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PLoS One ; 14(9): e0222458, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31536528


OBJECTIVE: To determine recent trends in maternal prepregnancy body mass index (BMI) and to quantify its association with birth and maternal outcomes. METHODS: A population-based retrospective cohort study included resident women with singleton births in the California Birth Statistical Master Files (BSMF) database from 2007 to 2016. There were 4,621,082 women included out of 5,054,968 women registered in the database. 433,886 (8.6%) women were excluded due to invalid or missing information for BMI. Exposures were underweight (BMI < 18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight (25.0-29.9 kg/m2), and obese (≥ 30 kg/m2) at the onset of pregnancy. Obesity was subcategorized into class I (30.0-34.9 kg/m2), class II (35.0-39.9 kg/m2), and class III (≥ 40 kg/m2), while adverse outcomes examined were low birth weight (LBW), very low birth weight (VLBW), macrosomic births, preterm birth (PTB), very preterm birth (VPTB), small-for-gestational-age birth (SGA), large-for-gestational-age birth (LGA), and cesarean delivery (CD). Descriptive analysis, simple linear regression, and multivariate logistic regression were performed, and adjusted odds ratios (AORs) with 95% confidence intervals (CIs) for associations were estimated. RESULTS: Over the ten-year study period, the prevalence of underweight and normal weight women at time of birth declined by 10.6% and 9.7%, respectively, while the prevalence of overweight and obese increased by 4.3% and 22.9%, respectively. VLBW increased significantly with increasing BMI, by 24% in overweight women and by 76% in women with class III obesity from 2007 to 2016. Women with class III obesity also had a significant increase in macrosomic birth (170%) and were more likely to deliver PTB (33%), VPTB (66%), LGA (231%), and CD (208%) than women with a normal BMI. However, obese women were less likely to have SGA infants; underweight women were 51% more likely to have SGA infants than women with a normal BMI. CONCLUSIONS: In California from 2007 to 2016, there was a declining trend in women with prepregnancy normal weight, and a rising trend in overweight and obese women, particularly obesity class III. Both extremes of prepregnancy BMI were associated with an increased incidence of adverse neonatal outcomes; however, the worse outcomes were prominent in those women classified as obese.

Índice de Massa Corporal , Resultado da Gravidez/epidemiologia , Adulto , California/epidemiologia , Feminino , Humanos , Obesidade Materna/epidemiologia , Sobrepeso/epidemiologia , Gravidez , Prevalência , Estudos Retrospectivos
Am J Perinatol ; 2019 Jul 31.
Artigo em Inglês | MEDLINE | ID: mdl-31365931


OBJECTIVE: To determine associations between maternal cigarette smoking and adverse birth and maternal outcomes. STUDY DESIGN: This is a 10-year population-based retrospective cohort study including 4,971,896 resident births in California. Pregnancy outcomes of maternal smokers were compared with those of nonsmokers. The outcomes of women who stopped smoking before or during various stages of pregnancy were also investigated. RESULTS: Infants of women who smoked during pregnancy were twice as likely to have low birth weight (LBW) and be small for gestational age (SGA), 57% more likely to have very LBW (VLBW) or be a preterm birth (PTB), and 59% more likely to have a very PTB compared with infants of nonsmokers. During the study period, a significant widening of gaps developed in both rates of LBW and PTB and the percentage of SGA between infants of maternal smokers and nonsmokers. CONCLUSION: Smoking during pregnancy is associated with a significantly increased risk of adverse birth and maternal outcomes, and differences in rates of LBW, PTB, and SGA between infants of maternal smokers and nonsmokers increased during this period. Stopping smoking before pregnancy or even during the first trimester significantly decreased the infant risks of LBW, PTB, SGA, and the maternal risk for cesarean delivery.

Heredity (Edinb) ; 122(5): 684-695, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30368530


Plant breeders are supported by a range of tools that assist them to make decisions about the conduct or design of plant breeding programs. Simulations are a strategic tool that enables the breeder to integrate the multiple components of a breeding program into a number of proposed scenarios that are compared by a range of statistics measuring the efficiency of the proposed systems. A simulation study for the trait growth score compared two major strategies for breeding forage species, among half-sib family selection and among and within half-sib family selection. These scenarios highlighted new features of the QuLine program, now called QuLinePlus, incorporated to enable the software platform to be used to simulate breeding programs for cross-pollinated species. Each strategy was compared across three levels of half-sib family mean heritability (0.1, 0.5, and 0.9), across three sizes of the initial parental population (10, 50, and 100), and across three genetic effects models (fully additive model, a mixture of additive, partial and over dominance model, and a mixture of partial dominance and over dominance model). Among and within half-sib selection performed better than among half-sib selection for all scenarios. The new tools introduced into QuLinePlus should serve to accurately compare among methods and provide direction on how to achieve specific goals in the improvement of plant breeding programs for cross breeding species.

