Determinants of life dissatisfaction among adults in the United States: A cross-sectional analysis of the National Health Interview Survey

Abstract

The number of Americans who report dissatisfaction with their quality of life has increased over the past several decades. This study investigated social- and health-related determinants of life dissatisfaction among adults in the United States (US). We conducted a cross-sectional observational study using data from the 2021 National Health Interview Survey, a nationally representative sample of adults in the US. We analyzed the association between self-reported life dissatisfaction and independent variables including demographics, family-level information, health status and conditions, functioning and disability, health insurance coverage, chronic pain, occupational variables, socioeconomic indicators, health-related behaviors, and psychological distress indicators. Survey multivariable logistic regression was used to determine the association among social- and health-related determinants and life dissatisfaction. The relative importance of each variable in the final model was determined using Shapley Additive Explanations values (0–100% scale). Among the 253.2 million civilian noninstitutionalized adults, 12.2 million (4.8%) reported life dissatisfaction. Recent psychological distress, unmarried status, poor general health, lack of social/emotional support, and lower food security were independently associated with life dissatisfaction (all P < .001). The relative importance of these variables in predicting life dissatisfaction was 39.3% for recent psychological distress, 22.2% for unmarried status, 18.3% for poor general health, 13.4% for lack of social/emotional support, and 6.9% for lower food security. Additionally, racial inequities were identified in the prevalence of these factors. Life dissatisfaction among adults in the US is associated with social- and health-related factors that are more prevalent in racial minority groups. The study findings suggest that resource prioritization should be targeted towards individuals with these factors, with particular emphasis on racial minority groups. This study aligns with US health policy initiatives and the results may help policymakers address the underlying factors contributing to life dissatisfaction among the US population.

1. Introduction

Surveillance of human well-being at the population level is essential for monitoring health trends over time and for identifying the determinants of well-being. The results of these surveillance efforts can inform policy decisions aimed at promoting health, reducing disparities, and addressing critical public health priorities and challenges. The US Department of Health and Human Services developed Healthy People 2030, a plan intended to promote, strengthen, and evaluate efforts to improve the health and well-being of Americans.^[1] Hundreds of measurable objectives were identified to monitor program progress during the decade. Each of these objectives are linked to resources that help organizations develop evidence-based health programs and policies.

A key objective of Healthy People 2030 is to improve life satisfaction, which is a subjective evaluation of overall contentment with life and well-being. As the primary Overall Health and Well-Being Measure, life satisfaction is an important metric to summarize and evaluate progress towards achieving the objectives of Healthy People 2030.^[2] Yet, the percentage of adults in the United States (US) reporting dissatisfaction in their quality of life tripled between 2001 and 2021.^[3] Although studies in highly selected subjects have reported factors contributing to life satisfaction and dissatisfaction,^[4–9] population-based studies on the topic are lacking. The purpose of this cross-sectional, population-based study was to determine the social- and health-related factors associated with life dissatisfaction among US adults and whether these factors differed by demographic status.

2. Methods

2.1. Study design and participants

This study used data from the 2021 National Health Interview Survey (NHIS),^[10] the primary source of health information on the civilian non-institutionalized population in the US. The NHIS is a cross-sectional household interview survey conducted annually to monitor the health of the US population. The NHIS employs geographically clustered sampling techniques that involve partitioning the US into geographic areas, with further division of some geographic areas into strata based on the population density. Adults within randomly selected households were interviewed in person or by telephone during the year. Questionnaires were administered between January and December 2021, resulting in 29,482 adult interviews, comprising a response rate of 50.9%.^[11] Written informed consent was obtained from all participants, and the National Centers for Health Statistics Ethics Review Committee approved the study. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology reporting guideline.^[12]

2.2. Outcomes

The primary outcome measure of this study was life dissatisfaction. Life satisfaction in the NHIS was assessed using the question, “In general, how satisfied are you with your life?” The response options included very satisfied, satisfied, dissatisfied, or very dissatisfied. Participants who responded dissatisfied or very dissatisfied were classified with life dissatisfaction for analysis purposes.

