Do Fruit and Vegetable Policies, Socio-Environmental Factors, and Physical Activity Influence Fruit and Vegetable Intake Among Adolescents?

Journal of Adolescent Health xxx (2019) 1e9

www.jahonline.org Original article

Do Fruit and Vegetable Policies, Socio-Environmental Factors, and Physical Activity Influence Fruit and Vegetable Intake Among Adolescents? Sandra A. Darfour-Oduro, Ph.D. a, *, Juan E. Andrade, Ph.D. b, c, and Diana S. Grigsby-Toussaint, Ph.D. a, b, d a

Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Champaign, Illinois Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Champaign, Illinois c Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Champaign, Illinois d Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, Rhode Island b

Article history: Received March 4, 2019; Accepted July 20, 2019 Keywords: Fruit and vegetable policies; Fruits and vegetables intake; Adolescents; Low- and middle-income countries (LMICs); Physical activity; Parental supervision

A B S T R A C T

Purpose: Several factors are known to influence the intake of fruits and vegetables (FV) among adolescents. However, few studies have examined the role that FV policies and associated factors (such as availability of food at home, parental support, and physical activity) play on consumption of FV, particularly among adolescents in low- and middle-income countries (LMICs). Method: Adolescent data (except for FV policy status) were obtained from the Global School-based Student Health Survey from 2004 to 2013. Information on FV policies was obtained from government ministries, World Health Organization databases, Scopus, and PubMed. Countries were designated as having the policy if the policy was issued at least a year before Global School-based Student Health Survey data collection (n ¼ 13 LMICs). Countries without FV policies were based on the absence of a policy between 2004 and 2013 (n ¼ 11 LMICs). The total analytic sample included 89,843 adolescents from 24 countries. Results: Logistic regression models revealed a positive association between the presence of FV policy and the adequate consumption of FV (adjusted odds ratio [AOR] ¼ 2.04; 95% confidence interval [CI]: 1.74e2.40; p-value < .001). Parental supervision was positively associated with sufficient intake of FV (AOR ¼ 1.62; 95% CI: 1.42e1.84; p-value < .001). Physical activity was also positively associated with adolescents consuming 5 servings of FV daily (AOR ¼ 1.30; 95% CI: 1.13e1.50; p-value < .001). Conclusion: Adolescents' physical environment (presence of FV policies, unavailability of food), social environment (parental connectedness, supervision, and bonding), and physical activity behavior are all significant predictors of adolescents' intake of FV. Ó 2019 Society for Adolescent Health and Medicine. All rights reserved.

Conflicts of interest: The authors have no conflicts of interest to disclose. * Address correspondence to: Sandra A. Darfour-Oduro, Ph.D., Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, 1206 South Fourth Street, 323 Armory, Champaign, IL 61820. E-mail address: [email protected] (S.A. Darfour-Oduro). 1054-139X/Ó 2019 Society for Adolescent Health and Medicine. All rights reserved. https://doi.org/10.1016/j.jadohealth.2019.07.016

IMPLICATIONS AND CONTRIBUTION

Adolescents living in lowand middle-income countries with fruit and vegetable (FV) policies have a higher intake of FV compared with those living in countries without FV policies. Parenting style does influence the intake of FV among adolescents in low- and middle-income countries. Physically active adolescents are more likely to consume World Health Organization's recommended quota of FV.

Adequate intake of fruits and vegetables (FV) is considered an important component of a healthy diet [1], especially among adolescents as healthy diet behaviors, including FV intake, continue into adulthood [2]. Low FV consumption is an important modifiable risk factor that is contributing to the rising global burden of chronic diseases. It is estimated that up to 2.7 million

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Figure 1. Results of the selection process for LMICs based on availability of FV policies before the year in which the GSHS data were collected.

lives could potentially be saved each year if FV consumption was sufficiently increased [1]. As reviewed in two meta-analyses and the results from a prospective cohort study have demonstrated, the increase FV intake reduces the risk for cardiovascular diseases (CVDs), cancer, and all-cause mortality [3e5]. Studies have also shown that several factors are correlated with the intake of FV among adolescents. These factors include age, gender, socioeconomic position, preferences for FV, parental FV intake, parental modeling, family rules, and parental encouragement and availability/accessibility to FV at home [6,7]. The family is a vital component of an adolescent's immediate environment since it is the parents who provide the food environment that encourages the consumption of certain foods regularly [8]. Kremers et al. [9] studied parenting style and fruit consumption among adolescents and found that fruit consumption was higher among adolescents with authoritative parents. In addition, adolescents who reported having parents with indulgent parenting styles were more likely to consume fruits than their adolescent counterparts from homes with little to no parental supervision [9]. Noia and Byrd-Bredbenner [10] found maternal FV intake to be consistently associated with child and adolescent FV intake. Moreover, the presence of high FV at home has also been associated with an increase in FV intake [11]. Thus, establishing healthy behaviors among adolescents through a supportive food environment, one that includes the consumption of FV, will result in continuous health benefits into adulthood.

