knowledge, attitudes, and behaviors regarding the weight effects of added sugar
Mackey, C., Plegue, M. A., Deames, M., Kittle, M., Sonneville, K. R., & Chang, T. (2018) · SAGE Open Medicine · doi:10.1177/2050312118801245 · Cited by 4
Clément, K. K., Voko, D.-R. R. B., Carole, K. A., KOUAME, K. B. E.-B., & Koffi-Nevry, R. (2018) · African Journal of Microbiology Research · doi:10.5897/ajmr2018.8951 · Cited by 4
“…of non-alcoholic but very sweet Gnamakoudji could have adverse effects on health and lead to cardiovascular disease (Johnson et al., 2009, Yang et al., 2014), obesity (Sievenpiper et al., 2012; Wang et al., 2013), diabetes (Basu et al., 2013) and dental caries (Moynihan and Kelly, 2014).”
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Hajmir, M. M., Shiraseb, F., Hosseininasab, D., Aali, Y., Hosseini, S., & Mirzaei, K. (2023) · Frontiers in Nutrition · doi:10.3389/fnut.2023.1226162 · Cited by 3
Authorised EU health claims for intense sweeteners and sugar replacers
Shortt, C. (2014) · Elsevier eBooks · doi:10.1533/9780857098481.3.151 · Cited by 4
Alzaid, A., Schlaeger, C., & Hinzmann, R. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0260 · Cited by 3
“In that study, Lustig and his group linked four international databases to determine what food supply predicted the prevalence of diabetes over a decade worldwide.(19) Findings showed diabetes prevalence generally increased from 5.”
BackgroundThe time has come to flag and reduce excess fructose intake
Brinton, E. A. (2016) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2016.08.040 · Cited by 3
The semiconscious choice of food as a potential obesogenity marker
Plaza, P. D., & Alejandra, M. (2016) · Cited by 3
Reframing Global Health Ethics Using Ecological, Indigenous, and Regenerative Lenses
Hathaway, M. D., Poland, B. D., & Mashford‐Pringle, A. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108692137.030 · Cited by 3
Population-Level Approaches to Preventing Type 2 Diabetes Globally
Siegel, K. R., & Albright, A. L. (2021) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2021.05.010 · Cited by 5
Health Equity and the Societal Determinants of Health
Birn, A., Pillay, Y. G., & Holtz, T. H. (2017) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780199392285.003.0007 · Cited by 5
Quality of self-management among diabetes mellitus patient
Sidiq, R., Widdefrita, W., Amos, J., et al. (2021) · International Journal of Public Health Science (IJPHS) · doi:10.11591/ijphs.v10i1.20576 · Cited by 3
“5% (1 out of 11 adults suffer from diabetes mellitus) in the world [1, 2].”
Development Assistance for Health
Zwi, A. B. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108692137.016 · Cited by 3
Ecological Ethics, Planetary Sustainability, and Global Health
Butler, C. D. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108692137.023 · Cited by 4
Markey, O., Lejeune, J., & Lovegrove, J. A. (2013) · Proceedings of The Nutrition Society · doi:10.1017/s0029665113002395 · Cited by 3
Ross, S. M. (2015) · Holistic Nursing Practice · doi:10.1097/hnp.0000000000000080 · Cited by 3
Social movement involvement and healthy diet and activity behaviors among US adults
Emley, E. A., & Musher‐Eizenman, D. R. (2018) · Health Promotion International · doi:10.1093/heapro/day009 · Cited by 3
“, 2007), added sugar has been strongly linked to health outcomes: There is a dose-response relationship between sugar exposure and diabetes prevalence (Basu et al., 2013), and added sugar intake is significantly associated with increased risk for CVD mortality (Yang et al.”
BackgroundCraig, J., Moul, C. C., & Niemesh, G. T. (2019) · Applied Economics · doi:10.1080/00036846.2019.1676875 · Cited by 3
“Basu et al. (2013) provide a meta-analysis documenting links of sugar consumption to diabetes.”
