Dietary patterns in Liberian refugees in Buduburam, Ghana

Maternal and Child Nutrition, Volume 13, No. 4, Year 2017

Ukuhunyushwa

Previous research suggests that acculturation (i.e., exposure and assimilation to local culture) is associated with changes in dietary patterns among immigrants. This study investigates this association in a refugee population using time in refugee settlement as a proxy for acculturation. A cross-sectional survey was conducted among a systematic sample to (a) identify dietary patterns in Liberian refugees and Ghanaians living in or near a refugee settlement, (b) compare adherence to these dietary patterns between groups, and (c) investigate the association between acculturation and dietary patterns in Liberian refugees. Participants were Liberian and Ghanaian women with young children living in the Buduburam refugee settlement or Awutu in Ghana (n = 480; 50% Liberian; mean age 28, SD 6.3, range 16–48 years). Time in settlement was assessed by self-report; food consumption was assessed by food frequency questionnaire. Principal component analysis was used to identify dietary patterns; a generalized linear model was used to test the association of interest. Three distinct dietary patterns emerged: Healthy, Sweets, and Fats. Ghanaians were more adherent to the Healthy pattern than Liberians (p < 0.05). Liberians were more adherent to the Sweets and Fats patterns than Ghanaians (p < 0.05). There were no significant differences in dietary pattern adherence among the Liberians based on time in settlement. Ghanaians living in Awutu were more adherent to the Healthy pattern than Ghanaians who lived in settlement (p < 0.05). Differences in dietary patterns were observed between Liberian refugees and Ghanaians. These differences were not associated with acculturation and may be related to the food environment in the settlement. A cross‐sectional survey was administered between July and August 2008 among 480 female Liberian refugees and Ghanaians living in the Buduburam refugee settlement and the nearby urban village of Awutu (5 km from Buduburam). Women were included in the study if they were Liberian or Ghanaian, were 16 years of age or older, had a biological child between the ages of six and 59 months, were not currently pregnant, had no health problem or condition that caused a modification to their diet (e.g., diabetes and heart disease), and lived in either the Buduburam refugee settlement or Awutu. A systematic sampling approach was used to identify and recruit participants. Within Buduburam, a central location was chosen in each of 12 zones. Four teams of interviewers (one Ghanaian and one Liberian per team) were employed to collect the data. Each team began at a central location within their assigned zone. Standing in that central location, the team chose a random direction and visited the first household they encountered. The team then went to every fifth house in the same block and then moved to the next block and continued the sampling procedure until reaching the desired sample size within that zone (120 Liberians in Zones 1–10; 119 Liberians and 121 Ghanaians in Zones 11 and 12; and 120 Ghanaians in Awutu). If the mother was not present in the household at the time of the visit, the household was revisited at a more convenient time. If more than one mother living in the household met the inclusion criteria, one mother was randomly chosen to participate. This same sampling method was also employed in Awutu. Trained Liberian and Ghanaian interviewers from the target communities administered the survey. The interviewers underwent 3 days of training on conducting the interviews, interview techniques, and taking anthropometric measurements. The Liberian interviews were conducted in English (Liberian pigeon English). The Ghanaian interviews were conducted in English or the local Ghanaian dialect based on the interviewee's preference. Each interview lasted 1.5 to 2 hr. Interviews were reviewed daily for quality and standardization. Participants were revisited if data were missing or if responses were inconsistent to resolve any issues. Verbal informed consent was obtained and formally recorded for all participants prior to survey administration. Participants were assured that all information would remain confidential, would not affect access to programs within the settlement, and would not be used for determining repatriation. Institutional Review Board (IRB) approval to conduct this study was obtained from the University of Connecticut and the University of Ghana IRBs. Yale University IRB granted approval to conduct data analysis. Representatives of the Buduburam refugee settlement gave permission to defer ethical approval for this study to the collaborating universities. The administered survey was pretested among five Liberian and four Ghanaian women meeting the inclusion criteria, and the survey was modified as a result. The final survey administered at each interview assessed the following: demographic/household characteristics, degree of acculturation, household food security, infant feeding practices, infant and maternal health status, and maternal dietary intake. The following anthropometrics were also assessed in the respondent and the index child: weight, height, mid‐upper arm circumference, and head circumference (children only). Dietary intake was assessed using a culturally appropriate detailed food frequency questionnaire (FFQ). The FFQ was adapted from the Block FFQ (Block et al., 1986) to include traditional Liberian and Ghanaian foods. Traditional Liberian and Ghanaian foods were included in the FFQ after conducting key informant interviews with Liberian refugees and Ghanaians living or working within the Buduburam refugee settlement or Awutu, visiting local markets, and consulting with