The presence of FV policies has had a positive impact on the consumption of FV [6]. In the U.S. and Finland, studies have found that students who participate in school lunch programs that provide FV have a higher intake of FV compared with students who do not participate in school lunch programs [6]. A recent systematic review study also found that the presence of policies supportive of a healthy school food environment increased the intake of FV [12]. According to the theoretical framework of the Pro Children Project as proposed by Klepp et al. [13], the determinants that influence intake of FV among adolescents can operate at the distal level, whereas others operate at the proximal level. The distal determinants of FV intake include those found in the cultural environment (e.g., socioeconomic status), the physical environment (e.g., dietary guidelines, school food policies, local food policies, and food availability at home), and the social environment (e.g., parental encouragement and parental rules). The cultural, physical, and social environments, in turn, influence the more proximal personal factors such as parental practices, family rules, and physical activity [13]. Most studies in low- and middle-income countries (LMICs) have focused on undernutrition, but with the nutrition transition the focus have changed on dietary behaviors that increase the risk for noncommunicable diseases (NCDs) such as CVDs and cancer [14,15]. As countries improve their economies, there has been an increase in the consumption of unhealthy diets, for

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Table 1 Countries with available/adopted policies at least one year before GSHS data collection and a list of countries without policies from 2004 to 2013 (N ¼ 24 countries) LMICs with GSHS data (2004e2013) Countries with policy (n ¼ 13) Malawi Jordan Egypt Maldives Dominica Grenada Jamaica Fiji Malaysia Mongolia Indonesia Philippines Thailand Countries without policy (n ¼ 11) Benin Mauritania Sudan Algeria Libya Morocco Syrian Arab Republic Pakistan Argentina Honduras Tonga

Policy status/year

GSHS data year

GNI

Available policy (2007) Available policy (2006) Adopted policy (2007) Adopted policy (2008) Available policy (2007) Available policy (2007) Available policy (2004) Adopted policy (2008) Adopted policy (2005) Adopted policy (2006) Available policy (2005) Available policy (2005) Available policy (2007)

2009 2007 2011 2009 2009 2008 2010 2010 2012 2013 2007 2011 2008

Low income Upper middle Lower middle Upper middle Upper middle Upper middle Upper middle Upper middle Upper middle Lower middle Lower middle Lower middle Upper middle

income income income income income income income income income income income income

No No No No No No No

policy policy policy policy policy policy policy

2009 2010 2012 2011 2007 2010 2010

Low income Lower middle Lower middle Upper middle Upper middle Lower middle Lower middle

income income income income income income

No No No No

policy policy policy policy

2009 2007 2012 2010

Lower Upper Lower Upper

income income income income

example, those high in calories from simple sugars and fats and low in FV and whole grains, especially among adolescents in LMICs [16,17] which is associated with NCDs such as CVDs and cancers [14,15]. In 2016, NCDs accounted for 56% of disabilityadjusted life years among adolescents globally and was a leading contributor to disease burden among adolescents [18]. Studies have also shown evidence of the double burden of malnutrition (i.e., undernutrition and overnutrition) seen among adolescents in LMICs [19]. This transition in dietary behaviors is occurring globally as it is evident in the 324 million adolescents who were reported as being overweight or obese in 2016 [18]. Thus, recognizing the factors that predict the intake of FV consumption among adolescents is critical in developing interventions to increase their intake. This will be helpful as the joint Food and Agriculture Organization/World Health Organization (WHO) workshop reached a consensus in 2004 that a per capita daily minimum of 400 g of FV should be the ultimate goal for all countries and encouraged each country to develop intermediate objectives to reach this goal [1]. To date, there have been few studies across LMICs focusing on determinants of FV consumption among adolescents [16,20,21]. The aim of this study is to determine the relationship between the physical and social environments as well as physical activity on the daily intake of FV among adolescents in LMICs. Methods The study was conducted using (1) Global School-based Student Health Survey (GSHS) data from 2004 to 2013 [22] and (2) FV policies information from 2004 to 2013 for 49 LMICs [23] (Figure 1). The GSHS is a standardized survey developed by the WHO in collaboration with the United Nations International Children's Emergency Fund, the United Nations Educational, Scientific and Cultural Organization, and the United Nations

middle middle middle middle

Program on HIV/AIDS, with technical assistance provided by the Centers for Disease Control and Prevention. It is a collaborative surveillance project designed to help countries measure and assess health behaviors and protective factors among students between the ages of 13e17 years. Country selection was based on the availability of GSHS data from 2004 to 2013 [24]. LMICs were defined as countries that had a gross national income (GNI) of less than $12,616 in 2012 [25]. Information on the availability of FV policies (policies/action plan/guidelines) from 2004 to 2013 were obtained from a review of the literature of FV policies in LMICs. The review was performed on government Web sites responsible for nutrition (Ministry of Health, Ministry of Agriculture, and the Ministry of Education) using the following search terms “Nutrition, fruits, vegetables, children, adolescents, schools and NCD.” A second review of policies was conducted using WHO databases (Global database on the Implementation of Nutrition Action and the Nutrition Landscape Information System). Finally, a third search was done using these search terms “Nutrition OR food AND Policy” and country name as well as “Fruits OR vegetables AND Policy” and country's name in abstract and citations in databases including Scopus and the U.S. National Library of Medicine's PubMed [23]. Countries were classified as having an available or adopted policy from 2004 to 2013 if the national policy document was published at least one year before the GSHS data were collected (n ¼ 13 LMICs) and countries without policies were based on the absence of a policy between 2004 and 2013 and availability of GSHS data (n ¼ 11) (Figure 1 and Table 1). The study did not require institutional review board approval. Survey measures The survey measures used were based on the following GSHS questions: [26].