A priori, we identified variables collected in the NHIS shown to correlate with life satisfaction measures in previous studies.^[9,13,14] Variables were selected among categories including demographics, family-level information, health status and conditions, functioning and disability, health insurance coverage, chronic pain, occupational variables, socioeconomic indicators, health-related behaviors, and psychological distress. Demographic variables included the Urban-Rural Classification Scheme for Counties,^[15] geographic household region, age category, sex, racial category, and highest education level attained. The physical health of participants was assessed by inquiring about their general health status, body mass index calculated from self-reported height and weight, and frequency of pain over the last 3 months. Disability status was derived from the Washington Group Short Set Composite Disability Indicator.^[16] Medical history variables included history of cigarette smoking, hypertension, arthritis, cancer, diabetes mellitus, coronary heart disease, chronic lung disease, myocardial infarction, kidney disease, stroke, chronic fatigue syndrome, and dementia. The social, emotional, and financial characteristics of the sample included the frequency of social/emotional support over the last 12 months, serious psychological distress in the past 30 days calculated from the Kessler Psychological Distress Scale (K6),^[17] marital status, parental status, student status, employment, number of hours worked per week, health insurance coverage, family income as a proportion of the federal poverty level, food security derived from the 10-item US Adult Food Security Survey Module,^[18] length of time in residence, and residence ownership. A detailed list of these variables is provided in Table 1.

Table 1.

Listing of variable names and descriptors in the 2021 National Health Interview Survey (NHIS) included in the current study.

Variable name	Variable description
Administrative
HHX	Randomly assigned, unique household number
WTFA_A	Sampling weight
PSTRAT	Pseudo-stratum for public-use file variance estimation
PPSU	Pseudo-PSU for public-use file variance estimation
Life dissatisfaction
LSATIS4R_A	In general, how satisfied are you with your life?, user recoded into 2 categories
Demographic
URBRRL	2013 NCHS Urban-Rural Classification Scheme for Counties
REGION	Household region
AGEP_A	Age of sample adult (top coded), user recoded into 5 categories
SEX_A	Sex of sample adult
RACEALLP_A	Single and multiple race groups, user recoded into 5 categories
EDUCP_A	Educational top coded level of sample adult, user recoded into 6 categories
Physical health
PHSTAT_A	Would you say your health in general is excellent, very good, good, fair, or poor?
BMICAT_A	Categorical body mass index, calculated from self-report of height and weight
PAIFRQ3M_A	In the past 3 months, how often did you have pain?
DISAB3_A	Washington Group Short Set Composite Disability Indicator
SMKEV_A	Smoked at least 100 cigarettes in entire life
HYPEV_A	Ever been told by a doctor or other health professional that you had hypertension?
ARTHEV_A	Ever been told by a doctor or other health professional that you had some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?
CANEV_A	Ever been told by a doctor or other health professional that you had cancer or a malignancy of any kind?
DIBEV_A	Ever been told by a doctor or other health professional that you had diabetes?
CHDEV_A	Ever been told by a doctor or other health professional that you had coronary heart disease?
COPDEV_A	Ever been told by a doctor or other health professional that you had chronic obstructive pulmonary disease, COPD, emphysema, or chronic bronchitis?
MIEV_A	Ever been told by a doctor or other health professional that you had a heart attack, also called myocardial infarction?
KIDWEAKEV_A	Ever been told by a doctor or other health professional that you had weak or failing kidneys?
STREV_A	Ever been told by a doctor or other health professional that you had a stroke?
CFSEV_A	Ever been told by a doctor or other health professional that you had chronic fatigue syndrome or myalgic encephalomyelitis?
DEMENEV_A	Ever been told by a doctor or other health professional that you had dementia, including Alzheimer’s disease?
Social, emotional, financial
SUPPORT_A	How often do you get the social and emotional support you need?
K6SPD_A	Experienced serious psychological distress in past 30 days, calculated from the Kessler Psychological Distress Scale (K6)
MARITAL_A	Marital status
PARSTAT_A	Parental status
SCHCURENR_A	Currently enrolled in or attending school
EMPWRKLSW1_A	Currently employed
EMPWKHRS3_A	Hours worked per week (top coded), user recoded into 6 categories
NOTCOV_A	Current health coverage
POVRATTC_A	Ratio of family income to poverty threshold for sample adult’s family (top-coded), user recoded into 7 categories
FDSCAT3_A	Food security status, derived from the 10-item U.S. Adult Food Security Survey Module
HOUYRSLIV_A	Length of time living in current house or apartment
HOUTENURE_A	Residence owned or rented

