Evidence map›Paper›PMID 35140061›Full record

Trial reportBMJ (Clinical research ed.)2022

App based education programme to reduce salt intake (AppSalt) in schoolchildren and their families in China: parallel, cluster randomised controlled trial.

Feng J He, Puhong Zhang, Rong Luo, Yuan Li, Yuewen Sun, Fengge Chen, Yuhong Zhao, Wei Zhao, Daoxi Li, Hang Chen and 12 more

Abstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in BMJ (Clinical research ed.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors.

Feng J HeWolfson Institute of Population Health, Barts and London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Puhong ZhangGeorge Institute for Global Health at Peking University Health Science Centre, China zpuhong@georgeinstitute.org.cn.ORCID 0000-0003-4610-9848
Rong LuoGeorge Institute for Global Health at Peking University Health Science Centre, China.
Yuan LiGeorge Institute for Global Health at Peking University Health Science Centre, China.
Yuewen SunGeorge Institute for Global Health at Peking University Health Science Centre, China.
Fengge ChenShijiazhuang Centre for Disease Control and Prevention, Shijiazhuang, Hebei Province, China.
Yuhong ZhaoChang'an Centre for Disease Control and Prevention, Shijiazhuang, Hebei Province, China.
Wei ZhaoShijiazhuang Centre for Disease Control and Prevention, Shijiazhuang, Hebei Province, China.
Daoxi LiLuzhou Centre for Disease Control and Prevention, Luzhou, Sichuan Province, China.
Hang ChenLuzhou Centre for Disease Control and Prevention, Luzhou, Sichuan Province, China.
Tianyong WuLuzhou Centre for Disease Control and Prevention, Luzhou, Sichuan Province, China.
Jianyun YaoYueyang Centre for Disease Control and Prevention, Yueyang, Hunan Province, China.
Changxing LouYueyang Centre for Disease Control and Prevention, Yueyang, Hunan Province, China.
Siyuan ZhouYueyang Centre for Disease Control and Prevention, Yueyang, Hunan Province, China.
Le DongGeorge Institute for Global Health at Peking University Health Science Centre, China.
Yu LiuSchool of Computer Science and Engineering, Beihang University, Beijing, China.
Xian LiGeorge Institute for Global Health at Peking University Health Science Centre, China.
Jing HeGeorge Institute for Global Health at Peking University Health Science Centre, China.
Changqiong WangWolfson Institute of Population Health, Barts and London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Monique TanWolfson Institute of Population Health, Barts and London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Jing SongWolfson Institute of Population Health, Barts and London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Graham A MacGregorWolfson Institute of Population Health, Barts and London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Funding

Medical Research Council MR/J015903/1Medical Research Council MR/T024399/1
6 · The paper itself

Abstract

objectiveTo determine whether a smartphone application based education programme can lower salt intake in schoolchildren and their families.

designParallel, cluster randomised controlled trial, with schools randomly assigned to either intervention or control group (1:1).

setting54 primary schools from three provinces in northern, central, and southern China, from 15 September 2018 to 27 December 2019.

participants592 children (308 (52.0%) boys; mean age 8.58 (standard deviation 0.41) years) in grade 3 of primary school (about 11 children per school) and 1184 adult family members (551 (46.5%) men; mean age 45.80 (12.87) years).

interventionChildren in the intervention group were taught, with support of the app, about salt reduction and assigned homework to encourage their families to participate in activities to reduce salt consumption.

main outcome measuresPrimary outcome was the difference in salt intake change (measured by 24 hour urinary sodium excretion) at 12 month follow-up, between the intervention and control groups.

resultsAfter baseline assessment, 297 children and 594 adult family members (from 27 schools) were allocated to the intervention group, and 295 children and 590 adult family members (from 27 schools) were allocated to the control group. During the trial, 27 (4.6%) children and 112 (9.5%) adults were lost to follow-up, owing to children having moved to another school or adults unable to attend follow-up assessments. The remaining 287 children and 546 adults (from 27 schools) in the intervention group and 278 children and 526 adults (from 27 schools) in the control group completed the 12 month follow-up assessment. Mean salt intake at baseline was 5.5 g/day (standard deviation 1.9) in children and 10.0 g/day (3.5) in adults in the intervention group, and 5.6 g/day (2.1) in children and 10.0 g/day (3.6) in adults in the control group. During the study, salt intake of the children increased in both intervention and control groups but to a lesser extent in the intervention group (mean effect of intervention after adjusting for confounding factors -0.25 g/day, 95% confidence interval -0.61 to 0.12, P=0.18). In adults, salt intake decreased in both intervention and control groups but to a greater extent in the intervention group (mean effect -0.82 g/day, -1.24 to -0.40, P<0.001). The mean effect on systolic blood pressure was -0.76 mm Hg (-2.37 to 0.86, P=0.36) in children and -1.64 mm Hg (-3.01 to -0.27, P=0.02) in adults.

conclusionsThe app based education programme delivered through primary school, using a child-to-parent approach, was effective in lowering salt intake and systolic blood pressure in adults, but the effects were not significant in children. Although this novel approach could potentially be scaled up to larger populations, the programme needs further strengthening to reduce salt intake across the whole population, including schoolchildren.

trial registrationChinese Clinical Trial Registry ChiCTR1800017553.

Indexed as

FamilyFeeding BehaviorSodium Chloride, DietaryChildChinaFemaleHumansMaleMiddle AgedMobile ApplicationsSchool Health ServicesSodium Chloride, Dietary

Identifiers

PMID35140061
PMCPMC8826455

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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.