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Table 2 Characteristics of the physical environment (food insecurity) of adolescents in LMICs with FV policies and LMICs without FV policies using the Global Schoolbased Student Health Survey (2004e2013) (N ¼ 89,843 adolescents) LMICs

Food insecurity

Countries with FV policies Jordan Never Rarely/sometimes Mostly/always Malawi Never Rarely/sometimes Mostly/always Egypt Never Rarely/sometimes Mostly/always Maldives Never Rarely/sometimes Mostly/always Dominica Never Rarely/sometimes Mostly/always Grenada Never Rarely/sometimes Mostly/always Jamaica Never Rarely/sometimes Mostly/always Fiji Never Rarely/sometimes Mostly/always Malaysia Never Rarely/sometimes Mostly/always Mongolia Never Rarely/sometimes Mostly/always Indonesia Never Rarely/sometimes Mostly/always Philippines Never Rarely/sometimes Mostly/always Thailand Never Rarely/sometimes Mostly/always Countries without FV policies Benin Never Rarely/sometimes Mostly/always Mauritania Never Rarely/sometimes Mostly/always Sudan Never Rarely/sometimes Mostly/always Algeria Never Rarely/sometimes Mostly/always Morocco Never Rarely/sometimes Mostly/always Libya Never Rarely/sometimes Mostly/always Syria Never Rarely/sometimes Mostly/always Pakistan Never Rarely/sometimes Mostly/always Argentina Never Rarely/sometimes Mostly/always

Table 2 Continued LMICs

N (weighted %)

Honduras

1,096 780 306 965 1,048 287 1,373 1,034 119 2,013 973 186 1,062 480 92 853 548 118 693 732 167 567 921 176 10,055 14,178 1,212 3,374 1,888 105 1,140 1,775 197 1,858 3,034 375 1,287 1,375 95

(50) (35.8) (14.1) (34.3) (47.3) (18.5) (53.5) (41.9) (4.5) (62.7) (30.4) (6.9) (64.3) (30.0) (5.7) (55.8) (36.1) (8.1) (39.5) (46.8) (13.7) (33.9) (55.4) (10.7) (40.3) (54.8) (4.9) (62.7) (35.3) (1.9) (35.7) (58.5) (5.9) (33.3) (59.9) (6.8) (47.3) (49.3) (3.4)

Tonga

741 1,488 454 837 983 213 1,236 761 179 2,446 1,675 389 1,948 619 308 676 1,250 281 1,456 1,300 324 3,780 1,043 311 1,321 588 589

(28.1) (54.2) (17.7) (41.1) (48.5) (10.4) (56.2) (34.2) (9.6) (54.8) (36.7) (8.5) (67.6) (21.7) (10.7) (30.2) (56.8) (13.0) (46.7) (42.2) (11.1) (74.6) (19.7) (5.8) (67.1) (29.8) (3.1)

Food insecurity Never Rarely/sometimes Mostly/always Never Rarely/sometimes Mostly/always

N (weighted %) 1,133 565 69 564 1,315 311

(63.3) (32.8) (3.9) (25.6) (60.2) (14.2)

Food insecurity: “During the past 30 days, how often did you go hungry because there was not enough food in your home?” The response options were (a) Never, (b) Rarely, (c) Sometimes, (d) Most of the time, and (e) Always. Parental connectedness: “During the past 30 days, how often did your parents or guardians understand your problems or worries?” The response options were (a) Never, (b) Rarely, (c) Sometimes, (d) Most of the time, and (e) Always. Parental Supervision: “During the past 30 days, how often did your parents or guardians check to see if your homework was done”? The response options were (a) Never, (b) Rarely, (c) Sometimes, (d) Most of the time, and (e) Always. Parental Bonding: “During the past 30 days, how often did your parents or guardians really know what you were doing with your free time?” The response options were (a) Never, (b) Rarely, (c) Sometimes, (d) Most of the time, and (e) Always. Physical Activity: “During the past 7 days, on how many days were you physically active for a total of at least 60 minutes per day?” The response options were (a) 0 days, (b) 1 day, (c) 2 days, (d) 3 days, (e) 4 days, (f) 5 days, (g) 6 days, and (h) 7 days. Fruits: “During the past 30 days, how many times per day did you usually eat fruits?” The response options were (A) I did not eat fruit during the past 30 days, (B) Less than one time per day, (C) 1 time per day, (D) 2 times per day, (E) 3 times per day, (F) 4 times per day, (G) 5 or more times per day. Vegetables: “During the past 30 days, how many times per day did you usually eat vegetables?” The response options were (A) I did not eat vegetables during the past 30 days, (B) Less than one time per day, (C) 1 time per day, (D) 2 times per day, (E) 3 times per day, (F) 4 times per day, (G) 5 or more times per day.

