Journal Name European Journal of Epidemiology

Article Title Adiposity has a greater impact on hypertension in lean than not-lean populations: a systematic review and meta-analysis

Journal name European Journal of Epidemiology

Authors Simin Arabshahi*, Doreen Busingye, Asvini K. Subasinghe, Roger G. Evans,

Michaela A. Riddell, Amanda G. Thrift

*Corresponding author. Epidemiology and Prevention Unit, Stroke and Ageing Research

Department of Medicine, Southern Clinical School, Monash University, Australia. Tel: +61

395-947-524; Fax: +61 399-029-791; Email address: [email protected]

Supplementary Fig. 1 a

Survey Country year Sex ES (95% CI) %Weight

Lean Raipur Rani, India 1994-95 M 1.14 (1.02, 1.26) 28.20 Rishi Valley, India 2006 M 1.20 (1.13, 1.29) 71.80 Subtotal (I-squared = 0.0%, p = 0.420) 1.18 (1.12, 1.25) 100.00

Not-lean South Western China 1989 M 1.21 (1.11, 1.30) 22.59 Rajasthan, India 1994 M 1.11 (1.07, 1.15) 36.51 Moradabad, India <1997 M 1.19 (1.17, 1.22) 40.91 Subtotal (I-squared = 82.4%, p = 0.003) 1.16 (1.10, 1.23) 100.00

NOTE: Weights are from random effects analysis

HTN more frequent in lower.8 BMI  1|  HTN more1.4 frequent in higher BMI b

Survey Country year Sex ES (95% CI) %Weight

Lean Raipur Rani, India 1994-95 F 1.23 (1.17, 1.29) 20.56 Moradabad, India <1997 F 1.19 (1.16, 1.22) 70.08 Rishi Valley, India 2006 F 1.16 (1.08, 1.25) 9.36 Subtotal (I-squared = 4.1%, p = 0.353) 1.20 (1.17, 1.22) 100.00

Not-lean South Western China 1989 F 1.09 (0.97, 1.23) 19.32 Rajasthan, India 1994 F 1.01 (0.98, 1.02) 80.68 Subtotal (I-squared = 35.0%, p = 0.215) 1.02 (0.97, 1.09) 100.00

HTN more frequent in lower.8 BMI  1|  HTN more1.4 frequent in higher BMI c

Survey BMI Country year Category Sex ES (95% CI) %Weight

Lean Evodoula, Cameroon 1994&2003 25-30 M 1.30 (0.60, 2.70) 12.55 Evodoula, Cameroon 1994&2003 30+ M 9.40 (1.60, 54.00) 3.81 Assam, India <2004 25-30 M 1.84 (1.08, 3.11) 16.94 Assam, India <2004 30+ M 4.04 (0.64, 25.39) 3.53 Tamil Nadu, India 2005-07 23-27.5 M 2.95 (2.48, 3.50) 24.40 Tamil Nadu, India 2005-07 27.5+ M 5.14 (3.89, 6.80) 22.48 South western, Uganda 2009 25+ M 3.15 (1.80, 5.50) 16.29 Subtotal (I-squared = 74.1%, p = 0.001) 2.97 (2.05, 4.31) 100.00

Not-lean Nationwide, Mexico 2002 25-30 M 1.85 (1.54, 2.23) 16.91 Nationwide, Mexico 2002 30+ M 3.55 (2.51, 5.02) 13.10 Fuxin, Liaoning, China 2004-06 24-28 M 2.01 (1.79, 2.26) 18.18 Fuxin, Liaoning, China 2004-06 28+ M 4.22 (3.35, 5.32) 15.88 Zhangqiu, China 2007 25-30 M 2.27 (2.05, 2.51) 18.40 Zhangqiu, China 2007 30+ M 3.17 (2.63, 3.58) 17.53 Subtotal (I-squared = 91.4%, p = 0.000) 2.66 (2.13, 3.33) 100.00 . NOTE: Weights are from random effects analysis

.8 1 10 HTN more frequent in lower BMI  |  HTN more frequent in higher BMI d

Survey BMI Country year Category Sex ES (95% CI) %Weight Lean Evodoula, Cameroon 1994&2003 25-30 F 1.30 (0.70, 2.30) 10.76 Evodoula, Cameroon 1994&2003 30+ F 3.40 (1.30, 8.70) 6.00 Assam, India <2004 25-30 F 2.06 (1.28, 3.32) 13.18 Assam, India <2004 30+ F 2.66 (0.84, 8.49) 4.44 Tamil Nadu, India 2005-07 23-27.5 F 2.32 (1.94, 2.78) 20.13 Tamil Nadu, India 2005-07 27.5+ F 3.25 (2.57, 4.11) 18.96 West Bengal, India 2007-11 25-30 F 3.94 (2.65, 5.86) 15.04 West Bengal, India 2007-11 30+ F 5.78 (3.31, 10.09) 11.48 Subtotal (I-squared = 69.6%, p = 0.002) 2.83 (2.16, 3.72) 100.00 Not-lean Nationwide, Mexico 2002 25-30 F 1.81 (1.36, 2.41) 13.18 Nationwide, Mexico 2002 30+ F 3.44 (2.60, 4.55) 13.30 Fuxin, Liaoning, China 2004-06 24-28 F 1.88 (1.67, 2.11) 15.84 Fuxin, Liaoning, China 2004-06 28+ F 4.24 (3.52, 5.12) 14.90 Zhangqiu, China 2007 25-30 F 2.04 (1.86, 2.25) 16.06 Zhangqiu, China 2007 30+ F 2.81 (2.41, 3.28) 15.38 South western, Uganda2009 25+ F 2.25 (1.53, 3.30) 11.35 Subtotal (I-squared = 92.1%, p = 0.000) 2.52 (2.00, 3.17) 100.00 . NOTE: Weights are from random effects analysis