2.3. Data analysis

Statistical analyses utilized complex sample methods that incorporated sampling weights, sample strata, and clusters, which were necessary to obtain accurate parameter estimates for the US population. Sample weights were calculated as the inverse of the probability of selection with additional adjustment for nonresponse patterns in order to estimate the number of persons in the population represented by each respondent. Taylor series linearization was used to estimate the variance in order to account for the stratified cluster sampling design. We used Fisher’s exact test to analyze the population-weighted life dissatisfaction proportion among the subject characteristic subgroups. Multivariate logistic regression was used to identify the association between subject characteristics and life dissatisfaction. The multivariate model used a best-subsets variable selection process based on the Akaike information criterion. We used a statistical machine learning approach, Shapley Additive Explanations (SHAP), to determine the relative importance of the variables in the final regression model. This analysis decomposes the regression model output and calculates SHAP values for each variable ranging from 0% to 100%.^[19] Finally, we determined the frequency of life dissatisfaction risk factors and calculated odds ratios to identify at-risk demographic subgroups. Statistical analyses were performed using Stata v16.1 (StataCorp, College Station, TX).

3. Results

The results of the analysis represented 253.2 million civilian noninstitutionalized adults in the US. Life dissatisfaction was reported in 4.8% of individuals, representing approximately 12.2 million US adults. Among the demographic subgroups, the highest percentage of adults reporting dissatisfaction with life was 7.8% among those reporting other/mixed race, 7.1% in individuals 85 years of age or older, 6.8% among individuals with less than a high school education, and 6.0% among those reporting Black/African American race (Table 2). Among subgroups of physical health characteristics, the highest percentage of adults dissatisfied with life was 32.9% among those self-reporting poor general health status, 22.2% in individuals with dementia, 20.7% in individuals with chronic fatigue syndrome, and 18.2% in individuals with a disability. All physical health subgroup categories were significantly associated with life dissatisfaction (all P < .001) (Table 3). Among the social, emotional, and financial factors, the highest percentage of adults dissatisfied with life was 38.9% among those reporting serious psychological distress in the past 30 days, 22.9% in those reporting very low food security, and 17.0% in those receiving social/emotional support rarely or never in the past 12 months. All social, emotional, and financial factors were significantly associated with life dissatisfaction (Table 4).

Table 2.

Demographic characteristics of a nationally representative sample of US adults in 2021.

Characteristic	Weighted percentage of US adults	Weighted percentage of subgroup dissatisfied with life	P value
All US adults	100	4.8
Urban/rural class*
Large central metro	31.9	5.0	.045
Medium/small metro	30.8	4.9
Large fringe metro	24.0	4.1
Nonmetropolitan	13.3	5.5
Household region
South	37.9	4.9	.09
West	23.8	4.8
Midwest	20.8	4.2
Northeast	17.5	5.4
Age (yr)
18–34	29.2	4.4	<.001
35–49	24.1	4.4
50–64	24.6	5.7
65–84	19.9	4.5
85 or higher	2.3	7.1
Sex
Female	51.7	4.6	.07
Male	48.3	5.1
Race
White	77.1	4.8	<.001
Black/African American	13.0	6.0
Asian	6.4	3.1
Other/mixed race	2.6	7.8
American Indian/Alaska Native	0.9	5.6
Highest education level
Less than high school	9.5	6.8	<.001
High school or equivalent	43.5	5.8
Associate degree	11.5	5.1
Bachelor’s degree	22.5	3.3
Master’s degree	9.8	2.4
Professional degree	3.3	2.5

^*Based on 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties.

