| Literature DB >> 30612591 |
Joseph Alvin Santos1, Briar McKenzie1, Kathy Trieu1, Sara Farnbach1, Claire Johnson1, Jimaima Schultz2, Anne Marie Thow3, Wendy Snowdon4, Colin Bell4, Jacqui Webster1.
Abstract
OBJECTIVE: Pacific Island countries are experiencing a high burden of diet-related non-communicable diseases; and consumption of fat, sugar and salt are important modifiable risk factors contributing to this. The present study systematically reviewed and summarized available literature on dietary intakes of fat, sugar and salt in the Pacific Islands.Entities:
Keywords: Fat intake; Pacific Island countries; Salt intake; Sugar intake
Mesh:
Substances:
Year: 2019 PMID: 30612591 PMCID: PMC6670018 DOI: 10.1017/S1368980018003609
Source DB: PubMed Journal: Public Health Nutr ISSN: 1368-9800 Impact factor: 4.022
Fig. 1Flowchart of studies included in the present systematic review on the contribution of fat, sugar and salt to diets in the Pacific Islands
Dietary study characteristics and reported data on fat, sugar and salt intake
| Reported data on intake | ||||||
|---|---|---|---|---|---|---|
| Study, country | Description, study design | Sample characteristics | Dietary assessment method | Fat | Sugar | Salt |
| Dela Cruz and Cash (2016)(
| Hybrid NCD and risk factor household survey Cross-sectional | Household survey; adults aged 18 years or above; | NCD risk factor questionnaire | BE | BE | |
| Statistics Office (2007)(
| Household Expenditure Survey Cross-sectional | 773 households from three regions in Cook Islands | Two-week food diary and expenditure | EX | EX | |
| Statistics Division (2014)(
| HIES Cross-sectional | 1988 households | Two-week food diary and expenditure | EX | EX | |
| Hanson | Nutrition intervention Pre–post intervention study | One adult from each household; seventy-five households at baseline and sixty-eight at follow-up | 7d Helen Keller International FFQ | BE | BE | BE |
| Kaufer | Food-based intervention Pre–post intervention study | One adult woman from each household; forty households within a Pohnpeian community | 7d FFQ; two non-consecutive 24H-FR and an attitudes questionnaire | AI, PC, BE | BE | |
| Fiji National Nutrition Survey 2017 (unpublished results) Fiji | National Nutrition Survey Cross-sectional | 3220 adults | 24H-FR | AI, MS | AI, MS | |
| Pillay | Salt reduction intervention Pre–post intervention study | Adults aged 25–64 years; | 24H-UNa | AI | ||
| Leon-Guerrero | Validity and reliability study Cross-sectional | Adults aged 18–61 years; | Quantitative FFQ validated by 2d food record | AI | AI | |
| Paulino | Comparative study of intake between feast and non-feast days Cross-sectional | Women aged 40 years and above living in Guam; | 24H-FR of a previous feast day and a non-feast day | PC | AI | |
| Bureau of Statistics (2014)(
| HIES Cross-sectional | 515 households | Two-week food diary and expenditure | EX | EX | |
| Baudchon (2009)(
| Household Consumption Survey Cross-sectional | 3704 households | Record of expenses and resources of households | EX | EX | |
| Office of Planning and Statistics (2014)(
| HIES Cross-sectional | 1145 households | Two-week food diary and expenditure | EX | EX | |
| Temple | Salt iodization and consumption survey Cross-sectional | 150 households in Moresby North East and Moresby South | Salt weighing | AI | ||
| Trieu | Salt reduction intervention Pre–post intervention study | Adults aged 18–64 years; | 24H-UNa | AI | ||