.8 1 10 HTN more frequent in lower BMI  |  HTN more frequent in higher BMI

Supplementary Fig. 1 Forest plots of the association between body mass index (BMI) and hypertension in populations in two categories of BMI in rural areas of low-to-middle income countries; BMI as (a) continuous variable in males, (b) continuous variable in females, (c) categorical variable in males, and (d) categorical variable in females

The center of each square indicates the effect size of that study and the horizontal lines indicate

95% CIs; the area of the square is proportional to the weight of the study; diamonds indicate pooled estimates in each category of BMI

Abbreviations: M males, F females, ES effect size, CI confidence interval, HTN hypertension

Definitions: (a) lean: mean BMI ≤ 19.9 kg/m2, not-lean: mean BMI ≥ 20.6 kg/m2; (b) lean: mean

BMI ≤ 20.2 kg/m2, not-lean: mean BMI ≥ 21.0 kg/m2; (c) lean: mean BMI ≤ 21.4 kg/m2 or BMI ≥

25 kg/m2 <17%, not-lean: mean BMI ≥ 23.0 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%; and (d) lean: mean

BMI ≤ 22.6 kg/m2 or BMI ≥ 25 kg/m2 <17%, not-lean: mean BMI ≥ 23.4 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17% Supplementary Fig. 2 a

Survey BMI Country year Category Sex ES (95% CI) %Weight Lean Evodoula, Cameroon 1994&2003 30+ M 9.40 (1.60, 54.00) 1.55 Fuxin, Liaoning, China 2004-06 28+ M 4.22 (3.35, 5.32) 24.22 Tamil Nadu, India 2005-07 27.5+ M 5.14 (3.89, 6.80) 21.68 Evodoula, Cameroon 1994&2003 30+ F 3.40 (1.30, 8.70) 4.77 Tamil Nadu, India 2005-07 27.5+ F 3.25 (2.57, 4.11) 24.03 Punial Valley, Pakistan 1995 >30 M&F 2.11 (1.30, 3.40) 13.08 Farafenni, Gambia 1996-97 30+ M&F 3.50 (1.20, 10.70) 3.74 Assam, India <2004 30+ M&F 3.10 (1.17, 8.22) 4.57 Amasaman, Ghana <2006 30+ M&F 6.86 (1.67, 28.20) 2.35 Subtotal (I-squared = 45.4%, p = 0.066) 3.75 (2.99, 4.69) 100.00 Not-lean Nationwide, Mexico 2002 30+ M 3.55 (2.51, 5.02) 11.15 Nationwide, Mexico 2002 30+ F 3.44 (2.60, 4.55) 12.63 Fuxin, Liaoning, China 2004-06 28+ F 4.24 (3.52, 5.12) 14.65 West Bengal, India 2007-11 >30 F 5.78 (3.31, 10.09) 7.26 Yarumal, Colombia 1994 30+ M&F 3.36 (1.48, 7.60) 4.38 Gonbad, Golestan, Iran 2004-08 30+ M&F 3.05 (2.88, 3.24) 16.59 Zhangqiu, China 2007 30+ M&F 2.91 (2.56, 3.38) 15.56 Yunnan, China 2008-10 28+ M&F 2.03 (1.84, 2.24) 16.17 NakhonRatchasima, Thailand 2010 30+ M&F 7.43 (1.68, 32.87) 1.62 Subtotal (I-squared = 89.9%, p = 0.000) 3.28 (2.69, 4.00) 100.00 . NOTE: Weights are from random effects analysis

.8 1 10 HTN more frequent in lower BMI  |  HTN more frequent in higher BMI b

Lean Assam, India <2004 30+ M 4.04 (0.64, 25.39) 2.20 Evodoula, Cameroon 1994&2003 30+ M 9.40 (1.60, 54.00) 2.40 Tamil Nadu, India 2005-07 27.5+ M 5.14 (3.89, 6.80) 95.40 Subtotal (I-squared = 0.0%, p = 0.774) 5.19 (3.95, 6.81) 100.00

