Dayeon Shin

Prepregnancy body mass index is an independent risk factor for gestational hypertension, gestational diabetes, preterm labor, and small- and large-for-gestational-age infants

Abstract Objective: We examined if prepregnancy body mass index (BMI) is a risk factor for gestational hypertension, gestational diabetes, preterm labor, and small-for-gestational-age (SGA) and large-for-gestational-age (LGA) infants with consideration of gestational weight gain, to document the importance of preconception versus prenatal stage. Methods: We used the data of 219 868 women from 2004 to 2011 Pregnancy Risk Assessment Monitoring System (PRAMS). Multivariate logistic regression analyses were performed to examine the effect of prepregnancy BMI for gestational hypertension, gestational diabetes, preterm labor, and SGA and LGA infants with consideration of gestational weight gain. Results: Regardless of gestational weight gain, women with obese prepregnancy BMI (≥30 kg/m2) had increased odds of gestational hypertension (adjusted odds ratios (AOR) = 2.91; 95% CI = 2.76–3.07), gestational diabetes (2.78; 2.60–2.96), and LGA (1.87; 1.76–1.99) compared to women with normal prepregnancy BMI (18.5–24.9 kg/m2). Women with underweight prepregnancy BMI (<18.5 kg/m2) had increased odds of preterm labor (1.25; 1.16–1.36) and SGA infants (1.36; 1.25–1.49), but decreased odds of LGA infants (0.72; 0.61–0.85) in reference to women with normal prepregnancy BMI (18.5–24.9 kg/m2). Conclusions: Regardless of adequacy of gestational weight gain, the risk of gestational hypertension, gestational diabetes, and LGA infants increases with obese prepregnancy BMI, whereas that of preterm labor and SGA infants increases with underweight prepregnancy BMI. Preconception care of reproductive aged women is as important as prenatal care to lower the risk of gestational hypertension, gestational diabetes, preterm labor, and SGA and LGA infants.

Dietary Patterns during Pregnancy Are Associated with Risk of Gestational Diabetes Mellitus

Maternal dietary patterns before and during pregnancy play important roles in the development of gestational diabetes mellitus (GDM). We aimed to identify dietary patterns during pregnancy that are associated with GDM risk in pregnant U.S. women. From a 24 h dietary recall of 253 pregnant women (16–41 years) included in the National Health and Nutrition Examination Survey (NHANES) 2003–2012, food items were aggregated into 28 food groups based on Food Patterns Equivalents Database. Three dietary patterns were identified by reduced rank regression with responses including prepregnancy body mass index (BMI), dietary fiber, and ratio of poly- and monounsaturated fatty acids to saturated fatty acid: “high refined grains, fats, oils and fruit juice”, “high nuts, seeds, fat and soybean; low milk and cheese”, and “high added sugar and organ meats; low fruits, vegetables and seafood”. GDM was diagnosed using fasting plasma glucose levels ≥5.1 mmol/L for gestation <24 weeks. Multivariable logistic regression models were used to estimate adjusted odds ratio (AOR) and 95% confidence intervals (CIs) for GDM, after controlling for maternal age, race/ethnicity, education, family poverty income ratio, marital status, prepregnancy BMI, gestational weight gain, energy intake, physical activity, and log-transformed C-reactive protein (CRP). All statistical analyses accounted for the appropriate survey design and sample weights of the NHANES. Of 249 pregnant women, 34 pregnant women (14%) had GDM. Multivariable AOR (95% CIs) of GDM for comparisons between the highest vs. lowest tertiles were 4.9 (1.4–17.0) for “high refined grains, fats, oils and fruit juice” pattern, 7.5 (1.8–32.3) for “high nuts, seeds, fat and soybean; low milk and cheese” pattern, and 22.3 (3.9–127.4) for “high added sugar and organ meats; low fruits, vegetables and seafood” pattern after controlling for maternal sociodemographic variables, prepregnancy BMI, gestational weight gain, energy intake and log-transformed CRP. These findings suggest that dietary patterns during pregnancy are associated with risk of GDM after controlling for potential confounders. The observed connection between a high consumption of refined grains, fat, added sugars and low intake of fruits and vegetables during pregnancy with higher odds for GDM, are consistent with general health benefits of healthy diets, but warrants further research to understand underlying pathophysiology of GDM associated with dietary behaviors during pregnancy.

Depression and Its Comorbid Conditions More Serious in Women than in Men in the United States.

