A decades-long decline in sperm counts in Western countries has coincided with an increase in obesity rates, prompting study into their association. Few of these studies have incorporated men of color, the sperm health of whom is relatively unknown. The present exploratory study evaluated the association between body mass index (BMI), race, ethnicity, and sperm parameters among a diverse sample of U.S. men attending a Washington, DC physician practice. Semen samples were collected and processed at a single laboratory and sperm concentration, motility, morphology, and count were evaluated according to World Health Organization (WHO) 5th edition criteria. Multivariate models accounted for covariates related to sperm health. The study population ( n = 128) was largely obese (45.3%) or overweight (34.4%), and 36.0% were black or Hispanic. Black men had lower adjusted sperm concentration compared to white men (75.0 million/mL to 107.4 million/mL, p = .01) and were more likely to have oligozoospermia ( p = .01), asthenozoospermia ( p = .004), and low sperm count ( p < .0001). Hispanic men had higher adjusted sperm concentration compared to non-Hispanic men (124.5 million/mL to 62.1 million/mL, p = .007) and were less likely to have teratozoospermia ( p = .001). Obesity and BMI were associated with lower sperm motility and count in crude models only. Given the study’s sample size its findings should be interpreted with caution but align with the limited epidemiological literature to date that has evaluated racial and ethnic differences in semen quality. Heightened clinical research attention is needed to ensure men of color are included in representative numbers in studies of urologic and andrologic health.

Previous studies suggest that at around 40 years of age, pregnancy rates achieved by IVF programmes fall and pregnancy loss rates increase. The actual age at which this occurs has not been clearly delineated. This study of 2,692 patients including 94 aged 41 or over shows that satisfactory pregnancy rates can be achieved up to and including age 40. As age 40 is approached the pregnancy loss rate increases to around 40%. In the 41 years and over group the pregnancy rate was poor at 6% (6/94) and the pregnancy loss rate very discouraging at 83% (5/6).

Rationale. We hypothesized that certain dietary components such as increased fat intake are associated with severity of obstructive sleep apnea (OSA). Methods. A total of 104 patients, diagnosed with OSA completed a validated dietary survey. The apnea-hypopnea index (AHI) was used to measure the severity of OSA. Subjects were divided using body mass index (BMI) into obese and overweight categories. Regression analysis was performed to predict severity of OSA from gender, BMI, age, % energy from fat, and the individual dietary components of the survey. Results. Overweight subjects who ate a diet high in fat (>35% of their total diet) had twice the severity of sleep apnea (AHI 18.2 ± 10.1 vs 36.6 ± 27.5; P = .001). There was a strong trend ( P = .056) in OSA severity between subjects eating processed meats “often” (AHI 42.5 ± 30.7) versus those eating “rarely/never” (AHI 28.9 ± 22.7). Eating greater than 2 servings of dairy daily was associated with worsening severity of OSA (AHI 26.2 ± 15.6 vs 39.7 ± 31; P = .04]. Conclusions. Dietary components such as fat intake and processed meats were associated with increased risk of OSA severity. In addition, 2 servings of dairy foods were associated with a decreased severity of OSA at presentation.

Introduction Adverse childhood experiences (ACEs) have been associated with physical and emotional problems such as obesity and depression in adulthood. This study evaluated the relationship between ACE scores and the severity of obesity. Methods We conducted a cross-sectional study of 119 adult patients at the GW Weight Management Clinic. They filled out an ACE survey examining trauma and household dysfunction. The main outcome was the severity of obesity measured by Body Mass Index (BMI). We estimated the adjusted mean difference between high and low ACE risk groups using - linear regression. Results The data suggest a positive relationship between ACE score and BMI. Patients with severe obesity are more likely to be a high ACE risk (50%) compared to others (24–25%). The average BMI in the high ACE risk group is 3.64 (95% CI: 0.25–7.03) higher than those in the low ACE risk group. The linear regression also showed that as the ACE score increased by 1, BMI increased by 1 unit (95% CI: 0.15–1.77). Conclusions Our findings suggest ACE is not just related with the prevalence of obesity, but also the severity of obesity in the overweight and obese population. The linear regression also showed that as the ACE score increased by 1, the BMI increased by 1 unit as well.