analytical example using nhis data files john r. pleis

Analytical Example Using NHIS Data Files

Analytical Example Using NHIS Data Files

John R. Pleis John R. Pleis

Research QuestionResearch Question

Is the type of health insurance coverage held by adults > 65 years of age associated with

flu shot use?

Is the type of health insurance coverage held by adults > 65 years of age associated with

flu shot use?

Additional CovariatesAdditional Covariates

• Race/ethnicity

• Region of residence

• Education, marital status, sex

• Smoking

• Number of physician office visits

• Race/ethnicity



• Smoking

• Number of physician office visits


• Regular place of health care

• Selected chronic conditions

• diabetes, respiratory difficulties, or heart disease

• Low-income program participation


• Selected chronic conditions

• diabetes, respiratory difficulties, or heart disease

• Low-income program participation

Data Files Data Files

• Determine which data files are needed for the analysis

• A good source for determining the file content is the Survey

• Description document:http://www.cdc.gov/nchs/nhis.htm

• Determine which data files are needed for the analysis

• A good source for determining the file content is the Survey

• Description document:http://www.cdc.gov/nchs/nhis.htm

http://www.cdc.gov/nchs/nhis.htm




















Data FilesData Files• This analysis will utilize data

from several files, which include:

• Person

• Sample adult

• Family

• This analysis will utilize data from several files, which include:

• Person

• Sample adult

• Family

Person FilePerson File• Each person record also has a

sampling weight

• Used to inflate each observation

• Adjusted for non-response as well as U.S. Census population totals by age, sex, and race/ethnicity

• Each person record also has a sampling weight

• Used to inflate each observation

• Adjusted for non-response as well as U.S. Census population totals by age, sex, and race/ethnicity

Person FilePerson File

• Sum of the weights = Size of the Civilian Non-Institutionalized Population

• For more information regarding weights and other design issues, please attend:Practical Applications in Design and Analysis of Complex Sample

Surveys (Session # 30)

• Sum of the weights = Size of the Civilian Non-Institutionalized Population

• For more information regarding weights and other design issues, please attend:Practical Applications in Design and Analysis of Complex Sample

Surveys (Session # 30)

Sample Adult FileSample Adult File• Each sample adult record

has a sampling weight • Different from the person

sampling weight• Sum of the weights = Size of

the Civilian Non-Institutionalized Population of adults > 18 years of age

• Each sample adult record has a sampling weight

• Different from the person sampling weight

• Sum of the weights = Size of the Civilian Non-Institutionalized Population of adults > 18 years of age

Sampling WeightsSampling Weights

• Each data file has its own sampling weights

• Weights should be used, if not:

• Totals, means, and proportions are affected

• Estimates such as regression coefficients are biased

• Each data file has its own sampling weights

• Weights should be used, if not:

• Totals, means, and proportions are affected

• Estimates such as regression coefficients are biased

2000: Race/ethnicity (%)Sample Adults (aged >

65)

2000: Race/ethnicity (%)Sample Adults (aged >

65)

Source: 2000 NHISSource: 2000 NHIS

RACE/ETHNICITY UNWEIGHTED WEIGHTED

Hispanic 9.3 5.9

NH White 77.8 83.9

NH Black 11.3 8.2

Sample DesignSample Design• The NHIS has a complex

sample design• The sample design affects

the computation of variance of estimates

• A complex sample will produce larger variances than a Simple Random Sample (SRS)

• The NHIS has a complex sample design

• The sample design affects the computation of variance of estimates

• A complex sample will produce larger variances than a Simple Random Sample (SRS)

Sample DesignSample Design• Compared to a SRS,

confidence intervals are wider, and statistical significance is harder to achieve for complex survey data

• If variance estimates are needed, the complex sample design should be accounted for in the analysis

• Compared to a SRS, confidence intervals are wider, and statistical significance is harder to achieve for complex survey data

• If variance estimates are needed, the complex sample design should be accounted for in the analysis

NHW vs. NHB Men Aged < 65: Bed Days

NHW vs. NHB Men Aged < 65: Bed Days

(1) (2) (3)

SRSUnweighted

SRSWeighted

ComplexWeighted

NHW NHB NHW NHB NHW NHB

Mean 3.42 5.19 3.52 5.36 3.52 5.36

S.E. ofMean .23 .78 .28 .89 .28 1.01

t-stat 2.18 1.96 1.79

Sig. Level p = .0293 p = .0497 p = .0738

Source: 2000 NHIS

Research QuestionResearch QuestionIs the type of health

insurance coverage held by adults > 65 years of age

associated with flu shot use?