Liberian refugees employed by the Buduburam nutrition program. Participating women were asked about their consumption (yes/no) of 132 food/beverage items over the past 6 months within the following 12 food/beverage categories: fruits; vegetables; beans and nuts; meats; fish and seafood; cereal and grains; milk and dairy products; snacks, sweets, and desserts; drinks; tubers; other foods; and traditional mixed dishes. Participants were shown pictures of various food/beverage items to ensure they clearly understood the food/beverage items in the list. They were then asked to report how many times they had consumed each food/beverage item, reported as either daily, weekly, monthly, or only occasionally. Participants were also able to provide the name and consumption frequency of any other foods/beverages they had consumed within the 12 food/beverage categories. Time in the Buduburam refugee settlement served as a proxy for acculturation. Time in the settlement was assessed in years and/or months during the interview through self‐report. Of the 132 specific food/beverage FFQ items collected, 34 were excluded in the final FFQ analyses, specifically 26 Liberian and Ghanaian traditional mixed dishes and eight food/beverage items that were added to the survey after survey administration began. The traditional mixed dishes were excluded to ensure food/beverage items were not double counted and consumption levels were not inflated because these mixed dishes consisted of mixed food groups (i.e., complex composition) and it was uncertain whether the constituents of these mixed dishes were included by participants in the reporting of individual food/beverage items. Those food/beverage items that were added to the survey after survey administration began were excluded because not all participants were asked about these foods/beverage items. Finally, any foods/beverages that participants specified in response to the prompt “other” (e.g., “other fruits, specify”) were not included in the analysis because these items were not systematically collected for every participant. This resulted in a final total of 98 food/beverage items included in the analysis. Research suggests that it is preferable to study dietary patterns and quality (i.e., whole diet) rather than individual food components (Newby & Tucker, 2004). Therefore, the FFQ data were recoded into 32 food groups using the groupings classified in the Nutrient Data System for Research software from the University of Minnesota (University of Minnesota, Nutrition Coordinating Center, Minneapolis, MN; Table 1). Average weekly frequency of consumption over a 6‐month period was calculated for each individual for each food group. For example, a response of one time per day was represented by 1 × 7 = 7 times per week. Food/beverage groups used in final analysis and descriptions Principal component analysis was used to identify distinct dietary patterns among all respondents. Principal component analysis assigned coefficients to each food group, which were used to generate dietary pattern scores (Newby & Tucker, 2004; Sofianou et al., 2011). Dietary patterns with eigenvalues greater than 1.5 were identified and were orthogonally rotated (varimax rotation; Newby & Tucker, 2004; Sofianou et al., 2011). Four dietary patterns were identified, explaining 33.3% of the variance. The food items were retained in the interpretation of their principal component if their loadings were ≥0.4, a cut‐off chosen to aid interpretation of results. Only three of the four dietary patterns were retained because it was not possible to interpret the meaning of the fourth dietary pattern (Table 2). Using all coefficients, an individual dietary pattern score was calculated for each individual for each dietary pattern. Individual dietary pattern scores were generated by multiplying the factor loading for each food group by the weekly frequency of consumption of each food group and then summing all products for each dietary pattern. The scores for each pattern were approximately normally distributed. A high positive score indicated high adherence to a dietary pattern, and a low score indicated little or no adherence to a dietary pattern (Newby & Tucker, 2004; Sofianou et al., 2011). Highest factor loadings of food/beverage groups by dietary patterna The generalized linear model was used to assess the association between time living in the Buduburam refugee settlement and dietary pattern scores. Three models were run with each dietary pattern score as an outcome. The dietary pattern score for each dietary pattern was included in the model as a continuous variable. Time living in the Buduburam refugee settlement was included in the model as the exposure proxy variable for acculturation. Five population subgroups were created based on this proxy variable: Liberian refugees who had lived in the settlement less than 8 years (the median for this group), Liberians who had lived in the settlement for 8 or more years, Ghanaians who had lived in the settlement less than 5 years (the median for this group), Ghanaians who had lived in the settlement 5 or more years, and Ghanaians who lived in Awutu (i.e., lived 0 years in the settlement). Each model was adjusted for the following covariates: age, marital status, level of education, employment status, income, household size, presence of electricity in the home, and whether or not money had been borrowed from or loaned to others in the past year. Marital status, level of education, employment status, income, presence of electricity in the home, and whether or not money had been borrowed from or loaned to others were included in the model as categorical variables. Age and household size were included in the model as continuous variables. All analyses were performed using SPSS (version 22.0).