Survey coding Food insecurity answers were coded 1 ¼ never, 2 ¼ rarely and sometimes, and 3 ¼ most of the time and always. Parental connectedness answers were coded 1 ¼ connected (most of the time and always), 2 ¼ some connection (rarely and sometimes), and 3 ¼ not connected (never). Parental Supervision answers were coded 1 ¼ supervised (most of the time and always), 2 ¼ some supervision (rarely and sometimes), and 3 ¼ not supervised (never). Parental Bonding answers were coded 1 ¼ bonded (most of the time and always); 2 ¼ some bonding (rarely and sometimes), and 3 ¼ no bonding (never). Physical Activity answers were coded 1 ¼ met WHO recommendations for 60 minutes for 7 days of physical activity, and 2 ¼ did not meet WHO recommendations. FV intake: Adolescents who ate (2 or more/day) servings of fruits and (3 or more/day) servings of vegetables were coded as 1 ¼ adequate FV intake (5 servings/day). Adolescents who ate

S.A. Darfour-Oduro et al. / Journal of Adolescent Health xxx (2019) 1e9 Table 3 Characteristics of the social environment of adolescents in LMICs with FV policies and LMICs without FV policies using the Global School-based Student Health Survey (2004e2013) (N ¼ 89,843 adolescents) LMICs

Social environment

Countries with FV policies Jordan Parental connectedness

Egypt

Maldives

Grenada

Jamaica

Malaysia

Mongolia

Indonesia

Connected Some connection Not connected Parental supervision Supervised Some supervision Not supervised Parental bonding Bonded Some bonding No bonding Parental connectedness Connected Some connection Not connected Parental supervision Supervised Some supervision Not connected Parental bonding Bonded Some bonding No bonding Parental connectedness Connected Some connection Not connected Parental supervision Supervised Some supervision Not supervised Parental bonding Bonded Some bonding No bonding Parental connectedness Connected Some connection Not connected Parental supervision Supervised Some supervision Not supervised Parental bonding Bonded Some bonding No bonding Parental connectedness Connected Some connection Not connected Parental supervision Supervised Some supervision Not supervised Parental bonding Bonded Some bonding No bonding Parental connectedness Connected Some connection Not connected Parental supervision Supervised Some supervision Not supervised Parental bonding Bonded Some bonding No bonding Parental Connectedness Connected Some connection Not connected Parental supervision Supervised Some supervision Not supervised Parental bonding Bonded Some bonding No bonding Parental connectedness Connected Some connection Not connected Parental supervision Supervised

Table 3 Continued LMICs

Social environment

N (weighted %) Parental bonding 898 670 576 1,089 660 408 1,000 670 506 871 1,062 554 1,089 921 478 1,170 888 418 1,008 1,077 853 851 1,077 1,058 1,403 1,047 1,047 462 541 422 425 554 470 537 539 373 499 617 460 627 562 408 630 562 388 8,277 11,751 5,411 3,618 11,821 9,967 11,334 11,034 3,025 1,656 2,220 1,475 2,532 2,033 798 2,615 1,896 806 1,099 1,516 472 1,045

(41.4) (31.3) (27.3) (49.9) (30.9) (19.2) (45.6) (31.0) (23.4) (34.7) (42.9) (22.4) (43.3) (38.1) (18.6) (46.4) (36.5) (17.1) (33.7) (37.7) (28.6) (28.5) (37.1) (34.4) (46.9) (35.3) (17.8) (31.6) (37.8) (30.6) (28.9) (38.3) (32.8) (36.7) (38.1) (25.2) (33.9) (40.6) (25.5) (39.4) (34.5) (26.2) (38.9) (36.4) (24.6) (31.5) (46.2) (22.3) (14.2) (46.2) (39.6) (43.1) (44.2) (12.7) (30.7) (41.7) (27.6) (46.7) (38.4) (14.9) (48.8) (36.2) (15.0) (35.0) (49.7) (15.3) (32.2)

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Philippines Parental connectedness

Parental supervision

Parental bonding

Thailand

Parental connectedness

Parental supervision

Parental bonding

Countries without FV policies Benin Parental connectedness

Parental supervision

Parental bonding

Mauritania

Parental connectedness

Parental supervision

Parental bonding

Sudan

Parental connectedness

Parental supervision

Parental bonding

Morocco

Parental connectedness

Parental supervision

Parental bonding

Libya

Parental connectedness

Parental supervision

Parental bonding

Syria

Parental connectedness

N (weighted %) Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding

1,522 540 1,385 1,328 365 1,420 2,739 1,081 1,147 2,625 1,418 1,662 2,601 973 928 1,227 560 994 1,201 522 1,215 1,142 340

(50.8) (17.0) (44.6) (44.6) (10.7) (27.1) (52.4) (20.5) (21.4) (49.6) (29.0) (30.8) (50.3) (18.9) (34.1) (45.1) (20.7) (35.8) (44.3) (19.8) (45.4) (40.0) (12.7)

Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected

1,097 1,074 505 1,281 933 463 1,207 1,011 445 658 624 693 956 559 447 694 676 606 750 730 663 935 722 461 918 697 508 785 829 1,246 1,283 808 782 1,110 706 1,029 710 660 755 758 586 797 948 626 571 832