Is the type of health insurance coverage held by

adults > 65 years of age associated with flu shot use?


• Race/ethnicity• Region of residence• Education, marital status,

sex• Smoking• Number of physician office

visits

• Race/ethnicity• Region of residence• Education, marital status,

sex• Smoking• Number of physician office

visits



• One place that the adult usually went to when either sick care or preventive health care was needed

• Does not include emergency rooms (< 0.5% of the sample)


• One place that the adult usually went to when either sick care or preventive health care was needed

• Does not include emergency rooms (< 0.5% of the sample)


• Respiratory difficulties

• Asthma (EVER)

• Chronic Obstructive Pulmonary Disease (COPD)

• Respiratory difficulties

• Asthma (EVER)

• Chronic Obstructive Pulmonary Disease (COPD)


• Heart disease (EVER)

• Coronary heart disease

• Angina pectoris

• Heart attack

• Any other heart condition

• Heart disease (EVER)

• Coronary heart disease

• Angina pectoris

• Heart attack

• Any other heart condition


• Low-income programs

• Supplemental Security Income

• Temporary Assistance for Needy Families (TANF)

• Food stamps

• Governmental rental assistance

• Low-income programs

• Supplemental Security Income

• Temporary Assistance for Needy Families (TANF)

• Food stamps

• Governmental rental assistance

Creating the FileCreating the File

• Not all the variables of interest for this analysis are contained in one file

• The Person, Sample Adult, and Family files can be merged to create one data file

• Not all the variables of interest for this analysis are contained in one file

• The Person, Sample Adult, and Family files can be merged to create one data file


• Person file

• Health insurance

• Race/ethnicity (all)

• Governmental rental assistance (last 12 months)

• Person file

• Health insurance

• Race/ethnicity (all)

• Governmental rental assistance (last 12 months)

Creating the FileCreating the File• Sample Adult file

• Flu shot use (last 12 months)

• Race/ethnicity (partial)

• Smoking, chronic conditions

• Number of physician office visits (last 12 months)

• Sample Adult file

• Flu shot use (last 12 months)

• Race/ethnicity (partial)

• Smoking, chronic conditions

• Number of physician office visits (last 12 months)

Creating the FileCreating the File• Sample Adult file

• Sample Adult weight

• Sample Adult file

• Sample Adult weight

Creating the FileCreating the File• Family file

• Any family member received any of the following in the past 12 months:• Supplemental Security Income• TANF• Food stamps

• Family file

• Any family member received any of the following in the past 12 months:• Supplemental Security Income• TANF• Food stamps

Creating the FileCreating the File• Person and Sample Adult files


• All files


• STRATUM/PSU (design info for correct variance estimates)

• Person and Sample Adult files


• All files


• STRATUM/PSU (design info for correct variance estimates)


• Data available at the NHIS URL:


• Data available at the NHIS URL:


• SAS and SPSS programs are

also available to create datasets

from the provided data

• SAS and SPSS programs are

also available to create datasets

from the provided data





Creating the FileCreating the File• Merge the Person, Sample

Adult, and Family files together to create one data file

• Needed to merge files to analyze the association between health insurance coverage and flu shot use

• Merge the Person, Sample Adult, and Family files together to create one data file

• Needed to merge files to analyze the association between health insurance coverage and flu shot use


• Each person and each family has a unique identifier (ID) in the NHIS

• These IDs are used to merge the data sets together

• Each person and each family has a unique identifier (ID) in the NHIS

• These IDs are used to merge the data sets together

Creating the FileCreating the File• Person-level ID

• Created from household number

• (HHX) and person number (PX)

• Family-level ID


• (HHX) and family number (FMX)

• Person-level ID


• (HHX) and person number (PX)

• Family-level ID


• (HHX) and family number (FMX)


SampleAdult file

Person file

= Adults aged < 65, non-Sample Adults aged > 65, and all children

Familyfile

= New file


• Why not drop the records for all children, all Adults aged < 65, and all adults aged > 65 who were non-Sample Adults?

• Depending on the situation, this could alter the variance estimates

• Why not drop the records for all children, all Adults aged < 65, and all adults aged > 65 who were non-Sample Adults?

