National Center for Health Statistics

Refusal Reasons: Changes Over Time and Differences 

Between Household Types in the National Health and 

Nutrition Examination Survey (NHANES), 2017-2019, 2021

Steven Fink, Matt Jans,, Denise Schaar, Jill Fleming, NCHS/DHANES

Kevin Chuang*, Henry M. Jackson Foundation

Andrew Caporaso, Jason Clark, George Dixon, Susan Genoversa, Minsun Riddles, Westat

October 25th, 2023 

Federal Committee on Statistical Methodology (FCSM)

* During the time this research was conducted, Kevin Chuang was a guest researcher at the National Center for Health Statistics (NCHS) through the Research Participation Program at the Centers for Disease 

Control and Prevention (CDC) administered by the Oak Ridge Institute for Science and Engineering (ORISE) fellowship program through an interagency agreement between the U.S. Department of Energy and CDC
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Disclaimer

The findings and conclusions in this presentation are those of the authors and do not 

necessarily represent the official position of the Centers for Disease Control and 

Prevention 
Unit Nonresponse is a Problem 

 Nonresponse is one of the most challenging issue for survey 

methodologists, especially due to steadily decreasing response 

rates since mid-1990’s

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ATUS-American Time Use Survey; CPS-Current Population Survey; GSS-General Social Survey; MEPS-Medical Expenditure Panel Survey; NCVSNational Crime Victimization Survey; NHANES-National Health and Nutrition Survey; NHIS-National Household Interview Survey; NSDUH-National 

Survey on Drug Use and Health; NSFG-National Survey of Family Growth

Source: Williams, D.. 2022. Survey Nonresponse: Trends, Challenges, and Strategies. Presented at the Federal Economic Statistics Advisory 

Committee. https://apps.bea.gov/fesac/meetings/2022-12-09/williams-survey%20response.pdf.
Refusals an Important Part of Unit Nonresponse

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 Understanding why participants refuse to respond to surveys can 

provide insights about people’s and survey participation

o Personality (Boyle, et al 2023)

o Mindsets (Bates and Creighton, 2000 and Olsen, 2013)

o Societal-level drivers 

o Nonrespondent typology (Medway, 2022, based on NHES:2019)
Study Objective and Research Questions 

 Examine refusal reason(s) from sampled households and adults 

in National Health and Nutrition Examination Survey (NHANES)

 Two research questions: 

1) Are there significant trends in dwelling unit and sampled adult refusal 

reasons over time? 

2) Do any trends over time look similar in dwelling units with and without 

minors? 

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Methods
What is NHANES?

 Goal: To assess the health and nutritional status of adults and 

children in the U.S.

 Collects person-level demographic, health, and nutrition 

information

 A nationally representative cross-sectional survey that includes: 

o Interview, including a household component

o Examination, including physical exams, and dietary components

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8

 Complex multistage probability 

sample design

 Selected households are screened 

to identify eligible participants

NHANES Sample Design
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NHANES Sample Design (cont)

 Cross-sectional 

 Noninstitutionalized civilian resident 

population

 Target sample: 5,000 individuals 

examined annually

 Data released in 2-year cycles
Evaluating Refusals in 2017-2019 and 2021

 Refusal reasons came from the 2017-2019 and 2021 NHANES 

data collection years to evaluate survey refusals from:

o 6,109 screener Dwelling Unit (DU) refusers out of 54,722 total DUs

o 10,954 adult Sampled Persons (SP) interview refusers out of 23,740 

total SPs (completes, SP refused screener, and other)

 DUs and SPs analyzed separately in two steps

 MEC refusals not included in this study

 Interviewers recorded up to 3 refusal reasons at any contact with 

a DU or SP

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Creation of Refusal Reason Categories

 5 categories of reasons created from 21 detailed refusal 

reasons used at DU and SP levels

o Combined conceptually similar reasons

 Final refusal reasons (from final contact) in each year

 When more than one refusal reason per DU or SP was 

recorded (at the final contact) within the larger five categories, 

it was coded as one refusal reason

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List of Refusal Reason Categories
Statistical Analysis Approach

 Trend tests performed for each DU and SP refusal reason, 

including the presence of a minor (and not providing a reason)

 Analysis used orthogonal polynomial contrasts, in accordance 

with NCHS guidelines*

* Ingram DD, Malec DJ, Makuc DM, Kruszon-Moran D, Gindi RM, Albert M, et al. 2018. “National Center for Health 

Statistics Guidelines for Analysis of Trends.” National Center for Health Statistics. Vital Health Stat 2(179).

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Results
DU Level - Three Reason Trends Significant

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Refusal Reason (grouped)

2017

(n=754)

%

2018 

(n=1,255)

%

2019 

(n=1,569)

%

2021 

(n=2,513)

%

Linear 

Trend Test

No Interest/Avoidance 49.3 41.4 44.6 47.0 p=.901

General Distrust of Surveys 

or Government 7.6 5.4 5.2 10.2 p<.001

Too Busy/Too Long 3.6 6.4 5.0 5.0 p=.469

Privacy Concerns 7.6 9.8 8.3 6.1 p=.011

Personal Health Decision 2.8 2.9 0.7 1.4 p<.003

Did not provide a reason* 29.2 34.0 36.1 30.4 p=.175

*Percentages do not add to 100% because DUs that reported a refusal reason can report more than one refusal reason.

