Screening for Pregnancy Status in a Population-Based Sample: Characteristics Associated with Item Nonresponse

Background.This study assessed item nonresponse (INR) in a population-based mail survey of physical activity (PA).Methods.A questionnaire was mailed to a random sample, with a 57% response rate (n = 2532). The magnitude and type of PA INR and the association with sociodemographic variables was examined using logistic regression.Results.Among survey respondents, 28% had incomplete PA data; 11% missed 1 item, 11% missed 2 items, and 5% missed all 3 items. Respondents missing 3 items tended to be female, less educated, low income, in poor health, and current smokers. The walking item was missed by 8% of respondents, and 18% and 23% missed the vigorous-intensity and moderate-intensity PA items respectively. These groups were sociodemograpically different from those without INR. Incomplete PA data was also associated with sociodemographic INR.Conclusions.Mail surveys may underrepresent individuals insufficiently active for health, in particular those of low socioeconomic position.

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The AMEL study, a cross sectional population-based survey on aging and malnutrition in 1200 elderly Lebanese living in rural settings: protocol and sample characteristics

BMC Public Health ◽

10.1186/1471-2458-13-573 ◽

2013 ◽

Vol 13 (1) ◽

Cited By ~ 31

Author(s):

Christa Boulos ◽

Pascale Salameh ◽

Pascale Barberger-Gateau

Keyword(s):

Population Based ◽

Cross Sectional ◽

Rural Settings ◽

Sample Characteristics ◽

Population Based Survey

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Item Nonresponse in Face-to-Face Interviews with Children

Journal of Official Statistics ◽

10.2478/jos-2014-0029 ◽

2014 ◽

Vol 30 (3) ◽

pp. 459-477 ◽

Cited By ~ 1

Author(s):

Sigrid Haunberger

Keyword(s):

Interaction Effects ◽

Population Based ◽

Item Nonresponse ◽

Panel Survey ◽

Child Gender ◽

Face To Face ◽

Child Age ◽

Interview Setting

Abstract This study examined item nonresponse and its respondent and interviewer correlates by means of a population-based, panel survey of children aged 8 to 11 who were surveyed using standardised, face-to-face interviews. Using multilevel, logistic analyses with cross-level interactions, this article aims to examine which effects of item nonresponse are subject to children as respondents or to the interviewers and the interview setting. Depending on the type of question, we found different effects for respondent and interviewer variables, as well as interaction effects between child age/interviewer age as well as child gender/interviewer gender. However, interviewer variance is for the most part not significant.

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TwinsUK COVID-19 personal experience questionnaire (CoPE): wave 1 data capture April-May 2020

Wellcome Open Research ◽

10.12688/wellcomeopenres.16671.1 ◽

2021 ◽

Vol 6 ◽

pp. 123

Author(s):

Aaruthy Suthahar ◽

Pramila Sharma ◽

Deborah Hart ◽

María Paz García ◽

Rachel Horsfall ◽

...

Keyword(s):

Personal Experience ◽

Population Based ◽

Population Based Study ◽

Health Records ◽

The United Kingdom ◽

Phase Wave ◽

Sample Characteristics ◽

Adult Twins ◽

Second Wave ◽

Experience Questionnaire

TwinsUK is a population-based study which consists of 14,575 adult twins at present (55% monozygotic and 43% dizygotic) who are between 18 to 101 years of age from around the United Kingdom (UK). In response to the coronavirus disease 2019 (COVID-19) pandemic and the resulting UK ‘lockdown’ restrictions, our team developed the TwinsUK COVID-19 personal experience (CoPE) questionnaire. To date the CoPE questionnaire has been implemented three times, once during the first lockdown (April-May 2020), once as the restrictions eased (July-August 2020) and another when we entered the second wave of the pandemic and stricter restrictions were put into place (October-November 2020). This data note details the sample characteristics, and response rates of the data collected during the initial lockdown phase (wave 1) using the CoPE questionnaire. This questionnaire was designed to capture a variety of social, behavioural, psychological, environmental and health factors. It includes both measures that have been collected previously in TwinsUK as well as new measures. This data can be combined with pre-pandemic TwinsUK data and biological and genetic data. TwinsUK will also soon be complemented with the availability of linked health records. All TwinsUK data is available upon request and details are provided on how to access the data below.

