Evidence map›Paper›PMID 31779602›Full record

ArticleBMC public health2019

Niacin, lutein and zeaxanthin and physical activity have an impact on Charlson comorbidity index using zero-inflated negative binomial regression model: National Health and Nutrition Examination Survey 2013-2014.

Hantong Zhao, Changcong Wang, Yingan Pan, Yinpei Guo, Nan Yao, Han Wang, Lina Jin, Bo Li

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in BMC public health, 2019. 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, top 80% of its field
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, 8 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Hantong ZhaoDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China.
Changcong WangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China.
Yingan PanDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China.
Yinpei GuoDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China.
Nan YaoDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China.
Han WangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China.
Lina JinDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China. jinln@jlu.edu.cn.
Bo LiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Avenue, Changchun, 130021, People's Republic of China. li_bo@jlu.edu.cn.
Jilin University · CN

Funding

National Natural Science Foundation of China No. 81973129
6 · The paper itself

Abstract

backgroundCombined with the increasing life expectancy, chronic medical conditions have gradually become the dominant cause of death and disability, and multimorbidity became an increasingly serious public health challenge. However, most existing studies have focused on the coexistence of specific diseases or relatively few diseases. Given one person may have multiple diseases at the same time, we applied Charlson Comorbidity Index (CCI) to systematically evaluate one's 10-year mortality. In this study, we explored the effects of nutrients and physical activity on CCI using National Health and Nutrition Examination Survey (NHANES) 2013-2014 data.

methodsThe study sample consists of one continuous cycle (2013-2014) of NHANES, and 4386 subjects were included in the study. Nutrients intake was measured by dietary recall, and physical activity was evaluated by the Global Physical Activity Questionnaire respectively. Besides, CCI was the sum of the scores assigned for each medical condition. We utilized zero-inflated negative binomial (ZINB) model to investigate the effects in nutrients intake and physical activity on CCI by adjusting for seven sociodemographic characteristics, smoking and drinking.

resultsAmong the 4386 participants, 2018 (68.7%) are Non-Hispanic White, over half participants (78.6%) drink. In count part (CCI ≥ 0), holding other variables constant, the expected change in CCI for a one-unit increase in niacin is 1.621(RR = 1.621, p = 0.016), in lutein + zeaxanthin is 0.974 (RR = 0.974, p = 0.031), and in sedentary time is 1.035 (RR = 1.035, p = 0.005). Moreover, those who do not have vigorous work activity would be more likely to have higher CCI than those who have (RR = 1.275, P = 0.045). In logit part (CCI = 0), the log odds of having CCI equals zero would increase by 0.541 and 0.708 for every additional vigorous recreational activity (OR = 0.541, p = 0.004) and moderate recreational activity (OR = 0.708, p = 0.017) respectively.

conclusionsLutein and zeaxanthin intake, vigorous work activity, vigorous recreational activity and moderate recreational activity may be good for one's health. Rather, increasing niacin intake and sedentary activity may be likely to raise 10-year mortality. Our findings may be significant for preventing diseases and improving health, furthermore, reducing people's financial burden on healthcare.

Indexed as

ExerciseAdultAgedChronic DiseaseComorbidityDietEnergy IntakeFemaleHumansLuteinMaleMiddle AgedNiacinNutrition SurveysRegression AnalysisZeaxanthinsLuteinNiacinZeaxanthinsCharlson comorbidity index (CCI)MultimorbidityNutrientsPhysical activityZero-inflated negative binomial (ZINB)

Identifiers

PMID31779602
PMCPMC6883694
OpenAlexW2990194936

What OpenQuestion holds

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Registered trials

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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.