Other topics
Improving vitamin A and D intake among Inuit and Inuvialuit in Arctic Canada: evidence from the Healthy Foods North study Mohammadreza Pakseresht,1 Fariba Kolahdooz,1 Joel Gittelsohn,2 Cindy Roache,1 André Corriveau,3 Sangita Sharma1 1
Department of Medicine, University of Alberta, University Terrace, Edmonton, Alberta, Canada 2 Department of International Health, Center for Human Nutrition, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA 3 Department of Health and Social Services, Government of the Northwest Territories, Centre Square Tower, Yellowknife, Northwest Territories, Canada Correspondence to Dr Sangita Sharma, Department of Medicine, University of Alberta, # 5-10, University Terrace 8303—112 St, Edmonton, Alberta, Canada T6G 2T4; [email protected] Received 3 July 2014 Revised 24 October 2014 Accepted 2 December 2014 Published Online First 19 December 2014
ABSTRACT Background People in Arctic Canada are undergoing a nutritional transition and increased prevalence of chronic disease. The Healthy Foods North diet and physical activity intervention was developed in 2007–2008 while working with populations in six communities in Nunavut and the Northwest Territories, Canada. Methods Four communities received the 1-year intervention (eg, conducting workshops, cooking classes and walking clubs) and two communities served as controls. Among the 263 adult evaluation participants, food frequency questionnaires were used to assess dietary intake at baseline and postintervention. Changes in mean nutrient intakes, nutrient density and dietary adequacy from baseline to postintervention were determined. The intervention impact on nutrient intakes was assessed through multivariate linear regression analysis. Results Post-intervention assessment showed a reductions in total fat, saturated, monounsaturated and polyunsaturated fatty acids, and increases in iron intake, only in the intervention group. More than a 4%-increase in the percentage of adherence to vitamins A and D recommendations was observed in the intervention group. After adjusting the regression models, respondents in the intervention communities significantly reduced their energy intake and increased their vitamins A and D intake. Conclusions The Healthy Foods North is an effective programme to improve dietary quality among populations of the Canadian Arctic. Long-term interventions are expected to be important factors in the prevention of diet-related chronic diseases in these communities.
INTRODUCTION
To cite: Pakseresht M, Kolahdooz F, Gittelsohn J, et al. J Epidemiol Community Health 2015;69:453–459.
Increasing rates of chronic diseases among Aboriginal populations in the Canadian Arctic may be attributable to the ongoing nutritional transition lowering their diet quality.1 2 3 Prior to contact with other societies, commonly consumed foods included locally harvested nutritionally rich products such as land and marine mammals, fish, birds and plants. Greater exposure to non-Aboriginal dietary practices resulted in dramatic dietary transitions, with a study conducted between 2007 and 2008 among Inuit and Inuvialuit populations revealing that people spent twice as much money on non-nutrient-dense foods compared with on traditional foods.4 The role of nutrient rich diets in the prevention of chronic disease has been welldocumented, with the WHO identifying nutrition as a modifiable determinant for disease prevention.5
The growing prevalence of chronic diseases combined with the reduced life-expectancy experienced by Aboriginal populations, particularly in the Northern territories, has contributed to increased costs for the national healthcare system.6 7 The total health expenditure per capita in 2010 for Nunavut (NU) and the Northwest Territories (NT) were $11 811 and $9906, respectively, compared to $5452 on average for Canada.8 Hence, chronic disease prevention programmes emphasising positive changes in diet may be beneficial for Northern Canada’s Aboriginal communities.9 10 The Healthy Foods North (HFN) programme was a culturally appropriate, community-based intervention developed for Inuit and Inuvialuit communities in NU and NT. HFN sought to improve diet through increased intake of essential micronutrients and decreased consumption of nonnutrient dense foods that contribute to high energy and fat intake. Baseline dietary assessments conducted for the programme found widespread inadequacies of micronutrient intakes and increased total energy intakes among adults.11 12 These observations were attributed to a high consumption of micronutrient poor, high-energy dense storebought foods.13 14 HFN’s objectives were to: (1) increase/maintain consumption of traditional and nutrient-dense foods, (2) promote food preparation methods without adding fat, (3) decrease processed food consumption and (4) increase physical activity.15 The objectives of the present study were to determine differences between baseline and postintervention intake of promoted nutrients (eg, vitamins A and D) and depromoted nutrients (eg, fat and sugar) and evaluate the impact of the HFN programme among Inuit and Inuvialuit communities.
