Country-specific key lifestyle factors and health outcomes for resource allocation in the general population: a network analysis across 29 countries

Li J 1 , Fong DYT 1 , Lok KYW 1 , Wong JYH 2 , Ho MM 1 , Choi EPH 1 Show all authors , Pandian V 3 , Davidson PM 4 , Duan W 5 , Tarrant M 6 , Lee JJ 1 , Lin CC 1 , Akingbade O 7 , Alabdulwahhab KM 8 , Ahmad MS 9 , Alboraie M 10 , Alzahrani MA 11 , Bilimale AS 12 , Boonpatcharanon S 13 , Byiringiro S 2 , Hasan MKC 14 , Schettini LC 15 , Corzo W 16 , De Leon JM 17 , De Leon AS 17 , Deek H 18 , Efficace F 19 , El Nayal MA 20 , El-Raey F 21 , Ensaldo-Carrasco E 22 , Escotorin P 23 , Fadodun OA 24 , Fawole IO 25 , Goh YS 26 , Irawan D 27 , Khan NE 28 , Koirala B 3 , Krishna A 29 , Kwok C 30 , Le TT 31 , Leal DG 32 , Lezana-Fernández MÁ 33 , Manirambona E 34 , Mantoani LC 35 , Meneses-González F 33 , Mohamed IE 36 , Mukeshimana M 37 , Nguyen CTM 31 , Nguyen HTT 31 , Nguyen KT 31 , Nguyen ST 31 , Nurumal MS 14 , Nzabonimana A 38 , Omer NAMA 39 , Ogungbe O 3 , Poon ACY 40 , Reséndiz-Rodriguez A 41 , Puang-Ngern B 13 , Sagun CG 17 , Shaik RA 9 , Shankar NG 42 , Sommer K 19 , Toro E 32 , Tran HTH 31 , Urgel EL 17 , Uwiringiyimana E 34 , Vanichbuncha T 13 , Youssef N 43