Table 3.

Physical health characteristics of a nationally representative sample of US adults in 2021.

Characteristic	Weighted percentage of US adults	Weighted percentage of subgroup dissatisfied with life	P value
All US adults	100	4.8
General health status
Excellent	24.6	1.8	<.001
Very good	34.0	2.5
Good	27.8	4.4
Fair	10.5	12.7
Poor	3.1	32.9
Body mass index (kg/m2)
Underweight (<18.5)	1.8	9.0	<.001
Healthy weight (18.5–24.9)	31.4	4.2
Overweight (25.0–29.9)	34.1	4.2
Obese (≥30)	32.8	5.6
Pain frequency
Everyday/most days	20.9	10.3	<.001
Some days/never	79.1	3.4
Disability*
Yes	8.8	18.2	<.001
No	91.2	3.6
Cigarette smoking history
Yes	34.5	7.0	<.001
No	65.5	3.7
Hypertension
Yes	31.5	6.4	<.001
No	68.5	4.1
Arthritis
Yes	21.3	8.2	<.001
No	78.7	3.9
Cancer
Yes	9.8	6.8	<.001
No	90.2	4.6
Diabetes mellitus
Yes	9.6	8.5	<.001
No	90.4	4.4
Coronary heart disease
Yes	4.9	10.2	<.001
No	95.1	4.5
Chronic lung disease
Yes	4.6	13.2	<.001
No	95.4	4.4
Heart attack
Yes	3.0	12.2	<.001
No	97.0	4.6
Kidney disease
Yes	2.9	13.4	<.001
No	97.1	4.6
Stroke
Yes	2.8	14.4	<.001
No	97.2	4.6
Chronic fatigue syndrome
Yes	1.3	20.7	<.001
No	98.7	4.6
Dementia
Yes	1.1	22.2	<.001
No	98.9	4.6

^*Derived from the Washington Group Short Set Composite Disability Indicator.

Table 4.

Social, emotional, and financial characteristics of a nationally representative sample of US adults in 2021.

Characteristic	Weighted percentage of US adults	Weighted percentage of subgroup dissatisfied with life	P value
All US adults	100	4.8
Social/emotional support in past 12 months
Always/usually	82.2	2.8	<.001
Sometimes	10.9	11.9
Rarely/never	6.9	17.0
Serious psychological distress in past 30 days*
Yes	3.7	38.9	<.001
No	96.3
Marital status
Married	51.8	3.1	<.001
Living with a partner	8.5	3.5
Neither	39.7	7.3
Parental status
No minor children residing in household	67.9	5.6	<.001
Parent of child residing in household	25.8	2.9
Non-parent of child residing in household	6.2	4.6
In school
Yes	8.8	3.7	.048
No	91.2	4.9
Employed
Yes	62.2	3.3	<.001
No	37.8	7.3
Employment hours per week
Unemployed	37.8	7.3	<.001
1–29	8.4	3.5
30–39	7.3	4.6
40–49	33.2	2.9
50–59	7.9	3.6
60 or more	5.3	2.8
Healthcare coverage
Yes	90.0	4.7	.045
No	10.0	5.7
Family poverty ratio
<1	9.9	10.2	<.001
1–1.99	17.5	6.9
2–3.99	29.5	4.9
4–5.99	20.0	3.2
6–7.99	9.6	2.2
8–9.99	5.7	2.5
10 or more	7.7	2.7
Food security†
Food secure	94.1	4.0	<.001
Low food security	3.6	15.1
Very low food security	2.3	22.9
Length of time in residence
Less than 1 year	11.7	5.5	.02
1–3 years	22.7	4.3
4–10 years	25.2	5.3
11 or more years	40.4	4.5
Residence ownership
Own	71.0	3.9	<.001
Rent	29.0	6.9

^*Calculated from the Kessler Psychological Distress Scale (K6).

