Multimorbidity patterns in South Africa: A latent class analysis

被引:6
|
作者
Roomaney, Rifqah Abeeda [1 ,2 ]
van Wyk, Brian [2 ]
Cois, Annibale [1 ,3 ]
Pillay van-Wyk, Victoria [1 ]
机构
[1] South African Med Res Council, Burden Dis Res Unit, Cape Town, South Africa
[2] Univ Western Cape, Sch Publ Hlth, Cape Town, South Africa
[3] Univ Stellenbosch, Dept Global Hlth, Div Hlth Syst & Publ Hlth, Stellenbosch, South Africa
基金
英国医学研究理事会;
关键词
multimorbidity; disease patterns; disease clusters; latent class analysis; prevalence; South Africa; NONCOMMUNICABLE DISEASES; HYPERTENSION; MORTALITY; HIV; DEFINITION; DIAGNOSIS; COMMITTEE; ANEMIA;
D O I
10.3389/fpubh.2022.1082587
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
IntroductionSouth Africa has the largest burden of HIV worldwide and has a growing burden of non-communicable diseases; the combination of which may lead to diseases clustering in ways that are not seen in other regions. This study sought to identify common disease classes and sociodemographic and lifestyle factors associated with each disease class. MethodsData were analyzed from the South African Demographic and Health Survey 2016. A latent class analysis (LCA) was conducted using nine disease conditions. Sociodemographic and behavioral factors associated with each disease cluster were explored. All analysis was conducted in Stata 15 and the LCA Stata plugin was used to conduct the latent class and regression analysis. ResultsMultimorbid participants were included (n = 2 368). Four disease classes were identified: (1) HIV, Hypertension and Anemia (comprising 39.4% of the multimorbid population), (2) Anemia and Hypertension (23.7%), (3) Cardiovascular-related (19.9%) and (4) Diabetes and Hypertension (17.0%). Age, sex, and lifestyle risk factors were associated with class membership. In terms of age, with older adults were less likely to belong to the first class (HIV, Hypertension and Anemia). Males were more likely to belong to Class 2 (Anemia and Hypertension) and Class 4 (Diabetes and Hypertension). In terms of alcohol consumption, those that consumed alcohol were less likely to belong to Class 4 (Diabetes and Hypertension). Current smokers were more likely to belong to Class 3 (Cardiovascular-related). People with a higher body mass index tended to belong to Class 3 (Cardiovascular-related) or the Class 4 (Diabetes and Hypertension). ConclusionThis study affirmed that integrated care is urgently needed, evidenced by the largest disease class being an overlap of chronic infectious diseases and non-communicable diseases. This study also highlighted the need for hypertension to be addressed. Tackling the risk factors associated with hypertension could avert an epidemic of multimorbidity.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Patterns of Multimorbidity in the General Danish Population. A Latent Class Analysis
    Larsen, F. Breinholt
    Pedersen, M. Hauge
    Friis, K.
    Glumer, C.
    Lasgaard, M.
    EUROPEAN JOURNAL OF PUBLIC HEALTH, 2018, 28 : 330 - 330
  • [2] Latent class analysis identifies multimorbidity patterns in pigs with respiratory disease
    Barnes, Tamsin S.
    Lajarca, Annierica
    Bernales, Rona
    Alvaran, Paul John J.
    Shiela Abe, Flora
    Adonay, Florencio
    Allam, Alvin G.
    Baluyut, Augusto S.
    de Castro, Ronilo O.
    Ignacio, Corazon S.
    Lantican, Tessa Lyrene D. C.
    Lapuz, Eduardo L., Jr.
    Lasay, Jommel
    Mananggit, Milagros R.
    Meers, Joanne
    Jane Moog, Sarah
    Palaniappan, Gomathy
    Palmieri, Chiara
    Parke, Christopher R.
    Sybil Rosales, Joy
    Tapel, Marlon
    Tolentino, Johannes
    Turni, Conny
    Villarba, Lorelie
    Villar, Edwin C.
    Blackall, Patrick J.
    PREVENTIVE VETERINARY MEDICINE, 2021, 186
  • [3] Identifying Patterns of Multimorbidity in Older Americans: Application of Latent Class Analysis
    Whitson, Heather E.
    Johnson, Kimberly S.
    Sloane, Richard
    Cigolle, Christine T.
    Pieper, Carl F.
    Landerman, Lawrence
    Hastings, Susan N.
    JOURNAL OF THE AMERICAN GERIATRICS SOCIETY, 2016, 64 (08) : 1668 - 1673
  • [4] Spatial Analysis of patterns of Multimorbidity in the Thai Cohort Study Using Latent Class Analysis
    Xiyu Feng
    Haribondhu Sarma
    Sam-ang Seubsman
    Adrian Sleigh
    Matthew Kelly
    Journal of Epidemiology and Global Health, 15 (1)
  • [5] Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis
    Sadarangani, Tina
    Perissinotto, Carla
    Boafo, Jonelle
    Zhong, Jie
    Yu, Gary
    BMC GERIATRICS, 2022, 22 (01)
  • [6] Multimorbidity patterns in adult day health center clients with dementia: a latent class analysis
    Tina Sadarangani
    Carla Perissinotto
    Jonelle Boafo
    Jie Zhong
    Gary Yu
    BMC Geriatrics, 22
  • [7] Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study
    Olaya, Beatriz
    Victoria Moneta, Maria
    Felix Caballero, Francisco
    Tyrovolas, Stefanos
    Bayes, Ivet
    Luis Ayuso-Mateos, Jose
    Maria Haro, Josep
    BMC GERIATRICS, 2017, 17
  • [8] Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study
    Beatriz Olaya
    Maria Victoria Moneta
    Francisco Félix Caballero
    Stefanos Tyrovolas
    Ivet Bayes
    José Luis Ayuso-Mateos
    Josep Maria Haro
    BMC Geriatrics, 17
  • [9] Identifying non-communicable disease multimorbidity patterns and associated factors: a latent class analysis approach
    Puri, Parul
    Singh, Shri Kant
    Pati, Sanghamitra
    BMJ OPEN, 2022, 12 (07):
  • [10] Inequalities in multimorbidity in South Africa
    John Ele-Ojo Ataguba
    International Journal for Equity in Health, 12