METHODS The HFN programme was evaluated through a quasi-experimental study design. The programme was conducted in six communities in NU (n=3) and NT (n=3). Selected communities included diverse proportions of Inuit and Inuvialuit populations of varying socioeconomic backgrounds.16 The intervention was conducted in one semiremote and one remote community in NT between May 2008 and August 2009, and two remote NU communities between October 2008 and November 2009. One remote community each in NU and NT served as controls. Based on themes identified during community participatory research,17 the HFN intervention
Pakseresht M, et al. J Epidemiol Community Health 2015;69:453–459. doi:10.1136/jech-2014-204623
453
Other topics included five phases: (I) 6 months of informative research to understand local concepts and cultural norms regarding healthy foods and food practices; (II) two 2-day workshops with stakeholders to identify foods and behaviours for intervention; (III) intervention refinement over 18 months to review evidence and finalise a list of foods and behaviours for intervention; (IV) 3-day training for trainees, local community health representatives, project coordinators and local store staff and (V) programme implementation and evaluation over 14 months. Some of the activities of the programme included healthy breakfasts, meal planning and cooking, sufficient intake of vitamins and minerals, pedometer challenges and walking clubs. Implementation sites included food stores, health clinics, offices and special community events. Promotional messages were communicated through local community media.15 Data collection has previously been described elsewhere.18 In brief, data collection was administered at baseline and 1 year following intervention. Using community housing maps, households were recruited following random selection of household numbers. This method ensured sampling from areas with varied proximities to food stores and hunting areas. One adult (≥19 years), typically the main food shopper or preparer, was selected to participate from each household, provided they had lived in the community for at least 6 months. Pregnant and breastfeeding women were excluded owing to the differences in their nutritional requirements and possible changes in energy expenditure. Three attempts were made before selecting a new household to substitute for a non-responding household. Written informed consent was obtained from all participants. Baseline response rates ranged between 69–93% and 65–85% in the NU and NT communities, respectively. Individuals selected at baseline from both groups were also interviewed at the end of the intervention. Participants were remunerated with gift cards. Baseline and postintervention data collection was carried out by community health workers, community members and university students, who were trained, evaluated and certified by the principal investigator (SS). Participants’ height and weight were measured in triplicate.18 Weight was adjusted between 1 and 2 kg for light to heavy clothing and recorded to the nearest 0.1 kg using a digital scale. Height was recorded to the nearest centimetre using a stadiometer. When participants declined measurements, self-reported measurements were noted. Culturally appropriate quantitative food frequency questionnaires (QFFQ) previously developed19 20 and validated21 22 for the populations were used to assess dietary intake. The questionnaire collected information on the typical frequency of food and beverage consumption over the past 30-day period classified into eight categories ranging from ‘never’ to ‘2 or more times per day’. Three-dimensional food models (NASCO, Fort Atkinson, Wisconsin, USA), packages of commonly consumed store-bought foods, standard units and local household utensils were used to assist participants’ estimate portion sizes.18 Participants’ socioeconomic status was assessed using a questionnaire collecting information on sociodemographic variables and material style of life (MSL), an additive scale of ownership of 20 items in working condition (Cronbach’s α=0.83).23 All interviewers were trained by the principal investigator (SS) in questionnaire administration and anthropometric measurements to ensure standardisation. For participants whose primary language was not English, either an interviewer fluent in the local language (Inuktitut or Inuinnaqtun) or an interpreter was used to conduct the survey. Interviews were carried out at participants’ homes and the majority were conducted in English. 454
Ethics statement Institutional Review Board approval was obtained from the Committee on Human Studies at the University of Hawaii and the Office of Human Research Ethics at the University of North Carolina at Chapel Hill. Additionally, the Ethics Committee of the Beaufort Delta Health and Social Services Authority approved this project. Aurora Research Institute in the NT and the Nunavut Research Institute in NU provided research licences.
