Consumption of Soda in the United States Vs Beef .gov
Am J Public Health. 2013 November; 103(11): 2071–2077.
Relationship of Soft Drink Consumption to Global Overweight, Obesity, and Diabetes: A Cross-National Analysis of 75 Countries
Abstract
Objectives. Nosotros estimated the human relationship between soft drink consumption and obesity and diabetes worldwide.
Methods. We used multivariate linear regression to estimate the association between soft drink consumption and overweight, obesity, and diabetes prevalence in 75 countries, decision-making for other foods (cereals, meats, fruits and vegetables, oils, and total calories), income, urbanization, and crumbling. Information were obtained from the Euromonitor Global Market place Information Database, the Earth Wellness Organization, and the International Diabetes Federation. Bottled water consumption, which increased with per-capita income in parallel to soft beverage consumption, served as a natural control group.
Results. Soft drink consumption increased globally from nine.five gallons per person per twelvemonth in 1997 to 11.4 gallons in 2010. A 1% rise in soft beverage consumption was associated with an additional 4.8 overweight adults per 100 (adapted B; 95% confidence interval [CI] = three.1, vi.5), 2.3 obese adults per 100 (95% CI = 1.1, 3.5), and 0.3 adults with diabetes per 100 (95% CI = 0.1, 0.8). These findings remained robust in low- and middle-income countries.
Conclusions. Soft beverage consumption is significantly linked to overweight, obesity, and diabetes worldwide, including in low- and centre-income countries.
Obesity and associated diabetes rates are rising worldwide.1–3 More 1.5 billion people worldwide are now overweight, and at least ane in 20 adults now accept diabetes.2,three Globally, obesity has doubled since 1980, such that most of the world's population at present lives in countries where there are more than deaths attributable to being overweight than to being underweight.three The prevalence of diabetes among adults aged twenty to 79 years rose from 5.v% in 2000 to seven.0% in 2010; sixty% of people with diabetes alive in low- or middle-income countries.ii
These adverse trends are often attributed to changing patterns of nutrition and decreased physical activity, in association with broader socioeconomic changes, such every bit economic development, urbanization, and aging.4 At that place is controversy whether increasing consumption of then-chosen "Western" foods, such as soft drinks and candy foods, is a contributing factor to obesity exterior of the The states and Western Europe.five–seven In the United States, consumption of sugar-sweetened beverages, particularly soft drinks, has been associated with ascent obesity and diabetes.8–11 Sugar-sweetened beverages contain large amounts of refined sugars, conferring a loftier glycemic load while having poor satiating properties, which is believed to contribute to excessive weight gain, the metabolic syndrome, and insulin resistance.12–14
There have been few empirical studies of the role of soft drinks on the epidemiology of obesity and diabetes in low- and eye-income countries.15,sixteen Major increases in soft potable consumption have occurred not only in the United states of america and Western Europe but besides in other countries; three fifths of global consumption now occurs exterior of Western countries. Yet, evidence to examination the hypothesis that such consumption is related to obesity and obesity-related wellness outcomes has been limited for 2 reasons. First, at that place has been a lack of consequent, comparable data on obesity and related health outcomes in low- and eye-income countries; but recently take international efforts been fabricated to systematically gauge body mass index and diabetes prevalence worldwide.2,3 2nd, there has been a lack of data to reflect the bodily consumption of soft drinks in these countries. Although the Nutrient and Agronomical Organization publishes data describing the availability of dissimilar commodities, manufacture data on bodily consumer-level purchasing only recently has go available in a systematically collected, comparable format.17
In this report, we drew upon recently published overweight, obesity, and diabetes prevalence data, and compared these data with new industry data sources to test the hypothesis that soft drink consumption was related to population-level rates of overweight, obesity, and diabetes worldwide.
METHODS
Manufacture data on soft potable sales were obtained from the EuroMonitor Passport Global Market Information Database (2011 edition). These data contained industry records of soft drink sales in 79 countries from 1997 to 2010.17 Information included per capita annual purchases of carbonated soft drinks (excluding bottled still or carbonated water, fruit or vegetable juices, coffee, tea, or sports drinks) in United states of america gallons, including both imported drinks and those manufactured domestically (e.g., franchises of multinational beverage companies).
