Optimizing protein intake is a novel strategy to prevent age associated loss of muscle mass and strength in older adults. Such a strategy is still missing for older adults from ethnic minority populations. Protein intake in these populations is expected to be different in comparison to the majority of the population due to several socio-cultural factors. Therefore, the present study examined the dietary protein intake and underlying behavioral and environmental factors affecting protein intake among older adults from ethnic minorities in the Netherlands. We analyzed frequency questionnaire (FFQ) data from the Healthy Life in an Urban Setting (HELIUS) cohort using ANCOVA to describe dietary protein intake in older adults from ethnic minorities in the Netherlands (N = 1415, aged >55 years, African Surinamese, South Asian Surinamese, Moroccan, and Turkish). Additionally, we performed focus groups among older adults from the same ethnic minority populations (N = 69) to discover behavioral and environmental factors affecting protein intake; 40-60% of the subjects did not reach minimal dietary protein recommendations needed to maintain muscle mass (1.0 g/kg bodyweight per day (BW/day)), except for Turkish men (where it was 91%). The major sources of protein originated from animal products and were ethnic specific. Participants in the focus groups showed little knowledge and awareness about protein and its role in aging. The amount of dietary protein and irregular eating patterns seemed to be the major concern in these populations. Optimizing protein intake in these groups requires a culturally sensitive approach, which accounts for specific protein product types and sociocultural factors.
BACKGROUND: Social inequalities in bodyweight start early in life and track into adulthood. Dietary patterns are an important determinant of weight development in children, towards both overweight and underweight. Therefore, we aimed to examine weight development between age 5 and 10 years by ethnicity, SES and thereafter by BMI category at age 5, to explore its association with dietary patterns at age 5.METHODS: Participants were 1765 children from the Amsterdam Born Children and their Development (ABCD) cohort that had valid data on BMI at age 5 and 10 and diet at age 5. Linear mixed model analysis was used to examine weight development between age 5 and 10 years and to assess if four previously identified dietary patterns at age 5 (snacking, full-fat, meat and healthy) were associated with weight development. Analyses were adjusted for relevant confounders, stratified by ethnicity and SES and thereafter stratified per BMI category at age 5.RESULTS: Overall, weight decreased in Dutch and high SES children and increased in non-Dutch and low/middle SES children. Across the range of bodyweight categories at age 5, we observed a conversion to normal weight, which was stronger in Dutch and high SES children but less pronounced in non-Dutch and low/middle SES children. Overall, the observed associations between weight development and dietary patterns were mixed with some unexpected findings: a healthy dietary pattern was positively associated with weight development in most groups, regardless of ethnicity and SES (e.g. Dutch B 0.084, 95% CI 0.038;0.130 and high SES B 0.096, 95% CI 0.047;0.143) whereas the full-fat pattern was negatively associated with weight development (e.g. Dutch B -0.069, 95% CI -0.114;-0.024 and high SES B -0.072, 95% CI -0.119;-0.026).CONCLUSIONS: We observed differential weight development per ethnic and SES group. Our results indicate that each ethnic and SES group follows its own path of weight development. Associations between dietary patterns and weight development showed some unexpected findings; follow-up research is needed to understand the association between dietary patterns and weight development.