Significant increasing linear trend Significant decreasing linear trend 
SP Level - Five Reason Trends Significant

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Refusal Reason (grouped)

2017

(n=754)

%

2018 

(n=1,255)

%

2019 

(n=1,569)

%

2021 

(n=2,513)

%

Linear 

Trend 

Test

No Interest/Avoidance 52.7 49.0 37.0 43.4 p<.001

General Distrust of Surveys or 

Government 3.1 3.0 4.7 13.8 p<.001

Too Busy/Too Long 19.8 19.1 21.1 16.8 p<.009

Privacy Concerns 3.7 5.1 9.6 7.8 p=.001

Personal Health Decision 9.3 9.4 4.6 5.0 p<.009

Did not provide a reason* 26.1 27.6 36.0 25.6 p=.001

*Percentages do not add to 100% because DUs that reported a refusal reason can report more than one refusal reason.

Significant increasing linear trend Significant decreasing linear trend 
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Refusal Reason (grouped)

2017

(n=1,614)

%

2018 

(n=1,761)

%

2019 

(n=1,587)

%

2021 

(n=2,679)

%

Linear 

Trend 

Test

No Interest/Avoidance 52.9 48.2 38.4 45.4 p<.001

General Distrust of Surveys 

or Government 3.2 3.4 4.2 13.5 p<.001

Too Busy/Too Long 18.3 16.9 21.2 15.0 p<.006

Privacy Concerns 3.5 5.0 9.1 8.7 p=.000

Personal Health Decision 11.5 10.7 5.6 5.9 p<.001

Did not provide a reason* 25.7 29.1 34.4 22.6 p=.004

*Percentages do not add to 100% because SPs that reported a refusal reason can report more than one refusal reason.

SP Level - Five Reason Trends Significant 

When No Minor Present in Household

Significant increasing linear trend Significant decreasing linear trend 
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Refusal Reason (grouped)

2017

(n=1,543)

%

2018 

(n=1,774)

%

2019 

(n=1,899)

%

2021 

(n=2,148)

%

Linear 

Trend 

Test

No Interest/Avoidance 51.0 49.3 32.7 37.6 p<.001

General Distrust of Surveys 

or Government 3.2 2.0 5.4 13.9 p<.001

Too Busy/Too Long 22.0 24.1 20.4 18.3 p<.009

Privacy Concerns 4.5 4.6 11.8 6.3 p=.368

Personal Health Decision 5.7 6.9 3.5 2.9 p<.001

Did not provide a reason* 26.6 26.0 37.4 29.3 p=.017

*Percentages do not add to 100% because SPs that reported a refusal reason can report more than one refusal reason.

SP Level - Four Reason Trends Significant 

When Minor Present in Household

Significant increasing linear trend Significant decreasing linear trend 
Conclusions
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Level of Analysis

Refusal Reason (grouped)

Dwelling 

Unit

Sampled 

Person 

(SP)

SP with No 

Minor in 

Household

SP With 

Minor in 

Household

No Interest/Avoidance Not sig.

General Distrust of Surveys 

or Government

Too Busy/Too Long Not sig.

Privacy Concerns Not sig.

Personal Health Decision

Did not provide a reason* Not sig.

DU and SP Trend Significance Tests Summary

Significant increasing linear trend Significant decreasing linear trend 
Findings Summary

 No interest/avoidance and too busy/too long were most common 

refusal reasons

 Most refusal reasons (at DU and SP level overall and by presence 

of a minor) show statistically significance change over time

o DU: No Interest, Too Busy, & Personal Health Decisions didn’t change over 

time

o SP: No change in Privacy Concerns when minor in HH, but increase when 

there was no minor in HH

 General Distrust of Surveys or Government shows the highest 

percentage increase 

 Personal health decision shows a decrease

 SPs not providing a reason decreased over the four years

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Study Limitations and Solutions

 Only examined trends comprising four years

o Plan to include 2022 and 2023 data in next analysis (look for us at 

AAPOR 2024)

 Only minor vs. no minor in the dwelling unit was explored 

o Other factors influence refusal reasons 

• Plans to explore predictive model including SP demographic 

characteristics, household factors, and neighborhood features

• Changes in interviewing staff and training over time may 

influence reasons recorded

o Interviewer variation in their ability to convert refusals to completes

o Additional training, especially role-playing may reduce non-response, 

but also collect better reasons for reasons for participate 22
Acknowledgements

 Recognition of dozens of Westat field interviewers over the past 

5 years providing refusal reason pardata for the study

 Several Westat and NHANES reviewers for their comments

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Thank you!

Questions? 

Sfink@cdc.gov