^†Derived from the 10-item U.S. Adult Food Security Survey Module.

In the multivariate logistic regression model, the following 5 factors were independently associated with life dissatisfaction; serious psychological distress in the past 30 days, unmarried status, poorer general health status, rarely/never receiving social/emotional support in the past 12 months, and lower food security (Table 5). The SHAP values indicating the relative importance of these variables in predicting life dissatisfaction were 39.3% for recent psychological distress, 22.2% for unmarried status, 18.3% for poor general health, 13.4% for lack of social/emotional support, and 6.9% for lower food security.

Table 5.

Multivariate predictors of dissatisfaction with life in a nationally representative sample of US adults in 2021.

Characteristic	Odds ratio*	95% CI	P value
General health status
Excellent	1 [ref.]	–	<.001
Very good	1.45	1.13, 1.85
Good	2.00	1.57, 2.56
Fair	4.95	3.83, 6.40
Poor	12.58	9.48, 16.7
Serious psychological distress in past 30 days†
No	1 [ref.]	–	<.001
Yes	6.43	5.18, 7.99
Social/emotional support
Always/usually	1 [ref.]	–	<.001
Sometimes	2.94	2.46, 3.52
Rarely/never	3.99	3.30, 4.83
Marital status
Married	1 [ref.]	–	<.001
Living with a partner	0.98	0.70, 1.38
Neither	1.94	1.67, 2.26
Food security‡
Food secure	1 [ref.]	–	<.001
Low food security	1.68	1.28, 2.20
Very low food security	2.04	1.51, 2.75

CI = confidence interval.

^*Odds ratio > 1 indicates higher odds of life dissatisfaction. Odds ratio < 1 indicates lower odds of life dissatisfaction.

^†Calculated from the Kessler Psychological Distress Scale (K6).

^‡Derived from the 10-item U.S. Adult Food Security Survey Module.

Several notable findings were observed when evaluating the prevalence of key life dissatisfaction correlates among demographic groups. First, Non-White racial groups including Black/African American, American Indian/Alaska Native, and other/mixed race were more likely to report a life dissatisfaction risk factor. Second, individuals in these racial groups reported a higher prevalence of rare or never social/emotional support. Third, very low food security was more prevalent among individuals reporting Black/African American, American Indian/Alaska Native, or other/mixed race (Table 6). These findings highlight the presence of racial inequity in the primary factors associated with life dissatisfaction among the US adult population.

Table 6.

Prevalence of key life dissatisfaction correlates among demographic groups in a nationally representative sample of US adults in 2021.

