Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Jan 4;12(1):e054741.
doi: 10.1136/bmjopen-2021-054741.

Biological and clinical correlates of the patient health questionnaire-9: exploratory cross-sectional analyses of the baseline health study

Collaborators, Affiliations

Biological and clinical correlates of the patient health questionnaire-9: exploratory cross-sectional analyses of the baseline health study

Robert M Califf et al. BMJ Open. .

Abstract

Objectives: We assessed the relationship between the Patient Health Questionnaire-9 (PHQ-9) at intake and other measurements intended to assess biological factors, markers of disease and health status.

Design, setting and participants: We performed a cross-sectional analysis of 2365 participants from the Baseline Health Study, a prospective cohort of adults selected to represent major demographic groups in the USA. Participants underwent deep phenotyping on demographic, clinical, laboratory, functional and imaging findings.

Importance: Despite extensive research on the clinical implications of the PHQ-9, data are limited on the relationship between PHQ-9 scores and other measures of health and disease; we sought to better understand this relationship.

Interventions: None.

Main outcomes and measures: Cross-sectional measures of medical illnesses, gait, balance strength, activities of daily living, imaging and laboratory tests.

Results: Compared with lower PHQ-9 scores, higher scores were associated with female sex (46.9%-66.7%), younger participants (53.6-42.4 years) and compromised physical status (higher resting heart rates (65 vs 75 bpm), larger body mass index (26.5-30 kg/m2), greater waist circumference (91-96.5 cm)) and chronic conditions, including gastro-oesophageal reflux disease (13.2%-24.7%) and asthma (9.5%-20.4%) (p<0.0001). Increasing PHQ-9 score was associated with a higher frequency of comorbidities (migraines (6%-20.4%)) and active symptoms (leg cramps (6.4%-24.7%), mood change (1.2%-47.3%), lack of energy (1.2%-57%)) (p<0.0001). After adjustment for relevant demographic, socioeconomic, behavioural and medical characteristics, we found that memory change, tension, shortness of breath and indicators of musculoskeletal symptoms (backache and neck pain) are related to higher PHQ-9 scores (p<0.0001).

Conclusions: Our study highlights how: (1) even subthreshold depressive symptoms (measured by PHQ-9) may be indicative of several individual- and population-level concerns that demand more attention; and (2) depression should be considered a comorbidity in common disease.

Trial registration number: NCT03154346.

Keywords: anxiety disorders; depression & mood disorders; mental health; public health.

PubMed Disclaimer

Conflict of interest statement

Competing interests: RMC: Employee of Verily Life Sciences and Google Health; Board member for Cytokinetics, Centessa, Keystone Symposia, the Center for Policy Analysis on Trade and Health, Clinical Research Forum, One Fifteen, Launch and Scale Speedometer, Think Tank, Human Health and Potential, United Medicines, Medicxi, and Clinetic. CW: Employee of Verily Life Sciences. MD: Consulting fees from Verily Life Sciences, Neuronix, Apollo Health, VitaKey, Neuroglee, Transposon, Otsuka; Research grants from Avanir, Lilly, Avid, Salix; Holds stock in Evidation Health, Advera Health Analytics, Transposon Therapeutics, Marvel Biome; Board membership in Apollo; Coinventor on patents for diagnosis or treatment of neuropsychiatric disorders. DSH: Research funding from NIMH; Consulting for Little Otter. DPM: Employee of and holds stock in Verily Life Sciences. JLM: Employee of Verily Life Sciences.