• Depending on the situation, this could alter the variance estimates


• Important to retain the file with all the observations and target the analysis to the particular domain of interest

• Several software packages for analyzing survey data (such as SUDAAN and STATA) have this capability

• Important to retain the file with all the observations and target the analysis to the particular domain of interest

• Several software packages for analyzing survey data (such as SUDAAN and STATA) have this capability

Analysis Analysis • Crosstabs of flu shot

propensity among adults > 65 years of age

• Multiple logistic regression • Data from the NHIS 2000

public use files

• Crosstabs of flu shot propensity among adults > 65 years of age

• Multiple logistic regression • Data from the NHIS 2000

public use files

Subpopulation Analyzed

Subpopulation Analyzed

• 6,180 Sample Adults > 65 years of age

• Representing a population of 32.7 million

• 6,180 Sample Adults > 65 years of age

• Representing a population of 32.7 million

AnalysisAnalysis

• 89 adults > 65 years of age (1%) did not provide their flu shot status and were excluded from the analysis

• 89 adults > 65 years of age (1%) did not provide their flu shot status and were excluded from the analysis

Flu Shot Rates By Health Insurance (aged >

65)

Flu Shot Rates By Health Insurance (aged >

65)

Medicaid and Medicare 54%Medicare 58%Medicare and Private 69%Medicare and other 72%

Medicaid and Medicare 54%Medicare 58%Medicare and Private 69%Medicare and other 72%

Flu Shot Rates By Race/ethnicity (aged

> 65)

Flu Shot Rates By Race/ethnicity (aged

> 65)

Non-Hispanic black 48%Hispanic 56%Non-Hispanic other 62%Non-Hispanic white 67%

Non-Hispanic black 48%Hispanic 56%Non-Hispanic other 62%Non-Hispanic white 67%

Flu Shot Rates By Education (aged >

65)

Flu Shot Rates By Education (aged >

65)< High School 58%High school/GED 65%Some college 66%A.A. degree 66%Bachelor’s degree + 74%

< High School 58%High school/GED 65%Some college 66%A.A. degree 66%Bachelor’s degree + 74%

Flu Shot RatesBy Regular Place of

Health Care (aged > 65)

Flu Shot RatesBy Regular Place of

Health Care (aged > 65)

Yes 65%No 25%

Yes 65%No 25%

Flu Shot RatesBy No. of Physician Office Visits, Last Year (aged >

65)

Flu Shot RatesBy No. of Physician Office Visits, Last Year (aged >

65)None 38%1 visit 60%2-3 visits 61%4-5 visits 67%6-7 visits 69%

None 38%1 visit 60%2-3 visits 61%4-5 visits 67%6-7 visits 69%

8-9 visits 72%

10-12 visits73%

13-15 visits74%

16+ visits 75%

8-9 visits 72%

10-12 visits73%

13-15 visits74%

16+ visits 75%

Odds Ratio (OR) From Logistic Regression


dependent variable = flu shot in last 12 monthsp<0.05


IND. VAR. LEVEL OR P-VALUEHEALTH

INSURANCE

Medicare and

Medicaid 0.96 0.74

Medicare (1.00) -Medicare

andPrivate

1.34 0.00

Medicare and

Other 1.89 0.01





IND. VAR. LEVEL OR P-VALUE

RACE/ETHNICITY NH black (1.00) -

Hispanic 1.40 0.03

NH other 1.20 0.53

NH white 1.65 0.00




EDUCATION < HS (1.00) -

HS / GED 1.26 0.00Some

college 1.22 0.06

A.A. degree 1.30 0.05

Bachelors + 1.64 0.00

dependent variable = flu shot in last 12 monthsp<0.05dependent variable = flu shot in last 12 monthsp<0.05





DR. VISITS None (1.00) -

1 1.97 0.00

2-3 1.86 0.00

4-5 2.56 0.00

6-7 2.72 0.00

8-9 3.16 0.00

10-12 3.29 0.00

13-15 3.29 0.00

16+ 3.34 0.00





REGULAR PLACE OF

CAREYes 2.87 0.00

No (1.00) -






REGION Northeast (1.00) -

Midwest 1.01 0.92

South 1.05 0.58

West 1.34 0.01






MARITALSTATUS

NeverMarried 1.33 0.28

Married 1.28 0.04

Separated 1.16 0.58

Widowed 1.30 0.03

Divorced (1.00) -





SEX Female 0.89 0.09

Male (1.00) -





LOWINCOME

PROGRAMSYes (1.00) -

No 1.14 0.25





SMOKINGSTATUS Current (1.00) -

Former 1.48 0.00

Never 1.47 0.00





HEARTDISEASE Yes 1.29 0.00

No (1.00) -





DIABETES Yes 1.01 0.95

No (1.00) -





RESP.PROBLEM

SYes 1.23 0.02

No (1.00) -

analytical example using nhis data files john r. pleis

Documents

sample adults

estimatesa complex sample

person sampling weightsum

preventive health care

data filecreating

filethe person

sampling weightsweights

family files