Not-lean Fuxin, Liaoning, China 2004-06 28+ M 4.22 (3.35, 5.32) 33.39 Nationwide, Mexico 2002 30+ M 3.55 (2.51, 5.02) 20.75 Zhangqiu, China 2007 30+ M 3.17 (2.63, 3.58) 45.86 Subtotal (I-squared = 51.1%, p = 0.130) 3.57 (2.95, 4.32) 100.00

HTN more frequent in lower.1 BMI  1|  HTN more10 frequent in higher BMI c

Lean Assam, India <2004 30+ F 2.66 (0.84, 8.49) 6.15 Evodoula, Cameroon 1994&2003 30+ F 3.40 (1.30, 8.70) 8.85 Tamil Nadu, India 2005-07 27.5+ F 3.25 (2.57, 4.11) 62.85 West Bengal, India 2007-11 >30 F 5.78 (3.31, 10.09) 22.15 Subtotal (I-squared = 19.2%, p = 0.294) 3.66 (2.72, 4.92) 100.00

Not-lean Fuxin, Liaoning, China 2004-06 28+ F 4.24 (3.52, 5.12) 34.62 Nationwide, Mexico 2002 30+ F 3.44 (2.60, 4.55) 28.84 Zhangqiu, China 2007 30+ F 2.81 (2.41, 3.28) 36.54 Subtotal (I-squared = 82.0%, p = 0.004) 3.43 (2.61, 4.51) 100.00

.1 1 10 HTN more frequent in lower BMI  |  HTN more frequent in higher BMI

Supplementary Fig. 2 Forest plots of the association between obesity (measured by BMI) and hypertension in populations in two categories of BMI in rural areas of low-to-middle income countries; (a) total population, (b) males, and (c) females

The center of each square indicates the effect size of that study and the horizontal lines indicate

95% CIs; the area of the square is proportional to the weight of the study; diamonds indicate pooled effect size in each category of BMI

Abbreviations: M males, F females, ES effect size, CI confidence interval, HTN hypertension

Definitions: (a) lean: mean BMI < 23.3 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥

23.3 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%; (b) lean: mean BMI ≤ 22.1 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 23.0 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%; (c) lean: mean BMI ≤ 22.6 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 23.4 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17% Supplementary Tables

Supplementary Table 1 Summary of studies of multivariable association between

mean body mass index and hypertension in rural areas of low-to-middle income countries

(RLMICs), according to rank order of population and BMI and type of analysis

BMI (kg/m2)a Location T M F BMI in the analysis: Continuous Lean South West, China [17] 20.8b 20.6 21.0 Rajasthan, India [19] 21.1b Raipur Rani, Haryana, India [20] Hypertensive – 20.5 22 Normotensive – 18.6 18.9 Total 18.9b 18.7b 19.1b Moradabad, India [25] Hypertensive – 23.0 22.7 Normotensive – 20.3 20.0 Total 20.4b 20.6b 20.2b Rishi Valley, India [40] 19.5 19.9c 19.2c Not- Lean Rajasthan, India [19] 21.4b JingNing County, China [27], She 22.2 – – JingNing County, China [27], Han 22.5 – – Lucknow, Uttar Pradesh, India [31] Hypertensive 24.5 – – Normotensive 20.4 – – Total 22.9b – – Fuxin, Liaoning, China [35] 23.0 – – Sub-Saharan Africa [41] 21.3 – – Hadinaru, Karanataka, India [44] 21.4 – – BMI in the analysis: Categorical Lean Farafenni, Gambia [24] 20.2b 19.8 20.5 Nationwide Vietnam [32] 19.5 – – Abhoynagar, Bangladesh [37] 21.0 – – Matlab, Bangladesh [37] 20.9 – – Mirsarai, Bangladesh [37] 20.7 – – WATCH Bangladesh [37] 20.1 – – Vadu, India [37] 21.2 – – BMI (kg/m2)a Location T M F Purworejo, Indonesia [37] 21.9 – – Chililab, Vietnam [37] 20.9 – – Filabavi, Vietnam [37] 19.5 – – Tamil Nadu, India [38] 21.7b 21.4 21.9 Sub-Saharan Africa [41] 21.3 – – Maharashtra, India [43] 19.7 – – Chirai Goan, Varanasi, India [23] – 7.8%c 8.0%c Assam, India [33] 6.9% – – South Western Uganda [48] – 4.1% West Bengal, India [45] – – 16.8% Punial Valley, Ghizar, Pakistan [22] 14.8% – – Not-Lean Evodoula, Cameroon [21] 1994 – 21.9 22.2 2003 – 22.5 23.4 Total 22.4b 22.1b 22.6b San Antonio, Nueva Ecija, Philippines [26] 23.1d – – Nationwide, Mexico [28] 26.8d 26.0d 27.3d Chachoengsao, Thailand [30] 25.0 – – Fuxin, Liaoning, China [34] 23.2 23.0 23.4 Gonbad, Golestan, Iran [36] 26.3d – – Kanchanaburi, Thailand [37] 23.8 – – Amasaman, Ga, Ghana [39] 23.2 – – Nandan County, China [46], Bai Ku Yao 22.2 – – Nandan County, China [46], Han Chinese 22.7 – – Hubei, China [49] 22.1 – – Zhejiang, China [51] 23.1 – – Yunnan, China [47] 23.3b 23.1 23.4 Yarumal, Colombia [18] 55% – – Inner Mongolia, China [29] 20.2%b 15.4% 23.6% Zhangqiu, Shandong, China [42] 59% – – South Western Uganda [48] – 18.4% NakhonRatchasima, Thailand [50] 44.0% – –

Abbreviations: T total, M males, F females.