(42.6) (38.6) (18.8) (49.6) (35.0) (15.4) (46.4) (36.9) (16.7) (33.9) (31.2) (34.9) (49.1) (28.3) (22.6) (35.3) (33.9) (30.8) (34.9) (35.3) (29.8) (45.2) (33.6) (21.2) (42.7) (34.1) (23.3) (27.4) (29.3) (43.3) (44.5) (28.3) (27.1) (39.0) (25.2) (35.8) (33.3) (31.1) (35.6) (35.3) (27.2) (37.4) (43.9) (29.0) (27.1) (26.4)

(continued on next page)

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Table 3 Continued LMICs

Social environment

Parental supervision

Parental bonding

Pakistan

Parental connectedness

Parental supervision

Parental bonding

Argentina

Parental connectedness

Parental supervision

Parental bonding

Honduras

Parental connectedness

Parental supervision

Parental bonding

Tonga

Parental connectedness

Parental supervision

Parental bonding

N (weighted %) Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding Connected Some connection Not connected Supervised Some supervision Not supervised Bonded Some bonding No bonding

1,143 1,097 1,235 1,061 770 1,191 1,051 844 2,723 1,590 820 2,630 1,581 940 2,552 1,795 759 1,016 572 304 722 680 515 1,058 536 293 807 548 389 902 500 353 950 454 329 604 923 666 855 869 431 673 821 697

(37.0) (36.6) (39.7) (34.5) (25.8) (37.4) (34.5) (28.0) (54.7) (29.8) (15.5) (52.5) (29.4) (18.1) (50.6) (34.6) (14.8) (53.6) (30.6) (15.8) (37.4) (35.4) (27.1) (56.4) (28.4) (15.2) (46.3) (31.1) (22.6) (51.4) (28.6) (20.1) (54.8) (26.3) (19.0) (27.1) (42.2) (30.7) (39.8) (39.8) (20.4) (30.4) (37.6) (30.0)

No data for Malawi, Dominica, Fiji, and Algeria. LMICs ¼ low- and middle-income countries.

(<2/day) servings of fruits and (<3/day) servings of vegetables were coded as 2 ¼ inadequate FV intake (<5 servings/day) [27].

Data analysis The data were analyzed using SPSS, version 21, software (SPSS, Inc., Chicago, IL). The GSHS data collection employs a complex sampling design [28]. The GSHS data were analyzed taking into account the weight, stratum, and primary sampling unit. Descriptive statistics were generated to determine the characteristics of adolescents' physical environment (food insecurity) and social environment (parental connectedness, parental supervision, and parental bonding) in countries with FV policies and in countries without FV policies (Tables 2 and 3). Logistic regression models were used to determine the association between the physical environment (presence or absence of FV policy in the country and food insecurity), social environment (parental connectedness, parental supervision, parental bonding), and personal factors (physical activity) on the

recommended daily intake of FV (5 servings). These factors were entered into the model starting with the adolescent physical environment, social environment, and physical activity behavior using the stepwise approach. Pseudo R Squares (Nagelkerke R2) was used to determine the model fitness and the contribution of each factor to the model. Age, sex, and countries GNI were used as confounders. The total analytic sample includes 89,843 adolescents from 24 countries. Results The study results showed that 13 countries had available or adopted the FV policies in their respective countries before data on the GSHS were collected. Thus, these countries were classified as having the “Presence of FV policy.” Eleven countries did not have policies and were classified as “No FV policy” (Figure 1 and Table 1). Of the 13 countries with FV policies, four countries (Malawi, Fiji, Philippines, and Thailand) had policies/action plan/ guidelines that were school based, where consumption of FV was encouraged in schools. Malawi and Fiji had policy/action plan/ guidelines that were community based. These guidelines focused on community-based preparation and consumption of FV. Eleven countries (Malawi, Jordan, Maldives, Jamaica, Dominica, Grenada, Fiji, Indonesia, Malaysia, Philippines, and Thailand) had policies/action plan/guidelines targeting the general public, where people were encouraged to grow and consume adequate amount of FV. Two countries (Indonesia and the Philippines) had policies/action plan/guidelines that targeted the environment. Availability and accessibility of FV in stores were promoted. The policy from the Philippines targeted the economy where the provision of subsidies/tax breaks on FV was encouraged to increase consumption. Four countries (Jordan, Indonesia, Malaysia, and Mongolia) targeted the mass media to raise awareness on the importance of FV consumption. Finally, Malaysia had policies/action plan/guidelines to meet the WHO recommendations of the daily servings of FV [23]. The generated descriptive statistics shows the unweighted frequencies and weighted percentages of food insecurity among adolescents in LMICs. Among countries with policies, the highest weighted percentage of adolescents who reported never going hungry due to unavailability of food at home were seen in Dominica (64.3%), Maldives (62.7%) and Mongolia (62.7%). Of the countries without policies, adolescents in Pakistan (74.6%), Morocco (67.6%), Argentina (67.1%), and Honduras (63.3%) were the most food secure (Table 2). Also, the highest weighted percentages of adolescents who lived in countries with policies that reported going hungry often due to unavailability of food at home were in Malawi (18.5%), Jordan (14.1%), and Jamaica (13.7%). Among countries without policies, the highest proportions of adolescents who went hungry often due to unavailability of food at home were seen in Benin (17.7%), Tonga (14.2%), and Libya (13%) (Table 2). Table 3 shows the generated descriptive statistics of the social environment of adolescents in LMICs. Of the countries with policies, adolescents in Jordan (41.4%) felt the most connected with their parents, and among countries without policies, adolescents in Pakistan (54.7%) and Argentina (53.6%) felt the most connected with their parents. With respect to parental supervision, among countries with policies, adolescents in Jordan (49.9%) and Philippines (49.6%) were the most supervised. In countries without policies, adolescents in Pakistan (52.5%) and Honduras reported being well supervised. For parental bonding,