| Martyn | Identification of household factors associated with nutrition Modelling | Data from HIES: 16 356 individuals and 2791 households | Data on household food expenditure from HIES | AV, MS | PC | AV, MS |
| Webster | Assessment of salt intake Cross-sectional | 293 individuals aged 18–64 years | 24H-UNa and behaviours questionnaire | AI, BE | ||
| Samoa Bureau of Statistics (2016)(
| HIES Cross-sectional | 2348 households | Two-week food diary and expenditure | EX | EX | |
| Land | Assessment of salt intake and iodine status Cross-sectional | 119 women aged 18–45 years | 24H-UNa | AI | ||
| Seiden | Trends in food availability and pricing Secondary analysis of data | National-level data | Data from annual food balance sheets | AV, MS | ||
| Tsuchiya | Assessment of factors associated with obesity Case–control | Fifty-seven controls aged 20 years or above | 24H-FR | AI, PC, BE | ||
| Solomon Islands National Statistics Office (2015)(
| HIES Cross-sectional | 4479 households | Two-week food diary and expenditure | EX | EX | |
| Aswani and Furusawa (2007)(
| Comparative study between marine protected areas and not Cross-sectional | Twenty households from six villages; participants aged 15 years or above | 24H-FR | AI | ||
| Konishi | Assessment of nutrient intake and food sources Cross-sectional | Thirty-four adults aged 40–59 years | Two seven-consecutive-day 24H-FR in two different seasons; food weighing | AI, MS, PC | ||
| Statistics Department (2010)(
| HIES Cross-sectional | 1983 households | Two-week food diary and expenditure | EX | EX | |
| Central Statistics Division (2010)(
| HIES Cross-sectional | 541 households | Two-week food diary and expenditure | EX | EX | |
| Vanuatu Ministry of Health 2017 (unpublished results) Vanuatu | Assessment of salt intake Cross-sectional | Adults aged 18–69 years; | Spot urine sample and behaviours questionnaire | AI, BE | ||
| Martyn | Identification of household factors associated with nutrition Modelling | Data from HIES: 3975 households from thirty islands | Data on household food expenditure from HIES | AI, MS | EX, PC | AI, MS |
| Vanuatu National Statistics Office (2012)(
| HIES Cross-sectional | 3975 households | Two-week food diary and expenditure | EX | EX | EX |
| Estime | Examination of links between trade and NCD Secondary analysis of data | Data from five countries: Samoa, | Secondary analysis of household-level food expenditure and consumption data | EX, PC | ||
| Micha | Estimation of global, regional and national dietary fat intake Modelling | Data from 266 surveys in adults from 113 countries | Data from previous surveys: Bayesian hierarchical modelling | PC | ||
| Powles | Estimation of global, regional and national salt intake Modelling | Data from 142 surveys of 24 h urinary Na and 103 dietary Na from sixty-six countries | Data from previous surveys; Bayesian hierarchical modelling | AI | ||
CNMI, Commonwealth of the Northern Mariana Islands; FSM, Federated States of Micronesia; PNG, Papua New Guinea; NCD, non-communicable disease; HIES, Household Income and Expenditure Survey; 24H-FR, 24 h food recall; 24H-UNa, 24 h urine collection; EX, household expenditure; BE, dietary behaviour; AI, absolute intake; PC, percentage contribution to energy intake; MS, main sources; AV, availability.
Only estimates for the control group were included.