Comparable age-standardized overweight prevalence data were obtained from the World Health Organisation's Global Database on Body Mass Index (2011 edition),3 reflecting the best available population-representative, survey-based estimates of the percentage of adults aged 20 years and older in each country who had a body mass index (BMI, defined equally weight in kilograms divided by the foursquare of height in meters) of 25 kg/m2or greater. The database similarly included estimates of obesity prevalence (percentage of adults older than 20 years with BMI ≥ thirty kg/mtwo) for 88 countries.3 Diabetes prevalence data for adults aged 20 to 79 years were obtained from the International Diabetes Federation'due south survey-based estimates for 202 countries for 2007, the twelvemonth with the most information and for which the most extensive checking and validation exercises were performed.2,18 Table 1 further describes the data and their summary statistics amid countries in different income groups.
TABLE 1—
Descriptive Statistics of the Study Sample
| Variable | Description | Low– and Centre–Income Countries, No. (Hateful ±SD) | High–Income Countries, No. (Mean ±SD) |
| Soft drink consumption, 1997–2010 | United states gallons of carbonated soft drinks sold in each country by yr, excluding bottled water, fruit or vegetable juices, coffee, tea, or sports drinks, merely including both imported drinks and those manufactured domestically (e.g., through franchising) | 38 (7.2 ±iv.9) | 41 (14.4 ±eight.7) |
| Overweight prevalence (aged≥ twenty y), 2008 | Population–based age–standardized survey estimates of the percent of adults older than 20 y in each land who have a BMI ≥ 25 kg/kii | 34 (38.1 ±20.1) | 48 (52.2 ±12.5) |
| Obesity prevalence (aged≥ 20 y), 2008 | Population–based age–standardized survey estimates of the percent of adults older than 20 y in each land who have a BMI ≥ xxx kg/m2 | 37 (fourteen.4 ±12.6) | 51 (nineteen.7 ±12.ix) |
| Diabetes prevalence (aged 20–79 y), 2007 | Population–based age–standardized survey and interpolated estimates of the percentage of adults aged 20–79 y in each country who meet international criteria for diabetes based on blood glucose testing | 118 (5.nine ±2.vi) | 84 (seven.viii ±iii.3) |
To adjust for potential misreckoning factors in all regressions, nosotros controlled for gross domestic product (Gross domestic product) per capita (expressed in constant 2005 international dollars purchasing power parity for comparability), population crumbling (the percentage of the population older than 65 years), and urbanization (the percent of the population living in urban areas), all from the World Bank Globe Development Indicators Database (2011 edition).19 To farther isolate the consequence of soft drink consumption, we incorporated a series of nutritional controls into all of the regressions. Specifically, we used the food balance sheets from the United Nations Food and Agricultural Organization's FAOSTAT database (2011 edition), for all available food categories, reflecting the market sizes of cereals, fruits and vegetables, meats, oils, and total food overall (expressed in terms of kcal/person/twenty-four hours) for each of the countries in the assay. Every bit a "command group," bottled water consumption (from the EuroMonitor database) was incorporated into all regressions because we did non expect bottled water consumption to relate significantly to weight or diabetes later on adjusting for potentially confounding factors, such as the GDP.
Our analysis proceeded in 2 steps. Start, nosotros assessed global trends and variation in soft drinkable consumption. Second, nosotros evaluated the relationship between soft drink consumption and overweight, obesity, and diabetes prevalence using multivariate linear regression models that included information from multiple countries (cross-national regression). The following linear regression models were specified:
In the preceding equations, i designates each country; OVERWEIGHT, OBESE, and DIABETES refer to the prevalence rates of these 3 conditions (percentage of adults); SODA refers to the gallons per capita per year of soft drink consumption; CEREAL refers to consumption of cereals in kilocalories percapita per day, and the subsequent nutrient-related variables similarly reverberate consumption of fruits and vegetables (FRUITVEG), meats (MEAT), oils (OIL), and overall total calories (TOTAL) in kilocalories per capita per day. ELDER refers to the percentage of the population older than 65 years; Gdp is the gross domestic product per capita; URBAN refers to the percentage of the population living in urban areas; WATER refers to bottled water consumption in gallons per person per yr; and ɛ is the error term. We further assessed the relationships between soft beverage consumption and overweight, obesity, and diabetes using locally weighted regression, which is a nonparametric smoothing technique using the Stata lowess command (StataCorp, College Station, TX; Figure i).