Definitions: BMI as (1) continuous variable: lean: mean BMI < 21.4 kg/m2; not-lean:

mean BMI ≥ 21.4 kg/m2. (2) as categorical variable: lean: mean BMI < 22.0 kg/m2 or

BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 22.0 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%. a Values are mean or percentage of overweight (BMI: ≥ 25 kg/m2). b Calculated based on weighting the number of study population in each group. c Percentage of overweight (BMI: >

25 kg/m2). d Reported by the author through personal contact. Supplementary Table 2 Studies of body mass index and hypertension in rural areas of low-to middle income countries (RLMICs), across categories of mean BMI and type of analysis

Survey BMI OR (95% CI) 2 Location year (kg/m ) Total Males Females Adjustments BMI in the analysis: Continuous Lean South Western, China [17] 1989 Cont. – 1.21 (1.11,1.30) 1.09 (0.97,1.23) Age, smoking status, alcohol consumption, physical activity, and heart rate Rajasthan, India [19] 1994 Cont. – 1.01 (0.98,1.02)a Age, education, physical activity, and smoking status Raipur Rani, India [20] 1994–95 Cont. – 1.14 (1.02,1.26) 1.23 (1.17,1.29) Age, education, SES, physical activity, smoking status, and alcohol consumption Moradabad, India [25] < 1997 Cont. – 1.19 (1.17,1.22) 1.19 (1.16,1.22) Age, WHR, SES, energy expenditure, 2 hour plasma insulin, 2 hour blood glucose, and salt intake Rishi Valley, South India [40] 2006 Cont. – 1.20 (1.13,1.29) 1.16 (1.08,1.25) M: Age, alcohol consumption, physical activity, education, and cholesterol F: Age, smokeless tobacco, education, and triglyceride Not-lean Rajasthan, India [19] 1994 Cont. – 1.11 (1.07,1.15)a Age, education, physical activity, and smoking status JingNing County, China [27], She 2002 Cont. 1.22 (1.16,1.28) – – Age, sex, and alcohol consumption JingNing County, China [27], Han 2002 Cont. 1.10 (1.03,1.18) – – Age, sex, and alcohol consumption Survey BMI OR (95% CI) 2 Location year (kg/m ) Total Males Females Adjustments Lucknow, Uttar Pradesh, India [31] 2003–04 Cont. 1.04 (0.88,1.23) – – Age, sex, WC, physical activity, smoking status, and diabetes Fuxin, Liaoning, China [35] 2004–06 Cont. 1.07 (1.06,1.08) – – Age, sex, smoking status, alcohol consumption, salt intake, and race Sub-Saharan Africa [41] 2006–07 Cont. 1.03 (1.00,1.07) – – Age, sex, village, sampling variables, television ownership, and work-related vigorous physical activity Hadinaru, Karanataka, India [44] 2007–08 Cont. 1.27 (1.19,1.35) – – Age, occupation, physical activity, fat intake, and diabetes BMI in the analysis: Categorical Lean Punial Valley, Ghizar, Pakistan [22] 1995 < 25 1 – – Age, smoking status, use of snuff, 25–30 2.01 (1.51,2.67) – – family history of hypertension, use of salted tea, and wine > 30 2.11 (1.30,3.40) – – consumption Chirai Goan, Varanasi, India [23] < 1996 > 25 1.71 – – Salt intake, fat intake, and energy (1.13,31.86) intake Farafenni, Gambia [24] 1996–97 ≥ 30 3.5 (1.2,10.7) – – Age and sex Nationwide Vietnam [32] 2003–04 < 18.5 1 – – Age, sex, education, and occupation 18.5–25 1.33 (0.92, 1.89) ≥ 25 2.67 (1.75, 4.08) Assam, India [33] < 2004 18.5–25 1 1 1 Age, sex, WHR, type of work, < 18.5 0.65 (0.53,0.78)b 0.54 (0.39,0.74)b 0.71 (0.55,0.91)b smoking status, tobacco chewing, alcohol consumption, extra salt 25–30 1.95 (1.37,2.78)b 1.84 (1.08,3.11)b 2.06 (1.28,3.32)b intake, and marital status ≥ 30 3.10 (1.17,8.22)b 4.04 (0.64,25.39)b 2.66 (0.84,8.49)b Abhoynagar, Bangladesh [37] 2005 ≥ 25 2.67 (1.89,3.77) – – Age, sex, and education Survey BMI OR (95% CI) 2 Location year (kg/m ) Total Males Females Adjustments Matlab, Bangladesh [37] 2005 ≥ 25 3.21 (2.28,4.53) – – Age, sex, and education Mirsarai, Bangladesh [37] 2005 ≥ 25 2.11 (1.53,2.92) – – Age, sex, and education WATCH, Bangladesh [37] 2005 ≥ 25 3.44 (2.12,5.58) – – Age, sex, and education Vadu, India [37] 2005 ≥ 25 3.29 (2.49,4.36) – – Age, sex, and education Purworejo, Indonesia [37] 2005 ≥ 25 2.51 (1.86,3.37) – – Age, sex, and education Chililab, Vietnam [37] 2005 ≥ 25 2.03 (1.39,2.96) – – Age, sex, and education Filabavi, Vietnam [37] 2005 ≥ 25 4.94 (2.57,9.5) – – Age, sex, and education Tamil Nadu, India [38] 2005–07 < 23 – 1 1 Age 23–27.50 – 2.95 (2.48,3.50) 