Fig. 2Summary of quality assessment (H, high quality; U, unclear quality; L, low quality; blank, not applicable) of studies included in the present systematic review on the contribution of fat, sugar and salt to diets in the Pacific Islands (note, quality assessment of two unpublished results was not completed: Fiji National Nutrition Survey 2017 and Vanuatu Ministry of Health 2017). *Refers to involvement during conception, design, conduct of research, including pre-testing and data collection, and distribution of results. †Assessed based on the appropriateness of the food composition database used to analyse the data, and whether a second person checked the linking of foods to the food composition table (FSM, Federated States of Micronesia)
Fat intake by type of outcome reported and country
| Type of intake data | Countries with data | Description of intake |
|---|---|---|
| Absolute intake | FSM | Kaufer, 2010 (24H-FR; adult women): 2005 (pre-intervention) 61·3 g/d; 2007 (post-intervention) 62·6 g/d |
| Fiji | National Nutrition Survey, 2017 (24H-FR; adults): 97·1 (95 % CI 96·0, 98·2) g/d | |
| Guam | Leon-Guerrero, 2015 (FFQ; adults aged 18–61 years): total fat 98·9 ( | |
| Solomon Islands | Tsuchiya, 2017 (24H-FR; controls aged ≥20 years): 25·4 ( | |
| Tonga | Konishi, 2011 (24H-FR; adults aged 40–59 years; median intake): males 107·0 g/d; females 88·0 g/d | |
| Vanuatu | Martyn, 2015 (modelling): 75·0 g/d; rural 73·0 g/d; urban 81·0 g/d | |
| Household expenditure | Cook Islands | 2007: 3·4 % |
| FSM | 2014: 0·9 % | |
| Nauru | 2014: 2·0 % | |
| New Caledonia | 2009: 1·5 % | |
| Palau | 2014: 2·0 % | |
| Samoa | 2016: 0·9 % | |
| Solomon Islands | 2015: 0·7 % | |
| Tonga | 2010: 3·1 % | |
| Tuvalu | 2010: 3·2 % | |
| Vanuatu | 2012: 0·01 % | |
| Main sources | Fiji | National Nutrition Survey, 2017 (24H-FR; adults): fish and seafood (fresh, canned, mixed food) 22·3 %, animal-source foods (poultry, mixed food, fresh meat and sausages) 18·8 %, wheat flour products (crackers, roti, instant noodles, sweets) 15·1 %, vegetable fat 8·6 %, coconut products 8·4 %, starchy staples 5·4 % |
| Samoa | Martyn, 2017 (modelling): coconuts (popo) 19·0 %, chicken pieces 13·0 %, canned mackerel 8·0 %, cooking oil 6·0 % Seiden, 2012 (secondary analysis): coconuts and copra, vegetable oils, bovine meat, mutton and goat meat, pig meat, poultry meat | |
| Tonga | Konishi, 2011 (24H-FR; adults aged 40–59 years): imported foods contributed 65 % of total daily fat intake | |
| Vanuatu | Martyn, 2015 (modelling): coconut or copra, cooking oil, peanuts, cabin biscuits, fresh beef, chicken | |
| Percentage contribution to energy | FSM | Micha, 2014 (modelling; saturated fat): 22·9 % Kaufer, 2010 (24H-FR; adult women): 2005 (pre-intervention) 23·3 %; 2007 (post-intervention) 26·2 % |
| Fiji | Micha, 2014 (modelling; saturated fat): 23·8 % | |
| Guam | Paulino, 2011 (24H-FR; women aged ≥40 years): total fat – feast day 34·1 ( | |
| Kiribati | Micha, 2014 (modelling; saturated fat): 27·0 % | |
| PNG | Micha, 2014 (modelling; saturated fat): 23·2 % | |
| RMI | Micha, 2014 (modelling; saturated fat): 22·9 % | |
| Samoa | Micha, 2014 (modelling; saturated fat): 27·5 % | |
| Solomon Islands | Tsuchiya, 2017 (24H-FR; controls aged ≥20 years): 14·5 ( | |
| Tonga | Micha, 2014 (modelling; saturated fat): 22·8 % Konishi, 2011 (24H-FR; adults 40–59 years): males 33·0 ( | |
| Vanuatu | Micha, 2014 (modelling; saturated fat): 25·7 % | |
| Availability | Samoa | Martyn, 2017 (modelling): overall 96 g/d; Apia 101 g/d; Northwest Upolu 87 g/d; Rest of Upolu 99 g/d; Savaii 106 g/d Seiden, 2012 (secondary analysis): total fat availability increased by 73 % from 81 to 139 g/d |
| Behaviours | FSM | Hanson, 2011 (FFQ; adults): frequency of consumption of turkey tails 0·8 d/week; fried foods 2·5 d/week; percentage consuming fried foods (often to daily) 38·0 % Kaufer, 2010 (FFQ; adult women): frequency of consumption of imported animal fat in 2005 2·1 d/week; in 2007 2·4 d/week |
| Solomon Islands | Tsuchiya, 2017 (24H-FR; controls aged ≥20 years): 82·5 % consumed oils and fats daily |
FSM, Federated States of Micronesia; PNG, Papua New Guinea; RMI, Republic of the Marshall Islands; 24H-FR, 24 h food recall.