Affiliations 

  • 1 School of Nursing, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
  • 2 School of Nursing and Health Studies, Hong Kong Metropolitan University, Hong Kong SAR, China
  • 3 School of Nursing, Johns Hopkins University, Baltimore, Maryland, USA
  • 4 Vice-Chancellor and Principal, University of Wollongong, Wollongong, Australia
  • 5 East China University of Science and Technology, Department of Social Work, Shanghai, China
  • 6 School of Nursing, The University of British Columbia, Kelowna, British Columbia, Canada
  • 7 The Nethersole School of Nursing, The Chinese University of Hong Kong, Hong Kong, China
  • 8 College of Medicine, Majmaah University, Al Majmaah, Saudi Arabia
  • 9 Department of Family & Community Medicine, College of Medicine, Majmaah University, Majmaah, Saudi Arabia
  • 10 Department of Internal Medicine, Al-Azhar University, Cairo, Egypt
  • 11 Department of Urology, College of Medicine, Majmaah University, Al Majmaah, Saudi Arabia
  • 12 School of Public Health, JSS Medical College, JSS AHER, Mysuru, India
  • 13 Department of Statistics, Chulalongkorn Business School, Bangkok, Thailand
  • 14 Kulliyyah of Nursing, International Islamic University, Kuantan, Malaysia
  • 15 Italian Association against Leukaemia, Lymphoma and Myeloma, Rome, Italy
  • 16 Diálogos Guatemala, Guatemala, Guatemala
  • 17 School of Nursing, Centro Escolar University, Manila, Philippines
  • 18 Nursing Department, Faculty of Health Science, Beirut Arab University, Lebanon
  • 19 Data Centre and Health Outcomes Research Unit, Italian Group for Adult Hematologic Disease, Rome, Italy
  • 20 Department of Psychology, Beirut Arab University, Beirut, Lebanon
  • 21 Department of hepatogastroenterology and infectious diseases, Damietta faculty of medicine, Al-Azher University, Kairo, Egypt
  • 22 Ergonomics Research Centre, University of Guadalajara, Jalisco, Mexico
  • 23 Laboratory of Applied Prosocial Research, Department of Basic, Developmental and Educational Psychology, Autonomous University of Barcelona, Barcelona, Spain
  • 24 Faculty of Health Sciences, University of Lethbridge, Lethbridge, Alberta, Canada
  • 25 Faculty of Nursing, Ladoke Akintola University of Technology, Ogbomosho, Nigeria
  • 26 Alice Lee Centre for Nursing Studies, National University of Singapore, Singapore, Singapore
  • 27 School of Nursing, Wijaya Husada Health Institute, Bogor, Indonesia
  • 28 Department of Optometry, University of Kwazulu-Natal, Durban, South Africa
  • 29 Ecove, Ghaziabad, India
  • 30 School of Nursing, Paramedicine and Health Care Science, Charles Sturt University, New South Wales, Australia
  • 31 Nam Dinh University of Nursing, Nam Dinh, Vietnam
  • 32 Pontificia Universidad Católica de Valparaíso, School of Social Work, Valparaíso, Chile
  • 33 Research Department, National Commission for Medical Arbitration, Mexico, Mexico
  • 34 College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
  • 35 Department of Physiotherapy, Presidente Prudente, Faculty of Science and Technology, São Paulo State University (UNESP), São Paulo, Brazil
  • 36 Pharmacology and Toxicology Department, Faculty of Pharmacy, Benghazi University, Benghazi, Libya
  • 37 School of Nursing and Midwifery, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda
  • 38 Centre for Language Enhancement, College of Arts and Social Sciences, University of Rwanda, Huye, Rwanda
  • 39 Faculty of Medicine, Alzaiem Alazhari University, Khartoum North, Sudan
  • 40 Faculty of Health Sciences and Sports, Macao Polytechnic University, Macao, China
  • 41 National Autonomous University of Mexico, Mexico City, Mexico
  • 42 Mental Health and Learning division, Wrexham Maelor Hospital, Wrexham, UKyy
  • 43 Medical-surgical Nursing Department, Faculty of Nursing, Cairo University, Cairo, Egypt
J Glob Health, 2025 Jan 10;15:04011.
PMID: 39791329 DOI: 10.7189/jogh.15.04011

Abstract

BACKGROUND: We aimed to identify the central lifestyle, the most impactful among lifestyle factor clusters; the central health outcome, the most impactful among health outcome clusters; and the bridge lifestyle, the most strongly connected to health outcome clusters, across 29 countries to optimise resource allocation for local holistic health improvements.

METHODS: From July 2020 to August 2021, we surveyed 16 461 adults across 29 countries who self-reported changes in 18 lifestyle factors and 13 health outcomes due to the pandemic. Three networks were generated by network analysis for each country: lifestyle, health outcome, and bridge networks. We identified the variables with the highest bridge expected influence as central or bridge variables. Network validation included nonparametric and case-dropping subset bootstrapping, and centrality difference tests confirmed that the central or bridge variables had significantly higher expected influence than other variables within the same network.

RESULTS: Among 87 networks, 75 were validated with correlation-stability coefficients above 0.25. Nine central lifestyle types were identified in 28 countries: cooking at home (in 11 countries), food types in daily meals (in one country), less smoking tobacco (in two countries), less alcohol consumption (in two countries), less duration of sitting (in three countries), less consumption of snacks (in five countries), less sugary drinks (in five countries), having a meal at home (in two countries), taking alternative medicine or natural health products (in one country). Six central health outcomes were noted among 28 countries: social support received (in three countries), physical health (in one country), sleep quality (in four countries), quality of life (in seven countries), less mental burden (in three countries), less emotional distress (in 13 countries). Three bridge lifestyles were identified in 19 countries: food types in daily meals (in one country), cooking at home (in one country), overall amount of exercise (in 17 countries). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P 

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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