Combining general and central measures of adiposity to identify risk of hypertension: a cross-sectional survey in rural India

Rathina Srinivasa Ragavan¹, Jordan Ismail¹, Roger G Evans², Velandai K Srikanth¹, Matthew Kaye¹, Rohina Joshi³, Kavumpurathu R Thankappan⁴, Clara K Chow⁵, Michaela A Riddell¹, Brian Oldenburg⁶, Ajay Mahal⁷, Kartik Kalyanram⁸, Kamakshi Kartik⁸, Oduru Suresh⁹, Nihal Thomas¹⁰, Gomathyamma K Mini¹¹, Pallab K Maulik¹², Simin Arabshahi¹, Amanda G Thrift¹³

Affiliations

¹ Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
² Cardiovascular Disease Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, Australia; Pre-clinical Critical Care Unit, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
³ School of Population Health, UNSW, Sydney, Australia.
⁴ Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India; Central University of Kerala, Kasaragod, India.
⁵ Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney and Department of Cardiology, Westmead Hospital, Sydney, Australia.
⁶ Melbourne School of Population and Global Health, University of Melbourne, Australia.
⁷ School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia; Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Australia.
⁸ Rishi Valley Rural Health Centre, Chittoor District, Andhra Pradesh, India.
⁹ Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia; Rishi Valley Rural Health Centre, Chittoor District, Andhra Pradesh, India.
¹⁰ Department of Endocrinology, Diabetes & Metabolism, Christian Medical College, Vellore, Tamil Nadu, India.
¹¹ Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India; Global Institute of Public Health, Ananthapuri Hospitals and Research Institute, Trivandrum, Kerala, India.
¹² George Institute for Global Health, New Delhi, India; University of New South Wales, Sydney, Australia.
¹³ Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia. Electronic address: Amanda.thrift@monash.edu.

PMID: 37142499
DOI: 10.1016/j.orcp.2023.04.005

Combining general and central measures of adiposity to identify risk of hypertension: a cross-sectional survey in rural India

Rathina Srinivasa Ragavan et al. Obes Res Clin Pract. 2023 May-Jun.

. 2023 May-Jun;17(3):249-256.

doi: 10.1016/j.orcp.2023.04.005. Epub 2023 May 2.

Authors

Affiliations

¹ Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia.
² Cardiovascular Disease Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, Australia; Pre-clinical Critical Care Unit, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
³ School of Population Health, UNSW, Sydney, Australia.
⁴ Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India; Central University of Kerala, Kasaragod, India.
⁵ Westmead Applied Research Centre, Faculty of Medicine and Health, University of Sydney and Department of Cardiology, Westmead Hospital, Sydney, Australia.
⁶ Melbourne School of Population and Global Health, University of Melbourne, Australia.
⁷ School of Public Health and Preventative Medicine, Monash University, Melbourne, Australia; Nossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Australia.
⁸ Rishi Valley Rural Health Centre, Chittoor District, Andhra Pradesh, India.
⁹ Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia; Rishi Valley Rural Health Centre, Chittoor District, Andhra Pradesh, India.
¹⁰ Department of Endocrinology, Diabetes & Metabolism, Christian Medical College, Vellore, Tamil Nadu, India.
¹¹ Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India; Global Institute of Public Health, Ananthapuri Hospitals and Research Institute, Trivandrum, Kerala, India.
¹² George Institute for Global Health, New Delhi, India; University of New South Wales, Sydney, Australia.
¹³ Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia. Electronic address: Amanda.thrift@monash.edu.

PMID: 37142499
DOI: 10.1016/j.orcp.2023.04.005

Abstract

Aim: In three socioeconomically diverse regions of rural India, we determined the optimal cut-offs for definition of overweight, the prevalence of overweight, and the relationships between measures of overweight and risk of hypertension.

Subjects and methods: Villages were randomly sampled within rural Trivandrum, West Godavari, and Rishi Valley. Sampling of individuals was stratified by age group and sex. Cut-offs for measures of adiposity were compared using area under the receiver operating characteristic curve. Associations between hypertension and definitions of overweight were assessed by logistic regression.

Results: Of 11 657 participants (50 % male; median age 45 years), 29.8 % had hypertension. Large proportions were overweight as defined by body mass index (BMI) ≥ 23 kg/m² (47.7 %), waist circumference (WC) ≥ 90 cm for men or ≥ 80 cm for women (39.6 %), waist-hip ratio (WHR) ≥ 0.9 for men or ≥ 0.8 for women (65.6 %), waist-height ratio (WHtR) ≥ 0.5 (62.5 %), or by BMI plus either WHR, WC or WHtR (45.0 %). All definitions of overweight were associated with hypertension, with optimal cut-offs being at, or close to, the World Health Organization (WHO) Asia-Pacific standards. Having overweight according to both BMI and a measure of central adiposity was associated with approximately twice the risk of hypertension than overweight defined by only one measure.

Conclusions: Overweight, as assessed by both general and central measures, is prevalent in rural southern India. WHO standard cut-offs are appropriate in this setting for assessing risk of hypertension. However, combining BMI with a measure of central adiposity identifies risk of hypertension better than any single measure. The risk of hypertension is significantly greater in those centrally and generally overweight than those overweight by a single measure.

Keywords: Body mass index; Hypertension; India; Prevalence; Waist-hip ratio.

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Conflict of interest statement

Declaration of Competing Interest All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare no support from any organization for the submitted work (apart from funding as outlined above). CKC, AGT, and RGE also report grants from the National Health & Medical Research Council (NHMRC; Australia) outside the submitted work; CKC, AGT, and RGE also report grants from the National Heart Foundation of Australia outside the submitted work. RKG reports research grants from the European Commission and the Polish Ministry of Science and Higher Education, outside the submitted work. RKG reports being a shareholder of Ajanta Pharma Limited, Divi’s Laboratories Limited, and NATCO Pharma Limited. There are no other relationships or activities that could appear to have influenced the submitted work.

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Combining general and central measures of adiposity to identify risk of hypertension: a cross-sectional survey in rural India

Affiliations

Combining general and central measures of adiposity to identify risk of hypertension: a cross-sectional survey in rural India

Authors

Affiliations

Abstract

Conflict of interest statement

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical