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Psychosocial stress and changes in estimated glomerular filtration rate among adults with diabetes mellitus.

Annor FB, Masyn KE, Okosun IS, Roblin DW, Goodman M - Kidney Res Clin Pract (2015)

Bottom Line: The psychosocial stress variable was not directly associated with eGFR in the final model.Factors found to be associated with changes in eGFR were age, race, insulin use, and mean arterial pressure.Among fairly healthy DM patients, we did not find any evidence of a direct association between psychosocial stress and eGFR changes after controlling for important covariates.

View Article: PubMed Central - PubMed

Affiliation: School of Public Health, Georgia State University, Atlanta, GA, USA.

ABSTRACT

Background: Psychosocial stress has been hypothesized to impact renal changes, but this hypothesis has not been adequately tested. The aim of this study was to examine the relationship between psychosocial stress and estimated glomerular filtration rate (eGFR) and to examine other predictors of eGFR changes among persons with diabetes mellitus (DM).

Methods: Data from a survey conducted in 2005 by a major health maintenance organization located in the southeastern part of the United States, linked to patients' clinical and pharmacy records (n=575) from 2005 to 2008, was used. Study participants were working adults aged 25-59 years, diagnosed with DM but without advanced microvascular or macrovascular complications. eGFR was estimated using the Modification of Diet in Renal Disease equation. A latent psychosocial stress variable was created from five psychosocial stress subscales. Using a growth factor model in a structural equation framework, we estimated the association between psychosocial stress and eGFR while controlling for important covariates.

Results: The psychosocial stress variable was not directly associated with eGFR in the final model. Factors found to be associated with changes in eGFR were age, race, insulin use, and mean arterial pressure.

Conclusion: Among fairly healthy DM patients, we did not find any evidence of a direct association between psychosocial stress and eGFR changes after controlling for important covariates. Predictors of eGFR change in our population included age, race, insulin use, and mean arterial pressure.

No MeSH data available.


Related in: MedlinePlus

Graphical representation of the final growth model.* A1c05–A1c08: Glycosylated hemoglobin measure from 2005 to 2008, respectively.† eGFR5–eGFR8: estimated glomerular filtration rate from 2005 to 2008, respectively.‡ Coworker support.§ Supervisor support.‖ Job demand.¶ Work decision authority.A1c, glycosylated hemoglobin; BMI, body mass index; eGFR, estimated glomerular filtration rate; MAP, mean arterial pressure; Med Coverage, oral hypoglycemic agents coverage during 2005.
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f0005: Graphical representation of the final growth model.* A1c05–A1c08: Glycosylated hemoglobin measure from 2005 to 2008, respectively.† eGFR5–eGFR8: estimated glomerular filtration rate from 2005 to 2008, respectively.‡ Coworker support.§ Supervisor support.‖ Job demand.¶ Work decision authority.A1c, glycosylated hemoglobin; BMI, body mass index; eGFR, estimated glomerular filtration rate; MAP, mean arterial pressure; Med Coverage, oral hypoglycemic agents coverage during 2005.

Mentions: The percent missing on covariates ranged between 0% and 41%, and the percent pairwise coverage for the covariates ranged between 0.39 and 1.00. The percent missing for the stress indicators ranged between 0.5% and 1.6% with covariance coverage ranging between 0.98 and 1.00. For eGFR measures, 49% had a measure on all four waves, whereas 91% had a measure on at least two waves. To address the missing values on exogenous predictors, we performed multiple imputations (10 times) in SAS for the measurement and the growth models. Descriptive statistics was performed in SAS software, version 9.3 (SAS Institute Inc., Cary, NC, USA) [36], while all the other analyses were performed in Mplus statistical software, version 6.1 (Muthén & Muthén, Los Angeles, CA, USA) [37]. Latent psychosocial stress variable was specified using confirmatory factor analysis (CFA) by loading the stress subscales on the latent stress variable (Fig. 1). Bivariate regression analysis was performed between the latent psychosocial stress and selected covariates including age, race, insulin use, and MAP. An unconditional growth model was fit to the four eGFR waves. Without a priori hypothesis about the functional form of the relationship between psychosocial stress and eGFR over time, stress was specified with direct effects on the repeated measures to allow for the greatest flexibility to obtain a time-varying effect estimates in the final growth model (Fig. 1). We controlled for HbA1c measures, sociodemographic variables (sex, age, race, education, neighborhood-based socioeconomic status), smoking, body mass index, insulin use, medication coverage (proportion of days covered by OH), and MAP. Study participants were grouped into two—those who experienced decline in eGFR and those who did not and subgroup analysis was performed for the two groups. The robust maximum likelihood estimator was used. All statistical significance was determined at a two-sided alpha level of 0.05.


Psychosocial stress and changes in estimated glomerular filtration rate among adults with diabetes mellitus.

Annor FB, Masyn KE, Okosun IS, Roblin DW, Goodman M - Kidney Res Clin Pract (2015)

Graphical representation of the final growth model.* A1c05–A1c08: Glycosylated hemoglobin measure from 2005 to 2008, respectively.† eGFR5–eGFR8: estimated glomerular filtration rate from 2005 to 2008, respectively.‡ Coworker support.§ Supervisor support.‖ Job demand.¶ Work decision authority.A1c, glycosylated hemoglobin; BMI, body mass index; eGFR, estimated glomerular filtration rate; MAP, mean arterial pressure; Med Coverage, oral hypoglycemic agents coverage during 2005.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4608872&req=5

f0005: Graphical representation of the final growth model.* A1c05–A1c08: Glycosylated hemoglobin measure from 2005 to 2008, respectively.† eGFR5–eGFR8: estimated glomerular filtration rate from 2005 to 2008, respectively.‡ Coworker support.§ Supervisor support.‖ Job demand.¶ Work decision authority.A1c, glycosylated hemoglobin; BMI, body mass index; eGFR, estimated glomerular filtration rate; MAP, mean arterial pressure; Med Coverage, oral hypoglycemic agents coverage during 2005.
Mentions: The percent missing on covariates ranged between 0% and 41%, and the percent pairwise coverage for the covariates ranged between 0.39 and 1.00. The percent missing for the stress indicators ranged between 0.5% and 1.6% with covariance coverage ranging between 0.98 and 1.00. For eGFR measures, 49% had a measure on all four waves, whereas 91% had a measure on at least two waves. To address the missing values on exogenous predictors, we performed multiple imputations (10 times) in SAS for the measurement and the growth models. Descriptive statistics was performed in SAS software, version 9.3 (SAS Institute Inc., Cary, NC, USA) [36], while all the other analyses were performed in Mplus statistical software, version 6.1 (Muthén & Muthén, Los Angeles, CA, USA) [37]. Latent psychosocial stress variable was specified using confirmatory factor analysis (CFA) by loading the stress subscales on the latent stress variable (Fig. 1). Bivariate regression analysis was performed between the latent psychosocial stress and selected covariates including age, race, insulin use, and MAP. An unconditional growth model was fit to the four eGFR waves. Without a priori hypothesis about the functional form of the relationship between psychosocial stress and eGFR over time, stress was specified with direct effects on the repeated measures to allow for the greatest flexibility to obtain a time-varying effect estimates in the final growth model (Fig. 1). We controlled for HbA1c measures, sociodemographic variables (sex, age, race, education, neighborhood-based socioeconomic status), smoking, body mass index, insulin use, medication coverage (proportion of days covered by OH), and MAP. Study participants were grouped into two—those who experienced decline in eGFR and those who did not and subgroup analysis was performed for the two groups. The robust maximum likelihood estimator was used. All statistical significance was determined at a two-sided alpha level of 0.05.

Bottom Line: The psychosocial stress variable was not directly associated with eGFR in the final model.Factors found to be associated with changes in eGFR were age, race, insulin use, and mean arterial pressure.Among fairly healthy DM patients, we did not find any evidence of a direct association between psychosocial stress and eGFR changes after controlling for important covariates.

View Article: PubMed Central - PubMed

Affiliation: School of Public Health, Georgia State University, Atlanta, GA, USA.

ABSTRACT

Background: Psychosocial stress has been hypothesized to impact renal changes, but this hypothesis has not been adequately tested. The aim of this study was to examine the relationship between psychosocial stress and estimated glomerular filtration rate (eGFR) and to examine other predictors of eGFR changes among persons with diabetes mellitus (DM).

Methods: Data from a survey conducted in 2005 by a major health maintenance organization located in the southeastern part of the United States, linked to patients' clinical and pharmacy records (n=575) from 2005 to 2008, was used. Study participants were working adults aged 25-59 years, diagnosed with DM but without advanced microvascular or macrovascular complications. eGFR was estimated using the Modification of Diet in Renal Disease equation. A latent psychosocial stress variable was created from five psychosocial stress subscales. Using a growth factor model in a structural equation framework, we estimated the association between psychosocial stress and eGFR while controlling for important covariates.

Results: The psychosocial stress variable was not directly associated with eGFR in the final model. Factors found to be associated with changes in eGFR were age, race, insulin use, and mean arterial pressure.

Conclusion: Among fairly healthy DM patients, we did not find any evidence of a direct association between psychosocial stress and eGFR changes after controlling for important covariates. Predictors of eGFR change in our population included age, race, insulin use, and mean arterial pressure.

No MeSH data available.


Related in: MedlinePlus