Relationship of soft drink consumption to the prevalence of (a) overweight amidst adults older than 20 years, (b) obesity among adults older than twenty years, and (c) diabetes amidst adults anile 20–79 years.
Notation. The curves on the graphs are the product of a robust locally weighted nonparametric regression describing the smoothed relationship between the x- and y-axis variables. The locally weighted regression is performed with the Stata lowess algorithm in which bandwidth*N observations are used to summate a smoothed value for each point in the curve; the default bandwidth is 0.8 and n = 79 countries. Consumption is the almanac boilerplate from 1997 to 2007 to reflect both the lagged and cumulative impact of consumption on body mass and diabetes. Y-axis variables are unadjusted in these figures. Bandwidth = 0.8.
We computed the average of almanac soft beverage consumption per capita from 1997 to 2007 in each country to capture that overweight and diabetes risks were related to sustained exposures to unhealthy foods (i.eastward., a cumulative and lagged event, not an instantaneous one).8 We similarly calculated the average annual consumption of other foods over the same period to capture their lagged and cumulative exposure effects. Regressions were weighted by state population. Log transformations were performed on skewed variables, and robust standard errors were calculated for all models.xx Statistics were calculated in StataSE version 10.1 (StataCorp.).
RESULTS
Soft drink consumption averaged x.vii The states gallons per capita per yr from 1997 to 2010 (SD vii.6) in the 79 countries for which data were bachelor. Average consumption worldwide increased from 9.5 gallons per person per year in 1997 to 11.4 gallons per person per year in 2010 (Figure 2a). An estimated 54% of soft potable consumption occurred in depression- and middle-income countries from 1997 to 2010. The average consumption in these countries increased from 6.six gallons per person in 1997 to 7.8 gallons in 2010. The increase of soft drinkable consumption in low- and center-income countries from 1997 to 2010 (ratio 7.viii:half-dozen.six gallons = ane.19) was higher than the increase in high-income countries (ratio 14.8:14.4 gallons = 1.03; P < .05 by paired t-test), indicating a difference in fourth dimension trends in soft drink consumption among countries at different levels of income.
Soft drink consumption in The states gallons per capita per year worldwide (a) over time and (b) vs GDP for the year 2010.
Note. GDP = gross domestic product; PPP = purchasing power parity. Gross domestic product per capita is expressed in 2005 international dollars PPP for comparability between countries. Bandwidth = 0.eight.
Soft beverage consumption generally increased with income (Figure 2b). On average, a x-times increase in per capita Gross domestic product was associated with a 5.1-times increase in the annual number of gallons of soft drinks consumed per person (95% CI = 3.viii, 6.4; estimated past linear regression of GDP on soft drink consumption). Equally shown in Figure 2b, nonetheless, at that place was great variability amidst countries in how much soft drink consumption occurred at dissimilar levels of per capita Gross domestic product, with college variation at higher income levels. The highest consumption among all countries from 1997 to 2010 was observed in the The states in the year 1998 (37.8 gallons per capita), after which consumption in the United States decreased to 31.two gallons per capita in 2010. This was followed by Mexico, where 31.7 gallons of soft drinks per person were consumed in 2007, decreasing but to 31.five gallons in 2010 (higher than in the United States that yr). Among all countries in 2010, Mexico's rate of consumption was followed by the Usa, then Argentina (30.6 gallons per capita per yr), Republic of chile (28.8 gallons), and the United Arab Emirates (27.three gallons). Among low- and middle-income countries (those with Gross domestic product per capita less than $12 275, which Mexico exceeds), Venezuela led the listing of consumers (at xviii gallons per capita per year), followed past Serbia (16.7 gallons), Brazil (16.v gallons), Guatemala (xvi.0 gallons), and the Dominican Republic (14.eight gallons).
