Perfluoroalkyl substances and kidney function in chronic kidney disease, anemia, and diabetes

Background: Anemia often complicates chronic kidney disease (CKD), leading to insufficient tissue oxygenation and hypoxic injury, the factor thought to underlie progression from CKD to renal failure. Perfluorocarbons are potent oxygen transporters used in organ preservation and synthetic blood development. Data are scarce on their relationship with kidney function, especially in diabetes where anemia and hypoxia are more prevalent. We investigated the relationship of perfluoroalkyl acids (PFAS) with kidney function and variation by diabetes and anemia status. Methods: Data on 53,650 adults (5,210 with diabetes) were obtained from the C8 Health Project. CKD was defined as an estimated glomerular filtration rate (eGFR) \u3c60 mL/min/1.73 m2. Four PFAS were investigated: perfluorohexane sulfonate (PFHxS), perfluorooctanoic acid, perfluorooctane sulfonate, and perfluorononanoic acid. Findings: Each PFAS was positively associated with eGFR among those with CKD or anemia; this was the strongest among those with both CKD and anemia, followed by those with CKD uncomplicated by anemia. These relationships were more pronounced among those with diabetes (all P\u3c0.01). In the absence of both CKD and anemia, PFAS was inversely associated with eGFR. Among persons with both anemia and diabetes, when further stratified by CKD stage, compared to an eGFR \u3c30, ORs (95% CI) for being in the eGFR ≥ 90, 60–89, 45–59, and 30–45 range, respectively, were 3.20 (2.00–5.13), 2.64 (1.83–3.80), 3.18 (2.17–4.67), and 1.99 (1.38–2.86) for each ng/dL increase in PFHxS. Results were similar for each PFAS. Interpretation: PFAS are inversely associated with kidney function in CKD and diabetes, with a stronger relation observed when anemia is present

Age at Menarche, the Leg Length to Sitting Height Ratio, and Risk of Diabetes in Middle-Aged and Elderly Chinese Men and Women

To evaluate the associations of age at menarche and the leg length-to-sitting-height ratio, markers of adolescent growth, with risk of diabetes in later life.Information from 69,385 women and 55,311 men, aged 40-74 years from the Shanghai Women's Health Study and Shanghai Men's Health Study, were included in the current analyses. Diabetes status was ascertained through biennial in person follow-up. Cox models, with age as the time scale, were used.There were 2369 cases of diabetes (1831 women; 538 men) during an average of 7.3 and 3.6 years of follow-up of the women and men, respectively. In females, menarche age was inversely associated with diabetes risk after adjustment for birth cohort, education, and income (HR = 0.95, 0.92-0.98). In both genders, leg length-to-sitting-height ratio was inversely related to diabetes (HR = 0.88, 0.80-0.97 for men; HR = 0.91, 0.86-0.96 for women) after adjustment for birth cohort, education, and income. Further adjustment for adult BMI at study enrollment completely eliminated the associations of age at menarche (HR = 0.99, 0.96-1.02) and the leg length-to-sitting-height ratio (HR = 1.00, 0.91-1.10 for men; HR = 1.01, 0.96-1.07 for women) with diabetes risk.Our study suggests that markers of an early age at peak height velocity, i.e. early menarche age and low leg-length-to-sitting height ratio, may be associated with diabetes risk later in life and this association is likely to be mediated through obesity

Racial Differences in Hepatocellular Carcinoma Incidence and Risk Factors among a Low Socioeconomic Population

The purpose of this study was to examine differences in risk factors associated with hepatocellular carcinoma (HCC) among White and African Americans from low socioeconomic backgrounds in the Southern Community Cohort Study (SCCS). The SCCS is a prospective cohort study with participants from the southeastern US. HCC incidence rates were calculated. Multivariable Cox regression was used to calculate HCC-adjusted hazard ratios (aHR) associated with known baseline HCC risk factors for White and African Americans, separately. There were 294 incident HCC. The incidence rate ratio for HCC was higher (IRR = 1.4, 95%CI: 1.1–1.9) in African Americans compared to White Americans. White Americans saw a stronger association between self-reported hepatitis C virus (aHR = 19.24, 95%CI: 10.58–35.00) and diabetes (aHR = 3.55, 95%CI: 1.96–6.43) for the development of HCC compared to African Americans (aHR = 7.73, 95%CI: 5.71–10.47 and aHR = 1.48, 95%CI: 1.06–2.06, respectively) even though the prevalence of these risk factors was similar between races. Smoking (aHR = 2.91, 95%CI: 1.87–4.52) and heavy alcohol consumption (aHR = 1.59, 95%CI: 1.19–2.11) were significantly associated with HCC risk among African Americans only. In this large prospective cohort, we observed racial differences in HCC incidence and risk factors associated with HCC among White and African Americans

Risk of Diabetes in Middle Age by Age at Menarche, HR (95% CI).

<p> <b>Descriptive statistics for age at menarche by quintiles of age at menarche are: Quintile 1: mean = 12 years, range = 8–13 years, std = 0.56 years; Quintile 2: mean = 14years, range = 14–14 years, std = 0 years; Quintile 3: mean = 15 years, range = 15–15 years, std = 0 years; Quintile 4: mean = 16 years, range = 16–16 years, std = 0 years; Quintile 5: mean = 17 years, range = 17–26 years, std = 0. 89 years.</b></p><p>*Expressed as per standard deviation change.</p><p>Model 1: univariate analyses. Model 2 controlled for birth cohort, education and income. Model 3 controlled for birth cohort, education, income, and BMI at baseline. Model 4 controlled for birth cohort, education, income, BMI at age 20, BMI at baseline, and participation in team sports during adolescence.</p

Risk of Diabetes in Middle-aged and Older Chinese Women by Height Components, HR (95% CI).

<p><b>Descriptive statistics for height components by quintiles in women</b>: <b>Height (m):</b> Quintile 1: mean = 1.50, range = 1.19–1.54, std = 0.03; Quintile 2: mean = 1.55, range = 1.54–1.57, std = 0.008; Quintile 3: mean = 1.58, range = 1.57–1.60, std = 0.008; Quintile 4: mean = 1.61, range = 1.60–1.63, std = 0.009; Quintile 5: mean = 1.66, range = 1.63–1.86, std = 0.02. <b>Leg Length (cm):</b> Quintile 1: mean = 68.3, range = 0.40–0.70, std = 1.86; Quintile 2: mean = 71.4, range = 70–72.3, std = 0.59; Quintile 3: mean = 73.4, range = 72.3–74.0, std = 0.54; Quintile 4: mean = 75.4, range = 74.05–76.5, std = 0.60; Quintile 5: mean = 78.9, range = 76.5–105.0, std = 2.18. <b>Sitting height (cm):</b> Quintile 1: mean = 80.3, range = 52.0–82.0, std = 2.13; Quintile 2: mean = 83.5, range = 82.1–84.0, std = 0.53; Quintile 3: mean = 85.0, range = 84.1–85.9, std = 0.30; Quintile 4: mean = 86.5, range = 86.0–87.0, std = 0.47; Quintile 5: mean = 89.2, range = 87.1–105.0, std = 1.48.</p><p>*Expressed as per standard deviation change. Model 1: univariate analyses. Model 2 controlled for birth cohort, education, and income. Model 3 controlled for birth cohort, education, income, and BMI at baseline. Model 4 controlled for birth cohort, education, income, smoking before age 20, BMI at age 20, BMI at baseline, and participation in team sports during adolescence.</p

Age-adjusted Characteristics of Study Participants by Incident Diabetes Status: the Shanghai Women's and Shanghai Men's Health Study, mean (SD) or % (n).

<p>N/A = not applicable</p><p>* = p<0·05</p><p>**Low income = 1: less 1000 yuans, Middle income = 2: 1000–1999 yuans, High income = 3: > = 2000 yuans.</p

Risk of Diabetes in Middle-aged and Older Chinese Men by Height Components, HR (95% CI).

<p><b>Descriptive statistics for height components by quintiles in men:</b><b>Height (m):</b> Quintile 1: mean = 1.62, range = 1.15–1.65, std = 0.03; Quintile 2: mean = 1.67, range = 1.65–1.69, std = 0.009; Quintile 3: mean = 1.70, range = 1.69–1.72, std = 0.008; Quintile 4: mean = 1.73, range = 1.72–1.75, std = 0.008; Quintile 5: mean = 1.78, range = 1.75–1.96, std = 0.03. <b>Leg Length (cm):</b> Quintile 1: mean = 74.1, range = 37–76, std = 2.02; Quintile 2: mean = 77.5, range = 76.1–78.9, std = 0.61; Quintile 3: mean = 79.5, range = 79–80, std = 0.47; Quintile 4: mean = 81.4, range = 80–82.5, std = 0.61; Quintile 5: mean = 84.9, range = 82.5–101, std = 2.06. <b>Sitting height (cm):</b> Quintile 1: mean = 85.6, range = 56.087.9, std = 1.84; Quintile 2: mean = 88.6, range = 88.0–90.0, std = 0.53; Quintile 3: mean = 90.5, range = 90.0–91.5, std = 0.53; Quintile 4: mean = 92.4, range = 91.6–93.1, std = 0.47; Quintile 5: mean = 95.2, range = 93.1–108.0, std = 1.51.</p><p>*Expressed as per standard deviation change. Model 1: univariate analyses. Model 2 controlled for birth cohort, education, and income. Model 3 controlled for birth cohort, education, income, and BMI at baseline. Model 4 controlled for birth cohort, education, income, smoking before age 20, BMI at age 20, BMI at baseline, and participation in team sports during adolescence.</p