I-AI Digest

Study Justification:

– Previous research suggests that acculturation is associated with changes in dietary patterns among immigrants.
– This study aims to investigate the association between acculturation and dietary patterns in a refugee population.
– The study focuses on Liberian refugees in Buduburam, Ghana, using time in the refugee settlement as a proxy for acculturation.
– Understanding the dietary patterns of refugees can provide insights into their nutritional health and inform interventions to improve their well-being.

Highlights:

– The study conducted a cross-sectional survey among Liberian and Ghanaian women with young children living in the Buduburam refugee settlement or Awutu in Ghana.
– Three distinct dietary patterns were identified: Healthy, Sweets, and Fats.
– Ghanaians were more adherent to the Healthy pattern, while Liberians were more adherent to the Sweets and Fats patterns.
– There were no significant differences in dietary pattern adherence among Liberians based on time in settlement.
– Ghanaians living in Awutu were more adherent to the Healthy pattern than Ghanaians living in the settlement.

Recommendations:

– Develop interventions to promote healthier dietary patterns among Liberian refugees, focusing on reducing the consumption of sweets and fats.
– Improve access to healthy food options within the refugee settlement to support adherence to a healthy dietary pattern.
– Consider cultural preferences and traditional foods when designing interventions to ensure their acceptability and effectiveness.
– Conduct further research to explore the factors influencing dietary patterns among refugees and their impact on health outcomes.

Key Role Players:

– Researchers and academics specializing in nutrition and public health.
– Non-governmental organizations (NGOs) working with refugees and providing nutrition support.
– Local community leaders and organizations within the refugee settlement.
– Government agencies responsible for refugee welfare and health.

Cost Items for Planning Recommendations:

– Research funding for conducting further studies and interventions.
– Budget for implementing nutrition interventions, including education programs, cooking demonstrations, and access to healthy food options.
– Staff salaries and training costs for researchers, nutritionists, and community health workers.
– Monitoring and evaluation costs to assess the effectiveness of interventions.
– Infrastructure and logistics costs for improving food access within the settlement, such as establishing community gardens or food distribution centers.

Amandla Obufakazi

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is relatively strong, but there are some areas for improvement. The study design is cross-sectional, which limits the ability to establish causality. Additionally, the self-report method for assessing time in settlement and food consumption may introduce bias. To improve the evidence, a longitudinal study design could be used to establish temporal relationships. Additionally, objective measures of acculturation and dietary patterns, such as biomarkers or dietary records, could be incorporated. Finally, a larger sample size and more diverse population could enhance the generalizability of the findings.