Several neighboring countries with otherwise similar economic, social, and cultural characteristics had vastly dissimilar soft drink consumption profiles and correspondingly divergent rates of obesity. For example, although Bulgarians drank 9.5 gallons per person per year on average betwixt 1997 and 2007 and exhibited a 12.4% prevalence of adult obesity in 2008, neighboring Serbians drank an average of xiv.3 gallons and had a 17.four% prevalence of obesity. Indonesians drank 0.six gallons and had a 2.four% obesity rate, whereas Thais drank 4.2 gallons and had a 7.8% obesity rate. Italians drank 8.2 gallons and had a nine.8% obesity rate, whereas Spaniards drank xix gallons and had a 15.6% obesity rate. Peruvians drank 10.viii gallons and had a 16.iii% obesity rate, whereas neighboring Chileans drank 25.4 gallons and had a 21.ix% obesity rate.
Soft Potable Consumption and Overweight and Obesity Prevalence
Every bit shown in Figure 1a and 1b, soft drink consumption was strongly and positively correlated with the prevalence of overweight (BMI ≥ 25 kg/k2; unadjusted r = 0.62; P < .001) and obese adults (BMI ≥ thirty kg/m2; unadjusted r = 0.55; P < .001). An inflection bespeak was observed in the dose-response relationship between soft beverage consumption and overweight and obesity prevalence, such that the rate of increase in overweight and obesity prevalence was greater at lower levels of soft drinkable consumption than at higher levels. At levels of annual consumption of less than vi gallons per person per twelvemonth, each 1 gallon increase in per capita annual soft potable consumption related to v more overweight adults per 100 among all nations (and 8 more per 100 among low- and heart-income nations) and 1 more obese adult per 100 among all nations (4 more per 100 among low- and middle-income nations). At levels of almanac consumption of more than than 6 gallons per person per year, each 1 gallon increase in per capita almanac soft drink consumption related to 0.5 more overweight adults per 100 among all nations (and 0.4 more per 100 among low- and middle-income nations) and 0.six more obese adults per 100 among all nations (0.i more per 100 among low- and middle-income nations). However, when tested using parametric piecewise linear regression (data available equally a supplement to the online version of this article at http://www.ajph.org) rather than nonparametric locally weighted regression, these changes in the effect size of soft drinks with consumption level were not meaning. Within the global sample, the 25th percentile of soft drink consumption (v.9 gallons per person per twelvemonth) corresponded to a 38% overweight and a 12% obesity prevalence, whereas the 75th percentile of consumption (16 gallons per person per year) corresponded to a 50% overweight and a 17% obesity prevalence.
Tabular array 2 presents the results of our multivariate statistical models that examined the effect of soft potable consumption on overweight and obesity prevalence. We plant that each one% rise in soft drink consumption was significantly associated with an additional 4.8 per 100 adults existence overweight (95% CI = 3.1, 6.5), afterward correcting for potential confounders, including Gross domestic product per capita, crumbling, urbanization, other food products, and total calories. No pregnant divergence in the magnitude of association was observed among low- and eye-income countries compared with high-income countries. When analyzing only the subset of countries that were depression- and middle-income, a 1% rise in soft beverage consumption was related to an additional 3.4 cases of overweight per 100 adults (95% CI = 0.6, half dozen.3) when decision-making for the same confounders.
