Development and validation of a depression risk prediction nomogram for US Adults with hypertension, based on NHANES 2007–2018

{"Background": "Depression is a leading cause of disability globally, affecting approximately 300 million people worldwide and about 8% of US adults. Hypertension is strongly associated with depression, with hypertensive patients showing higher prevalence of depressive symptoms compared to non-hypertensive individuals. Despite this known association, few clinical predictive models exist specifically for depression risk in hypertensive patients. The nomogram is a widely used prognostic tool in medicine that allows estimation of individual event probabilities. This study aimed to develop and validate a nomogram for predicting depression risk in US adults with hypertension using the National Health and Nutrition Examination Survey (NHANES) database from 2007 to 2018.", "Methods": "Data were drawn from six NHANES survey cycles (2007\u20132018). Hypertension was defined per ACC/AHA guidelines as systolic blood pressure >130 mmHg and/or diastolic blood pressure >80 mmHg. Inclusion criteria were adults aged \u226520 years with hypertension who completed demographic surveys, physical exams, and questionnaires. After excluding those with missing data for key variables, the final study population comprised 13,293 participants. Depression was assessed using the PHQ-9 scale, with a score of \u226510 considered indicative of depression. Demographic characteristics (age, sex, race, marital status, education), medical history (diabetes, coronary heart disease, heart failure, myocardial infarction, stroke, cancer), lifestyle factors (smoking, alcohol use, sleep time on workdays, sedentary time), and anthropometric measures (BMI, waist circumference, poverty-to-income ratio) were collected. The dataset was randomly split into training (70%) and validation (30%) sets. Univariate and multivariate logistic regression (incorporating NHANES sample weights) were used to identify independent predictors of depression in the training set. A nomogram was constructed based on significant predictors. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).", "Key Results": "Of the 13,293 hypertensive participants, 1,269 had depression (902 in training set, 367 in validation set). The mean age was 54.08 years, mean BMI 30.80 kg/m\u00b2, mean poverty-to-income ratio 3.04, mean sleep time 7.11 hours, mean sedentary time 378.38 minutes, and mean waist circumference 104.82 cm. Among depressed patients, 493 were male and 776 were female. Multivariate logistic regression identified 11 independent predictors included in the nomogram: age (OR 0.99 per year, 95% CI 0.98\u20131.00, p=0.007), male sex (OR 0.48, 95% CI 0.39\u20130.61, p<0.001), race (Non-Hispanic Black vs. White: OR 0.60, 95% CI 0.48\u20130.75, p<0.001), education (college graduate or above vs. less than 9th grade: OR 0.58, 95% CI 0.36\u20130.92, p=0.02), marital status (married/living with partner vs. never married: OR 0.67, 95% CI 0.48\u20130.93, p=0.02), poverty-to-income ratio (OR 0.78, 95% CI 0.71\u20130.85, p<0.001), sleep time on workdays (OR 0.84, 95% CI 0.77\u20130.91, p<0.001), sedentary time (OR 1.00, 95% CI 1.00\u20131.00, p=0.002), current smoking (OR 2.31, 95% CI 1.72\u20133.10, p<0.001), former alcohol use now abstaining (OR 1.87, 95% CI 1.25\u20132.80, p=0.003), and heart failure (OR 1.58, 95% CI 1.02\u20132.44, p=0.04). The ROC analysis showed an AUC of 0.757 (sensitivity 0.586) for the training set and an AUC of 0.724 (sensitivity 0.626) for the validation set. Calibration curves demonstrated good agreement between predicted and observed probabilities. Decision curve analysis confirmed the nomogram's clinical usefulness across a range of threshold probabilities.", "Clinical Implications": "This nomogram provides a practical, clinically accessible tool for estimating depression risk in hypertensive patients using easily obtainable variables. The model highlights several modifiable risk factors\u2014including smoking, alcohol use, sleep duration, and sedentary time\u2014that could be targeted in preventive interventions. The finding that women with hypertension have approximately 50% higher risk of depression than men underscores the need for gender-sensitive screening approaches. The strong association between lower socioeconomic status (lower income and education) and depression risk suggests that mental health screening should be prioritized in disadvantaged populations with hypertension. The study's limitations include reliance on self-reported data for some variables, potential selection bias from excluding participants with missing data, lack of external validation, and restriction to the US population, which may limit generalizability to other cultural contexts."}