BackgroundSneed, N. M., Patrician, P. A., & Morrison, S. A. (2019) · Nursing Forum · doi:10.1111/nuf.12399 · Cited by 3
Verma, R., Bansal, C., & Jain, T. (2020) · International Journal of Ayurvedic Medicine · doi:10.47552/ijam.v11i2.1418 · Cited by 3
Koep, J. L., BARKER, A. R., Banks, R., Banger, R. R., Lester, A. B., Sansum, K. M., Weston, M. E., & Bond, B. (2021) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2020-0853 · Cited by 3
“, 2018) and frequent SSB consumption in youth is associated with CVD risk factors such as decreased insulin sensitivity (Basu et al., 2013), hypertension (Nguyen et al.”
BackgroundBohm, I. (2016) · DiVA at Umeå University (Umeå University) · Cited by 3
You, W., & Henneberg, M. (2022) · Research Square · doi:10.21203/rs.3.rs-1325952/v1 · Cited by 3
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Tang, C. S., Mars, M., James, J., de Graaf, K. C., & Appleton, K. M. (2021) · Foods · doi:10.3390/foods10061172 · Cited by 3
“Defined as “monosaccharides and disaccharides added to foods and beverages by the manufacturer, cook or consumer, and sugars naturally present in honey, syrups, fruit juices and fruit juice concentrates” [1], free sugar intakes have been positively associated with increased prevalence of dental caries [2], cardiovascu…”
BackgroundAdded Sugars and Health: What Do We Really Know?
Rippe, J. M., & Angelopoulos, T. J. (2016) · Springer eBooks · doi:10.1007/978-3-319-43027-0_20 · Cited by 2
Obesity, Mortality, and the Obesity Paradox
Gutterman, S. (2016) · North American Actuarial Journal · doi:10.1080/10920277.2016.1241183 · Cited by 2
“Basu et al. (2013) conducted a study using cross-sectional data on diabetes and nutritional components of food from 175 countries using United Nations Food and Agricultural food supply data.”
MethodErnährungsempfehlungen beim metabolisch-vaskulären Syndrom
Lechner, K., Erickson, N. T., Lechner, B., & Horn, F. (2018) · Aktuelle Ernährungsmedizin · doi:10.1055/s-0043-124599 · Cited by 2
“Tag/Person aus Zucker zeigt sich, verglichen mit einer isokalorischen Menge anderer Nährstoffe, eine 11-fache Prävalenzzunahme des Diabetes mellitus Typ 2 – diese Effekte sind kalorien- und körpergewichtsunabhängig [31].”
BackgroundNeoliberalism, Power Relations, Ethics, and Global Health
Benatar, S. R., Upshur, R. E. G., & Gill, S. R. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108692137.018 · Cited by 2
Evaluation of Mesoporous TiO2 Layers as Glucose Optical Sensors
de Zárate, D. O., Serna, S., Ponce-Alcántara, S., & García‐Rupérez, J. (2022) · Sensors · doi:10.3390/s22145398 · Cited by 4
“In relation to the food industry, the application of sensors allows the determination of the glucose content of certain products, such as soft drinks, whose intake is one of the leading sources of added sugars in some countries’ diets, and increases the risk of obesity and diabetes [35].”