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Comparison of sample characteristics in two pregnancy cohorts: community-based versus population-based recruitment methods

BMC Medical Research Methodology ◽

10.1186/1471-2288-13-149 ◽

2013 ◽

Vol 13 (1) ◽

Cited By ~ 15

Author(s):

Brenda MY Leung ◽

Sheila W McDonald ◽

Bonnie J Kaplan ◽

Gerald F Giesbrecht ◽

Suzanne C Tough

Keyword(s):

Population Based ◽

Community Based ◽

Recruitment Methods ◽

Sample Characteristics

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Relationship Between Future Time Orientation and Item Nonresponse on Subjective Probability Questions: A Cross-Cultural Analysis

Journal of Cross-Cultural Psychology ◽

10.1177/0022022117698572 ◽

2017 ◽

Vol 48 (5) ◽

pp. 698-717 ◽

Cited By ~ 10

Author(s):

Sunghee Lee ◽

Mingnan Liu ◽

Mengyao Hu

Keyword(s):

Subjective Probability ◽

Future Orientation ◽

Population Based ◽

Cultural Analysis ◽

Cross Cultural ◽

Time Orientation ◽

Item Nonresponse ◽

Individual Level ◽

Cultural Research ◽

The Future

Time orientation is an unconscious yet fundamental cognitive process that provides a framework for organizing personal experiences in temporal categories of past, present, and future, reflecting the relative emphasis given to these categories. Culture lies central to individuals’ time orientation, leading to cultural variations in time orientation. For example, people from future-oriented cultures tend to emphasize the future and store information relevant for the future more than those from present- or past-oriented cultures. For survey questions that ask respondents to report expected probabilities of future events, this may translate into culture-specific question difficulties, manifested through systematically varying “I don’t know” item nonresponse rates. This study drew on the time orientation theory and examined culture-specific nonresponse patterns on subjective probability questions using methodologically comparable population-based surveys from multiple countries. The results supported our hypothesis. Item nonresponse rates on these questions varied significantly in the way that future orientation at the group as well as individual level was associated with lower nonresponse rates. This pattern did not apply to nonprobability questions. Our study also suggested potential nonresponse bias. Examining culture-specific constructs, such as time orientation, as a framework for measurement mechanisms may contribute to improving cross-cultural research.

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Diet and pregnancy status in Australian women

Public Health Nutrition ◽

10.1017/s1368980008003212 ◽

2009 ◽

Vol 12 (6) ◽

pp. 853-861 ◽

Cited By ~ 63

Author(s):

Alexis Hure ◽

Anne Young ◽

Roger Smith ◽

Clare Collins

Keyword(s):

Diet Quality ◽

Economic Status ◽

Food Group ◽

Epidemiological Studies ◽

Population Based ◽

Dietary Folate ◽

Pregnancy Status ◽

Nutrient Reference Values ◽

Nationally Representative

AbstractObjectiveTo investigate and report the diet quality of young Australian women by pregnancy status.DesignPregnancy status was defined as pregnant (n 606), trying to conceive (n 454), had a baby in the last 12 months (n 829) and other (n 5597). The Dietary Questionnaire for Epidemiological Studies was used to calculate diet quality using the Australian Recommended Food Score (ARFS) methodology. Nutrient intakes were compared with the Nutrient Reference Values for Australia and New Zealand.SettingA population-based cohort participating in the Australian Longitudinal Study on Women’s Health (ALSWH).SubjectsA nationally representative sample of Australian women, aged 25 to 30 years, who completed Survey 3 of the ALSWH. The 7486 women with biologically plausible energy intake estimates, defined as >4·5 but <20·0 MJ/d, were included in the analyses.ResultsPregnancy status was not significantly predictive of diet quality, before or after adjusting for area of residence and socio-economic status. Pregnant women and those who had given birth in the previous 12 months had marginally higher ARFS (mean (se): 30·2 (0·4) and 30·2 (0·3), respectively) than ‘other’ women (29·1 (0·1)). No single food group accounted for this small difference. Across all pregnancy categories there were important nutrients that did not meet the current nationally recommended levels of intake, including dietary folate and fibre.ConclusionWomen do not appear to consume a wider variety of nutritious foods when planning to become pregnant or during pregnancy. Many young Australian women are failing to meet key nutrient targets as nationally recommended.

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