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Kiritimati is an isolated coral atoll in the Pacific Ocean, and is one of 32 islands that comprise the Republic of Kiribati. Obesity and type 2 diabetes rates are high in Kiribati, but the causes and rates of childhood obesity/diabetes are unknown. However, it has been hypothesized that high consumption of sugar-sweetened beverages on Kiritimati may be a contributing factor. The investigators therefore conducted a study in Kiritimati in September 2018 with the aim of 1) quantifying obesity and diabetes rates amongst children on Kiritimati and 2) testing the feasibility of a sugar-reduction intervention in Kiritimati schools. The investigators randomized the two high schools on the island to either the control group or the intervention group. The investigators measured height/weight, continuous blood glucose (using flash glucose monitoring), and diet (using 24-hour diet recalls). One week into the study, the intervention school received an intervention, which consisted of installation of a water filter at the school, the provision of water bottles to each student at the school, and a 30-minute educational presentation on the link between sugar consumption and type 2 diabetes. The investigators then measured how blood glucose and diet changed the week following the intervention, and compared this to the control school.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control School | No Intervention | This school did not receive intervention (until after the study was completed) | |
| Intervention School | Experimental | This school received a one-week sugar-reduction intervention |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Sugar-reduction intervention | Behavioral | The intervention consisted of a) installation of a water filter at the school. b) each participant received a metal water bottle. c) a registered dietitian gave a 30-minute presentation on sugar reduction for the purposes of type 2 diabetes prevention |
| Measure | Description | Time Frame |
|---|---|---|
| Change in mean blood glucose (mg/dL) | A continuous glucose monitor was attached to all participants, which collected data for 2 weeks. Mean blood glucose was calculated for each participant using GlyCulator, an online tool for analyzing CGM data. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in mean amplitude of glycemic variability (MAGE) (mg/dL) | A continuous glucose monitor was attached to all participants, which collected data for 2 weeks. Glycemic variability (mean amplitude of glycemic excursions) was calculated for each participant using GlyCulator, an online tool for analyzing CGM data. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in standard deviation (mg/dL) of continuous glucose monitor data | A continuous glucose monitor was attached to all participants, which collected data for 2 weeks. Glycemic variability (standard deviation) was calculated for each participant using GlyCulator, an online tool for analyzing CGM data. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in coefficient of variation (percent) of continuous glucose monitor data | A continuous glucose monitor was attached to all participants, which collected data for 2 weeks. Glycemic variability (coefficient of variation (percent) was calculated for each participant using GlyCulator, an online tool for analyzing CGM data. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in J-index of continuous glucose monitor data | A continuous glucose monitor was attached to all participants, which collected data for 2 weeks. Glycemic variability (J-index) was calculated for each participant using GlyCulator, an online tool for analyzing CGM data. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Elizabeth Beale, MD | University of Southern California | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Southern California | Los Angeles | California | 90033 | United States | ||
| Kiritimati |
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| ID | Term |
|---|---|
| D003924 | Diabetes Mellitus, Type 2 |
| D009765 | Obesity |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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|
| 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in area under the curve of continuous glucose monitor data | A continuous glucose monitor was attached to all participants, which collected data for 2 weeks. Glycemic variability (area under the curve) was calculated for each participant using GlyCulator, an online tool for analyzing CGM data. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in total sugar consumption (g/day) using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in total sugar intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in added sugar consumption (g/day) using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in added sugar intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in total water consumption (g/day) using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in total water intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in unsweetened water consumption (servings/day) using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in unsweetened water intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in energy (kcal/day) consumption using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in energy (kcal) intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in total carbohydrate (g/day) consumption using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in total carbohydrate intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in percent calories from carbohydrate consumption using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in % calories from carbohydrate intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in percent calories from total sugars consumption using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in % calories from total sugars intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in percent calories from added sugars consumption using 24-hour dietary recalls | The investigators conducted 24-hour diet recalls and entered data into the NDSR database for comparison of change in % calories from added sugars intake between the control and intervention schools (time x group interaction). | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (tioka) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (tang) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (toddy) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (ice block) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (soda) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (juice) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (fruit drinks) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| Change in sugary beverage (coffee/tea) consumption using beverage frequency questionnaires | The investigators conducted beverage frequency questionnaires which asked about consumption of popular beverages on Kiritimati (specifically: "how many days per week do you typically drink this drink?" and "how much each day?") then compared change pre-and post-intervention between the two groups (time x group interaction) in servings/day. | 2 weeks (1 week pre- and 1 week post-intervention) |
| London |
| Kiribati |
| D004700 | Endocrine System Diseases |
| D050177 | Overweight |
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |