A cross-sectional analysis of factors associated with the teachable moment concept and health behaviors during pregnancy.

BACKGROUND: Pregnancy is often associated with a change in health behaviors, leading some to suggest that pregnancy could be a teachable moment for lifestyle change. However, the prevalence and underlying mechanism of this phenomenon is not well understood. The aim of this study is to explore the prevalence of a teachable moment during pregnancy, the psychosocial factors that are associated with experiencing such a moment, and its association with actual health behaviors. METHODS: In this cross-sectional study, 343 pregnant Dutch women completed an online questionnaire. Participants reported on their intentions to change lifestyle due to pregnancy, their current health behaviors, and several psychosocial factors that were assumed to be linked to perceiving a teachable moment during pregnancy: perceived risk, affective impact, changed self-concept, and social support. Multivariable linear and logistic regression were applied to the data analysis. RESULTS: Results demonstrate that 56% of the women experienced a teachable moment based on intentions to change their health behavior. Multivariate regression analyses revealed that changed self-concept (ß = 0.21; CI = 0.11-0.31), positive affect (positive ß = 0.28; CI = 0.21-0.48), and negative affect (ß = 0.12; CI = 0.00-0.15) were associated with higher intentions to change health behavior. Conversely, more perceived risk was associated with lower intentions to change health behavior (ß=-0.29; CI = 0.31 - 0.13). Multivariate regression analyses showed a positive association between intentions to change health behavior and diet quality (ß = 0.11; CI = 0.82-1.64) and physical activity (OR = 2.88; CI = 1.66-5.00). CONCLUSIONS: This study suggests that pregnancy may be experienced as a teachable moment, therefore providing an important window of opportunity for healthcare professionals to efficiently improve health behaviors and health in pregnant women and their children. Results suggest that healthcare professionals should link communication about pregnancy-related health behaviors to a pregnant women's change in identity, affective impact (predominantly positive affective impact) and risk perception to stimulate the motivation to change healthy behavior positively.

Association between skeletal muscle index prior to liver transplantation and 1-year mortality posttransplant.

BACKGROUND: Liver transplantation is the only curative therapy for end-stage liver disease (ESLD). Sarcopenia is often defined as the loss of muscle quantity (skeletal muscle index [SMI]), but muscle attenuation (MA), a surrogate marker of muscle quality, is also decreased in ESLD. We assessed pre-liver transplant SMI and MA and their association with posttransplant mortality, complications, and length of intensive care unit (ICU) and hospital stay. METHODS: In 169 consecutive patients with ESLD who underwent a liver transplantation between 2007 and 2014, SMI and MA were measured on computed tomography scans at time of placement on the waiting list for liver transplantation. The primary outcome of interest was 1-year posttransplant mortality. Secondary posttransplantation outcomes of interest were complications within 30 days and length of stay in the ICU > 3 days and in the hospital >3 weeks. Logistic and Cox regression analyses were performed. RESULTS: MA was associated with 1-year posttransplant mortality rate (hazard ratio=0.656, 95% CI=0.464-0.921, P = 0.015). The highest quartile of SMI had a lower odds for the total length of stay in the hospital lasting >3 weeks (odds ratio=0.211, 95% CI=0.061-0.733, P = 0.014). MA was associated with a prolonged ICU stay; this was, however, not statistically significant after adjustment for age, sex, and Model for ESLD score. CONCLUSION: Lower MA is associated with a longer length of ICU stay and 1-year mortality after liver transplantation, whereas low SMI was associated with a total length of hospital stay.

Visceral adipose tissue is a better predictor than BMI in the alternative Fistula Risk Score in patients undergoing pancreatoduodenectomy.

BACKGROUND: Muscle attenuation (MA) and visceral adipose tissue (VAT) have not yet been included in the currently used alternative Fistula Risk Score (a-FRS). The aim of this study was to examine the added value of these parameters as predictors of clinically relevant postoperative pancreatic fistula (CR-POPF) in the a-FRS after pancreatoduodenectomy compared to Body Mass Index (BMI). METHODS: A single center retrospective cohort study was performed in patients who underwent pancreatoduodenectomy between 2009 and 2018. The a-FRS model was reproduced, MA and VAT were both combined and separately added to the model instead of BMI using logistic regression analysis. Model discrimination was assessed by ROC-curves. RESULTS: In total, 329 patients were included of which 55 (16.7%) developed CR-POPF. The a-FRS model showed an AUC of 0.74 (95%CI: 0.68-0.80). In this model, BMI was not significantly associated with CR-POPF (p = 0.16). The MA + VAT model showed an AUC of 0.81 (95%CI: 0.75-0.86). VAT was significantly associated with CR-POPF (per cm2, OR: 1.01; 95%CI: 1.00-1.01; p < 0.001). The AUC of the MA + VAT model differed significantly from the AUC of the a-FRS model (p = 0.001). CONCLUSION: Visceral adipose tissue is of added value in the a-FRS compared to BMI in predicting CR-POPF in patients undergoing pancreatoduodenectomy.

Both muscle quantity and quality are predictors of waiting list mortality in patients with end-stage liver disease.

BACKGROUND AND AIMS: Malnutrition is highly prevalent in patients with end-stage liver disease (ESLD) and associated with impaired clinical outcome. Previous studies focused on one component of body composition and not in combination with nutritional intake, while both are components of the nutritional status. We aimed to evaluate the most important risk factors regarding body composition (muscle mass, muscle quality and fat mass) and nutritional intake (energy and protein intake) for waiting list mortality in patients with ESLD awaiting liver transplantation (LTx). METHODS: Consecutive patients with ESLD listed for LTx between 2007 and 2014 were investigated. Muscle mass quantity (Skeletal Muscle Mass Index, SMI), and muscle quality (Muscle Attenuation, MA), and various body fat compartments were measured on computed tomography using SliceOmatic. Nutritional intake (e.g. energy and protein intake) was assessed. Multivariable stepwise forward Cox regression analysis was used for statistical analysis. RESULTS: 261 Patients (mean age 54 years, 74.7% male) were included. Low SMI and MA were found to be statistically significant predictors of an increased risk for waiting list mortality in patients with ESLD, with a HR of 2.580 (95%CI 1.055-6.308) and HR of 9.124 (95%CI 2.871-28.970), respectively. No association between percentage adipose tissue, and protein and energy intake with waiting list mortality was found in this study. CONCLUSION: Both low muscle quantity and quality, and not nutritional intake, were independent risk factors for mortality in patients with ESLD.

Effect of Early Individualized Dietary Counseling on Weight Loss, Complications, and Length of Hospital Stay in Patients With Head and Neck Cancer: A Comparative Study.

Patients with head and neck cancer (HNC) are at risk for undernutrition. Dietary counseling during treatment has positive effects on nutritional status and quality of life, however, the effects of dietary counseling started before initiation of treatment are currently unknown. Therefore we assessed the effect of early individualized dietary counseling (DC) on weight loss, major complications, and length of hospital stay (LOS) in patients with HNC. Ninety-five newly diagnosed HNC patients with (risk of) undernutrition receiving DC were compared to 95 matched HNC patients receiving usual nutritional care (UC). Difference in weight change over time was analyzed by generalized estimating equations (GEE). Differences in complications and LOS were studied by Pearson chi-squared and student's t-tests. Weight change between diagnosis and end of treatment was -6.0 ± 6.9% (DC) and -5.4 ± 5.7% (UC; GEE: -0.4kg, 95% confidence interval: -1.2 to 0.5; P = 0.44). Less DC patients experienced overall postoperative complications (44%/70%, P = 0.04). No effect on major postoperative or (chemo)radiotherapy complications or LOS was found. This study showed a lower prevalence of overall postoperative complications in HNC patients receiving DC but could not demonstrate an effect on weight loss, other complications, and LOS.

Systematic screening for undernutrition in hospitals: predictive factors for success.

BACKGROUND & AIMS: Since 2007, systematic screening for undernutrition has become a performance indicator (PI) for hospitals within the National Benchmarks on Quality of Care of the Dutch Health Care Inspectorate (HCI). Its introduction was guided by a national implementation program. The aim of this study was to evaluate the screening results from 2007 to 2010 and to identify predictive factors for achieved screening results. METHODS: All 97 Dutch hospitals were obliged to report screening results to the HCI. An additional questionnaire was developed to determine hospital characteristics, including hospital type, size, participation in implementation program, screening tool used, use of electronic records, presence of hospital-wide or ward task forces, and protocol-defined referral. Multivariate linear regression analysis was used to identify predictive factors for the obtained screening results in 2010. RESULTS: The mean screening percentage increased from 51 ± 28% in 2007 (n = 75 hospitals, n = 340,000 patients) to 72 ± 17% in 2010 (n = 97; n = 1,050,000) (p < 0.01). Eighty-one hospitals returned the questionnaire. A higher screening percentage was associated with more clinical admissions (highest vs. lowest tertile: ß = 14.0, 95% CI 3.9-20.5; p < 0.01; middle vs. lowest: ß = 7.3, -0.8 to 15.6; p = 0.05), presence of protocol-defined referral to a dietician (ß = 10.5, 2.9-18.0; p < 0.01), and use of the SNAQ screening tool (vs. MUST: ß = 9.1, 1.7-16.6; p = 0.02). CONCLUSION: Screening percentages have increased significantly since the introduction of the PI. Screening was more frequent in hospitals which have more patient admissions, protocol-defined referral to a dietician, and who use the SNAQ screening tool. This information may assist in improving Dutch screening rates and in implementation in other countries.

High prevalence of undernutrition in Dutch community-dwelling older individuals.

OBJECTIVE: To examine the prevalence of undernutrition in community-dwelling older individuals (≥65 y) using data from various settings. METHODS: A cross-sectional observational study was performed to examine the prevalence of undernutrition in three samples (all ≥65 y): 1) 1267 community-dwelling individuals participating in a large prospective population-based study, the Longitudinal Aging Study Amsterdam (LASA) in 1998/99; 2) 814 patients receiving home care in 2009/10; and 3) 1878 patients from general practices during the annual influenza vaccination in 2009/10. Undernutrition was assessed by the Short Nutritional Assessment Questionnaire 65+. RESULTS: Mean age was 77.3 y (SD 6.7) in the LASA sample, 81.6 y (SD 7.4) in the home care sample, and 75.3 y (SD 6.5) in the general practice sample. The prevalence of undernutrition was highest in the home care sample (35%), followed by the general practice (12%) and LASA (11%) samples. The prevalence of undernutrition increased significantly with age in the general practice and LASA samples. Gender differences were observed in the general practice and home care samples; women were more likely to be undernourished in the general practice sample and men were more likely to be undernourished in the home care sample. CONCLUSION: The prevalence of undernutrition in Dutch community-dwelling older individuals was relatively high, especially in home care patients.

Rehabilitation patients: undernourished and obese?

BACKGROUND: The aim of this study was to assess the prevalence of undernutrition in patients in Dutch rehabilitation centres and to measure the diagnostic accuracy of available screening tools. METHODS: This cross-sectional multicentre study was conducted in 11 rehabilitation centres in The Netherlands. Patient's nutritional status was determined by the amount of weight loss during the last 1, 3 and 6 months and body mass index (BMI). Diagnostic accuracy was assessed for 5 screening tools: Short Nutritional Assessment Questionnaire (SNAQ), Short Nutritional Assessment Questionnaire Residential Care (SNAQRC), SNAQ65+, Malnutrition Universal Screening Tool and Mini nutrition Assessment-short form. RESULTS: Twenty-eight percent of the patients were severely undernourished and 10% were moderately undernourished. In the undernourished group, 28% were overweight (BMI 25-30) and 19% were obese (BMI > 30). The SNAQ65+ is the recommended screening tool due to its high diagnostic accuracy (sensitivity 96%, specificity 77%, positive predictive value 62%, negative predictive value 90%) and quick and easy use. The MNA had the worst diagnostic accuracy, with a sensitivity of 44%. CONCLUSION: The prevalence of undernutrition in patients in Dutch rehabilitation centres is high. Almost half of the undernourished patients were overweight or obese. Therefore, it is important not only to screen for undernutrition, but also carefully to assess possible overweight/obesity in every undernourished rehabilitation patient.

Predictors for achieving protein and energy requirements in undernourished hospital patients.

BACKGROUND & AIMS: Providing sufficient protein an energy is considered crucial in the treatment of undernutrition. Still, the majority of undernourished hospital patients have a suboptimal protein and energy intake. The aim of this study was to investigate predictors for achieving protein and energy requirements on the fourth day of admission in undernourished hospitalized patients. METHODS: 830 adult undernourished patients (SNAQ ≥ 3) were retrospectively included. Intake requirements were defined as ≥1.2 g protein per kg bodyweight and ≥100% of the energy requirement based on calculated resting energy expenditure according to Harris & Benedict + 30%. Logistic regression analyses were performed to investigate predictors for achieving the requirements. RESULTS: Protein and energy intake had been recorded for 610 patients, of whom 25.6% had sufficient protein and energy intake. Protein requirements were less commonly met than energy requirements. Complete case analyses (n = 575) showed that negative predictors for achieving the protein and energy requirements were: nausea (OR = 0.18; 95%CI = 0.06-0.53), cancer (0.57; 0.35-0.93), acute infections (0.63; 0.37-1.01) and higher BMI (0.84; 0.79-0.89). Positive predictors were: a higher age (1.01; 1.00-1.03), chronic lung disease (3.76; 2.33-6.07) and receiving tube feeding (3.89; 1.56-9.73). CONCLUSION: Only one in four undernourished hospital patients meets the predefined protein and energy requirements on the fourth day of admission. Nausea, cancer, acute infections, BMI, age, chronic lung disease and tube feeding were identified as predictors for achieving protein and energy intake.

Prevalence of undernutrition in Dutch hospital outpatients.

BACKGROUND: The prevalence of undernutrition in hospital inpatients is high. Earlier detection and treatment in the hospital outpatient clinic may help to reduce these numbers. The purpose of this study was to assess the prevalence of undernutrition in hospital outpatients in the Netherlands, to determine high risk departments, and to determine the percentage of patients receiving dietetic treatment. METHODS: This cross-sectional multicenter study was conducted in nine hospitals. Patients who visited the outpatient clinic on one of the screening days in the period March-May 2008 received a short questionnaire and were weighed. Patients were classified as severely undernourished, moderately undernourished or not undernourished. RESULTS: 2288 patients were included in the study, of which 5% were severely undernourished and 2% were moderately undernourished. The prevalence of severe undernutrition was highest in the outpatient departments of oral maxillofacial surgery (17%), oncology (10%), rehabilitation (8%), gastroenterology (7%) and pulmonology (7%). Only 17% of all severely undernourished and 4% of all moderately undernourished patients reported to receive dietetic treatment. CONCLUSION: The prevalence of undernutrition in hospital outpatients is generally low but largely undertreated. Future screening should focus on high risk departments.