2.32 (1.94,2.78) ≥ 27.50 – 5.14 (3.89,6.80) 3.25 (2.57,4.11) Sub-Saharan Africa [41] 2006–07 < 18 1 – – Age, sex, village, sampling 18–25 1.17 (0.75,1.80) – – variables, television ownership, and work-related vigorous > 25 1.64 (0.95,2.85) – – physical activity Maharashtra, India [43] 2007–08 ≥ 25 2.59 (1.87,3.58) – – Age, sex, education, smoking status, alcohol consumption, hypercholesterolemia, and diabetes West Bengal, India [45] 2007–11 <18.5 – – 1.56 (1.14,2.14) Age, education, income, kitchen 18.5–24.9 – – 1 location, fuel type, and food habit 25–30 – – 3.94 (2.65,5.86) > 30 – – 5.78 (3.31,10.09) South western Uganda [48] 2009 < 18.5 – 1 M: Age, education, and glucose ≥ 18.5–25 – 2.27 (1.69,3.04) 7 mmol/L; ≥ 25 – 3.15 (1.80,5.50) Not-lean Yarumal, Colombia [18] 1994 < 25 1 – – Age, sex, smoking status, Survey BMI OR (95% CI) 2 Location year (kg/m ) Total Males Females Adjustments 25–30 2.41 (1.32,4.40) – – diabetes, stress, family history of ≥ 30 3.36 (1.48,7.60) – – hypertension, and family history of myocardial infarction Evodoula, Cameroon [21] 1994 & 18.5–25 – 1 1 Age, education, smoking status, 2003 < 18.5 – 0.9 (0.4,2.3) 0.4 (0.1,0.9) alcohol consumption, and year of study 25–30 – 1.3 (0.6,2.7) 1.3 (0.7,2.3) ≥ 30 – 9.4 (1.6,54.0) 3.4 (1.3,8.7) San Antonio, Nueva Ecija, 1998 ≥ 25 2.38 (1.34,4.22) – – Age and family history of Philippines [26] hypertension Nationwide, Mexico [28] 2002 < 25 – 1 1 Age, education, and early life 25–30 – 1.85 (1.54,2.23) 1.81 (1.36,2.41) experiences ≥ 30 – 3.55 (2.51,5.02) 3.44 (2.60,4.55) Inner Mongolia, China [29] 2002–03 ≥ 25 2.37(1.82, 3.08) – – Age, sex, WC, alcohol consumption, hyperlipidemia, and hyperglycemia Chachoengsao, Thailand [30] 2003 > 23 3.41 (1.80,6.45) – – Age, family history of hypertension, and marital status Fuxin, Liaoning, China [34] 2004–06 < 24 – 1 1 Age, education, smoking status, 24–28 – 2.01 (1.79,2.26) 1.88 (1.67,2.11) alcohol consumption, lipid disorder, salt intake, and ethnicity ≥ 28 – 4.22 (3.35,5.32) 4.24 (3.52,5.12) Gonbad, Golestan, Iran [36] 2004–08 <18.5 0.59 (0.53,0.66) Age, sex, education, wealth score, 18.5–25 1 smoking status, physical activity, black tea consumption, green tea 25–30 1.89 (1.79,1.99) consumption, and ethnicity ≥ 30 3.05 (2.88,3.24) Kanchanaburi, Thailand [37] 2005 ≥ 25 2.42 (1.95,3) – – Age, sex, and education Amasaman, Ga, Ghana [39] < 2006 18.5–25 1 – – Age, sex, education, occupation, 25–30 5.80 (1.39,24.3) – – job-related physical activity, Survey BMI OR (95% CI) 2 Location year (kg/m ) Total Males Females Adjustments ≥ 30 6.86 (1.67,28.2) – – smoking status, alcohol consumption, contraceptive use, and diabetes Zhangqiu, Shandong, China [42] 2007 < 25 1 1 1 Age, sex, education, physical 25–30 2.13 (1.99,2.28) 2.27 (2.05,2.51) 2.04 (1.86,2.25) activity, smoking status, and alcohol consumption ≥ 30 2.91 (2.56,3.38) 3.17 (2.63,3.58) 2.81 (2.41,3.28) Nandan County, China [46], Bai < 2008 > 24 2.01 (1.15,3.48) – – Age, WC, education, physical Ku Yao activity, alcohol consumption, Nandan County, China [46], Han < 2008 > 24 1.81 (1.07,2.72) – – triglycerides, total energy intake, Chinese total fat intake, sodium intake, total dietary fibre intake, and ethnic group Yunnan, China [47] 2008–10 ≥ 28 2.03 (1.84,2.24) – – Age, sex, education, household income, smoking status, alcohol consumption, family history of chronic diseases, and ethnicity South western Uganda [48] 2009 < 18.5 – 1 F: Age, WC, and glucose ≥ 7 18.5–25 – 1.74 (1.29,2.33) mmol/L ≥ 25 – 2.25 (1.53,3.30) Hubei, China [49] < 2010 ≥ 24 1.53 (1.18,1.97) – – Educational level, sedentary work, physical exercise, alcohol consumption, positive family history of hypertension, salty diet, vegetable and fruit intake, animal insides intake, and dysarteriotony (pressure difference > 60mmHg or <20mmHg between SBP and DBP) Zhejiang, China [51] 2010 < 23 1 – – Age, education, income, alcohol 23–25 1.67(1.48,1.89) – – consumption, diabetes, and Survey BMI OR (95% CI) 2 Location year (kg/m ) Total Males Females Adjustments ≥ 25 3.29(2.94,3.69) – – triglycerides NakhonRatchasima, Thailand [50] 2010 ≥ 30 7.43 – – Age, education, occupation, (1.68,32.87) presence of high cholesterol, having mild to high stress