BACKGROUND Depression is a major public health problem by itself and for its comorbid conditions. We aimed to determine gender differences in the prevalence of depression and how depression is related to comorbid conditions and metabolic biomarkers. METHODS This study included men (n=986) and women (n=1,280) aged 20-79 years who were included in the 2007-2010 National Health and Nutrition Examination Survey. Depression was assessed with the Patient Health Questionnaire (PHQ-9). The associations between depression (PHQ-9 score ≥10), self-reported comorbid conditions, and metabolic biomarkers of comorbid conditions were determined by multivariable logistic regressions adjusting for potential confounders. RESULTS The prevalence of depression in men and women were 7.9% and 12.1%, respectively (p<0.01). The odds ratios (OR) of various comorbid conditions (asthma, arthritis, gout, coronary heart disease, heart attack, stroke, diabetes mellitus, thyroid problem, and metabolic syndrome) by the status of depression were significantly higher in women. High C-reactive protein (CRP) was a significant predictor of depression in men (OR 2.02, 95% confidence interval [CI] 1.11-3.67) in unadjusted model. In women, high fasting blood glucose, high glycohemoglobin, and high CRP were significant predictors of depression (OR 1.20, 95% CI 1.28-3.01; OR 2.44, 95% CI 1.21-4.92; OR 1.44, 95% CI 1.01-2.06; OR 1.79, 95% CI 0.19-2.67, respectively) after controlling for age, education, race/ethnicity, marital status, ratio of family income to poverty, and physical activity. CONCLUSIONS Women had higher prevalence of depression and higher number of significant associations between socioeconomic status, comorbid conditions, and metabolic risk factors by the status of depression than men. Public health attentions are needed to improve womens mental health.

Pre-Pregnancy Weight Status Is Associated with Diet Quality and Nutritional Biomarkers during Pregnancy.

Although the positive association between pre-pregnancy overweight and obesity with excessive gestational weight gain is well known, it is not clear how pre-pregnancy weight status is associated with gestational weight gain through maternal diet during pregnancy. This study aimed to examine the relationship between pre-pregnancy weight status and diet quality and maternal nutritional biomarkers during pregnancy. Our study included 795 U.S. pregnant women from the National Health and Nutrition Examination Survey, 2003–2012. Pre-pregnancy body mass index (BMI) was calculated based on self-reported pre-pregnancy weight and height. The cutoff points of <18.5 (underweight), 18.5–24.9 (normal), 25.0–29.9 (overweight), and 30 kg/m2 (obese) were used to categorize pregnant women’s weight status. Diet quality during pregnancy was assessed by the Healthy Eating Index (HEI)-2010 based on a 24-h recall. Multivariable logistic regressions were used to estimate the odds ratios (OR) and 95% confidence intervals (CI). For all pregnant women included in this study, the mean HEI-2010 (±standard error of the mean (SEM)) was 50.7 (±0.9). Women with obese pre-pregnancy BMI demonstrated significantly lower HEI-2010 compared to those with underweight and normal pre-pregnancy BMI, respectively. In an unadjusted model, women with pre-pregnancy obesity BMI had increased odds for being in the lowest tertile of HEI-2010 (33.4 ± 0.5) compared to those with underweight pre-pregnancy BMI (OR 5.0; 95% CI 2.2–11.4). The inverse association between pre-pregnancy overweight and obesity status and diet quality during pregnancy persisted even after we controlled for physical activity levels (adjusted OR (AOR) 3.8; 95% CI 1.2–11.7, AOR 5.4; 95% CI 2.0–14.5, respectively). Serum folate concentration (ng/mL) was significantly higher in underweight women compared to overweight women (23.4 ± 1.7 vs. 17.0 ± 0.8, p < 0.05). Serum iron concentration (ng/dL) was significantly higher in normal weight women compared to overweight women (86.2 ± 5.0 vs. 68.9 ± 3.0, p < 0.05). An inverse association was found between pre-pregnancy weight status and diet quality and maternal nutritional biomarkers during pregnancy. Poor diet quality as measured by HEI-2010 was shown among overweight and obese women. Nutrition education and interventions need to be targeted to those women entering pregnancy as overweight and obese.

Pre-Pregnancy Body Mass Index Is Associated with Dietary Inflammatory Index and C-Reactive Protein Concentrations during Pregnancy

