Evidence map›Paper›PMID 32297139›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2020

ZIP Code-Level Estimates from a Local Health Survey: Added Value and Limitations.

Qifang Bi, Fangtao He, Kevin Konty, L Hannah Gould, Stephen Immerwahr, Amber Levanon Seligson

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Qifang BiNew York City Department of Health and Mental Hygiene, Queens, NY, USA. qbi1@jhu.edu.
Fangtao HeNew York City Department of Health and Mental Hygiene, Queens, NY, USA.
Kevin KontyNew York City Department of Health and Mental Hygiene, Queens, NY, USA.
L Hannah GouldNew York City Department of Health and Mental Hygiene, Queens, NY, USA.
Stephen ImmerwahrNew York City Department of Health and Mental Hygiene, Queens, NY, USA.
Amber Levanon SeligsonNew York City Department of Health and Mental Hygiene, Queens, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We assessed the added value and limitations of generating directly estimated ZIP Code-level estimates by aggregating 5 years of data from an annual cross-sectional survey, the New York City Community Health Survey (n = 44,886) from 2009 to 2013, that were designed to provide reliable estimates only of larger geographies. Survey weights generated directly-observed ZIP Code (n = 128) level estimates. We assessed the heterogeneity of ZIP Code-level estimates within coarser United Hospital Fund (UHF) neighborhood areas (n = 34) by using the Rao-Scott Chi-Square test and one-way ANOVA. Orthogonal linear contrasts assessed whether there were linear trends at the UHF level from 2009 to 2013. 22 of 37 health indicators were reliable in over 50% of ZIP Codes. 14 of the 22 variables showed heterogeneity in ≥4 UHFs. Variables for drinking, nutrition, and HIV testing showed heterogeneity in the most UHFs (9-24 UHFs). In half of the 32 UHFs, >20% variables had within-UHF heterogeneity. Flu vaccination and sugary beverage consumption showed significant time trends in the largest number of UHFs (12 or more UHFs). Overall, heterogeneity of ZIP Code-level estimates suggests that there is value in aggregating 5 years of data to make direct small area estimates.

Indexed as

Health SurveysResidence CharacteristicsAdultCensusesCross-Sectional StudiesHumansNew York CityPopulation healthSurveyZIP Code

Identifiers

PMID32297139
PMCPMC7392987

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.