Characteristic	Poor general health status		Recent serious psychological distress		Rare/never social/emotional support		Unmarried		Very low food security
	%	Odds ratio (95% CI)*	%	Odds ratio (95% CI)*	%	Odds ratio (95% CI)*	%	Odds ratio (95% CI)*	%	Odds ratio (95% CI)*
All US adults	3.1		3.7		6.9		39.7		2.3
Age (yr)
18–34	0.8	1 [ref.]	4.9	1 [ref.]	6.3	1 [ref.]	58.7	1 [ref.]	2.9	1 [ref.]
35–49	2.1	2.72 (1.71, 4.33)	3.6	0.74 (0.60, 0.92)	6.8	1.09 (0.94, 1.28)	27.3	0.26 (0.24, 0.29)	2.6	0.88 (0.69, 1.13)
50–64	4.6	6.12 (4.08, 9.18)	3.6	0.72 (0.59, 0.89)	7.6	1.22 (1.04, 1.43)	29.3	0.29 (0.27, 0.32)	2.4	0.80 (0.63, 1.03)
65–84	5.1	6.93 (4.57, 10.5)	2.2	0.44 (0.35, 0.55)	6.8	1.09 (0.93, 1.28)	36.7	0.41 (0.38, 0.44)	1.2	0.39 (0.29, 0.53)
85 or higher	10.0	14.3 (8.80, 23.3)	3.5	0.71 (0.43, 1.19)	6.6	1.05 (0.79, 1.39)	64.9	1.30 (1.09, 1.54)	0.3	0.10 (0.04, 0.29)
Sex
Female	3.0	1 [ref.]	4.6	1 [ref.]	6.5	1 [ref.]	42.1	1 [ref.]	2.6	1 [ref.]
Male	3.2	1.06 (0.91, 1.24)	2.7	0.59 (0.50, 0.68)	7.3	1.14 (1.02, 1.27)	37.2	0.82 (0.77, 0.86)	2.0	0.79 (0.66, 0.96)
Race
White	3.1	1 [ref.]	3.7	1 [ref.]	5.5	1 [ref.]	36.3	1 [ref.]	1.9	1 [ref.]
Black/African American	3.7	1.20 (0.95, 1.51)	4.0	1.08 (0.87, 1.35)	9.1	1.73 (1.46, 2.07)	59.4	2.58 (2.33, 2.85)	5.2	2.87 (2.29, 3.59)
Asian	2.3	0.75 (0.50, 1.14)	2.3	0.60 (0.38, 0.95)	12.6	2.49 (2.04, 3.05)	33.6	0.89 (0.78, 1.01)	0.9	0.47 (0.26, 0.85)
Other/mixed race	3.0	0.97 (0.60, 1.57)	6.5	1.80 (1.23, 2.63)	9.4	1.94 (1.12, 3.34)	46.8	1.93 (1.50, 2.50)	4.8	2.64 (1.78, 3.93)
American Indian/Alaska Native	5.4	1.78 (1.01, 3.15)	5.2	1.42 (0.86, 2.35)	10.1	1.79 (1.28, 2.50)	52.4	1.55 (1.31, 1.84)	7.9	4.47 (1.81, 11.1)

CI = confidence interval.

^*Odds ratio > 1 indicates higher odds of reporting life dissatisfaction risk factor. Odds ratio < 1 indicates lower odds of reporting life dissatisfaction risk factor. Subgroups in which the 95% confidence interval of the odds ratio excludes 1 are bolded.

4. Discussion

This cross-sectional, population-based study sought to identify factors associated with life dissatisfaction among US adults in 2021. Among the social- and health-related factors in this study, 5 key determinants of life dissatisfaction were identified: serious psychological distress in the past 30 days, unmarried status, poorer general health status, rarely/never receiving social/emotional support in the past 12 months, and lower food security. Interestingly, variables reflecting age, sex, race, education, income, and employment did not independently contribute to the final model. However, racial inequity was identified among the primary correlates of life dissatisfaction in the US adult population, particularly among individuals reporting Black/African American, American Indian/Alaska Native, or other/mixed race.

The results of this study address a central goal of US health policy as outlined in Healthy People 2030 by identifying disparities in the well-being of US adults.^[1] This study identified 5 primary correlates of life dissatisfaction in the US adult population, which tended to be more prevalent among nonwhite individuals. Thus, the results of this study may serve as a baseline for continued monitoring of the well-being in the US adult population over the next decade, as well as prioritizing public health policies including initiatives to address racial inequities.

Recent serious psychological distress was the strongest correlate of life dissatisfaction and was more prevalent among younger adults, females, and individuals reporting other/mixed race. While the underlying causes of psychological distress were unavailable in this study, these at-risk subgroups should be targeted to ensure access to preventive and interventional mental health resources. Another notable finding of this study was the independent contribution of lack of social/emotional support to life dissatisfaction. This finding supports the importance of social ties outside of the household for improving life satisfaction. Interestingly, poorer overall self-reported health status was a stronger correlate of life dissatisfaction than history of any individual disease diagnosis. The chronic diseases and health-related risk factors assessed in this study were associated with life dissatisfaction; however, their associations were substantially reduced when controlling for subjective overall health appraisal. Food insecurity was the least prevalent among the correlates of life dissatisfaction yet was highly associated with racial inequity in individuals reporting Black/African American, American Indian/Alaska Native, or other/mixed race. Food insecurity is more prevalent in subpopulations not ascertained in the current study such as individuals with poor sleep quality,^[20] drug addiction,^[21] and those living in large households,^[22] which may partially explain its independent association with life dissatisfaction after adjusting for social and health factors. A stated priority area of Healthy People 2030 is to reduce the prevalence of food insecure households by 40% over the next decade. Thus, focusing on nutrition assistance programs and addressing unemployment among at-risk populations identified in this study may serve to meet this objective.