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Table 4 Results of logistic regression models showing the association between adolescents physical environment, social environment, and personal factor (physical activity) on meeting the WHO recommendations for daily intake of fruits and vegetables (5 servings), using the Global School-based Student Health Survey (2004e2013) (N ¼ 89,843 adolescents) Variables

Physical environment Presence of FV policy No FV policy (Ref) Food insecurity Never hungry Sometimes hungry Mostly/always (Ref) Social environment Parental connectedness Connected Some connection Not connected (Ref) Parental supervision Supervised Some supervision Not supervised (Ref) Parental bonding Bonded Some bonding No bonding (Ref) Personal factor Physical activity Met WHO's recommendations for daily physical activity Not meeting the recommendation (Ref)

Crude

Model 1 (Nagelkerke R2 ¼ .017)

Model 2 (Nagelkerke R2 ¼ .031)

Model 3 (Nagelkerke R2 ¼ .034)

OR (95% CI)

AOR (95% CI)

AOR (95% CI)

AOR (95% CI)

1.48 (1.30e1.69)***

1.62 (1.42e1.85)***

2.03 (1.73e2.39)***

2.04 (1.74e2.40)***

.94 (.81e1.09) .82 (.71e.94)**

.92 (.79e1.06) .74 (.65e.86)***

.88 (.74e1.05) .76 (.64e.90)**

.88 (.74e1.04) .75 (.63e.90)**

1.19 (1.06e1.34)** .97 (.87e1.09)

NA NA

1.06 (.93e1.21) .91 (.81e1.02)

1.05 (.92e1.20) .91 (.81e1.03)

1.51 (1.33e1.71)*** 1.12 (1.02e1.24)*

NA NA

1.61 (1.41e1.83)*** 1.16 (1.05e1.28)**

1.62 (1.42e1.84)*** 1.17 (1.05e1.29)**

1.09 (.98e1.20) .96 (.86e1.08)

NA NA

.86 (.77e.95)** .85 (.75e.96)**

.84 (.75e.93)** .84 (.74e.95)**

1.42 (1.24e1.63)***

NA

NA

1.30 (1.13e1.50)***

Each model was controlled for age, sex, and GNI; * p < .05, ** p < .01, *** p < .001. Models 1, 2 and 3 were all significant at p < .05. AOR ¼ adjusted odds ratio; CI ¼ confidence interval; FV ¼ fruits and vegetables; NA ¼ not applicable; OR ¼ odds ratio; WHO ¼ World Health Organization.

adolescents in Argentina (56.4%), Honduras (54.8%), and Pakistan (50.6%) reported bonding well with their parents. Table 4 depicts the association between adolescents' physical environment, social environment, and physical activity behavior on meeting the recommendations of five or more servings of FV. The study results showed that adolescents who live in countries with policies (odds ratio [OR] ¼ 1.48; 95% confidence interval [CI]: 1.30e1.69), are connected to their parents (OR ¼ 1.19; 95% CI: 1.06e1.34), are supervised (OR ¼ 1.51; 95% CI: 1.33e1.71), have some supervision (OR ¼ 1.12; 95% CI: 1.02e1.24), and exercise 60 minutes daily (OR ¼ 1.42; 95% CI: 1.24e1.63) are more likely to consume five or more servings of FV than those adolescents who live in countries without policies, not connected with parent, not supervised by parents, and do not exercise 60 minutes daily for seven days, respectively. However, adolescents who reported sometimes or rarely going hungry were less likely (OR ¼ .82; 95% CI: .71e.94) to consume five or more servings of FV compared with adolescents who went hungry often (food insecurity). Controlling for age, sex, and GNI model 1 shows that the presence of FV policy is positively associated with adolescents meeting WHO recommendations for daily intake of FV (adjusted OR [AOR] ¼ 1.62; 95% CI: 1.42e.85). Also, adolescents who reported going hungry sometimes were less likely to meet the recommendations (AOR ¼ .74; 95% CI: .65e.86) compared to adolescents who reported going hungry often. Model 2 shows the association between adolescents' physical and social environment variables on meeting five or more servings of FV daily while controlling for age, sex, and GNI. The study results showed that the presence of FV policy (AOR ¼ 2.03; 95% CI: 1.73e2.39), having parental supervision (supervised AOR ¼