Abbreviations: OR odds ratio, CI confidence interval, Cont. continuous, SBP systolic blood pressure, DBP diastolic blood pressure, BMI body

max index, WC waist circumference, WHR waist-to-hip ratio, SES socioeconomic status.

Definitions: BMI as (1) continuous variable: lean: mean BMI < 21.4 kg/m2; not-lean: mean BMI ≥ 21.4 kg/m2. (2) as categorical variable: lean:

mean BMI < 22.0 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 22.0 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%.

a Relative risk (RR). b Participants who used antihypertensive medication were excluded from this analysis. Supplementary Table 3 Summary of studies of multivariable association between waist circumference and hypertension in rural areas of low-to-middle income countries (RLMICs), according to mean body mass index and type of analysis

BMI (kg/m2)a WC (cm)b Location T M F T M F WC in the analysis: Continuous Lean Nandan County, China [46], Bai Ku 22.2 – – 71.5 – – Yao Nandan County, China [46], Han 22.7 – – 74.4 – – Chinese Lucknow, Uttar Pradesh, India [31] Hypertensive 24.5 – – 85.9 – – Normotensive 20.4 – – 71.6 – – Not-lean Fuxin, Liaoning, China [53], Han 23.1 – – 80.4 – – Fuxin, Liaoning, China [53], Mongolian 23.6 – – 81.9 – – WC in the analysis: Categorical Lean Tamil Nadu, India [38] 21.6 21.4 21.9 78.7 71.5 South western Uganda [48] – 4.1% WC: F: ≥ 80 cm; M: ≥ 94 cm – 1% Thiruvananthapuram, Kerala, India [55], 16.8% – – LS WC: F: ≥ 80 cm; M: ≥ 85 cm 46.8% – – Not-lean Yunnan, China [47] 23.3c 23.1 23.4 – 81.2 79.5 Fuxin, Liaoning, China [54] – – 23.4 – – 80.0 Inner Mongolia, China [29] 20.2%c 15.4% 23.6% WC:F: ≥ 80 cm; M: ≥ 85 cm – 31.9% 47.8% Virgem das Graças, Minas Gerais, Brazil 31%c 12.9% 48.3% – – – [52] South western Uganda [48] 18.4% WC: F: ≥ 80 cm; M: ≥ 94 cm – 31.2%

Abbreviations: T total, M males, F females, LS longitudinal study.

Definitions: WC as (1) continuous variable: lean: mean BMI < 23.1 kg/m2; not-lean: mean

BMI ≥ 23.1 kg/m2. (2) as categorical variable: lean: mean BMI < 23.3 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 23.3 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%.

16 a Values are mean or percentage of overweight (BMI: ≥ 25 kg/m2). b Values are mean or percentage of abdominal overweight. c Calculated based on weighting the number of study population in each group.