Figures

Figure 1
Figure 1
Top 30 factors associated with PHQ-9 score adjusted by age, sex, and age by sex interaction. LASSO regression model one comprised age, sex, and age by sex interaction. The LASSO-predicted value was used to estimate a covariate-adjusted effect for all other candidate variables. BMI, body mass index; LASSO, least absolute shrinkage and selection operator; PHQ-9, Patient Health Questionnaire-9; WBC, white blood cell.
Figure 2
Figure 2
Top 30 factors associated with PHQ-9 score adjusted by age, sex, age by sex interaction, race, ethnicity, socioeconomic status and health behaviours. LASSO regression model two comprised age, sex, age by sex interaction, race, ethnicity, socioeconomic status and health behaviours. The LASSO-predicted value was used to estimate a covariate-adjusted effect for all other candidate variables. BMI, body mass index; LASSO, least absolute shrinkage and selection operator; PHQ-9, Patient Health Questionnaire-9.
Figure 3
Figure 3
Top 30 factors associated with PHQ-9 score adjusted by age, sex, age by sex interaction, race, ethnicity, socioeconomic status, health behaviours, and medical conditions. LASSO regression model 3 comprised age, sex, age by sex interaction, race, ethnicity, socioeconomic status, health behaviours and medical conditions (except mental health disorder diagnoses or disorders directly related to mental health or depression). The LASSO-predicted value was used to estimate a covariate-adjusted effect for all other candidate variables. BMI, body mass index; LASSO, least absolute shrinkage and selection operator; PHQ-9, Patient Health Questionnaire-9.
Figure 4
Figure 4
Top 30 factors associated with PHQ-9 score adjusted by age, sex, age by sex interaction, race, ethnicity, socioeconomic status, health behaviours, medical conditions, symptoms and allergies. LASSO regression model 4 comprised age, sex, age by sex interaction, race, ethnicity, socioeconomic status, health behaviours, medical conditions (except mental health disorder diagnoses or disorders directly related to mental health or depression), symptoms (except those that are directly related to mental health or depression) and allergies. The LASSO-predicted value was used to estimate a covariate-adjusted effect for all other candidate variables. ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; HbA1c, haemoglobin A1c; LASSO, least absolute shrinkage and selection operator; MCH, mean corpuscular haemoglobin; MCHC, mean corpuscular haemoglobin concentration; PHQ-9, Patient Health Questionnaire-9; RBC, red blood cell; WBC, white blood cell.
Figure 5
Figure 5
Top 30 factors associated with PHQ-9 score adjusted by age, sex, age by sex interaction, race, ethnicity, socioeconomic status, health behaviours, medical conditions, symptoms, allergies and physical function. LASSO regression model 5 comprised age, sex, age by sex interaction, race, ethnicity, socioeconomic status, health behaviours, medical conditions (except mental health disorder diagnoses or disorders directly related to mental health or depression), symptoms (except those that are directly related to mental health or depression), allergies, and physical function. The LASSO-predicted value was used to estimate a covariate-adjusted effect for all other candidate variables. ALT, alanine aminotransferase; AST, aspartate aminotransferase; GFR, glomerular filtration rate; HbA1c, haemoglobin A1c; HDL, high density lipoprotein; LASSO, least absolute shrinkage and selection operator; LDL, low density lipoprotein; MCH, mean corpuscular haemoglobin; MCHC, mean corpuscular haemoglobin concentration; MCV, mean corpuscular volume; MDRD, modification of diet in renal disease; MPV, mean platelet volume; pH, potential hydrogen; PHQ-9, Patient Health Questionnaire-9; RBC, red blood cell; TSH, thyroid-stimulating hormone; WBC, white blood cell.

References

    1. GBD 2017 Disease and Injury Incidence and Prevalence Collaborators . Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the global burden of disease study 2017. Lancet 2018;392:1789–858. 10.1016/S0140-6736(18)32279-7 - DOI - PMC - PubMed
    1. Perry PJ. The interaction of major depression and medical illness, 2005. Available: https://www.medscape.org/viewarticle/517033
    1. Kampling H, Baumeister H, Bengel J, et al. . Prevention of depression in adults with long-term physical conditions. Cochrane Database Syst Rev 2021;3:CD011246. 10.1002/14651858.CD011246.pub2 - DOI - PMC - PubMed
    1. Zhdanava M, Kuvadia H, Joshi K, et al. . Economic burden of treatment-resistant depression in privately insured U.S. patients with physical conditions. J Manag Care Spec Pharm 2020;26:996–1007. 10.18553/jmcp.2020.20017 - DOI - PMC - PubMed
    1. Rosenblat JD, Kurdyak P, Cosci F, et al. . Depression in the medically ill. Aust N Z J Psychiatry 2020;54:346–66. 10.1177/0004867419888576 - DOI - PubMed

Publication types

Associated data

LinkOut - more resources