Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention.

Stress leads to physiologic dysfunction and cardiometabolic disease. Allostatic load score (ALS) measures stress-induced cardiovascular, metabolic, and inflammatory biomarkers. We estimated the odds of high ALS by reason for and age at immigration, duration of American residence, number of children, and socioeconomic status in 193 African immigrants (male: 65%, age 41 ± 10 y (mean ± Standard Deviation (SD)), range 22–65 y). ALS was calculated with High-ALS defined as ALS ≥ 3.0 and Low-ALS defined as ALS < 3.0. Oral glucose tolerance tests (OGTT) were performed, the cardiovascular disease (CVD) risk estimated, and TNF-α, an inflammatory cytokine, measured. Logistic regression was used to estimate odds of High-ALS. In the High- and Low-ALS groups, ALS were 4.0 ± 1.2 vs. 1.3 ± 0.7, diabetes prevalence: 14% vs. 4%, CVD risk: 23% vs. 8%, TNF-α levels: 15 ± 9 vs. 11 ± 6 pg/mL, respectively (all p ≤ 0.01). Immigrants were more likely to be in the High-ALS group if their reason for immigration was work or asylum/refugee (OR 2.18, p = 0.013), their age at immigration was ≥30 y (OR 3.28, p < 0.001), their duration of residence in United States was ≥10 y (OR 3.16, p = 0.001), or their number of children was ≥3 (OR 2.67, p = 0.019). Education, income, health insurance, marital status, and gender did not affect High-ALS odds. Factors adversely influencing allostatic load and cardiometabolic health in African immigrants were age at and reason for immigration, duration of residence in America, and number of children.

Dietary acculturation may explain the increasing risk of diet-related diseases among African immigrants in the United States (US). We interviewed twenty-five Ghanaian immigrants (Youthn13, Age (Mean ±sd) 20 y ± 5⋅4, Parents (n6) and Grandparents (n6) age 58⋅7 ± 9⋅7) living in New York City (NYC) to (a) understand how cultural practices and the acculturation experience influence dietary patterns of Ghanaian immigrants and (b) identify intergenerational differences in dietary acculturation among Ghanaian youth, parents and grandparents. Dietary acculturation began in Ghana, continued in NYC and was perceived as a positive process. At the interpersonal level, parents encouraged youth to embrace school lunch and foods outside the home. In contrast, parents preferred home-cooked Ghanaian meals, yet busy schedules limited time for cooking and shared meals. At the community level, greater purchasing power in NYC led to increased calories, and youth welcomed individual choice as schools and fast food exposed them to new foods. Global forces facilitated nutrition transition in Ghana as fast and packaged foods became omnipresent in urban settings. Adults sought to maintain cultural foodways while facilitating dietary acculturation for youth. Both traditional and global diets evolved as youth and adults adopted new food and healthy social norms in the US.

The overall consensus is that foreign-born adults who come to America age < 20 y achieve economic success but develop adverse behaviors (smoking and drinking) that lead to worse cardiometabolic health than immigrants who arrive age ≥ 20 y. Whether age of immigration affects the health of African-born Blacks living in America is unknown. Our goals were to examine cultural identity, behavior, and socioeconomic factors and determine if differences exist in the cardiometabolic health of Africans who immigrated to America before and after age 20 y. Of the 482 enrollees (age: 38 ± 1 (mean ± SE), range: 20–65 y) in the Africans in America cohort, 23% (111/482) arrived age < 20 y, and 77% (371/482) arrived age ≥ 20 y. Independent of francophone status or African region of origin, Africans who immigrated age < 20 y had similar or better cardiometabolic health than Africans who immigrated age ≥ 20 y. The majority of Africans who immigrated age < 20 y identified as African, had African-born spouses, exercised, did not adopt adverse health behaviors, and actualized early life migration advantages, such as an American university education. Due to maintenance of cultural identity and actualization of opportunities in America, cardiometabolic health may be protected in Africans who immigrate before age 20. In short, immigrant health research must be cognizant of the diversity within the foreign-born community and age of immigration.

Background: Predicting undiagnosed diabetes is a critical step toward addressing the diabetes epidemic in populations of African descent worldwide. Objective: To review characteristics of equations developed, tested, or modified to predict diabetes in African descent populations. Methods: Using PubMed, Scopus, and Embase databases, a scoping review yielded 585 research articles. After removal of duplicates (n = 205), 380 articles were reviewed. After title and abstract review 328 articles did not meet inclusion criteria and were excluded. Fifty-two articles were retained. However, full text review revealed that 44 of the 52 articles did not report findings by AROC or C-statistic in African descent populations. Therefore, eight articles remained. Results: The 8 articles reported on a total of 15 prediction equation studies. The prediction equations were of two types. Prevalence prediction equations (n = 9) detected undiagnosed diabetes and were based on non-invasive variables only. Non-invasive variables included demographics, blood pressure and measures of body size. Incidence prediction equations (n = 6) predicted risk of developing diabetes and used either non-invasive variables or both non-invasive and invasive. Invasive variables required blood tests and included fasting glucose, high density lipoprotein-cholesterol (HDL), triglycerides (TG), and A1C. Prevalence prediction studies were conducted in the United States, Africa and Europe. Incidence prediction studies were conducted only in the United States. In all these studies, the performance of diabetes prediction equations was assessed by area under the receiver operator characteristics curve (AROC) or the C-statistic. Therefore, we evaluated the efficacy of these equations based on standard criteria, specifically discrimination by either AROC or C-statistic were defined as: Poor (0.50 – 0.69); Acceptable (0.70 – 0.79); Excellent (0.80 – 0.89); or Outstanding (0.90 – 1.00). Prediction equations based only on non-invasive variables reported to have poor to acceptable detection of diabetes with AROC or C-statistic 0.64 – 0.79. In contrast, prediction equations which were based on both non-invasive and invasive variables had excellent diabetes detection with AROC or C-statistic 0.80 – 0.82. Conclusion: Equations which use a combination of non-invasive and invasive variables appear to be superior in the prediction of diabetes in African descent populations than equations that rely on non-invasive variables alone.