There have been a limited number of studies examining the association between pre-pregnancy body mass index (BMI) and dietary inflammation during pregnancy. Our aim is to examine the association between pre-pregnancy BMI and the Dietary Inflammatory Index (DII)™ and C-reactive protein (CRP) concentrations during pregnancy. The study included 631 pregnant American women from the National Health and Nutrition Examination Survey (NHANES) cross-sectional examinations from 2003 to 2012. Pre-pregnancy BMI was calculated based on self-reported pre-pregnancy weight and measured height. The cut-offs of <18.5 (underweight), 18.5–24.9 (normal), 25.0–29.9 (overweight), and ≥30 kg/m2 (obese) were used to categorize the weight status of pregnant women prior to pregnancy. The DII, a literature-based dietary index to assess the inflammatory properties of diet, was estimated based on a one-day 24-h recall. Multivariable linear and logistic regressions were performed to estimate beta coefficients and the adjusted odds ratios (AORs) and 95% confidence intervals (95% CIs) on the association of pre-pregnancy BMI categories with the DII and CRP concentrations during pregnancy. After controlling for variables including: race/ethnicity, family poverty income ratio, education, marital status, month in pregnancy, and smoking status during pregnancy; women who were obese before pregnancy (n = 136) had increased odds for being in the highest tertile of the DII and CRP concentrations compared to women with normal weight (AORs 2.40, 95% CIs 1.01–5.71; AORs 24.84, 95% CIs 6.19–99.67, respectively). These findings suggest that women with pre-pregnancy obesity had greater odds of reporting higher DII and having elevated CRP. In conclusion, high pre-pregnancy BMI was associated with increased odds of pro-inflammatory diet and elevated CRP levels during pregnancy in the USA.

Changes in iodine status among US adults, 2001–2012

Abstract Urinary iodine concentrations (UICs) in the US have been reported to be stable since 1988–1994, although those in selected subgroups remained low. We aimed to investigate iodine status among adults (≥20 years) by two different criteria of assessing iodine deficiency in population. Utilizing National Health and Nutrition Examination Surveys 2001–2012, we conducted linear logistic regressions adjusting for covariates. The prevalence of <50 μg/L UIC was higher in women than in men; increased from 11.6% (2001–2004) to 13.2% (2009–2012) at the national level and in young adults, non-Hispanic blacks (NHBs) and non-users of iodine-containing supplements (all, p <0.05); the adjusted odds ratios (95%CI) in young adults (1.54 [1.11–2.15], p = 0.0007) and NHBs (1.70 [1.15–2.52], p = 0.0078). Median UICs confirm women and NHBs being in borderline iodine status. Recognizing the critical consequence of iodine deficiency particularly in women and NHBs, regular monitoring of iodine status is important for public health in the US.

Total Water Intake from Beverages and Foods Is Associated with Energy Intake and Eating Behaviors in Korean Adults

Water is essential for the proper functioning of the body. Even though a recommendation exists for adequate water intake for Koreans, studies identifying actual water intake from all beverages and foods consumed daily in the Korean population are limited. Thus, we estimated total water intake from both beverages and foods and its association with energy intake and eating behaviors in Korean adults. We used a nationally representative sample of 25,122 Korean adults aged ≥19 years, from the Korean National Health and Nutrition Examination Survey 2008–2012. We performed multiple regression analyses, adjusting for sociodemographic and health-related variables to investigate the contribution of overall energy and dietary intakes and eating behaviors to total water intake. The mean total water intake excluding plain water was 1071 g (398 g from beverages and 673 g from foods) and the estimated plain water intake was 1.3 L. Among Korean adults, 82% consumed beverages (excluding plain water) and these beverages contributed to 10% of daily energy intake and 32% of total water intake from beverages and foods. For every 100 kcal/day in energy intake, water intake consumed through beverages and foods increased by 18 g and 31 g, respectively. Water intake from beverages and foods was positively associated with energy from fat and dietary calcium, but inversely associated with energy density and energy from carbohydrates. When there was a 5% increase in energy intake from snacks and eating outside the home, there was an increase in water intake from beverages of 13 g and 2 g, respectively. Increased daily energy intake, the number of eating episodes, and energy intake from snacks and eating outside the home predicted higher water intake from beverages and foods. Our results provide evidence suggesting that various factors, including sociodemographic status, dietary intakes, and eating behaviors, could be important contributors to the water intake of Korean adults. Findings from this cross-sectional analysis may provide insight into strategies for promoting adequate water intake among Koreans.