17 Supplementary Table 4 Studies of waist circumference and hypertension in rural areas of low-to-middle income countries (RLMICs), across categories of mean body mass index and type of analysis

Survey OR (95% CI) Location year WC (cm) Total Males Females Adjustments WC in the analysis: Continuous Lean Lucknow, Uttar Pradesh, India [31] 2003–04 Cont. 1.09 (1.02,1.18) – – Age, sex, BMI, physical activity, smoking status, and diabetes Nandan County, China [46], Bai < 2008 Cont. 1.73 (1.12,2.12) – – Age, BMI, education, physical Ku Yao Chinese activity, alcohol consumption, Nandan County, China [46], Han < 2008 Cont. 1.35 (1.20,2.46) triglycerides, total energy intake, Chinese total fat intake, sodium intake, total dietary fibre intake, and ethnic group Not- lean China [53], Mongolian Chinese 2004–06 Cont. 1.018 (1.012,1.023) – – Age, sex, BMI, education, smoking status, alcohol consumption, lipid China [53], Han Chinese 2004–06 Cont. 1.018 (1.015,1.020) – – disorder, diabetes, family history of hypertension, and salt intake WC in the analysis: Categorical Lean Tamil Nadu, India [38] 2005–07 M: ≥ 90 – 3.34 (2.80,3.98) 2.51 (2.12,2.98) Age F: ≥ 80 South western Uganda [48] 2009 M: ≥ 0.94 – 1.41 (0.47,4.19) M: Age, BMI, education, and glucose ≥ 7 mmol/L; Thiruvananthapuram, Kerala, India 2010 M: ≥ 85; 2.45 (1.45,3.70)a – – Age, sex, BMI, education, physical [55], LS F: ≥ 80 activity, smoking status, alcohol consumption, Total cholesterol to

18 Survey OR (95% CI) Location year WC (cm) Total Males Females Adjustments HDL ratio, LDL, fruit and vegetable intake, and BP Not-lean Inner Mongolia, China [29] 2002–03 M: ≥ 85; 1.34 (1.07, 1.68) – – Age, sex, BMI, alcohol F: ≥ 80 consumption, hyperlipidemia, and hyperglycemia Virgem das Graças, Brazil [52] 2004 M: < 94; 1 – – Age, sex, BMI, WHR, education, F: < 80 alcohol consumption, total M: 94– 2.63 (0.98,7.02) – cholesterol, HDL, LDL, 102; triglycerides, body fat percentage, F: 80–88 and skin colour M: ≥ 102; 3.84 (1.50,9.85) – F: ≥ 88 Fuxin, Liaoning, China [54] 2004–06 < 80 – – 1 Age, education, physical activity, b smoking status, alcohol 80–88 – – 1.31 (1.26,1.37) consumption, and diet ≥ 88 – – 1.78 (1.64,1.94)b Yunnan China [47] 2008–10 M: >90; 3.01 (2.59,3.48) – – Age, sex, education, household F: > 80 income, smoking status, alcohol consumption, family history of chronic diseases, and ethnicity South western Uganda [48] 2009 F: ≥ 80 – 1.37 (1.07,1.74) F: Age, BMI, and glucose ≥ 7 mmol/L

Abbreviations: OR odds ratio, CI confidence interval, Cont. continuous, M male, F female; Cont., continuous; Cont. continuous, SBP systolic blood pressure, DBP diastolic blood pressure, BMI body max index, WHR waist-to-hip ratio, SES socioeconomic status.

19 Definitions: WC as (1) continuous variable: lean: mean BMI < 23.1 kg/m2; not-lean: mean BMI ≥ 23.1 kg/m2. (2) as categorical variable: lean: mean BMI < 23.3 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 23.3 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%. a Participants did not take antihypertensive medications the last two weeks before they were examined. b Prevalence ratio (PR).

20 Supplementary Table 5 Studies of prevalence of hypertension in rural areas of

Low-to-middle income countries (RLMICs), according to mean body mass index

(BMI) and type of analysis for the association between BMI and hypertension

Location Survey year No HTN % BMI in the analysis: Continuous Lean South Western, China [17], T 1989 8,241 2.6a Rajasthan, India [19], F 1994 1,166 17 Raipur Rani, Haryana, India [20], T 1994–95 2,559 4.5 Moradabad, India [25], M < 1997 140 11.2 Moradabad, India [25], F < 1997 115 8.6 Rishi Valley, India [40], T 2006 1,474 11.4a Pooled Total 13,695 5.3b Not- Lean Rajasthan, India [19], M 1994 1,982 24 JingNing County, China [27], She, T 2002 1,168 31.9 JingNing County, China [27], Han, T 2002 520 21.9 Lucknow, Uttar Pradesh, India [31], T 2003–04 400 14.5 Fuxin, Liaoning, China [35] , T 2004–06 45,925 37.8 Sub-Saharan Africa [41], T 2006–07 1,485 22 Hadinaru, Karanataka, India [44], T 2007–08 1,423 15.0 Pooled Totalb 52,903 35.8 P-valuec 0.0001 BMI in the analysis: Categorical Lean Punial Valley, Ghizar, Pakistan [22], T 1995 4,203 14.3a Nationwide Vietnam [32], T 2003–04 2,020 14.3a Assam, India [33], T < 2004 3,180 33.3 Abhoynagar, Bangladesh [37], T 2005 1,983 16.8 Mirsarai, Bangladesh [37], T 2005 2,028 24.1 WATCH Bangladesh [37], T 2005 1,997 9.3 Vadu, India [37], T 2005 2,074 23.6 Purworejo, Indonesia [37], T 2005 1,946 24.1 Filabavi, Vietnam [37], T 2005 2,000 15.1 Matlab, Bangladesh [37], T 2005 2,061 17.1 Chililab, Vietnam [37], T 2005 2,194 18.3 Tamil Nadu, India [38], T 2005–07 10,463 21.5 Sub-Saharan Africa [41], T 2006–07 1,485 22 Maharashtra, India [43], T 2007–08 3,591 25.3 West Bengal, India [45], F 2007–11 1,186 26.3 South western Uganda [48], M 2009 2,719 22.5 Pooled Totalb 45,130 20.8