1.61; 95% CI: 1.41e1.83); as well as having some supervision (AOR ¼ 1.17; 95% CI: 1.05e1.29) were all positively associated with adolescents consuming five or more servings of FV daily. On the other hand, adolescents who reported going hungry sometimes (AOR ¼ .76; 95% CI: .64e.90), bonded with parents (AOR ¼ .86; 95% CI: .77e.95), or had some bonding with parents (AOR ¼ .85; 95% CI: .75e.96) were less likely to meet the WHO recommendations for daily intake of 5 servings of FV compared with adolescents who went hungry often and have no bonding with their parents, respectively. Model 3 depicts the association between adolescents' physical and social environment, and physical activity behavior on consuming five servings of FV daily while controlling for age, sex, and GNI. The results of the full model show that adolescents who live in countries with FV policies (AOR ¼ 2.04; 95% CI: 1.74e2.40), who are supervised by the parents all the time (AOR ¼ 1.62; 95% CI: 1.42e1.84), or who have some form of parental supervision (AOR ¼ 1.17; 95% CI: 1.05e1.29), and who are physically active for 60 minutes daily for seven days (AOR ¼ 1.30; 95% CI: 1.13e1.50) are more likely to consume five or more servings of FV daily. However, adolescents who reported sometimes going hungry (AOR ¼ .75; 95% CI: .63e.90), who bond with their parents (AOR ¼ .84; 95% CI: .75e.93), or had some bonding with their parents (AOR ¼ .84; 95% CI: .74e.95) were less likely to meet the WHO recommendations for daily intake of FV compared with adolescents who went hungry often and reported not bonding with their parents, respectively. Finally, the pseudo R2 value increased as adolescents' social environment factors and physical activity behavior were added to their physical environment factors in explaining their intake of FV (Table 4).

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Discussion Although policies related to lifestyle behaviors (such as increasing consumption of FVs have been effective in high-income countries [6,12,29e31]), few studies have examined relevant policy effectiveness for adolescents in LMICs. This developmental stage is critical since many life-long lifestyle behaviors begin during adolescence and could have a substantial effect on the current NCD epidemic observed during adulthood [32]. In addition, mortality associated with NCDs occurs at a much younger age in LMICs compared with high-income countries [15]. This confirms the need to explore the physical environment, social environment, and physical activity as determinants of the daily intake of FV among adolescents in LMICs. The study results showed that the presence of FV policy in LMICs is positively associated with adolescents meeting the WHO recommendations for daily intake of FV. Adolescents in countries with FV policy were 1.48 times more likely to consume five servings of FV compared to adolescents in countries without FV policies. A similar positive impact of policies/action plan/ guidelines on health behavior has been observed in high-income countries. Several independent studies [33e36] found that food guidelines that primarily focused on FV offered as part of school lunch programs led to an increased FV availability and this ranged from .28 to .48 additional servings/day [37]. Also, studies in the U.S. and Finland found that students participating in school lunch programs consume more FV than those who do not [6].The evidence shows that the presence of policies addressing food choices and dietary gaps in high-income countries and LMICs may lead to lifestyle modifications, including an increase in the consumption of FV by targeted populations. Overall, FV policies create the environment that encourages the intake, availability, and accessibility of FV to improve diet and health outcomes. According to the Food and Agriculture Organization, “Food security is a situation that exists when all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life” [38]. The GSHS assessed food security by determining the number of adolescents who went hungry because there was not enough food in the home. This study found the availability of food at home (food security) was negatively associated with adolescents meeting the WHO recommendations for daily FV. Batgerel et al. [39] also found that adolescents who always experienced hunger in the last month (food insecurity) were more likely to have adequate FV intake compared to the adolescents who did not feel hungry (food security). It is important to note that availability of food as presented in the GSHS data does not necessarily mean availability of FV, and this could be the reason why a negative association was found in this study. Parenting style has a direct influence on adolescents' eating behaviors. According to Nicklas et al. [8], the family is a vital component of an adolescent's immediate environment since it is the parents who provide the food environment that encourages the consumption of certain foods regularly. This study found that parental supervision was positively associated with adolescents consuming 5 servings of FV daily. These findings are consistent with those from Kremer et al. [9] who found that adolescents raised in an authoritative home consumed more fruits than those raised with other parenting styles. These authors also found that adolescents with authoritative parents perceived the most social support towards fruit consumption [9]. Peltzer and Pengpid [20] also found that lack of parental supervision was also positively