Food Group Intakes as Determinants of Iodine Status among US Adult Population

Adequate intake of iodine is essential for proper thyroid function. Although dietary reference intakes for iodine have been established, iodine intake cannot be estimated due to the lack of data on iodine contents in foods. We aimed to determine if food group intakes can predict iodine status assessed by urinary iodine concentration (UIC) from spot urine samples of 5967 US adults in the National Health and Nutrition Examination Survey (NHANES) 2007–2012. From an in-person 24-h dietary recall, all foods consumed were aggregated into 12 main food groups using the individual food code of the US Department of Agriculture (USDA); dairy products, meat/poultry, fish/seaweed, eggs, legumes/nuts/seeds, breads, other grain products, fruits, vegetables, fats/oils, sugars/sweets, and beverages. Chi-square test, Spearman correlation, and multiple linear regression analyses were conducted to investigate the predictability of food group intakes in iodine status assessed by UIC. From the multiple linear regressions, the consumption of dairy products, eggs, and breads, and iodine-containing supplement use were positively associated with UIC, whereas beverage consumption was negatively associated with UIC. Among various food group intakes, dairy product intake was the most important determinant of iodine status in both US men and women. Subpopulation groups with a high risk of iodine deficiency may need nutritional education regarding the consumption of dairy products, eggs, and breads to maintain an adequate iodine status. Efforts toward a better understanding of iodine content in each food and a continued monitoring of iodine status within US adults are both warranted.

Low Urinary Iodine Concentrations Associated with Dyslipidemia in US Adults

Iodine is an essential component of the thyroid hormone which plays crucial roles in healthy thyroid function and lipid metabolism. However, the association between iodine status and dyslipidemia has not been well established at a population level. We aimed to test the hypothesis that the odds of dyslipidemia including elevated total cholesterol, triglycerides, low-density lipoprotein (LDL) cholesterol and apolipoprotein B, and lowered high-density lipoprotein (HDL) cholesterol and HDL/LDL ratio are associated with urinary iodine concentration (UIC) in a population perspective. Data of 2495 US adults (≥20 years) in the National Health and Nutrition Examination Survey 2007–2012 were used in this study. Two subgroups (i.e., UIC below vs. above the 10th percentile) were compared of dyslipidemia as defined based on NCEP ATP III guidelines. The differences between the groups were tested statistically by chi-square test, simple linear regressions, and multiple logistic regressions. Serum lipid concentrations differed significantly between two iodine status groups when sociodemographic and lifestyle covariates were controlled (all, p < 0.05). Those with the lowest decile of UIC were more likely to be at risk for elevated total cholesterol (>200 mg/dL) (adjusted odds ratio (AOR) = 1.51, 95% confidence interval (CI): 1.03–2.23) and elevated LDL cholesterol (>130 mg/dL) (AOR = 1.58, 95% CI: 1.11–2.23) and lowered HDL/LDL ratio (<0.4) (AOR = 1.66, 95% CI: 1.18–2.33), compared to those with UIC above the 10th percentile. In US adults, low UIC was associated with increased odds for dyslipidemia. Findings of the present cross-sectional study with spot urine samples highlight the significant association between UIC and serum lipids at population level, but do not substantiate a causal relationship. Further investigations are warranted to elucidate the causal relationship among iodine intakes, iodine status, and serum lipid profiles.

Identifying Dietary Patterns Associated with Mild Cognitive Impairment in Older Korean Adults Using Reduced Rank Regression

Diet plays a crucial role in cognitive function. Few studies have examined the relationship between dietary patterns and cognitive functions of older adults in the Korean population. This study aimed to identify the effect of dietary patterns on the risk of mild cognitive impairment. A total of 239 participants, including 88 men and 151 women, aged 65 years and older were selected from health centers in the district of Seoul, Gyeonggi province, and Incheon, in Korea. Dietary patterns were determined using Reduced Rank Regression (RRR) methods with responses regarding vitamin B6, vitamin C, and iron intakes, based on both a one-day 24-h recall and a food frequency questionnaire. Cognitive function was assessed using the Korean-Mini Mental State Examination (K-MMSE). Multivariable logistic regression models were used to estimate the association between dietary pattern score and the risk of mild cognitive impairment. A total of 20 (8%) out of the 239 participants had mild cognitive impairment. Three dietary patterns were identified: seafood and vegetables, high meat, and bread, ham, and alcohol. Among the three dietary patterns, the older adult population who adhered to the seafood and vegetables pattern, characterized by high intake of seafood, vegetables, fruits, bread, snacks, soy products, beans, chicken, pork, ham, egg, and milk had a decreased risk of mild cognitive impairment compared to those who did not (adjusted odds ratios 0.06, 95% confidence interval 0.01–0.72) after controlling for gender, supplementation, education, history of dementia, physical activity, body mass index (BMI), and duration of sleep. The other two dietary patterns were not significantly associated with the risk of mild cognitive impairment. In conclusion, high consumption of fruits, vegetables, seafood, and protein foods was significantly associated with reduced mild cognitive impairment in older Korean adults. These results can contribute to the establishment of dietary guidelines targeting older Korean adults to reduce mild cognitive impairments. Future prospective cohort studies are warranted to examine the effect of the seafood and vegetable dietary pattern on reducing mild cognitive impairment to prove the cause–effect relationship between dietary patterns and cognitive function.