BackgroundA serious game about Covid-19: design and evaluation study
Bouroumane, F., & Abarkan, M. (2023) · International Journal of Informatics and Communication Technology (IJ-ICT) · doi:10.11591/ijict.v12i3.pp195-204 · Cited by 2
Ibrahem, A. M. A., Omran, A. M. A., Alaithan, D. T., Aldandan, K. A., Al-Shaghab, M. A., Alkhudhayr, A. M., Ramadhan, B. A., Alshehab, S. J., Alkhudhair, M., Alamer, A. A., et al. (2023) · Cureus · doi:10.7759/cureus.50045 · Cited by 2
The use of intralesional epidermal growth factor in the treatment of diabetic foot ulcers
Kurtuluş, B., & Aydın, E. (2023) · Journal of Medicine and Palliative Care · doi:10.47582/jompac.1350351 · Cited by 2
Habib, S., Hamadneh, N. N., Hasan, A., Almamy, A. S. M., & Hamadneh, B. N. (2025) · Healthcare · doi:10.3390/healthcare13101093 · Cited by 2
“Although our study found no direct link between nutritional quality and malnutrition, prior research affirmed its significance in dietary management [43].”
Mwakyoma, T., Graham, C., Hamooya, B. M., et al. (2025) · PLoS ONE · doi:10.1371/journal.pone.0328172 · Cited by 2
Morbid Symptoms, Organic Crises, and Enclosures of the Commons
Gill, S. R., Bakker, I., & Wamsley, D. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108692137.019 · Cited by 2
Hidayat, T., Sugiarto, & Wiboworini, B. (2021) · International Conference on Health and Medical Sciences (AHMS) · doi:10.2991/ahsr.k.210127.016 · Cited by 2
“Type-2 DM is the type of diabetes that has the highest prevalence and continues to increase worldwide [2].”
BackgroundWhat Is the Role of Regulation in the Management and Prevention of Obesity?
Ries, N. M. (2013) · Current Obesity Reports · doi:10.1007/s13679-013-0068-5 · Cited by 2
“28], including hypertension and diabetes [6].”
Sweeteners: Regulatory Aspects
García‐Almeida, J. M., Cornejo-Pareja, I. M., Muñoz‐Garach, A., Gómez‐Pérez, A. M., & Garcı́a-Alemán, J. (2016) · Reference series in phytochemistry · doi:10.1007/978-3-319-26478-3_12-1 · Cited by 3
Confronting Complacency in the Face of Calamity: Mobilizing for the Home Front War against Diabetes
Schillinger, D. (2016) · Journal of Endocrinology and Diabetes · doi:10.15226/2374-6890/3/5/00163 · Cited by 2
“[11]Even in emerging economies, however, DM2 is concentrated in lower socioeconomic groups; sugar exposure, rather than the size of food market economies, explains why urbanization and income have correlated with DM2 rates.[12] We must vehemently counter the argument that unhealthy environments are a necessary byprodu…”
Szwergold, B. S. (2017) · Rejuvenation Research · doi:10.1089/rej.2017.1974 · Cited by 4
In Critique of “In Defense of Sugar”: The Nuance of Whole Foods
DiNicolantonio, J. J., & O’Keefe, J. H. (2018) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2018.07.006 · Cited by 2
Metadata
- Authors
- Basu, S., Yoffe, P., Hills, N., & Lustig, R. H.
- Affiliations
- Stanford University (US)
- University of California, Berkeley (US)
- University of California, San Francisco (US)
- Corresponding author
- Basu, Sanjay
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-02-27
- Volume
- 8
- Issue
- 2
- Pages
- e57873
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3584048
- OpenAlex
- W2014750665
- Cited by
- 435
- References
- 43
- Citations by year
- 2026: 11 · 2025: 10 · 2024: 16 · 2023: 21 · 2022: 29 · 2021: 66 · 2020: 37 · 2019: 31 · 2018: 34 · 2017: 34 · 2016: 48 · 2015: 41 · 2014: 31 · 2013: 23
- FWCI
- 37.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- eScholarship (California Digital Library) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- sugar consumption, type 2 diabetes, diabetes prevalence, sugar availability, soft drink consumption, obesity, dietary exposure, dose-response relationship, cross-national comparison, socioeconomic determinants of health, urbanization, income
- MeSH terms
- Adult, Aged, Energy Intake, Carbohydrates, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Humans, Middle Aged, Obesity, Selection Bias, Prevalence, Models, Econometric, Young Adult
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