associated with inadequate intake of fruits (AOR ¼ 1.25; 95% CI: 1.04e1.49; p-value < .05) and vegetables (AOR ¼ 1.57; 95% CI: 1.30e1.89; p-value < .001) among adolescents. The study results showed that parenting style influences the intake of FV among adolescents. Sedentary lifestyles along with low physical activity are key contributors to overweight and obesity rates worldwide. In this study, we found that adolescents who were active for a total of 60 minutes daily (meeting the WHO recommendations) were more likely to consume  5 servings of FV daily compared to adolescents who did not meet the WHO recommendations for daily physical activity behavior. Our results are consistent with those of Peltzer and Pengpid [21] who used the GSHS data to determine FV consumption and associated factors among adolescents attending schools in five Southeast Asian countries. The authors found that being physically inactive was associated with inadequate intake of FV among adolescents. Our study builds on the knowledge that in general, individuals with healthy lifestyle behaviors in one area (e.g., physical activity) are more likely to also engage in healthy behaviors in another aspect of their lives (e.g., dietary behavior). Strengths and limitations The study has several strengths and limitations. It is among the few cross-national studies examining the determinants and predictors of FV consumption among adolescents in LMICs. Second, the study applied the pro children model [13] developed and used in some European countries to determine if the constructs in the models are significant predictors of daily FV intake in LMICs. The limitations of this study include the use of the GSHS data, which surveys adolescents in schools; thus, the association between the adolescents' physical environment, social environment, and physical activity might not necessarily be a reflection of the FV consumption among all adolescents in LMICs. Specifically, poorer (or low-income) adolescents who are unable to attend school or have dropped out would not be captured by the WHO GSHS. Second, adolescents had to recall and self-report their FV consumption patterns during the past 30 days. This approach may result in either overestimating or underestimating consumption behaviors, leading to information bias. We also cannot be certain that the five servings of FV reported by the adolescents were equivalent to 400 grams since we could not quantify the servings from the GSHS data. Also, it would have been useful to take into consideration parents' FV intake since parental modeling could have an effect on adolescents meeting the WHO recommendation, but the GSHS does not collect this information. Furthermore, the addition of variables such as parental socioeconomic status, adolescents preferences for FV, knowledge and attitude towards FV consumption, availability of FV at school, self-efficacy, and perceived barriers would have improved the models, but these variables are not included in the GSHS data set. Owing to this limitation, only a few variables were included in the models resulting in the low R-squares reported. This low Rsquare has also been reported by Batgerel et al. [39] in their studies using the GSHS data from students in Mongolia. The criteria for determining the availability of FV policies have some limitations. In this study, a country was designated as having an available policy if the policy has been present in the country for at least a year before the collection of GSHS data. It is important to note that availability of policy in a country does not

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necessarily mean that it has been implemented and reaching the target audience as such there should be caution with the interpretation of the study results. Also, only policies from 2004 to 2013 were reviewed. Thus, some countries might now have policies but were classified as not having policies in this study. Also, we cannot speculate as to what aspects of specific policies have an impact on adolescents meeting or not meeting the WHO recommendations as we relied on a secondary data source. This was a cross-sectional study, so we did not prospectively follow the adolescents' trajectory from the implementation of the policies to their specific health behaviors. We conclude that adolescents' physical environment, social environment, and physical activity behavior are significant predictors of daily intake of FV. Acknowledgments The authors are grateful to the Government Ministries (Ministry of Health, Ministry of Agriculture, and Ministry of Education) and the World Health Organization, for making the policy documents publicly available. They are also grateful to the World Health Organization and the Centers for Disease Control and Prevention for making the GSHS data publicly available. They also thank the country coordinators and the students who participated in the GSHS data collection. Funding Sources This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. References [1] Joint Food and Agriculture Organization/World Health Organization. Workshop on FVs for health. Report of a Joint FAO/WHO Workshop, 1-3 September 2004, doi:10.1016/j.icrp.2009.12.007. [2] Velde SJ, Twisk JWR, Brug J. Tracking of FV consumption from adolescence into adulthood and its longitudinal association with overweight. Br J Nutr 2007;98:431e8. [3] Aune D, Giovannucci E, Boffetta P. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose- response meta-analysis of prospective studies. Int J Epidemiol 2017;46:1029e56. [4] Miller V, Mente A, Dehghan M, et al. Fruit, vegetable, and legume intake, and cardiovascular disease and deaths in 18 countries (PURE): A prospective cohort study. Lancet 2017;390:2037e49. [5] Wang X, Ouyang Y, Liu J, et al. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: Systematic review and dose-response meta-analysis of prospective cohort studies. BMJ 2014;4490:1e14. [6] Rasmussen M, Krølner R, Klepp K-I, et al. Determinants of FV consumption among children and adolescents: A review of the literature. Part I: Quantitative studies. Int J Behav Nutr Phys Act 2006;3:22. [7] Pearson N, Biddle SJH, Gorely T. Family correlates of FV consumption in children and adolescents: A systematic review. Public Health Nutr 2008; 12:267e83. [8] Nicklas TA, Baranowski T, Baranowski JC, et al. Family and child-care provider influences on preschool children's fruit, juice, and vegetable consumption. Nutr Rev 2001;59:224e35. [9] Kremers SPJ, Brug J, de Vries H, Engels RC. Parenting style and adolescent fruit consumption. Appetite 2003;41:43e50. [10] Noia DJ, Byrd-Bredbenner C. Determinants of fruit and vegetable intake in low-income children and adolescents. Nutr Rev 2014;72:575e90. [11] Larson N, Laska MN, Story M, Neumark-Sztainer D. Predictors of fruit and vegetable intake in young adulthood. J Acad Nutr Diet 2012;112:1216e22. [12] Micha R, Karageorgou D, Bakogianni I, et al. Effectiveness of school food environment policies on children's dietary behaviors: A systematic review and meta-analysis. PLoS One 2018;13:1e27. [13] Klepp K, Pérez-Rodrigo C, De Bourdeaudhuij I, et al. Promoting fruit and vegetable consumption among European school children: Rationale, conceptualization and design of the pro children project. Ann Nutr Metab 2005;49:212e20.

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