21 Location Survey year No HTN % Not-Lean Evodoula, Cameroon [21], T 1994 & 2003 1,132 26.7 San Antonio, Nueva Ecija, Philippines [26], T 1998 336 23.0 Nationwide, Mexico [28], T 2002 6,035 37.7a Inner Mongolia, China [29], T 2002–03 2,532 37.2 Chachoengsao, Thailand [30], T 2003 527 17.8 Fuxin, Liaoning, China [34], T 2004–06 45,925 37.8 Gonbad, Golestan, Iran [36], T 2004–08 39,399 42.9 Kanchanaburi, Thailand [37], T 2005 2,146 27.7 Amasaman, Ga, Ghana [39], T < 2006 362 25.4 Zhangqiu, Shandong, China [42], T 2007 20,167 30.6 Nandan County, China [46], Bai Ku Yao, < 2008 485 21.9 T Nandan County, China [46], Han Chinese, < 2008 501 28.9 T Yunnan, China [47], T 2008–10 10,007 32.8 South western Uganda [48], F 2009 3,959 22.6 Hubei, China [49], T < 2010 2,438 26.9 Zhejiang, China [51], T 2010 10,525 27.0 Pooled Totalb 146,476 36.0 P-valuec 0.0001

Abbreviations: HTN hypertension, M male, F female, T total.

Definitions: Hypertension: SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg or using antihypertensive medication. BMI as (1) continuous variable: lean: mean BMI < 21.4 kg/m2; not-lean: mean BMI ≥ 21.4 kg/m2; (2) as categorical variable: lean: mean BMI < 22.0 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 22.0 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%. a Calculated based on weighting the numbers of participants in the study. b Calculated based on weighting the numbers in each study. c P-value from chi-square test for comparison of the prevalence of hypertension with the first group of BMI category.

22 Supplementary Table 6 Studies of prevalence of hypertension in rural areas of low-to-middle income countries (RLMICs), according to mean body mass index and type of analysis for the association between waist circumference and hypertension

Location Survey year No HTN % WC in the analysis: Continuous Lean Lucknow, Uttar Pradesh, India [31], T 2003–04 400 14.5 Nandan County, China [46], Bai Ku Yao, <2008 485 21.9 T Nandan County, China [46], Han Chinese, <2008 501 28.9 T Pooled Totala 1,386 18.1 Not- Lean Fuxin, Liaoning, China [53], Mongolian, T 2004–06 9,236 42.0 Fuxin, Liaoning, China [53], Han, T 2004–06 36,154 36.7 Pooled Totala 45,390 37.8 P-valueb 0.0001 WC in the analysis: Categorical Lean Tamil Nadu, India [38], T 2005–07 10,463 21.5 South western Uganda [48], M 2009 2,719 22.5 Pooled Totala 13,182 21.7 Not-Lean Inner Mongolia, China [29], T 2002–03 2,532 37.2 Virgem das Graças, Minas Gerais, Brazil [52], 2004 287 47.0 T Fuxin, Liaoning, China [54], F 2004–06 23,178 38.6 Yunnan, China [47], T 2008–10 10,007 32.8 South western Uganda [48], F 2009 3,959 22.6 Pooled Totala 39,963 35.5 P-valueb 0.0001

Abbreviations: BMI body mass index, WC waist circumference, T total, M males, F females, LS longitudinal study.

Definitions: Hypertension: SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg or using antihypertensive medication. b WC as (1) continuous variable: lean: mean BMI < 23.1 kg/m2; not-lean: mean BMI ≥ 23.1 kg/m2; (2) as categorical variable: lean: mean BMI < 23.3 kg/m2 or BMI ≥ 25 kg/m2 <17%; not-lean: mean BMI ≥ 23.3 kg/m2 or BMI ≥ 25 kg/m2 ≥ 17%.

23 a Calculated based on weighting the numbers in each study. b P-value from chi-square test for comparison of the prevalence of hypertension with the first group of BMI category.