Abstract

A cross‐sectional survey was administered between July and August 2008 among 480 female Liberian refugees and Ghanaians living in the Buduburam refugee settlement and the nearby urban village of Awutu (5 km from Buduburam). Women were included in the study if they were Liberian or Ghanaian, were 16 years of age or older, had a biological child between the ages of six and 59 months, were not currently pregnant, had no health problem or condition that caused a modification to their diet (e.g., diabetes and heart disease), and lived in either the Buduburam refugee settlement or Awutu. A systematic sampling approach was used to identify and recruit participants. Within Buduburam, a central location was chosen in each of 12 zones. Four teams of interviewers (one Ghanaian and one Liberian per team) were employed to collect the data. Each team began at a central location within their assigned zone. Standing in that central location, the team chose a random direction and visited the first household they encountered. The team then went to every fifth house in the same block and then moved to the next block and continued the sampling procedure until reaching the desired sample size within that zone (120 Liberians in Zones 1–10; 119 Liberians and 121 Ghanaians in Zones 11 and 12; and 120 Ghanaians in Awutu). If the mother was not present in the household at the time of the visit, the household was revisited at a more convenient time. If more than one mother living in the household met the inclusion criteria, one mother was randomly chosen to participate. This same sampling method was also employed in Awutu. Trained Liberian and Ghanaian interviewers from the target communities administered the survey. The interviewers underwent 3 days of training on conducting the interviews, interview techniques, and taking anthropometric measurements. The Liberian interviews were conducted in English (Liberian pigeon English). The Ghanaian interviews were conducted in English or the local Ghanaian dialect based on the interviewee's preference. Each interview lasted 1.5 to 2 hr. Interviews were reviewed daily for quality and standardization. Participants were revisited if data were missing or if responses were inconsistent to resolve any issues. Verbal informed consent was obtained and formally recorded for all participants prior to survey administration. Participants were assured that all information would remain confidential, would not affect access to programs within the settlement, and would not be used for determining repatriation. Institutional Review Board (IRB) approval to conduct this study was obtained from the University of Connecticut and the University of Ghana IRBs. Yale University IRB granted approval to conduct data analysis. Representatives of the Buduburam refugee settlement gave permission to defer ethical approval for this study to the collaborating universities. The administered survey was pretested among five Liberian and four Ghanaian women meeting the inclusion criteria, and the survey was modified as a result. The final survey administered at each interview assessed the following: demographic/household characteristics, degree of acculturation, household food security, infant feeding practices, infant and maternal health status, and maternal dietary intake. The following anthropometrics were also assessed in the respondent and the index child: weight, height, mid‐upper arm circumference, and head circumference (children only). Dietary intake was assessed using a culturally appropriate detailed food frequency questionnaire (FFQ). The FFQ was adapted from the Block FFQ (Block et al., 1986) to include traditional Liberian and Ghanaian foods. Traditional Liberian and Ghanaian foods were included in the FFQ after conducting key informant interviews with Liberian refugees and Ghanaians living or working within the Buduburam refugee settlement or Awutu, visiting local markets, and consulting with Liberian refugees employed by the Buduburam nutrition program. Participating women were asked about their consumption (yes/no) of 132 food/beverage items over the past 6 months within the following 12 food/beverage categories: fruits; vegetables; beans and nuts; meats; fish and seafood; cereal and grains; milk and dairy products; snacks, sweets, and desserts; drinks; tubers; other foods; and traditional mixed dishes. Participants were shown pictures of various food/beverage items to ensure they clearly understood the food/beverage items in the list. They were then asked to report how many times they had consumed each food/beverage item, reported as either daily, weekly, monthly, or only occasionally. Participants were also able to provide the name and consumption frequency of any other foods/beverages they had consumed within the 12 food/beverage categories. Time in the Buduburam refugee settlement served as a proxy for acculturation. Time in the settlement was assessed in years and/or months during the interview through self‐report. Of the 132 specific food/beverage FFQ items collected, 34 were excluded in the final FFQ analyses, specifically 26 Liberian and Ghanaian traditional mixed dishes and eight food/beverage items that were added to the survey after survey administration began. The traditional mixed dishes were excluded to ensure food/beverage items were not double counted and consumption levels were not inflated because these mixed dishes consisted of mixed food groups (i.e., complex composition) and it was uncertain whether the constituents of these mixed dishes were included by participants in the reporting of individual food/beverage items. Those food/beverage items that were added to the survey after survey administration began were excluded because not all participants were asked about these foods/beverage items. Finally, any foods/beverages that participants specified in response to the prompt “other” (e.g., “other fruits, specify”) were not included in the analysis because these items were not systematically collected for every participant. This resulted in a final total of 98 food/beverage items included in the analysis. Research suggests that it is preferable to study dietary patterns and quality (i.e., whole diet) rather than individual food components (Newby & Tucker, 2004). Therefore, the FFQ data were recoded into 32 food groups using the groupings classified in the Nutrient Data System for Research software from the University of Minnesota (University of Minnesota, Nutrition Coordinating Center, Minneapolis, MN; Table 1). Average weekly frequency of consumption over a 6‐month period was calculated for each individual for each food group. For example, a response of one time per day was represented by 1 × 7 = 7 times per week. Food/beverage groups used in final analysis and descriptions Principal component analysis was used to identify distinct dietary patterns among all respondents. Principal component analysis assigned coefficients to each food group, which were used to generate dietary pattern scores (Newby & Tucker, 2004; Sofianou et al., 2011). Dietary patterns with eigenvalues greater than 1.5 were identified and were orthogonally rotated (varimax rotation; Newby & Tucker, 2004; Sofianou et al., 2011). Four dietary patterns were identified, explaining 33.3% of the variance. The food items were retained in the interpretation of their principal component if their loadings were ≥0.4, a cut‐off chosen to aid interpretation of results. Only three of the four dietary patterns were retained because it was not possible to interpret the meaning of the fourth dietary pattern (Table 2). Using all coefficients, an individual dietary pattern score was calculated for each individual for each dietary pattern. Individual dietary pattern scores were generated by multiplying the factor loading for each food group by the weekly frequency of consumption of each food group and then summing all products for each dietary pattern. The scores for each pattern were approximately normally distributed. A high positive score indicated high adherence to a dietary pattern, and a low score indicated little or no adherence to a dietary pattern (Newby & Tucker, 2004; Sofianou et al., 2011). Highest factor loadings of food/beverage groups by dietary patterna The generalized linear model was used to assess the association between time living in the Buduburam refugee settlement and dietary pattern scores. Three models were run with each dietary pattern score as an outcome. The dietary pattern score for each dietary pattern was included in the model as a continuous variable. Time living in the Buduburam refugee settlement was included in the model as the exposure proxy variable for acculturation. Five population subgroups were created based on this proxy variable: Liberian refugees who had lived in the settlement less than 8 years (the median for this group), Liberians who had lived in the settlement for 8 or more years, Ghanaians who had lived in the settlement less than 5 years (the median for this group), Ghanaians who had lived in the settlement 5 or more years, and Ghanaians who lived in Awutu (i.e., lived 0 years in the settlement). Each model was adjusted for the following covariates: age, marital status, level of education, employment status, income, household size, presence of electricity in the home, and whether or not money had been borrowed from or loaned to others in the past year. Marital status, level of education, employment status, income, presence of electricity in the home, and whether or not money had been borrowed from or loaned to others were included in the model as categorical variables. Age and household size were included in the model as continuous variables. All analyses were performed using SPSS (version 22.0).

Izinto zokwakha

N/A

Emisha

Based on the provided description, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health (mHealth) Applications: Develop and implement mobile applications that provide pregnant women and new mothers with information and resources related to maternal health. These apps can offer guidance on nutrition, prenatal care, breastfeeding, and postpartum care.

2. Telemedicine: Establish telemedicine services that allow pregnant women in remote areas to consult with healthcare professionals and receive prenatal care remotely. This can help overcome geographical barriers and improve access to healthcare services.

3. Community Health Workers: Train and deploy community health workers who can provide education, support, and basic healthcare services to pregnant women and new mothers in underserved areas. These workers can help bridge the gap between communities and healthcare facilities.

4. Maternal Health Vouchers: Implement a voucher system that provides pregnant women with access to essential maternal health services, such as prenatal care, delivery, and postpartum care. These vouchers can be distributed to women in need, ensuring they can access quality healthcare services.

5. Transportation Support: Address transportation barriers by providing transportation support to pregnant women in remote areas. This can include arranging transportation to healthcare facilities for prenatal visits, delivery, and postpartum check-ups.

6. Maternal Health Education Programs: Develop and implement educational programs that focus on maternal health and target pregnant women, their families, and community members. These programs can raise awareness about the importance of prenatal care, nutrition, and safe delivery practices.

7. Maternal Health Clinics: Establish dedicated maternal health clinics in underserved areas to provide comprehensive prenatal care, delivery services, and postpartum care. These clinics can be staffed with skilled healthcare professionals who specialize in maternal health.

8. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services. This can involve leveraging private sector resources and expertise to expand healthcare infrastructure and services in underserved areas.

9. Maternal Health Hotlines: Set up toll-free hotlines staffed by healthcare professionals who can provide information, support, and guidance to pregnant women and new mothers. These hotlines can be accessed from anywhere, providing a convenient and accessible resource for maternal health-related inquiries.

10. Maternal Health Awareness Campaigns: Launch targeted awareness campaigns to educate communities about the importance of maternal health and encourage women to seek timely and appropriate care. These campaigns can utilize various media channels, community events, and local influencers to reach a wide audience.

It’s important to note that the specific context and needs of the target population should be considered when implementing these innovations.