TABLE ii—
Associations betwixt Soft Drink Consumption and Overweight, Obesity, and Diabetes Prevalence
| Overweight Prevalence (BMI > 25 kg/m2) | Obesity Prevalence (BMI > 30 kg/one thousand2) | Diabetes Prevalence | ||||
| Determinant | Low– and Middle–Income Countries, B (95% CI) | All Countries, B (95% CI) | Low– and Eye–Income Countries, B (95% CI) | All Countries, B (95% CI) | Low– and Middle–Income Countries, B (95% CI) | All Countries, B (95% CI) |
| Soft drinks | 0.034* (0.006, 0.063) | 0.048*** (0.031, 0.065) | 0.023* (0.002, 0.044) | 0.023*** (0.011, 0.035) | 0.0050* (0.0001, 0.0090) | 0.003* (0.001, 0.008) |
| Fruits and vegetables | 0.00002 (–0.00176, 0.00181) | 0.00002 (–0.00176, 0.00181) | 0.00002 (–0.00176, 0.00181) | 0.00002 (–0.00176, 0.00181) | 0.000005 (–0.00013, 0.00014) | 0.00006 (–0.00005, 0.00017) |
| Cereals | −0.019 (−0.074, 0.037) | −0.004 (−0.020, 0.012) | 0.005 (−0.020, 0.029) | 0.002 (−0.008, 0.011) | 0.000 (−0.004, 0.004) | 0.001 (−0.002, 0.004) |
| Meats | −0.060 (−0.140, 0.015) | −0.021 (−0.049, 0.007) | −0.014 (−0.048, 0.021) | −0.005 (−0.023, 0.012) | −0.008* (−0.015, −0.002) | −0.008*** (−0.013, −0.004) |
| Oils | −0.079 (−0.210, 0.052) | −0.012 (−0.043, 0.019) | −0.008 (−0.062, 0.047) | −0.004 (−0.020, 0.013) | −0.003 (−0.013, 0.007) | −0.007* (−0.013, −0.001) |
| Total calories | 0.037 (−0.052, 0.130) | 0.015 (−0.003, 0.034) | 0.003 (−0.031, 0.037) | 0.005 (−0.005, 0.014) | 0.002 (−0.002, 0.006) | 0.001 (−0.001, 0.004) |
| Age (% of population ≥ 65 y) | 0.280 (–1.238,1.798) | 0.280 (–1.238, 1.798) | 0.280 (–1.238, 1.798) | 0.280 (–1.238, 1.798) | 0.0879 (–0.0740, 0.250) | –0.176 (–0.357, 0.0053) |
| Gross domestic product per capita | 0.0014 (–0.0019, 0.0047) | 0.0014 (–0.0019, 0.0047) | 0.0014 (–0.0019, 0.0047) | 0.0014 (–0.0019, 0.0047) | 0.00003 (–0.00023, 0.00029) | 0.00007 (–0.00003, 0.00018) |
| Urban population (% of total population) | –0.0334 (–0.532,0.465) | –0.0334 (–0.532,0.465) | –0.0334 (–0.532,0.465) | –0.0334 (–0.532, 0.465) | –0.0292 (–0.0900, 0.0316) | –0.0004 (–0.0534, 0.0525) |
| Bottled water | –0.322 (–5.628, 4.984) | –0.322 (–v.628, four.984) | –0.322 (–5.628, 4.984) | –0.322 (–5.628, 4.984) | –0.205 (–ane.140, 0.730) | 0.878 (–0.0275, 1.728) |
| Countries, no. | 21 | 54 | 22 | 58 | 37 | 75 |
| R 2 | 0.810 | 0.675 | 0.580 | 0.498 | 0.364 | 0.413 |
Similarly, nosotros found that a 1% rising in soft drink consumption was significantly associated with an boosted 2.3 cases of obesity per 100 adults, subsequently controlling for other foods (including total calories and bottled h2o), GDP per capita, urbanization, and crumbling (Table ii; 95% CI = 1.5, 4.4). Again, at that place was no pregnant deviation across country income levels of the estimated effect size.
Soft Drink Consumption and Diabetes Prevalence
For diabetes prevalence, we found that the observed relationships between soft potable consumption and diabetes prevalence among low- and middle-income countries paralleled those between soft drink consumption and overweight and obesity prevalence. As shown in Figure 1c, there was a like inflection signal in the locally weighted regression curve between annual soft potable consumption and diabetes prevalence subsequently about 6 gallons per person of consumption. Each gallon increase in per capita consumption corresponded to an additional 0.5 cases of diabetes per 100 adults aged 20 to 79 years in low- and middle-income countries (data bachelor every bit a supplement to the online version of this article at http://www.ajph.org), but the bend among all countries was less pronounced (Effigy 1c), suggesting that the association of soft drink consumption with diabetes prevalence among wealthier countries was less clear than among poorer ones (although this was nonetheless in a generally upward direction).