Artigo em Inglês | MEDLINE | ID: mdl-30564431


Background: Preterm birth (PTB) is associated with increased infant mortality, and neurodevelopmental abnormalities among survivors. The aim of this study is to investigate temporal trends, patterns, and predictors of PTB in California from 2007 to 2016, based on the obstetric estimate of gestational age (OA). Methods: A retrospective cohort study evaluated 435,280 PTBs from the 5,137,376 resident live births (8.5%) documented in the California Birth Statistical Master Files (BSMF) from 2007 to 2016. The outcome variable was PTB; the explanatory variables were birth year, maternal characteristics and health behaviors. Descriptive statistics and logistic regression analysis were used to identify subgroups with significant risk factors associated with PTB. Small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA) infants were identified employing gestational age based on obstetric estimates and further classified by term and preterm births, resulting in six categories of intrauterine growth. Results: The prevalence of PTB in California decreased from 9.0% in 2007 to 8.2% in 2014, but increased during the last 2 years, 8.4% in 2015 and 8.5% in 2016. Maternal age, education level, race and ethnicity, smoking during pregnancy, and parity were significant risk factors associated with PTB. The adjusted odds ratio (AOR) showed that women in the oldest age group (40-54 years) were almost twice as likely to experience PTB as women in the 20- to 24-year reference age group. The prevalence of PTB was 64% higher in African American women than in Caucasian women. Hispanic women showed less disparity in the prevalence of PTB based on education and socioeconomic level. The analysis of interactions between maternal characteristics and perinatal health behaviors showed that Asian women have the highest prevalence of PTB in the youngest age group (< 20 years; AOR, 1.40; 95% confidence interval (CI), 1.28-1.54). Pacific Islander, American Indian, and African American women ≥40 years of age had a greater than two-fold increase in the prevalence of PTB compared with women in the 20-24 year age group. Compared to women in the Northern and Sierra regions, women in the San Joaquin Valley were 18%, and women in the Inland Empire and San Diego regions 13% more likely to have a PTB. Women who smoked during both the first and second trimesters were 57% more likely to have a PTB than women who did not smoke. Compared to women of normal prepregnancy weight, underweight women and women in obese class III were 23 and 33% more likely to experience PTB respectively. Conclusions: Implementation of public health initiatives focusing on reducing the prevalence of PTB should focus on women of advanced maternal age and address race, ethnic, and geographic disparities. The significance of modifiable maternal perinatal health behaviors that contribute to PTB, e.g. smoking during pregnancy and prepregnancy obesity, need to be emphasized during prenatal care.

Artigo em Inglês | MEDLINE | ID: mdl-30094052


Background: Low birth weight (LBW) is a leading risk factor for infant morbidity and mortality in the United States. There are large disparities in the prevalence of LBW by race and ethnicity, especially between African American and White women. Despite extensive research, the practice of clinical and public health, and policies devoted to reducing the number of LBW infants, the prevalence of LBW has remained unacceptably and consistently high. There have been few detailed studies identifying the factors associated with LBW in California, which is home to a highly diverse population. The aim of this study is to investigate recent trends in the prevalence of LBW infants (measured as a percentage) and to identify risk factors and disparities associated with LBW in California. Methods: A retrospective cohort study included data on 5,267,519 births recorded in the California Birth Statistical Master Files for the period 2005-2014. These data included maternal characteristics, health behaviors, information on health insurance, prenatal care use, and parity. Logistic regression models identified significant risk factors associated with LBW. Using gestational age based on obstetric estimates (OA), small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA) infants were identified for the periods 2007-2014. Results: The number of LBW infants declined, from 37,603 in 2005 to 33,447 in 2014. However, the prevalence of LBW did not change significantly (6.9% in 2005 to 6.7% in 2014). The mean maternal age at first delivery increased from 25.7 years in 2005 to 27.2 years in 2014. The adjusted odds ratio showed that women aged 40 to 54 years were twice as likely to have an LBW infant as women in the 20 to 24 age group. African American women had a persistent 2.4-fold greater prevalence of having an LBW infant compared with white women. Maternal age was a significant risk factor for LBW regardless of maternal race and ethnicity or education level. During the period 2017-2014, 5.4% of the singleton births at 23-41 weeks based on OE of gestational age were SGA infants (preterm SGA + term SGA). While all the preterm SGA infants were LBW, both preterm AGA and term SGA infants had a higher prevalence of LBW. Conclusions: In California, during the 10 years from 2005 to 2014, there was no significant decline in the prevalence of LBW. However, maternal age was a significant risk factor for LBW regardless of maternal race and ethnicity or education level. Therefore, there may be opportunities to reduce the prevalence of LBW by reducing disparities and improving birth outcomes for women of advanced maternal age.

G3 (Bethesda) ; 5(10): 2155-64, 2015 Aug 18.
Artigo em Inglês | MEDLINE | ID: mdl-26290571


A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors have proposed a GSI; however, they have not used simulated or real data to validate the GSI theory and have not explained how to estimate the GSI selection response and the GSI expected genetic gain per selection cycle for the unobserved traits after the first selection cycle to obtain information about the genetic gains in each subsequent selection cycle. In this paper, we develop the theory of a GSI and apply it to two simulated and four real data sets with four traits. Also, we numerically compare its efficiency with that of the phenotypic selection index (PSI) by using the ratio of the GSI response over the PSI response, and the PSI and GSI expected genetic gain per selection cycle for observed and unobserved traits, respectively. In addition, we used the Technow inequality to compare GSI vs. PSI efficiency. Results from the simulated data were confirmed by the real data, indicating that GSI was more efficient than PSI per unit of time.

Simulação por Computador , Modelos Genéticos , Seleção Genética , Algoritmos , Conjuntos de Dados como Assunto