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Measuring Unintended Pregnancy in 2000-2001 Hawai`i PRAMS Data Limin Song, M.P.H., C.H.E.S. Cheryl B. Prince, Ph.D., M.P.H. Nighat Quadri, M.S., M.P.H.

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Presentation on theme: "Measuring Unintended Pregnancy in 2000-2001 Hawai`i PRAMS Data Limin Song, M.P.H., C.H.E.S. Cheryl B. Prince, Ph.D., M.P.H. Nighat Quadri, M.S., M.P.H."— Presentation transcript:

1 Measuring Unintended Pregnancy in Hawai`i PRAMS Data Limin Song, M.P.H., C.H.E.S. Cheryl B. Prince, Ph.D., M.P.H. Nighat Quadri, M.S., M.P.H.

2 Traditional question Thinking back to just before you got pregnant with your new baby, how did you feel about becoming pregnant? I wanted to be pregnant sooner I wanted to be pregnant later I wanted to be pregnant then I didn’t want to be pregnant then or at any time in the future

3 Traditional Definition sooner + then = intended later + never =unintended

4 Filter Question When you got pregnant with your new baby, were you trying to become pregnant? (No/Yes)

5 Question? Exclude ‘TRYING’ women from unintended group?

6 Purpose To compare data on intendedness using both questions vs. only traditional question To determine the best measurement tool of pregnancy intendedness for the State of Hawai`i.

7 Hawai`i PRAMS Native Hawaiian/Part Hawaiian women Women living in rural areas outside of Honolulu

8 Honolulu

9 Methods Analyzed demographic characteristics of Hawai`i PRAMS mothers delivering in Compared statistics between traditional unintended pregnancy definition and definition using both questions

10 Results Sample size6,251 Respondents5,009 (80%) Estimated live births33,991 (Weighted population size)

11 CharacteristicsPercent Age < > Education <12 years 12 years >12 years Marital Status Married Not married Results

12 CharacteristicsPercent Race/Ethnicity Chinese & Japanese Filipino Hawaiian/Pt Hawaiian Other Asian & Pac. I. Other Nonwhite White Residence Urban Honolulu Rural Oahu Neighbor Islands Income <$10,000 $10,000-30,000 $30,001-50,000 >$50, Results

13 I wanted to be pregnant: Trying to get pregnant Yes No Sooner29.49%6.41% Later 4.99% 61.16% Then64.68%16.83% Didn’t want 0.84% 15.59%

14 Results Unintended pregnancy Intended pregnancy Use one question (traditional) 44.3%55.7% Use both questions 41.6%58.4%

15 Unintended Pregnancy Rate Among Seventeen States: 33.7% % (Utah) (Louisiana) 1999 PRAMS Surveillance Report

16 Extending the Study Other Measurements: Wanted Mistimed Unwanted Ambivalent

17 Commonly Used Definition I wanted to be pregnant: Sooner + then = wanted Later = mistimed Never = unwanted

18 Two additional questions When you got pregnant with your new baby, were you or your husband or partner doing anything to keep from getting pregnant? (yes/no) What were your or your husband’s or partner’s reasons for not doing anything to keep from getting pregnant? (one option is ‘I didn’t mind if I got pregnant’)

19 Our Results Wanted – 50.29% Mistimed – 28.53% Ambivalent – 12.88% Unwanted – 8.29% Unclassified % (1)

20 How did we get these numbers? Use information from all four questions Include women with some missing values

21 Conclusions The intention to become pregnant is a difficult concept to measure precisely. Discussing with the family planning program staff for further decision.

22 Limitation Since stillbirths are not included in the PRAMS data set, measuring the prevalence of pregnancy intendedness using PRAMS data will never be 100% accurate.

23 Public Health Benefits Development of a stable and reliable measurement tool Directing scarce resources to focus on populations at risk.

24 Acknowledgements Ms. Marisa Martin, Family Health Service Division, former Hawai`i PRAMS Data Manager George Lin and Caryn Tottori, Office of Health Status Monitoring Hawai`i PRAMS team Dr. Nedra Whitehead, Division of Reproductive Health, CDC

25 Keep Marching…

26 sooner + using BC = mistimed, otherwise sooner=wanted later + (trying or didn’t mind) =ambivalent, otherwise later=mistimed then + using BC = ambivalent, otherwise then=wanted never + (trying or didn’t mind) = ambivalent, otherwise never=unwanted missing feel + trying = wanted missing feel + (not or missing try) + using BC = unwanted missing feel + (not or missing try) + (not using or missing BC) + mind =unwanted missing feel +(not or missing try) + (not using or missing BC) + didn’t mind = wanted missing feel + not trying + not using BC + missing mind = ambivalent all missing = unclassified How did we get these numbers?


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