In the multivariate regression analysis, each 1% increase in soft drinkable consumption was significantly associated with a rise in diabetes prevalence by 0.five cases per 100 adults among the 37 low- and middle-income countries for which data were available, later controlling for other foods (including full calories), Gross domestic product per capita, urbanization, and aging (Table 2; 95% CI = 0.01, 0.9). A ane% rise in soft drink consumption was likewise significantly correlated with an boosted 0.3 cases per 100 adults among the overall country dataset of 75 countries afterwards the controls were incorporated (95% CI = 0.1, 0.viii).
Robustness Checks and Sensitivity Analyses
We assessed whether there were differences in the regression results from low- and middle-income countries, or from low- and center-income countries combined and loftier-income countries, and did not observe substantial differences between the two land groups in the regressions (P > .05 when testing issue heterogeneity). We ran an interaction specification, in which a country dummy was used to stand for only low-income countries, and then only low- and center-income countries, and in which the dummy variable interacted with soft drink consumption. We establish that the coefficient on this term was always nonsignificant and near zippo, suggesting no statistical bear witness for significant heterogeneity in the human relationship of soft drink consumption with overweight and obesity and diabetes betwixt country income groups.
Bottled h2o consumption increased in parallel to soft drink consumption over time (from an average of v.7 gallons per capita in 1997 to 11.3 in 2010) and rose 4.3-times with each 10-times increase in Gross domestic product (95% CI = 2.7, 5.9), exhibiting a similarly scattered distribution of consumption among countries of different income levels as soft drink consumption (run into data available as a supplement to the online version of this article at http://www.ajph.org). No significant relationship, however, was observed between bottled water consumption and overweight, obesity, or diabetes prevalence (Tabular array 2 and information available as a supplement to the online version of this article at http://www.ajph.org).
To test the assertion that soft drink consumption might pose greater risks of obesity and diabetes amongst women than among men for unclear reasons,21,22 we disaggregated the statistical models by gender. Several countries had estimates among women rather than among all adults (i.east., nine boosted countries' information were available for overweight and obese female person prevalence only than for prevalence among all adults). None of the results was qualitatively inverse, nor was meaning heterogeneity of upshot observed past gender (P > .05 in effect heterogeneity test), but the association between soft drinkable consumption and obesity and overweight prevalence among men in the subset of low- and middle-income countries barbarous from significance because of low statistical power (see data bachelor as a supplement to the online version of this commodity at http://www.ajph.org).
DISCUSSION
Our study analyzed the relationship between soft drink consumption and prevalence of overweight, obesity, and diabetes. Nosotros found that soft drink consumption was significantly associated with population-level rates of overweight, obesity, and associated diabetes worldwide, including in low- and middle-income countries.
Industry analysts propose that soft drink consumption is expected to rise by fifteen.seven% over the adjacent five years in depression- and middle-income countries and 9.5% worldwide.17 To put the magnitude of the associations nosotros institute into perspective, this projected rise in soft drink consumption would stand for to an additional 2.3 billion adults who are overweight, 1.i billion adults who are obese, and 192 one thousand thousand new cases of diabetes worldwide over the adjacent v years, with at least lx% of the burden falling on low- and center-income countries.