Statistical analysis Data from all six communities were combined for analysis. Baseline differences in the communities’ demographic and socioeconomic variables by intervention assignment were analysed using a Student t test for continuous normally distributed variables and a χ2 test and a one-way analysis of variance for categorical variables. To determine total daily nutrient intake, data from three datasets (food composition table, QFFQ and food items portion weights) were analysed by the Food Frequency Questionnaire Analysis Program in STATA (StataCorp LP, College Station, Texas, USA), programmed by the first author. The programme was also used to extract the main food source of each nutrient and to determine the percentage of contribution of different food items in total daily intake of the nutrient. The mean and SD of daily energy and nutrient intakes were calculated for all participants at baseline and postintervention. As the index of diet quality, nutrient densities per 1000 kcal were calculated by dividing each participant’s daily nutrient intake by their energy intake (kcal), multiplied by 1000. Observations with energy outliers of >5000 kcal were excluded. No participant reported daily energy intake
Improving vitamin A and D intake among Inuit and Inuvialuit in Arctic Canada: evidence from the Healthy Foods North study Mohammadreza Pakseresht,1 Fariba Kolahdooz,1 Joel Gittelsohn,2 Cindy Roache,1 André Corriveau,3 Sangita Sharma1 1
Department of Medicine, University of Alberta, University Terrace, Edmonton, Alberta, Canada 2 Department of International Health, Center for Human Nutrition, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA 3 Department of Health and Social Services, Government of the Northwest Territories, Centre Square Tower, Yellowknife, Northwest Territories, Canada Correspondence to Dr Sangita Sharma, Department of Medicine, University of Alberta, # 5-10, University Terrace 8303—112 St, Edmonton, Alberta, Canada T6G 2T4; [email protected] Received 3 July 2014 Revised 24 October 2014 Accepted 2 December 2014 Published Online First 19 December 2014
ABSTRACT Background People in Arctic Canada are undergoing a nutritional transition and increased prevalence of chronic disease. The Healthy Foods North diet and physical activity intervention was developed in 2007–2008 while working with populations in six communities in Nunavut and the Northwest Territories, Canada. Methods Four communities received the 1-year intervention (eg, conducting workshops, cooking classes and walking clubs) and two communities served as controls. Among the 263 adult evaluation participants, food frequency questionnaires were used to assess dietary intake at baseline and postintervention. Changes in mean nutrient intakes, nutrient density and dietary adequacy from baseline to postintervention were determined. The intervention impact on nutrient intakes was assessed through multivariate linear regression analysis. Results Post-intervention assessment showed a reductions in total fat, saturated, monounsaturated and polyunsaturated fatty acids, and increases in iron intake, only in the intervention group. More than a 4%-increase in the percentage of adherence to vitamins A and D recommendations was observed in the intervention group. After adjusting the regression models, respondents in the intervention communities significantly reduced their energy intake and increased their vitamins A and D intake. Conclusions The Healthy Foods North is an effective programme to improve dietary quality among populations of the Canadian Arctic. Long-term interventions are expected to be important factors in the prevention of diet-related chronic diseases in these communities.
INTRODUCTION
To cite: Pakseresht M, Kolahdooz F, Gittelsohn J, et al. J Epidemiol Community Health 2015;69:453–459.
Increasing rates of chronic diseases among Aboriginal populations in the Canadian Arctic may be attributable to the ongoing nutritional transition lowering their diet quality.1 2 3 Prior to contact with other societies, commonly consumed foods included locally harvested nutritionally rich products such as land and marine mammals, fish, birds and plants. Greater exposure to non-Aboriginal dietary practices resulted in dramatic dietary transitions, with a study conducted between 2007 and 2008 among Inuit and Inuvialuit populations revealing that people spent twice as much money on non-nutrient-dense foods compared with on traditional foods.4 The role of nutrient rich diets in the prevention of chronic disease has been welldocumented, with the WHO identifying nutrition as a modifiable determinant for disease prevention.5
The growing prevalence of chronic diseases combined with the reduced life-expectancy experienced by Aboriginal populations, particularly in the Northern territories, has contributed to increased costs for the national healthcare system.6 7 The total health expenditure per capita in 2010 for Nunavut (NU) and the Northwest Territories (NT) were $11 811 and $9906, respectively, compared to $5452 on average for Canada.8 Hence, chronic disease prevention programmes emphasising positive changes in diet may be beneficial for Northern Canada’s Aboriginal communities.9 10 The Healthy Foods North (HFN) programme was a culturally appropriate, community-based intervention developed for Inuit and Inuvialuit communities in NU and NT. HFN sought to improve diet through increased intake of essential micronutrients and decreased consumption of nonnutrient dense foods that contribute to high energy and fat intake. Baseline dietary assessments conducted for the programme found widespread inadequacies of micronutrient intakes and increased total energy intakes among adults.11 12 These observations were attributed to a high consumption of micronutrient poor, high-energy dense storebought foods.13 14 HFN’s objectives were to: (1) increase/maintain consumption of traditional and nutrient-dense foods, (2) promote food preparation methods without adding fat, (3) decrease processed food consumption and (4) increase physical activity.15 The objectives of the present study were to determine differences between baseline and postintervention intake of promoted nutrients (eg, vitamins A and D) and depromoted nutrients (eg, fat and sugar) and evaluate the impact of the HFN programme among Inuit and Inuvialuit communities.