Values reported as mean total fat intake, unless stated otherwise;
Values reported as percentage contribution of total fat to energy, unless stated otherwise.
Sugar intake by type of outcome reported and by country
| Type of intake data | Countries with data | Description of intake |
|---|---|---|
| Absolute intake | Guam | Paulino, 2011 (24H-FR; women aged ≥40 years; added sugar): feast day 89·5 ( |
| Household expenditure | Cook Islands | 2007: 3·0 % |
| FSM | 2014: 2·1 % | |
| Kiribati | 2014: 13·0 % | |
| Nauru | 2014: 5·5 % | |
| New Caledonia | 2009: 4·7 % | |
| Palau | 2014: 4·0 % | |
| Samoa | 2016: 2·2 % | |
| Solomon Islands | 2015, 2014: 2·6 % | |
| Tonga | 2010: 4·2 % | |
| Tuvalu | 2010: 8·0 % | |
| Vanuatu | 2015, 2012: 1·9 % | |
| Percentage contribution to energy | Kiribati | Estime, 2014 (secondary analysis): 34·0 % |
| Samoa | Martyn, 2017 (modelling; brown sugar): 8·0 % | |
| Solomon Islands | Estime, 2014 (secondary analysis): 2·0 % | |
| Vanuatu | Martyn, 2015 (modelling): 3·6 % Estime, 2014 (secondary analysis): 4·0 % | |
| Behaviours | CNMI | Dela Cruz, 2016 (questionnaire; adults aged ≥18 years): about 75 % of adults drink one or more SSB daily |
| FSM | Hanson, 2011 (FFQ; adults): percentage consuming imported sugar foods (often to daily) 16·0 %; imported drinks with sugar (often to daily) 72·0 % Kaufer, 2010 (FFQ; adult women): frequency of consumption of sugar (imported product or added to local food) in 2005, 3·2 d/week; in 2007, 1·9 d/week |
FSM, Federated States of Micronesia; CNMI, Commonwealth of the Northern Mariana Islands; 24H-FR, 24 h food recall; SSB, sugar-sweetened beverage.
Values reported as percentage contribution of sugar to energy, unless stated otherwise.
Confectionery.
Sugar, jam, honey, chocolate, confectionery.
Sugar alone.
Sugar and confectionery.
Salt intake by type of outcome reported and by country
| Type of intake data | Countries with data | Description of intake |
|---|---|---|
| Absolute intake | FSM | Powles, 2013 (modelling): overall 6·5 g/d; males 6·8 g/d; females 6·2 g/d |
| Fiji | National Nutrition Survey, 2017 (24H-FR; adults): 8·9 g/d Pillay, 2017 (24H-UNa; adults aged 25–64 years): baseline 11·7 ( | |
| Guam | Leon-Guerrero, 2015 (FFQ; adults aged 18–61 years): 10·1 ( | |
| Kiribati | Powles, 2013 (modelling): overall 5·6 g/d; males 5·9 g/d; females 5·4 g/d | |
| PNG | Powles, 2013 (modelling): overall 6·2 g/d; males 6·6 g/d; females 5·9 g/d Temple, 2009 (salt weighing; mean per capita salt consumption): 5·6 ( | |
| RMI | Powles, 2013 (modelling): overall 6·5 g/d; males 6·8 g/d; females 6·2 g/d | |
| Samoa | Trieu, 2017 (24H-UNa; adults aged 18–64 years): baseline 7·3 ( | |
| Solomon Islands | Powles, 2013 (modelling): overall 5·9 g/d; males 6·2 g/d; females 5·6 g/d | |
| Tonga | Powles, 2013 (modelling): overall 6·9 g/d; males 7·3 g/d; females 6·6 g/d | |
| Vanuatu | Ministry of Health, 2017 (spot urine; adults aged 18–64 years): overall 7·2 ( | |
| Household expenditure | Cook Islands | 2007: 0·1 % |
| Vanuatu | 2012: 1·8 % | |