Study Limitations
Our analysis, still, had several caveats. First, the available manufacture data on soft potable consumption included all carbonated soft drinks. This class of soft drinks might include some "diet" sodas that might have lower calories and a lower glycemic index than regular soft drinks. Although diet drinks are less commonly available and more expensive than their sugar-sweetened counterparts in well-nigh countries,17 their presence would dilute the association between soft drink consumption and health outcomes, making our results conservative. Second, the soft drinkable consumption dataset did non include fruit drinks that were independently related to the risk of diabetes, likely because of their loftier sugar content.14,23 3rd, soft drink consumption data were industry estimates based on consumer purchasing, and some soft drinkable purchases might not upshot in full consumption (as a outcome of wastage), potentially overestimating consumption levels in some areas. Related to this issue, the soft drinkable data included consumption among children, whereas the overweight and obesity and diabetes information were only on adults; this would tend to understate the bear upon of soft drink consumption on the health outcomes. Of annotation, the industry sources used in this analysis provided higher estimates of soft beverage consumption than self-reported data used in other analyses,24 potentially reflecting the underestimation of individuals in their degree of consumption or wastage betwixt purchased products and consumed products. Similarly, the Food and Agronomical Organization data reflecting other food sources corresponded to the market place availability of these food types rather than recorded consumption. This would tend to overestimate the consumption of other foods, leading us to make conservative estimates of the impact of soft drinkable consumption. Fourth, we used diabetes prevalence data that were estimated from bachelor surveys, merely in several countries such survey data were incomplete, and therefore, were interpolated, particularly amid sub-Saharan African nations. These information besides reflected total diabetes rates as disaggregated rates for only blazon ii diabetes (thought to be obesity-related) and were unavailable; however, it was widely agreed upon that more than 90% of these diabetes cases were type 2 diabetes.2 Similarly, information on the distribution of BMI and the relationship betwixt individual-level BMI and soft drink consumption remained unavailable and would be an of import area for further research to reduce the likelihood of the ecological fallacy (i.e., to test whether those consuming the most soft drinks are in fact those with the highest BMI). Console information analysis (longitudinal fourth dimension-series analysis) should be performed to verify our results once comparable long-term information on weight and diabetes become available and once it is physiologically clear what the time delay is between consumption and weight change or development of diabetes.
As with whatever observational study, clan did not necessarily indicate causation, and using population-level data offered the potential for ecological fallacies. Nevertheless, we observed a consistent and strong clan betwixt soft beverage consumption and cross-sectional overweight, obesity, and diabetes prevalence, even later correcting for other types of foods available on the market and for plausible controls, including income, urbanization, and aging. Equally a farther indicator of specificity, nosotros did not find an consequence of bottled water consumption on overweight, obesity, or diabetes prevalence, suggesting that the observed furnishings were probable non the result of other unobserved lifestyle changes associated with economic growth as well the metabolic and nutritional effects of soft drinks themselves.
Our written report has important implications for future research. There is a clear need to meliorate understand the marked variations in population-wide consumption of soft drinks. Several countries, peculiarly Mexico, Argentina, and Republic of chile, experienced much higher consumption of soft drinks for their levels of GDP per capita than others, such as Singapore, Korea, and Malaysia. Furthermore, the observation that countries with high levels of Gdp had widely varying levels of soft beverage consumption, with some having less than a gallon per person per year of average consumption, suggests that higher soft drinkable consumption is not an inevitable result of economic growth.
It will be important to identify what strategies maintained a lower level of soft drink consumption in some loftier-income nations; such strategies might help preclude the further rise of obesity and diabetes in low- and heart-income nations. Although individual-level analyses and controlled trials are useful in investigating detailed mechanisms relating food consumption to obesity and diabetes, the reward of an ecological study such as this one was that past comparison many countries, we could investigate population-wide factors that might accept had the greatest potential to contribute to illness. These strategies might be particularly of import as countries' markets become more than integrated into the international economic system, a process that is expected to increase the probability of importing soft drinks and developing franchise arrangements with large multinational soft drink manufacturers and distributors.
Conclusions
Overall, our study indicated that soft potable consumption was significantly associated with obesity and diabetes prevalence worldwide, fifty-fifty in low- and middle-income countries. Thus, the continued rise of soft drink consumption poses a global public wellness risk of worsening obesity and diabetes.
Acknowledgments
No specific sources of funding were provided for this enquiry.
Human being Participant Protection
Human being participant protection was not required because no human participants were directly involved in this research.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828681/
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