AI Innovations Description

The study described in the provided text aimed to investigate the association between acculturation and dietary patterns among Liberian refugees and Ghanaians living in or near a refugee settlement in Buduburam, Ghana. The researchers conducted a cross-sectional survey among 480 female participants, including Liberian and Ghanaian women with young children. The survey collected data on demographic characteristics, degree of acculturation, household food security, infant feeding practices, infant and maternal health status, and maternal dietary intake.

The researchers used a food frequency questionnaire (FFQ) to assess dietary intake. The FFQ included 132 food and beverage items, which were categorized into 12 food and beverage groups. Participants were asked about their consumption frequency of each item over the past 6 months. The data from the FFQ were then recoded into 32 food groups using the Nutrient Data System for Research software.

Principal component analysis was used to identify distinct dietary patterns among the participants. Three dietary patterns were identified: Healthy, Sweets, and Fats. The Healthy pattern was found to be more adherent among Ghanaians compared to Liberians, while Liberians showed higher adherence to the Sweets and Fats patterns. The researchers did not find any significant differences in dietary pattern adherence among Liberians based on time in the settlement. However, Ghanaians living in Awutu, a nearby urban village, showed higher adherence to the Healthy pattern compared to Ghanaians living in the settlement.

To assess the association between time in the settlement and dietary pattern scores, the researchers used a generalized linear model. The model included the dietary pattern scores as outcome variables and time in the settlement as the exposure proxy variable for acculturation. The analysis was adjusted for various covariates, including age, marital status, level of education, employment status, income, household size, presence of electricity in the home, and borrowing or lending money in the past year.

In summary, the study found differences in dietary patterns between Liberian refugees and Ghanaians living in or near the refugee settlement. These differences were not associated with acculturation but may be related to the food environment in the settlement. The findings suggest that interventions to improve access to maternal health should consider the dietary patterns and food environment of the target population.

AI Innovations Methodology

The study described in the provided text focuses on investigating the association between acculturation and dietary patterns among Liberian refugees and Ghanaians living in or near a refugee settlement in Buduburam, Ghana. The methodology used in this study includes a cross-sectional survey conducted among a systematic sample of participants. Here is a brief description of the methodology:

1. Sample Selection: The study included 480 female Liberian refugees and Ghanaians living in the Buduburam refugee settlement and the nearby urban village of Awutu. Participants were selected using a systematic sampling approach, where teams of interviewers visited households in a random direction and selected every fifth house in the same block until reaching the desired sample size within each zone.

2. Data Collection: Trained Liberian and Ghanaian interviewers administered the survey, which included questions about demographic/household characteristics, degree of acculturation, household food security, infant feeding practices, infant and maternal health status, and maternal dietary intake. Anthropometric measurements were also taken for the respondents and their children.

3. Dietary Intake Assessment: Dietary intake was assessed using a culturally appropriate food frequency questionnaire (FFQ) adapted from the Block FFQ. Participants were asked about their consumption of various food and beverage items over the past 6 months within different food categories. The FFQ data were recoded into 32 food groups using the groupings classified in the Nutrient Data System for Research software.

4. Identification of Dietary Patterns: Principal component analysis was used to identify distinct dietary patterns among all respondents. Coefficients were assigned to each food group, and dietary pattern scores were generated for each individual based on the factor loading and frequency of consumption of each food group.

5. Statistical Analysis: The generalized linear model was used to assess the association between time living in the Buduburam refugee settlement (proxy for acculturation) and dietary pattern scores. Three models were run, with each dietary pattern score as an outcome variable. The models were adjusted for various covariates, including age, marital status, level of education, employment status, income, household size, presence of electricity in the home, and borrowing/loaning money.

6. Data Analysis: All analyses were performed using SPSS (version 22.0).

In summary, this study employed a cross-sectional survey methodology to investigate the association between acculturation and dietary patterns among Liberian refugees and Ghanaians in Buduburam, Ghana. The study collected data through interviews, anthropometric measurements, and a food frequency questionnaire, and used statistical analysis to examine the relationship between time in the settlement and dietary pattern scores.

Umbhali

Dima Health

Statistics:

Citations: 4

Identifiers:

DOI: 10.1111/mcn.12401

ISSN: 17408695

Research Areas:

Disparities, Food Security, Health System and Policy, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Social Determinants

Study Countries:

Ghana

Study Design:

Cross Sectional Study, Phenomenological Study

Study Approach:

Quantitative

Participants Gender:

Female

Yabelana ngalokhu: