Food environment index and preterm birth rate in the counties of the United States.

OBJECTIVES: To determine the relationship between Food Environment Index (FEI) and Preterm Birth (PTB) rate at the county level of the United States of America (USA) (primary), while evaluating the interaction of multiple factors within a framework of sociodemographic, maternal health, maternal behavioral, and environmental factors. METHODS: This is a population-based retrospective cohort ecological study from 2015-2018. The study compares the characteristics of the population of the counties of the USA. All counties with complete data on their PTB rate and the independent variables were included in the study. Independent variables with greater than 20% missing data were excluded from the study. Purposive sampling technique was applied. A total of 2983/3142 counties were included in the study. RESULTS: The median PTB rate of all counties was 9.90%. The highest PTB rate (23.3%) was in Tallapoosa County, Alabama and the lowest (3.4%) in San Juan County, Washington State. After adjusting for variables, PTB rate had a significant association with FEI (coefficient of correlation - 0.36, p < 0.01, 95% CI - 0.19 to - 0.04). Increase in the rate of unemployment, African American race, adult smoking, obesity, uninsured rate, sexually transmitted diseases (STD), high school education and air pollution was associated with an increase in PTB rate, while an increase in FEI and alcohol abuse rates was associated with a decrease in PTB rate. CONCLUSIONS: FEI can predict the PTB rate in USA counties after adjusting for sociodemographic, health, behavioral and environmental factors. Future studies are needed to confirm these associations and consider them when making policies to reduce PTBs.

Birthweight - is it linked to minor illness in adulthood?

OBJECTIVE: The Barker's hypothesis states that poor nutrition in vitro is linked to low birthweight and major illness, in particular cardiovascular disease, in later life. Reported here is an investigation to establish links with birthweight and minor illness. METHODS: 78 participants whose birthweight ranged from 1.93 kg to 4.88 kg with a mean to 3.31 kg completed a symptom checklist. RESULTS: Analysis of variance indicates that those with a higher birthweight experience less minor illness. Regression analysis indicates that birthweight is significantly predictive of levels of some minor illnesses. CONCLUSION: This investigation adds a new dimension to Barker's hypothesis and shows that early environment can also affect levels of minor illness. It is suggested that susceptibility to minor illness may be explained by coactions between structure, function and environment prior to birth.