Biomedical subjects

Rachel Gold

Publications and source records attributed to Rachel Gold.

4 recordsLinked to original sources

PubMed2006

Race/ethnicity, socioeconomic status, and lifetime morbidity burden in the women's health initiative: a cross-sectional analysis.

OBJECTIVES: We sought to assess the extent to which race/ethnicity and socioeconomic status (SES) are independently and jointly related to lifetime morbidity burden by comparing the impact of SES on lifetime morbidity among women of different racial/ethnic groups: white, black, Hispanic, American Indian/Alaska Native (AIAN), and Asian/Pacific Islander (API). METHODS: Using baseline data from the Women's Health Initiative (WHI), a national study of 162,000 postmenopausal women, we measured lifetime morbidity burden using a modified version of the Charlson Index, and measured SES with educational attainment and household income. In multivariable simple polytomous logistic regression models, we first assessed the effect of SES on lifetime morbidity burden among women of each racial/ethnic group, then assessed the combined effect of race/ethnicity and SES. RESULTS: Five percent of all women in the study population had high lifetime morbidity burden. Women with high lifetime morbidity were more likely to be AIAN or black; poor; less educated; divorced, separated, or widowed; past or current smokers; obese; uninsured or publicly insured. Lower SES was associated with higher morbidity among most women. The extent to which morbidity was higher among lower SES compared to higher SES women was about the same among Hispanic women and white women, but was substantially greater among black and AIAN women compared with white women. CONCLUSIONS: This study demonstrates the importance of considering race/ethnicity and class together in relation to health outcomes.

Black or African American↗

PubMed2005

Predicting time to subsequent pregnancy.

OBJECTIVES: Women in poverty may benefit from avoiding closely spaced pregnancies. This study sought to identify predictive factors that could identify women at risk for closely spaced pregnancies. METHODS: We studied 20,028 women receiving welfare (cash assistance) from Washington State. Using Cox proportional hazards methods, we estimated the effects of individual- and community-level variables on time from an index birth until a subsequent pregnancy (between June 1992 and December 1999). Prediction models developed in a random half of our data were validated in the other half. Receiver operator characteristic plots appropriate for proportional hazards models were calculated to compare the sensitivity and specificity of each model. RESULTS: At 5 years of follow-up, the most predictive model contained just individual-level variables (age, education, race, marital status, number of prior pregnancies); the area under the receiver operator characteristic curve was 0.66 (.62-.69). The addition of community-level variables (percent in poverty, with a high school degree or higher, Black, Hispanic, in an urban area; female unemployment rate; income inequality) added little predictive ability. Differences were found between women with different individual- and community-level characteristics, but the results suggest that these factors are not strong predictors of pregnancy spacing. CONCLUSIONS: Individual- and community-level characteristics are associated with interpregnancy intervals; however, we found little evidence that the selected variables predicted pregnancy interval in a useful manner.

Adolescent↗

PubMed2005

Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force.

BACKGROUND: Childhood and adolescent overweight and obesity are related to health risks, medical conditions, and increased risk of adult obesity, with its attendant effects on morbidity and mortality rates. The prevalence of childhood overweight and obesity has more than doubled in the past 25 years. Purpose. This evidence synthesis examines the evidence for the benefits and harms of screening and early treatment of overweight among children and adolescents in clinical settings. METHODS: We developed an analytic framework and 7 key questions representing the logical evidence connecting screening and weight control interventions with changes in overweight and behavioral, physiologic, and health outcomes in childhood or adulthood. We searched the Cochrane Library from 1996 to April 2004. We searched Medline, PsycINFO, DARE, and CINAHL from 1966 to April 2004. One reviewer abstracted relevant information from each included article into standardized evidence tables, and a second reviewer checked key elements. Two reviewers quality-graded each article with US Preventive Services Task Force criteria. RESULTS: Although BMI is a measure of relative weight rather than adiposity, it is recommended widely for use among children and adolescents to determine overweight and is the currently preferred measure. The risk of adult overweight from childhood overweight provides the best available evidence to judge the clinical validity of BMI as an overweight criterion for children and adolescents. BMI measures in childhood track to adulthood moderately or very well, with stronger tracking seen for children with >or=1 obese parent and children who are more overweight or older. The probability of adult obesity (BMI of >30 kg/m(2)) is >or=50% among children >13 years of age whose BMI percentiles meet or exceed the 95th percentile for age and gender. BMI-based overweight categorization for individuals, particularly for racial/ethnic minorities with differences in body composition, may have limited validity because BMI measures cannot differentiate between increased weight for height attributable to relatively greater fat-free mass (muscle, bone, and fluids) and that attributable to greater fat. No trials of screening programs to identify and to treat childhood overweight have been reported. Limited research is available on effective, generalizable interventions for overweight children and adolescents that can be conducted in primary care settings or through primary care referrals. CONCLUSIONS: BMI measurements of overweight among older adolescents identify those at increased risk of developing adult obesity. Interventions to treat overweight adolescents in clinical settings have not been shown to have clinically significant benefits, and they are not widely available. Screening to categorize overweight among children under age 12 or 13 who are not clearly overweight may not provide reliable risk categorization for adult obesity. Screening in this age group is compromised by the fact that there is little generalizable evidence for primary care interventions. Because existing trials report modest short- to medium-term improvements (approximately 10-20% decrease in percentage of overweight or a few units of change in BMI), however, overweight improvements among children and adolescents seem possible.

Adolescent↗

PubMed2002

Teen births, income inequality, and social capital: developing an understanding of the causal pathway.

Many studies have demonstrated a relationship between income inequality and poor health, but how does income inequality impact health? One possible explanation is that greater income inequality undermines social capital (social cohesion, civic engagement, and mutual trust in a community). We conducted path analyses of the relationship between income inequality, poverty, and teen birth rate, testing for the mediating effect of social capital in 39 US states. Birth rate was affected by both poverty and income inequality, though income inequality appeared to affect teen birth rate primarily through its impact on social capital.

Adolescent↗