A unique characteristic of this study was the presence of the Covid-19 pandemic during the survey period. The pandemic caused widespread negative effects on mental health, social relationships, and financial stability, all of which may have plausibly influenced life dissatisfaction.^[23] The prevalence of health conditions and psychological distress observed during this period was more pronounced than in previous periods.^[24] Further, the lack of social and emotional support may have been magnified due to the ongoing social isolation measures.^[25] Additionally, the pandemic disproportionately affected racial and ethnic minority groups, which may have exacerbated the disparities observed in this study since these groups are more likely to experience living and working conditions that predispose them to worse outcomes.^[26] Although the influence of Covid-19 was not a focus of this study, the unique circumstances presented by the pandemic should be considered when interpreting these results.

Future research in this field should expand on the results of this study by identifying additional risk factors for life dissatisfaction and examining the causes underlying the identified correlates. This could involve longitudinal studies to assess the direction of the observed associations over the next decade and measuring the relative contribution of health and non-health factors to life satisfaction. Additionally, the potential impact of interventions to improve the identified risk factors should be evaluated, specifically the effects of mental health treatments, social support programs, and food security initiatives on overall life satisfaction. Such research would align with the priorities of Healthy People 2030 by informing the development of evidence-based interventions to promote overall well-being and reduce health disparities in Americans.^[1]

This population-based study had several important strengths. First, the results were generalizable to the US population of non-institutionalized civilian adults. This contrasts with much of the work on correlates of life satisfaction that focused on highly selected samples with limited generalizability.^[4–9] Second, the NHIS enabled the evaluation of population-based health characteristics across different sociodemographic groups that may not be accurately estimated in smaller studies. Third, we determined the relative importance of covariates in predicting life dissatisfaction using SHAP values, which allowed practical interpretation of the regression model outputs. Finally, the objectives of this study reflect those of Healthy People 2030,^[1] underscoring the societal importance of the results. Despite these strengths, this study had several limitations that require further discussion. First, the cross-sectional design of this study precluded us from determining whether the observed associations with life dissatisfaction were causal. Second, subgroups of the population, including individuals with no fixed address, persons living abroad, on military bases, in long-term care institutions, and in correctional facilities, were excluded from the NHIS, which may limit the generalizability of these findings. Finally, inaccuracies may exist within the NHIS database owing to recall and response bias since the database is primarily comprised of self-reported data.

5. Conclusions

Life dissatisfaction in US adults is associated with social- and health-related factors that are more prevalent in racial minority groups. The study findings suggest that resource prioritization should be targeted towards individuals with these factors, with particular emphasis on racial minority groups. This study aligns with US health policy initiatives and the results may help policymakers address the underlying factors contributing to life dissatisfaction in the US population.

Author contributions

Conceptualization: Anna L. Miller, Mehul Bhattacharyya, Ruemon Bhattacharyya, Frederick Frankhauser, Larry E. Miller.

Formal analysis: Larry E. Miller.

Investigation: Anna L. Miller, Mehul Bhattacharyya, Ruemon Bhattacharyya, Frederick Frankhauser.

Supervision: Larry E. Miller.

Writing – original draft: Larry E. Miller.

Writing – review & editing: Anna L. Miller, Mehul Bhattacharyya, Ruemon Bhattacharyya, Frederick Frankhauser.