| Main sources | Fiji | National Nutrition Survey, 2017 (24H-FR; adults): wheat flour products (roti, breakfast crackers, bread, homemade flour products) 27·6 %, fish and seafood 16·8 %, animal-source foods 16·2 %, salt 13·7 %, savoury snacks 8·2 % |
| Samoa | Martyn, 2017 (modelling): table salt 39·0 %, instant noodles 9·0 %, canned mackerel 9·0 % | |
| Vanuatu | Martyn, 2015 (modelling): bread contributed 15·4 % of Na available, water taro 7·5 %, cabin biscuits 7·4 %, tinned tuna 7·0 % | |
| Availability | Samoa | Martyn, 2017 (modelling): overall 7·4 g/d; Apia 7·8 g/d; Northwest Upolu 7·3 g/d; Rest of Upolu 7·6 g/d; Savaii 7·0 g/d |
| Behaviours | CNMI | Dela Cruz, 2016 (questionnaire; adults aged ≥18 years): two-thirds consume at least one serving of processed meats daily |
| FSM | Hanson, 2011 (FFQ; adults): frequency of consumption of imported salty foods 0·7 d/week; percentage consuming salty foods (often to daily) 8·0 % | |
| Samoa | Webster, 2016 (questionnaire; adults aged 18–64 years): avoid processed food 58·7 %, look at Na labels on food 42·6 %, do not add salt on the table 43·8 %, buy low-salt alternatives 54·9 %, do not add salt when cooking 49·0 %, use spices other than salt 43·9 %, avoid eating out 60·9 % | |
| Vanuatu | Ministry of Health, 2017 (questionnaire; adults aged18–64 years): avoid processed food 76·6 %, look at Na labels on food 32·1 %, do not add salt on the table 60·7 %, buy low-salt alternatives 69·4 %, do not add salt when cooking 74·2 %, use spices other than salt 61·1 %, avoid eating out 16·2 % |
FSM, Federated States of Micronesia; PNG, Papua New Guinea; RMI, Republic of the Marshall Islands; CNMI, Commonwealth of the Northern Mariana Islands; 24H-FR, 24 h food recall; 24H-UNa, 24 h urine collection.
Values were converted to salt in g/d (393·4 mg sodium=1 g salt).
Most recent fat, sugar and salt intake estimates and dietary assessment method used
| Country | Year | Intake (g/d) | Dietary assessment method | |
|---|---|---|---|---|
| Fat intake | ||||
| FSM | 2005 | 62·6 | 24H-FR | |
| Fiji | 2017 | 97·1 | 95 % CI 96·0, 98·2 | 24H-FR |
| Guam | 2015 | 98·9 |
| FFQ |
| Solomon Islands | 2017 | 25·4 |
| 24H-FR |
| Tonga | 2011 | 107·0 M 88·0 F |
| 24H-FR |
| Vanuatu | 2015 | 75·0 | Dietary modelling | |
| Sugar intake | ||||
| Guam | 2011 | 47·3 |
| 24H-FR |
| Salt intake | ||||
| FSM | 2013 | 6·5 | 95 % CI 5·5, 7·7 | Dietary modelling |
| Fiji | 2017 | 10·3 |
| 24H-UNa |
| Guam | 2015 | 10·1 |
| FFQ |
| Kiribati | 2013 | 5·6 | 95 % CI 4·6, 6·8 | Dietary modelling |
| Papua New Guinea | 2013 | 6·2 | 95 % CI 5·3, 7·3 | Dietary modelling |
| RMI | 2013 | 6·5 | 95 % CI 5·5, 7·7 | Dietary modelling |
| Samoa | 2017 | 7·5 |
| 24H-UNa |
| Solomon Islands | 2013 | 5·9 | 95 % CI 5·0, 7·0 | Dietary modelling |
| Tonga | 2013 | 6·9 | 95 % CI 5·8, 8·1 | Dietary modelling |
| Vanuatu | 2017 | 7·2 |
| Spot urine collection |
FSM, Federated States of Micronesia; RMI, Republic of the Marshall Islands; M, males; F, females; 24H-FR, 24 hour food recall; 24H-UNa, 24 h urine collection.