METHODS The HFN programme was evaluated through a quasi-experimental study design. The programme was conducted in six communities in NU (n=3) and NT (n=3). Selected communities included diverse proportions of Inuit and Inuvialuit populations of varying socioeconomic backgrounds.16 The intervention was conducted in one semiremote and one remote community in NT between May 2008 and August 2009, and two remote NU communities between October 2008 and November 2009. One remote community each in NU and NT served as controls. Based on themes identified during community participatory research,17 the HFN intervention
Pakseresht M, et al. J Epidemiol Community Health 2015;69:453–459. doi:10.1136/jech-2014-204623
453
Other topics included five phases: (I) 6 months of informative research to understand local concepts and cultural norms regarding healthy foods and food practices; (II) two 2-day workshops with stakeholders to identify foods and behaviours for intervention; (III) intervention refinement over 18 months to review evidence and finalise a list of foods and behaviours for intervention; (IV) 3-day training for trainees, local community health representatives, project coordinators and local store staff and (V) programme implementation and evaluation over 14 months. Some of the activities of the programme included healthy breakfasts, meal planning and cooking, sufficient intake of vitamins and minerals, pedometer challenges and walking clubs. Implementation sites included food stores, health clinics, offices and special community events. Promotional messages were communicated through local community media.15 Data collection has previously been described elsewhere.18 In brief, data collection was administered at baseline and 1 year following intervention. Using community housing maps, households were recruited following random selection of household numbers. This method ensured sampling from areas with varied proximities to food stores and hunting areas. One adult (≥19 years), typically the main food shopper or preparer, was selected to participate from each household, provided they had lived in the community for at least 6 months. Pregnant and breastfeeding women were excluded owing to the differences in their nutritional requirements and possible changes in energy expenditure. Three attempts were made before selecting a new household to substitute for a non-responding household. Written informed consent was obtained from all participants. Baseline response rates ranged between 69–93% and 65–85% in the NU and NT communities, respectively. Individuals selected at baseline from both groups were also interviewed at the end of the intervention. Participants were remunerated with gift cards. Baseline and postintervention data collection was carried out by community health workers, community members and university students, who were trained, evaluated and certified by the principal investigator (SS). Participants’ height and weight were measured in triplicate.18 Weight was adjusted between 1 and 2 kg for light to heavy clothing and recorded to the nearest 0.1 kg using a digital scale. Height was recorded to the nearest centimetre using a stadiometer. When participants declined measurements, self-reported measurements were noted. Culturally appropriate quantitative food frequency questionnaires (QFFQ) previously developed19 20 and validated21 22 for the populations were used to assess dietary intake. The questionnaire collected information on the typical frequency of food and beverage consumption over the past 30-day period classified into eight categories ranging from ‘never’ to ‘2 or more times per day’. Three-dimensional food models (NASCO, Fort Atkinson, Wisconsin, USA), packages of commonly consumed store-bought foods, standard units and local household utensils were used to assist participants’ estimate portion sizes.18 Participants’ socioeconomic status was assessed using a questionnaire collecting information on sociodemographic variables and material style of life (MSL), an additive scale of ownership of 20 items in working condition (Cronbach’s α=0.83).23 All interviewers were trained by the principal investigator (SS) in questionnaire administration and anthropometric measurements to ensure standardisation. For participants whose primary language was not English, either an interviewer fluent in the local language (Inuktitut or Inuinnaqtun) or an interpreter was used to conduct the survey. Interviews were carried out at participants’ homes and the majority were conducted in English. 454
Ethics statement Institutional Review Board approval was obtained from the Committee on Human Studies at the University of Hawaii and the Office of Human Research Ethics at the University of North Carolina at Chapel Hill. Additionally, the Ethics Committee of the Beaufort Delta Health and Social Services Authority approved this project. Aurora Research Institute in the NT and the Nunavut Research Institute in NU provided research licences.
Statistical analysis Data from all six communities were combined for analysis. Baseline differences in the communities’ demographic and socioeconomic variables by intervention assignment were analysed using a Student t test for continuous normally distributed variables and a χ2 test and a one-way analysis of variance for categorical variables. To determine total daily nutrient intake, data from three datasets (food composition table, QFFQ and food items portion weights) were analysed by the Food Frequency Questionnaire Analysis Program in STATA (StataCorp LP, College Station, Texas, USA), programmed by the first author. The programme was also used to extract the main food source of each nutrient and to determine the percentage of contribution of different food items in total daily intake of the nutrient. The mean and SD of daily energy and nutrient intakes were calculated for all participants at baseline and postintervention. As the index of diet quality, nutrient densities per 1000 kcal were calculated by dividing each participant’s daily nutrient intake by their energy intake (kcal), multiplied by 1000. Observations with energy outliers of >5000 kcal were excluded. No participant reported daily energy intake
